THE$S ‘

 

mullIlilu’flllll‘flllljlfllllIll “

31293 017

 

LIBRARY
Mlchigan State
University

 

 

 

This is to certify that the

dissertation entitled

A Systems Method for Evaluating The
Sustainability of Ag-Production:

An Evaluation of Banana Production
In Costa Rica.

presented by

Carlos E. Hernandez

has been accepted towards fulfillment
of the requirements for

Doctoral degree in Resource Development

 
   
 

Major professor

Date October 8 , 1997

MSUL! an Affirmative Action/Equal Opportunity Institution 0-12771

 

PLACE IN RETURN Box to remove this checkout from your record.
TO AVOID FINE return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

'. UL 2 9 2005

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1“ WM“

 

AN EV}

 

A SYSTEMS METHOD FOR EVALUATING
THE SUSTAINABILITY OF AG-PRODUCTION:
AN EVALUATION OF BANANA PRODUCTION IN COSTA RICA

BY

Carlos E. Hernandez

A DISSERTATION

Submitted to Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Resource DeveIOpment

1997

AN Ev

 

Th5 Z

r
"“~Iav~:e
”IV I
"and

U )vuvd's'n Ir

llnnq

.c a .3 pt:
51:33 crop

.PA‘. fl

' J'thlon‘

I’ve s}.
an. . a... {e :

flu...

33: 393:9 r
339’“ t.

“' 'a._{e I

h
5n.»
”“56 hat

N-
3”:th I

C u

 

ABSTRACT

A SYSTEMS METHOD FOR EVALUATING
THE SUSTAINABILITY OF AG-PRODUCTION:
AN EVALUATION OF BANANA PRODUCTION IN COSTA RICA

By

Carlos E. Hernandez

This dissertation proposes a method for evaluating the sustainable
performance of agricultural production practices. It uses Costa Rica’s banana
production industry as a case to test the method. It presents an overview of
banana production in Costa Rica based on the importance of bananas as an
export crop and the environmental and social impacts associated with their

production.

The paper takes a systems approach to define the banana production
system and explicates it with a model. Cause and effect relationships are
identified. The intensities of these relationships are derived using hard data

when available, and expert opinion when no data exists.

A panel of experts rates the conventional production practices and the
alternative production practices. A mathematical method is structured to
aggregate ratings into sustainable performance indices. Best available
alternative practices are recommended, based on the resulting indices. It is
hoped that these recommendations will help bring about a more balanced

approach to the exploitation of Costa Rica's natural and human resources.

DEDICATED

To Amalia, Gabriela and Jaime for their support and love.

To Dr. Gordon and Norma Guyer for taking us in their home.

' N H” iflc'
“.I-*"
0‘”.

31”,.-

I. A.
l 7:“ ii
‘I‘ *5 B"
W 'v- P _
LA IR} IF;
S'W-Hv at

A n...
.Iu M3...

3513.135

C't-vess :

' Ml Gra:
58'9“:

IV'“‘

as “l6 ma
' Dr 35¢“
Iliange
. MI €933“

anCSUCC;

 

ACKNOWLEDGMENTS

This document would not have been possible without the support of the

following institutions and persons:

0 The W. K. Kellogg Foundation’s International Student Fellowship Program,
which provided financial assistance and logistical support. Special credit
should be given to Dr. Norman Brown who always offered encouragement
and wisdom and to Dr. Rick Foster for his friendship and active participation
as my academic adviser within the Foundation.

. EARTH College, which awarded the leave of absence to complete the course
work, granted licenses to complete the research, and contributed with
resources to prepare this document. Individual recognition is warranted for
Dr. Jose A. Zaglul and Dr. James B. French for their support, understanding,
and patience. Special acknowledgment needs to be given to my colleagues
and friends in the faculty and staff of EARTH College, who provided
encouragement, professional advice, editing, and clerical support in the
process of writing this document.

. My Graduate Committee who offered very useful advice and guidance,
especially Dr. Cynthia Fridgen who granted tutelage and invaluable counsel
as the major professor and leadership as chair of my guidance committee.

0 Dr. Scott Vlfitter who co-authored with me the articles that created the
foundations for this dissertation, and provided invaluable advice and
guidance.

0 My fellow students who provided most needed companionship, understanding
and support.

 

usroma
l

USTOF FIG;

SHAKER 1

:‘l’iOD CTTC

N
a N
C
1
.v

<
v (D

- N
O
(D ‘ '—
(n
r O
(l

'U

Ix)

#8
(I)
m

T
D

r

25 a
26 has.

_——1 rs) N N N N (
(J) (7) (1) (7) (1) :7;
. . , . ‘,_J n'

-_,7
(D
3 2-) (n A (a (\J

N
\1
O
(7
3‘)
(

 

TABLE OF CONTENTS

LIST OF TABLES ..................................................................................................... VIII
LIST OF FIGURES ...................................................................................................... x
CHAPTER 1
INTRODUCTION ........................................................................................................... 1
1.1 Topic of the Dissertation ................................. ‘ ........................................ 1
1.2 Philosophical and Theoretical Framework .............................................. 2
1.3 Objective ................................................................................................ 8
1.4 Definitions .............................................................................................. 9
1.4.1 Systems Approach ...................................................................... 9
1.4.2 Sustainability and Sustainable Development ............................ 16
1.4.3 Agroecology .............................................................................. 28
1.4.4 Ecological Engineering .............................................................. 31
1.4.5 Monitoring Sustainability ........................................................... 33
1.5 The researchable questions, problem and search for solutions ........... 43
1.6 Statement of hypothesis ....................................................................... 46
1.7 Justification and relevance ................................................................... 47
1.8 Conditions outside the control of the producers that have a bearing on
change ................................................................................................. 53
1.9 Conclusion ........................................................................................... 55
CHAPTER 2
PROBLEM FOCUSED LITERATURE REVIEW .......................................................... 57
2.1 Introduction .......................................................................................... 57
2.2 Systems Approach ............................................................................... 59
2.3 Costa Rica ............................................................................................ 61
2.4 Banana Production in Costa Rica ........................................................ 63
2.5 Systems Analysis of Banana Production .............................................. 66
2.6 Wastes and Alternatives ....................................................................... 76
2.6.1 Nonpoint Source Residuals ....................................................... 76
2.6.2 Point Source Degradable Wastes ............................................. 85
2.6.3 Point Source Liquid Waste ........................................................ 86
2.6.4 Point Source Nondegradable Waste ......................................... 88
2.6.5 Hazardous Waste - Agrochemical Containers ........................... 91
2.7 The Challenge ...................................................................................... 93
Conclusion ........................................................................................... 94

CHAPTER 3

WIRES
lzn'uw -~--

4 ‘9’?“ "

1 I .-
. .. I
32 P::-,
".4
34
5"”
.344
an
3.1.:
ha.
:44
33 Part:
14 [pcbol

(A, (A, 'U (A, (A, (p) -

A
:5 '325
‘ l
V,
n h
vLI
In
:n 821'
Lffiro.
l-l. ,;
Cc: I

cum 4
tsuusm

4.1 lr‘w'
. '—

 

42 Pa'e
43 Co".
4.4 A35.
45 Cr
‘5 Fit-352'E
4.7 Rag
4.8 Def-

(1)

4.10 H-,.:

In

WINGS. C:

5-1 Int." I
5.2 p;

 

K ' : '
“’3 RE‘QJI
‘ “ -.

v4 I13.

I

v4“

 

n

I
5.4;

 

CHAPTER 3

 

METHODS .................................................................................................................. 97
3.1 Introduction .......................................................................................... 97
3.2 Problem Setting .................................................................................. 105

3.2.1 Restatement of the Problem .................................................... 105
3.2.2 Research Questions ................................................................ 106
3.2.3 Assumptions ............................................................................ 107
3.2.4 Tasks ....................................................................................... 108
3.3 Participants ........................................................................................ 110
3.4 Instrumentation and Measures ........................................................... 113
3.4.1 Analytic Hierarchy Process and ECPro ................................... 113
3.4.2 Scales and Calculations .......................................................... 120
3.4.3 Consistency, Reliability and Validity ........................................ 123
3.5 Procedures ......................................................................................... 125
3.5.1 Data Collection and Calculations ............................................. 125
3.5.2 Research Method Flow Chart .................................................. 128
3.6 Statistical analysis .............................................................................. 130
Limitations and Delimitations ............................................................. 134
Concluding Remarks .......................................................................... 134

CHAPTER 4

RESULTS - - - - - ......................................................................................... 135
4.1 Introduction ........................................................................................ 135
4.2 Panel of Experts ................................................................................. 137
4.3 Conventional Production Practices .................................................... 141
4.4 Alternative Production Practices ........................................................ 143
4.5 Criterion Variables .............................................................................. 145
4.6 Relative Weights (Intensities) ............................................................. 149
4.7 Ratings ............................................................................................... 157
4.8 Definition of BAP ................................................................................ 162
4.9 Sustainable Performance lndices (SPl) .............................................. 173
4.10 Hypothesis Testing ............................................................................. 174

CHAPTER V

FINDINGS, CONCLUSIONS AND RECOMMENDATIONS ...................................... 184
5.1 Introduction ........................................................................................ 184
5.2 Problem Statement ............................................................................ 184
5.3 Researchable Questions .................................................................... 187
5.4 Findings and Conclusions .................................................................. 188

5.4.1 What are the important criteria that must be met in order to
perform in a sustainable manner? ........................................... 188

5.4.2 What are the conventional banana production practices (CPP) in
Costa Rica? ............................................................................. 189

vi

(h
35
(;)

(I!
.5
f H

(n
.t;
(T)

:45

' AAIA
0-.-
vii.

5
.5 Ce":

:
U.
c
v

N‘ r-a'
AVPe-qu
k‘3nafi} .

.PV- u

BIZDQ’a:

 

 

 

5.4.3
5.4.4

5.4.5.
5.4.6.

Are the OFF performing in an environmentally, socially and
economically acceptable manner? .......................................... 190
Are there best available practices (BAP) that have a better
environmental, social and/or economical sustainable
performance? .......................................................................... 191
Should banana production for the export market be abandoned?
................................................................................................ 1 92
What areas should be further researched and developed to
improve sustainable performance? ......................................... 193

4.5.7 Is it necessary to significantly change the market component of
the system in order to improve the sustainable performance of
banana production for the export market? ............................... 195
5.4.8 Was the analytical method proposed appropriate to answer the
previous questions? ................................................................ 196
5.5 Recommendations ............................................................................. 199
5.6 Concluding Remarks .......................................................................... 201
Appendix A ................................................................................... 206
Appendix B ................................................................................... 233
Bibliography ................................................................................. 273

vii

LIST OF TABLES

Table 1 - Inputs vs. residuals for the plantation in a banana production system72

Table 2 - Inputs vs. residuals for the packing plant in a banana production system

.......................................................................................................... 73

Table 3 - lndices and information needed to calculate waste generation in
banana production ............................................................................ 74
Table 4 - Waste Generated in Banana Production ........................................... 75
Table 5 - Panel of Experts .............................................................................. 102
Table 6 - Aggregated Two-way Classification ................................................. 105
Table 7 - Scale of Relative Importance (Saaty, 1996. P. 54) .......................... 121
Table 8 - Environmental Sustainable Performance Indicator Scale ................ 122
Table 9 - Social Sustainable Performance Indicator Scale ............................. 122
Table 10 - Economic Sustainable Performance Indicator Scale ..................... 123
Table 11 - Two-way Classification Experimental Design ............................... 132
Table 12 - Procedure for ANOVA ................................................................... 132
Table 13 - Procedure for Testing a Planned Orthogonal Comparison ............ 133
Table 14 - Panel of Experts ............................................................................ 139

Table 15 - Rejected Alternative Production Practices Based on Low ENPI 164
Table 16 - Rejected Alternative Production Practices Based on Low SOPI164
Table 17 - Rejected Alternative Production Practices Based on Low ECPI 165
Table 18 - Rejected Alternative Production Practices Based on Low ISPI ...... 165

Table 19 - Rejected Activities that Merit Review. ............................................ 166
Table 20 - APP Rejected Because of Unavailability. ...................................... 167
Table 21 - CPP with Unacceptable Levels of Performance ............................ 169

viii

Table 22 - Best Available Production Practices ...................................... 170

Table 23 - Best Available Labor Management Practices ......................... 172
Table 24 - CPP with Unacceptable Level of Performance ........................ 173
Table 25 - Experimental Design Matrix ................................................. 176
Table 26 - Descriptive Statistics of the Two Samples .............................. 177
Table 27 - Results from the ANOVA Using MINITAB .............................. 177
Table 28 - Results of Comparison of SPlcpp with SPI bap ....................... 180

Table 29 - Results of Comparison of SPlcpp to 0.600 Using MICROSTAT.. 180
Table 30 - Results of Comparison of SPlbap to 0.600 Using MICROSTAT.. 180

Table 31 - Tabulation of SPI by Segment of PE ..................................... 181
Table 32 - Descriptive Statistics of the Two Segments ............................ 182
Table 33 - Results of Comparison of SPlbap to 0.600 Using MICROSTAT.. 182
Table 34 - Agreement to Participate .................................................... 233
Table 35 - Independent Variables ....................................................... 235
Table 36 - Environmental Effect Intensities (weights) Assigned by PE ........ 260
Table 37 - Social Effects Intensities (weights) Assigned by PE ................. 263
Table 38 - Mean Value Substituted in Equation to Calculate SPI ............... 266

LIST OF FIGURES

Figure 1 - Resource Versus Consumption ............................................ 22
Figure 2 - Odum’s Parachute Theory ................................................. 32
Figure 3 - Axinn’s Theory .................................................................. 24
Figure 4 - Map of Costa Rica: Banana Growing Region & EARTH College. 62
Figure 5 - PainIvise Comparison Matrix ................................................ 117
Figure 6 - Methods Flow Cart ............................................................ 129
Figure 7 - Foundation Structure for the Environmental Component ........... 152
Figure 8 - Foundation Structure for the Social Component ....................... 153
Figure 9 - Foundation Structure for the Economic Component .................. 154
Figure 10 - Superstructure for Production Systems ................................ 155
Figure 11 - Individual 95% Confidence Intervals for Mean Values ............. 178
Figure 12 - Individual 95% Confidence Intervals for Mean Values ............. 182
Figure 13 - Macro Level Banana Production Model ................................ 206
Figure 14 - Micro Level Banana Production Model ................................. 207
Figure 15 - Mega Elements of a Sustainability Performance Index ............ 208
Figure 16 - Micro Criteria for an Environmental Performance Index ........... 209
Figure 17 - Micro Criteria for an Environmental Performance Index ........... 210
Figure 18 - Micro Criteria for an ENPI (Conservation of Biodiversity) ......... 211
Figure 19 - Micro Criteria for an ENPI (Pollution Prevention) .................... 212

Figure 20 - Micro Criteria for an ENPI (Rational Consumption of Inputs)..... 213
Figure 21 - Micro Subocriteria for ENPI (Integrated Residual Management) 214
Figure 22 - Micro Sub-criteria for ENPI (Residual Generation) .................. 215

M l
-
'I'V ‘-

" . M" It. 3':

‘ .Ilar

[Are

-II}:':

I - Its":

' LV‘IIC':

 

 

Figure 23 - Macro Criteria for a Social Performance Index ...................... 216

Figure 24 - Micro Criteria for a SOPI (Health Hazard Prevention) .............. 217
Figure 25 - Micro Sub-criteria for a SOPI (Prevention Measures) ............. 218
Figure 26 - Micro Sub-criteria for a SOPI (Prevention Measures) .............. 219
Figure 27 - Micro Sub-criteria for a SOPI (Services) ............................... 220
Figure 28 - Micro Sub-criteria for a SOPI (Education) ............................. 221
Figure 29 - Micro Criteria for a SOPI (Job Security) ................................ 222
Figure 30 - Micro Criteria for a SOPI (Capacity Enhancement) ................. 223
Figure 31 - Micro Criteria for a SOPI (Benefits to Local Communities) ........ 224
Figure 32 - Micro Sub-criteria for a SOPI (Stress on Community’s Health). 225
Figure 33 - Micro Criteria for a SOPI (Benefits to National Community) ...... 226
Figure 34 - Micro Criteria for an Economic Performance Index ................. 227
Figure 35 - Micro Sub-criteria for ECPI (Fringe Benefits) ......................... 228
Figure 36 - Micro Criteria for an ECPI (Cost of Resources - Inputs) ........... 229
Figure 37 - Environmental Component of Banana Production Systems ...... 230
Figure 38 - Social Component of Banana Production Systems ................. 231

Figure 39 - Economic Component of Banana Production Systems ............ 232

xi

ASysterr

git-5:9.

W33"

.‘Irvv-

UPI"

than :

This

V'P

thCQfin ,
II

 

Dissertation

A Systems Method for Evaluating the Sustainability of Ag-production:
An Evaluation of Banana Production in Costa Rica

Carlos E. Heméndez
Chapter 1

INTRODUCTION

"... we need not merely a vision, but a shared vision, one that
guides and unites us in our day-to-day decision making. Such a
vision, a common blueprint, can infuse society with a sense of
purpose as we try to build a new wortd, one much more attractive
- than today's (Lester Brown, 1993, p. 19). "

1.1 Topic of the Dissertation

This dissertation presents a systematic method for evaluating the
sustainability of agricultural production systems. It advances a normative
philosophy (blueprint) to define sustainable production. It assumes that a
systems approach is a suitable and acceptable method that can guide the
analysis and support the hypothesis. It establishes a Sustainable Performance
Indicator (SPI) to assess the conventional and the best available practices for
crop production. The problem is framed using a holistic approach that integrates

multiple issues and disciplines within a resource-development framework.

The author explores and assesSes the conventional agricultural

technology used in the present to produce bananas in Costa Rica. Since there

in ma-‘ '
.3 ~-== ll‘

Weave

I"
5 .

(t)

'Eira’;
32262232361
5:225 in a
C'xxtzan '.

it"s-rim .
“'Uvmy. ‘

 

 

 

The
Seaaf‘a p13,
Its-r. 3,309.
amnion

30" ,,,
“s“gsESI

 

are many kinds and qualities of bananas and many target markets, it is essential
to specify the fruit type that is considered in this research. The label "world-class
bananas" implies that the fruit meets the quality, service and price standards
required by the United States and European markets. It also means that the fruit
competes in the open market without the enjoyment of any trade privileges from
the receiving country. If the fruit qualifies as world-class, it has a general market
acceptance throughout the global free and open market. To achieve world-class
status in a very competitive market, the producer must use leading-edge
production technology that delivers a standard that is difficult for other

competitors to match at a profit making cost (Johannson, 1996).

The object of this exploration is to study state-of-the-art world-class
banana plantations in Costa Rica. The leading-edge technologies that have
been adopted by progressive producers will be evaluated to determine their
contribution towards sustainable development. The results will serve to identify

and suggest a path for further improvement.

1.2 Philosophical and Theoretical Framework

This section outlines the author's journey in search of a vision, a blueprint
that defines the philosophical and theoretical framework upon which sustainable
development can be built and connected to the practice of food production. This
emerging paradigm begins by exploring today's scenario, then identifies current
models of development, and finishes with a working definition of sustainable

agricultural production.

The
e':7aSZBS
93:77:72: r."

mes {Ca}

 

12:43! res:

.A'M. A" “O'h
a U£D-'I n J

NEIE'
37: YOLI‘Q

(2‘53 Vv- s
Urn-.3 a L. a~ .-

.

Cn .:
SUCCE-
future
- air,
Subs;
Car‘w

lid
0

due.

 

Mac:

.309.
aijL
IS WI]
IVDCQ

3

The twentieth century industrial growth and development paradigm
emphasizes economic gains over ecosystem integrity. It is based on reductionist
economic models which inadequately recognize ecosystem integrity, ethics and
values (Daly and Cobb, 1989). Human wants and needs have prevailed, and
natural resources have been regarded as inexhaustible. Furthermore, the

allocation of benefits has not always been equitable and just.

Never before has there been more concern for the effects of human
activities on the earth's land, water, atmospheric, and biotic resources. Flavin
and Young (1993, p. 180) eloquently capture the essence of this interest by

stating that -—

"On its own terms, the modem industrial system is extraordinarily
successful... But much of the affluence has been borrowed from
future generations. Destruction and degradation of natural assets -
- air, land, water, forests, plants and animals species - have
subsidized the profits of many businesses in the late twentieth
century. For industries around the wortd, the debts are coming
due. "

In a complementary statement, Brown (1993, pp. 18-20) states that -

”T he existing economic system is slowly beginning to selfidestnrct
as it undermines its environmental support systems. The question
is whether we will initiate the changes in time and manage the
process or whether the forces of deterioration and decline will
prevail, acquiring a momentum of their own... The question is not
only what do we need to do, but how can we do it quickly - before
time runs out and the entire world is caught in the downward
spiral...(Brown, 1993, p 20). "

The Brundtland Commission served notice to the world community that

the trend of economic growth threatened the future of humanity. It clearly

recognized the cause of the problem and stated that:

4

"T he Earth is one but the world is not. We all depend on one
biosphere for sustaining our lives. Yet each community, each
country, strives for survival and prosperity with little regard for its
impact on others. Some consume the Earth's resources at a rate
that would leave little for future generations. Others, many more in
number, consume far too little and live with the prospects of
hunger, squalor, disease, and eariy death. (Quoted by
Wackemagel, Onisto and Mata. 1995 p. 26) "

The Earth Summit in Rio (1992) serves as testimony that the world
community has concurred. Agenda 21 promotes a strategy for change and the

Earth Council supports and aids in the needed transition toward a new paradigm

of development. However, little has been achieved beyond rhetoric.

"The Earth '3 population grows daily, poverty spreads, non-
renewable resources are further depleted, more waste is dumped in
oceans and the atmosphere, the ozone hole continues to grow and
CO 2 levels continue to climb. Humanity's impact, or ecological

footprint, grows while the global ecosystem 's productivity, on which
we depend for survival, continues to decline (Wackemagel, Onisto
and Mata, 1995. p. 1)."

Going beyond discourse implies making hard choices that are not
politically palatable among the empowered minority who feel their status quo

threatened. How can it be popular to them if

"the richest fifth of humanity earns over 60 times more than the
poorest fifth (Wackemagel, Onisto and Mata, 1995. p. 2) "

and where

"3/4 of current consumption goes to 1 . 1 billion people who live in
afiluence, while 1/4 of the consumption remains for the other 4. 7
billion people (Wackemagel, Onisto and Mata, 1 995. p. 2) "?

Is it not obvious who has to make the sacrifice?

The when, what and how of necessary change is not generally shared.

On one side, the paradigm espoused by "Deep Ecology" appeals for urgent

. r _
,fia ’0 1" .—
1?“: 'a d"

A “(P He'e IS

Dir-f

P I-I
_AA.I‘A~
.VV V

"9‘; less

"GPNI 3‘ A;
v

‘3: v,

In be

£3':“l~h ‘5-
'3 '*

5'“:~' I
U :u;3n 6

T'fifi! Q “
'1‘ 3'9 tr E
F 6,

ans 326d 8-

'31-‘38 I339 ”I

vaches 8

 

:Mg'i
Walgred :.
0..
“who Uv.
. V"
n
vr’ In” I
I [ev‘
'3’:
b d 1‘
“a“ re
n ,
,af

 

5

constraint of economic growth and a negative human population growth rate;
restraint in human activity in favor of ecosystem preservation; and recognition of
innate values and equity among species (Colby, 1990). Many insist that the
biosphere is already beyond its limits, and predict eminent crisis (Meadows,
Meadowsand Randers, 1992). On the other extreme, the disciples of "Frontier
Economics" (neo-economists) place their faith in technological solutions,
productivity, individuality and self-interest, and values based on market prices.
They insist on the necessity of infinite economic growth. They question the

urgency of change based on the failure of previous predictions of doom.

In between these extremes, many natural and social scientists are
searching for a way of working together to advance sustainability, environmental
protection, eco-management, and eco—development. This group seeks to
promote the concept that agriculture is a complex system that cannot be
abstracted as an industry divorced from nature; to confront the reality that natural
resources are limited; to favor long-term over short-term planning; to recognize
values that go beyond market price as elements to be considered in an economic
analysis; to endorse the search for advanced appropriate technologies; and to
encourage grassroots movements to empower people and generate the
controlled effervescence of gradual change (Colby, 1990; Soldrzano, del
Camino, Woodward, Tosi, Watson, Vésquez, Villalobos, Jimenez, Repeto and
Cruz, 1991; Beus and Dunlop, 1990; Altieri, 1987). The followers of this
paradigm recognize the importance of meeting human needs and integrating

natural and social process to redefine values. They concede that if humans do

6

not perceive and assign proper significance to natural resources, eventually
these resources will be depleted, degraded, destroyed, or exchanged for

alternative resources of superior monetary value.

Nowhere is the need for change better manifested than in the industrial
agriculture of today. The success of the "Green Revolution" is attributed to the
industrialization of agriculture. Under this system, high agriculture yields depend
largely on inputs of fossil fuel energy rather than efficient conversion of solar
energy through photosynthesis. If synthetic inputs are removed, yields fall
because soils are exhausted (Hall, 1990). Industrial agricultural models can be
maintained as long as the price of fossil fuel remains low. The present market
price is not a true reflection of the scarcity of fossil fuels. There is a strong
possibility that in less than 30 years, petroleum reserves will be concentrated in
only four nations, which can then dictate price to the rest of the world. If this
happens, societies that rely exclusively on industrialization models will face

catastrophe (Hall, 1990).

Harwood (Committee on Sustainable Agriculture and the Environment in
the Humid Tropics - CSA, 1993. p. vii), suggests that a new attitude of
stewardship and sustainable management is required if our global resources are

to be conserved and at the same time remain productive. He states that,

"thoughtful and prompt actions, especially positive policy changes,
are required... to reverse environmental degradation caused by
improper or mismanaged crop and animal production systems... "

ills-2

’ . _
I‘ll-AQ. 'F‘;
"v v In“,

i

gave.

The 3

“g..

‘ as.

.S. _‘.,
f0! 5
no: :
0&9:
{USE
99's:
”7:3 '
the

Ma;

 

7

However, it is one thing to prescribe change while it is an entirely different

thing to implement change.

"Decisions conceming the management of natural resources will
always be made in the political arena... In the past, many such
decisions have been made without adequate information about the
consequences of the actions as they relate to near-tenn and long-
terrn availability and quality of natural resources and vital ecological
processes. Frequently these decisions have resulted in the loss of
resources or in the need for expensive recovery actions. Thus, the
challenge is to provide the best possible information so that
decisions can be based on the most accurate predictions of any
action (Risser, Lubchenco, Christensen, Dillon, Jacob, Johnson,
Matson, Moran and Rosswall, 1993, p. 5). "

It is especially important to recognize that political issues are affected by
specific interest groups and are not always representative of the greatest public
good.

The Earth Monitoring and Reporting Program of the Earth Council states
that:

"Sufficient information is available to make the necessary decisions
for a sustainable future; but it is also clear that these decisions are
not being made. This lack of government action underscores the
need for encouraging people 's involvement. In fact, hope for the
future depends on people taking up sustainability as their own
personal cause. The challenge is to change the way people live in
this world by changing the way they see the worid, and changing
the way people see it by changing the way we live in it
(Wackemagel, Onisto and Mata, 1995. p. 2)."

This necessarily involves empowering people

"in building a more secure, equitable and sustainable future, in a
spirit of solidarity and common responsibility (Wackemagel, Onisto
and Mata, 1995. p. 2)."

Therefore, a substantial challenge is to seek, collect and provide sound
information to the policy makers and their constituencies organized in a way that
can be easily understood and translated into appropriate values.

 

halal an;

 

M.
l .-’

‘~ 333’":
My

. .
”735’513r1~

a, I .
a=r5uiima
lh o
\-

 

1 .3 Objective

This dissertation accepts the challenge of conceptualizing a systematic
method of seeking, cOIIecting and providing sound information in order to
evaluate the sustainable performance of Ag-production. It tests this method

rating the performance of world class banana production in Costa Rica.

Most research has concentrated on the task of going beyond the

Brundtland Commission's (1987) definition of sustainable development

("meet the needs of the present without compromising the ability of
future generations to meet their own needs ")

and have continuously worked to produce and refine sustainability
indicators that measure the present condition and the effects of change
(Wackemagel, Onisto and Mata, 1995). This dissertation goes beyond numerical
indicators, and begins by proposing a conceptual model in an effort to connect
natural and social processes, and search for solutions that take into account the
interactions of social, economic and biophysical components. It seeks
understanding of the effects of human attempts to control nature by managing

agricultural ecosystems.

The immediate task of this chapter is to develop a normative philosophy
that can guide sustainable banana production. It acknowledges that sustainable
agricultural production can contribute to the sustainability of humanity, but that it
is only one element of a complex solution. Furthermore, it should not lead to the

false expectation that change will be universally embraced and fully implemented

we 153'

males 3 a

 

1.4 Deli:

1.4.1 Sys‘.

'
Flog l
‘. P" .
.VF Vayheh
Sq'a. l

V "‘IJHIS Q;

.3 in...

w “Han :
V‘h‘
J'gense’

 

 

9

in the near future. Implementation involves alteration in cultural habits, which

makes it a Iong-tenn project.

1.4 Definitions

1 .4.1 Systems Approach

H. T. Odum (In Mitsch and Jorgensen, 1989, p. 101) advises that

"as the resources of the worid become increasingly limiting to the
expansion of the human economy, the management of the planet
must tum more and more to a cooperative role with the planetary
life support systems, sometimes called stewardship of nature. "

The problems of development are becoming more complex and less
solvable by conventional technological means. In the past, society has relied on
technical solutions that solve one type of problem only to find that they have
created another type (Mitsch, 1993). The narrowness of conventional
approaches to analysis and problem solving is the culprit in such mistakes.
Solutions to human problems are better solved by finding symbiotic relationships
of human and natural mutually reinforcing systems (Odum, H. T. ln Mitsch and
Jorgensen, 1989). Analysis and problem solving approaches must evolve to

meet the challenge of new complexities.

"Science is a process, a method of studying reality in order to gain
knowledge (Feet, 1992, p 19) ".

The scientific method is the conventionaly accepted procedure of
observation and careful experimentation to obtain facts. Normally it uses a
reductionist approach that consists of breaking down the elements of a problem,

isolating each element from the rest, and studying each separately.

 

A s,

 

 

whole.

10

"Taken to excess, reductionism encourages concentration on detail
to the exclusion of the whole and can be seriously misleading
(Peet, 1992, p. 21)."

Reductionism incorrectly assumes that the sum of the parts equals the

A systems approach is a tool that facilitates holistic analysis of a complex

system by characterizing its nature in such a way that the decision making can

take place in a logical and coherent fashion. It is a

“way of thinking about the set of interconnected parts that makes
up the whole in such a way as to bring out the properties of the
whole rather than those of the parts (Peet, 1992, p. 25)"

thus, minimizing the occurrence of the

"fallacies of narrow-minded thinking (Churchman, 1968, p. x). "

Systems are classified as isolated, open, or closed depending on how

they interact with their surroundings.

"An isolated system exchanges neither energy nor matter with its
environment (Peet, 1992, p 14). "

Isolated systems have not been identified on earth, not even in the

laboratory. A closed system exchanges only energy with its surrounding

environment.

"T he earth is a closed system, since only solar energy comes in
and only heat is rejected to outer space (Peet, 1992, p 14)." In
contrast, "an open system exchanges both energy and matter with
its environment. Thus, all living organisms, ecosystems, and
economies are open systems since they consume food, reject
wastes, and take heat from or give it to their environment (Peet,

1992, p 14)."

p.
H
V

In R‘Alrt
hta‘uvnv

 

ear-ere '

.IV.

twssaz

UVVv

.1
ifie n ”a"

U" My
522') an:

s

‘
LOC 1329 °

 

11

Therefore, sinks ("the utimate destination of material or energy flows
(Meadows, Meadows and Randers, 1992, p 278)"), transformation processes
and throughputs ("the flow of energy and materials needed to keep the economy
functioning (Meadows, Meadows and Randers, 1992, p. 279)"), are critical

elements in defining and understanding systems.

The first step in studying a system is to define the problem. Then it is
necessary to determine the appropriate spatial and temporal limits of the system.
The dimensions of the system are fundamental in measuring the potential of the
study and are set according to its objectives. If the system's boundaries are set
too large, the perceived and measurable signals may be too aggregated. On the
contrary, if the boundaries are set too small, the information may be too complex,

troublesome to synthesize, and thus, very difficult to interpret.

To analyze agricultural production systems, del Camino and Muller (1993)
recognize eight levels of spatial limits or scales of analysis: global, regional,
national, regions within a nation, local, farm, agronomic procedure, and
microscopic systems. They identify the farm level as the convenient level for
studies of sustainable agricultural production. This level facilitates the analysis in
detail and the identification of internal and external causes and effects, and
appropriate opportunities for actions. As recommended by del Camino and
Muller (1993), care is taken not to isolate the analysis and ignore interaction with
vertically (systems defined by larger and smaller scales) and horizontally
(different sub-systems at the same scale) overlapping chains of connections

among components and systems. Therefore, it is necessary to consider, in

‘1‘ lfi‘IA""
I” J ’U

C 36

Niel. Tr

5.3513338.
u.

rg'IEtafy LI

I? 3" hr
i0\

Ass

 

 

12

lesser detail, agricultural production in at least three additional levels or scales of
organization - global system, nation, and agronomic procedure. Furthermore, to
understand the implications of agronomic procedures, it is sometimes necessary

to understand the microscopic scale.

The next step is to break down the system into functions or components.
In essence, components are points of transformation or sinks of energy and
matter. They are interrelated by cause and effect, stimulus and response. In
substance, interrelations between components are evidenced by throughputs.
Monetary units are the conventional way that economists account for throughputs

in an economic system (Hall, Cleveland and Kaufman, 1992).

As stated before, agricultural production systems are cpen and pervious to
interactions from other systems. Inputs and outputs of a system under study are
recognized by the throughputs that necessarily cross the arbitrary boundaries set
between two horizontal or vertical sub-systems (Meadows, Meadows and
Randers, 1992). In this manner, production systems are intimately related to
other systems and are subject to effects from changes made in adjacent systems

(Peet, 1992).

From the human ecology perspective, Axinn (1988, pp. 10-12)

summarizes this process with the following statement:

”Wherever there are human beings, they carry out certain basic
functions... From a systems perspective these functions may be
viewed as components, linked with each other so that change in
any component affects the entire system. Any interaction with
outside systems will be reflected by change within the system...

 

In:

amast

 

13

There are various forces pushing in the direction of change, and
counterforces pushing in the direction of continuity. At any
particular point in time, things are as they are because the forces in
one direction balance the forces in other... no outside intervention
occurs in a vacuum. Change results from introduction of additional
forces in the change side, or from reduction of some forces on the
continuity side. "

In contrast to the holistic character of the systems approach, a reductionist
approach consists of breaking down the elements of a problem, isolating each
element from the rest, and studying each separately. In the end, the different
elements are assembled together assuming that the sum of the parts equals the
whole, and no adequate consideration is given to the synergism among
elements. Consequently, reductionism is not an appropriate approach for

studying open systems.

Using scientific knowledge and experience, the reaction of every action
can be traced through the system and behavior predicted. Based on this
prediction, indicators can be developed to measure the level of performance of
each component, adjustments can be made to improve performance, or
components and standards may be modified to fit reality. This process is called
modeling, and often is accompanied by an effort to assign mathematical formulas
to quantify stimulus and response. However, it is important to keep in mind that

a model is only a simplified representation of reality.

"It is our best attempt to symbolize our thoughts, but it is only a
model of those thoughts (Meadows, 1992, p. 105). "

[ma-31$.

IUUU'v-

F.”

 

Fly-

 

14

Appropriately, Daly and Cobb in their book - For the Common Good
(1989)- warn the reader of the dangers of placing too much credence on

models.
Finally, systems thinking is guided by the following principles:

1. A system must be analyzed through different viewing windows or frames.
Churchman states that -

'T he systems approach begins when first you see the world
through the eyes of another (1968, p. 231). "

2. Each window or frame has strengths and weaknesses, and no one frame
fully explains reality. Churchman's point of view is that -

'T he systems approach goes on to discovering that every wortd
view is terribly restricted (1968, p.231). "

3. There are no correct or incorrect views, just different ways of interpreting
information. Churchman's reaction is that -

"T here are no experts in the systems approach (1968, p 231). "

4. Analytical thinking is opportunistic. Churchman states that -

"When you postpone thinking about something too long, then it may
not be possible to think about it adequately at all (1968, p. 8). "

5. The challenge of systems thinking is to learn what everybody knows by re-
addressing what seems obvious. From this point of view, "The systems
approach is not a bad idea (Churchman, 1968, p. 232)."

The product of this research is a systematic analysis and the development
of a banana production model that assists stakeholders with identifying the
components and their interactions, and the inputs and the output at
predetermined scales. This facilitates the analysis of alternative technologies
and their effects on the system in a holistic manner and the evaluation of them as

to their effective contribution to sustainable development of agroindustry.

, e
‘ .39!“ R.
*v iii V

 

858'?" L

A. «Af's
6......

that I“c

Hts-h

'A'fl- .A. .-
-viiv\ -

t: 3: ba:

“"9 'l':
meaning;

meagre

m’C‘BTIIH-M
":11

 

15

This dissertation is the author’s attempt to assist the reader in seeing the
world of banana production through a case example and the author’s personal
experience in the banana industry. As such, it is restricted and skewed. It is the
author’s interpretation of the information available which leads to the conclusion
that little time remains before remediation of damages caused by unsustainable
production practices is no longer an option. Thus, this is the opportune moment
to go back to the basics and verify what seems obvious using a multidisciplinary
framework. It is necessary to see banana production through the eyes of
entomologists, soil and crop scientists, toxicologists, social scientists,
economists, ecologists, producers, banana workers, communities, wholesalers,
retailers, produce suppliers, consumers, and governments. Each view exposes
significant aspects, yet all are restricted and do not provide the entire illustration.
Each observer has a unique porthole that provides a section of the entire
panorama. At the same time, each spectator interprets the pictures in a different
manner, and forms a singular conception. Consequently, there are no right and
wrong impressions, and accordingly, there are no experts. Every one's notion is
meaningful, and the summation of views approximates the intact reality.
Therefore, the larger the number of vistas the greater the precision, and the more

meaningful the vision.

1.42 So

1.4.2.1

 

 

 

16

1.4.2 Sustainability and Sustainable Development
1.4.2.1 Introduction

Sustainability and sustainable development are terms often used but
seldom understood. Both are essential elements of the philosophical and
theoretical framework for this dissertation. Therefore, it is necessary to move
beyond stock definitions and analyze thoroughly the significance and implications
of their meanings. This section begins by proposing an overall simplified
definition, then expands to its significant components. Next, it integrates
innovative pertinent theories on how to achieve sustainable development, and
exposes three fundamental conditions for it to occur. Finally, it explores the key

elements of a definition for sustainable agricultural production.

1.4.2.2 Sustainability

According to Wackemagel, Onisto and Mata (1995),

"In essence, sustainability is a simple concept: living equitably
within our ecological means. "

The wording may be simple but a deep probe requires a complex

explanation. Because of complexity, it is essential to use a systems approach.

As stated in the previous section, sinks and throughputs are important
elements in defining and understanding systems. Furthermore, they constitute
the foundation for the definition of sustainability. The Laws of Thermodynamics

govern sinks and throughputs.

17

"T he First Law of Thermodynamics, the law of conservation of
energy, states: Energy can be neither created nor destroyed, only
converted from one form to another. When one energy form is
converted into others, the total resulting energy remains the same...
The accounts always balance; no exception has ever been
identified (Peet, 1992, p. 33). "

Therefore, the solar energy that penetrates our atmosphere must equal the total
energy captured, transformed and stored plus the energy dissipated as heat into
space. However, the capacity to do work with the transformed energy is not the
same as that of the original energy. This leads us to the Second Law of

Thermodynamics.

"T he Second Law of Thermodynamics - the entropy law - can be
stated as follows: All Physical processes proceed in such a way
that the availability of the energy...decreases (Peet, 1992, p. 36). "

This means that no transformation of energy is 100% efficient. In each
progressive transformation energy is degraded. The result is that each
transformation yields a new form of energy which is less available to do work.
The Second Law of Thermodynamics highlights the existence of finite limits for

earth and ecosystems.

Notwithstanding that natural processes conform to the laws of
thermodynamics, viewed from a global spatial and temporal scales, ecosystems
are self-organizing and self-sustaining and contribute to reduction of global

entropy. According to Easterbrook (1995, p. 661)

”the complexity hypothesis posits that a function of life is to defy the
second law of thermodynamics... Complexity theorists believe...
that in some manner not yet grasped, the universe came prewired
to favor complex systems over entropy. "

 

T7-

is” 3;" 3'1,

'0 A I'Ar-
V 'U V»-

"Lion A

1I‘EI,V V

F A...
59.4.56

 

18

This is accomplished through elaborate interactions of matter and energy

which are driven by an external source of energy - the sun (Peet, 1992).

"The conversion by plants of solar energy from outside the
biosphere to biomass (matter) within it is the only means by which
living systems, including humans, can circumvent the Second Law
of Thermodynamics and decrease biospheric entropy (van den
Berg and van der Straaten, 1994, p.50). "

Captured solar energy is transformed and stored as stock or flow
resources. The transformation of solar energy into stock resources requires
millions of years. Stock resources are referred to as nonrenewable resources
because they can not be replenished within temporal limits that are relevant to
human existence. In contrast, solar energy can be transformed and stored as
flow resources in a relatively short period of time. Flow resources are referred to

as renewable resources (Peet, 1992).

Through the process of photosynthesis, solar energy plus minerals
existing in the ecosystem are transformed into organic matter. As a byproduct,
high quality energy is transformed into waste products, and dissipated heat.
Other living organisms consume the energy stored in organic matter to transform
them into other types of organic matter and into waste, releasing heat in the
process. Through a complex cycle, decomposing organisms further transform
organic waste matter until it is mineralized with waste generation and heat loss at
each step of transformation. In this transformation process, energy is temporarily

stored in the form of renewable resources but eventually degrades and

dissipates.

 

,A‘ ~v-A'
Sullbta" ':

("D

"3

(‘)

s

(L I
‘q

 

19

Regardless of the increase in entropy of each transformation,
sustainability is theoretically possible because open and closed systems receive
energy (and, for open systems, matter) from their surroundings. These systems
can theoretically go on forever provided solar energy keeps coming in (Peet
1992, p. 42). Wackemagel, Onisto and Mata (1995) conclude that a system is
sustainable as long as the average rate of energy and matter consumed, in all

forms, equals their average replenishable rate.

Economics is the methodology used by humanity to manage the
distribution of land and resources. Technological breakthroughs have falsely
encouraged people to believe that there are no limits to this world (Peet, 1992).
Humanity has found ways to efficiently extract resources from nature.
Progressively, stored energy has been consumed without consideration of future
generations, and many flow resources are being consumed far beyond their
replenishable level (Meadows, Meadows and Randers, 1992). Furthermore,
humanity, through technology, discovered how to create synthetic materials,
some which are difficult to transform by natural processes into other forms and
some which are toxic, and has thus been able to bypass natural processes.
These anthropogenic activities have temporarily empowered humanity to survive
in hostile environments in population sizes beyond the system's sustainable
carrying capacity. The results are an increase in the rate of waste generation

beyond the assimilation rate (Meadows, Meadows and Randers 1992).

20

The prevailing neoclassic economic approach promotes accelerated
transformation of resources (production) and consumption. This economic

paradigm

"necessarily and unavoidably degrades the resources that sustain it

(Peet, 1992, p.37) ". "In strong contrast to economic systems,

ecosystems accumulate energy, matter, and order (Peet, 1992, p.

45)."

Thus, people should take a careful look at ecosystems, make an effort to
understand them, and manage them accordingly. Unless humanity reduces
consumption, improves process efficiency and recycling, and/or develops
technology to capture more solar energy before it is dissipated into space, the

ecosystem will increase entropy and the economic system will eventually run out

of available energy to do work.

In summary, an economic system that consumes resources at excessive
rates leads to depletion and scarcity of vital resources to sustain it. An economic
system that generates waste beyond the ecosystem's capacity to assimilate it,
degrades and eventually is not able to provide the basic resources needed to
sustain it. Finally, a system that does not check population growth rates,
exacerbates resource consumption and waste generation and leads to

unsustainable effects (van den Berg and van der Straaten, 1994).

1.3.2.3 Sustainable Development

Sustainable development implies growth, resulting in increased

consumption. Rachel Carson, Paul Ehrlich, Norman Myers, among others,

(,3

61‘5"!“ :-
and 3‘; ‘h
I

 

21

question Earth's ability to support further growth, casting doubt on the possibility
of achieving sustainable development (Easterbrook, 1996). The following

synopsis of theories will explain how sustainable development can take place.

George Jacobson (quoted by Easterbrook, 1996, p. 659) declares that

"T here is almost no circumstance in which something isn't changing
the natural system. The system may seek an equilibrium but it's
never allowed to get there. So we might as well not expect the
classical balance of nature to exist. "

H. T. Odum (personal communication, August 1995) elaborates by stating that
ecosystems are constantly in flux. They have the ability to redesign themselves
in accordance with the following parameters: a) the capacity to capture solar
energy and transform it into other forms, b) the capacity to store it temporarily,
and c) the consumption rate by living organisms in the system. As the availability
of stored resources increases, life is stimulated and the consumption rate
increases (See figure N°1). At a particular point in time, consumption is equal to
the replenishable rate. As consumption continues to climb, organisms start to
draw upon accumulated resources until all are consumed. At this point, the
ecosystem adjusts, populations decrease, and consumption falls drastically. This
process is repetitive at all levels (spatial and temporal limits) of ecological
hierarchy. Thus ecosystems are never truly stable but in constant flux and
adjustment. On a global spatial and geologic time scale, there are evidences of
several cycles, which involve high amplitude (magnitude of the adjustment) and
low frequency (time between adjustments). The smaller the limits of the system,

the smaller is the amplitude and the higher is the frequency.

22

 

 

 

 

 

 

 

CONSUMPTION

AVAILABLE

RESOURCES
a)
I“ DOWN-SIZING
° 1.
n:
D
O
U)
2.".

GROWTH
HISTORIC EVIDENCE PRESENT CYCLE
TIME —>

 

 

 

Figure 1 - Resource Versus Consumtion

Odum (personal communication, August 1995) believes that the present
economic system has reached its peak, that the ecosystem is beginning to

redesign itself, and the probability of drastic effect on humans are high.

Fortunately, humans have the rational capacity to control the fall by down-
- sizing in an orderly manner. Odum calls it the "parachute theorY' (personal
communication, 1995) By so doing, humans can manage the process to slow it
down and to control the magnitude of the adjustment. In theory, society can
choose a datum level of consumption that permits us. to flux at a higher frequency
with a low amplitude (See figure N° 2). This is equivalent to relative stability for

an indefinite time (sustainability).

 

RESOURCES

 

23

 

 

 

 

PRESENT

{3 AVAILABLE CONSUMPTION
o /
n:
a
8 SUSTAINABILITY
m
a:

V

TIME —->

 

 

 

Figure 2 - Odum’s Parachute Theory

Viewed from the social perspective, George Axinn (RD 876 class notes,
1993) proposes that the levels of economic development are cyclic and that at
any one time components of a system, at any scale, may be underdeveloped,
developed or overdeveloped (see figure N° 3). Components that are
overdeveloped have excessive demands that cannot be met by the support
systems and thus decline to the developed state, and momentum will cause them
to decline further until they are underdeveloped. Systems, which are
underdeveloped, have the capacity to grow to the developed state because their
consumption is below the support system's capacity and, once developed,

momentum carries them to over-development. The cycle repeats itself.

t .
Trecre. .

If“ he

Figure 3

(7992} as

and has

 

24
Theoretically, societies can control the magnitude and frequency of the cycle,
with the purpose of achieving a relative stability, by controlling negative and

positive growth.

 

 

OVERDEVELOPED

 

 

 

 

 

DEVELOPED DEVELOPED

 

 

 

 

 

 

 

 

 

UNDERDEVELOPED

 

 

 

 

Figure 3 - Axinn’s Theory

Both theories hold true as long as population growth is stabilized. Piel
(1992) asserts that as human well-being increases, population growth decreases

and has a tendency to stabilize. Human well-being is tied to human health

“which includes, not only the need for economic goods, but also
that for satisfactory social relationships and favorable natural
environment (Huss, 1994, p. 14). "

25

According to Langmore (1994, p. 55),

"development is about improving human well-being, increasing
choices, and strengthening economic security. It is a mistake to
aim simply for improvement in efficiency in the hope that in the long
run this will be associated with improvements in equity. Trickle
down policies have failed. "

Therefore, social equity means that those that have must promote

development for those that have not.1

Careful examination indicates that Axinn's theory is harmonious and
complementary to Odum's theory. The integration of both theories allows us to
conclude that ecologically and socially, through sustainable development
(simultaneous positive and negative growth), it is possible to achieve

sustainability.

The achievement of sustainable development requires understanding of
people's complex role in an ecosystem. Society has created an economic
system, which governs the exchange of goods and services among people. To
facilitate trade, values are artificially measured using money. In today's
consumer society, actions are motivated by the certainty that monetary benefits
will surpass costs. Change will not occur unless it is economically feasible and

attractive to those that have the power to change. As Magi O. Brian (personal

' If we apply Rawls's Theory of Justice in combination with Axinn's theory, all members of
society should be in agreement with this statement because at some point in time they
will be in a position to help and in another they will need help.

namm‘u’

U' .I‘eF

it 4

er

1

((3

Of: ”‘A

I Ic
'zl's. .
CAN-“,1 C

 

 

26

communication, visit to EARTH College 1995), President of the U. S. Fish and

Vlfildlife Foundation, says "If it pays, it stays".

However,

”the primary objective of any economic activity is the production
and distribution of goods and services for the benefit of humanity
(Georgescu-Rouegen, 1976 quoted by Huss, 1994, p. 16). "

From this point of view, economic development is an essential element of

sustainable development.

"On the other hand economic development, misunderstood as
mere growth, threatens the autonomous ability of the individual, the
community and the worid as a whole (Huss, 1994, p. 16) "

to promote human well-being.

In summary, sustainable development implies change from a strategy of
maximizing economic growth and production to minimizing present and future
human suffering. It means reducing ecological destruction by reducing the rate
of demand for renewable and non renewable resources. It means improving the
quality of life of the less empowered people by controlling the consumption of the
wealthy privileged class. However, unless change is economically feasible it

generally will not occur.

Based on the previous discussion and information gathered from the
' literature, the next section recognizes the fundamental elements of definitions for
sustainable agricultural production and posits a specific definition for this

dissertation (see p. 28).

1.42.4

(D

EYE CCI‘.“

 

 

 

(n

((1

27

1.4.2.4 Sustainable Agricultural Production

Sustainable Agricultural Production has several definitions. The following

are common concepts:

'Iong—temr maintenance of natural resources and agricultural
productivity; minimal adverse environmental impacts; adequate
economic returns to fanners; optimal production with purchased
inputs used only to supplement natural processes that are carefully
managed; satisfaction of human needs for food, nutrition, and
shelter; and provision for the social needs of health, welfare, and
social equity of farm families and communities. All definitions
embrace environmental, economic and social goals...(CSA, 1993,
p. 22). "

Based on del Camino and Muller (1993. p 29), sustainable agriculture is a
set of human interventions that effectively and rationally manage resources and
the agroecosystem to satisfy the changing necessities of people, while
maintaining or improving the resource base, avoiding environmental degradation,
and assuring in the long run a productive and equitable development. In
compliance with the previous concepts, sustainable agricultural production

systems must fulfill the following objectives:

a. Maintain or improve the natural resource base
b. Avoid environmental degradation

c. Maintain production and productivity

d. Minimize purchased inputs ‘

e. Distribute costs and benefits in an equitable manner

f. Respect the values and principles of the society

9. Satisfy present and future human needs for food, nutrition, health,

welfare, and shelter

28
h. Enhance the quality of life of the farmers and society as a whole.

For the purpose of this dissertation, sustainable production of world-class
bananas is defined as follows:

The sustainable production of world-class bananas is a broad
spectrum of agro-cultural practices 2 that includes the efficient
and rational use of natural resources and the agroecosystem.3
It seeks to ensure long-range production, productivity, and
profitability by maintaining and improving the resource base
and preventing environmental degradation. It distributes
costs and benefits fairly and equitably, and respects
community values and principles, all with the objective of
satisfying society's present and future needs, and improving
the quality of life of the community. (Synopsis of concepts
expressed by del Camino and Muller, 1993; and Tabora, 1991; and
CSA, 1992)

Agroecology and Ecological Engineering are disciplines that encompasses
methods which can assist in achieving the goals of sustainable agricultural

development, and are the subject of the next sections.

1.4.3 Agroecology
Natural systems are highly diversified and are structurally complex. These

properties

"provide a natural mature ecosystem with a measure of stability in a
fluctuating environment (Altieri, 1983, p. 15 quoting Murdoch,

 

2 The art, customs and science of managing land, crops and the people involved in it.

3 An Agroecosystem is an ecosystem that has been disturbed by humans using soil
resources to produce plants and animals for their immediate consumption or for further
industrial processing. Therefore, the ecosystem is subjected to ecological as well as
socio-economic constraints (Mata and Quevedo, 1990 and Altieri, 1987).

‘ Defined by Hernandez, C. 1996. Guacimo, Limbn: Escuela de Agricultura de la Regibn
Tropical Hameda. Edited by: Rincbn H., Fallas, C. and Alfaro, M., and translated to
English by Judy, W.

ju

l
mini ..
“It vuu ..

35:53
)8???
Were:
a c
an: . '61

I656“! a

d'mfin' ‘

l'4il |l\
v

U :-

 

29

1975). Severe stresses in the external physical environment, for
example, (such as a change in moisture, temperature or light
conditions) are less likely to adversely affect the entire system, for
in the presence of a highly diversified biota, numerous altematives
exist for the transfer of energy and nutrients through the system.
Hence, the system is capable of adjusting and continuing to
function with little if any detectable disruption. Similarly, intemal
biotic controls (such as predator-prey relationships) prevent
destructive oscillations in population numbers further promoting the
overall stability of the system (Altieri, 1983, p 15). "

Industrialized conventional agriculture simplifies the ecosystem by
introducing human intervened systems (agroecosystems) of few crops and
animals (Altieri, 1983). The objective of agroecosystems is to create managed
system that can efficiently capture and transform solar energy into resources
easily available at levels of productivity capable of satisfying human needs and
generating economic profit. In exchange, the agroecosystem loses its integrity
and flexibility which in turn affects compatibility, resiliency, longevity, stability, and

renewability (T abora. 1991).

"T he net result is an artificial ecosystem which requires constant
human intervention for its operation (Altieri, 1983, p, 15). "

Industrialized agroecosystems have proven capable of high yields, but
they are very fragile and susceptible to severe stresses caused by the external

physical environment (Altieri, 1983). They behave as immature ecosystems with

diminished ability to

"perform protective functions in terms of nutrient cycling, soil
conservation and population regulations. The functioning of the
system is thus dependent upon continued human intervention

(Altieri, 1933, p. 1 7) ".

Modern industrialized agroecosystems require considerable amounts of

renewable and non-renewable resources from outside the system to substitute

sin Ear

nay-.16
a Win.

_ 4 m (j H.‘ j 0)

j

—0-

 

30

functions done by nature in less disturbed systems. Furthermore, waste is
generated and introduced into a simplified system that has a reduced
assimilation capacity. Environmental degradation and non-sustainable growth

evidence the result of irrational resource use and waste generation.

The solution is to design alternative production ecosystems that are
similar in structure to natural systems. Altieri (1983, p. x) defines alternative

agriculture as

"an y approach to farming that attempts to provide sustained yields
through the use of ecologically sound management technologies.
Strategies rely on ecological concepts, such that management
results in optimum nutrient and organic matter cycling, closed
energy flows, balanced pest populations and enhanced multiple
use of the landscape. "

'T he scientific discipline that approaches the study of agriculture
from an ecological perspective is herein termed 'agroecology' or
'agricultural ecology' and is defined as a theoretical framework
aimed at understanding agricultural processes in the broadest
manner. The agroecological approach regards farm systems as
the fundamental units of study, and in these systems, mineral
cycles, energy transformations, biological processes and socio-
economic relationships are investigated and analyzed as a whole.
Thus, agroecological research is concerned not with the
maximization of production of a particular commodity, but rather
with the optimization of the agroecosystem as a whole. This tends
to refocus the emphasis in agricultural research away from
disciplinary and commodity concerns and towards complex
interactions among and between people, crops, soil, livestock
(Altieri, 1983, p. x)", economy, and environment.

 

am

Hagan. A r
U'H' ”LIV

Ire-Mt .
'I‘u'u‘: .a

93.388

is

{n ‘10-)

wov
V

(I:

(DC/)(T:

I")

 

31

1.4.4 Ecological Engineering

Ecological engineering is an emerging discipline and there is much
disagreement on precise definitions. The task to be accomplished by the
Scientific Advisory Committee (SAC) of the Scientific Committee for the
Problems of the Environment (SCOPE) on Ecological Engineering, of which the
author is a member, is to reconcile differences and arrive at acceptable
definitions.5 The author is not excited over defining a new discipline. The
important issue is to recognize that there is a new paradigm developing which

includes concepts and techniques that merit adoption.

 

5 The following are a few of the definitions presented to the November 1995 SAC-SCOPE
meeting in Estonia. The challenge is to extract from them what is useful and develop a
operational definition for this dissertation. According to Straskraba (Czech Academy of
Sciences), ecological engineering is the use of technological means for ecosystem
management based on profound knowledge of the principle on which natural ecological
systems are based, and transfer of this knowledge into management in such a way that
the cost and impacts are minimized. According to Ann Marie Jansson (Stockholm
University), ecological engineering is the design of human society in hamony with the
natural environment for the benefit of both. According to Mitsch (Ohio State University), it
is the design of sustainable ecosystems that integrate human society with its natural
environment for the benefit of both. According to Prof. Yan (Chinese Academy of
Science), ecological engineering is an overlapping science that makes the necessary
connection between ecology, technology, economics and sociology for sustainable
development. Mitsch (personal meeting notes) lists the fundamental concepts of
ecological engineering as follows:

. "Self-design (self organization) - Man plants the seeds but nature will choose the best
one for the system."

. "Ecosystem conservation - Do not throw parts of the systems away because you may
need them later (conservation of biodiversity)"

. ”Restoration as the acid test - Fix the damage that we have done. As we do it, we test
the theory."

. “Focus on biological systems."

E:
van ;‘

P" 4

|
|
...a..c‘.: w
|
$33.33;,
|
ETI‘ICTI."
of ma“
sne- s.ts
$723855 *

l‘ r
R a, ,.
v 558?,

f‘IA

viz-Ilse

EI‘IITQM

 

32

Ecological engineering, as interpreted by the author, implies limited
human intervention on ecosystems through design and management of
productive processes that use integrated knowledge of ecology, technology,
sociology and economics for the mutual benefit of both society and the
environment. At the plantation level, it is the integrated design and management
of human intervention and disturbance of the ecosystem, so that the waste of
one subsystem or process becomes the resources of a second subsystem.6 This
process generates a resource cycle that approximates the natural nutrient cycle

of balanced ecosystems.

Applying the previous definition, eco-managers control disturbance and
identify and track all components that generate waste. Ecological Engineers
design and formulate clean and appropriate technologies7 that eliminate,
substitute or minimize undesirable inputs and processes. Together managers
and designers work to minimize intervention and maximize production by using
the capacity of an ecosystem to adapt and self-design. Ecology is the basic
science used to understand the interaction between organisms and the

environment. System analysis is the management method of tracking sinks and

 

° This definition is a product of discussion at the Estonia SAC-SCOPE conference and not
originally mine. It is part of my notes on the conference but no individual credit is
included.

7 Cleaner technologies have three basic objectives: (i) to generate less environmental

pollution (water, air and soil) per unit of production, (ii) to generate less waste per unit of
production, and (iii) to use less natural resources (water, energy raw materials) per unit of
production. Note that cleaner technologies do not mean zero pollution. It is a dynamic
concept that has to be reviewed and results fed back to the system constantly to

33

throughputs. Sustainability indicators, such as energy efficiency and waste, not

money, are the common denominator of value.

Ecological economics is a tool necessary to keep score and measure
economic success or failure. Through multidisciplinary task forces, the negative
effects are minimized, the environment is conserved and biodiversity is

protected.

Using Ecological Engineering concepts, the best management practices
can be defined and implemented into the production system. However, it is
necessary to evaluate the results in order to introduce feedback mechanisms
with appropriate signals to correct and improve the system. The following
section defines evaluation through matrix analysis and identifies descriptors and

indicators for sustainable banana production.

1.4.5 Monitoring Sustainability

1.4.5.1 Introduction

As stated previously, most experts agree on three basic conditions for
sustainable development - environmental stability, economical feasibility, and

social acceptance and justice. The problem is how to measure and evaluate

 

incorporate in the system of production the best technologies available at a particular
point in time.

34

these conditions without undue abstraction so that there at least is an ordinal

ranking of achievement.

Pure economic theory only accounts for values that show up in a perfect

market system.

"T o introduce into this picture judgments about relative values or
purposes not correlated with price would dismpt the entire
discipline (Daly and Cobb, 1989, p. 93). "

Exceptions or market failures are identified as externalities and a modest
attempt is made to correct them. However, the corrections do not take
satisfactory account of the significance of the environment, consider accurately
cultural fitness or equity, or the welfare of future generations (van der Bergh and
van der Straaten, 1994; Daly 1991). Consequently, policy decisions routinely fail
to acknowledge these components (van der Bergh and van der Straaten, 1994,
p. 103) because analytical tools used rely heavily on mathematical economic
models, such as Cost Benefit Analysis or National Accounting System, which are
assumed to be value-neutral. However, society is not value neutral and the

models fail to portray reality (Daly and Cobb, 1989, p. 95).

In hopes of solving the problem, Ecological Economists have developed
procedures for quantifying qualitative elements such as intrinsic values,
principles and ethics. These methods have a danger of assigning precise
monetary values and encompass all components through imprecise and indirect
procedure. The non-expert end-users, such as politicians, may assign excessive

faith to the number value to make policy decisions that have monumental effect

35

on society. Daly and Cobb (1989) refer to this as the "Fallacy of Misplaced

Concreteness".

Naes (1986, p. 510) suggests that the solution is to be found in

philosophical concepts and states that

—"What is needed is a methodology of persistently connecting basic
value judgments and imperative premises with decisions in
concrete situations of interference and noninterference in nature.
What I therefore suggest is that ...scientists repeatedly and
persistently deepen their arguments with reference to basic value
judgments and imperative premises. That is, they should announce
their normative philosophy of life and discuss environmental
problems in their most comprehensive time and space frame of
reference. "

In summary, disagreements and discontent with available methods
justifies the necessity for further research to find an integrated analytical
approach that assigns careful and explicit attention to the complex dynamic

processes that integrate

"economic activity, the physical-material output, the environmental
consequence, and the welfare impact (van der Bergh 1994, p. 4) ".

Care should be taken to avoid falling into the same mistakes and indulge

in "Misplaced Concreteness". Consequently, the following tasks claim relevance:

9 State a normative philosophy to reach sustainable production.

0 Recognize descriptors with proper and measurable indicators of
sustainability.

0 Advance a method to judge qualitatively the effects of production strategies
in relation to the accomplishment of the normative philosophy, and to
translate this judgment through a holistic and systematic method into
quantitative ordinal indicators.

14112

> I
.5. _
LEVI."

FAA” '7'
VVV‘

r. .
Imp“:

a Sjsf
C337:

549395

elierk

 

 

36

1.4.5.2 Sustainability Accounting

Howard Brown (1996. p. 2-3) gives new meaning to Darwin's "survival of
the fittest" by slightly modifying it to "survival of the fitter". This implies that those
that survive are the "most willing and able to fit into their environment". He

further illustrates his point through Howard Odum's

"often-quoted assertion that one can understand a system only by
understanding the system into which it fits (the environment) ".

If the banana industry wishes to survive, it must create new and innovative
mechanisms to understand and measure its fitness for success. Thus, the
information needed must go beyond the financial balance sheets and also

include environmental and social elements.

Bayley and Soyka (1996, p.14) introduce the concept of environmental
accounting and define it as a set of tools used to gather and provide numerical
information to track the accomplishment of environmental goals. They warn that
a system should respond to internal needs rather than those outside the
organization and thus any accounting system should be tailor made. They also
. suggest that a good practice is to start small and grow as you learn and acquire

experience.

Metcalf, Minter and Hobson (1996. pp. 7-11) introduces the environmental

performance indicator (EPI) and defines it as

"a tangible measure that provides a reference point to track
progress in a specific environmental area "

and lists the following best practices:

 

(I)

((1
4'.

00....

37

Use of a bundle of objective measurable-indicators.
Indicators have meaningful units.

EPI data are collected and reported periodically.

A structured reporting mechanism is utilized.

Quantitative goals are established for each indicator.

Tracks are analyzed and continuous improvement is pursued.

Furthermore, Metcalf, Minter and Hobson (1996. pp. 7-11) notes the

following benefits of using EPI:

Defines quantitative rather than less effective subjective, often ambiguous,
goals and tracks progress towards achieving them.

Highlights areas of excellence and serves as a means of recognizing
employees' efforts.

Demonstrates continuous improvement and a quest for excellence.

Identifies weak spots in environmental mangement which need further
aflenfion.

Allows management to allocate limited resources in an efficient manner.

Provides a communication tool to convert accurate and concrete
environmental performance information to stakeholders.

Provides a mechanism for establishing accountability for environmental
results and reward systems that attach employee compensation to
performance goals.

EPI are not enough because they do not take into consideration economic

and social indicators. However, EPI provides the ground work for the elaboration

of the Sustainability Performance Indicator (SPI) in this dissertation. All the

general elements previously discussed related to EPI are valid for SPI.

Environment and economics come together when eco-efficiency is

considered. The Business Council of Sustainable Development (Fiksel, 1996)

defines an eco-efficient firm as a

38

“corporation that achieves more efficiency while preventing
pollution through good housekeeping, materials substitution,
cleaner technologies, and cleaner products and that strives for
more efficient use and recovery of resources."

Cleaner processes modify technology to reduce pollution and waste;
cleaner products imply a redesign of products so that they generate less pollution
and waste throughout their life cycle; and efficiency involves rational use of
resources so that fewer materials and less energy is used per unit of value
produced. In this new age an economically successful firm must design safe and

eco-efficient products and processes.

Fiksel (1996) emphasizes the necessity to include high-level
environmental metrics to give appropriate signals to decision makers. He gives

the following examples of performance metrics or indicators:

Energy consumed during product life cycle.

Total fresh water consumed during processing.

Toxic and hazardous materials used in production.

Total waste generated during production.

Hazardous waste generated during production.

Air emissions and water effluents generated during production.

0......

Greenhouse gases and ozone-depleting substances released during life
cycles.

Percent of recyclable materials available at end of life.
Percent of product recovered or reused.

Purity of recyclable materials recovered.

Percent of product disposed or incinerated.

Fraction of packaging or containers recycled.
Average life-cycle cost incurred by manufacturer.

0......

Purchase and operating cost incurred by the customer.

Once more, energy and waste (throughputs) show up as key indicators.

1.4.5

sis":

39

1.4.5.3 Evaluation Matrix

Matrix analysis is a common and useful tool in environmental impact
studies. Its virtue is that it is a viable and proven way of synthesizing, organizing,
visualizing, and valuing, in a systematic manner, the multiple elements which
contribute to the environmental impact of an action (Edmunds and Letey, 1975).
The best known matrix method for environmental impact analysis was developed
by Dr. Luna Leopold in 1971 (cited by Nava from Lepez, 1991). It consists of 100
independent variables laid out on the horizontal axis and 88 dependent variables
listed on the vertical axis. The impact of the independent variable on the
dependent variable is evaluated according to importance and magnitude. The
results are registered at the cell marking the intersection of the column and row
of the matrix arrangement (Kolhman, 1997). Each cell of the matrix is divided in
two segments by a diagonal line. Impact values are recorded on the upper left
comer and importance values in the lower right comer (cited by Nava from
Conesa, 1995). Values of importance and magnitude are assigned by the
researchers in a subjective manner using a scale from one to ten (cited by Nava
. from GTZ and IICA, 1996). One represents minimum impact and significance.

Ten represents maximum values. In Leopold’s method, zero is not a valid value.

The Leopold's Matrix method has important limitations, as a research tool,
in that it is qualitative and subjective. It depends on the personal appreciation of
the evaluators and thus has a reduced replicability. However, it has proven to be
very useful in preliminary analysis and to identify problems that require a more

rigorous analysis (cited by Nava from GT2 and IICA, 1996)

40

This dissertation adopts and modifies a method similar to Leopold's Matrix
to measure the impact of agricultural practices on sustainability. An analysis to
determine the degree of sustainability has two additional degrees of complexity *
more than does the environmental impact analysis - in addition to environmental

impact, it considers social and economic impacts.

As in environmental impact analysis, sustainability has many independent
variables, which together determine the final effect or outcome (dependent
variable) of any action. The first task is to determine the most important and
relevant dependent variables using a systematic method that can be replicated

with reasonable ease.

Veroutis and Aelion (1996) developed a system to compare criteria and
assign levels of relative importance by using an Analytical Hierarchy Process

(AHP). This process is defined by them (1996, p. 63) as

”a multicriteria decision-making methodology that enables
consideration of extensive sets of dissimilar qualitative and
quantitative criteria in making a decision ".

They further state that

"the methodology juxtaposes the qualities and features of the
options against the relative importance of the evaluation criteria to
derive an aggregated measure of performance. This analysis is
based on a rational (and scientifically defensible) mathematical
algorithm, thereby adding credibility to the ranking... AHP is based
on the concept that when a fundamental metric is unavailable,
assigning relative importance can be done much more accurately
and reliably by using comparisons among competing issues rather
than by using an arbitrary metric scale. "

41

As a result, a pairwise matrix comparing decision criteria is developed which
Veroutis and Aelion call a "Criteria Mapping Matrix". In this matrix a list of
dependent variables is established. These variables are listed in the horizontal
and vertical axis. Each variable is compared to all the others and relative
importance is judged. Veroutis and Aelion (1996) suggest a fundamental scale
of importance starting with equal importance, which is given a value of 1, and
ending with a 9 indicating extreme importance. Summing each row tabulates the
matrix. Then, the totals of each row (last column) are added. Relative
importance weights (%) are assigned by dividing the sum of each row by the sum

of the totals.

The next task is to identify actions or methods of doing different tasks
(independent variables) and determining the impact they have on the
sustainability criteria (dependent variables). Some actions will enhance
sustainability and some will have a detrimental impact. A fundamental scale of
values to assess impact, similar to the one used in the "Criteria Mapping Matrix",

must be devised to avoid positive and negative signs in impact valuing.

The final step is to set an optimal standard of sustainability and to
compare agricultural practices to this standard. Allenby (1996, p. 77) developed
a matrix analysis system "to bridge the gap between the doable and the optimal"
to analyze materials for the design of products using the "Design for the
Environment Approach" (DFE). Important criteria, which he calls elements
(dependent variables) are identified and arranged in the horizontal axis of the

matrix. Optimal conditions are identified for each element and a "Matrix Element

Pr

~.~

 

42

Checklist" is developed that asks the appropriate questions to determined if the
optimal condition is met. The different life cycle processes are identified and
recorded in the vertical axis. Each material chosen for evaluation is tested at

each level of the life cycle by proceeding through the Matrix Element Checklist.

An analogous procedure can be developed for agricultural production.
The elements, in this case, are the sustainability criteria, the levels in the life
cycle are the different components of the banana production system, and the
different methods and technologies in the production process substitute the
materials tested. Optimal conditions are defined to minimize negative impact on
sustainability. A Matrix Element Checklist is developed to ask the appropriate
questions and determine the degree of optimal compliance. Values for
compliance of each method can be compared to the optimum values. Ideal
compliance can be assigned a value of one; and acceptable compliance a value

of 0.6. In the AHP method, no compliance can be assigned a zero.

Since the relative weights of importance of the dependent variables were
previously determined, the sustainability evaluation matrix is simplified. The
assigned compliance value of each independent variable is multiplied by the
relative weight of each dependent variable. The resulting value is a coefficient of
impact. The sum of the coefficients of impact is a measure of degree of

sustainability that can be defined as a sustainability index.

a:

S?

(I)

43

This dissertation will measure the degree of sustainability for the best
available practices in the case of world class banana production and will

compare these values to other suggested methods of production.

1.5 The researchable questions, problem and search for solutions

The overriding researchable question is - is it possible to attain a
sustainable production system of world-class bananas by modifying the
conventional production technology presently used in Costa Rica without
significantly changing the market component? This dissertation assumes the
affinnative. However, it is important to recognize that some experts believe that
no monoculture system can be sustainable. More optimistic experts are
convinced that technology can only help approximate sustainability; few accept
that a truely sustainable system can be attained; and many believe that the
market must suffer considerable modification before sustainability in production

can be achieved.

The problem is that there is no clear definition of what constitutes a
sustainable production system or a systematic method of evaluation. EARTH

(Escuela de Agricultura de la Region Tropical Humeda)8 owns a state-of-the-art

 

° Escuela de Agricultura de la Regibn Tropical Humeda (EARTH) translates into English as
the College of Agriculture of the Humid Tropical Region. EARTH is a non-profit, private,
international university dedicated to education in agricultural science and natural
resources, contributing to sustainable development of the humid tropics. It is located in
the district of Guacimo, province of Limbn, Costa Rica. This location is immersed in the
major banana producing region of the country. EARTH College owns and operates a
large commercial banana plantation (283 Ha.) that offers a unique opportunity for the
search, application and verification of new and appropriate knowledge. Beginning in

44

banana plantation that produces world-class bananas. It uses improved
technologies that are guided towards sustainable production, and has earned the
ECO-OK seal of the Rainforest Alliance. However, the faculty of the College
feels that it falls short of the ideal situation. Other plantations, some which also
have the ECO-OK seal, have experimented with different practices that
apparently improve the conventional technology, but there is no consensus of the
experts to what constitutes a sustainable plantation, what the best available
practices to achieve sustainability are, or what parameters should be used to
judge the degree of sustainability. It follows that there is no existing plantation in
Costa Rica that is using a farming system that is universally accepted as a state

of the art sustainable production system.

Considering the previous discussion, the dissertation will ask the following

questions:

0 What is a working definition of sustainable banana production?

o Is it possible to construct a systems model of world-class banana production
in Costa Rica at three levels of ecological organization that adequately takes
into account the ecological, social and economic components, their
interactions, and the inputs and outputs of the system?

9 Using the system model, can a suitable quantitative measuring method be
devised to evaluate and relate these effects to the normative philosophy of
sustainability, and can appropriate quantitative ordinal sustainability indexes
be developed to evaluate banana production processes?

9 Can the system model help in answering the following questions?

 

1991, EARTH College pioneered an effort to identify and solve the problems of banana
production through a waste management project financed by the W. K. Kellogg
Foundation. Consequently, waste reduction and management has been vastly improved,
reforestation of rivers banks completed, end of pipe treatment systems implemented to
assure water quality, agrochemical risk to humans decreased, and understanding of the
problems enhanced.

(H

(.7)

45

0 Is the current banana production in Costa Rica sustainable?

0 If not, what changes can be implemented to improve sustainability?

0 What are the effects on the ecosystem of proposed changes?

0 Which proposed changes contribute the most to sustainable production?

0 Can a sustainable production system be implemented without changes to
the market structure?

0 What bundle of technologies gives the greatest effect in seeking
sustainable banana production? Can these best available practices be
used as a base datum for comparison?

0 Is it necessary to change the market structure to implement new and
appropriate technologies?

The following tasks are proposed to answer these questions:

. Formulate a theoretical definition for sustainable production of world-class
bananas acceptable to a panel of leading experts in the field and
representatives of the different sectors of the banana business
(stakeholders).

. Use a systems model to recognize cause and effect relationships and typify
independent, dependent and control variables.

. Arrange these variables in a matrix system.

. Choose a reduced set of dependent variables to monitor according to degree
of importance based on value judgment by a panel of experts.

. Identify a group of sustainability performance indicators (SPI) to measure
each dependent variable chosen, aggregate them when possible, and set
minimum acceptable criteria.

. Recognize practices that have demonstrated merit (independent variables)
and choose a package of best available practices through consultation with
stakeholders

. Test the resulting bundle of best available practices against the minimum
criteria, and verify the hypothesis by judging the degree of compliance with
minimum acceptable SPI criteria.

. Identify deficiencies that merit further inquiry.

46

Consensus on a definition for sustainable production of bananas and
choice of monitoring variables will be pursued through personal interviews with a
select group of experts. The best available practices will be identified through
personal interviews with specialist of the following aspects of the production
system - environment, social and economy aspects. Details for each task will be
outlined in Chapter 3 - Methods. The desired result is a verifiable and replicable
method able to generate useful information for decision makers. This information
should signal compliance or point out areas that require the allocation of

resources for further development.

1.6 Statement of hypothesis

The hypotheses are as follows:

Hypothesis A
Ho: The Conventional Production Practices (CPP) are
environmentally, socially and economically sustainable.
H1: The CPP are not environmentally, socially and economically
sustainable.
Hygothesis B
Ho: The Sugested Production Practices (SPP) are
environmentally, socially and economically sustainable.
H1: . The SPP are not environmentally, socially and economically

sustainable.

The independent variables reflect new clean and appropriate technologies
identified as the best available practices that the producer can introduce to the

production system, and the dependent variables reflect the causal effects on

47

inputs and outputs by modifications in the system. The world-class standards for
fresh fruits and the market structure are the control variables since they are
beyond the producer's dominion. The analysis tool is a systems model of a
banana plantation, a theoretical definition of sustainable banana production, and

a matrix analysis of measurable effect indicators.

1.7 Justification and relevance

The problems of banana production for the export market have important
repercussions, which transcend political frontiers. Bananas are produced in most
of the tropical countries of the world, and it is a basic food source for the people
of these countries. The tropics represent about 20% of the earth's land mass.
Approximately 45% of this area is located in Latin America, 30% in Africa, and
25% in Asia. The region is home to two billion people distributed in
approximately sixty countries. Banana varieties used for the export market are
particularly well adapted to the humid tropic ecosystem, often referred to as
tropical rainforest. About 7% of the earth's land surface fits the tropical rainforest
ecosystem's characteristics. The experts believed that these areas are critical
and very sensitive because they harbor more than half of the world's plant and
animal species (CSA, 1993). Due to climate and edaphic conditions, the tropical
rainforest ecosystems are very fragile and susceptible to disturbance by human

activity.

Brazil and India are the largest producers of bananas in the world,

however they produce essentially for internal consumption. Since this research

 

 

ls II"

N'-
V v

 

NH“
H Um.

8X2:

 

48

is limited to the study of the problems caused by the conventional technology
used to produce world-class bananas, fruit from Brazil and India are disregarded.
The Philippines and Ecuador are the third and fourth largest producers in the
world respectively, however the Philippines exports less than half of its
production while Ecuador exports 90.2% of its production, and is the largest

exporter of bananas in the world (Soto, 1992).

Costa Rica is the second largest exporter supplying 15% of the total
export market and is the focus of this study. This country was chosen as a
representative case because of high productivity, the use of advanced
industrialized agricultural technologies, a marked and growing interest by its
citizens for environmental integrity, availability of data, and logistic advantages

for conducting the research.

EARTH's banana farm9 is located in the center of the banana producing
region of Costa Rica. The climatic and edaphic conditions are not the best or
worst in this region and the production is slightly above the country's average.
EARTH's plantation is divided into five distinct projects serviced by one packing
plant. The smallest project is 40 hectares, the largest 140 hectares, and all are
connected to the packing plant by a cable transportation system. The oldest
project has been farmed continuously for the past 30 years and the newest

started production in the last five years.

 

See footnote number 7.

 

the

 

5.2?

QF‘AI

49

In Costa Rica, the smallest plantation growing bananas for export has 40
hectares and the majority of the farms range between 100 and 300 hectares.
The oldest farms have been in production in excess of 100 years, most have
been in production for at least 10 years, and the newest have recently started
production. Therefore, EARTH's commercial farm is representative of typical
world-class banana plantation for Costa Rica. It is distinguished from the others
because of its continuous effort to identify and employ the best available people

and environmental friendly technologies.

This study emphasizes the best available practices that are controlled by
the producer, and recognizes the importance of externally controlled variables,
such as markets and trade policies, that have a colossal effect on sustainable
production but are beyond the producer's control. The United States is the
largest importer of fresh bananas (32%), followed by Germany (13%) and Japan
(8.7%). The United States and Germany are primarily supplied from Latin
American producers while Japan is supplied by the Philippines (Soto, 1992).
According to 1991 statistics, Costa Rica exported 51.8% of its bananas to the
United States, and 49.2% to Europe (Sanchez and Barrientos, 1992). Because
of their predominance as customers, the study is limited to the structure and

standards of these two markets.

World-class banana production is a critical element of Costa Rica's
economy. This agroindustry is the most important generator of foreign currency.

It is an important source of jobs and opportunities for related businesses, and

50

supplies many services to the communities. These bountiful benefits to Costa

Rica are reciprocated by immense corresponding costs.

The literature reveals sufficient information on biological and agricultural
aspects of banana production. However, there is a lack of published information
on environmental and ecological aspects. Daniel Janzen (1983, p. 77) confirms

this situation, stating that —

"Though extensive in occunence, the banana plantation as an
ecological habitat has been little studied. "

This lack of information points to an opportunity for pertinent and much
needed research and peer reviewed publication, which can be generally
accepted as trustworthy. It confirms the need for verification of suppositions and
rejection of unsupported declarations that the effects of banana production on the
environment are not as inoffensive as producers proclaim, or as severe as

environmental activists portray them.

As stated in previous sections, there are many definitions of sustainability,
yet there is not one that is universally accepted. There are fewer definitions of
sustainable agricultural development, but once again, there is no consensus (del
Camino and Muller, 1993). Finally, the literature does not provide a definition of
sustainable production of bananas for the export market. Many experts believe
that a universally accepted definition is detrimental and that one should be
derived to fit each case and purpose. Nevertheless, the Instituto lnteramericano
de Cooperacibn Agricola (IICA, 1991) manifests that the lack of a precise and

objective definition is the first difficulty to overcome in defining strategies for

SL.‘

(1.

r‘f':

51

sustainable development. It also recognizes the importance of identifying

indicators capable of measuring beyond economic growth.

A prerequisite to solving the problems of the banana export industry, it is
necessary to elaborate a united and integrated strategic plan including the
development of a matrix to measure economic, environmental and social impact.
However, before a matrix can be developed, it is imperative to define what
constitutes sustainable‘production of bananas and what the objectives and

principles are that must guide this activity.

Notwithstanding the lack of an objective and clear definition of sustainable
development, the literature revealed a consensus that three conditions must be
achieved for sustainable development: 1) economic feasibility, 2) environmental
soundness and 3) social appropriateness and equity. According to the opinion of
many experts, present world-class banana production practices in Costa Rica fail

all three requirements for the reasons that will be analyzed in detail in Chapter 2.

The problem is complex and so are its causes.10 The causes can be
divided into the following five categories and ranked by their degree of difficulty in

the following manner: 1) Cultural and Social, 2) Political, 3) Market, 4) Financial,

 

1° A detailed analysis of the causes was conducted by the author through a series of
workshops with EARTH's faculty and fourth year students. The typical forth-year student
has had sufficient theoretical courses and practical experiences to express a very
educated opinion.

 

 

3'33

Va

 

 

M
a"\l

52

l.11 Due to the complexity of the problem and causes, the

and 5) Technica
pertinent question is how to analyze proposed changes in a holistic manner so
that changes introduced in one component do not create even greater problems

in other components.

A systems approach is a proven tool that facilitates holistic analysis by
characterizing the nature of the system under study in such a way that the
decision making can take place in a logical and coherent fashion. The first step
is to define an appropriate temporal and spatial scale, or levels of organization.
The larger the limits, the more information is available and the larger the need for
aggregation. The resulting model is therefore the less powerful and sensitive.
Conversely, if the scale is too small, the model becomes insensitive to interaction
with higher levels of organization (del Camino and Muller, 1993). The
appropriate level of analysis for this dissertation is the banana plantation.
Nonetheless, it recognizes interactions with global, regional, national, local and
micro scales. The system's model used serves as a map of components, actions

and reaction, and inputs and outputs.

The long-term goal is to develop an integrated set of guiding principles

and measurement system that can steer the industry toward sustainable

 

'1 Note that the technical problems and causes are the least difficult to solve. The faculty
and the students interviewed all felt that the technology is available if the other 4
problems are solved.

53

development. The short-term goal is to identify the best available practices for

immediate implementation by the producers.

1.8 Conditions outside the control of the producers that have a bearing
on change

The banana export industry was born approximately 120 years ago with
the development of transnational marketing firms (Soto, 1992). History shows
that these firms were not kind guests of producing countries or good stewards of
the environment. It is a past that the people of Costa Rica wish to forget, but
should not forget. The important issue is to learn from the past, analyze the

present and find ways to improve the future.

The magnitude of the banana industry is very large and complex.
Considering all the different components, it is a multi-national and multi-billion
dollar industry (The Packer, 1994). Consequently, it is very attractive to large
transnational firms because it is an opportunity to create a vertically integrated
system capturing many profit centers. These include production, transportation,
and marketing. It easier for small local firms to master the production component
. of the equation, however transportation and marketing is a superior challenge.
Because markets demand quality, service and price, and their territorial limit is
the world, they require a sophisticated and large support infrastructure. This
translates into large investments, economy of scale and experience. Therefore,

giant transnational firms control the market.

 

"Lj
‘

3.”

T)
“ 'V
( I

51'

 

COL

ma

ss':

54

Controlling the market means controlling quality standards, quantity and
price. In the consumption end of the equation, it is accomplished through price
and brand recognition. In the production side, there is no choice. Transnationals
buy from whomever they choose at the price they set. When governments of
producing nations intervene, transnationals use powerful politicians to exert
pressure through loss of most favorable nation status, or by blocking bilateral aid

and multilateral loans.

Transnational firms have primarily three home origins - United States,
Europe, and Latin America. However, their ownership and legal structure is not
necessarily tied to one country. The order in which origin was presented reflects
the importance, experience and market share. At the present time, there is a
struggle between Europe and the United States to change that order and home
governments adopt policies which favor their own transnationals at the expense
of economic, social and environmental impacts in the less powerful producing
countries. As a producing nation, Costa Rica has suffered, but it has learned to
maneuver and take advantage of competition among these firms to make

substantial changes.

The model that is being proposed, identifies the links and measures the
effects of marketing policy changes. It can be used to identify the missing direct
feedback loops between consumers and producers. Through this connection,
the producer can educate the consumer, create market niches, and generate

opportunities to sell the product of new non-conventional technologies.

55

1.9 Conclusion

The following summary scans the information presented in this chapter:
According to the opinion of many experts current banana production technology
is not sustainable because it fails the three basic conditions: 1) economic
feasibility, 2) environmental soundness, and 3) social appropriateness and
justice. There is an urgent need to verify this opinion. If true there is an urgent
need for change and improvement. However, there is no universally acceptable
normative philosophy that guides changes towards sustainability. Furthermore,
there is no systematic method that traces and measures effects through the
entire system. This is important because change in one component will
automatically affect all other connected components of the system. Positive
change in one component may bring disaster in other components. In
conclusion, there is a need for a systematic method capable of identifying and
evaluating the effects of changes and of determining their contribution to

sustainable development.

The next step in this dissertation is to place the problem within its
environment. Chapter 2 presents the banana case noting problems, symptoms
and causes, and suggesting solutions. Then, the details of the proposed method
will be presented in Chapter 3. Chapter 4 will bring together and analyze the
results. Finally Chapter 5 will present the findings, conclusions and

recommendations.

The previous discussion has confirmed the value of developing a

normative philosophy, but it has highlighted the complexity of the proposed

56

hypothesis. It has recognized that the producer controls not all elements of the
banana industry. It has alerted the author to the need for setting realistic
boundaries to this research. It has reminded the author that he has an
immediate task to accomplish and that he can not tackle the entire problem. In
essence, this dissertation marks the beginning of a permanent and dynamic
search for a vision for the banana industry of Costa Rica as it tries to develop a
sustainable system of production with the purpose of building a new and better
world, one that offers greater opportunities for a better quality of life for present

and future generations.

Chapter 2

PROBLEM FOCUSED LITERATURE REVIEW

2.1 Introduction

This chapter is a revised and up-dated version of the article titled

“A Systems Approach to Evaluating and Managing the
Environmental Impact of Banana Production in Costa Rica”

written by the author of this dissertation and Dr. Scott Witter and published
in AMBIO in May 1996. The objective of this chapter is to review the available
literature in order to appraise present conditions in the world-class banana
production industry, identify the major problems, and to seek alternative solutions

to improve the sustainable performance of the banana production processes.

An important part of Costa Rica's 20th century agricultural growth and
development has been the increase in banana production and economic growth
without regard to ecosystem integrity. Human wants and needs have prevailed,
and natural resources have proved to be exhaustible. Furthermore, the
allocation of the benefits from the exploitation of the natural resource base has
not always been equitable among Costa Ricans or between transnational

companies who mine the country's resources.

Ecologists, especially non-Costa Rican ones, want to adopt John Muir's

(early American ecologist) approach to Costa Rica's natural resources,

57

58

conserving and preserving the abundant biodiversity of flora and fauna for future
generations at all costs. Yet, if national and transnational companies that
degrade the environment are too restricted by environmental regulations and
move to a country with fewer restrictions, as they have throughout history (Casey
Gaspar, 1979), it is only Costa Ricans who will suffer. A balance must be sought

between unsafe resource exploitation and needed economic growth.

Vlfithin Costa Rica and throughout the humid tropics, the concept of
sustainable development is gaining momentum as countries face the reality that
most renewable natural resources are quite limited (Brown, 1993; CSA, 1993;
Edwards, Grove, Harwood and Pierce, 1993; MIRENEM, 1992; Prance, 1989).
The necessity for long-term planning is being discussed by all of the banana

sector stakeholders.

This chapter presents an overview of banana production in Costa Rica
based on the importance of bananas as an export crop and the environmental
impacts associated with their production. The author takes a systems approach
to identifying problems and suggesting ways that will help to balance the
economic exploitation of Costa Rica's natural resources with long-term

environmental integrity.

W

(I,

W
\

fl)

 

,_

if.
V

 

59

2.2 Systems Approach

A system is defined as

“Any phenomenon, either structural or functional, having at least
two separable components and some interaction between these
components (Churchman, 1968). ”

A systems approach is a tool that facilitates comprehensive analysis by
considering the nature of the system under study on many levels and in such a
way that the decision making can take place in a logical and coherent fashion,
thus minimizing the occurrence of “the fallacies of narrow-minded thinking"

(Churchman, 1968).

The first step is to define the spatial and temporal boundaries of the
system under consideration. The system is broken down into components and
functions that control exchange among components and that are interrelated by
cause and effect, stimulus and response. This process helps identify internal
and external causes and effects, inputs and outputs, and the appropriate

opportunities for action.

At least in theory, the consequences - that is, the reaction of every action -
- can be traced through the system and a resulting behavior predicted. On the
basis of this prediction, adjustments can be made to improve the system and/or
components and standards may be modified to fit reality. This process is

referred to as modeling, and its purpose is to help with conceptualizing,

 

 

60
organizing, and communicating complicated phenomena (Hall, Cleveland and
Kaufmann, 1977). Modeling is often accompanied by an extensive effort to

assign mathematical formulas to quantify stimulus and response.

At the beginning of a systems analysis, however, mathematical modeling
is often unreliable. Models depend on the volume and precision of existing data
and especially on the quality of the underlying concepts. When all are poor, as
they frequently are because of collection techniques and a lack of knowledge of
the system itself, the model may have little bearing on the existing situation. It is
often far better to start at the beginning and develop a conceptual/descriptive
model followed by a diagrammatic or flowchart depicting the system (Hall and
Day, 1977). This is then followed by the development of an appropriate
mathematical model which can be converted to a computer program that allows
for an analytical quantification and/or simulation of the system (Hall and Day,
1977). The objective of this dissertation is to develop a mathematical model.
This model organizes data gathered from a panel of expert assigning weights to
the interactions between components of the system. It also allows for the
experts to rate production practices based on their impact on the environment,
society and the economy. The result is a Sustainable Performance Index that
assigns a grade according to the degree of sustainability of alternative production

practices. Such analysis, by its nature, requires interdisciplinary thinking and

action.

61

2.3 Costa Rica

Costa Rica's climate is tropical and subtropical, and the interception of the
trade winds by the central mountain range produces large quantities of
precipitation along the northeast slopes with annual rainfall in excess of 1500 to
4000 mm. Large-volume, rapidly flowing rivers originating in the mountains
chisel high-mineral volcanic rock sediments from the mountain slopes and
deposit them in the lowlands. Some of these sediments are ideally suited for
high-production banana plantations. The Caribbean coastal plains of Costa Rica
possess bountiful areas with soils that possess these characteristics and account
for 98 percent of the total area planted (Figure 4) (Sanchez and Barrientos,

1992).

Commercial banana plantations are generally located at altitudes below
200 meters with annual rainfall levels below 4000 mm and are usually on sites
with little or no slope. They require a complex drainage system to funnel excess

water from the site (Lauer, 1989).

Bananas produced for the international markets can only be commercially

produced on the best soils.

“They require flat terrain, deep (no less than 1.20 meters), good
structure, and well.drained soils (humid but not saturated) with a
high balance of nutrients (especially potassium) and a pH between
6 and 7. 5" (Soto, 1992).

To maintain commercial production rates, it is necessary to add significant

amounts of fertilizer to the soil throughout the entire growth cycle.

62

Costa Rica's Banana Producing Regions

 

Flguro 4 - Map of Costa Rlca: Banana Growlng Raglan 8. EARTH Collage
Location

63

2.4 Banana Production in Costa Rica

Minor Keith started the first commercial banana plantation in Costa Rica in
1872, in Zent Valley. By 1879, Costa Rica was exporting bananas regularly to
the United States (Soto, 1992). It was at this time that the first transnational
companies emerged, attracted by generous land concessions, tax exonerations,

and other government incentives.

The Boston Fruit Company and Minor Keith joined forces in 1899, forming
the United Fruit Company. This partnership helped develop a worldwide market
for bananas, and began the dominance of United Fruit over Central American

banana production. By 1920, United Fruit was well established in most of the
Central American countries. And by 1930, United Fruit owned about 4 percent of
the total territory of Honduras, Guatemala, Costa Rica, and Panama. The
company's political influence brought about the humiliating characterization of
these countries as ‘Banana Republics', a perception still held by much of the

world.

Unregulated exploitation strategies of maximum production with minimum
input typified early transnational operations. Eventually, of course, production
efficiency dropped and, when the Panama banana disease forced production
down further, United Fruit began abandoning plantations along the Atlantic coast
of Costa Rica and transferring operations to the Pacific coast (Casey Gaspar,

1979; Kepner, 1935; McCann, 1976).

64

By 1956, the government of Costa Rica had become concerned about the
growing number of banana plantations abandoned due to the ‘Panama disease',
inefficient production technologies, and the careless use of the country's natural
resources by the United Fruit Company. The need for a shift in the banana
production process was apparent, and so began the second era of banana
production in Costa Rica. In an attempt to offset the, downward trends, the
government recruited Standard Fruit Company, which not only established its
own plantations but also began purchasing fruit from Costa Rican producers

(Bourgois, 1989; McCann, 1976).

Standard Fruit introduced the Valery banana clone, which was resistant to
the Panama disease, produced increased yields, had favorable packing and
shipping characteristics, and generated a product that was acceptable to
international consumers. This transformation was not without side effects,
however. The Valery banana required considerable chemical intervention as
Well as intensive field and processing management (i.e., plastic bags, special
packaging, and atmospheric controls during shipment). Therefore, while the
addition of Standard Fruit introduced competition to the banana economy, it
changed banana production from a low chemical input system to one dependent
on large volumes of pesticides, herbicides, and fertilizers. While government
regulates the chemicals that can be used in Costa Rica, the transnational
companies have traditionally determined the volume, kinds, and frequency of

chemical use in banana production.

65

The nationalization of the banana market in Ecuador in 1965 resulted in
the migration of other transnational companies to Costa Rica, further intensifying
competition and the need to produce more per hectare (Soto, 1992). A decade
later, United Fruit was reorganized, becoming the United Brands Company, and
introduced the Chiquita label to Costa Rica. In the 1980s, United Brands closed
its operations on the Pacific coast of Costa Rica and returned to the Atlantic
under the name of Compania Bananera del Atlantico Ltda (COBAL). COBAL
aggressively expanded banana production along the Atlantic and now is the
second largest producer in the country. Today, the transnational companies
produce 40 percent of the total harvest and control another 58 percent of the
country's banana exports. Although Costa Rican-owned companies produce 60
percent of the bananas exported, the majority of the companies follow
transnational—dictated production practices and quality standards, and the

bananas are exported under the control of the transnationals.

Costa Rica, as a national policy and by the actions of many individuals
and companies, has chosen to generate much of the revenues needed for
foreign exchange through growing traditional cash crops for export.12 The

agricultural sector of Costa Rica contributed 19.6 percent of the gross national

‘2 The World Resource Institute (T hrupp, 1994) defines nontraditional exports as "various
agricultural products destined for export markets, other than coffee, bananas, cotton,
beef, and sugarcane. A product is considered nontraditional if it: 1) in not produced in the
particular country before, such as broccoli in Ecuador, 2) was traditionally produced for
domestic consumption but is now exported; or 3) is a traditional product but is now
exported in a new market." As a corollary, coffee, bananas, cotton, beef, and sugarcane
are defined as traditional export crops.

66

product and banana production accounts for almost 30 percent of the sector's
total receipts (IUCN, 1991). Since 1990, no other export commodity surpasses
the contribution of bananas to foreign currency income in Costa Rica. Based on
the 1994 statistics, bananas were the most important crop generating $552.3
million (dollars US), followed by coffee at $300.2 million, meat at $51.3 million
and sugar at $32.1 million (Banco Central de Costa Rica, 1995). In 1994, the
banana export revenues represented 25% of all export revenues. In 1995,
revenues from banana exports rose to $649 million and the Government of Costa
Rica collected a total of $44.3 million in export taxes (Paez and Zufliga, 1996). It
is unclear how much of the banana export revenue actually remains in the hands
of the Costa Rican producers; however, it is apparent that the price paid to the

producer accounts for only about 25 percent of the consumers' price.

The economic impact of this production on Costa Rica's regional economy
is also quite significant. It takes 0.89 workers per hectare per year to manage
the plantation. Approximately 43,000 Costa Ricans are directly dependent on
banana production for their livelihood, and this does not include part-time

employment on plantations or the domestic service industries that support the

banana producers (Foro Industrial, 1994).

2.5 Systems Analysis of Banana Production

The ecosystem provides humans with the habitat in which they live and

the resources necessary to satisfy their needs and expectations. Development of

67

resources requires change. If managed properly, the change provides positive

benefits; if not, the opposite is true (Axinn, 1988; Colby, 1990).

There are five basic paradigms for the management of the relationship
between humans and nature: deep ecology, frontier economics (e.g., the
exploitative practices of the transnational companies), environmental protection,
resource management, and ecodevelopment (19). Each has both positive and
negative sides, but ecodevelopment appears to offer the best chance for long-

term sustainability (Colby, 1990). Ecodevelopment attempts to restructure the

relationship between production and the environment.

“It sees most development activity as a form of management of this
relationship; environmental management, economic development,
and socio-ecological development might virtually become semantic
distinctions for the same subject: the integrated convolution of
conscious civilization and nature” (Co/b y, 1990).

The ecodevelopment approach is used in this paper to seek a balance
between the need to produce high quality bananas to generate foreign currency
and the need to protect Costa Rica's environment. The following discussion goes
through the conceptual, diagrammatic, and mathematical systems modeling

Processes.

Figures 13 and 14 in Appendix A are conceptual diagrammatic models of
a banana production system in Costa Rica. Three major components within the
ecosystem are identified: the plantation, the packing plant, and the housing units.
Every input has an influence on the output and eventually on the banana market,

if the system is maintained through a continuous cycle. The output of bananas

68

requires a series of inputs. It is necessary to remember that besides the desired
usable output, the fruit, there are output wastes generated that must be managed

if the banana production system is to be sustainable.

Perhaps the most complex and least-understood component of the
system, outside of the plantation manager, is the agroecosystem itself. To
understand it, it is useful to redefine the boundaries of the system to a smaller
scale (Figure 14 in Appendix A). There are two types of dynamics present in the
system: those that can be controlled by human actions, and those that are
controlled by nature. The dynamics controlled by humans are shown outside the
rectangles and are the focus of this paper. The human and natural factors,
however, are not independent of each other and any human action in the system

has an impact on the natural processes.

Harvesting a crop removes nutrients from the system (CSA, 1993;
Cunningham and Saigo, 1990; Nebel, 1990). High-level production systems, like
bananas, extract large quantities of nutrients and water. Soil nutrients cannot be
replaced by mineralization of the parent soil or natural fertilization via
decomposition at the same rate as they are removed by harvest, and must be
augmented with commercial inputs. Water losses from evapotranspiration are
Significant in the amount of energy required, but the water loss itself is
rePlenished by the large amounts of precipitation occurring yearly in the banana

production region.

69

Monoculture production systems, like bananas, increase the concentration
of food sources for other organisms (i.e., insects, bacteria, and fungi). As a result
of an abundant food supply, such organisms multiply readily and begin to
compete with humans for the harvest. Consequently, high-production systems
require high levels of inputs, not only to produce a product, but also to eliminate

competing organisms (Cunningham and Saigo, 1990; Nebel, 1990; Peakall,
1992).

Fertilizers, herbicides, fungicides, and insecticides are not entirely used by
the plants nor are they retained within the plantation, leaving the system as liquid
leachates, surface runoff, erosion, or gases. These byproducts often have a
dramatic impact on the environment, especially through surface water systems
(Figure 14 in Appendix A). In addition, pests and soil organisms appear to adjust
to biocides by developing a resistance to the chemicals (Peakall, 1992; McKenry,
1991). This generates a positive feedback by creating the need for higher

quantities of inputs and new chemicals to maintain production levels.

Unfortunately, humans do not readily develop resistance to these
chemicals and the adverse effects can be severe, for example, cancers, sterility,
and genetic malformations (Ragsdale and Sister, 1991). Epidemiological data
regarding banana production in Costa Rica have shown more than 10 percent
higher instances of sterility and damage to kidneys, liver, brain, nervous systems,
lungs, heart, eyes, blood, skin, metabolism, and the overall immune system in
people associated with banana production as compared to the general

population (Hilje, Castillo, Thrumpp and Wesseling, 1992). These side effects are

70

hard to account for in economic evaluations and are not internalized as a cost of

banana production systems.

A list of human-controlled inputs has been developed from the
agroecosystem model. The inputs and outputs at the plantation and packing
plant, plus the type of residual and its treatment components, are listed in Table
1 and 2. Considering information gathered from Costa Rican producers and the

management experiences gained at the EARTH College's plantation in Limon,
indices have been developed to quantify the residual materials entering the
ecosystem (Table 3). In some cases, calculations using these indices by area
and by unit of production have resulted in different estimates of the amount of
waste generated. In these cases, the highest number is presented to represent

the largest potential impact.

Table 4 summarizes the results obtained by applying the quantities
reported in Table 3 to the 1995 banana export statistics. Table 4 shows that for
each ton of bananas exported, 0.5 tons of waste is produced that will require

onsite treatment.

In order to grasp the magnitude of this waste problem, it is useful to
contrast banana production waste to the total waste generated in Costa Rica (all
urban sources found in the waste stream combined) on a daily basis. A study
perforrned in 1990 (Government of Costa Rica and GT2, 1990) found that the

total amount of waste generated per day in Costa Rica is 11,764 tons. The total

71

waste generated per day by banana production requiring onsite treatment is 2

626 tons or 22 percent of the total waste generated in the country (Table 4).

72

Table 1 - Inputs vs. residuals for the plantation in a banana production

 

 

 

 

 

system
System Inputs Residual Materials Type of Treatment
Component Residual __
Plantation Agrochemicals Chemicals Non-point Type of Treatment
Fungicides Liquids source Reduction
Nematicides - Leachates Degradable Substitution
Herbicides - Runoff
Fertilizers - Gases
Solids
- Sediments
Agrochemical _ Containers Point source Type of treatment
Containers Solid waste Non- Solid waste
- Paper bags degradable - Reduction
- Cardboard - Triple rinse
boxes - Recycling
- Plastic bags - Incineration
- Plastic jugs - Landfill ash
- Metal drums - Rinse water
Rinse water - Containment
- Neutralization
- Biodegradation
- Oxidation
_ _ Evaporation
Plastics Plastics Point source Type of treatment
Bags Polypropylene - Reduction
Twine twine Collection
Polyethylene - Reuse
bag Recycling
Incineration
Landfill ash

 

 

 

 

 

 

73

Table 2 - Inputs vs. residuals for the packing plant in a banana production

 

 

 

 

 

 

 

 

 

 

system
System Inputs Residual Materials Type of Treatment
Componen Residual
t
Packing Fruit Cardboard boxes Point source (') Exit system and
Plant Cardboard Pallets Degradable 8. must be treated at
Boxes Plastic straps non- market destination.
Pallets Plastic bags degradable
Plastic Straps Spoiled fruit
Fungicide Peels
Plastic Bags
Fruit raceme Substandard bananas Point source Reduction
Degradable Sale in local
market
Value added by-
product
Animal feed
Compost
Biogas
Landfill
Fruit raceme Banana flowers Point source Return to
Degradable plantation
Fruit raceme Raceme's stems Point source Return to
Degradable plantation
Value added by-
product
- Fiber
- Paper
- Humic acid
- Compost
- Landfill
Plastic Bags Plastic bags Point source Plastic - Same as point
non- 3
degradable
Fungicide Agrochemicals Point source Agrochemicals
Coagulants Degradable Reduction
Substitution
Fruit Organic materials Point source Coagulation
- Crowns Degradable Filtration
Latex Return to
plantation
Water Residual water Point source Water
Degradable - Primary treatment
Recycle
Secondary
treatment
Retum to
environment

 

 

 

 

 

 

74

Table 3 - lndices and information needed to calculate waste generation in

banana production

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Description lndices Waste
generated in
tons per
year
1. % Fruit exported 80%
2. % Fruit rejected 20%
3. Weight perbox in KG. 18.14
4. Boxes exported in 1995 112 Million
5. Tons exported = (4*3/1000) 2.03 Million
6. Tons produced = (5/1) 2.53 Million
7. Wasted substandard fruit = (6'2) 508,000
8. Boxes per raceme 1.10
9. Average weight per raceme in KG. 27.21
10. No. racemes produced = (4'8/1) 154 Million
11. No. of racemes per tree 1
12. Average weight of raceme's stern in KG. 2.5 kg.
13. Waste stems (12‘10/1000) 385,000
14. Area under production 52,166
15. Twine per raceme in KG. 0.0322
Ref. McNeel lntemational Corp. (Personal letter
March 10, 1997)
16. Twine residuals = (10'15) 4,960
17. Average weight of plastic bag in KG. 0.038
Ref. McNeel lntemational Corp. 1997

18. Plastic bag waste 5,850
19. KG.IHA.IYear plastic packing material 65.00
20. Plastic packing material = (14'19/1000) 3,390
21. Weight in KG. of crowns and flowers per raceme 0.35
22. Crowns and flowers = (21 '10/1000) 53,900

 

 

 

75

Table 4 - Waste Generated in Banana Production

 

 

 

 

 

 

 

 

 

 

 

 

Treatment Within System’s
Limits

DESCRIPTION TONS OF WASTE TONS OF WASTE PER 100
GENERATED PER TON EXPORTED
YEAR

Non-Degradable Waste

Twine 4,960

Plastic Bags 5,850

Agrochemical Containers C") 782

Total Non-Degradable 1 1 ,592 0.57

Degradable Waste

Crown and Flowers 53,900

Raceme's Stems 385,000

Fruit Rejected 508,000

Sub-Total 946,900 46.65

Total Waste Requiring 958,492 47.22

 

 

 

Generated in Costa Rica (”)

 

 

Bananas Exported 1994 in 2,030,000

Tons

Waste Requiring Treatment 2,626

Within System’s Limits per

Day

Total Waste Per Day 11,764 100

 

(*) McNeeI International Corp. (Personal letter, March 10,1995

(”)National Program for Waste Management (1990)

 

76

2.6 Wastes and Alternatives

The first solution to waste is to reduce its quantity at each processing
point. Waste products generated must be reused until all useful qualities have
been recycled or made into new products. When all recycling strategies have
been exhausted, the remaining waste must be disposed of via incineration and/or

deposited in a properly designed and managed landfill.

Banana wastes may be broken down into five primary categories:
nonpoint source residuals, point source degradable solid waste, point source

liquid waste, point source nondegradable waste, and hazardous waste.

2.6.1 Nonpoint Source Residuals

The nonpoint residuals are the least understood and most difficult to treat.
They are generated through the use of chemical and natural fertilizers,
nematicides, fungicides, and herbicides. The only insecticide widely used is
impregnated in the blue plastic bags used to cover the raceme. The chemicals
most often used include (brand name): Karrax, Ranger, Roundup, Counter,
Dipel, Furadan, Mocap, Rugby, Beniate, Bravo, Dithane, and Mertak. All, if used
in improper concentrations or in violation of manufacture’s recommendations,
can cause acute oral, dermal, or inhalation poisoning of people and animals in
and around the plantation (Hilje, Castillo, Thrupp, and Wesseling, 1992). The

quantity of the residuals depends on the amount and frequency of application,

77

the type of chemical, soil type, precipitation, temperature, wind velocity, location,

and method of application.

Bananas are commonly fertilized with synthesized chemical nutrients.
Fertilization is applied manually. There is considerable waste when chemical
fertilizers are applied heavily and infrequently because the plants can not benefit
from the application before much of it is washed away or dissipated. It is
estimated that the harvest of 40 tons per hectare per year removes 56 kg/ha/year
of nitrogen, 24 kg of phosphate, and 220 kg of potassium (Soto, 1994).
However, the most common quantities applied are: 300-500 kg phosphorus, 400-
700 kg potassium, 80-150 kg magnesium, with the objective of maintaining the
quality and size of fruit for export (Sanchez, 1996). Therefore, the plant does not
utilize a large quantity of applied fertilizer. Part of this material leaches from the
soil and contaminates surface and groundwater. A portion is immobilized in the
soil and a portion is volatilized. Consequently, a better practice is to apply
fertilizers 14 to 22 times during the growth cycle and with a 20 to 50% reduction
in the rate of application, depending on the physical and chemical properties of

the soil and the nutritional state of the plants (crop logging).

Black Sigatoka is a major pest in banana production (Soto, 1994). Black
Sigatoka affects the productivity of the plant and quality of the fruit, and causes
premature ripening. A successful operation depends to a great extent on
proficient pest control. Good cultural practices constitute the first line of defense
against black Sigatoka. A good drainage system, sanitation measures, weed

control, and monitoring of climate and the disease reduce the degree of infection

78
and chemical use. In addition, infected leaves or parts of the leaves are removed
weekly to reduce the inoculate. Dead leaves are also removed to eliminate

insect habitat and protect the fruit.

However, the aggressive nature of this fungus necessitates the frequent
application of fungicides to maintain productivity and quality. Fungicides to
control black Sigatoka are applied with aerial spraying. This method constitutes

a possible source of nonpoint source pollution.

The transnational grower-buyers have their own control systems. Most of
these companies operate their own equipment and have their own airport
facilities. Other transnational companies contract services with Independent

national spraying companies and rent airport facilities.

Most independent producers cannot afford to own their own planes and
operate airport facilities. Independent producers have the option of choosing the
control system and the spraying company. However, the quality of the fruit is
controlled by the transnationals who buy the fruit, and the quality depends to a
great extent on the control of black Sigatoka. To avoid quality problems and to
ensure a good service, many independent producers consider it more convenient
to contract with the transnationals the planning and implementation of control
programs for their plantations. Since the transnational grower-buyers have
adequate technical support and monitoring, this arrangement helps ensure that

only approved products are used for aerial spraying.

79

The frequency of spraying is from 28 to 45 cycles per year and
represents 12 - 16% of the costs of production. The fungicides sprayed are either
systemics or protectants. In recent years, the use of systemic fungicides has
been reduced drastically because there are evidences that the black Sigatoka

has developed resistance to this type of fungicide.

The products are mixed according to'the purpose of the control. The
principal products used are Triazoles, Benimidazoles, Mancozeb, Clorothalonill,
Morfolinas and agricultural oil. Most control programs include 50 -. 75% of the
applications with Mancozeb. The rate of application of the systemic fungicides is
approximately 100 grams of active ingredients for each 20 liters of inert liquid per

hectare (PE 16, 1997).13 The protectant fungicides require a much higher rate.

The government approves and regulates the types of chemicals that may
be used for pest control. However, the “cocktails” (mixtures of chemicals) are
“trade secrets” that are zealously guarded because they may provide a

competitive edge among the companies.

All the fungicides used, with the exception of Calixin, are approved by the
EPA and must meet strict testing guidelines for persistence and biodegradability
(PE 16, 1997). Calixin is not registered with the EPA because it is not used for

agriculture in the United States of America. It is registered in European countries.

 

‘3 The information in section 2.6.1 is a compendium of information supplied by the Panel of
Experts. Panel Expert (PE) 16 is referenced individually because the information was
supplied verbally during the interview and latter confirmed in writing.

80

However, the EPA regulates residual tolerances on imported fruit, requiring that
the chemicals pass a rigorous registration process including tests for toxicity and

biodegradation (PE 16, 1997).

Studies performed by the chemical companies have demonstrated that
approximately 20% of applied fungicides are lost to drift and do not reach the
intended destination. This creates a contamination problem for the areas
bordering the plantation, and the degree of importance depends on the geometric
layout of the plantation, the proximity of rivers and centers of population, and the
flight pattern of the cropduster. Studies conducted by the Universidad Nacional
have demonstrated the presence of limited amounts of fungicides used in the
control of black Sigatoka in waters of canals and rivers around banana

plantations (Castillo, 1997).

Spray drift has become a major concern for the general public in the
United State. As a result, a Spray Drift Task Force was created in 1994 which is
studying mechanism to reduce this problem (Boillot, 1997). These new and

improved methods will eventually reach Costa Rica and alleviate the problem.

Of the 80% of the fungicide that arrives at the intended destination,
approximately 65% is deposited on the leaves. The remaining 15% passes
through the canopy falls to the ground In the case of systemic fungicides, the
plant absorbs the active ingredient in the first 8 hours. In the case of protectants.
the fungicides generally have sticking compound incorporated in the formulated

product so it adheres to the leaves. Sometimes additional gumming agents are

81

incorporated (PE 16, 1997). However, it is highly probable in humid tropical
climates that some of the fungicide is washed off the leaves by rain and falls to
the plantation floor. Depending on weed and residue management practices,
part of the fungicide that falls to the floor will be deposited on dead banana tissue
and vegetative ground covers (weeds). The rest of the material falls on the soil
(PE 16, 1997). The fungicide that falls to the ground can not be considered a
total loss. It serves to neutralize the sources of inoculation that are associated

with living and dead vegetative material on the plantation floor.

According to the registration test presented to EPA, the fungicides used
for black Sigatoka control have a short life and are designed for rapid
biodegradation. They are also fairly insoluble in water and have a high affinity
with clay particles, so they are easily immobilized, reducing the probability of

subsurface migration (PE 16, 1997).

Surface migration of the fungicide in runoff depends on the lapse of time
between application and precipitation event, as well as the intensity and duration
of the precipitation event. The fungicides that wash into the canals probably
precipitate out of solution and bond to the sediments. Because the active
ingredient has a short life and is biodegradable, fungicides that are immobilized
in the sediments probably metabolize quickly (PE 16, 1997). Further study of
metabolites generated from fungicides and their fate is necessary because these

by-products may have a detrimental impact on the environment (Castillo, 1997).

82
To minimize the risks of pollution and so that the fungicide application
fulfills its objective, spraying is done only when favorable climatic conditions
exist. This infers that it cannot be raining, there can be no threat of imminent rain,
and the temperature must be below 28-29 degrees C, the wind velocity below 4

meters per second, and the relative humidity less than 70—80%.

Precautions are taken to avoid spraying rivers or springs. Some
plantations do not respect buffer zones for rivers, streams, and springs. The
majority of plantations do not have buffer zones along roads. New plantations
and some of the older plantations have begun to correct this problem, creating

buffer zones for waterways as well as for roads.

With few exceptions, the banana companies’ facilities for mixing the
product and filling the airplane are located in airports and are equipped with
sedimentation tanks. There are serious deficiencies in the design of most of
these systems. Some airport facilities, especially those operated by transnational
companies, have equipment for recycling residues and containment systems for

spills, which considerably reduces the risk of contamination.

Nematodes constitute a major past in banana (Soto, 1994). Integrated
pest management practices are the first line of defense against nematodes.
Nematicide applications are restricted to the areas having the probability of
damage greater than an economic threshold, by means of a systemic inventory

of nematode populations, percentage of living and dead roots, and the quantity of

83

uprooted plants. Carbamates and organophosphates are applied. The majority

of the chemicals used are highly toxic (Sanchez, 1996).

Carbamates and organophosphates are applied. The majority of the

chemicals used are highly toxic.

Depending on the climate, the age of the plantation and the chemical
product used, nematicides are applied from 2 to 3 times per year. Nematicides
are applied in granular form containing 10-15% active ingredients and 85-90%
inert. The average use of nematicide active ingredient is from 7 to 15 kg per
hectare per year depending on the frequency and dosage applied (PE 16, 1997).
The active ingredient is only released from the granules in humid conditions

(Sanchez, 1996).

Strong rains, combined with bare soils and a good drainage system,
increase the probability that the nematicides will migrate to water sources.
However, the presence of granules outside the area of application is not
necessarily an indication of that migration, because in general the active
ingredient is located on the surface of the granule and is rapidly released.

Therefore, granules found off-site may only contain inert materials.

In general, the floor of the plantation is maintained free of all weeds (bare).
Adequate control of the population, utilizing maximum shade, helps to minimize
the growth of weeds. Weeds are controlled manually and with chemicals.
Chemical control is used more frequently because it is much cheaper than

manual labor. To reduce herbicide applications, the organic residues are

34

deposited as ground cover or mulch. Cycles of herbicide application depend on
quantity and type of weed. Applications are normally made every 4 to 6 weeks.
The most common herbicides are paraquat, diquat, ametryn, glyphosphate, and
ammonium glyfosinate. An average of 0.5 to 1 liter per hectare per cycle is
applied in liquid form sprayed from tanks worn on workers' backs (Sanchez,

1996).

Chemical residuals are transported outside the system by wind and water.
It is very difficult to quantify the volume and concentration of these residuals. The
best available method to determine the extent of the pollution is to sample and
test surface and subsurface waters. However, due to the extensive drainage
system required for banana production and the dilution from high rainfall
amounts, variations in concentration level are often large and can vary from day

to day.

Testing programs to obtain reliable statistics are both complex and
expensive. Currently, there are no long-term databases that can be used to
clearly quantify the extent of the nonpoint residuals problem and develop
appropriate policies for dealing with it in Costa Rica. A solution to this problem
needs to be a high governmental priority. Perhaps a tax that can be passed on
to the international consumer could fund such a program as they, too, will benefit

from more environmentally sound production systems.

85

2.6.2 Point Source Degradable Wastes

The raceme stem is the central shaft of the banana plant to which the
banana fingers are attached. The stem is discarded once the fruit is harvested
and becomes a significant source (volume) of residual organic solids. Disposal
methods for the stern depend on where the waste is generated. Some
plantations detach the fruit from the stem in the field, but the majority remove it at

packing plant.

Before 1993 most plantations removed the stems at the packing plant and
disposal was limited to transporting them to dumps. Traditional these dumps
were open-air sites that were often located along riverbanks. The stems
deteriorate rapidly, and the residues were eventually carried away by
floodwaters. Once in the river, this residue hampered boat transportation. Also,
the deteriorating stems often had a pronounced impact on the water's oxygen
content, limiting or killing aquatic life and adversely affecting the overall aesthetic

conditions for those who lived on the banks of the river.

Most commercial planters have realized that these wastes are valuable
organic fertilizers. At the present time, stem disposal consists of spreading the
discarded stems and leaves across the plantation floor, either whole or chopped.
Chopped stems decompose fairly rapidly, adding water and nutrients to the soil
and providing weed control within the plantation's boundaries. Value-added

alternatives are extracting the fiber to manufacture paper and removing the sap

86

to produce organic fertilizers. EARTH College has been successful in developing

an economically viable process for producing paper from the stems.

From 16 to 25 percent of the bananas produced do not meet export
standards because of handling bruises, scars, stains, crown infections, mutilated
fingers (a cluster of bananas is referred as a hand and the single banana is
called a finger), and unacceptable dimensions. Of these, small percentages are
exported as second-class fruit at a considerable price reduction. Before 1993,
most plantations deposited the remaining bananas in the same open-air dumps
as the stems. Since then, the industry has explored alternative uses for these
damaged bananas. Several industries have started processing these bananas
into puree, juice, chips, and baby food. Some farmers use these bananas as
cattle feed with favorable results. The extraction of starch from bananas is a
feasible alternative that is being researched. All of these alternatives create the
opportunity for more economic growth in Costa Rica and are more

environmentally responsible than dumping.

2.6.3 Point Source Liquid Waste

A large quantity of high-quality water is required during the banana
packing operation. Water is used to cushion the fruit during handling and
transportation from one section of the process to the next, as well as to clean the
fruit and processing facilities. EARTH College's packing plant uses
approximately 12 liters of water per second to process 4000 boxes of bananas

during a 10-hour day (108 liters per box of bananas shipped). When

87

extrapolated to the yearly production of Costa Rica, the total water required for
banana production is 12.1 million cubic meters of water per year. Even though
the production regions have no shortage of water, this is a great deal of

contaminated water to return untreated to the environment.

Bananas have a flower attached at the tip of the fruit at the time of
harvest. When the flower is removed at the packing plant, the fruit oozes a white
milky latex. This latex is also produced from the wound created by removing the
fruit from the fruit stem and sculpturing the crown (point that attaches a cluster of
bananas). If not handled properly, the latex will stain the fruit and make it
unacceptable for the export market. Consequently, it is necessary to wash the
fruit as soon as possible after removing the flower and forming the crown. The
fruit will continue to secrete latex unless a coagulant—alum (aluminum sulfate)—
is added to the wound. Because the wound is also susceptible to fungus, itis
necessary to treat the crown of the banana with Mertak, a fungicide. The
flowers, the crown chips, the latex, the Alum and Mertak pose a risk of

contamination for the surface water downstream of the packing plants.

To address this problem, most packing plants have added water filter
system to remove the solids from the water. Tests on the water following
filtration have found that aluminum has been kept within acceptable limits, and
biological oxygen demand (BOD) was approximately 26 ppm. However, test
performed by the National University of Costa Rica have shown traces of

biocides in the residue waters. In response to these findings, some plants have

88

begun programs to contain, collect, and treat the chemical residues using clay to

immobilize and, in time, biodegrade the active ingredients.

The next step in the process will be to reduce the amount of water used by
reengineering the packing process, to purify the residual water and to recycle it.
Finally, the hope is to eliminate processing water as a point source of pollution.
This may be accomplished using engineered wetlands as a secondary treatment,

but further research is needed.

2.6.4 Point Source Nondegradable Waste

Plastic bags have been used in banana production for 30 years. Workers
put bags over the banana raceme when the fingers start pointing upward. The
bags perform three basic functions: (1) they are a physical and chemical barrier
to insects; (2) they serve as a barrier to contaminants (i.e., fungicides for black
Sigatoka control); and (3) the plastic creates a micro-environment that stimulates
fruit development. Bananas produced without plastic bags have a 10 percent
higher rejection rate from the transnational companies than do those produced in
a bag. This 10 percent is worth $60 million per year to Costa Rican producers,

so the bags will continue to be used.

Plastic is traditionally sold in precut bags, a wasteful practice because
plants are not entirely uniform in size. An alternative is to purchase plastic by the
roll so it can be cut to the precise size needed for each fruit raceme. At EARTH

College this practice has resulted in a 25 percent reduction in the amount of

89

plastic used and yearly savings in material costs of US$15.000 ($49 per hectare).

There is no significant difference in the amount of labor required.

Before 1993, the traditional disposal method was to simply rip the bags off
and throw them on the plantation floor or dump them into the open-air disposal
areas. If all of the plastic bags used in banana production in Costa Rica in 1991
were joined together, they could form a greenhouse large enough to cover the
country's entire banana production region (EARTH, 1991 - Statement made by

Diego Escorriola). Thus, suitable disposal is not a small problem.

The most promising environmental breakthrough for the disposal of plastic
bags is recycling by melting and reforrnulating. A plastic bag recycling plant is
now operating in Costa Rica that processes the bags generated by 70% of the
hectares planted. A significant amount of the remaining 30% is collected, part is

exported and part is stored for future treatment (Recyplast, 1997).

Another significant nonbiodegradable residual of banana production is
plastic twine. The twine is used to anchor the bananas, so that the weight of the
fruit and the wind will not collapse the plant. Traditional harvesting methods
include discarding the twine directly onto the plantation floor. The twine is not
biodegradable and accumulates over time. Eventually, the soil becomes so
contaminated that development of an adequate plant root system is impaired and

mechanical tillage becomes all but impossible.

Research into alternatives has included bamboo supports and

biodegradable twine. However, neither alternative has proved to be feasible for

90

large-scale production. The plastic twine is 40 percent cheaper, less time-
consuming to attach, and easier to use; thus, it will continue to be used. In some
countries, the twine is reused after several strands of discarded twine are braided
together. This is not common in Costa Rica, but may offer the chance for cottage
industries surrounding the plantations where residents could harvest the twins
from the plantation, braid it, and sell it back to the plantation. Outreach
educational programs are needed to make the locals aware of the opportunity

and teach the skills necessary for them to take advantage of it.

Since 1994, a plant that recycles plastic operates in Limén, Costa Rica
that treats approximately 20% of the waste material generated. Most of the
remaining twine residue is collected and stored for future solutions. Among the
most promising solutions is the use of these residuals as fuel for cement
production. The lndustria Nacional de Cemento (INCSA), in Cartago, Costa
Rica, has tested plastic incineration with respect to the air pollution control
equipment installed at this factory with promising results. INCSA offers to pay
seven cents of a US dollar per kilogram of twine cut into 3-centimeter strips and
relatively free of contaminants. Several companies are looking into the logistics
necessary and the economical feasibility of this alternative. These are promising
trends for Costa Rica's environment and should also produce additional

revenues.

91

2.6.5 Hazardous Waste - Agrochemical Containers

It is difficult to project the magnitude of the container problem on a
national scale, because of the large variation in the size and type of containers
used. An estimate by McNeel International Corp. (Personal letter March 10,
1997) reveals the following annual generation of residual packaging for 1996 in
the banana industry: one hundred and four tons of recyclable HDPE
agrochemical packaging, five-hundred and ten tons of steel packaging and one-

hundred and sixty eight tons of paper packaging.

The primary environmental risks associated with agrochemical containers
are handling them (spilling) and storing them (leakage). The solution is risk
prevention through appropriate handling procedures, containment structures, and
spill control. The chemical manufactures have ample recommendations and the
government of Costa Rica has regulations for the design and operation of these
facilities. The problem is in the implementation by the producers. Since 1993,
most of the large plantations, especially those owned by the transnational
companies have started building adequate facilities and have appropriate
procedures for handling agrochemicals in their installations. However, due to the
high cost of these improvements and the low market prices for bananas, a

considerable number of plantations still have inadequate facilities.

92

The airports from where the cropdusters operate constitute a major area
of environmental risk. A recent visit with EARTH students (July 1997) to the
Batan, Limén airport revealed the efforts made by Dole and del Monte to ensure
safe storage, appropriate and safe handling of the chemicals by the operators,
containment and control of residuals and spills, recycling of residual liquids, and
handling of used containers. During this stay, it was possible to witness that the
chemical companies are picking up the used containers and removing them from
the working site for treatment or storage at their installations. Nonetheless, it
also revealed the lackof prevention mechanism by other cropdusting operations.
In this occasion a plane (not part of Dole or del Monte's operations) had a
mechanical failure and the load was spilled over the runway. The chemical was
rinsed off the runway into a drainage ditch with no efforts to contain the spill or
treat it. The obvious presence of agrochemicals in the drainage ditches around
this airport showed that this incident was not an exception caused by an
unfortunate accident. It also evidenced the absence of government inspectors

and control personnel.

After risk prevention, the next best procedure is recycle the used
containers. The best procedure for recycling is to send the entire container back
to the company to be filled and reused, much like Coca-Cola bottles. This
system is fairly widespread in the United States and it is currently being
introduced in Costa Rica for fungicide and nematicide containers. At the present

time most banana producers have included in their agrochemical purchasing

93

agreements a clause that obligates the distributor for the collection and treatment

of the empty containers.

The government of Costa Rica currently will not issue permits to for the
incineration of hazardous materials, including plastic containers. Therefore, most
empty non-recyclable pesticide containers are kept at storage facilities. They
represent a real and present danger to Costa Rica's environment and citizens.
Some companies are reducing this risk by triple rinsing, compacting and storing

for future treatment.

Notwithstanding extensive education campaigns, often people, both rural
and urban, use the plastic and metal containers to hold water and grain that are
later used for human consumption. Again, there is a need for government or
university outreach programs to educate people about the risks and help them
find safer alternatives. Furthermore, it is necessary to enforce the laws and force
all the chemical companies into assuming direct responsibility for disposing of

their used containers.

2.7 The Challenge

Costa Rica has passed a number of laws in an attempt to protect its
citizens and environment from human-introduced environmental hazards.
Enforcement of these laws in Costa Rica, as in most of the world, remains a
.major problem. Only recently have some banana producers recognized the
environmental impacts of these combined problems. Their interest is primarily

based on fears of how lntemational consumers and markets will react to

94

documented or inferred cases of environmental and/or human poisonings

(EARTH, 1991).

In order to implement rapid change, it may be most important to determine
what it will take to influence international consumer preferences to buy a banana
that may not have a perfect skin color or size, but can be produced without
further damaging Costa Rica's environment. Producers will follow consumer
demands faster than laws can be passed or environmentalists and politicians can
articulate their fears and concemsl Until this happens, though, we must
continue to seek more and better practices for producing bananas to meet the

worlds needs.

Conclusion

This chapter systematically depicts the environmental impacts associated
with banana production and some of the historical, political, and economic
reasons why these conditions exist. The challenge for the fifth paradigm
(ecodevelopment) in the evolution of banana production is to reconcile
. production methods and economic needs with the conservation of Costa Rica's
environment. This will require long-term commitment from Costa Rican
producers, transnational producers, the government of Costa Rica, the research

community, and the consumers of Costa Rican bananas.

Promising signs of improvement and changes in the attitudes and actions
of some producers are apparent in the emplacement of plastic recycling plants,

introduction of recyclable fungicide and nematicide containers, mulching of

95

organic wastes, and turning non-biodegradable wastes into new commercial
products. These changes may stem from fear of a possible consumer boycott,
the recognition that traditional technologies are self-destructive, or the
development of an environmental ethical code of conduct. But regardless of the
reason, since 1991 the environment is a common theme of discussion among
banana producers. At the same time, it is also evident that producers and the
research community do not yet fully comprehend the complex interactions
between humans and their environment, and that there are many problems that

have no solutions at the present time.

History shows that changes in paradigms (e.g., from frontier economics to
ecodevelopment) are slow to occur and that the period of change is filled with
conflict between immediate needs for economic gratification and the perceived

needs of the next generation. The questions that cannot be answered yet are:

How fast will the environment deteriorate?
What will be the impact on Costa Rica's economy and citizens?
Will producers be willing to change even if it means lower profit margins?

\Mll world consumers be willing to share in the cost of growing a different
type of banana?

If the stakeholders who depend on banana production maintain their
traditional ways and rely only on new technology to overcome production
problems, the future is not bright. Such practices, when combined with the

economic theory that allows for the substitution of new resources to meet

96

consumer needs, may also allow a transnational company to simply move to

another country and leave Costa Rica holding the proverbial (plastic) bag!

Chapter 3
METHODS

3.1 Introduction

The first chapter of this dissertation defined a vision, a blue print to guide
those responsible for agro-production systems to see the world as a complex
system that requires responsible stewardship. H. T. Odum defined stewardship
as a management strategy of the planet that pursues a cooperative role with the
planetary support systems (in Mitsch and Jorgensen, 1989). Accordingly,
Chapter I advances the philosophy of sustainability, and dissects it into three
basic components -- environmental, social and economic sustainability. It also
promotes the analysis of systems through the use of systems theory, defining it
as the study of complexity. Chapter I introduces a world-class banana
production system as a specific case to test the validity and appropriateness of

the systems approach.

The second chapter recognizes the present state of affairs of world-class
banana production. It uses pertinent literature to identify the problem, its size, its
causes, and possible solutions. It introduces a model advanced by Hernandez
and Witter (1996), that outlines the production system. The Hernandez and
Witter model (H & W model - Figures 13 and 14) is a schematic drawing that
portrays, in a palpable manner, the limits of the system under consideration and

the different components of the system. It defines inputs and outputs, and it

97

98

evinces the interactions among components of the system. It is an attempt to
bring order to the apparent chaos of complexity, interdependence, and

interactions. However, it lacks one fundamental element. It does

not render precise intensities for each of the interactions. The definition of

intensities is the next task of this dissertation.

As defined in Chapter I of this dissertation, an agricultural production
system is an open system. Open systems are complex and interdependent on
other adjacent systems. The complexity of open systems require a systems

approach, which was defined as a

“we y of thinking about the set of interconnected parts that makes
up the whole in sucha away as to bring out the properties of the
whole rather than those of the parts (Peet, 1992, p. 21 )."

Thus, the problems that arise from agricultural production cannot be studied in

isolation.

"They cannot be factored out of the whole, each explained on its
own and the set of explanations thrown together to explain the
whole (Saaty and Keams, 1991. p. 3). "

Furthermore, open systems are not static because the environment that

surrounds them is continually in flux (Odum — personal communication, 1995).

Under these conditions, the definition of intensities is a difficult task
because it involves measuring interactions between the production system, and
the environment, the society and the economy. Each of these components has
different instruments and scales of measurement. Furthermore, it is important to

acknowledge that there is meaningful information that is not derived from the

99

traditional scientific method, and that can not be measure with physical
instruments. This is especially true when dealing with human perceptions,
values and feelings. If the objective is to influence decision makers to act
according to the blueprint which was defined in Chapter I, then these perceived
values are an important catalyst of choice. As stated by Saaty and Keams

(1991,p.7)

"addressing these problems requires an approach which enables
us to use a variety of relevant information including both 'hard’ data,
such as quantifiable information, and 'soft' data derived from
intuition, experience, values, judgments and imaginative
guesswork".

This dissertation proposes a systematic method to assign intensities and
derive performance indicators based on systems theory. The method is
appropriate for studying problems and choosing the best solution from an array
of alternatives. In essence, this is a decision-making method that has six steps

leading to one objective. The steps are the following:

0 define a typical conventional production method,
0 identify the problems and impacts of this method,
0 identify feasible solutions,

0 establish criteria and standards,

a assign relative importance to the criteria, and

- rate each alternative solution to derive performance indicators according to
the degree of fitness with the chosen criteria and standards.

100

The objective is to choose the alternative solution with the highest

performance indicators. Because of complexity, the method considers

"multiple criteria or objectives, many of which are intangible, or
subject to uncertainty and risk, and vary in purpose and function
(Expert Choice, Inc. 1995, p. 181)."

This chapter describes the method that was used to dissect the H & W model,
define production methods, identify cause and effect relationships, define and
prioritize criteria, and assign value to the performance of production techniques
in minimizing negative impacts and maximizing benefits on the environment
(Environmental Performance Indicator - ENPI), the society (Social Performance
Indicator - SOPI) and the economy (ECPI). The weighted combination of the
ENPI, SOPI and the ECPI results in the Sustainability Performance Indicator
(SPI).

The method used a multicriteria decision making tool based on the
Analytic Hierarchy Process (AHP) developed by Dr. Thomas L. Saaty at the
Wharton School of the University of Pennsylvania. A decision support software
package designed by Dr. Ernest H. Fonnan - ECPro for Windows by Expert
Choice, Inc.- was identified that organized this process, prepared the
questionnaires, did the relevant calculations, checked the consistency of the

system, and rendered the reports.

A synopsis description of the proposed method follows: the foundation of
the method was the H & W model (Figures 13 and 14 in Appendix A). The most
significant production activities (predictor or independent variables) were

identified, listed and defined from the literature, field visits, and the authors

101

practical experience. The list of activities was consulted with a Panel of Experts
(See Appendix B, Table 36 - Independent Variables) and modified accordingly.
Cause and effect diagrams were assembled (See Appendix A, Figures 15
through 36) and the H & W model was expanded (See Appendix A, Figures 37
through 39). These diagrams were consulted and modified according to the
individualized opinion of a Panel of Experts (PE). The criterion (or dependent)
variables were identified from the cause and effect diagrams, and a hierarchy
structure (See Chapter 4, Figures 7 through 10), with levels of relative

importance among the criteria, was assembled.

The next step was to assign relative weighted importance to each criteria
at the different levels of the hierarchy structure. When available, 'hard' data (is.
cost data) was introduced to define the comparative weights among criteria. In
the absence of 'hard' data, comparative value data was gathered using a verbal
argumentative approach through one-on-one personal interview of a Panel of
Experts (PE) in banana production. Table 14 in describes the members of the

PE and their contribution to this dissertation.

The Delphi method“ was used for interviewing. Experts assessed relative

weights using the questionnaire prepared using the ECPro software and the

 

“ The Delphi method is a well known process that gathers information and seek consensus

from a panel of experts while keeping their names anonymous and confidential. Each
member of the panel responds to a previously prepared questionnaire and the answers
are reviewed by the rest of‘the panel allowing for adjustment and consensus (Saaty,
1996).

102

intensity scales defined by the AHP method (Saaty and Vargas, 1994, p. 6; Saaty

and Kearns, 1991, p. 27).

The predictor or independent variables were divided into two categories -
Conventional Production Practices (CPP) and Best Available Practices (BAP).
Expert opinion evidenced the existence of more than one alternative Suggested
Production Practice (SPP) for some tasks. However, the SPP are not
necessarily the BAP. It is necessary to rate these practices and judge if they are
trully better and if they are available at the present time. For this reason, several
SPP treatments were analyzed and differentiated by a numerical subscript. The
suggested alternative methods of production, or the SPP, were rated for each of
the bottom-line criteria of the hierarchy structure using the AHP value scales

(See Tables 7 through 10 in Section 3.4.2). If 'hard' data was available, this data

was transformed and adjusted to fit into the AHP value scale.

Table 5 - Panel of Experts

 

 

 

 

 

 

 

 

 

 

 

 

Expert N# Description Contribution

1 Independent producer Evaluator

2 Educator and researcher Environmental

Advisor

3 Educator Evaluator

4 Transnational employee Evaluator

5 Independent financial consultant Evaluator

6 Transnational employee Social Advisor

7 Environmental labeling group Evaluators

8 Independent production consultant Evaluator

9 Researcher Evaluator

10 Independent producer of organic bananas with Environmental
direct marketing Advisor

 

 

 

 

103

 

 

 

 

 

 

 

 

 

 

11 Farm manager for an independent producer Evaluator

12 Researcher Evaluator

13 Private consultant -— Environmentalist Evaluator

14 Educator and researcher in anthropology Social Advisor

15 Educator, researcher and independent producer Evaluator

16 Group of transnational employees Production Advisers

 

In order to compare the CPP and SPP to a standard for sustainable
practices, the researcher assumed that a sustainable system tolerates a
moderate amount of negative impact and that a Sustainable Production Practice

(SPP) corresponds to a moderate (0.60) SPI.

The data was introduced into the ECPro software. This program
organized the data in square reciprocal matrixes (See Figure 5 in Section 3.4.1 -
Pairwise Comparison Matrix). Mathematical calculations were processed by the
ECPro software using eigenvectors and eigenvalues as described by Saaty and
Keams (1991, pp. 22-38). Consistency was checked by calculating a
consistency ratio (CR) (Saaty and Kearns, 1991, p. 33). The Delphi Method
permits the researcher to discuss results with the experts with the purpose of

reviewing assessments to improve consistency and seek consensus.

The end product was an aggregated Sustainability Performance Indicator
(SPI) which is composed of an aggregated Environmental Performance Indicator
(ENPI), Social Performance Indicator (SOPI) and Economic Performance
Indicator (ECPI) for the total analysis and for each production task (Predictor

Variable). The derived intensities introduced into the AHP, a product of the

104

opinions stated by the PE, correspond to the intensities for each of the

interactions described in the modified H & W model.

The scale used to derive the indices was a ratio scale with a range from
zero to one. The data was assumed to be normally distributed and a parametric
statistical method was used to test the significance of the results. The author
recognizes that this was a gross assumption. However, Earl Babble (1983, pp.

427-428) has the following comments on tests of significance:

"Test of statistical significance, strictly speaking, make assumptions
about data and methods that are almost never satisfied completely
by real social research. Despite this, the tests can serve a very
useful function in the analysis and interpretation of data. . .I
encourage you to use any statistical technique - any measure of
association or any test of significance - on any set of data if it will
help you understand your data. . . You should be wary of interpreting
the 'significance' of the test results too precisely,
however. . .Anything goes, if it leads ultimately to the understanding
of data and the social world under study. "

The results were arranged in a two-way classification by treatments and
by replication. The three treatments considered were CPP, SPP and SPP (See
Table 6 - Aggregated Two-way). The ten replications correspond to the opinion
of the ten experts. The hypothesis stated that the results were samples of the
same population and that variance was a result of random error. An analysis of
variance of a two-way classification system was used to test the hypothesis with
an F-test. In case the hypothesis was rejected, an orthogonal variance analysis
was conducted to identify which sample had variations beyond expected random

error (Snedecor and Cochran, 1973, p.299-311).

105

Table 6 - Aggregated Two-way Classification

= reatments (k)

 

1 1

This chapter is divided into seven sections, the first being this introduction.
The second section re-states the problem, identifies the critical questions raised
by the problem statement, states the assumptions made, and sets the tasks for
answering. the questions. The following section describes the panel of experts
that took part in the study. The fourth section describes the instrument and
measurements that were used in the study and the fifth section enumerates each
of the steps that were taken. The sixth section is dedicated to outlining the
statistical techniques that were used to analyze the data and test the hypothesis.
This chapter concludes by stating the limitations of the study. The results of the

application of the method are presented in the next chapter.

3.2 Problem Setting

3.2.1 Restatement of the Problem

The facts presented in Chapter 1 and 2 document the following

statements:

9 All agricultural production practices introduce a disturbance in the ecosystem
and have a resulting impact on the environment, society, and the economy.
A production practice performs in a sustainable manner when the negative
impact on society and the environment are minimized, and the benefits to
society and the economy are maximized.

106

o The environment has the resiliency to assimilate a moderate amount of
disturbance. Conventional production practices (CPP) for growing bananas
introduce a massive disturbance in the ecosystem and their impact may be
beyond the limits of environment to absorb the insult. Therefore, banana
CPP may not be performing in environmentally sustainable manner.

9 Banana CPP brings many benefits to the workers, neighboring communities
and the nation, but they also may be directly or indirectly responsible for part
of the serious social problems evidenced in the banana production region.
Furthermore, banana exports require a large national resource investment
that generates a substantial economic benefit to a few transnational firms,
national firms, and individuals. Conventional development paradigms rely on
the trickle down effect for benefits to reach all the stakeholders. The present
structure of ownership and marketing of bananas may provoke a deficient
distribution of benefits. Therefore, banana CPP may not be performing in a
socially sustainable way.

0 The present banana market conditions may be generating insufficient
economic benefits to Costa Rica that may not compensate for the negative
impact on the environment and society. Therefore, CPP may not be
performing in an economically sustainable pattern.

9 Consequently, the banana CPP used in Costa Rica may not have an
acceptable sustainable performance level and it may be necessary to
introduce best available practices (BAP) to improve the net benefit.

9 BAP may also have negative impact on the environment, the society and the
economy. Therefore, BAP may not achieve an acceptable level of
sustainable performance.

0 If both CPP and BAP are not performing to a desired level of sustainability,
then it may be advisable to abandon banana production. However, the
negative impact on the environment, society and the economy of Costa Rica
of abandoning banana production may be catastrophic. Alternatives to
banana production may perform in a less sustainable manner. Therefore, it
is critical to collect information, appraise it and organize it, using a systematic
method, to identify areas that require further research and development, and
to aid decision makers in taking sustainable actions.

3.2.2 Research Questions

An analysis of the problem statement presented in the previous section,
indicates that, the proposed method muSt answer the following six critical

questions:

if

107

1. What are the important criteria that must be met in order to perform in a
sustainable manner?

2. What are the CPP?

3. According to the PE and in reference to a set of criteria and standards, are
CPP performing in an environmentally, socially and economically sustainable
manner?

4. According to the PE, are there SPPs other than the CPP or are the CPP the
best available practices known?

5. If the CPP are replaced by SPP, will they have a better environmental, social
and/or economically sustainable performance?

6. If the answer to question 2 and 4 are negative, what areas should be further
researched and developed to improve sustainable performance?

3.2.3 Assumptions

In order to answer the questions stated before, it was necessary to make

the following premises:

1. A great deal of the information required to make a decision is not "hard"
data, but based on opinion and perceptions. Expert opinion is a valid
method of collecting data as long as the instrument used is valid and
systematically applied. The AHP is a well documented and validated
instrument for collecting data based on systems theory (Veroutis and
Aelion, 1996; Saaty, 1996; Saaty and Vargas, 1994; Saaty and Keams,
1991; and Saaty and Vargas .1991).

2. Consistency, in the opinion of experts, is an important element, but not
irreconcilable in accomplishing the objectives of this research.

"Perfect consistency in measurement even with the finest
instruments is difficult to attain in practice... (Saaty and Keams,
1991, p. 33). " "A central point in our approach is that people are
often inconsistent, but priorities must be assigned and things done
despite inconsistency (Saaty, 1996, p. 9). " Therefore, "...what we
need is a way of evaluating how bad it (consistency) is for a
particular problem (Saaty and Keams, 1991, p. 33) ",

and decide whether the resulting level of inconsistency is tolerable.
Therefore, there is a tolerable level of inconsistency acceptable to reach a
conclusion. According to Saaty (1996) a 10% consistency is acceptable.

3.2

108

Values between 10 and 20% should be verified and values over 20% must
be rejected.

3. The world-class quality standards cannot be changed in the short term.
Therefore, it is sensible for this research to hold this variable constant.

4. The oversupply of bananas in the market makes the banana market a
buyers’ market. Therefore, the market price of bananas is beyond the
producer’s control. On the basis of marketing experiences and research,
producers must assume that consumers are not willing to pay more for
world-class bananas that are produced in a sustainable manner.
Therefore, the producers that adopt BAP must minimize cost and assume
any additional cost that may arise.

5. Established on experience, producers must assume that a large sector of
consumers are willing to choose world-class bananas that are produced in
a sustainable manner over ones that are not if there is no difference in
price. Therefore, there exists a market share advantage for producers
that make the necessary changes to improve their production system.

6. There are trustworthy labeling mechanisms that allow the producer to
sustain claims about the method of production used. Therefore, the
consumers can trust the labels to make their choice.

7. Any and all systems of production cause a disturbance in the environment
and society. Production practices that cause no negative impact are
impossible. There are levels of sustainable performance which range
from a very low level to a very high level of sustainable performance.
Therefore, it is reasonable to assume that sustainable production
practices consist of a balance between positive and negative impact to the
environment, society and the economy, and that sustainable systems
tolerate a moderate amount of negative impacts.

8. Banana plantations in Costa Rica, by law and by market attrition, are
located in areas that posses the optimal ecological conditions for their

growth. Therefore, climatic and edaphic variables are assumed to be
constant.

3.2.4 Tasks

The abridged description of the tasks performed to seek answers to the

questions presented in section 3.2.2 are as follows:

10.

11.

109

Select a panel of experts (PE) and interview individually each of the
experts. Consider the information from each individual expert as a
repetition of the experiment.

Divide the H & W model into three separate models - environmental,
social and economic models.

Transform the information presented in each of these three models into
environmental, social and economic cause and effect diagrams, and
validate this information with the PE.

Convert the information in cause and effect diagrams to three separate
(environmental, social and economical) hierarchial structures of goals,
criteria, sub-criteria, and standards. Work with each hierarchy structures
independently to derive an ENPI, SOPI and ECPI. Load this information
into the ECPro software to create the horizontal elements (criterion
variables) of the rating matrix.

Determine, with the help of the PE, the relative weight of the ENPI, SOPI
and ECPI to determine the SPI.

Define, with the help of the experts, the CPP and SPP for each production
task. Load this information in the ECPro software to create the vertical
elements (predictor variables) of the rating matrix.

Determine, through expert opinion and hard data, the relative weights of
the environmental and social hierarchy structure and load the information
into the ECPro software. Use the pairwise comparison module or the data
module to register expert opinion into the software depending on which
system is more comfortable for the expert. The software program
transfers and assigns these values to each of the horizontal elements of
the rating matrix. Since the relative weights for the environmental and
social impact vary depending on the impact of each individual production
task, create a separate program for each task.

Determine the relative weights of the economic hierarchy structure by
identifying an economically sustainable farm and unloading hard data into
the ECPro software. Identify this farm with the help of the PE.

Verify consistency and validate results with the each of the members of
the PE.

Assess the CPP and SPP through individual expert’s opinion and load
separately the results into the rating matrix of the ECPro software.

Run the ECPro software and determine the indices for each of the experts
opinion for each task separately and calculate individual ENPI and SOPI.
Combine the individual ENPls and SOPls into single values by assigning

12

14

110

relative weights to each of the tasks and calculating the average weighted
value.

12. Classify the results in a two way matrix - - treatment versus repetition .
Consider each expert opinion as a repetition of the experiment. Place the
treatments (CPP, SPP, and SPP) in the columns and the repetitions in the
rows, and test the hypothesis statistically using SPSS software.

13. Set the SPP rating at a value of 0.60.

14. Test the hypothesis using ANOVA. If rejected, test the hypothesis with an
orthogonal comparison.

15. Recommend changes in production practices and areas for further
research and development.

3.3 Participants

The validity of data derived from expert opinion depends on the use of
diversity of disciplines and plurality of convictions. Nonetheless, the arbiters
must have similar objectives and have a positive constructive attitude towards
improving the sustainable performance of the banana production process.
Furthermore, judges must be well-informed generalists who have sufficient
expertise to understand, analyze, and assess the impact of the different tasks of
the production process on the environment, the society, and the economy. As
discussed in section 3.2.3, the assessments by the experts must meet a minimal
acceptable degree of consistency. For these reasons, the selection of the PE

was purposive and non-random.

Due to the complexity of the problem, it was necessary to include
specialists in the PE who did not participate in the predictor variable assessment
process. This specialized group of experts contributed to their areas of

expertise, such as the definition of social and economic criteria and their

111

weighting. Only the experts that were judged competent to voice an opinion on
the three areas of assessment were asked to rate the independent variables.
From the statistical perspective, the heterogeneity of the PE improves the non-

dependency of the treatments.

The experts were chosen based on their recognition as academic
researchers and educators, authors of related books and articles, prominent
independent producers, transnational staff working in the conservation of the
environmental, production practice innovator, members of trade organizations,
regulatory government agents, and members of certification bodies. The names
were selected from a short list that was drawn with the help of EARTH's faculty

and staff.

The experts chosen were offered confidentiality to assure them that their
opinions would be kept as personal and not as official positions of their
employers. A letter of informed consent was signed by the each of the experts
and the researcher. A copy of this letter remained with the expert and the
originals were deposited in a sealed envelope with the comptroller of EARTH
College for safekeeping. A copy of a sample letter was included in Appendix B

and is labeled Figure 34 — Agreement to Participate.

Since this is, in essence, a qualitative dissertation and uses intensive
interviews, the number of experts that form the panel relies more on what is
deemed reasonable and convenient to develop a convincing argument, and less

on statistical testing arguments (Rudestam and Newton, 1992). The minimum

numbel
were c
predictt

Assign:

l
majority
judgme
appropr
had to l
was inte
DD. 115-
Consister

giving the

Altl
geometric
mernber l

repeilflOns

To n

Additionally,

112

number of panel members was judged to be ten. However, fourteen experts
were chosen and were asked to contribute in developing the criterion and
predictor variables. Ten experts were asked to participate in the second phase -

Assignment of Values and Ratings.

Confidence in the results depends on extracting results in line with the
majority preference. Saaty (1996, p. 66) recommends reaching consensus in
judgment by group discussion. Focused interviews and group sessions were not
appropriate since panel members were assured confidentiality and their opinions
had to be kept anonymous. The next best method was chosen. Each expert
was interviewed separately using the Delphi Method (Saaty and Keams, 1991,
pp. 115-118, Saaty, 1996, pp. 66-70). To improve confidence, validity, and
consistency, the resulting data was discussed with each of the panel members

giving them the opportunity to comment and review their contribution.

Although the ECPro software has the capability of calculating and loading
geometric averages for multiple opinions, the data obtained from each panel
member was loaded individually and the program was run obtaining ten

repetitions of the experiment for two treatments - CPP and SPP.

To maintain confidentiality, the names of the panel members were not
revealed to the other members of the panel or made public in this document.
Additionally, identification numbers were assigned to each of the panel members

and data was stored under their ID number.

113

3.4 Instrumentation and Measures

3.4.1 Analytic Hierarchy Process and ECPro

As stated previously, the necessary task to complete the H & W model
was to calculate the intensity of the different interactions. Once the intensities
were determined, then it was possible to calculate the sustainable performance
level of each production process on the environment, the society and the
economy. The instrument used to accomplish this task was the AHP, and ECPro
was the software used to perform the mathematical calculations and organize the

results.

The theory behind the AHP was developed in 1971 as a contingency
planning tool for the Department of Defense. Since then, it has been used
extensively for many applications such as architectural design, designing
mousetraps, selection of bridges, determining market attractiveness of
developing countries, development of 'new product pricing strategy, etc. The
researcher became aware of this process by Veroutis and Aelion's (1996) use of
this tool for total environmental quality management. The researcher was able to

contact Veroutis by phone, and he recommended the software.

The researcher examined five books (Saaty, 1996; Saaty and Vargas,
1994; Saaty and Vargas, 1991; Saaty and Keams, 1991; and Expert Choice,
1995) specifically related to AHP, and there was no reference to the use of this
process for assessing sustainability or calibrating a agro-production model. The

innovative use of this method advances a validated procedure that can be easily

114

replicated for modeling other agricultural production processes and testing their

sustainable performance.

The AHP is based on the theory of operation of the human mind. The
thought process of an individual involves the identification of complex problems
and their decomposition. Then, relationships are identified among decomposed
elements and these relationships are prioritized into a hierarchy structure.
Finally, all the information is synthesized and a decision is made (Saaty and
Keams, 1991, p.19-22). AHP uses matrix analysis grounded on sound
mathematical theory. Expert Choice, Inc. has developed a software called
ECPro that facilitates the use of AHP. ECPro guides decision making through

seven basic steps (Expert Choice, 1996, p. 184):

1. Defining problem and research
Identifying feasible alternative solutions

Structuring a model

2

3

4. Making judgments

5 Synthesizing

6 Examining and verifying the decision
7 Documenting the decision

The purpose of each step is to organize knowledge and data in a logical

process. The first step requires the execution of the following tasks:

1. Re-state the problem and the questions that need to be answered.
2. Confirm the objective and the criteria for fulfilling it.

3. Determine the standards for rating performance of the alternatives.

115

These steps are basically accomplished in Chapter I.

The next step is to identify as many feasible alternative solutions as

possible through

"brainstorming, wide discussion, research into what is available,
and solicitation of ideas and views from others (Expert Choice,
1995, p. 186).”

Chapter 2 of this dissertation searches the literature for alternatives, and
advance some recommendations by Hernandez and V\fitter (1996). Other

alternatives, ideas and views were solicited by interviewing the panel of experts.

The third step organizes all the available information into a logical
hierarchy by identifying the components of the problem, grouping them in
clusters according to the relationships shown in the model, and prioritizing these
clusters. The software manual identifies two approaches for this structuring
process - top-down and bottom-up. The top-down approach was used for this
research because the information for establishing the hierarchy structure was

provided through the H & W model and the cause and effect diagrams.

The top-down approach required the definition of an objective (sustainable
performance of production processes) and placed the objective at the top of the
hierarchy. The next layers in the structure were occupied by the criteria and sub-
criteria necessary to meet the objective. The criterion variables were divided into
three categories: environmental, social and economic. Each of these categories
was further subdivided into specific indicators that were linked to the causes

shown in the Cause and Effect Diagrams (Appendix A, Figures 15 through 36).

116

The following layers were occupied by the performance rating standards. The
assignment of the levels of performance were done through expert opinion and

the rating module of the ECPro software.

The production tasks (predictor variables) were chosen using Life Cycle
Analysis criteria but the processes were truncated at the plantation limits. The
resulting list of independent variables is presented in Appendix B, Table 36.
Production processes begin with planting and population control and end with
packing. Labor management processes were included separately and were
listed in the same table beginning with labor contracts and ending with collective
bargaining practices. Up-stream and down-stream processes were not included

in the scope of this study.

The end product was a decision tree composed of parents, siblings,
children, and grandchildren. Figures 7,8, 9, and 10 in found in Chapter four are

the resulting hierarchy diagrams.

Expert Choice recommends a group process to do the structuring. Since
confidentiality was a limiting factor, the group process was not appropriate. In
this case, the Delphi method was used to enhance and validate the results with

each member of the PE independently.

Once the hierarchy structure was completed, the fourth step was to
compare elements of the structure at equal levels and to determine their
importance or intensity with respect to their parent element. For this purpose,

square and reciprocal comparative matrices were arranged by the software

117

where the elements of the columns were identical to the elements of the rows.

The comparison matrix is presented in Figure 5.

When 'hard' data was available, intensities were calculated directly using

the data module of the ECPro software.

In the absence of 'hard' data,

comparative judgments were made by the experts using Table 7 - Scale of

Relative Importance" which was validated in other AHP applications (Saaty,

1996, p. 54). However, the majority of the experts chose to enter their judgment

directly using the data module of the ECPro software by assigning percentages

to each criteria, then translating the results into pairwise comparisons and

comparing validity and consistency. The software program has the build-in

capacity to assist in performing this operation.

 

 

 

 

 

 

 

 

 

 

I=fiow C1 C2 C3 Ch

j=Cqumn j=1 j=2 j=3 j=n

C1 8., = 311 a“ = 312 a“ = 813 a“ = a".

I: 1 = WC1/ WC1 = W01, WCZ = WC1/ WC; = WC1/ WC“
= 1

C, a“ = an a, = an a., = an a - a2n

i= 2 = WCzl WC1 = WC2/ WC; = W02! WC; = WCzl WCn
321= 1/ 312 = 1

Ca aij = 331 at] = 832 a - 333 a: aan

i= 3 = W03! WC1 = WC3/ WC: = WC3/ WC; = WC“
331= 1/ 313 332:1/323 =

C" ag=am au=an2 a=an3 au=am

i= n = WC2/ WC, = WC,J WC; = WC"! W03 = WC"! WC“
am=1la1n a,,2=1la;1n a,,;,-1Ia3n =1

 

Figure 5 - Pairwise Comparison Matrix

The researcher had originally planned to conduct the

directly log the answers into a laptop computer.

interviews and

Using the ECPro built-in

 

118

capability, questionnaires can be displayed in the computer screen to guide the
experts in the evaluation process. However, due to the complexity and the
extent of the resulting hierarchical structure, the time requirements to conduct the
interviews, approximately eight hours, went beyond the limits of endurance of the
experts. The majority of the experts chose to fill the questionnaires on their own
and submit them to the interviewer later. Consistency was calculated and the
expert was allowed to change his/her judgment to correct values in order to
comply with allowable inconsistency ratios. By using the data module as a
starting place and then translating to pairwise comparisons, consistency
problems were almost entirely eliminated. A visual check for validity was made

possible through a bar graph display available by using the ECPro software.

Saaty, in his justification of the judgment scale, quotes psychological

experiments performed by Miller (1956) that show that

"individuals cannot simultaneously compare more than seven
objects (plus or minus two) without being confused (Saaty and
Vargas, 1991, p. 22)."

Using the same criteria, comparative matrices were limited to less than
five elements for pairwise comparisons. This was accomplished by clustering
elements under similar criteria and subdividing into sub-criteria. An exception
was registered in. the economic matrix where it was necessary to include eight

elements. However, in this case, the data was “hard data” which requires no

expert judgment.

119
The fifth step was to load each of the CPP and SPP predictor variables
into the Rating Spreadsheet in the ECPro software. Performance ratings were
assigned by the experts using the ECPro rating module scales (decimal numbers
with a range of zero to one). SPP with low ratings were pre-screened and
discarded. The ECPro software was used to calculate the ENPI, SOPI, ECPI
and the SPI. The results were synthesized and introduced into the SPSS

software package.

120

3.4.2 Scales and Calculations

The use of the AHP and the ECPro software dictate the scales for the
pairwise comparisons. The development, justification and testing of this scale is
amply discussed by Saaty (1996, pp. 53-64) and by Saaty and Kearns (1991, pp.
44-45 and 26-28). The judgments are qualitative and have a corresponding
scale value. The range of the scale is from 1 to 9. After the calculations are
processed, the weighted intensity results are expressed in ratio values whose
sum is equal to one. Table 7 - Scale of Relative Importance, describes the scale

used.

121

Table 7 - Scale of Relative Importance (Saaty, 1996. P. 54)

 

 

 

 

 

 

 

 

 

 

 

 

Intensity of Definition Explanation
Importance
1 Equal importance Two activities contribute equally to the
objective
3 Weak importance of one over Experience and judgment slightly favor one
another activity over another
5 Essential or strong importance Experience and judgment strongly favors
one activity over another
7 Very strong or demonstrated An activity is favored very strongly over
importance another, its dominance demonstrated in
practice
9 Absolute importance The evidence favoring one activity over
another is of the highest possible order of
affirmation
2.4.6.8 lnterrnediate values between When compromise is needed
__ adjacent scale values
Reciprocals If activity i has one of the above A reasonable assumption
of above nonzero numbers assigned to it
values when compared with activity j,
then j has the reciprocal value
__ when compared with l
Rationales Ratios arising from the scales If consistency were to be forced by

obtaining n numerical values to span the
matrix

 

 

122

ECPro has the capacity to perform assessment with ratings (Expert
Choice. 1995, pp. 125-149). This module of the program allows the user to
integrate pairwise comparisons for assigning weights to criteria with the capacity
to rate multiple alternatives. This process involves the rating of different
alternatives against a standard. In this case the standard is the SPP that is
assigned a rated value of 0.60. which corresponds to an acceptable sustainable
performance. The scale values were translated into word descriptors in order to
load the information into the ECPro software (See Figures 8 through 10). The
indices of impact, calculated using ECPro. are expressed as decimal numbers
ranging from zero to one, zero representing the least impact and one the
maximum impact. The following tables describe the scales used for rating the

different alternatives for environmental. social and economic impact.

Table 8 - Environmental Sustainable Performance Indicator Scale

 

Table 9 - Social Sustainable Performance Indicator Scale

 

123

Table 10 - Economic Sustainable Performance Indicator Scale

 

 

 

 

 

 

 

 

Rating Descriptor Description

1.0 Ideal Costs of proposed production practice are considerably
lower than those of conventional production practices

0.8 Desirable Costs of proposed production practice are lower than those
of conventional production practices

0.6 Acceptable Costs of proposed production practice are equal to those of
conventional production practices

0.4 Moderately Unacceptable Costs of proposed production practice are slightly higher
than those of conventional production practices

0.2 Highly Unacceptable Costs of proposed production practice are higher than
those of conventional production practices

0.0 Extremely Unacceptable Costs of proposed production practice are considerably
higher than those of conventional production practices

 

 

 

3.4.3 Consistency, Reliability and Validity

As shown in the previous section. clear process and structure of scoring
were established to assure consistent results among the panel members. The
hierarchical structure and the questionnaires were explained using graphical
displays in the computer to assure understanding by the panel members. A few
of the experts chose to enter the answers to the questionnaire directly into the
computer. The majority chose to enter the judgments in printed versions of the
questionnaires and the researcher entered the answers into the software
program. When inconsistencies or errors were detected, the researcher
contacted the expert to validate the answer. This procedure insures the

completeness of all parts of the inquest.

The validity of the method was secured by choosing validated instruments
such as the AHP and ECPro software. The cause and effect diagrams were
constructed based on a banana production system diagram that was presented

in a peer-reviewed journal publication (Hernandez and Vlfitter. 1996). The

 

124

hierarchical structure was assembled from the Cause and Effect diagrams.
Consistent validated scales were chosen to standardize the units of
measurement. Consistency was checked to ensure that the judgments were
within the acceptable limits. The Delphi Method allowed the researcher to review
preVious expert opinions with the other members of the EP, and the experts
made adjustments when inconsistencies, misjudgments or mistakes were

recognized.

All measurements are subjected to experimental error, and pairwise
comparisons are no exception. The type of inconsistency possible in pairwise
comparisons can be better explained by the following example: An expert is
asked to compare the value of three panoramic views. The letters A. B and C
identifies views. If the judge rates “A” three times better than “B” and “B" two
times better than “C”. a consistent judgment should rate “A” six times better than
“C”. However, it is entirely possible in a painrvise comparison between “A" and
“C” that the judge rates “A” only four times better than “C". Because of the nature
of the problem this inconsistency may be acceptable. On the other hand if “C” is
judged better than “A”, the researcher may want to discuss the inconsistency and
ask the judge to review his assessment. Inconsistencies in judgments in
pairwise comparisons are expected, and the amount that can be tolerated
depends on the nature of the problem. Therefore, the important issue is to
calculate the amount of inconsistency so that the researcher can make a

decision whether to accept the judgment or reject it.

125

Calculating a consistency index (Cl). a random consistency number and
establishing a consistency ratio (CR) checked consistency in this experiment.
The procedure for calculating the CR was amply explained by Saaty and Keams
(1991, p. 33). Furthermore, Saaty and Keams (1991. p. 34) recommend an
acceptable CR of 10%. but cautioned not to discard the possibility of accepting
higher values depending on the nature of the problem up to a maximum value of
20%. For this experiment. the following criteria was fixed before the interviews
started: all values over 10% must be reviewed with the panel of experts and after
review inconsistencies can be allowed up to 20%. Data which does not meet this
criteria must be discarded. Since most experts chose to start their analysis by
entering percentages and then checking validity by converting to pairwise

comparisons, the inconsistencies ratios were kept well below the value of 10%.

3.5 Procedures

3.5.1 Data Collection and Calculations

This section lists all the steps and tasks that were performed to collect

and process the data for this project.

1. Formation of the panel of eimerts; - A list of names was compiled by
asking EARTH's faculty and staff to suggests names of noteworthy
experts in banana production. These names were complemented by the
authors personal acquaintances within the banana industry. From the list,
the researcher chose ten experts and contacted them by phone to
schedule a meeting.

126

First Meeting
A full explanation of the project was given to the candidate and his
cooperation was requested. In return, the candidate was promised

confidentiality.

Each candidate was asked to sign a standard letter of informed consent.
A copy was given to the participant and the original was filed with EARTH
College's Comptroller to guarantee confidentiality. If any of the candidates
refused to give consent, another candidate was chosen from the list and
step one was repeated.

A number was assigned to each panel member to identify him without
violating the confidentiality pledge.

The last task of the first meeting was to secure an appointment for the first
90 minute interview.

First Interview

The first step was to allow the panel member to clear any doubts as to his
participation.

The expert was asked to review the cause and effect diagrams.
Comments, additions and corrections were recorded directly on the
diagrams. Latter, after carefully reviewing the notes taken, the cause and
effect diagrams were amended. Using the Delphi Method of interviews.
the revised copy of the cause and effect diagrams were then used to show
the next expert. In this way, each expert was allowed to comment on the
changes suggested by the other members of the panel. The final version
was presented in a meeting of the Environmental Banana Commission.
The members of this commission made comments and suggested a few
changes, which were introduced to the diagrams.

The list of conventional production practices (predictor variables) chosen
from a life cycle analysis was reviewed. The description of each task was
carefully reexamined, experts volunteered 'hard' data to complement the
description. and the list was improved. The improved list was presented
to the next expert, giving each expert the opportunity to comment and
improve the description of the previous expert.

The expert was asked to suggest potentially better practices (SPP) that
merit consideration and further research. and a full description of that
practice was noted in the space opposite the corresponding CPP predictor
variable. Each expert was shown the information given by the previous
expert allowing him to complement and add alternative SPP. When
available. 'hard' data was added to the description. The final list of SPP

127

was reviewed and summarized by the investigator. a description was
prepared. and doubts were checked by phone communication with the
experts. For some of the predictor variables there were more than one
SPP chosen and in a few cases, the CPP were deemed the best available
practice. The compiled list of CPP and SPP predictor variables was used
for the assessment in the second interview.

Before ending the first interview. a second interview appointment was
secured.

Transfer Information to ECPro

The information gathered was synthesized and loaded into the software
package.

mm

The first step was to allow the panel member to see the results of the first
interview in advance of the second meeting.

The next step was to meet the each expert and explain once more the
procedure for the filling out the evaluation questionnaire.

A laptop computer was used to display the AHP structure and the
evaluation questionnaires.

Each of the questions was reviewed and the expert was asked to make a
judgment.

A few of the experts chose to fill the questionnaire directly in the computer
in the presence of the researcher and reasoning each of their answers.
This procedure took approximately 3 hours.

Most of the experts chose to go through several of the questions with the
researcher. they filled the answers. asked questions and then finished the
questionnaires on their own. In this case the interview took approximately
90 minutes.

Transfer Information to ECPro
The answers to the questions were loaded into the ECPro software.

The results were checked for consistency. Inconsistent judgments were
discussed with the experts to allow him or her to make corrections.

The expert was asked to rate each CPP and SPP predictor variable.
Ratings were loaded in ECPro software and results printed.

128

7. Data Analysis

a. The results were arranged in a matrix configuration to facilitate analysis.

b. The data was prepared for statistical analysis and loaded into SPSS.

c. The hypothesis was tested.

8. Recommendation and Conclusions

a. From the information gathered, recommendations were made and a

strategic plan was formulated to implement them.

3.5.2 Research Method Flow Chart

A flow chart of the procedure described in the previous section is shown in

Figure 6.

129

‘ CHECK & CORRECT ewes '&

, EFFECT DIAGRAMS 1'

TEST
,. ‘ . H YPOTHESIS
6: SPP 3- CPP-BAP

TEST
HHYPOTHESIS . __
Ho: CPP - BAP ‘

Ho: BAP - SPP

 

Figure 6 - Methods Flow Chart

130
3.6 Statistical analysis
The experimental design used for this dissertation was a two-way
classification or randomized block design (Snedecor and Cochran, 1967, p.299;

Kachigan, 1986, p.301). The following assumptions were made:

0 Each observation is a random sample of a population defined by a
combination of a treatment and a block (kn).

o Populations of kn are normally distributed.
Treatments and repetitions are independent and do not interact.
0 Measurements are in interval scales.

In order to test the hypothesis it was necessary to state it in the form of the
null hypothesis. This hypothesis was based on the assumption that there were
no significant differences between the SPI calculated for conventional production
practices and the SPI calculated for best available practices, and that these
indices were statistically equal to the assumed SPI value for acceptable
sustainable production index (0.60). This hypothesis can be expressed in

mathematical terms in the following manner:

H01 “CPP = IJSPP = SPP
SPP = 0.06

In mathematical terms the alternative hypothesis was stated in the

following manner:

H1: IICPP at USPP at SPP

The mathematical model for this two-way classification experimental

design was represented by the following formula:

131

Yij=l1+at+l3cp+etcp

where,
u = Overall Mean
ai = Treatment (Row) Effect
Bj = Replication (Column) Effect
eij = Independent Random variable Dueto Experimental Error

The treatment and repetition effects are random and cancel out. This is

expressed mathematically as follows:
2a. = 28,“ = 0

The independent random variable due to experimental error can be

estimated by choosing the level of acceptable error for this experiment. which

was assumed to be 0.05.

In accordance to Snedecor and Cochran (1967, p. 306). the following

assumptions were made in order to test this mathematical model:

1. “The mathematical form ()1 + a,’ + {3}) implies that the row and
column effects are additive. ”
2. “The 5,] are independent random variables, normally

distributed with mean 0 and variance 0’. They represent the extent
to which the data depart from the additive model because of
experimental enor (Snedecor and Cochran, 1967, p. 303).”

“The residual sum of squares measures the extent to which the
linear additive model fails to fit the data (Snedecor and Cochran,

1967, p. 306).”

The steps necessary to calculate the differences are expressed in table

Table 11:

132

Table 11 - Two-way Classification Experimental Design

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

‘ i= Rows Treatment 1 Treatment 2 Treatment 3 Replication Mean

j = Columns Row Mean
Replications or CPP SPP SPP

blocks (n):

1 X1] 0.60 _ x1

2 0.60 _ X2

3 0.60 _ X3

0.60

n == 10 0.60 _ xn

Treatment Mean _ _ _

= Column Mean xcpp xspp 0.60 XTQTAL

SS = Sum of Squares T = Total c = Column r = Row

881' = 22 2(xij - x)2
_ . . 2

SSc - 2 n, (X) - X)
_ . . 2

SSr - 2 n. (X1 - X)

SScr = Residual error sum of square deviations = 2 (xij - Xj - xi + x)2 = SSE
SSE = Sum Square Error or Sum Square Residual
SScr = Total - Column - Row

The F- test was applied using the following ratios and comparing them to

the F charts for 0.05 significance level:

Table 12 - Procedure for ANOVA

 

 

 

 

 

Source of SS df Variance Fraction for
Variation F - Test
Treatments SSc c - 1 sc2 = SSC / (c-1) $62 I 5ch
Repetrtrons SS, r - 1 sr2 = SSr / (r-1) $r2 / $ch
Resrdual SScr (c-1)(r-1) $ch = Sscr / (c-1)(r-1)

Total SST cr -1

 

 

 

 

 

 

 

133

If the null hypothesis is not rejected, there is no need for further testing

because there are no significant differences among the data and all three

treatments can be assumed equal. If the null hypothesis is rejected. then it is

necessary to do further hypothesis testing as follows:

H0:
H1:
H0:

H1:

IJCPP = SPP
UCPP ¢ SPP
IJSPP = SPP

IJSPP e SPP
SPP = 0.60

To accomplish this testing a Planned Orthogonal Comparison (Kachigan,

1986, pp. 304-311; USDA, 1966, pp.6-14) was used. The table 13 illustrates the

procedure.

Table 13 - Procedure for Testing a Planned Orthogonal Comparison

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

T1 = T2 = T3 = 'Bir. Dif2 Divisor Sum of the
CPP SPP SPP ' Squares
gqntrast 1 +1 -1 0 gigs:- (+1)2+(-1)2"n SSc1
ggntrast 2 0 +1 -1 XSPP-XSPP (+1)2+(_1)2. SScz
ss=ssT
8831 = +1 (CPB -1(SPP)
(+1)2+<-1)2*n
SScz = +1 (SPP) -1lSSP)

 

(+02 +<-1>2 * n

C1 F-Test = SSc1/ SST

 

134

CZ F-Test = SSc2/ SST

Limitations and Delimitations

In the analysis of the information resulting from the application of this
method, it was necessary to keep in mind the many assumptions that were made
and the limitations. which these assumptions impose on the method. The
conclusions reached and recommendations made took into consideration these

limitations.

Concluding Remarks

The previous sections describe the method used to collect and analyze
the data. The foundations of the method used rest on the H & W model which
was presented in an article published by the author of this dissertation and Dr.
Scott G. Vlfitter in AMBIO and edited in Chapter 2 of this document. However,
the model lacks one fundamental element. It does not render precise intensities
for each of the interactions shown. The definition of interaction intensities is the
instrument necessary to judge sustainable performance. The development of a
method to obtain weighted intensities among the different interactions between
the environment, society and the economy and the derivation of sustainable

performance indices was the fundamental contribution of this dissertation.

The following chapter summarizes the results of applying this method. It
arranges the data in an orderly fashion to facilitate analysis and synthesis. The
fourth chapter sets the stage for the formulation of recommendations and

conclusions.

Chapter 4

RESULTS

4.1 Introduction

The problem and questions to be answered in this dissertation were
introduced in the first chapter. Sustainable agricultural production became the
beacon to guide the search for solutions. The fundamental pillars that support
sustainable agricultural production were recognized as the environment, society
and the economy. Systems theory was utilized as the road to detect sustainable
solutions. Chapter I introduced world-class banana production system as a
specific case to test the validity and appropriateness of the proposed systems

method for evaluating the sustainability of ag-production.

The second chapter prepared the road by dissecting, classifying and
quantifying the problem through the collection of information available in the
literature. It introduced a basic model advanced by Hernandez and Witter
(1996), that outlines the production system. This model defined the limits. the
components, the inputs and outputs. and it evidenced the interactions among the
different components of the system. It served as a map that facilitated the
search for a sustainable solution. However, it lacked precise intensities for each
of the interactions and it did not consider the social and economic elements of

the system.

135

136

A method to assign intensities and derive performance indicators based
on systems theory was proposed in Chapter 3. In essence, this was a decision-
making method that had several steps leading to one objective — organizing
information to assist producers in identifying and applying the best available

method for growing bananas in a sustainable manner.

This chapter presents the results of applying the decision-making process
outlined in the previous chapters. It is organized according to the ten
consecutive steps that were taken to complete the process. The sections of this

chapter discusses each of those steps:

Section 4.2 - Identifies and describes the panel of experts (PE).

Section 4.3 - Defines the conventional production practices (CPP),

Section 4.4 - Lists the alternative production practices (APP).

Section 4.5 - Establishes criteria and standards.

Section 4.6 - Assigns relative weight to the criteria,

Section 4.7 - Rate the CPP and the APP, and calculate environmental,
social and economic performance indicators (ENPI. SOPI
and ECPI).

Section 4.8 - Rejects the APP that fail the criteria for BAP,

Section 4.9 - Calculates the sustainable performance indices (SPI), and

Section 4.10 - Tests the hypothesis.

Sections 4.3 through 4.5 report the results of the first interview, and
sections 4.6 and 4.7 compile the results of the second interview. The rest of the

sections give the results of the calculations and statistical analysis.

137

The following sections contain the facts presented as tables and figures.
It also includes the author’s description of what is important about the facts and
the process of gathering the facts. The discussions of the findings and

conclusions are reserved for the next chapter.

4.2 Panel of Experts

A careful search for a balanced PE was a fundamental requirement to
achieve adequate results. A total of 18 experts were consulted in the first round
of interviews, of which two declined to continue with the study. Twelve of these
(PE 1. 3, 4, 5, 7. 8. 9. 10. 11. 12, 13. and 15) were chosen to fill out the
questionnaires based on their holistic knowledge of the industry. Four (PE 2. 6,
14 and 16) were used as consultants in specific areas of this study. Out of these
four consultants, one was used as a test run to calibrate the other
questionnaires. The pilot questionnaire was discarded because it could not be
reconciled with the format of the subsequent questionnaires. Additionally, the
expert in reference (PE 2) disqualified himself from emitting opinions regarding
social issues because he is a foreign national and did not consider himself to be
familiar with Costa Rica’s society. It is noteworthy to say that his interview was
very valuable. Besides serving to calibrate subsequent interviews and
questionnaires. priceless information was derived from the interview that was

incorporated into the definition of the environmental criterion used.

Ten (PE 1. 3, 4. 5, 7. 8, 9, 11, 12 and 13) out of the 13 experts chosen to

fill out the questionnaire, submitted complete questionnaires. One (PE 15) out of

138

the two remaining experts submitted opinion Only in the environmental section of
the questionnaire. However, all of the experts were interviewed at least twice

and valuable information was gathered from them.

Table 14 enumerates and describes each of the experts and gives details
of their participation. To ensure confidentiality. each expert was identified by
number and not by their names. Their characteristics are carefully summarized
as not to reveal their identity. However, the experts chosen are well known in the

industry. the industry is a close-nit group.

Great effort was placed in balancing the PE since the study is based on
opinions. Five of the ten experts that completed the questionnaires are directly
involved in production of bananas (PE 1, 4, 5, 8 and 11). The remaining five
experts are directly involved in support services for the industry, including
education of the future managers of the industry, and doing the research and
development of many of the alternative production practices (PE 3, 7, 9. 12 and
13). The expert that partially completed the questionnaire is involved in both
areas. production and support (PE 15). As will be noted in the appropriate
section. there is a significant statistical difference in the resulting indices among

the two groups.

Table 14 - Panel of Experts

139

 

Description

Participation

 

A national producer that is the
owner of a large plantation
producing bananas for a
transnational buyer.

Pei participated in three interviews and completed
the evaluation questionnaire.

He also supplied his farm's financial data, which
combined with the information from two other farms,
set the weights for the economic criteria.

 

College professor specializing in
tropical crops.

He participated in two interviews and collaborated in
the pilot questionnaire. He provided a major portion
of the information used to define environmental
criteria. He also contributed with several innovative
APPs

 

College professor specializing in
tropical crops.

He participated in one interview, reviewed and
commented the results of the first interview. and
completed the evaluation questionnaire in the
presence of the researcher. Each answer was
justified orally providing great insight for the
researcher.

 

Staff member of a transnational
grower-buyer.

A biologist and a specialist in
environmental and social issues
of banana production.

He participated fully in at least three interviews, and
completed the evaluation questionnaire. He
contributed greatly to the definition of the criterion
variables and the CPPs and APPs.

His questionnaire was one of two first generation
questionnaires. which had a large amount of detail.
The experience served to streamline the rest of the
questionnaires.

 

Economist in charge of financial
affairs for three large
independent farms. He worked
for many years as a financial
officer for a transnational
g_ro_wer-buyer.

He participated in three interviews and completed
the evaluation questionnaire. He also compiled and
prepared the financial data from three farms. which
served to assign weights to the economic criteria.

 

 

Staff member of a transnational
grower specializing in safety and
human resources.

He participated in one interview and supplied a
major portion of the information used to define the
social criteria. He also collaborated in defining the
APPs for the social component of the study.

 

Certification NGO that emits
environmental labels and
specializes in wood. bananas
and oranges.

Pe7 consists of a group of three, two agronomists
and a lawyer (two females and one male). The
group participated in two interviews and completed
the evaluation questionnaire. Their questionnaire
was one of two first generation questionnaires that
had a large amount of detail. The experience
served to streamline the rest of the questionnaires.

 

 

 

Consultant to several
independent producers.
Specialist in production
practices. Author of several
articles in production and

environmental issues.

 

He participated in at least three interviews and
completing the evaluation questionnaire.

His participation was crucial in the definition of CPPs
and APPs.

 

 

Table 13 Cont’d

140

 

Researcher specializing in
environmental issues of banana
production.

Peg participated in at least three interviews and
completing the evaluation questionnaire.

His participation was crucial in the definition of
criterion variables and CPPs and APPs. He also
collaborated in streamlining the questionnaires.

He completed the evaluation questionnaire in the
presence of the researcher. Each answer was orally
justified providing great insight for the researcher.

 

 

 

 

 

 

 

 

10 National independent producer He participated in two interviews and contributed in
of organic bananas. the definition of criterion variables and in suggesting

innovative APPs.

11 Superintendent of several He participated in at least three interviews and
banana plantations. He is completed the evaluation questionnaire.
directly responsible for His participation was crucial in the definition of CPPs
productivity and quality of fruit. and APPs.

12 Researcher specializing in He participated in at least three interviews and
agronomic issues of banana completed the evaluation questionnaire.
production. His participation was crucial in the definition of

criterion variables and CPPs and APPs. He also
completed the evaluation questionnaire in the
presence of the researcher. Each answer was
justified orally providing great insight for the
researcher.

13 Biologist. environmentalist and He participated in one interview. reviewed and
consultant to the banana commented the results of the first interview. and
industry. completed the evaluation questionnaire in the

presence of the researcher. Each answer was orally
justified providing great insight for the researcher.

14 College professor and an Pe14 participated in one interview and supplied
anthropologist. information used to define the social criteria.

15 College professor and owner of He participated fully in at least three interviews, and
a banana plantation. Author of partially completed the evaluation questionnaire. He
several books and articles. contributed greatly to the definition of the criterion

variables and the CPPs and APPs. __

16 Group of three high level, This group reviewed the article published in AMBIO

 

corporate staff members of a
transnational grower-buyer
company.

 

by Hernandez and Witter (1996) and the list of CPP
APP. They emitted a written opinion. There was
one joint interview, in addition to several E-mails,
personal and phone conversations with the
coordinator of the group to verify details. A major
portion of their considerations were incorporated to
this document. This information is referenced
separately in the document as PE16 because it was
obtained through a different procedure than that
used to obtain the information supplied by the rest of
the experts.

 

 

141

The following three sections present the results of the first interview with
the experts. The objective of the first interview was to identify the independent
and criterion (dependent) variables. The independent variables are the
conventional and the alternative production practices. The dependent variables

are the criteria that were used to evaluate the independent variables.

4.3 Conventional Production Practices

The identification of Conventional Production Practices (CPP) was very
complex. Few banana production companies in Costa Rica have exactly the
same production practices. Transnational growers attempt to standardize
practices in their plantation, but different environmental conditions forces
customized procedures for each plantation. Furthermore, edafic differences
within plantations require adjustments and customized procedures for each
section of the plantation. Financial constrains limit a large number of producers
in adopting some recommended practices that improve environmental and social
performance. These differences contribute to the great disparity in level of

sustainable performance among plantations in Costa Rica.

Due to the previous reasons. the definition of conventional production
practices was very troublesome. A great amount of time was spent in the
interviews rendering a precise detailed base-line definition for CPP. The
researcher prepared and presented to the experts a first draft document based

on definitions and descriptions made by Sénchez (1996) and Soto (1994). Each

142

of the experts had the opportunity to review this definition and the changes made

by the other experts at least twice.

The final definition is a compromised definition and not all experts are in
total agreement with every stipulation. Therefore. it is important to note that the
description of CPP cannot be generalized and used to describe the standard
practices of the industry because they do not exist. Some plantations have a
technological package that is similar to the one described in this document, some
apply more advanced practices and some have a less sophisticated package.
The description of CPP is only a benchmark definition to compare with the

alternative production practices.

On the left side of Table 35 in Appendix B, the CPP have been
categorized by type of activity. each of the practices was assigned a number and
described at length. The activities were divided into three categories: Production
(identified by numbers ranging from one through six), Labor Management
Practices (identified by the number seven), and Macros (identified by the number
eight). The first category was subdivided into Field Practices (numbers ranging
from one to five) and Packing Practices (number six). Each subdivision was
further subdivided and assigned letters. The Labor Management category
(seven) was subdivided into Hiring Practices (a), Fringe Benefits (b), Risk
Prevention (c) and Others (d). The experts were issued a final draft copy of
Table 35 in Appendix B in Spanish as a reference for use in assigning ratings

and filling the questionnaire. A few changes were made in the final English

143

version of the document in response to comments made during the evaluation.

These modifications did not change the basic definition, but made it precise.

The definition of the CPP completed the first objective of the initial
interview. The second objective was to compile a list of alternative production
practices that after careful analysis and evaluation could be considered best
available practices (BAP). The following section presents the list and description

of the suggestions given by the experts.

4.4 Alternative Production Practices

The PE was asked to identify and define the APP. Each expert had at
least two opportunities to review the list of APP and the changes made by the
other experts. Even if the majority of the experts were not in agreement with one
or more of the suggested alternative practices, none of the suggested APP were
removed from the list. The APP were not considered best available practices
(BAP) until the results were analyzed and statistically tested against basic
criteria. The experts had the opportunity to voice their opinions of the APP
through their ratings. Some recorded their opinions in writing. The alternatives
with low ratings, as well as those that were not fully available at the time of
evaluation, were rejected from the list of BAP. Many of the APP were already in
use in some plantations. Others were not fully tested and require pilot field trials
before industry-wide acceptance. The experts were quick to point out which

were tested and which were not. Careful note was taken of their opinion and it

144

was used to discard APP with high ratings, but that were not available at that

time.

On the right side of Table 35 in Appendix B, the APP suggested by the
experts were recorded and organized using the same categories and sub-
categories that were established in the previous section. Each was assigned a
number and described in length. Since the categories and sub-categories for the
CPP and APP coincide, the right side of Table 35 in Appendix B exhibits the
alternative practices for the CPP shown on the opposite side. It is important to
note that several of the APP apply for multiple categories and were evaluated in
more than one category. The members of the PE were supplied with a Spanish
version of this table as a reference to assign ratings and fill the questionnaire.
No changes in the description of the APP were made in the English version of

the table.

The method proposed in Chapter 3 calls for the creation of an evaluation
matrix to rate the CPP and APP. The list of CPP and APP completes the vertical
axis of the evaluation matrix. The next task is to designate the criterion variables
that constitute the horizontal axis of the matrix and become the headings of the
columns. The application of any of the production practices (the rows of the
matrix) will have an effect on the environment, the people and the economy (the
columns of the matrix). The purpose of the next section is to identify the criteria

to evaluate the effect caused by the production practices.

145

4.5 Criterion Variables

Figures 15 through 36 in Appendix A represent cause and effect diagrams
(fishbone diagrams) that are generic to any agricultural production activity. The
difference is in the inputs. which are specifically tailored to represent the
production of world-class bananas. The boxes in these diagrams are used to
designate the criterion variables at three levels of detail — mega, macro and
micro. Some of the micro criteria were further subdivided to show more detail.

The shaded boxes show the level of detail included in this study.

These diagrams were assembled with the help of the PE. The author
constructed an initial set of diagrams that were shown to a major segment of the
PE (15 experts) on an individual basis. Each of the experts contributed to the
diagrams. and his contribution was included in the diagrams shown to the expert
in the following interview. Using the Delphi method. all experts had the
opportunity to comment and contribute to the diagram at least twice. The
Environmental Banana Commission (CAB)15 also reviewed the diagrams and
made suggestions. The final version of the cause and effects diagrams was a
compromise among the experts. In contrast to the definition of the CPP, in this

case there was general agreement by the PE.

Due to the complexity of the system, it was impossible to draw one

general diagram. It was necessary to create a cascade of diagrams that proceed

146

from the macro to the micro components of the system. In essence, the
components of the diagrams are the dependent variables of the system. This
means that any production activity (independent variables) occurring within the
system has an effect on all the components shown on the diagrams (dependent
or criterion variables). Some of the effects are direct. yet others are indirect and

less obvious.

The arrows shown in the diagrams (Figure 15- through 36 in Appendix A)
depicted vectors. The mathematical dimension of the vector (the arrows in the
diagrams are not drawn to scale) was a product of the intensity (relative weights
assigned by the PE - see section 4.6) multiplied by the rating of performance
(see section 4.7). The direction of the arrows showed whether the effects were
beneficial (+) or detrimental (-). Vectors that point to the right showed beneficial
effects and vectors that point to the left showed negative effects. The
performance index was the resulting vector, which was the sum of all the impact
vector. Since the ECPro software does not permit positive and negative
numbers, a scale of zero to one was chosen. A rating of 0.6 was defined as the
acceptable level or the fulcrum point between positive and negative effects.
Numbers above this point show positive effects and numbers below show

negative effects. A rating of 0.6 indicates a balance between negative and

 

‘5 CAB is a multidisciplinary group of experts representing all the banana industry’s

stakeholders in Costa Rica whose objective is to recommend environmental policy for the
industry.

147

positive forces, which was the minimum expected condition of any of the

activities in order to be acceptable.

Following suggestions from the Environmental Banana Commission and
some of the experts, the main headings were chosen to indicate positive
performance, in an effort to set a constructive note to the study, and not to
antagonize the producers. For example, instead of using the term “Pollution

Generation” to indicate a criteria. the term “Pollution Prevention“ was used.

The cause and effect diagrams were used to revise and complete the
H&W model proposed in Chapter 3. Figures 37. 38 and 39 in Appendix A
illustrate the revised model. The most significant change was the addition of the
social and economic elements to the model. Each element of the system was
sketched in a different figure. The combined drawing depicts a banana
production system. Notwithstanding the importance of the intimate
interconnection of the three elements of the system. no interactions or feedback
loops were shown that links the three diagrams. The interconnection was
recognized but not shown in order to simplify the diagrams. Intensities were only
shown for the economic model since the values were a product of hard data.

Intensities for the other two components are the subject of section 4.6.

The diagrams defined the limits of the system by enclosing the
components (the banana plantation and the packing plant) within a curve edge

rectangle. The vectors within the limits of the system represent the interactions

148

among the components of the system. The arrows outside the limits evidenced

the inputs and outputs of the system.

The components shown in the cause and effect diagrams were used to
build the hierarchical structure essential to the ECPro software. For the pilot
questionnaire. the hierarchical structure included five levels of detail. The
resulting evaluation matrix was very large and it required too much time to
complete each of the three questionnaires (environmental, social and economic).
Since the experts could not be expected to invest this amount of time in
completing the questionnaires, it was necessary to reduce the levels of detail.
Two modified questionnaires were prepared and presented to PE 4 and PE 7.
The time requirements were reduced to eight hours to complete the three
questionnaires. After consultation with several of the members of the PE. it was
decided to reduce the level of detail even more. The shaded boxes shown in the
diagrams depict the level of detail and the criterion variables included in the
hierarchical structure and final questionnaires. The amount of time necessary to
fill the final questionnaires was three hours. This time requirement exceeded the
commitment made to the members of the PE in the letter of informed consent.
Ten members of the PE, agreed to continue their participation, one completed

only one of the three questionnaires. and one dropped out of the study.

It is important to recognize that the dependent variables are not
independent of each other. They are interconnected by feedback loops. The
model becomes very complex if feedback loops were considered and lose clarity.

Therefore, the cause and effect diagrams only considered direct relationships.

149

and ignored indirect relationships (feedback loops). As a consequence, the
resulting hierarchical structure digitized into the ECPro software had no feedback
loops incorporated into it. It is significant to note that the software used has the
capacity to include feedback loops. However. the size and complexity of the

questionnaires is augmented beyond manageable levels.

At this stage, the objectives of the first interview were accomplished. The
second interview had two objectives: define the intensities of the criterion
variables and rate the CPP and APP. As indicated before. the arrows shown on
the diagrams depicted vectors and the value of the vector depended on the
intensity and the rating. The intensity of a vector was synonymous to the
importance of the criterion variable. The objective of the next section was to
present the set of values (weights) that were given by the PE to each of the

criterion variables chosen for the evaluation matrix.

4.6 Relative Weights (Intensities)

From the results obtained in the pilot run (PE 2), it was evident that the
degree of importance for each of the criterion variables varies according to the
activity that was being analyzed. Furthermore. activities could be grouped
according to type, and each type of activity had a different degree of effect on the
sustainability of the system. For this reason, the activities shown on table 35 in
Appendix B were arranged according to categories and sub-categories forming a
pyramidal hierarchical structure. This structure was subdivided forming two

pyramidal hierarchical structures with two levels of analysis. Borrowing from civil

150

engineering structural terms. the higher hierarchical structure was referred to in
this document as the superstructure (SS) and the lower hierarchical structure as
the foundation structure (F8). The lower structure was used to calculate the
individual ENPI. SOPI. and ECPI for each expert and each category of activities.
The average value of the index (ENPI, SIPI and ECPI) for each expert and
category was plugged into the SS structure to calculate the aggregated

sustainable performance index (SPI).

It was necessary to divide the hierarchical structures into two structures
because the ECPro software allows for only five hierarchical levels. and at least
six levels were necessary to analyze the system in a single hierarchical structure.
Furthermore. the separation into two hierarchical structures permitted calculation
of environmental performance indices (ENPI), social performance indices (SOPI),
and economic performance indices (ECPI) individually for each of the CPP and
APP. This allowed the analysis of each activity before aggregating into a
collective index (SPI). If the single structure had been used, the calculation of
the SPI would have been done in one step without reporting the intermediate

values.

Figure 9 illustrates the F8 for the environmental component. figure 10
Illustrates the F8 for the social component, Figure 11 Illustrates the F8 for the
economic component of the system. and Figure 12 represents the SS. The
components of the FS correspond to the lowest level of detail (micro level)
criterion and sub-criterion variables that were presented in Figure 15 through 36

in Appendix A. Each activity was rated using these bottom line criterion

151
variables. The rating scale was shown on the right side of Figure 7 and 9. In
Figure 8, the rating scale was substituted by the word “ratings” for reasons of

space in the drawing.

152

 

Biodiversity 33%

lPlanting W 21%.
In uts 20%
I Natural Resources 20%

Biodive ' 29%
Drainage Wu 93%.

In uts 25%
l I Natural Resources 23%

 

 

 

Biodive 27%
Pest Management ' n 2531i.

In uts 25%
I Natural Resources 20%
Biodivers 31%
Fertilization I Pollution 27% IDEAL

 

 

 

 

 

 

 

 

 

In uts 21%
Natural Resources 21%

l Biodive ' 32%
Harvest I Pollution 33%

I lnEuts 25%-
| Natural Resouces 15%

 

Biodivers' 31% -
Packing I Pollution 23%
In uts 18%-
I Natural Resources 27%

Biodivers' 30%

 

Macros

 

 

In uts 19%
I Natural Resources 23%

1.0
ltflwat'ifal Resources :83- DESIRABLE 0‘9-
. ACCEPTABLE 0._6_
" i ‘ Biodive 31% MODERATELY UNACCEPTABLE 0.4
m Cm lam—0:“ 28% HIGHLY UNACCEPTABLE 02

an; . - - _ PT : 2 n .

 

 

Figure 7 - Foundation Structure for the Environmental Component

 

153

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Health Hazards 29%
Workers 62% Mork Contract 28%
Job Security 24%
Enhancement 18%
Contractual Conditions ' '
[Local Community 24%
[National Community 14%
Health Hazards 3%
Workers 56% [Work Contract 27%
Job Security 25%
Enhancement 18%
Fringe Benefits fi
[Local Community 32%
[National Community 12%
Health Hazards 36%
Workers 62% [Work Contract 27%
ob Security 23%
Enhancement 14%
Risk Prevention fi
ocal Community 24%
[National Community 13%
Health Hazards 29%
Workers 56% [Work Contract 26%
Job Security 27%
Enhancement 18%
Other '
[Local Community 30% }
[National Community 14%
Workers 55%
Macros [
[Local Community 33%
[Niational Community 12%

 

'—

 

 

RATINGS

 

 

Figure 8 - Foundation Structure for the Social Component

 

154

 

 

Overhead 1 1.5%

 

lnfraestructure ‘ 1.I%

 

 

 

 

 

 

 

 

Labor 3I.8% DEAL 1.0
DESIRABLE 0.3
ACCEPTABLE 05
MODERATELY UNACCEPTABLE 0.4
Contractors 49% HIGHLY UNACCEPTABLE 0,2

 

 

| EXTREMELY UNACCEPTABLE 0.0

 

Environmental
Protection 1.0%

 

 

 

Figure 9 - Foundation Structure for the Economic Component

 

155

 

General 30% Planting

49%

 

 

 

 

  
 

 

 
 

 

 

[Drainage 51%
Sigatoka 57%
Pest
Management 39° Nematodes 28%
. I ,
Fied 64,6 I 15%

 

 

[fertilization 14%

 

Fruit Care 11%

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Environmental 32% fl-Iarvest 6%

[Packing 22%

[Macros 14%

Hiring

Practices 31%

Fringe

Benefits 16%

Risk

Others

Macros 9%

Production

Activities 50% Field 63% 3
[Packing 37% ?
Hiring

[Economic 33% Practices 39%
' [Fringe Benefits 39%

Labor Risk

Activities 40% Prevention 22%
[Others 0"?

Macros 10%

 

 

 

 

 

 

Figure 10 - Superstructure for the Production System

      
 

 

156

Table 36 and Table 38 in Appendix B show the individual weights given by
the PE for each category and criteria. The individual weights were used to
calculate the individual indices for each expert. The data evidences a wide range
of values. For this reason, it was judged necessary to identify outliers and
eliminate them. The statistical analysis of the data was made at three confidence
intervals (95%, 90% and 75%), setting limits at both tails-ends of the normal
distribution curve. A 75% confidence level was chosen after analyzing the
outliers. With this level of confidence, only one or two extreme values were
rejected. However, there are a few exceptions where more than two values were
rejected. The majority of the resulting mean values differ by only a few percentile
points from the mean values calculated using the entire data set. The maximum
variation was 7%. Table 36 and Table 38 in Appendix B show the individual
weights given by the PE for each category and criteria. The individual weights

were used to calculate the indices.

The average weights have no bearing on any of the numbers used to test
the hypothesis. However. the average weights show general tendencies and
help define the importance of the interactions among elements of the model,
which was one of the objectives of this dissertation. Figures 7 and 8 show the
mean intensities'as percent values for the environmental Foundation Structure
(FS) and the social F3. The economic intensities were derived from hard data
generated from the 1996 financial reports from three farms. and are shown in
Figure 9. The weights or intensities given by the PE to the elements in the SS

are shown in Figure 10.

157

In reference to Figure 10, the results show that the weight given by the
experts to the three principal components of sustainability - environmental, social
and economic — were approximately equal. Within the environmental
component, the field activities predominated with 64% of the weight. Of the field
activities, pest management received the highest weight (39%), followed by
general practices (30%). Judging from the results, there was no doubt in
identifying the control of black Sigatoka as the most impacting practice on the
environment. followed by drainage and planting practices. Vlfithin the social
component of the system, hiring practices was the highest priority given, closely
followed by risk prevention practices. Within the economic component,
production activities were the most important elements. followed by labor

activities.

At this point, the vertical and horizontal axis of the evaluation matrix were
finalized and the first objective of the second interview was accomplished. The
next step was to fill the cells of the matrix by rating each CPP and APP with
respect to the criterion variables. The experts were asked to fill questionnaires
and rate the impact of each of the production activities. The objective of the next

section is to report the results of the evaluation ratings given by the experts.

4.7 Ratings

The instrument for rating the CPP and APP was a questionnaire
containing the evaluation matrix. This matrix was subdivided into three major

matrixes - the environmental, social and economic evaluation matrixes. A large

158

volume of data was generated. The tabulated data was not included in this
section because it requires reduction and synthesis for it to be meaningful. This
section includes the author’s description of what is important about the process

of gathering the facts and reducing them to meaningful indices.

Ideally. all of the production and labor practices should be evaluated in
each of the components of the system (environment, social and economic). As a
result of experiences derived from the pilot questionnaire, it became evident that
the experts can rate only direct effects of the CPP and APP with a good degree
of confidence and consistency. For example, production activities, such as
planting and population control, drainage or fertilization, have direct effects on
the workers primarily in health hazard prevention but not on the other criteria and
sub-criteria (for example Benefits to the Local Community). Therefore. the
expert doing the rating was not clear on how to rate the activity with respect to

indirect relationships and it was difficult to cross check all criteria.

To solve this problem, the researcher decided, after consultations with the
experts. that all salary and risk prevention measures for field activities be
separated and placed under labor related issues and evaluated in the social
evaluation matrix only. In this manner, all labor related issues were held
constant while rating production activities with respect to environmental criteria,
and all environmental issues were held constant while rating labor related
activities with respect to social criteria. As a result. labor related activities are not

rated in the environmental evaluation matrix. and production practices are not

159

rated in the social evaluation matrix. In the case of the economic evaluation
matrix. all production and labor practices were rated under the same economic

criteria.

Using the environmental evaluation matrix, a total of 87 production
activities were rated against four criterion variables: Conservation of Biodiversity.
Pollution Prevention. Rational Use of Inputs and Conservation of Natural
Resources. Since the intensities of each category of activity were different, it
was necessary to prepare different matrices for each group of activities. As a
result. eight environmental evaluation matrices were prepared each representing
one of the following categories of activities: Planting and Population Control,
Drainage, Pest Control, Fertilization. Fruit Care, Harvest, Packing and Macros
(See figure 7 in section 4.6). The category Macros was used primarily to
compare in a general manner the performance of conventional practices against

the possibility of abandoning the production of bananas.

The social evaluation matrix served to rate 46 labor related activities with
respect to three major criterion variables: Benefits to Workers and Families,
Benefits to the Local Community, and Benefits to the National Community. The
criteria Benefits to Workers and Family was further subdivided into four sub-
criteria: Health Hazard Prevention. Work Conditions and Benefits, Job Security.
and Workers Enhancement (improvement through experience and training) (See

figure 8 in section 4.6).

160

The economic evaluation matrix was used to rate 131 activities. These
included 85 production activities, 44 labor related activities and two macro

activities common to both, production and labor issues (See figure 9).

As stated in the methods chapter, the scale used to rate the production
practices was from zero to one; zero being an extremely unacceptable impact
and one being an ideal impact. An acceptable impact was set 0.6. In the
majority of cases, the experts omitted the decimal point. This was not a problem
except with the rating of 0.1 and one. In several occasions, the researcher had

to recheck the ratings with the experts to verify the numbers.

As stated in the methods chapter. the CPP economic ratings were
assumed as acceptable and were assigned a rating of 0.6. The APP were rated
according to the cost increment or deduction. Cost increments necessary to
apply the APP were assigned values below 0.6 and in accordance with their

severity. Cost deductions were assign values above 0.6.

Each of the experts was asked to fill a set of 14 evaluation questionnaires
with 4950 judgments per expert. Out of 12 full sets of questionnaires distributed,
10 were returned completed, one expert returned the set partially filled, and one
expert dropped out of the study. Four out of the ten experts preferred to fill the
evaluation matrices (questionnaires) in the presence of the researcher and offer
reasons for their ratings. This process was very enriching. and the preferred
method. Due to limitations of time. six of the experts preferred to fill the

questionnaires at their convenience. Out of this group of six, three

161

questionnaires indicated problems that required at least one additional interview

and corrections.

A review of the tabulated results evidenced a few empty matrix cells.
Some cells were left open because the expert did not wish to give an opinion and
some because of error. The researcher had feedback interviews with three of
the ten experts to correct problems. One of the experts, which left a block of
cells without filling was not available for consultation. As a result one percent of
the individual ENPI. SOPI, and ECPI could not be calculated. The effect was
that 8.8% of the average indices had to be calculated with less than ten expert
opinions. With one exception. all averages were calculated with at least nine

expert opinions.

Due to paste and copy error by the researcher. activity APP7cj -
“Observance of Re-entry Period” was left out of seven of the questionnaires, and
the resulting average was judge not representative of the PE. For this reason. it
was excluded from the list of BAP. This was an unfortunate mistake because of

the activity’s importance.

The empty cells had very little consequences in the final analysis because
approximately half of the APP with empty cells were rejected as BAP through
statistical analysis. The other half had very little effect because the procedure
required the determination of average ENPI, SOPI and ECPI values for each
category of activities. In the case that an individual index could not be calculated

for lack of information. averages were calculated with the available indices.

162

None of the averages were calculated with less than nine indices. These
average values were substituted into SS to calculate the aggregated
sustainability performance index (SPI). As a result. the experimental design with

three treatments and ten repetitions (expert opinions) was maintained intact.

After the completion of this step, sets of intermediate indices were
available for summary, analysis and testing. To calculate the SPI for the BAP
(SPlbap), it was first necessary to determine a tentative list of BAP. The next
section presents the list of BAP and details of the statistical procedure used to

reject APP that did not meet the criteria.

4.8 Definition of BAP
The following criteria were applied to judge an APP worthy of being a

best available practice: the alternative practice must be better than the
conventional practices that are being used today, and they must be available for
immediate application. Furthermore, a best available practice must be
environmentally, socially and economically acceptable individually and
holistically. Since a data set of ENPI, SOPI and ECPI was compiled in the last
step, It was possible to perform a one tail student-t test to determine which of the
APP did not meet acceptable levels of the performance indices. According to the
scale established for this study, an activity must have indices above 0.6 for it to

be acceptable. Therefore, the hypothesis for this analysis was as follows:

HOS [.lapp = 0.6
H1: [.lapp < 0.6

163

A significant level of 0.05 was chosen for this analysis. Table 15. 16 and
17 show the activities that were rejected as BAP under environmental, social and
economic criteria respectively. These tables also show the indices calculated for
each expert opinion. the mean value. the standard deviation, the calculated
student-t for 0.6, and the reference student-t for a significance level of 0.05 and
corresponding degrees of freedom. Activities that were below the values of
student-t for 0.6 at the chosen significant level were rejected. It is important to
note that APP 8 - abandon banana production for export purposes — received

the lowest social rating (highly unacceptable).

As stated earlier. the best available practices must be environmentally,
socially and economically acceptable not only individually but also holistically.
To meet this criteria, the ENPI, SOPI, and ECPI were combined using the
weights assigned by the experts for the environmental, social and economic
elements of the system. This procedure yields an SPI for each activity, which is
designated as the individual sustainability performance index (ISPI). The test
becomes more stringent because the aggregation changes the shape of the
distribution curve, maintaining the mean but making the curve narrower. As a
result. the range of values in the no reject area is narrower. The results of this

test are shown on Table 18.

 

164

Table 15 - Rejected Alternative Production Practices Based on Low ENPI

 

 

 

 

 

 

 

 

ENVIRONMENTAL PERFORMANCE INDEXES (ENPI)

EXPERT NUMBER 0.60
AP 1 3 4 5 7 8 9 11 12 13 15 Mea ST STD T- T-
P n DD ER STU STU

EV R (2) CK

1aa 0.6 0.16 0.56 0.72 0.43 0.48 0.44 0.22 0.52 0.60 0.61 0.49 0.1 0.05- -

0 7 2.25 1.81
2ai 0.6 0.33 0.53 0.60 0.34 0.65 0.20 0.52 0.58 0.40 0.51 0.48 0.1 0.04- -

4 0 5 2.70 1.81
2cf 0.1 0.35 0.55 0.43 0.55 0.50 0.74 0.10 0.56 0.50 0.40 0.44 0.1 0.05- -

8 0 8 2.93 1.81
4af 0.6 0.30 0.27 0.68 0.55 0.52 0.73 0.60 0.20 0.60 0.00 0.46 0.2 0.07 - -

0 0 3 2.03 1.81
4bd 0.2 0.45 0.21 0.26 0.57 NO 0.80 0.24 0.45 0.80 0.60 0.46 0.2 0.07 - -

7 0 2 1.92 1.83

 

 

 

 

 

 

 

 

 

 

 

 

Table 16 - Rejected Alternative Production Practices Based on Low SOPI

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SOCIAL P—ERFORMANCE INDEXES (SOPI)
EXPERT NUMBER 0.600 T-
_ STU
A 1 3 4 5 7 8 9 11 12 13 Mea STD. STD. T- CHE
P n DEV. ERR. STU CK
P (2)
8 0.10 0.30 0.36 0.00 0.39 0.20 0.19 0.10 0.20 0.10 0.19 0.13 0.04 -10.2 -1.83

 

 

 

 

 

165

Table 17 - Rejected Alternative Production Practices Based on Low ECPI

 

ECONOMIC PERFORMANCE INDEXES (ECPI)
EXPERT NUMBER

 

1

3

4

5

7

8

11

12

13

Mea

STD.
DEV.

STD.
ERR.

.600
1'.
STU
(2)

1'.
STU
CHE

 

2ac
2cd
3h
3i
4ae
4ba
4bc
4bd
4b9
5b
6i
6i
7ch
7ck
7cp
7cs
7cu
7cx

 

0. 50
0. 64
0. 41
0.41
0.33
0.41
0.30
0.41
0.51
0.25
0. 41
0. 45
0.35
0.41
0.50
0.48
0.43
0.60

 

0.40
0.39
0.54
0. 50
0.48
0.50
0.31
0.48
0.55
0.61
0. 61
0. 56
0. 30
0. 54
0. 56
0.58
0.45
0.58

 

0.58
0.58
0.73
0.71
0.53
0.61
0.61
0.59
0.66
0.66
0. 61
O. 63
0.70
0.68
0. 59
0. 63
0.63
0.73

 

0.50
0.10
0.35
0. 35
0. 34
0. 62
0.32
0.23
0. 45
0. 44
0. 31
0.43
0.55
0.45
0.51
0.48
0.33
NO

 

0.62
0.59
0.61
0.61
0.60
0.57
0.57
0.58
0.60
0.57
0. 56
0. 58
0.59
0.60
0.60
0.60
0.00
0.60

 

0.40
0. 31
0. 44
0 33
0. 64
0. 41
0.40
0.43
0.53
0.50
0.40
0. 54
0. 53
0.50
0.53
0.58
0.49
0.49

 

 

0.48
0.14
0.31
0.31
0.43
0.50
0.40
0.41
0.51
0.36
0. 31
0. 50
0.53
0.60
0.61
0.50
0.42
0.70

 

0.60
0.63
0.65
0.69
0.45
0.60
0.45
0.50
0.57

0. 61
0. 62
0. 60
0.54
0. 57
0.60
0.60
0.53

 

0.50
0.40
0.50
0.50
0.60
0.60
0.60
0.60
0.60
0.50
0. 60
0. 60
0.40
0.50
0.50
0.60
0.50
0.40

 

0.52
0.42
0.52
0.51
0. 50
0.54
0. 45
0.48

0.50
0. 51
0. 55
0.51
0. 53
0. 55
0. 60
0.43
0.52

0.08
0.20
0.14
0.16
0.11
0.09
0.13
0.11

0.12
0.13
0. 07
0.12
0.08

0.06
0.18

 

0.10

 

 

-3.00
-2.88
-1.85
-1.92
-3.11
-2.07
-3.69
-3.41
-2.40
-2.47
-2.25
-2.44
-2.33
-2.66
-3.59
-1.94
-3.01

 

-2.31

-1.83
-1.83
-1.83
-1.83
-1.83
-1.83
-1.83
-1.83
-1.86
-1.86
-1.86
-1.86
-1.83
-1.83
-1.83
-1.83
-1.83
-1.86

 

 

Table 18 - Rejected Alternative Production Practices Based on Low ISPI

 

 

 

INDIVIDUAL SUSTAINABLE PERFORMANCE INDEXES (ISPI)
EXPERT NUMBER

 

1

3

4

5

7

8

9

11

12

13

Pro
m.

STV.
DEV.

STD.
ERR.

.600
1'-

STU
(0-6)

T-STU
CHEC
K

 

2aa
23c
2ai
2aj
20f
4bd
5b

 

0.56
0.61
0. 57
0. 61
0.31
0.42

NO

 

0.45
0.42
0.49

0.50
0.51
0. 51
0. 43

 

0.56
0.55

0.63
0.58
0.46
0. 58
0.47

 

0.58
0.63
0.60

0.59
0.42
0.53
0.31

 

0.50

0.48
0. 49
0. 58
0.58
0.59
0.59

 

0.59
0.52
0.57

0.50
NO
0.56
NO

 

0.49
0.53
0.43
0. 63
0. 68
0.67
0.57
0.51

 

0.64
0.50
0.57

0. 36
0.42

0.43

 

0.52

0.59
0. 55
0. 62
0. 52
0. 61
0. 61

 

0.60
0.57
0. 50
0. 33
0.50
0.67
0. 63
0. 40

 

0.55

0.55
0. 56
0. 52
0.52
0. 55
0.47

 

0.059
0.057
0.064
0.100
0.115
0. 101

0.099

 

0.019
0.018
0.020
0.033
0.036
0.034
0. 020
0.033

32.73
-3.20
-2.73
-1.18
-2.15
-2.43
-2.59

 

-3.98

-1.83
-1.83
-1.83
-1. 86
-1. 83
-1.86
-1.83

 

-1.94

 

 

166

As evidenced in the preceding tables. five APP were rejected under
environmental criteria. one under social criteria. 18 under economic criteria, and
one that was not previously rejected by using the ISPI. One activity, the
incineration of plastic twine (APP 4bd), was rejected under environmental and

economic criteria.

Some of the activities rejected because of economic criteria merit review
because they are critical for compliance with the law, or because the results

seem irrational. Table 19 Show these activities.

In addition to the activities rejected by statistical test, some activities were
rejected because. according to the experts directly involved in production of
bananas, these activities are not available at the present time. Table 20 lists
these activities. The APP in this list Show promising signs but have not been fully
tested in the field, and the risks of application without exhaustive testing are

beyond justification and acceptance by the producers.

Table 19 - Rejected Activities that Merit Review.

 

APP # SUMMARY DESCRIPTION

 

6j Deposit the reject bananas that cannot be used for industrial production in trenches.

 

7cp Mark areas of herbicide application with labels indicating the date of application and
the re-entry period.

 

7cs Improve hygiene practices (frequent hand washing. prohibition of food consumption
during activities involving handling£f bags, prohibition of smoking).

 

 

 

7cx Use spraying chambers in the packing plants to prevent worker exposure.

 

 

167

Table 20 - APP Rejected Because of Unavailability.

 

APP

 

 

 

 

 

 

 

 

 

 

N° SUMMARY DESCRIPTION
2ad Use biological controls for prevention (i.e., enhanced microorganisms - EM) and treatment
(i.e., Serratia that attacks the cell wall of fungi).
2ba Use biological products:
a. Paecilomycis
b. Plants that attract and trap nematodes, such as Crotalaria.
6. Biological products (enzyme extracts and natural antagonistic substances) that are
safer to workers and to the environment.
The leachate from organic decomposition is an organic material that has recently proven
in laboratory tests (CORBANA) to be successful in combating nematodes.
2bc Apply systemic nematodes applied directly to the stump of the mother plant The daughter
absorbs the nematicide and transports it to the roots.
It is necessary to investigate the level of exudation from the roots and the possibility of
damaging beneficial microorganisms. In addition, it is necessary to verify that there are no
residues in the fruit.
2bd Apply nematicides directly to the roots by means of a hole made with a spike, into which a
gel capsule is inserted. The hole is then covered with soil. ‘
4ag Use reusable bags made of mosquito netting (15 to 20 uses per bag). The fruit must be
covered for only 3 weeks of its growing cycle.
6f Use reusable pallets, made with recycled material that is recycled once it has lost its
operational capability.
7aa Introduce a Sistem of plots assigning all the labor to a group without specialization.
7cq Substitute the clorpyrifos in the plastic bags with insecticides that are less toxic to humans

 

(cypermetrynes).

 

The last requirement to establish the list of BAP is to verify that the CPP

are not acceptable, and require better practices. If the CPP are acceptable. then

the alternative practice must offer a considerable advantage. The same

procedure and parameters were used for testing CPP that were used for testing

the APP.

0.6.

The hypothesis for this analysis is as follows:

Ho: papp= 0.6

H1: [lapp < 0.6

Table 21 lists the CPP that were rejected for having indices lower than

It is important to note that all the CPP that were tested against the

 

168

environmental criteria were rejected. which means that the PE judged them
environmentally unacceptable. All the CPP. that were tested for social criteria
fail to be rejected by the statistical test. This means that the PE assigned ratings
to the conventional labor management practices that were equal or above the

acceptable rating of 0.6.

Table 22 and 23 (lists the BAP for production practices and labor
management practices with their number and a summary description of each
activity. Some of the best available practices were Similar and were common to
two or more categories of activities. One, two or three asterisks noted these
practices. Activities that were given one asterisk correspond to the creation of
buffer zones, two asterisks correspond to the establishment of cover crops. and
three asterisks correspond to the use of organic fertilizers and soil amendments.
Many plantations in Costa Rica have technological packages that include a large
number of the practices included in Table 22 and 23. All of the practices
included in BAP list are presently being used in at least one plantation in Costa

Rica.

169

Table 21 - CPP with Unacceptable Levels of Performance

 

13170

ENVIRONMENTAIT’ERFORMANCE INDICES (ENPI)
EXPERT NUMBER

 

1

3

4

5

7

8

9

11

12

13

15

Mea

ST

DE.

STD

.60
1-
STU
(2)

t-
STU
CK

 

4a

4b

 

 

.600
.600

.600
.600
.600
.600
.600
.600
.600

 

.270
.420
.200
.220
.200
.265

.240
.275
.545
.300

 

.496
.559
.515
.463
.460
.391
.210
.550
.522

 

.600
.600
.600
.600
.600
.600

.600
.600

.600

.320

 

.413
.515
.430
.361
.363
.584
.487

.551
.600

 

.600
.600
.600
.600
.600
.600
.600

.600

.220

 

.290
.550
.200
.240
.200
.300
.540
.460
.400
.420

 

.200
.480
.280
.100
.800
.600
.440
.440
.600
.320

 

.364
.465
.209
.309
.314
.325
.150
.150
.230
.275

 

.280
.600
.200
.200
.200
.200
.200
.400
.600
.500

 

.416
.451

.138
.163
.258
.227
.380
O

O

 

.412
.531
.383
.348
.409
.429
.390

.440

.525
.369

 

.15 .

.07

.18 .

.19
.22
.17
.18
.15
.12
.13

 

.07
.05

.05

 

4.28
3.37
3.74
4.39
2.93
3.39
3.76
3.47
1.96
5.72

 

1.81
1.81
1.83
1.81
1.81
1.31
1.81
1.83
1.83
1.94

 

 

170

Table 22 - Best Available Production Practices

 

 

 

 

 

 

 

 

 

 

 

 

0
N SUMMARY DESCRIPTION
FIELD PRACTICES
GENERAL PRACTICES
Planting and Control of Population -
1ab Divide the area of production into 11 parcels and totally renew one parcel per year.
1ac Rotate areas that do not meet the minimum established level for efficient productio
and keep these areas in fallow for at least one year.
1ad To renew the areas in production, plant the seedlings in bags of compost and-or
bokashi (4 kg per bag).
1ae(*) Reforest the banks of rivers, streams, springs and along roads with quick growing
species of medium height.
1af(*) greats a buffer zone at least 15 m wide around the perimeter of the plantation.
FIELD PRACTICES
Drainage
1ba Design rational drainage system using engineering methods.
1bc Plant renovated areas by shaping the floor of the plantation into domes to improve the
system of superficial drainage.
1bd (“) Plant and maintain a cover crop on the floor of the plantation.
1ba Construct sediment traps in the secondary and tertiary canals.
PEST MANAGEMENT
Control of Black Sigatoka
23b Introduce monitoring techniques for prediction and methodology for decision making
based on the ecology and biology of the plantation, the characteristics of the fungus.
and climatic conditions.
2aa Use a helicopter to Spray fungicides in specific places where an airplane is not
effective or could cause problems.
2af(*) Reforest a minimum strip of 15 m along the banks of rivers, streams, Springs and
along roads with quick growing species of medium height
2ag(‘) Create a buffer zone at least 15 m wide around the perimeter of the plantation. This
zone should be planted with native species to restore the ecosystem and improve
biodiversity.
2ah(“) Plant and maintain vggetative cover in the draiEge canals.
PEST MANAGEMENT
Control of Nematodes
2bb Introduce organic material into plantation soil to promote organisms antagonistic
toward pathogenic nematodes.
2ba Use application systems with returnable security packaging (is. Surefill).
2bf Plant and maintain a cover crop to improve the retention of the nematicides and to
reduce the risk of witgr contamination.
2ca('*) PEST MANAGEMENT
2cb(“) Control of Weeds
Plant a vegetative cover crop on 70 - 80 % of the floor of the plantation.
26c(*") Establish an acceptable threshold for vegetative cover on the floor of the plantation
and maintain the maximum acceptable cover.
26a

 

Cover plantation soil with minicompost piles that generate organic manure and act as
mulch to prevent the growth of weeds. -
Use low volume sprayng systems for the application of systemic herbicides.

 

 

171

Table 22 (Cont’d)- Best Available Production Practices

 

 

 

 

 

 

 

 

 

 

 

 

 

N° SUMMARY DESCRIPTION
FERTILIZATION
3a Design fertilization programs based on soil studies, the climate, and the requirements
of the cultivation.
3b Increase the frequency of applications and reduce the amount of fertilizer per
application.
36 Vary the forms of fertilizer application according to the weather and edafic factors.
3d Use application techniques that localize fertilizer in the most apprOpriate locations for
plant uptake.
3e(*“*) Complement fertilizers with applications of organic biological products and compost
3f Apply micronutrients via aerial Spraying to complement normal fertilization.
39 Apply humic acid complemented with micro- and macro-nutrients that can be applied to
the leaf and/or the soil.
3j(*") Plant and maintain cover crops to capture and released the fertilizer slowly.
3k(*) gtgblish a buffer zone between areas where fertilizer is applied and the canals.
FRUIT CARE
Bagging
4aa lntercalating bags with and without insecticides in areas with low Colaspis pressure,
carefully monitoring the farm for insect pests and damage.
4ab Use a “necktie system“ introducing a strip of material impregnated with insecticide
inside the bag instead of impregnating the bag itself.
4ac Use a continuous roll of plastic instead of precut bags (Layfiat).
4ad Use high de_nsity polyethylene bags.
FRUIT CARE
Propping
4bb Install overhead aerial support systems.
4ba Use twine made with 20 to 40% recycled resin.
40f Use continuous rolls of twine dispensed from a backpack and cut with an appropriate
tool.
HARVEST
5a Remove the hands from the bunch in the field to avoid the use of cushions.
5C Deflower the fingers in the field to eliminate Microlepidoptera larvae and organic
residues in the packing plant.
5d Pre-wash the fruit by setting up sprinklers along the cable way to lubricate and freshen
the fruit during transport.
PACKING
6a Use packing material that is recycled and recyclable.
6b Redesign the tanks to reduce the volume of water used, and recycle the water through
the selection tanks.
66 Purify the water so the water used throughout the packing process can be recycled.
6d Install filters to treat the effluent water that is contaminated with agro-chemicals.
69 Certify the wooden pallets.
69 Use the rejected fruit as a source of organic material for making compost.
6h Process the stem of the bunch for compost, paper, or other uses.
6| Redesign maintenance areas so the floors are impermeable and spills of grease and
combustibles can be contained.
6k Use spraying chambers and modify the conventional hydraulic spray nozzles to
electrostatic nozzles, considerably reducing the volume of application and avoiding
spilling and loss.
6m Relocate and redesign the warehouses for agro-chemicals and the plastic bags

 

impregnated with insecticides to reduce the risk of environmental contamination and to
increase the safety of the workers.

 

 

172

Table 23 - Best Available Labor Management Practices

 

 

 

 

 

 

N° ; SUMMARY DESCRIPTION
HIRING PRACTICES
7ab Implement a system of bonuses for quality and yield of work.
730 Create a bonus system that promotes attendance and prevention of accidents.
7ad Pay the severance benefit for good workers each six months as a premium for their
work.
7aa Require that all contractors comply with the laws and regulations concerning workers’
r_ights, including those clauses related to the safely guidelines and hygiene.
FRINGE BENEFITS
7ba Actively collaborate with local authorities and neighborhood development associations
to improve public services in the communities surrounding the plantation.
7bb Help workers to construct their own homes in the neighboring communities.
7be Help workers to construct and operate a transportation company to provide transport
services for employees and students.
7bd Help to construct and maintain a community cultural clubs.
7be Establish a system of nursery schools so women have the same opportunities as men
to work in the plantation.
7bf Establish a training program for the families of the workers to promote the creation of
micro-enterprises that provide services to the plantations and the communities.
7bg Designate land not used for banana production as space for family gardens for the
workers.
7bh Promote religious activities within the plantation community and in neighboring
communities.
7bi Promote organizations that support women and families.
LABOR MANAGEMENT PRACTICES
RISK PREVENTION
7ca Strengthen the occupational safety unit.
7cb Fund a preventative medicine unit that includes a company doctor.
7cc Create a data bank to track occupational accidents.
7cd Include a labor contractual clause requiring the use of safety equipment
7ca Establish an obligatory orientation course for all workers.
7cf Establish a unified training program and license workers to cany out high risk jobs.
7cg Institute routine, programmed safety courses for pilots. warehouse employees, and
mixing plant operators to improve the operation of the airport facilities.
7ci(*) Create protection and buffer zones of at least 100 in between the plantation, the
packing plant, and employee living quarters.
7cj Evacuate field workers before aerial spraying and observe re-entry period
7cl Guide aerial spraying by using a “Flying Flagman' system or with GPS.
7cm If a GPS system is not available, use mobile globes.
7co Partially eliminate the use of herbicides and control weeds manually.
7cr Determine the bass range of cholinesterase in each worker who is in contact with
clorpyrifos and monitor blood levels every three months.
7ct Install aerial support systems for propping banana plants.
7cv Redesign the workplace with ergonomics in mind.
7cw Relocate and redesign warehouses for agro-chemicals and plastic bags to improve

 

workers’ safety and minimize the risk of environmental contamination.

 

 

173

The establishment of a list of BAP, allowed for the calculation of the mean
ENPI, SOPI, and ECPI for each of the categories included in the SS. Table 38
Shows the results of this procedure and the indices (ENPI, SOPI, and ECPI) for
the CPP. This table was included in Appendix C because it was very extensive.
These resulting mean values were introduced into the SS to calculate the SPlepp

and SPIbab and the results are reported in the next section.

Table 24 - CPP with Unacceptable Levels of Performance

 

ENVIRONMENTAL PERFORMANCE INDEXES (ENPI)

EXPERT NUMBER 0.60

 

 

1

3

4

5

7

8

9

11

12

13

15

Mean

STD
DEV

STD
ERR

'r.
STU
(2)

STU
CK

 

1a
1b
2a
2b
2c

4a
4b

 

0.600
0.600
0.600
0.600
0.600
0.600
0.600
0.600
0.600
NO

 

0.270
0.420
0.200
0.220
0.200
0.265
0.240
0.275
0.545
0.300

 

0.496
0.559
0.515
0.463
0.460
0.391
0.210
0.550
0.522
NO

 

0.600
0.600
0.600
0.600
0.600
0.600
0.600
0.600
0.600
0.320

 

0.413
0.515
0.430
0.361
0.363
0.584
0.487
0.544
0.551
0.600

 

0.600
0.600
0.600
0.600
0.600
0.600
0.600
NO

0.600
0.220

 

0.290
0.550
0.200
0.240
0.200
0.300
0.540
0.460
0.400
0.420

 

0.200
0.480
0.280
0.100
0.800
0.600
0.440
0.440
0.600
0.320

 

0.364
0.465
0.209
0.309
0.314
0.325
0.150
0.150
0.230
0.275

 

0.280
0.600
0.200
0.200
0.200
0.200
0.200
0.400
0.600
0.500

 

0.416
0.451
NO

0.138
0.163
0.258
0.227
0.380
NO

NO

 

0.412
0.531
0.383
0.348
0.409
0.429
0.390
0.440
0.525
0.369

 

0.15
0.07
0.18
0.19
0.22
0.17
0.18
0.15
0.12
0.13

l

l

 

0.04
0.02
0.06
0.06
0.07
0.05
0.05
0.04
0.04

 

-4.28
-3.37
~3.74
-4.39
-2.93
-3.39
-3.76
-3.47
-1 .96
-5.72

 

-1.81
-1.81
-1.83
-1.81
-1.81
-1.81
-1.81
-1.83
-1.83
-1.94

 

 

4.9 Sustainable Performance lndices (SPI)

Using the results reported in the previous sections, the SS hierarchical
structure was programmed into ECPro and the corresponding SPI calculated.
One individual program was created for each expert because the intensities were
different. The SPI values for the CPP and BAP for each of the experts were
introduced into the experimental design matrix (Table 25 in section 4.10). The
ten experts fill the rows of the matrix. The columns contain the SPlcpp for each

expert, the second column contains the SPlbap for each of the corresponding

174

experts, and the third column holds the value representing an acceptable level
for performance index (0.6). The completion of the experimental design matrix
makes it possible to test the hypothesis. The next and final section of this

chapter presents the results of the hypothesis testing.

4.10 Hypothesis Testing

The objective of this dissertation. as stated in its title. was to design a
systems method for evaluating the sustainability Of ag-production. Banana
production for the export market in Costa Rica was chosen to test the method.

Correspondingly, the following questions were asked:

0 Can a suitable quantitative measuring method be devised to evaluate the
sustainable performance of agricultural production practices?

0 Can appropriate quantitative ordinal sustainability indices be developed to
evaluate banana production processes?

To answer these questions, a method was designed that contemplated a
mathematical procedure to derive indices to test sustainable performance. The
adequacy of the proposed method was to be tested by answering the following

questions:

1 Is the current banana production in Costa Rica sustainable?

0 If not, what changes can be implemented to improve sustainability?

175

Accordingly. the proposed hypotheses were the following:

Hypothesis A
Ho: The CPP are environmentally, socially and economically
acceptable.
H 1: The CPP do not environmentally, socially and economically
acceptable.
Hypothesis B
Ho: The BAP are environmentally, socially and economically
acceptable.
H1: The BAP are not environmentally. socially and economically
acceptable.

The experimental design used for this dissertation was a two-way
classification matrix using three treatments and ten repetitions. The treatments
were conventional production practices, best available practices and minimal
acceptable sustainable practices. The three treatments were organized in the
columns of the matrix. The repetitions were the indices derived from the opinions
given by the ten experts. Table 25 presents the experimental design matrix with
the values resulting from the calculation of the SPI for CPP and BAP for each
expert. The scale used to judge sustainable performance, stated that acceptable
performance requires an SPI equal or better than 0.6. lndices below 0.6 were
not acceptable. For this reason the third column of the matrix was filled by an

index value of 0.6.

176

Table 25 - Experimental Design Matrix

 

Two levels of testing were proposed. In the first level, a one-way analysis
of variance (ANOVA) procedure was proposed to test if the two sets of data were
samples of the same population and if the mean of those samples was
statistically equal to 0.600. In mathematical terms, the hypothesis to be tested

was expressed as follows:

Ho: [JCpp = Ubac = 0.600

H1: [.lcpp #3 [.Lbacab 0.600

A significance level of 0.05 was chosen for this analysis.

Table 26 shows the descriptive statistic and table 27 shows the results of
the ANOVA. From the results. it is evident that for a Significance level of 0.05 the
null hypothesis is rejected. In order not to reject the null hypothesis. it would be
necessary to use a significance level of 0.001. Figure 4.26 was given as part of
the results using MINITAB which was very illustrative. The figure represents

theoretical acceptance range of values at a confidence level of 95% and using a

177

pooled standard deviation for the three columns being tested. The SPIcpp data
set apparently had a minimal area of its acceptable range of values that overlaps
the “acceptable index value" theoretical acceptance range of values. The
SPlbap had a larger area of overlap. This meant that the SPlbap were closer to

0.6 than the SPIcpp.

Table 26 - Descriptive statistics of the two samples

AN
DEWATK”!

 

Table 27 - Results from the ANOVA Using MINITAB

SQUARE

 

178

 

-+ ......... + ......... + ......... + .....
SPIcpp ( ------ * ------ )
SPIbap ( ------ * ------ )
Acceptable ( ...... * ...... )

0355 """" 0'. figs """" a. $8 """" 5358""

 

 

 

Figure 11 - Individual 95% Confidence Intervals for Mean Based on Pooled
Standard Deviations

The rejection of the null hypothesis means that at least one of the data
sets is not a sample of the same population. It was necessary to do a second
level of analysis to identify which set or sets of data were not equal. For this
analysis, one-way ANOVA was performed comparing SPIcpp with SPIbap (Case 1),
and then comparing SPlbap with 0.600 (Case 2). The procedure was repeated
comparing SPIcpp with 0.600 (Case 3). The hypothesis to be tested is expressed

in mathematical terms as follows:

Case 1
H03 llcpp = llbap

H13 llcpp + Ilbap

179

Case 2
Ho: [.lbac = Acceptable = 0.600

H1: [.lbac=[= 0.600

Case 3
Ho: [..Icpp = Acceptable = 0.600

H1: [lcpp=[=0.600

The results are shown in Tables 28. 29. and 30. According to these
results, in the first and third cases the null hypothesis was rejected at a
Significance level of 0.05. In the second case the null hypothesis was not
rejected. The significance of these findings is that there is a considerable
difference between SPIcpp and SPlbap, that SPIbap is statistically equal to the
acceptable level of performance, and that SPIcpp is at an unacceptable level of
performance. Therefore, the answer to the question - is the current banana
production in Costa Rica sustainable? is no, assuming that the CPP is
representative of the industry. Since SPIbap is equivalent to 0.60 (acceptable
sustainable performance). the answer to the question - what changes can be
implemented to improve sustainability? is given by the list of activities in Table

4.12 and 4.13.

180

Table 28 - Results of Comparison of SPIcpp with spibap Using MICROSTAT

 

 

 

 

 

 

 

 

 

 

Group Mean n
1 .548 10
2 .636 10
Grand Mean .592
SOURCE SUM OF DEGREES MEAN F RATIO PROB.
THE OF SQUARE
SQUARES FREEDOM (MS)
‘ (SS) (DF) _
Between .039 1 .039 13.244 .001876
flthin .053 18 .0029303
Total .092 29

 

Table 29 - Results of Comparison of SPIbap to 0.600 Using MICROSTAT

 

 

 

 

 

 

 

 

 

 

 

Group Mean n
2 .636 10
3 .600 10
Grand Mean .618
SQU"R'C'E' SUM OF D—EGREES—TEAN F"RA' Tio” F"RoB.
THE OF SQUARE
SQUARES FREEDOM (MS)
‘ (SS) (DF)
Between 0065885 1 0065885 4.283 0.053
Within .028 18 .0015384
“Total .034 29

 

Table 30 - Results of Comparison of SPIpr to 0.600 Using MICROSTAT

 

 

 

 

 

 

 

 

 

 

 

Group Mean n
1 .548 10
3 .600 10
Grand Mean .574
SOURCE SUM , OF— DEGREES' -M_EAN FRA' TIO PROB.
THE OF SQUARE
SQUARES FREEDOM (MS)
(SS) (DF)
_BeTween .013 1 .013 9.639 .006116
lvtthin .025 18 .0013919
Total .038 19

 

 

 

 

181

As stated in section 4.2, the composition of the PE was carefully balanced
including half of its members as being directly involved with production of
bananas, and the other half indirectly involved. To justify the selection process, it
was important to identify if there were differences in the sustainable performance
indices derived from the opinion of each segment. A one-way ANOVA was
performed comparing the indices of one segment against the other. The

hypothesis for this test is as follows:

Ho: ”prod. = [lnon-prod.

H1: [.lprod.+ [.lnon-prod.

The results of this analysis are shown on Tables 31, 32 and 33.
According to the results of the test, the null hypothesis was rejected. The two
sets of data are different at a Significant level of 0.05. However. it is important to
note that at a Significance level of 0.0238, the null hypothesis would not be
rejected. This means that the normal distribution curves for both sets have

almost no overlap. Figure 12 illustrates this information graphically.

Table 31 - Tabulation of SPI by Segment of PE

PROD. -. it ' NON-PROD

 

182

Table 32 - Descriptive Statistics of the Two Segments

NAM n l
DEVIATION
. 1

 

Table 33 - Results of Comparison of SPIpr to 0.600 Using MICROSTAT

 

 

 

 

 

Figure 12 - Individual 95% Confidence Intervals for Mean Based on Pooled
Standard Deviations

183

By observing the descriptive statistics, it was evident that the experts in
the segment that were not directly involved in production, had a wider range of
opinions (.1085 point spread versus .44 and a standard deviation of 0.0452
versus 0.0196), and that they were more likely to give lower ratings. The
explanation stems from the fact that the non-production segment of the experts
was involved in a wider range of activities and was less homogeneous than the
segment that is directly involved in production. Furthermore, the segment
directly involved in production could not afford the luxury of being pessimistic

about banana production because it was their source of financial sustenance.

The previous sections of this chapter have described and illustrated the
results in tables and figures. Remarks were made pointing out the importance of
the results and explaining them. In the next chapter, the author has the charge
of making sense of the results, drawing conclusions and offering

recommendations.

Chapter V

FINDINGS, CONCLUSIONS AND RECOMMENDATIONS

5.1 Introduction

The purpose of this chapter is to interpret the results presented in the
previous chapter in search of an answer to the researchable question object of
this dissertation. With the intention of ordering this procedure. section 5.2 of this
chapter revisits the problem statements presented in Chapter One. Section 5.3
examines the researchable question and dissects it into its components. Section
5.4 - Findings and Conclusion - submits the answers to the researchable
questions. Section 5.5 presents recommendations, and section 5.5 presents the

concluding statements

5.2 Problem Statement

The facts presented in Chapter One and Chapter Two of this document

sustain the following problem statements:

0 All agricultural production practices introduce disturbances in the ecosystem
and have a resulting impact on the environment, society, and the economy.
A production practice is sustainable when the negative impact on society and
the environment are minimized, and the benefits (present and future) to
society and the economy are maximized.

o The environment has the resiliency to assimilate a moderate amount of‘
disturbance. Conventional production practices (CPP) for growing bananas
introduce a massive disturbance in the ecosystem and their impact may be
beyond the limits of the environment to absorb the insult. Therefore, banana
CPP may not be performing in an environmentally sustainable manner.

184

185

0 Banana CPP brings many benefits to the workers and their families,
neighboring communities and the nation. but they also may be directly or
indirectly responsible for part of the serious social problems evidenced in the
banana production region. Furthermore, banana exports require a large
national resource investment that generates a substantial economic benefit
to few transnational firms, national firms, and individuals. Conventional
development paradigms rely on the trickle down effect for benefits to reach
all the stakeholders. The present structure of ownership and marketing of
bananas may provoke a deficient distribution of benefits. Therefore, banana
CPP may not be performing in a socially sustainable way.

0 The present banana market conditions may be generating insufficient
economic benefits to Costa Rica that may not compensate the negative
impact on the environment and society. Therefore, CPP may not be
performing in an economically sustainable pattern.

0 Consequently, the banana CPP used in Costa Rica may not have an
acceptable sustainable performance level and it may be necessary to identify
and introduce the better practices (BAP) to improve the net benefit.

0 BAP also have negative impacts on the environment, the society and the
economy. Therefore, BAP may not achieve an acceptable level of
sustainable performance.

0 If both CPP and BAP are not performing to a desired level of sustainability,
then it may be advisable to abandon banana production. However.
abandoning banana production may have a catastrophic impact on the
environment, society and the economy of Costa Rica. Furthermore.
alternatives to banana production may perform in a less sustainable manner.

These problem statements introduce a sequence of uncertainties that are
considerably important to decipher for the future of countries that have a large
dependency on cash crops for their current well being. To clarify these
uncertainties. it is critical to collect, appraise and organize information, under a
systematic method. A systematic method allows the analyst to clarify the
questions latent in the problem statements, to identify components of the system
that require immediate change, to appraise alternative solutions, and to
recognize areas that demand further research and development. The end-result
is an appropriate set of recommendations that aid the decision makers in taking

sustainable actions. The objective of this dissertation was to propose and test a

186

systematic method of analysis for evaluating the sustainable performance of
agricultural production practices. It uses banana production for the world market
to test the adequacy of the method. The researcher recognizes that there are
not enough “hard facts” available at this time and relies on the opinion of a panel

of experts.

The first task was to outline a working definition of sustainable banana
production. The following definition was adopted after an extensive review of the

literature and consultations with several of the members of the PE,

“The sustainable production of world-class bananas is a broad
spectrum of agro-cultural practices that includes the efficient and
rational use of natural resources and the agroecosystem. It seeks
to ensure long-range production, productivity, and profitability by
maintaining and improving the resource base and preventing
environmental degradation. lt distributes costs and benefits fairly
and equitably, and respects community values and principles, all
with the objective of satisfying society's present and future needs.
and improving the quality of life of the community". (Synopsis of
concepts expressed by del Camino and Muller. 1993 and Tabora,
1991, and CSA, 1992)"

The challenge was to construct a model of world-class banana production
in Costa Rica that adequately fits this definition and answers the questions
inferred in the problem statements. After the model was delimited, the challenge
was to devise a suitable quantitative measuring method to evaluate and relate
the effects of production practices on the environment, society and the economy.

This implied the development of a quantitative method of calculating

187

sustainability performance indices to evaluate production processes. The
resulting indices, to be judged appropriately. had to answer the questions of the
problem statement with a reasonable degree of confidence and replicability for

most agricultural practices.

5.3 Researchable Questions

The question object of this dissertation was - Is it possible to attain a
sustainable production system of world-class bananas by modifying the
conventional production technology presently used in Costa Rica without
Significantly changing the market component? Because of its complexity, It was

prudent to dissect this question into its components.

1. What are the important criteria that must be met in order to perform in a
sustainable manner?

2. What are the conventional banana production practices (CPP) in Costa
Rica?

3. Are the CPP performing in an environmentally. socially and economically
acceptable manner?

4. Are there best available practices (BAP) that have a better environmental,
social and/or economical sustainable performance?

5. Should banana production for the export market be abandoned?

6. What areas should be further researched and developed to improve

sustainable performance?

 

1° Defined by Hernandez, C. 1996. Guacimo, LimOn: Escuela de Agricultura de la Regibn
Tropical Hi’imeda. Edited by: Rincbn H.. Fallas, C. and Alfaro, M., and translated to
English by Judy, W.

188

7. IS it necessary to Significantly change the market component of the system
in order to improve the sustainable performance of banana production for
the export market?

8. Was the analytical method proposed appropriate to answer the previous
questions?

5.4 Findings and Conclusions

This section will address each of the eight questions proposed in the

previous section by interpreting the information presented in Chapter IV.

5.4.1 What are the important criteria that must be met in order to perform
in a sustainable manner?

There was unanimous agreement among the members of the PE that the
criteria for sustainable performance contain three major components:
environmental, social and economic criteria. Furthermore, there was general
conformity among the experts that these components could be subdivided into
criteria and sub-criteria forming a pyramidal hierarchical structure with different
levels of detail. Figures 15 through 36, are a product of review and consensus
by the experts. No individual objections were presented to any of the criteria or
sub-criteria presented in the figures. Therefore. it can be concluded that the
criterion variables used in this research, and presented in Figures 15 through 36,
represent reasonably the important criteria that must be considered to evaluate
agricultural production activity, and to judge them with respect to their degree of

sustainable performance.

189

5.4.2 What are the conventional banana production practices (CPP) in
Costa Rica?

After the interview process. it became evident that few banana production
companies in Costa Rica have exactly the same production practices. Different
environmental conditions among areas of production require each plantation to
customize its technological package. Furthermore, edafic differences within
plantations require adjustments and customized procedures for each section of
the plantation. Financial constrains limit a large number of producers in adopting
some well-recognized best available practices. These differences contribute to
the great disparity in level of sustainable performance among banana plantations

in Costa Rica.

Table 35 in Appendix 8, contains a base line definition of CPP used to
compare and rank the alternative production practices. It is a compromised
definition and none of the experts agree with every stipulation. Therefore, this
description of CPP cannot be generalized and used to characterize the standard
practices of the industry because they do not exist. Some plantations have a
technological package that is similar to the one described in this document, some

apply more advanced practices and some have a less sophisticated package.

For this reason, the method applied in this dissertation is not appropriate
to determine the level of sustainable performance of the entire banana growing
industry of Costa Rica. It is only appropriate to rate the sustainable performance

of individual plantations.

190

5.4.3 Are the CPP performing in an environmentally, socially and
economically acceptable manner?

The CPP. as described in the base line definition used in this dissertation,
were rated holistically below the acceptable sustainable performance level of 0.6.
The mean SPIcpp value awarded was 0.548, which corresponds to a descriptive
rating that is situated between moderately unacceptable (0.4) and acceptable
performance levels. Even the lowest value given by the experts places the CPP
within this descriptive rating level. It is also evident that even the most optimistic

of the experts did not rate the CPP much above acceptable.

If the indices are examined before aggregation, the CPP failed the
environmental criteria (mean ENPI = 0.435), but received an acceptable rating in
the social criteria (mean SOPI = 0.631). Furthermore, it is Significant that there iS
unanimous consensus that if Costa Rica decides to abandon banana production
for the export market, there would be a highly negative effect (mean SOPI =
0.194) on the workers. their families. and the local communities in which they

live.

At the present time, not all banana plantations in Costa Rica are
economically sustainable. An important group of farms are under the
management of the banks because they were not able to meet their financial
obligations (ANAPROBAN, 1995). According to the experts. the majority of the
farms are breaking even or have low profits. Most producers have adopted

strategies to contain costs and to survive until there are better market conditions.

191

5.4.4 Are there best available practices (BAP) that have a better
environmental, social and/or economical sustainable performance?

Table 22 and 23 contain an extensive list of best available practices that if
applied improve considerably the sustainable performance of the CPP as they
are described in this document. Many of these BAP are already being applied by
a large number of farms. All of the BAP in the list are successfully being applied

in at least one farm.

A considerable group of BAP. contributes favorably to the environmental
performance of more than one category of activities. Evidently the creation of
buffer zones, the establishment of ground covers and the addition of organic
matter to the soil of the plantation. are practices that Significantly decrease the
negative impacts of banana production on the environment. All three categories
contribute to the conservation and restoration of biodiversity. However, it is
crucial to recognize that increasing biodiversity includes the addition of
organisms that are health threatening to the workers. such as snakes and
insects. It is also important to note that there are more accidents caused by cuts
and bruises than there are due to accidents with agrochemicals. Therefore. the
implementation of BAP requires considerable planning and modifications of

safety procedures.

Notwithstanding, the relatively acceptable social ratings given by the
experts to the CPP, there is a large list of activities that would enhance the

quality of life of the workers, their family and the local community where they live.

192
It is noteworthy that many of the BAP included in the list are related to risk

prevention.

Most of the BAP have an important impact on the economic sustainability
of the system. For this reason. the mean SPlbap rating given by the experts
drops to a level close to 0.6. As stated before. many of the plantations have
difficulty implementing these practices because they are very close to the break
even point and have adopted strategies to reduce costs until there are better
market conditions. However, many plantations that have adopted some of the
BAP manifest that the increment in costs is temporary, that costs tend to return to
the original level and in many cases they tend to decrease after the initial phase.
For this reason. growers need to implement the recommended BAP on a gradual
manner. Growers need to choose from the list of BAP those which best fit their
operational conditions, and those that make the largest positive impact. The
implementation of too many BAP in too short a time can lead to serious

economic and agronomic problems.

5.4.5 Should banana production for the export market be abandoned?

Judging from the results. banana conventional production practices, as
defined in this dissertation, are at worst moderately unacceptable, and there are
a large number of best available practices that make it possible to improve.
Furthermore, there is consensus among the experts that to abandon banana
production would cause a social catastrophe suffered primarily by the workers,

their families and the local communities. If Costa Rica abandons banana

193

production for the export market. there still would be a market demand and the
transnational companies would probably transfer their operations to other
countries with lower environmental and social requirements. In conclusion. the

answer to this question is a definite and emphatic no.

5.4.6. What areas should be further researched and developed to improve
sustainable performance?

Since resources are limited. it is important to use the intensities assigned
by the PE to identify the areas where the allocation of resources has the largest
impact on the environment and society. The intensities given by the experts to
the three principal components of sustainability — environmental, social and
economic — were approximately equal. Vlfithin the environmental component, the
field activities predominated with 64% of the weight. Of the field activities, pest
management received the highest weight (39%), followed by general practices
(30%). There was no doubt in identifying the control of black Sigatoka as the

most impacting practice on the environment.

Within the context of the previous paragraph, it is important to make
reference to Table 20. This table presents a list of APP rejected because they
require further research. This list includes activities related to biological pest
management. Research emphasis Should be given to these activities because
their impact on the environment and costs is critical and decisive for improving

sustainable performance of banana production.

194

Within the social component of the system. hiring practices was given the
highest priority, closely followed by risk prevention practices. Since the banana
workers of Costa Rica are the highest paid agricultural workers in the country
and the highest paid banana workers in the region, improvement in this area is
limited without out-pricing Costa Rica’s bananas in the world market. In contrast,
risk prevention is of utmost importance to preserve the quality of the workers and
their ability to maintain their jobs and sustain their families. Investment in risk
prevention reduces cost to the plantation owner by minimizing unproductive time
and safeguarding the training investment made in each worker. It is critical to
recognize that good health is a prerequisite for good quality of life, and good

quality of life is a crucial objective of sustainable development.

Examining the economic component (Figure 9). the largest effect is
manifested in the inputs (49.7%). The highest cost input is packaging (40.5% of
the inputs). It iS interesting that the experts did not provide any significant cost
reduction best available practice for packaging. This indicates that the
conventional practice is the best available for the quality standards demanded by
the market. It also indicates that there is a great need for further research and

development in this area.

The fungicides (15.5% of the inputs) are the second most important item
of the inputs and black Sigatoka control contributes greatly to this item. Pest
management and Sigatoka were already identified as areas that are critical.
Economic considerations re-enforce the necessity for further research and

development in black Sigatoka control.

195

The second most important item in the economic component is the labor
component (31.8%). Salaries and Benefits constitute the majority of cost. Risk
prevention is a hidden cost component included in this item that was already

identified as a critical area for research and development.

4.5.7 Is it necessary to significantly change the market component of the
system in order to improve the sustainable performance of banana
production for the export market?

The results demonstrate that it is possible to make a significant difference
in the sustainable performance of banana production without changing the
market component of the system. It is also true that the burden for change is
being placed on the producer and not on the consumer. As stated before, many
producers are close to the break-even point due to low market prices and are

hesitant to accept changes unless costs are maintained constant or are lowered.

Price recognition for producers adopting better production practices is a
powerful catalyst for the prompt adoption of BAP. A higher price for products that
do not physically evidence quality differences is difficult to achieve under the
present market structure. However, in a buyer's market, where there is excess
production, marketing companies are open to use product differentiation methods
to improve their market share. To recognize products produced under BAP. the
consumer needs a reliable and well-recognized labeling system. There are many
organizations and methods for awarding green labels and a few for issuing good
trade practice labels. ChiqUita has chosen to use the ECO-OK label as a means

of improving their image and as a mechanism of differentiating their bananas

196

from those of the competition. Companies like Del Monte have chosen to pursue
certification under ISO 14000 because it is an lntemational organization that is
recognized in the United States and Europe. The method tested in this
dissertation can be integrated into the ISO 14000 and the ECO-OK certification

methodology.

5.4.8 Was the analytical method proposed appropriate to answer the
previous questions?

The systematic method of analysis proposed provided significant results,
allowing the researcher to answer the questions with a reasonable level of
confidence. The results permitted statistical synthesis, analysis and hypothesis
testing. There was no indication that this method had any problems of

applicability to other agricultural activities.

The steps necessary to complete the analysis are well defined and are
easily replicated. However. the method, as used in this research. is highly
sensitive to the composition of the Panel of Experts. It is critical to have a
balanced multidisciplinary panel that includes experts working in the full range of
task related to the agricultural activity in question. Othenrvise, the results may be

skewed and not replicable.

Using focus interviews instead of the Delphi method for the first interview
may enhance the performance of the Panel of Experts. The focus interview
allows for the interchange of ideas and the arrival of consensus opinions. The

disadvantage is that the researcher cannot be committed to maintaining

197

confidentiality. This would limit the participation of some experts whose job
security may be threatened by their opinions. In this case an important segment
of participants may be limited and the results may be skewed. It is important to
keep the second interview on an individual basis because the focus interview
limits the application of statistical methods for synthesis, analysis and hypothesis

testing.

As stated in section 5.4.3. the CPP described for this research are not
necessarily representative of the banana growing industry. For this reason, the
method. as applied inthis dissertation, is not appropriate to determine the level of
sustainable performance of the entire banana growing industry of Costa Rica. It
is only appropriate to rate the sustainable performance of individual plantation.
As such. it is an appropriate method for awarding market labels to individual

plantations.

In order to emit an accurate generalized judgment on the industry, it is
necessary to evaluate every plantation and aggregate the results. This is a
monumental undertaking that requires the consensus of all the owners Since
property rights are well defined and respected in Costa Rica. A viable
alternative, but less accurate, is to choose at random a significant number of
plantations. apply the method and aggregate the results. This procedure
requires institutional sponsorship and assurance of confidentiality. Otherwise the
individual researcher will probably encounter resistance by the owners of the
plantation since the information gathered may reveal trade secrets or may be

used to discredit their operation.

198

One of the members of the PE criticized and questioned the method used.
His opinion is noteworthy and should be recorded. His convictions prevented
him from assigning weights to the three fundamental elements of sustainability —
environmental, social and economic. To him each element deserves 100% and if
one fails all fall. In his View, sustainability has to be looked at as an organism,
which has several vital organs that allow it to survive. If one vital organ fails, the

organism dies even if the other organs are perfectly healthy.

Assuming that the organism's analogy is valid, homeostasis maintains the
equilibrium regulating and compensating the different interactions among the
other organs. before total failure occurs in one organ. This permits the organism
to regenerate or repair the organ that is malfunctioning. From the results
obtained in this research. evidently the situation has not reached fatalistic
consequences. It is still possible to compensate the Shortcomings of one
component with the benefits of the others. Furthermore, there is a long list of
BAP that can be used to improve the shortcomings of the present system. Thus
the separation of sustainability into its three basic components (environmental,
social and economic) and the assignment of weights or intensities is justifiable

using the organism's analogy.

In conclusion, the overall results of the method proposed were
satisfactory. The method proved to be useful for gathering, organizing and
analyzing large quantities of complex subjective and objective data. It is
sufficiently sensitive to allow the user to draw conclusions. The method can be

applied to other agricultural production activities and can be replicated.

199

Notwithstanding its overall success. it proved to have Shortcomings that must be
adjusted for better results. These Shortcomings will be addressed in the
following section - Recommendations. Since the proposed method has merits
and may be used for prospective applications. the name Sustainability
Performance Evaluation Method and the acronym SPEM will be used for future

reference.

5.5 Recommendations

The overall success of the application of SPEM for rating agricultural
production practices according to their sustainable performance index and the
opportunities available for future use. motivates the researcher to make the

following recommendations:

0 SPEM. as applied in this research. was dependent on subjective evaluation
data for the environmental and social components. SPEM easily allows the
incorporation of “hard facts” as they become available. Furthermore, SPEM
is flexible permitting the inclusion of more levels of detail. To validate the
results of this dissertation, it is recommendable to use the cause and effect
diagrams (Figure 15 through 36) to identify future studies. Preferably, these
investigations should be Specifically framed within the environmental and
social components to derive data based on objective facts.

0 It is advisable to identify an organization that represents all the banana
industry’s stakeholders to develop the full potential of SPEM. The
Environmental Banana Commission is the banana industry’s forum for the
discussion of environmental issues. The representatives of all the banana
industry’s stakeholders integrate CAB. Because of the intimate relationship
that the environment has with the social and economic elements of the
system, CAB can easily be amplified to include them into its platform. In its
modified form, CAB can become an effective channel for attaining excellence
in sustainable performance and SPEM a useful tool to evaluate change.

0 It was not possible to successfully evaluate the overall sustainable
performance of the banana growing industry because the CPP could not be
defined to the overall satisfaction of the experts. Since this evaluation may
be useful for planning purposes. it is recommendable that a trade-
organization assumes the challenge of gathering the necessary information.

200

The CAB has an in-place system of inspection that audits the growers’
compliance to the 1993 environmental commitments made by the industry to
the people and government of Costa Rica. The SPEM can easily be
incorporated into this system of inspections as an evaluation tool. The
aggregated results of CAB’S evaluations using SPEM can provide a reliable
appraisal of the environmental performance of the industry.

There is a need to revitalize the combined efforts of the industry to attain
excellence in sustainable performance. It is recommendable that the
industry. through CAB. adopts the list of BAP compiled in this dissertation as
their goal, assuming a new challenge and bolstering its commitment to
sustainable development.

The panel of experts, through the definition of weights or intensities,
identified the areas 'that have the largest effect on sustainable performance.
This is useful information that should be considered by the industry to define
their research and development programs. This is especially true of
CORBANA’S research and development department, which provides
information to all the growers of Costa Rica.

SPEM has the potential of becoming a useful tool to evaluate the sustainable
performance of individual farms. It can be applied by the owners to rate their
individual operation with respect to other plantations. and to define areas that
need improvement. The banana industry, through CAB, should sponsor a
series of workshops to analyze each of the elements of sustainability and
validate SPEM. If as a result of these workshops SPEM is validated. CAB
should disseminate it as a tool for planning the investments of the industry
and the individual growers.

SPEM Should be scrutinized by certification organizations. such as the
Rainforest Alliance and the AMBIO foundation, to assign ratings and to
determine plantation that merit a sustainable performance label. Growers.
through labels. need a reliable and inexpensive method of gathering and
relaying information to the consumers that differentiate their product over
those of the competition. SPEM provides a mechanism for certification of
growers’ claims. On the other end. consumers need to feel confident that the
information provided by the label is correct and verifiable. lnforrnation
processed by SPEM can be replicated and verified by auditors. Most
available market labels recognize specific elements of sustainability, but no
major market label recognizes a combined sustainability rating. SPEM offers
a mechanism for certification organizations to amplify labeling scope.

The banana industry of Costa Rica has been singled-out by European
environmental groups and criticized for the negative impacts that it
supposedly has on society and the environment. The banana industry
Should conduct a comparative analysis of the bananas. coffee, cattle. sugar
cane, citrus. heart of palm and pineapple industries’ to determine overall
sustainable performance. It Should also include a comparative study
between bananas and some of the crops produced in the European

201

countries. These studies should include the analysis of the banana industry
of other producing countries, especially those that enjoy trade privileges from
the European Union. The results of these studies can verify the banana
industry's comparative and relative effects on the environment and society.
and guide Costa Rican producers into a new decade of prosperity.

5.6 Concluding Remarks

Banana production for the export market is a very important activity for
Costa Rica’s social and economic stability. Conventional banana production
practices, as defined in this dissertation. have a moderately unacceptable
Sostainable performance level. New and better “eco-safe” production
technologies are needed that are environmentally and socially friendly, as well as

cost effective.

Large-scale production of “eco-safe” bananas is difficult and complex
under the ecological conditions found in the humid tropics. The future is in the
application of clean technologies. which use natural resources and processes
rationally, and decrease producers' dependency on agrochemicals. Eco-
development compatible technologies and biotechnology will play important roles

in this new sustainable banana production paradigm.

There are evidences that the adoption of better production practices may
bring positive long-term economic effects, which counter-act the investments that
are needed. At thiS- time there are not enough conclusive evidences that this is
the case. Furthermore, not all the appropriate clean technologies proposed by
the panel of experts have been tested on a large scale. Consequently. growers

have reservations in adopting them because of the risk involved. Validation of

202

best practices at the pilot project level is urgently needed before industrial wide

use can be recommended.

Individual growers should carefully analyze the best available practices.
The objective is to identify which of these practices best fits individual conditions
and which will contribute with the largest impact to improve sustainability.
Gradual implementation of the best fitting and available practices is advocated in
order to minimize the initial shock and allow for a gentle adjustment of the

system.

A considerable sector of the banana industry is economically stressed,
and funds for research and development are not readily available. The
introduction of fresh sources of funds is necessary. The industry’s troubles are
partially adjudicated to the excessive reliance on agrochemicals and the
developed pest resistance to them. The agrochemical companies are profiting
from this dependency, and have the funds required for developing clean
technologies. No one expects these companies to invest in changes that
decrease their profits. However, new concepts and innovative technologies, that
permit a particular agrochemical company to develop a market edge over its
competitors, provide a powerful incentive for investment. Research institutions
such as CORBANA and the universities must look towards multilateral
developing agencies for funds for research and development to address areas

that are of no interest to the agrochemical companies.

203

The European Union countries are projecting stricter barriers on the
purchase of products that are not produced with eco-safe technologies. A small
but vociferous group of consumers has demonstrated a willingness to purchase
and pay for "organic products". However. there is no indication that political
barriers and license requirements, which frustrate independent marketing effort
to introduce eco-safe bananas in Europe, are going to change. On the other
hand. banana-marketing firms are not willing to introduce eco—safe bananas
voluntarily as a choice to the consumer because there are not enough market
incentives. Therefore. Costa Rica's growers must form strategic alliances to
educate the consumers and differentiate eco-safe bananas from others. The
consumer must have a clear understanding that by purchasing an eco-safe
banana he or She is contributing not only to the conservation of the environment.

but also to the improvement of the workers’ and the communities’ quality of life.

Transnational companies play a very important roll in the banana business
and should be kept as an Significant part of the banana industry in Costa Rica.
Nevertheless, Costa Rica’s authorities Should have effective control mechanism
and alternate marketing options to maintain a balance between the economic
interest of transnational companies and the well being of the country. It should
use lntemational conventions. and bilateral and multilateral trade agreements to

ensure a place in the market for Costa Rica's fresh bananas.

Costa Rica should also promote added value processing of the fresh fruit.
There is a great potential for eco-safe bananas in the baby food business that

Should be optimized. Other banana products have been extensively researched

204

such as starch, flower, alcohol, vinegar, syrup, juice, and snacks. The high level
of education of Costa Rica’s labor force is a strength in the establishment of high
technological processes. The government Should motivate research and
development of new and appropriate value-added technologies. and aid projects.
which pursue this line of business. Authorities should re-direct revenue collected
through the environmental tax on banana exports to its original destination -

research and development of human and environmental health.

The Government of Costa Rica Should provide incentives for crop
diversification and the elimination of unproductive farms. It should also check the
concentration of land in few hands. Cooperative farms in banana production
have not been successful. Therefore. new and innovative schemes should be
introduced to increase the opportunities of small farmers to make a decent living.
using their land wisely. The forestry sector has taken the lead with the carbon
exchange and wood futures programs. The banana sector Should follow their

example.

There is a place for banana production in the future of Costa Rica.
provided that decision makers act wisely to make appropriate and timely
adjustments. Properly digested information is a key factor in making wise
decisions. This dissertation contributes with a method - SPEM — to
systematically collect, synthesize and analyze large quantities of complex data.
It is capable of ranking alternative solutions using sustainable performance
indices. It is also capable of monitoring the effects of change to provide

feedback information. SPEM is a useful decision making tool that can contribute

205

positively in the sustained development of a new era of prosperity for Costa

Rica's banana industry.

APPENDICES

APPENDIX A

206

 

0
G)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Heat
Water
Solid m Dmncstic “m BnufSecoads
Sediments Fun . .
W “Wm ”mu:
ad Myaf’h‘ Enemy Polypropylene
. . Liquid residuals Fowl P
Carbon dim Leadiucs H I I I i 5°” “'3'”
Rain water
Hydrogai
Ground m M
Blots . . W“
Sm, & [ Housmg Unit [
Leaves
I Banana
‘ Cardboard
M ——’Bsnnsrscune__p PachngPlant _.> Willy“;—
Fungicide
Pallets
Plum:
. . Polyethylene
Fatiliws Pfinégzdes _ Polyprqaylaie Consul-n
:icogcn N 'o'dcs Psthogui ancieficnl P II Fan . .
calcium Herbicides biological scents and:
Phosphorus Insecticides Insects Cardboard
Calcium carbonate Weeds
.___I - Major production compatriot

_’ -Flowofmsterislssndai¢gy

Figure 13 - Macro Level Banana Production Model

Spoiledhanu

Pallets
We
WW residuals

207

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Wind drill
Harvest
4— Nematicide
Packing <— Herbicide
plan, 8 Banana «— Fertilization
<— Plastics
fl .. “ Plantation 4— Land. Soil 8. Minerals
3 i g Solid Waste
Water 3 r
r- Plantation Floor Decomposition
l—l-l
< > Samoa mm 1‘;
M Anna" "um” Immobilization W
0 Chemical x
. Biological
6
/ Hydrosphere
A Loaohato Surface wine:
V . Cmels
I Groundwato 0 Riva!
r 0 lefi
0 Ocean:

 

 

Lilliaspliere

 

Figure 14 - Micro Level Banana Production Model

 

208

 

-*:‘.'.»‘ Maggi-i". {tr ”-15

‘.‘- e
; ' ’ ‘ r
:= :.'«lft?slti.'ll'.‘n,ll ,.

 

_‘ 'x—‘a‘ ‘ 3“-
final) (hull?-

11 viii-”1M l ' H {7157

 

 

 

 

Figure 15 - Mega Elements of a Sustainability Performance Index.

209

 

 

 

RATIONAL (BE 0?

NATURALRESOURCE ,

, MVATIONOF ’
to f 3101mm 1

 

 

 

 

MOW“

"r’fs: ‘

 

 

 

   

 

 

 

 

 

Figure 16 - Macro Criteria for an Environmental Performance Index.

210

 

CONSERVATION CORRECTIVE RESTORATION

 

MEASURES MEASURES MEASURES
O\ \\ “mum“

 

OF NATURAL -
®\\\\ RESOURCE
LANDS GENETIC

SCENIC sou. WATER
BEAUTY CAPE STOCK

 

 

 

Figure 17 - Micro Criteria for an Environmental Performance Index -

211

 

CONSERVATION comm RESTORATION
MEASURES

SELECTIVE USE OF TOXIC
P

 

SIMPLIFICATION
OF COMMUNITY RESSURE SUBSTANCES

POLLUTION

 

 

 

Figure 18 - Micro Criteria for an Environmental Performance Index
(Conservation of Biodiversity).

212

 

INTEGRATED
RESIDUAL
MANAGEMENT

CARBON
SEQUESTERING

 

 

 

RESIDUAL
GENERATION

 

Figure 19 - Micro Criteria for an Environmental Performance index
(Pollution Prevention)

 

213

 

INPUT
MANAGEMENT
PRACTICES

a _ V ‘. v.>.-~ --'-->p r- . _ 4. t
..;!.I'\. 'u:'.<

yin; . : 3.51m {w
' '4'“ ‘\ “: ~, ‘1' 1:4 I W; h 'T
D ~i-JNti'n‘IIEHHrwill}:iv
‘ n.. x} . It »

lif‘; I V,;';v'1[s-

".f f. “ ' I”. i: I: ‘ w,

 

 

 

 

 

Figure 20 - Micro Criteria for an Environmental Performance Index (Rational
Consumption of Inputs)

214

 

REDUCTION

RECYCLING
INCINERATION
LAND FILLING
INTEGRATED RESIDUAL
MANAGEMENT
AIR FILTERS /
WATER FILTERS
GROUND COVERS

SEDIMENT TRAP

 

 

 

 

 

Figure 21 - Micro Sub-Criteria for an Environmental Performance Index
(Integrated Residual Management)

215

 

 

WATER
DISCHAROES

«— DOMESTIC SEWAGE
/ AGROCHEMICAL LEACHATES

‘——— SUBSURFACE PLOW
AGROCI'IEMICALS

SEDIMENTS
PLASTICS

ORGANIC LEACHATES
/ ! { FUELS & LUBRICANTS

SURFACE RUNOFF

@

 

  
  
  
  
 
 
 

I RESIDUAL GENERATION ‘_

 

PLASTICS
AGROCI‘IEMICALS
PETROCI-IEMICALS
HEAVY METALS

NOISE
ODOR
TOXIC GASES

  
   
 
 
 

 

 

 

«ORGANICS CFC
«DOMESTIC WASTE ooz
METAL SCRAPS
SOIL
l DISCHARGE] I AIR EMISSIONS I

 

 

 

 

Figure 22 - Micro Sub-criteria for an Environmental Performance Index
(Residual Generation)

216

 

 

 
  

BENEFITS TO WORKERS
AND FAMILY

  
    

Ammm
LOCALCOMMUNITY

 

 

 

 

 

 

 

   

 

 

 

 

Figure 23 - Macro Crlteria for a Social Performance Index

217

 

 

CURATIVE MEDICINE I

 

 

I PREVENTION MEASURES I

 

@——»

 

REDUCTION &

SUBSTITUTION OF
TOXIC SUBSTANCES

 

EXPOSURE TO TOXIC
SUBSTANCES

I RISK I

 

P

 

VHBALTI'I

PREVENTION

 

 

Figure 24 - Micro Criteria for a Social Performance Index (Health Hazard

Prevention)

 

218

 

INFORMATION SUPERVISION
ORGANIZATION —->

EXPERIENCE \

TRAINING
CHOICE OF APPROPRIATE TOOLS -—>

IN-PLACE PROCEDURES —->

    
   
 

STAFF

 

PREVENTION
MEASURES

 

 

HYGIENIC ———> “’0“ ”ODE
*— LONG SHIFT DURATION

SAFETY EQUIPMENT -—> 4—— HIGH DIFFICULTY

‘ LARGE PHYSICAL STRESS
ERGONOMICS

PAYMENT MODE
ACCIDENTS & SICKNESS

\\ LACK OF TRAINING
BAD WORK ENVIRONMENT

PREVENTIVE MEDICINE NEGLIGENCE

 

NUTRITION

POOR HEALTH CONDITIONS

 

 

 

Figure 25 - Micro Sub-criteria for a Social Performance Index (Prevention
Measures)

219

 

 

FAIR INCOME
LEGAL BENEFITS
SERVICES \\

MERIT SYSTEM

EDUCATION 0

MOTIVATION

 

 

 

 

 

 

Figure 26 - Micro Sub-criteria for a Social Performance Index (Prevention
Measures)

220

 

 

HOUSING
TRANSPORTATION
RECREATION
POTABLE WATER
WASTE TREATMENT
ELECTRICITY
® 1 >I SERVICESJ
SCHOOLS *
COMPANY MD /
HEALTH CLINICS
DAYCARE CENTER
FOOD
CHURCH

 

COMMUNICATIONS
COMMUNITY ORCHARDS

 

 

 

Figure 27 - Micro Sub-criteria for a Social Performance index (Services)

221

 

 

 

 

 

SCHOLARSHIPS
BOOKS
UNIFORMS
TRANSPORTATION
SCHOOL SUPPLIES
@ I ‘ EDUCATION
SHORT COURSES ON
SKILLS FOR FAMILY
MEMBERS

 

 

 

Figure 28 - Micro Sub-criteria for a Social Performance Index (Education)

222

 

LABOR AVAILABILITY OF FREEDOM TO
OWNERSHIP OR ALTERNATIVE BARGAIN AND
PROFIT SHARING JOBS ORGANIZE

 

 

6) al JOB SECURITY I

 

SEXUAL
DISCRIMINATION HARASSMENT

 

 

 

Figure 29 - Micro Criteria for a Social Performance Index (Job Security)

223

 

 

 

  

LABOR
QUALITY
IMPROVEMENT
WORK ETHICS
ABILITY
LEVEL OF KNOWLEDGE .
Q) ‘ CAPACITY

 
   
 
 

 

<— DISSATISFACTION

+- I-IIGH ROTATION

+- ABSENTEEISM

LABOR INSTABILITY

 

 

 

Figure 30 - Micro Criteria for a Social Performance Index »

224

 

BENEFITS

  
  
 
 
 
 
  
 
  
    
 

JOB GENERATION

DEMANDFOR PRIVATE SERVICES
ENRICHMENI'OF LOCAL CULTURE
INFRASTRUCTURE BUILDUP

INVESTMENTS
LOCALTAXES

BENEFITS TO
® THE LOCAL
COMMUNITY

 

 

 

PUBLIC STRESS ON
DEPENDENCY LOSS OF LOCAL SERVICES COMMUNITY‘S
ON ONE CROP CULTURE OVERLOAD HEALTH

 

 

 

Figure 31- Micro Criteria for a Social Performance Index (Benefits to Local
Community)

 

 

HOUSING

    
  

 

 

 

 

 

STRESS ON
COMMUNIT‘I‘S "
HEALTH
FAMILY
STRUCTURE

ACTIVITY

COMMUNITY
ORGANIZATIONS

HEALTHY
RECREATIONAL
ACTIVITIES

 

 

Figure 32 - Micro Sub-criteria for a Social Performance Index (Stress on
Community’s Health)

226

 

POSITIVE EFFECTS

   
    

ECONOMIC MULTIPLICATION EFFECT —"'>
INDIRECT JOBS GENERATION

REVENUE —>
INFORMATION & __>

 

  

 

 

 

TECHNOLOGY BENEFITS'IOTHE
NATIONAL
‘__ INFRASTRUCTURE 7 ' COW
OVERLOADING

    
    
 
   

‘ CONCENTRATION OF LAND OWNERSHIP

CONCENTRATION OF POWER IN FEW INDIVIDUALS

MARKET DIST ORTION & INSECURITY

‘ FINANCIAL RISKS
NEGATIVE EFFECTS

 

 

 

Figure 33 - Micro Criteria for a Social Performance Index

227

 

 

 

 

 

 

 
 
  
 

+MAINTENANCE

OVERHEAD INFRASTRUCTURE I .3 COST
<— ADMINISTRATION SALARIES

<— FINANCIAL

d—DEPRECIATTON
<— TAxES

 

 

 

 

 

 

  

 

 

 

 

 

Figure 34 - Macro Criteria for an Economic Performance Index

228

 

 

LABOR ORGANIZATIONS
SPORT FACILITIES
HEALTH SERVICE
TRANSPORTATION \
FRINGE

V

@ /( BENEFITS
EDUCATION .
FOOD
HOUSIN

WATER

 

 

 

 

 

 

 

Figure 35 - Micro Sub-criteria for an Economic Performance Index (Fringe
Benefits)

229

 

 

PESTICIDES FERTILIZERS BOXES

INSECTICIDES -)
FUNGICIDES -)
AGRICULTURAL OILS -)
DISINFECTANTS -)
SEALANTS ->
NEMATICIDES -)

HERBICIDES ->

 
 
   
 
  
  
 

CHEMICAL) CARDBOARD

ORGANIC .) GLUE)

 

 

 

   
 

 

® , COSTOT'RESOURCES
’ FUEL * _- (INPUTS) , , _
CUSHIONS -) ELECTRICTTY .)
BAGS ') ENERGY
PLASTICS LUBRICANT
EQUIPMENT
lNl-RASTRUCI‘UR

 

 

 

Figure 36 - Micro Criteria for an Economic Performance Index

230

£23m cozosuoi 2.2.3 o Co EoconEoo _EcoEcoLEEN - ha 959".

 

 

ZHEZQt~>Z

v.k.£<.v.~ Ufik

 

   

_rm,rm3n_z_

,—_n_v_~_<2 .CDxH.
Imam; J<UC._

_.uv_m< E
...xCA—Xu

  

      

    

  

wavy—30mm:
mo in: ‘—<ZC—._.<~_

     

            

>h—m:m>_:O—m
ZO FUEL—mm—

>H3<wm
U_ZwUm

 

2.. . .. 4 .. . A" . :
i=ac=w ,_,Zm_2A—_DOH_

“EDISZ u_su:a><
...EiomEoOoQ j szhUDzhwz‘zp—z.
. . >053.

«_mD;
m4<_~_m:.<2 OZ_¥U<A.

 

       

«:55 mLm<>r “I,
29mg: A 2:;

‘|

mU_Pm<I_A_

Loo: 5:22;:

nU_._.m<I_L

      

 

II

A0<m $214k

uZTSh

A/

8631x9031 3W1

 

maxim—4:97;;
mm:__b_h<2zz
muAZumexm—I
wahU<zPZCU

ii'Mm—“Il

   

 

 

 

’ :Ezaggu k

mmwazyu—DZD;

WNO~LRMQ us
EDENESQU

mm_OZ do
.Lkhwiaxl:

mmm<0 EXCP

 

 

   

 

 

mZO_mm_Zu ~:<
ukvfltkaEh—x I '— ..MKDANZ~ K0

 

:IQ “1: >2

ZCThEEDWZQD
d<2©~h<-

 

ZO—th—>m—IA_ ZO—hDAAOA—

 

 

231

805$ 5.8.52; «cocoa a ho “cocoa—coo _o_oom - on. 2:9".

 

Busy—um d «Om—<4

mun—m m>_._.<0m

 

 

PZMZmUZ’xT—Z _
aims—£03

>FEDUmm
m0..

1 o _.—.Zm>m~E
Dm<N<I

~1=§< Vt % FS<mI
MNMMMQAS mtmmzmm
mOZEn.

m._._u_mzmm
4<Om5

 

 

mm_~_<4<m

 

 

000m ESE

 

 

 

 

 

 

 

 

 

 

$33358 uuz<x2mz_

.363 528mm

450%

Emu—hm—
m>i<omz wEmzmm BBB—mm 859
E Em.
mHU—r—bgm
OHM—Fm

 

 
  

 

  

525k
UZ~¥US~

 

+

xh~>53§50
d 3(th <2

  

52¢"—

 

  

 

Emu—um
Puma—DZ.

 

 

 

232

 

E225 cozoaooi Sign a “_o Eocanoo o_Eocoom .. mm 2:2“.

 

 

 

 

 

.\ zmzzoniz .
So _ Stzazzoo 32o: <2 mozfiSmE
Sou a
5:585
4<HNvawmwwwazm $23.3 JSUOm
> Ltzbzzoo 363
_mmseuaxem<xmz;

 

 

 

 

 

 

 

 

 

_ mPU<¢FZOU

mmx<L
S...
_ o<mzzm>o 325.3 a a a
, , Sn:
Sf

 

 

 

 

 

 

 

4.8.3 EEG S<S<§ £22: Lzmzmsom
8.6 hz<4<mw
e3 >9.sz
S8. :3
mflb~hb<~k 3.3
QQMNHN m4<_mm._.<2 DEV—Dc;—
S; 3:”..me mOzEL ‘ 95 2. Rf. 8.55..
So: mtmmzmm .203 . .
Sade 8&5: Sn 2“ H&“Wfik g a $33.59.
m0m<4

keoi. me_U_._.<2mz

 

kite mun—_Uazmx

on. $56622”.
:ozfioagm as: 58 e
..Im v. m < 2
m

MURN‘QSQU
. LRLMDQCE

 

 

 

 

 

 

..m..=~.~>= k6
ZQfihkzxmeQU
d<20~h vi

 

 

APPENDIX B

233

Table 34 - Agreement to Participate

PANEL MEMBER N°I DATE:

 

PROJECT DESCRIPTION

Many developing countries depend largely upon cash crops for hard currencies. This strategy
has brought economic benefits to these countries and to many individuals, but it also has had a
negative impact on the environment and society. This dissertation defined a vision, a blue print to
guide those responsible for agro-production systems to see the world as a complex system that
requires responsible stewardship, and to aid them in choosing production practices that minimize
the impact on the environment and society while maintaining an acceptable level of economic
benefits. It sets sustainability and sustainable agricultural production as its aim.

This dissertation examines Costa Rica's world-class banana production appraising its current
production system and exploring alternative production techniques. It develops a systematic
method of valuing and accounting impacts using a panel of experts for assessment. The method
under scrutiny aids to dissect the problem by identifying cause and effect relationships of the
different tasks required to produce world-class bananas, assessing the relative importance of
each relationship, and accounting for their contribution to environmental, social and economic
sustainability. As a result, it points out tasks that demand change, and areas that require further
research and development.

This thesis contemplates the following issues:

- Any agricultural practice introduces a disturbance in the ecosystem and has a resulting impact on
the environment. The environment has the resiliency to assimilate a limited amount of this
impact.

- Conventional world-class banana production introduces a massive disturbance in the ecosystem,

and its impact may be beyond the limits of environmental. Therefore, conventional world-class
banana production may not be environmentally sustainable.

- Conventional world-class banana production brings benefits to the workers and their families, but
it also has negative impacts that may be partly responsible for some of the serious social problems
evidenced in the surrounding communities. Furthermore, world-class banana exports require a
large national investment that generates a substantial economic benefl compensate the impact that
production has on the environment and society. Therefore, conventional world-class banana
production may not be economically sustainable.

Consequently, the conventional world-class banana production system used in Costa Rica may
not be sustainable and it may need substantial modifications.

You are a distinguished expert in world-class banana production and have much to contribute in
the development of this project. For this reason, you are being asked to be a member of the
panel of experts that will assess the different tasks performed in the production of this important
commodity for Costa Rica.

234

STATEMENT OF INFORMED CONSENT
I have read the project's description and I understand that:

I.

2.

The time required for each of three interviews is about 90 minutes each and that there is no
payment for my participation.

The nature of my participation includes answering questions and discussing with the investigator a
series Of issues relating to the impact of banana production practices on the sustainability of the
system.

My participation is entirely voluntary and I may terminate my involvement at any time without
penalty.

My identity will only be known to the principal investigator and a limited research staff. My
identity will be kept confidential and the report of research findings will not permit associating me
with specific responses or findings.

All data collected are for research purposes only.

There is no foreseeable physical, psychological, social, legal or economic risk associated with this
research. .

If I have questions about the research, or I need to talk to the researcher during or afier my
participation in the study, I can contact the researcher by calling (506) 255-2000, extension 2900
or by writing to: Carlos E. Hernandez PO. Box 4442-1000, San Jose, Costa Rica.

I fully understand the scope of this project and I declare my consent to participate as a member of
the panel of experts.

Expert's Signature: Date:

Principal lnvestigator’s Signature: Date:

 

235

 

.mea one 38$: 2
3:338. ocm 39> Lofiem 26; ___3 9539. DE 6233
c. .cozflcma 2: Lo :3 as 25 .6sz 3:35 .6 >533
09.2 m 350985 $82: $5 .23 05 o. ooEmamcg
co§> .63 Lo: 9. vv Emoxon L063 3858 Lo

.>__m:coE 03: En 95332 can 953:... .3582 van
3%ch 2o 33:33 we age: conga: ..o 303 €280.
E8: .335: 33.38 ocm EoEomcEm _mzmam Dogma: o5

 

 

 

 

 

mom: 5 35.33 OS :53 626303 5 women 05 39.2 o h on? 5859: 0... 62.00.35 bo> m_ :3 L933 05 3 85396
an? 9: Lo man: 9.: :0 9.0: m_ 2o: 9: 5 3323 .5526:
.mcomofima Co 203 5263 9: 2mg 2: 3:03: 35 3:8 293E ocm 33:84.95 coon
9.85 g .Eoctocti .cozflcma «coco: 05 E 303035 m_ was $89: $5. 303303 Lo SE: 5923 beefing
3:839, Co 033.: m can :32: m_ 2:=:oocoE Co E936 3380. new 89> :9: 2 @5288 33.0» 2m 323:3
DE .539: £5 5 fine» Lo: 988; Log 9.2 0.3 mama on... .326 xeozro 2 .0 c_ nocm__anoom m_ 389:
26:3 9.: 5 =8 9: 25 _mtofiE 9:35 .o 333:: 38. $5 .3326...“ Co “E: 05 mm Lozmgoocflm ocm ...23:mo
28098:. .5305: x: 2 mafia 26:3 2: c. SE32 320 .352: «5 Co 33330: 9: m_ SEER. 7.0.: o5 .0 0:0
Eco» .3339: .o «E: 05 33:3 .5. $828 one 33:33
05 .8 32.3 c_ 3:333 9: Co women 33530:: 53522 .6 mega? 3235 2a 9.9:. .3339: Co «_c: DE 323 9
.333: 3.3.38 So. use 5.23% x83 “.o 3335 m_ 32! Co $093 9: 65.5an mm c265. 3009: a 3:95
.mooofiEoc Lo 3:938 3:. ”2202.88 9.36:2 ace: 3 296:» DE 95.3 Eoe 328 m Co 33028 on...
9: 9.3228 623.38 3030.03 use 33:33 Co .303 .23: Eot .0 «Steps:
.90. 0.3388 5255.: o ocean. .3332: 328%.. .2 our 5 .563 £83 Eot 63339: DEERE 9a.: 5 3:25
.92 33583 E:E_:_E 05 Loop. .0: oo «as much 283. an? 3583 En $83.: one 80230: .o co: 35.38
.oomam
com» .3 893 95 on? can 635 ion music... 2 one .25 .05 33:83
26:8 2.50... 3621.: 3 25 33:33 Co mean 9: maze an? .0 mac: .0 9523 DE .Eofiooama as ho toga 9: 23:3.—
0. .52 .2383: m s m_ 83.: DE Co EoEomcmtm .3QO on...
.EoEomcEm 3:3» 26.. 03:0: a 5:5 .__om DE .6 23x2 9: co 93:33
3.38; .8 353 Stu - 8mg 852% 3; 5 an: 288.. .8 mama 82 2 8: a E28 9: 92388:.
door: fie3£ Lo 32.8 5;, 335280 2:323 “mean; one m mm .363 2m :3 nob 3.323 a mm 3939: En 333m

05 £5, QED .355 an no 3:83.: o5 .0 tea Ema aa< -zOFSDQOa no ..Omhzoo oz< OzeSa 3 ECU
wmo_._.o<mm Sufi

wmoFo<mnPrrzm2mF0<z<2 w>:.<zmm.5< .z wmocbéa ._<zO:.zm>zoo oz

 

 

 

83%.; 2353:... - an asfl

 

236

 

0.0000
00.00. 000 00000000 00. 5 0:0.. .00E.000 .0:..0000

05
an?

000..
080.00.: 0... 00 00:0.00. 5000.0 .0 ..00:00 0... .3 00.00....0
.0000. 0. 0500.0 ..00 0:20 __0..00 0...: 000.0 0. 00.000.
0.0 000..0.00.: .005 5.0.0038“. ...00 00. .00.. 0.000.:0
.0 00.0000. 0... 000 .00..0.00.: 0... 80.. >030 0.00.0.0000.00
.0 00:000.. 00. .00..0.00.: 00000: 0... 5 00.020 ..00 .0

 

 

 

 

£0.00

 

00.. 0.0.. 0... 0. 00.30.08 E0.0>0 .0000 0... .0 00000200008 00...
.00..0.00.: 0... .0 .00.. 0.... 00 :0.0 .050 0 50.0.0.0 000 .00.: ::< .0500. 5.00.: 00.0.2.0: 0...: 0008.0 0000.0.0::0
00: 000..0.00.: .50. < 0.0000 00.00. 000 ..00000000
00050.0 .0.00.0::0 .0 0.0.90 0.... 0.6.95 0. 000.00 0.0. 0:. 0000...: .0 0003.00 00:0 00 0>00 000..0.00.: .0 300.00. 05
00..0.00.: 00. .0 .00.. 0... 05:000 .5 000.0 00.0500. .00.: ::< 0.0.00. 00... 000. 000. 00 .0 5:00 0
.0 0.00. 0.030520 0.... 050.500. 000000 0... 000 .00..0.00.:
..00. .0 20:05.00 00. 500000.00 >.0:0..00 0... .0 000.50 00. 0.0.. .0.0.s 0000x0 0.0.0 0. 000: 0. 0:...
0.0.5 00.0.00 0000.0.0 0000:0020 ”05.000 .0 0.02 .0... 00... .000t:0::0 .0 .0.0...0::0 00 000.0000 0. 00050.0
.00... 0. 00000.: 0.0. .0 .000 .0...0. 00.0 .E0.0..0 0000.0.0 0... .0 00.000 0:. 05000.00
0.000.000 0.0.0 0. 000 050000. 000 0500.0 00:00. 0. .00.: .0822. 00005500.: 5.3 000.0 .0:... ..00 000 030.030...
0. 0.0000 .00000000 0... 0003.0: 000.0 0.... 0.0.0 0. 050:. 0:. .00.: 00000: 00. .0 .000.:0.0>00 .00...:0 0.... .0. 00.500.
5.00.: 00.0.8.0: 00.0: 0.0.0.0 0000.0.0 000..:0::0 ..0.00. ::< 0. E0.0..0 0000.0.0 0>.000.x0 00 .000...0000 000... 0. 0:0
.0.. >_0>..0.0. 0. 0.0.00. 0.. .. 000.0..000 000.000 on 000
05000.. 3 000:00 000800 00 0003.0: 0.0302. 00.:.0.0:0.0. 00. 000 .00.. .0: 0.0. 0000
.0 .000 0... 000 .0 .0.000 00..0.0:0 .0 0.000 05.02.0000 000 000. 0003.0: 0. 0000.0 0000. 5 00..0..:.00.: 0.0.5.0
3 0.0.0.0 0000.0.0 0... .0 3.00:00 0... 0009.0 ...3 .0... 0.0.2. ..00 0 0...... 000.00. 5 0.50.0 0.0 000000: 00.0 0.000 0.
.550. .o 0.308... 9.. .0 0.0.0520: 00.320. 0... 800.0: 0:. 00.220:
0. 0000.00. 05.005000 00.0: 0.0.9.0 0000.0.0 00. 00.00%. R... wmo_._.o<m: 0.5.“.
00.0.0200... 0.6.0.5 000 0.0.0.6000 0... 0.0.00. 0. 00.00% .0.:000. 000.0 00 000020.:
02.00 5.3 00.00.: 0: 03000 000~ 0...... 030.00.: 0... .0 .0. 0... .0 ..00 00. 00 00:00:00 0.0 00..0.::0: 0... .0 .0..000
.0.00..00: 0... 00:0.0 00.; E m. .000. .0 0000 .0..:: 0 0.00.0 ::< 000 0.30.0 .0 00000.: 0.... 0. 00.0.0000 00.003 0.0008 0... ._<
.006. 20.00.06 0. 00...; 00.0.0.0
0.0.0... 0.5.00... .0 00.0000 0530.0 0.05.. 0...... 0000. 00. 30.00. 00.0: 05.00.: 0.0.0: ..00 0... 0N....0.0 000..0.00.: 00.0w

000.0 000 005.:0 .0E00..0 .0.0>.. .0 00.00: 00. 00.0% 4%...

 

 

 

 

- .008. znfifiio. .0 60.500 02<1i§0wrm

 

237

 

 

 

.0000. .0 ..0.0 ..00 0.... 00.0000 .0... 0..0..00
..0... 808.09. 000 czm - 00.80088 .00. 080.000.00.28
00000000 :0... :0.80>90 .0. 0.9.08 .00.00.0.0 00...

8080.000 03.00.90
0.000000 003 000.0000. 0.0. ..0000 0. 80.0>0 000000
00. >..00.2 .9000000.0 000.09.020 0...: 8080.000 00.00
0:.>0.00 .0..0.000 0...... 80.0>0 0:.>0.00 .0000 0.... 00.0800

.0900008 0>..00..00 00088009 000
.000800 .0 800.0 000 >....00090 00. 00.0.0900 .000...0000
0..08..0 .00.0000 .00..0.0>0 .0 0.0.0 0.. 000 00000.0 0.... .0
90000.0 .0 .0>0. 00. >030 080.0>0 000.... 0:00.008 0008.8
000 .00000. 0... .0 02.000.00.000 0... 0000808 0... .0 30.0.0
000 30.000 0... 00 00000 00.0.08 00.0.000 .0. >00.000....08
0:0 0000.090 .0. 00008000. 0:09.008 00000.8.

80.80090
.0 0090 000 00:0N >0 00.000000 090000. 0.0.. .0 0.809 0...
0000 0000.000 00 0.0000 080.090 00... 0.000 .000.00. 0 00
00.8.0000. 000 8090.00. 00000. 0. 0. 00000.0 0.... .0 0000.00
00.: 00.00000 80880>00 000 .00.:00800 .00.8000900
0.000090 80.. 0028800900. 0...... 00.00.8800 0 >0
00.0.000. 0:0 >.0.00..00 00 0.0000 080.090 0000... 0.0 000
.00.80.0>0 080.0990. 080.090 .9800 090.008. 00.30.0Lw

 

00m
an?

000
ma<

gnu
00...

00m
002

 

0:.>0.00 .0000 .0. 0000 0.0 0.00090

00>9000 >80 .0... 90000 00.0... 808000000 0.... 0:00.808
000 000000 .00.:000. 0.000000 0.60 90>00..030.0
.000000009. 0... 000.0 00000808 ..00. .0. 080.090
.9800 .0 0000808088. 000 00800.0 0... 0.000..00009.
0.... 5.3 .09800 0. 80.0088 0.08 .00.0000 0.000090
800000000. >008 .00.>.00 0000 0 0.0000 0. 000 080.090
>.._000 0.0>0 0 ... 00.9005 0.00.0 .0 .9800 0... :0 800.0 .090
0 0. 0000000 £000 00. 000 0.0.. 0... >00 00.... 2000000000..
00. >0 00:00:00 0. ..0.. 0... .0 >...000 0... ..0>0..>0... .>:00800
0:.>0.00 00. 000 890.0 .9800 00. 00.00000 .0 00000
0... 0>00 0.000090 800000000. .00.....00. ..00..0 0.0.000 000
0000.0 030 ..00. 02.0 0. 0.9.0 .00000 0.000090 800000000.
.005. 00.....00. 009.0 .09 0:0 00.000800 0:.>0.00
.000..00 5.3 000.200 80.800 00.000800 .000..0:0:9.
.050 .00.....00. 009.0 030 ..00. 9.0... 000 8080.000
:30 ..00. 0.0.000 00.000800 0000. .0 .005. .080.0>0 .9800
030 ..00. 9.00 903000390 .000..00000.. 00... 0:.>0.00
.0000 0..) 00..000 90 9.900% 0.00.0 .9800 0. 000.0.0000
.>.._000 000

>..>..0000.0 0.0.0.08 0. 000.0.000. .0 00..00..000 80000.. 00.
00.9.0080: 00000. 0.0. .0 0.0.0: 02009000 0... 09.030...
0.0.. 0... .020... 0:0 00.00.. .000... 0.00.8.0 0.

00>089 00.0 90 00>00. 0000 0.0.0000. 0... 00000. 0. >200;
00>089 90 00>00. 0... .0 0000 .0 00>00. 00.00.:. 000.000
0. .000 .00.8000 000 00000.0. .0 00.000 00. 00000. 00000.0
00. 0:0 0.0:...0 .0 0009.008 000 ..9800 0003 .0900008
0000.800 .80.0>0 0000.90 0000 < 9.0.00.5 0.00.0 80.000
0000.00 .0 00.. .0... 0... 0.0...0000 000.890 .9980 0000
<v.o...<0.w x050 ....0 000.200
ww<wm§ oz< whwmn. 00 005.200

 

 

06000

 

 

238

 

 

. .>..0.0200.0 0>908. 000 890>0000 00. 90.09 0.00.0000
02.00 0.8. 0080.0 00 0.0000 000~ 0.0... 0000808 00. .0
.0.08000 00. 00090 00.3 8 m. .000. .0 000~ .0000 0 9090

0.0.0.. 50.00... .0
00.0000 00.290 00.00 5.3 0009 000.0 000 000000 0809.0
.0.02. .0 00.000 00. 000.0 8 m. .0 00.0 8088.8 0 .0990”.

..00 .0

0.0000 00. 00009 0. 0000808 00. .0 .0.08000 00. .000 .0
05.9.0 0... .o .00.. .00... 0... c. 0000.08

8000.0 .00. 00:0N .0000 0:0 .090. .0 000.0 8000.00 0. .0
.0090 02.98.5800 000 0.00.0

000.000 .0:0..0.0000 000300.00 .0000 :00 ..00 0.00; .0
”00.080800 0.0 0000.008 00.2.2.0.

00. 000.0 0000 00 0.0000 .. 00.000000 0 .0 .000 00... 00.
.0 9.00 0. 080.090 00000 0.000 .0 02.0000 .00 0. 9.0.9.0 :0
0.00; 0000.0 00.0000 0. 000.0.000. >900 0. .0.08..00 0 00:

 

000
0....

.0w
an...

000
an?

 

..9000090 00. .0 89.00

.00... 00. 000 82.0.0000 .0 0.0.000 0:0 90>0 .0 >..8.x0.0 00.
8000808 0.... .0 .00>0. 00.08000 00. :0 0000000 00000008.
.0 09000 00. 000 0000808 00. 00000.00 000.0 00.
.0. 80.090 02.00.80.000 0 00.090 ..00 00.0.000. 00>900:
.0090 0000808 00.0.0.00 0.8.; 0.000 >.0000.0 ...3
00.0 000008. 00. 0000. .00 0000 .00. 00.0.08... 00. 0000808
.0 0090 0200008 0.0....» 000000 0.00... 0. 00.0 .00...
00000.0. 00. 0.0..) ..0. .00 0000 000 ..00 0. .00. 0. 000.0.000.
00.0% .o .80 00.9.0990 .0... 00.220500 05.. 00.3.0
000000.008...

000 >..0.x0. .0. 0.00. 00.00.00. 000090 00098.00.
00900... 0 0000 0.00.8000 00. .00. 000.000. ..00. 000008.
:0 0000908. .000.00. 00.0.009 <0m 00. 0052.0... .000.0000
000095 0. 00.90.00. 0. .. .00008< .0 00.0.0 09...:
00. 0. 90000000 .0. 0000 .0: 0. .. 0000000 <0w 00. 0......
00.0.0.00. .00 0. 000.00 .>....00090000.0 000 8:90.900 .0.
000000.00 00009 80.0 .008 .008 0:0 <0m 00. >0 00>9000
90 000.00 .0 0000098 00. 0.0... .0000 000.0.000. 00. ..<
.99 .000.0 0008 0 9.000. 000.0.000. 80.00.90

00... 90.000 .00 0.00.. ..00. .0 0.0... cm 0000 .0. 0.00.00.00.
02.00 .0 0890 00.. 290809000 0. 000.0.000. 0.80.0>0
00. .0 00..00..000 .0 0.9 00.0 .00~00:0.2 0...... 000000.800
00. .0 $2 - 00 000.00. 080.090 .9800 .005. ...0 .90..00..00
000 005.0005. ....00.00.90.0 0000000.... .00.0N00.8.:0m
.00.0~00... .90 0000 0.00090 .00.0:..0 00 .0 ..9800
00. .0 0000.00 00. 0. 00.0.0000 00.08 0.0 0.00090 00 .r
09.000. 0000 000 00.80.0>0 0. 00090.00”.

080.0990 .0 00.80.0>0 .0000 0.0 00>900 000.0.000.
00.. 00000090 .0 0.000 00. .0 .00. - N. 0.000900. 000
.00.. .00 00.0>0 00 0. 0m 80.. 0. 0:.>0.00 .0 >0:0000.. 00...

.. 0.50. 5.05.0.0 0.050 .0 008.200

 

 

 

 

239

 

 

00..000> 0000. .0 05.9008 00. 0.0890

000 >00_000090.0 00.00 00..000> 80.0.09 00...: 000 00.050
.>.0.00 00.00900. 000

.0008. .0.00809.>00 00.0009 000090 .000. 0. .0.000080
.90.00 0 00 00000 0. .. .00000N >0 000090 0. 000 0.02.3
0800 009. 00... .0.09.0>x0~0 0. 0800 0.. .00000 >00.0
0.0. .000 00000 00..00..000 0.. 000 0000098. >.8000. 002.
0.08.08 2.00 < .9800 .00.8000 .0. 00.000.08 2.00 00.9.00
.00..00.0>0 90.0. .0. 00000000880000

.00..0090000.0
.0. 80.00.00. 0280 00. 90.000 0. 0.9.0 >0_0 0050.00. 000
080.0>0 00..0.008.000 80.0.00 00..00..0000 8080.088 000
00._0>09 .0. 080.0>0 00...0.00. 00.00008 >.00000 .000..9000
.0 0000808088. 00. 000.000. 00.....00. 009.0 9.908.

.000...0000
00.2. 000 0.0.90080. .0000 .0 000.00>00 00.0.0. 000 0.900....
0.0... .0 02905.... 0.0.0800 0000000 .0 0000.00 00. 0......
00..000. 000 00..00.>00 .0. 08089.00. 00.00 80.0 .0 >900

.0.0000 0000.90 00. 0. .0>00 0>..0.000> 0.0.0.08 000 .m0|_m.

 

.00
0....

.0w
002

..00
00...

 

...00 00. 00 ..0. .000.08 00. .0 .00. 00...

000002.. 0.9.00 00090 0>..0.000> 000 0000.. 000000 0000
=0 00.0800 00 __..s 98.0 0... o. 0.0. .0... 00.0.05. 0... .o
..00 000.890 .008000008 000.00. 000 0002. 00 00.000000
..00... 0000800

00. 0. 0:0. 000 0.9 >0 00>00. 00. 00 000002. 0. 80.00.00.
90.00 00. .0 0800 .00. 0.0.0000 0. .. 00202.0... 09909000.
90 0.0000 00.8800 .000...000 00800800 00>00.
00. 0. 00.0000 .. 00 .00090 090.0000. 00. 0. 09909000.
00000800 000.0..0 0>00 0.90000 000.0.000. 00. 080.0990
.0 0000 00. 0. .0.000 0 .0... 00. 0. 80.0 00. >0 000.0000 00
0. 0000.000 0. 80.0900. 0.0.00 00. .00.80.0>0 .0 0000 00. 0.
.00090

00. 0. 0:0. >00000 00. 00090. 000000 .30.. 008.080. 00 ..
09.00. 00. 00 00..00000 0. $00 >_908.x0.000 00..00..000
00000.0. 00. .0 09.0.0 .00. 00.0.000. 00. .0 $00 00. .0
80.090 00. 9030.0 000 00.0 0.000 0000.

0.00805 ...2. 0000.08 00>908. 000 .000 0000... 80.090
0.0. 00009 0. 80.000008 00.>00.0 0. 00.02. 000. 0. 00.090
002.. 090.. ..00... ..00 >900 0 ...000. 0 0.... 99.0 09.0: 00. 0.
0:000 .90000 00. .0. 800000 .0.08 0 080000 000 ..00 >90m
.000..9000 000000 0000.0 0.0>0

000 0.008 .0 0.902. 0. 9.0.00.0 0.00.0 .0 .9800 00. 0. 0000
000.0.000. .0 080080 09.8.. .0 0000090 00. 0900000800
0>00 .000.002 000.9020: 00. >0 00.000000 00.00.m
.N 0800. (0000.06 005E“. 000.0200

 

 

 

 

240

 

 

 

 

208:935 05
:0 63.5 cm 96; c8 £03233 $05 3:83 Emmmoom:
m. 28 .35 van 822ch E2. 3.88% 3:69.308 “.0
33m .555“. .5055 vow._onEmE 59.535 2w 3.3.63
«5 s Bazoefi em as 82282 6339883
2m uca mg. :05 m o5... m_mo_Em;o 05 038mm
.35.:me

05 2 3:3 ucm 5:23 “.0 So 3:33.83 5305 g 20:3
«.28 we 25 so: 533 ___z .823; m_ as 02292
0...... .305 53.83695 can 5:53am c3253 9:: “_o 3%.
m5 :0 3:33 :05: E 365:2 9: ,6 5:89.: oomtam
60:89:. momtamnam .0 $5205

2: @5262 .BEBOEE 269.... 9a >2: ow $6.2th >90 .2
Esta :9; m «>2 ucm Em; :_ 0328:. >53 83 En >3...
.cozmufimmuofi Sam. .8 umcgmou 9.0? new wt. to...» a 05;
3229.2 9F .30: 8:353 05 co _mtEmE 9:939
33 new 95>: 5;, 3668mm 9m 35 c2389.. .0 3059....
3:95»: 9 3me 952m 05 2 £5 55 386:2 as...
8 3:08 5.0%6 xoSquO 40ml._.zoo

 

 

 

 

 

 

 

 

241

 

 

 

65.2.5950 .o v.5. 9.. 80:3. 2983.28

5...? .25..» .o. v.82?» 59:55:00 25 8:53.
95.0.60. .0. 59.5.33 96.. .mm.cmano 3:56:88.
.5 3.880 32.. 2.5038 .mm.....om. ..oa..m mEow
.2..ng $9.. .o .8... .o 5.92. 9.. 5 3.05.83 35.3
2w 0.9: .mxcm. 8.3.553... 5.3 3353 En new 3.8.5
5 3.80. Em 9.595 9.. m5=c new .260... 9.. 9.3...
.0. 3.5.8. .mm.cma...oo 9.23 9.. 55.3098 .2... 55>
.38. .2 mm :03 mm 9.2.5.95 .0. 8:3 .mtan

05.3.0 .530... 5... 82.8 o. 593 gm... 25.95... .050
o... .0 058 new 2.5.95... >32 .33. 9.0.... mmcon .055
9m; .9. on 20.6.5... .0 3.8.3:. 0..... .mmctaw new .mEmmbm
.m.m>.. .o. mmcou .955 .038. .0.. on 25.35... 9.5.»).
.35....» .o w.m>.. 9.39%.. 505 o. 5...... 2m 9.5.38...
.38.? cm...

«mm. 3.562. m>..m.m. 0... new .283 .2. E v 26.3 3.8.?
“.53 o... .0 $29.... mméw 26.3 3 .8... 0.3.938».
9.. .5m. .5588. .o .85.. o: 2. :8 9m... 655m. on .0:..8
.. .m... 8.3.5 m2: Exm 20.5.2.8 o..mE..o o.nm.o>m. :9...»
2.5 9.0.. m. 9.38% .o>..om.Eo m.. 5.5:. 5.655% 050.95.
9.. .5... 8 new 3.655850 .0 9.5. 9.. 3.5.5:. oh
.v 280. 5.9.56 .93 .o .0558

 

 

 

 

242

 

 

05.00.50.000 6.0.0 .0 0.0.. 00. 00000. 0. 000 00060050:
00. .0 00000.0. 00. 06.05. 0.00.0 6.60 0 50.505 000 .00...

0.00.00 .0...
05000000 2.6000 0.00506. 0...... 050.0>0 00..00..000 00:

...00 0..... 006.60 000. 0. 0.00
0..... 00.60:. 0. 0.00000 .00 0 00.03 0.0. .0500 0 0...... 0005
0.0.. 0 .0 00005 >0 0.00. 0... 0. 2.0050 000.0..0500 200<

0.0.. 0... 50000.00. 00 0.0
0.0... .00. >..6> 0. 20000000 0. .. .000.000 0. 050.000.00.55
006:8 050020.. .0 2.0.008 0... 0:0 0.8.
00. 50.. 05.0006 .0 .06. 00. 0.000005. 0. 6000000: 0. ._

.08. 00. o. ._ 008000..
000 00.00050: 00. 00.0000 .0.00000 00 0. ..00.0 60.05
00. .0 050.0 00. 0. 2.0050 00..000 0000.050: 0.50.0>0 200<

0000.050: 0.0000500 0.030. 000.00.00.00 050.0006
0.0506 0. ..00 0000.006 0.0. .000.05 0.0006 00000.00.

6.500 .0 0000.05 600000500
00.00 000.0.00 0000. 0. 50.02000 00000. 50.00 0. 0.00.5000
05.006 0..; 05.00.0500 0. 0000 00 000 .2500 60.0065
008.050.. 05.258 0. 6000800 0.. 2 22.6000.

0.00. >.0.0.000. 0. 006.0 2.0000. 000 .00. 6.6.05
0.0006 00 0. 00500050000 0.0006 50.. 0.00000. 0.... .0
..00500..>00

00. 0. 000 0.00.02. 0. 6.00 0.0 .00. 600006000 000500050
.0660 000 0.00.0.0 05>~00. 0.00006 .00.00.0.m .0
0.6.0.06

00 0000 0000.050: 00.. 000 600.0 .00. 0.00.0 .0
0.0>50..0000 .0

0.802.. 3022.. 000

 

.0N
an:

00m
n.0<

00w
an?

00w
0..?

00m
nE<

30
.60.

 

0.050.000 .000.00. .0 050.006

0... 0.0.>0..0 0. $000.... 000 0000.2. 0.050.000 00.0..0500
0.00.50. .0 000 00. 00000000. 0>00 00.000500 0500
0.0.6.05 ..00. 50.000 200

>05 000.00 0000. 00.0006 06.0.05 00000.0. 20.00. 0. 000
0.0006 0... .0 000000 00. 00 00.000. 0. 50.00.05 0260 0....
.0.0000 0. 0000000 05.0.0.5 .0... .0 05.00.05 00 2.600000:
.00 0. 00..00..000 .0 00.0 00. 00.0.00 00300.0 .0 0000006
00. .6626... .000.000 6.0.... 0. 0.0.0.5 ...3 000.0..0500
00. .00. >....00006 0... 0000.00. .50.0>0 00050.0 0000 0
000 0.60 0.00 0..; 000.0500 .050. 009.0 0000.008 0.500
0. 00.0006 0... 50.. 00000.0. 200 0. 50.00.00. 02.00 0.....
00:60 000000 000 600000.. 00. :0 05000000 60>

.00 0.0.00.. .00 0.. m. 0. s 50.. 0. 50.00.00. 02.00 055.0500
.0 000 0006.6 00.0 .000. $00.00 000 0.00.00.00. 02.00
$070.. 0550.000 5.0. 6.0006 0. 00..000 0.0 000.0..0502
..00> .00 005..

m 0. w 52. 00..000 0.0 60.00050: .0000 .0266 60.5000
0... 000 600.006 0... .0 000 00. 0.05.6 0... 00 05000000
.008. 200.0 0.0 0000 0.00.5000 0... .0

2.6.65 00 .. 00.600 0.0 00600000000006 000 00.050060
0.00.0 00.00.00

.0 >...0000 0... 000 .0.00. 0000 000 00.2. .0 00050060
00563000 000.0500 .0 20.005. 0.06.0>0 0 .0 00005 >0
0.0066. 0.500000 00 000. 6.00.0 000500 .0 >.._.0.00006
00. 00.>0... 000.0 0... 0. 00.00.00. 0.0 000000.600 60.5000
0000.050: .05000 0000.00

.0 00.. .0... 00. 0.0 0000006 505000005 .000 00660.0.
mmoo...<2mz “.0 0010.200

ww<wm§ oz< whmm0 ...O 00.0.0200

 

 

 

 

 

 

243

 

 

.0000; .0 0.30.0 00. 050.66 6.6.05 05.600.
00. .0 00.000.00 00. 000 00.6 60050555 .0 05.0.50.
.0 600000.. 00... 00.05 00 .00 000 0.0005 0.0006 0.0.0000
.00. 00.6 60050555 >0 00.060 00 000 ..00 05.0506 00.0

.660 0.000000 50.505

0. 6.500 .00005 005000. .00. 0.06.0 000.... .0 05006.6
00 0. 000 0. 0.00000 60.5000 50.. 00.00.50 .000 .000
.050. 00.0 00.0 0.0.500 .055000 .0 0.000 00. 0. .0000 00 0.
00.0006 0. .. 05.000 0. >000000. 0 05.0000 0. .00 .0>.0000x0
0.05 5.00 0. .000 00 .. 05.00006 0. 0000000 02.0000
.0 0>...000 0060000500 .00 0>00 000006 0.0. .0 0.00. 0.0.“.
...00 00.

.0 0.00.0. 000 00..0.00 00. 00665. 0000. 0.005 000 0.0.5
0. 0000.00. 00 .P 050.000.0065 6.5.0000 .0 005 00. 000
..00 0... 0.0. 05.6. .0 000060600. 00. 000000. 000006 0......
.0.00006

0.26.0 000.... 00.0 0. 000 0>.0000x0 >6> 0. 6.500 .00005
000... 000000 0. 6.05.... ..0... 000500 0. >..0.x0. ..6. 000 .0005.
.0.00500..>00 __050 0 0>00 .00. 0006.060 0.50.0>0 >60<
.006000 00.00500 60.0 000 000.> 0505.6 .0 00..

0. 660 0000.0 00.0.050. 0... .0... 00 20260.00 000 2.00005
0000.... 6.500 0006.060 .0 000 00. 0.00.5..0 2.0060 .660
0.0060000 5050.05 00. 0.0.0.05 000 05.0506 00. .0 .00..
0... 00 .060 0>..0.000> .0. 50000.0. 0.0060000 00 00.60.00

.60....6. 000.0 0 00 0.00 000 0500.0 0.0..000
20>..00..0 6.60 0>..0.000> 0..... 0.000 05>0 .000 500. 0.0.00..
2.050 000 0500.00 0.0.000 ...3 00.0 6.60 0.... 05.0506
00. .0 .00.. 00. .0 5. cm - on 00 .060 0>..0.000> 0 50.0

 

8N
66<

80
an...

80
Lain...

 

.0000... .0 0.26.0 00. 00.5.0.5 0.00.00

.00000 5050.05 00.0....0 05.0.0000 00. .0 6.500 0.000004.
...00

0... 00 ..0. 0. 000.00. 0.0006 .000..00.600 00.0.0.00 00000. 0 ..
00000 .0606... 00 06.... 0.50. 50.. 00>060 5.0. 0.00..

5 00.600 0. 0.0>0 .00 0.0.000 .00 .0... r 0. 0.0 .0 0006>0 0<
. 0650220 556550 000 .0.000000020

.0>..050 ..0050 ..0000.00 0.0 000.506.. 6558 .005 00...
.0500... 0 0. 0 >66 0005 2.0560 0.0 005.0560... 000....

.0 00>. 000 2.5000 00 000000 00..00..000 006.06.. .0 00.0>0
.0000 0. 00.0.0.00 50065006 0 00000 0500 0.

..000. .00005 000.

600000 0005 0. .. 0000000 250000.. 0.05 0000 0. 6.58
.055000 0.055000 0...... 000 2.00005.00..0.500 0.0 0000>>
.0000; .o 00.6.0 0... 05...... 9.0 0.000...

50.0 00.0 0...... 000.0 5 05.0506 0... .0 60.. 00. 000000. .00..
000. .0000... .0 6.6.05 .00.00.0 00. 0. >..0000 0550.0 00....
.660. 00002.

..0 .0 00.. 000.0.505 0. 05.0506 00. .0 .00.. 00. ..06000 0.
0000.5 “.0 09.5200

00000.0 02... 00.000 “.0 ..Owwzoo

 

 

 

244

 

 

$35.5 EB 3:0 .0 xm:
9: $885 8.x 333 9.5228 .2 £02 _macmE ho mm: 9:.
.8933 2 5mg “6 >5? auctmm omamo >9:

65 megs Emma. new 955 M6 xm: 05 $8.05 298 2520
.5835 9.0.2

__o xm: m m_ 99: con; 323m 3 230%... EmumanogsE
:30 “_o 5:38 9: new mug; *0 65:8 .358 och

 

 

”mc_Em>>
SN
.muooz, ER. 9 3:22 mum mm: an?
253 Ea «Sm EOE 9:98 25 umo. 29:03 05
msoaum. ...m__mEm 53:. En 883 9:. .32220; 2.53.6 mom
.0 cozmgaam m5 .8 mEQm>m 9.32am 0E2? 30. am: an?
. .3303 55, .082 5
0mm: 53 mm: 39:59 35. 295.0 new 3: :o 9.28%
flaw» w 2 v _o 0:. m mm... :85 .953 gm; yo ztsem now
05 .0950 2 :93 55 5:853 9: ho boo: 2.: .300 an? 8.203 momw>>% AOmEOo

 

 

 

245

 

 

...8 as .39....
.8. o... o. 3.3% on :8 65 $553.23... new 6.0.... .3
BEmEoEEoo Eon 0....2. w. 3531.08. .maEsréom 2...?

.9382

8.3% .25 820.9... 5.; 8...... 2... 3:25:29... 2:
683.....3

.552. 2083950 2 9.38% _mcom as 8552.82... >32

.83 3 :8 c8033...
«:23 Ea... 33.3. 0.590 .29.... 6.2.9.. c9820
.28.. 3:8 EB. 2.3m a... .mu._om 3.880... .33 .22.
9.8 .mmsm 905:5. .wo_Em..o o. .cmeano m m. c.2205
2.... ..o..... 9.. 939...... .0555. 0.590 .5888 new 80:3...
.8520... 0.590 .0 9.33.33 5.? 205.?3 29:29:00

.38? Eu... .2 2.0.280. 29.33%
.moE m5 5 5555. 3:80. am... 8:25.02 :33..aam 3...

£203 0..—mum van
5533 m5 9 9.6.88 :88..an 83.3.0. .0 2:3. 05 an)

.89 REESE m5 .0 flmoo 05 $396 new .2 3.3:888
£3.55. 5 3:39. 05 688.900... 9.5.. £5.53:
.0 mac. 9.. mm~.:._c.E $80... m2... ...xoom 2 on .3 .0555.
.0 >553. 2.. $898.. Sn .03. .o anEm 05 330.0...
2.: .mcozflaam 583.3 2:. 35...... $382 2.. 8.20

.coangao 05 .0 9:95.33. 2.. new
.29....0 m5 5»..qu ..om :0 Emma 9550... 5.65.3.9 5.80!

 

an?

5

aa<

ma<

aa<

on
mm<

mm
an?

 

 

.6580. no.3 8cm... 9: .0 25m

.2853: 05 new ..8 05 .0 $2.30... 30.2.9.0 new $8.93..
9.. :0 9.9.32. 9.33 mé >55 m. 20.6 5.55.3.3 0.....
..mfizficaoa new wowtam

29:59:00 >9: :25. can 9.203. 9 .8. m. “a... .w~___..£
9.... .cozm~.__§o> new 5:96 :8 £95. 9.28m. 2 .3.
m. :3 us... .25.. m5 5 8.2m m. age... 9.. .o E. .5... as
3 Bus: m. 55:5. 8:95 9.. .o __m .2. .2229: ...Sxm
8. E... .o 8.7. .25 3.63 9.. 9.53%... .o 2:830 9.. 5.3
.EBmmcmmE 9. on You €23.38 9. oonéov £29.39... 9.
ooméom mam 3.39.... 3.553 c0888 .8... 9... 23.382.
.0 9. own 9...... .2239... .o 9. «N 630...: .o .8229.
on «.922 Ememémco. ov .0 imam... 9.. .m... 858......» m. =
.333 m. 5.69... 99.3 2.2.0.3 5.59... 9:

595.5 8.3% on 8.... c8 = 5.325... 3.8m w. 5.65.3.9.
25:5: .3_E9.o 8535...? 5.? 03.3.0. o... mmcmcmm

ZO.._.<N_.=._.mmu_

 

 

 

 

246

 

 

0.0000 0... 000 09.000
0. 05:00. 0.0;; 000.0 0003.00 0000 .0000 0 50:00.3

..0~___..0. .0 002 0... 000.550. 000 ..00...
000..00 .0 380.9 0:. 000000. 00.0 .0>00 0.... £05000 5 0.000
00.0 00.0 .0>00 0c. :0...) 00500060000 0030.5 0000020
.000.00. 0.0090 .0 E.0. 05 c_ 2320 00000.0. 00 ___s 0.00.50:
0...? .0550. 0.0.000 0. 000.0 .0>00 £0.50... 0:0 .c0_0

.00.. 0 .0 0000:. .5 .0.:0000 0... .0 .00.. c. 0.0.. 0 c_ 00003 0.0
0.030. 000s... .m.c0_..:c 00020. 2320 .05 0.030. .0N___..0. 00:

0.300.
0000 00.0..05800 0>0; .00—.0:. 05 :0 0.00090 :0 .02

..0050050 .0.. 3.000 .0.00 .0 00005:... 0....
05.00: 000 0000000. 006203 0.00. 0.0.00.0 .0... 0.00020
000E>~c0 _00_0.0_0_0 0.0 00% 0.0.0380» 530.0 00:

 

0.»
an?

_m
0%

.m
an?

 

 

6.28. 20.25500.

 

W50

 

 

247

 

 

 

00.. 0... 0.5.; 00.0.0.
.0: 0. 0.00...0.0.0.E 0 .00.00000:. .0 000 0... 00.0>0 000.00.
0.... 00.3 00.00 0. 000.. 00.0... .0 .08 0E 0.0.0 00.0.0.0
0.. .0 00.003 0 2:0 .0. 00.0>00 00 .000. ..0... 0...? ..000 .00
0000 00 0. 05 00.00: 000000.: .0 000E 0000 0.00000. 00:

..0.. 0... .0 .0.00 000 00.00.00.. .5390
0.0 :0 .0000 0.... 3.00) .0.0000. _000. 0. 0000 0000.0 00...

.0000 200000000... 000

00.0300. 000 00000. 00 :00 000350200 3.0000
.000... ...0.. 0... 0000.0 :000.00..0 ..0 0.00. 030:0 0:0 20.00.
0.0:. 0000 3.0000 .030. .0 000350200 .0.0.00.:0E 0. .0.000
0. .000.00. 0.... 0000000 3.0000 .000... .0 000350200 00...

.000.000000.

0... .0 0.0000 0... 0.0.. .9003 0.... 0.00.0.0 80.030 0...... .x00 00.
0.0.. 0.00.... 0000000... 0. 0000.0 0.: 0.0.. 0.0 0. .0000; 0...
>0 00.000 00 :00 .0.... x00 0 0. 00.000 0. 0000.0 0... 000.000 0.
.0000 0. .000.00. 000. 0000000 .00....00000

0.0.: 0. 0:0 ..00.:0>:00 0.0.: 0. 6000.0 000. 0000 0.0.030
0..: 00:00 0... .0 £000. 0... 0. 00.2080 .00 0. =0. 0.:
00.30... 0000 .000.0 .0 000.00. 0000.0 .0 ..0. 0000:..000 0 00:
...00.. 000 0... 000000205.

.0 000.00. 000 0.... 00.0:. 00.000000. 5.3 00.000900... .000.0E
.0 00.0 0 00000000. 00000.0 0...... ..00.0.0 0.0.00: 0 00:

09.000. 0. 0000.00 000 0.000 .0000.
.0. ..00. 0... .0 0:02.09: 3.0.00 .0.0000.0 0.000.00 30.
5.3 000.0 :. 002000000. .0053 000 5.3 0000 0000.00.20.

 

00..
0.2

.3

.00..

00v
00<

00..
00..

00v
00<

000
00<

000
00L.

 

00.0.00. 00 0. .000 .0.0_ 0.0 0:0

000000.03 0 :. 00.0.0 0.0 0000 0..... 00.000050 0:0 00.00.00
0.0 0000 0... ..00.0 0509.000 0... 0. ..00.0 00.000000 0:. 0.
0000000 0... 5.3 00000008. 0.0 ..0.. 0.... .0>00 .0... 0000 0.....
.000 0... 3.0000.

0. 00000 00. .0 ..00 .030. 0... 0. 00.. 0050 00.0.00 0 0:0 00.00
.00.000:0.. 0 5.3 0000000 0. 000 0... .00.0_ 00> 0. 00:00
0... 0.003 00000 :_ ...0.. 0.... .0 000 0... 00.00.00. .0.00 00003
0.00 0000.0 0 5.3 0.0.00. 0... 0. 00.. 0. 000 00. 2.00002
.0008 00.0.0000 .00....3 0.0.03

.000.00. .00.0 000.000 0. 00000000 00.0.0.0 0. 00.030020 .0
80000.0 390 .000.002 000.0020: 0... >0 00.000000 00.0000
...0: 2.000000 0. .0:.0000 .000 00.003

NS 00.0 0... :0 00.000000. .0 800000 00.0 ..00:.:0..>:0
0... 0. 0.00098 5.3 0000.000 2.00000 00.000000. 0....0
.0.0.x0 0000.00 .0 0.0.. 0... 00:3 200 0. 000 0.. 0.0.0.0...
.0>.0:00x0 0.0.: 0. 00.000000. ....3 000 0..... ..00» 0... .0 ..00
.0... 9.000. 2:0 .050 000 000 0... 0. 000.000000. .0 000 0...
2.000. .0: 00 0.0.0. 00.0w 00000000000 0... .0 00.50.20.
00.000000. 5.3 00.0000.0E. 0.0 0000 0000 0... .0 3.00.00. 0....
.00000.

00 0. .00.; 0... 0:0 09.0... 00-00 0.0.. 0. 000.. 05 .0 £000. 0.:
.0000 002.5000: 00.0.0000 0.05.0 0.0..

5.3 00.0>00 0.0 0.003 03. .00. 0... :......3 000.080 000... .0
..0.. 000.080 2.0000. ...0.. 0... .0 530.0 00. 00.0.0.0000 .0...
0.0.5.0200: 0 0.00.0 0. 0:0 ..00>.0.. 0... .0 000 .0008 0...
.0008 0. 0000.00 .00.:0000... .0.0000. 0.0.. 000.000 0.0>0 0 0.

02.0645

 

 

0.50.... 9.... 0O wm<0

00000

 

248

 

 

0.0.00. 05 5.3.00.0
000.000 05 0. .. 0000 000 .00>0.. 00000 00.3. 05 .00..00

..00. 0.0002000 00 5.3 .00
000 0.009.000 0 0.2. 0000000.0 00.3. .0 0:2 000000000 00...

0.00. 00.0300. ..00 0. 00 5.; 000... 00..... 000

.000.00
.0 00000020 0.... .0. 00.0.0000 .00.. 05 0000.00. 0. 0000.00.
.000.00 .0 000>0 05 0. 00...... 0003020200 05 20.00.00.

.000000 .0 020.000 0. 3.0.0 .0. 000000 .0. 030.0 0.
.000.00. 0>..0.000> .0 0.0.000 000 00500.30 05 0. 0000000.
000 .000... 0000 600200. 000000 .0. .000.00. 0>..0.000> 00...

.0...
00.00.00.. 05 .0 30.000 00>200... 000 00000.0 E2. 00.. ..00
.0 000000.502 0.000.000 .0 00000>0.0 ..000. .0 000000.323
..00>.0... .0 0000 0.00.0 00:0. .0 00000....._0 00.3. .0 3.0500.
00>20E. 0. 000 00. 000. 05 0. .000000 0. .00 02000008 0.00.
2.00.0. 0. 00500. 0...... 000.030 000000 .0000 000E0>0 ..0.00_

20.030 ..00000 .0000 00 .0. .000 0 00 0000 00 000 ..
..00.0; 0.000000 00 000000. 00.. 00.. 05 0000 .05 303 0 0000
0. .0.00. 30.0 0. 0.0.0000 0. .. ...000 030.0 .05 .000.00. 00.2.
300 00 000 .020 .0....00 0..; 0.00000 00 0200 .0... 0.00.0
0... .0 000200 00.0>0 0.0.030 0.0... 0.0.030 .00.000000 05
00 0305. 00.0 0. 0050... 0.0+ .020 .05000 0 0.00.3. 05 0. M

 

00..
00<

.00
002

000
00<

Ev
00<

00v
00<

00¢
00<

00¢
00<

 

..00000<000.
00000.0>0 000200 .05 30202300 05 0. 00.00 .050

00002.0. 300. 0.0.030 0.5 0.0.0.0000". 00000.0..0 3.0.00
0.300. 3.0.00. 0.0200 05 0. 00.3. 05 .0 0000000000.. 000
00000.30 05 ..0>030... ..00000.0 .0 0.00.020 05 05.0393
.00. 00 00.3. 05 00.00 .0 3....0.0000 05 0>00 0000.00.
.000.00 0..... .000020 000 000200 .0000... 0. 00.80.0000
.0 0000000 000 0.00.0 00..0300. 05 0. 00.3. 0... 00.000002.
.0 .000 05 0. 000 .00.00 0. 00.3. 05 .0 00.33000 .000
0.00.00.0000 0 00.. 0000.000 0...... .00..0300. .0... 00.0.0 000
0.0.. 05 0.0.. 00.3. 05 .00..00 0.0.0. .002 .0.00 3000.0 05 .<
...00

05 00.02000 00000303 05 0. 00.03.0080 000 .. 00.00.30
.00 003.000 05 0. 000 03002000000 0. 00.3. 05 0000000
0.00.0 000300.00 .0 ..00000 00. 00.00 00.3.

0003020200 .0 05000. 000. 0.-.... 03. 30 00 0.0.. 0.0 0.00.0
0... ..00.030 0.5 0. 00002000 .0 .000 30. 0 00.. 00.300. ..
0000000 0.0.030 0.00000 05 000 00008003 05.0 3.00.0.0 00.0
000000.. 000.

00000.0..0 0000 .05 0000.00>00 3002 00.. 00.0 .. ..0>030...
0.0.030 0.00000 0... I 0000 0.0.030 .0.0000 .00... 05 005
.000... 0. 20.030 0.5.0.000 05 .0.00 3000.0 05 .< .00.0020
.0. 000.000 00.00 0. 000000008 0.00.00.0000 0. 0.00.0
.0020...

000. 0000.00.0000 000 00000.05 .00... .05 00003050 3002
00.. 20.030 0.5 ..0>030: .000 .00.0. 0.0000 0 000 .. 0000000
0.0.030 0.000 0000.26 05 000 000000.03 .0 3.000.... <
0.00000 000 0000.00 .0.000 0000.05

.000 0. 00.0020 .0 000500. 00..... 2.00.000 0.0 0.0.;
02.00000

0.50.“. m...... 00 mm<0

 

 

00000

 

249

 

 

0.0. 00000.0. 05 0:00.50. 0:0
3:00.. 0.. 0:.>0.00. .200... ...E 0.... 0000.. 0:0 .000 00.0:.E..0
0.0.9.0 0..... 000000.. 05.00 .5... 0... c0500.. 0:0 0.00.50. 0.
..0; 0.000 0... 9.0.0 0.00.....00 0: 9....00 .5 ...E 05 00030.0

.030:
0... .0 .000 05 0.... 000009.... 00 0.000 009.0. 0 .0.... .0300
0 0. 0.0..... .00.0 9.0.000 0.... c. 0000.00. 0.0090 0:0 0020.
80.000.00.92... 0.05.5.0 0. 0.00 0... c. 0.09.: 0... .0....0000

..00.0... 0:0 000.9. .0005. 0.05.00 .00; 0:0 0.0.00.. _0...00t0.
0.0.00.. .0..00 000.0... 00>..0E0._0 0..... .00.0 9.0.000 0...
0. ...E 0... 05000000.. .0. 00000.10 000.00... 05059.0 00:

.0.000 5:00.60 05 0. 0.000
.3 00000000.. 000 00.000 0. .00 0.0 0000 2.003 0...... .0020...
05 00.50 0000 0000.0 0... .0 E0500. 030:0 00000.0 0......

0.0.. 0.... 0. 080.0 ..E.
0... 00>00. 0:0 ..0... 0... 0.00.0.0 .0000 0.0.0.0 0...... 08.0.0.0
0000.000 2.0.0000 0. 00000000.. 0.0 0000.. 0...... .000...000 .0
00: 0... 0.0>0 0. 0.0... 0... c. 50:00 0.... Ea... 00:0: 0.... 0>0£0m

 

an?

0m
an?

no

mm<

00
k4.

 

 

0.000.000 .0 .0.. 0.... 05000.0... 0:0 55.0.00 050000.
0.00.0.0 0. 00..0.000 0.... .00>0.... 0. 0.0..0. 0.... ..0...>> 0.0.0.0
..00030 0... 0:0 .0.0000 00050.0 .0 .00...:0 0... 0:0. 0:. .0
000.0 05 ..0 0000000 00000.0 0.... .0 0000900000 0...... .9003
05 ..0 .0.000 0. 0:0 .0.. 05 0. 000.000 000. 000000 ..0.
0... .0 00: 0..... $030300 0... 0. 00000000.. 00 0. .00 05 ..0
9.0... 0. :05... 02h 0.03.0.5 0.5. .0 0.00.0000 05 :0 00000000
.00 0 .0 0.0.0.80 ..0. < 30.0% ..0”. 0... 00: 0....0. 30....

.zocan

0... 5.3 .00.0 9.0.000 0... 0. 00000000.. 0. 00.. 0000.0 0.;
0.0.00? >0 030.000 0... 9.0.0 000000 0.0 005003

..0.0..0a 0. ...030500 05 9.0.0 00:0 .0... 0.0..0. 0.... ..o .00.0
9.0.000 0... 0. 00000000.. :05 0. 20:2. 0..... 0.0.6. .0 .00
0 0. 0000000 0.00.. 0 ..0 020.000 0... E0... 95... 0. £055 0......
0.0.0:. 00 0. 02.0.0.0 00.3.00 E3808... 0..... 00.003 0....

.0 .00.—.030 0... :0 030.000 0... 0. 00000000.. 0. 00:3 0.....
.0053 0.0 >0... ..0... 0:0 .0010...

...E. 00000. 0.0 009.000 0..... 02.0... 0.0.. 0000.00 .c0>0.0
0. 50:3 0... .0 0.09... 0... 0003.00 c0>o.s 0.0 009.000
.0000E00 .0.. 0. ...E 0... 00 00.00% 000.003 0 ..0 05.00.
00.2030 0 0. 000.0 .. ..00.0 05 0.0.. .00 0. :05... 0... 00.05
5.50....

0003 ...0>0.0 0. 0:0 0.0032. 0.0.00.8... o. .00: 02.0.5.0
0... :0 000.00 0:0 00009.0 0. .0..0.0E 0.0090 .000.00..
0000.0

0.... ..0 ..0. 0. 600000 00..00 ...coEEoo .E0.000=000 0.;
.0055 0... 0.600 .0...— ._.0.0 0... .00

o. 05.5 .0 0.0500... 0 9.00 2.02.06 00.0030; 0. £0.50 0.....
hmw>m<z

 

@000

 

 

250

 

 

000000.00 00.2.2.0. 0000.000 000000.. 0. 02.00080
.0.00000. .0. 0000 00 .00000 .00. 0000000 .000. 00. ..00000

.0000 .00.0 .0 .0868
00.80 .00.00 .0 02.00080 .00.0000. 0. ..B. 0080.0. 00. 00:

.0000
.00.0 .0 ..0000 00000.00 .0. 00000 00. .0 0.0.0 00. 00000.0

00000.00 000.00.
.0. .000.00. 2000.0 .0 00.000 0 00 ..00 0200.0. 00. 00:

.b__.00000 .002.8000 0.. .00. 000 .. 0000 00.0.60.
0. .00. .000.00. 00.0.60. 0..; 0000. 0.200 0.00000. 00:
0.2.00 000003 00. .0.000

.0.00.E000.0.00 0......
00.00.E0.000 0. .00. .0.03 .000.00 00. .00.. 0. 0.0..... __800.

020.60. 00 000 00000.0
00.2000 00. 5000080. 0000 .0.03 00. 00 .0.03 00. .0000

.0200. 02.00.00 00. 0000.0. .0.03 00. 0.0.60.
000 .0000 .0.03 .0 00.0.0> 00. 00000. 0. 0200. 00. 00.0000”.

0.00.050. 000 00.9.00. 0. .00. .000.00. 000.000 00:

 

.0
0%
_0
0%
..0
0%
0%
.0
0%
0%
an...

an?

00
an?

00
L002

 

 

0.00.0. .8300 0.0.. 00.00.000
0003 0.0.. 0000. .00 000 00.05.00 0. 0003 00. .00.
00.00.000 00 0. 0.00. 80.0.00. 000 0003 00. .0 0.000 00.
00 .0008 00 0. 0.00. ..80000 0. 0.200 00000; 00 00200.0
0.0 00.60 00. .00.. 00. .0 00..00..000 00. 00 00.000000
..00.000. .. 0.00 0. 000 0. 00.0 000 00.00.0000 0.0

00.80 00 ... .x00 00. 00.00. 0000.0 0. 000 .0 .0000 2.00.0 <
.0.. ..0. 00.00 .00.03 00.00.00 .00E 00. 0..; 002.00. 00. 00
0000000 .60 00. .0 .00.0; 00.0 00.80 0. 0000.0 0. ..0... 00 ..
.00.0

000.000 00. .0 .0.0.s ..000. 00. 0...: 00000.0. 0.0 0.00080
0000. .0 0.000.00. 00 .. 0.00020 0000. ...000 0. 0.000.000
.0.0000 000 0.00.0 00.0w ...N08. .0 2000000020... 000
0.00.0.< 0....0 00.00.. 0. .. .00000; 0000 000 ..0... 00. 0000
.000000 .00 0.0... N. 000098 02.8020

000000 0.8000600 0 .0. .00.0 000.000 0 0. 00000 .0.0>>
...E. 00. 0.0.0 000 .00. x0.0. 00. 0>0E0.

0. 00.00.:. ow 0. t. .000. .0 .0. ..00. 0.0. 0. 00.0.00. ..00
00.. 0.00. 00.x0.0..00 00. 00..00 00.0.5 0.00 .0020 0...... ..00.
02.0.2. 0 0. 00..00000 0. .0..000 .0.000 000000 .00. 00.. 00...
$00-8 0.0.. 00008

02.00.00 00000 0.8 00000.0. 00. $0.000 .0 00000 000
0000.00 .0000. .000 00. 00 00.000000 0.000.. .0 0.0.00.0
0.0. .00 000 22.000 ..0 00.80000 .000003 0. ..00 00...
.0..$. 00>.00 0 00.00 00000.00 0.0 00000 00 ._.

.00>00.0.

000. 0.0 0.030.. 00... .200 0009.0 .00 0.0000 00.000.
008000.00 00... .00.00..0. .0 00.00000 000. 000.8000
000 .00.00000. .00.00000. 0.0 0000000 00. 000 00>900.
0.0 0000 2.00.0 00. ..00.0 000.000 00. .0 .0200 000...

02.20.00

 

 

 

251

 

 

. .00.0 000.000 00.
0. 00.0.0 00 .00 0.0000 0.020.000.20< 0.00003 0.... .0 20.00
00. 0000.00. 0. 000 02.00.2808 .0.00202.>00 .0 ..0.. 00.
00000. 0. 0022.800. 0..; 00.000202. 0000 2.00.0 00. 000
0.020.000.200 .0. 000000203 00. 00.0000. 000 0.00200

.002 000 00....00 00.0.0>0 000 02.80000 .0 00.0.9 00.
00.0000. 20202008 020000 2.0.02.020 0. 020000 >200
2.00.0..0 _000..00>08 00. .0.000. 000 0.000.000 0:.>0.00 00:

0020.08 00 000 020000028
000 0000.0 .0 0...00 000 20000000.... 0.0 0.00.. 00. 00
0.0..2 000 0.0.00.. .0000 00. .0. 000.0 000000.200. 00.00000

 

E0
00<

 

.0000. 00. .0 0200
..0 002.020 0.0 0.020.000 .0 .0020.0.08 000 00..00>0.0
0.020.000 0>0E0. 0. 0.0..... .0 00.0.0>0

.000...000 .0.03 ...000800 0>00 0.00.0 000.000 30. ...0>
000000.. 0. 00..00000 0. .0 0000.020

00. 0.0. 00.0.0280. 0. 0.0.... 00. >0 000.0.0. .000.00. 00...
0.00.. .0 0.0000 0.0. 000.0520 0. 000. 000 00..00 0>oE0.
0. .0.... 0 0000.0. 000000 .00.0 000.000 00. 0.0.. .0.03 00...
.00.0.0 00. 0. 2.2.2.0 0000000.

000 0082.8 0. .0220 000 .032. 00. 00 0000 0.00.0
000.000 00. ..0 00.0.0000 0.00.... 2000.0 00. .0 .00. 00...
.00..0.00.0

00. 0.0. 00.0.0280. 00.00 0.0.00 0000000 0.0 00.0.0
00. 0008 00.00 0. .00..0.00.0 00. .0 .00.. 00. 00 00..00000
000 0.00 00. 0. 00000000.. .00.0>80. 0.0 00.0.0 00..
02.0 0000 0. ..0.. 00.8.0. 00. 000.0 0.000020

.00.0 ..0.. 00.8.0. 00. 02.000 .0. 000000.. .0 00.0.0>0 0>00
000..0.020 000000 00. .0 .000 .00 .00. 00.0.. ...0 0000020
00 0. 0000 0000 0>..0E0..0 .0. 0.00.00 0. .00. ..0.. .000.000
0.000203

.00.0 000 0.00 9.00. o. ..0.. 00.8.0. .0 00....0000 00.0.
00.0008 ..00.00 000 .00..0005. 00 0000 0.00.0 00.000020
.00.0 .0 0...00 .0. 000. 00 0.00 00.0 0. ..2. 0.0. .0 00.0w
02.00.0008 000.00 .0. ..0.. 000..

00 .0.000. .000. 00. 0. 0.00 0. ..0.. .....000 00800 00. .0 0.08
.02000 .0.00

0 0200.008 0. .00.0 000.000 00. 0. 00.0.0000 0.00.5 00...
00.0.0050.

00 .000. .. .0.000 00 000. 0.00. .0. 0.00.. 00. .0 .00.0.08 00.
0. 2.050. ..0.. 05 ._ .28.. c. 000 0. 00000000.. 0. ..0.. 0....
.208. 000.90..

 

 

 

252

 

 

8:33.50 2.53 2 .228 .6 52»? m 5.3—gm
.055»; new 35623 293 m5 2 352 3»sz
305 9.6205 dim... 29:03 955050 226.32
new 36. m5 5;, zano 920ch __m. 55 233mm

.vto; :05 .2 £2.55 a mm 2208 x_m
:03 £9.33 uoom .2 8228 new $3 3:890» 05 5a

$5280 .0 5:555
95 00:35.3 8882a 55 E2m>m «23 a 23.0

€38 Ea £96 8 8mg 28 on 232.9. to; .2
23:10 23» new >596 .8 33:3 3 82m? a 29:29:.

.cozmufiooam 505;,
955 m 2 Sam. 9: __m oscgmmm 303 he E9m>m m 8.63:.

 

can
an:

sun?

can
an?

can
an?

«E
nar<

 

€82.05 3 brown. 05 .3 3959.2 m_ =5

.53.: 25 “o: m_ 00:08.. mE... .mEmcmn icon “.0 $80 05
295 2 33.3 35 5;, $08.50 mme was 8:Em_EE_
.30.: EE mcozflcma 3a.... 62¢ .mEmNm; 35.3380
82.. 3:33 van .3303 Eco». ..cmE>o_aEmc:
$3 3:893 new ooze... 5:08.05 .55.:
5:335 .mcozmoma 300 .5953 05 3 355%.»
9:30.. Eco» «289 89:0; 9: .2299: van £9.33
9: 5E 58% 52:8 28353 ho €035 2:
mtawzmm ..<0m._

.2338?

5 “8:9; 05 2m 89:03 2ch ho $585 2:.
mm_m<._<w

.omEEEoo =85:on m5 5;, 95383:

505? acmecwmcmtm 035 c. $9.20 9.9: 2 om:
“o: m_ coaflcma 9; 29:03 ho $5888 “coca—EX
m 5? 282:. 85:09.: 2m 8me .65 new mme 9:
gang 250: cm :0 Ban 9m mxmfl m5 .0 3m“. bm>

.xmfl mcficoawmtoo m5 .8 x83 B :5 .3

Ban 2m moon; 9:. .So moEmo .383 05 55 xmfl 05 o.
@5288 :9, 8mm; 2:. dam? m mm: mxmfl “.0 flow comm
.20: m5 s 968 ho “mm 9.0 5 3:30QO £9.83 9:.
539:8 mcmcma 9:

E 2626 33.an 2m 39:03 «:23 “_o btofiE ma...

wmozbéa 02.1.1
szEDZOO 1093 Loz< 4<_00w

 

 

sumo

 

253

 

 

.000...03 0.0 0.00.00 0.0:. 0.03 >0.» 0.
000.0 .0.000000 000 0.0» 0 0>00 00.0..00 0:00> .0:. 00.00.00
0.0... .00..0.00.0 0:. 0. .003 0. 000. 00 00...:000000 0500
0:. 0>00 00.003 00 0.00:0» 000.0: .0 E0.0>» 0 :0..:0.0m

0.0.003 .0
00580. 0:. .0. 000.0000».0 0.00000w .00.>0E 20.003 .0000..0
0. m0) 0 5.3 .000. 00.0.5.0. 0 ..0.00. .00.0 0:. .0 >.:.:0E
.000000 0. 0.:0>0 .0.0..00 .0 0.0.00.0 0 .00E0.0E. .00.0
.00—0.00 0 .0. 00.0 000.080 0 0.0.0.00. 0:0 .00..0000 0. 0.0...

.0.0000.»
000 000>0.0E0 .0. 000.20» 000000.. 00.5.0 0. >0000.00
0000000000.. 0 0.00000 000 .00..»000 0. 0.0.003 0.0:

.00.0 0.0. .00E0_0E.

0. 000..0.00000 0.0 .00.00. 000 000.>00 .000.003 0»:
.>:00.0000. 000 00.000 .

000.500. 00..00..0000 .0 00..00..000. .

00.00 ..0. 0 .0 000. .0 0.00 000 00000.00 .

050000.“. .

”00...>..00 00.326. 0:. 0. 00.00000 >0 000.000.2000
00.000090: 0:. 0. 000.0: 030 ..00. 8.0.0000 0. 0.0003 0.0...

.00..0.00.0 0:. 00.0.00 0.... 0:3 0.00003 0:. .0 00.03.03

 

000
an?

3.0

an?

00>.
an?

nah
n_n_<

 

000.0 0:000 000 00.2. 0:. .0 0:0...0000 0.:0.0>:

0:0 >00..00» 00 __03 00 >500: 000. .0008 00.00. .005.
.0000 0.0000000. 0 .0 000. >.._000 0. 000000 0>00 000.003
.0:. 0.0000 0. 0000.00.00. .0. .00E0.000 0030.0 000
0.000 >..00.00.0 .050 00.00.0000 0.0.0.00. 0080.003 0:...
000....

.000...0000 .0 00.2.5 .0. >000 0 000 $00 0.00:.05. $00
0000.. .0. >000 0 .00: 00.0 >0: ... .0800. .0 000000.590
0:. 0. 0.000.000 000 0002.00 00.0000 .00x0_00.00
0...00» 0.0.0.0E 00008003 00000: .0 3.00.00. 0:...
20....<mmowm

..00000 ..00... 000 0. :0..0.00.0 0:. :0 00.>.. 0:00.003

.0 00.0..00 0:. .0. 0000000000... 00030.0 :0..0.:0.0 00.:
zO....<...mO0wz<m... hzwoahw

.00..0.00.0 0:.

0. 0000...> >900: .00: 00.000: 0.0003 0:. 0. 02. ..000
0:3 0.0.003 .0. 0000000000.. 00390 000..0.00.0 0:...
zO...<._.mO0wz<m.r «9.00.5

.>..0.._.00.0 ..0. >00 0.0: 0. >0.»:00 0 000300 0000.000

0:. .00.0000 0.00003 0:. 0. 0>.. 0:3 000>0_0..00 000:. ..0...
>..._0_mhom..m

..00.0 00.0.0.0.00. 000 .0.0000. .0 .0008 05000000035
00:00:00 000000 00.03 0.00.00 .000000.0.0E 00.0.5.0
.0. 03.000000. 0.0 00.000800 0:... .00...:0. 0.0:. 000
0.00.003 .00000000 ..00. 0. 00.00: .000 00000203 >00...

00. 00.0.0000 0.0.: .00..0.00.0 0:. 00.000000» 000.00.00.00 026:0...
0:. c. 08.28 0.3.0 2,905. o. 22.0.8000 20002960 2.. 02900200 020.003
080300.00 20 00.00500 _000. 5.; 0.0.30.8 202.2 00< 000.30.»... 0005 02< .5000

 

 

 

 

254

 

 

00......2 05 50.03 50000 .05 05505590 2080...

0.2000 05. 0.00.... 0.0... 2.03 .0.000.
22500.. 09500:. 000.0 55.0 .2 05 00.02550 03.9.0.
.2 00000 205.000 .00...:08E00 92.02.90: 0. 05
3.5558 00.525... 05 0.5.3 055.500 03.9.0. 2080....

052.03 55 .2 050.00. 2.82
.2 00000 00 55050.0 0550 .2 000: .0: 05. 205.03

6000.00 0.5 .2 525: 00 50 <2. .0 00.0.8.0
0..... 00.5.5558 05 05 05525.0 05 2 002.50
0030.0 .05 050.55.50.05 .0 5500.0 05 2080.0
2 0.02.03 05 .0 00......2 05 .2 5050.0 9.50.. 0 50.523

 

5..
an?

.3.
an?

a...
an?

.2.
RE

 

.0550; 05 2 5.2.0 05050 09.... .0 050.000
020.205.. 05 .0 ..00 00 .0 0005200000 3.52.8
05 530.5 55.0 0.250 5.58.50 05; 0:5. >52

mam...sz >....z:s=200

62.0.3.5

5 00 005.000 0.0.5.. 0 05.. 05525.0 .0 3:20... Eh
.00.._E2 ..05 05 0.0503 05 00.300 2 .2000 €000.00

m 2.0 0.5.0 .0050... 0 0.20.0... 05525.0 .0 >520... 0.....
:55...

.2003 2056.5

05 000.3000. 02000.0 £052.00 0.0>0 2 00.50.. 05.0000
05 0005.05 5525.35 0. 00000.0 .050 2 95.20
0.0 08.2 0.05. 052805050 05 0.02 92.05,.
.2 00050... 200 05 .55.. 05 000.0 .0 55500050. 05
:0 000.300 50500.0 ...050 0.0050 520 05525.0 0...00
02.222...

.0:..2E: 05 050 050020.. 2:05:00

00.0 5:... 00500300 .2 00.0.0000 05 00.20.2050 .25
080m 0.02.00 05 .0 0055.508 05 59.0.5 5.2.5
.0550; ..05 .0 558:5 05 5.3 0.0.. 05525.0 >55.
20....<o:om

.0.000. wzfifizoo 02.2%;

 

 

 

255

 

 

.05.. ..00. 005005550 00.0.05
00. 00 00.000000 002 0.05 ..0... .30 .050 2 0.050... 2.00.0.0
000 050530 2 0050.550 .0 020055.00 0300. 5.00:
.0 250.55. 00. 000 .00.000050 00503020 .00..005000
.0.00.>20 .00..0000200 .m<o .<z<mmoo 0003.00
005200000 00325 0.0.020 00.0.05 005.03 0 00..020m

.50.... ..05 .0 0053005 05
5 0003 00 .032 .05 00055.0 00500.20 25.05.35 000
00.300020 5.0.00 _0005003000 05 ..0 003.00. 0.32.0 00.300
0...... 0.0.50; ..0 .2 02300 550.550 5.200500 5 00..020m

0030.0 05.0 00050.0... .2 00050000 00..0200 05.00.00.300
50.00 .0 003 05 005.300. 0030.0 550550 .000. 0 003.00.

00.30002
0520055 0.2020 2 000300 05 .0 0.0.0000 5 003.00.
05 0.50.000 _0005003000 ..00... 2 0.000 0.00 0 0.00.0

000.0 50.... 05 .0 00.20505 05 030.5.
05 65.0.... .0550; 000.2005 000 000020.000. 0.0.50...
00. .0 005.0000 50.030 0... .2 0.0.000000. 0. 2.3 .2000
50000.00 0 0003.00. .05 ..03 00.0.000. 05255.0 0 0030.

5520.300 05 0.00. .00.00 05 05 .0552. 0.030000
.500030 .00..0.00. ...0000000 00520 0.32.0 ..03 2F 0.0.50;
0.... .0 5.00.. 05 .0 0.000 0.... 00 00000.0 0.0 005.500
_000500500 .0... 00 ..03 .0200 _0005003000 05 00500050

 

.0..

00..

0.02

00..
an?

00..
0.00.

00..
000.

00..
an?

 

 

00.05 .0550. 0.00500 0>00

2 20.00.... ..0... 05300. 05525.0 .0 500.30 00.0. <
0.02 0.... 2 000.3000. .5502. 0.00.000

05525.0 0... .0 .0520... 0... 6.205.... 5520.300
00N._0.0000 05 0.02 0.02.05 .000 05 .0 5505.53
05 000 00.000 0... 0. 2520.0 .5502. .02.. 05
.0 000 0.000.000 _0005003000 050.550. 00 00.000 00.0.
0 0. 0000000 00000.0 00..03020 05 .0 55.0.50 0......
.500... .0 0.0.5.2 05 ..0 5.0. .00 05.0300.

05 2 050.0000 000020030 058. .0 .000.00050. 05
.2 0003055.... .0.0000 0>00 05525.0 .0 .0520... 0...?
500205300.

0.5 0...... 20.000 05525.0 05.0 55200. 0...... ....0.00..00
0. 5020.300 00500.20 550.00 .5. 000.2 2000 .000:
0.2.... 0.3.8.2.... .3505 05 2.0 .22.. 2.0.05

.0 23.500. .000502 05 ..00.0. 000050 00 00.00.2050
.200202.>0w 05 0032... 00.050 0.0 00.000200
00.0. 000 ..00.0 .0. 0.00.020 00.50.... 5.0.00 _0005003000
0. 0.050.... 00.0.05 .0. .00.0..0 0 0>00 00.50.50 00.0. 00...
.02.. 50.00 .0

0.3.500. .000502 05 2 0.000.000 5000. 2 05 0.50.000
.0.00503 .0 0050520 000.. 2 005300. 0.0 05525.0 .2
.00.0.020

..05 0.200.. 0. 05 00.0..00...00 .0. 5.00.. _0005003000
.0. 005500.00 .0550; 0 05000.0 05525.0 .00.).
..00.00 .0.00503 .0 .00E00000E 05.2 ..03

02.050.50.00 .0E0.5 5 0>00 05525.0 .0 ...5200. 0.....
00.0.... 009.00? museum 0.. wwoFo<m0
wmo....0<m0 «.005 020. ._<.00m

 

 

0.500

 

256

 

 

 

.000 0..;
.0 80.050 .5800... 055.0. 0 00.03 50 00.50.00 .0500 00.30

0550.00 2
.050 0203005 00 2 0.00 .00 0.0 00002083050 05.03025
.0. 2.3 0.0050... 0.0.. .2 0.2.000 50000.080 00..020w

200500 55002. 055.050 .0500; 05 0005000088002
.03020 50 0058.200 085 .0 00500 0 .0. 00.05 0... .0 .30
80... 000.. 05 00.50.00 .0500 20.00 0.0.503 0.0.. 0.0300>w

.0.003 .0 00.08.00 0.0.0000 0... .0220 0. 0000N .0500

c. 00.00... 00.0000 0.0.00 .0 0.... 0... 0..; ..0..:00 00.0.0.0
”005300 .0 0.02

...50 .00.8000200 0.3.000 0. 000 0.05.00 05.... 0.020

0. 5.0.0.. 83.008 0. 320 .0... 00.0000 0..; 0200.0 0.0 00000
000... .0... 0.00.220 0. ._ .0050 000.... 5 030.0 00 .00 0.3000
0.00.8000 2.300. .00. 000.0 .00.0 .0 000003 0.2.030
00.>.. 0050.080 000 ..00.0 005.000 00. 80525.0 0...
0003.00 8 00. .000. .0 .0 00000 .0..30 05 550220 2020

005500 _0005003000 .00>0.0
0. 0503. 0500.0 020.050 00.03 00050.0 000530030 __200.

00.....00. ..00.0 0... .0 0000.000 0...
05.08. 0. 0.20.000 .00.0 00508 000 00052080 0030020....
.20.... .2 000.300 5.0.00 00882020 .0055. 23.500.

 

.0500...

..0..
..0..

.0..
..00.

.0
50.0.0.
005
0.0.0.

00.
..0...

 

0.250....
000... .2 02.302 0. .0080.300 0050220 0.03020
0050.00 0... 0. 000005 20 008 00.. 00.0 00525.0 0...
5 0.0.50... 50 020.30.008 80.050 00.. 0 003 00.000800
00.50.00 .0500 00. .0 .02 0..... .m00 0...... 00.50.00
.0 2.8.. 0... 0.05000 0.05200 .0 0320 .00..008. 0<
.00..0.00.0

0... 80.. 0.0530 00.>.. 00.580. 05 00000 .0..30
00500.0 50 80.020 0.0. .0008 2 03000 0>00 05525.0
.50 0..... .0000. 0. .0000200 00000 .0..30 0>00 .00
00 05525.0 .0 5.5208 0.... .000500 05 080050 .205
.0. 0000~ .0..30 0... .00000. .00 00 05525.0 080w
.00..0.00.0 0... 50...... 0.05030 00.>.. 0050.080 000 0.00.0
005.000 ..0... 0>00 05525.0 .0 .00830 00.0. 0 0052.0...
.000500 .0 0.0>5 0.00.0 005.000 0.0050 0.2000
550.3000 00.50.00 0.0>0 0. 000.0. 20 05530020
0.0.00.0 ..00.0 .0 .0....00

0.8.805200

055.000 000 0050020.. .2 0503.500 508 0... 0. 000050
0.20.08 05 ..200. 005. 00525.0 0... 0000.0. 0.2502.
.0 .008058 0... 2 0.05.00 .00020 0.0000 0... 00503
00050.0

.25. 00.0.0 0000.002. 00300.. 05 00055.0

 

 

 

257

 

 

 

.6555» .o 50.9.20 .003 .o 05.20..
0:.>.0>:. 00...>..00 0:.:00 5002.028 000. .0 :0...:.:0.0
.0:.:003 0:0: E0000... 000..00.0 0:0.0»: 0>0.0..:.

.050: 0.0
0.0>0. 000.0.00:..0:0 0:. ...:0 000:0:0 0: 0.00:0 00...>..00
0.0.003 0:. 50.0.: .00.00... .3 00:..E0.00 00:0. .055:
0:. 30.0: 0.0>0. 0.5.5.0 .9003 0 .. .0:.:0E 00.5 b0>0
0.0>0. 000.: .0..:0E 0:0 00.50.20 :..3 .00.:00 :. 0. 0:3
.9003 :000 :. 000.0.00:..0:0 .0 00:0. 000: 0:. 05:00.00

..00:....0::00>0. 0:0:3: 0. 0.x0. 000. 0.0.0:.
000.0..000:. :..3 000: 0000.0 0:. :. 00.30.20 0:. 0.0.0005

.00..00 .0.:00. 0:. 0:0 :0..00..000 .0 0.00
0:. 0:..00.0:. 0.000. 5.3 :0..00..000 00.0.0.0: .0 000.0 000.2

.:0.: 0. .0..:00 .0::0...

.0 .08 9.. ..0..; 0.8.00 c. .00.... ..0... 00.6. 5:5,. 26.
0:0 .009... .0.:0E:0..>:0 30. :..3 0020.90: 0.:.0.0>0 >.00<
.00.0

.0>00 0 .0. 0.0009000 00003 .0 :0..00.00 :0:0.:. 2.00:0...
00003 .0..:00 .000.0.0.0: .0 00: 0:. 0.0:.E..0 2.0.000

..:0.: .0 .0.x0 .0:. 0:0...0:00 0:.3 0:0 0.0.0.0060. .000:
0:. .0 000.:0>00 00:0. 0:0 :0..0.:0.0 0:. :. .0: 0.0 0.0...03
0.0.. .0:. 00.00c0 00:.0E 0...... .:0..000. 0:0 :0..00.>0:
.0. 02053.8. 050: 0:.>0.00 .0E:.00: 0.0...0c. 0:0 .00»

00800.. .0 000.0 :. 0.0.00.0:. 00 :0..0.:0.0 0:. .0 .00.. 0:. 0.
00.0:0:0 0000.0 0.50.: 000 .0.:0..0>0 .0: 0. E0.0>mm.w 0 ..

 

8..
aa<

.00
an?

.8.
00<

00.
00<

00»
0.0.4

:00
an?

E0.
an?

 

.000.0.0:=. :000

0. 0.09:0:0 0:.>0.00 .0.0000 0>0: 0.:0.0 0:...000 050.0
05600

0.0.003 ..0:. .0. 5060.000

02.00.90 0.000000 00: 0:0..0.:0.0 .0 3.8.0:. 0: ..
0000>> .0 .0..:00

0.0>0 0:. .0 0:0 0:0 0:.::.00:

0:. .0 0.0:.0 0:0 0.0>0 0:. .0 0.00.E 0:. :. 0.0:.0 0.0>0
:000 0.0.0: 0.0.003 .00. 00.:00600 050w .000: .0000.0
0:. :0 0:.0:0000 00..0> 0:..0..:0E .0 >0:0000.. 0: ..
.00.0..:0:. 0. 000... .0.0x.03 :. 000.0.00:..0:0 .0 .0>0. 0:.:
.000.0..0:.0: .0 5000.300 .000 .030:0 .0:... 0.0.002.

0.0.. 0N.E.:.E 0. .:0E0.:00 02.00.90

.003 0. 00.500. 0.0 000.0..0E0: 2000 0:3 0.0.00.5
.0.x0. >.:0.: 0.0 000: 0.2.00.0 0: ..

00020802 .0 .0..:00

.0....00. wwa .wmmxmog mozomm O... wwo...0<mn.

 

 

0000.0

 

258

 

.wz. 0:0
mmoo .0 000.200 0:. 0.:0E0.0:.00 0:3 .0.000 0:00:80

0 0>0: 0:0..0.:0.0 .0 .0080: 00.0. < .0:0..0...0:. 000:. .3
000.>0.0 000.200 0:. 02000. 0. .:0.. 0:. 0>0: 0.0.0.05
2.:.0. .0:.0.: 0:0 .9003 0:... $2.. 00:0.00:. .0
0.2.0... .2202 a... 0:0 .0000. 20.090 2580 .080
0.00.0 0.000 :000.:. 00.00:. 0. .9003 :000 .30. >0

...zmsEflE. ._<o.om..2
mmo....0<m0 ”.005 n..z< ..<.oow mwxho

 

 

0.00096 .9003
.:0>0.0 0. 0.:0.0 0:...000 0:. :. 0.00805 0:.>0.00 00:

0.:0.0 0:...000 0:. :. 00.0.0 00
.0: 0.00:0 0.00.80:0.0.0< .:0..0:.:.0.:00 .0.:0E:0..>:0 .0
..0.. 0:. 0~.E.:.E 0:0 0.0.00 .0.0:.03 0>0.0E. 0. 000: 0000.0
0:0 0.00.80:0.0.00 .0. 000020.03 :0.0000. 0:0 0.08.00

.:00005. 2.0.00000 0. 0:..:0.. .0 :0.0000.
0: 0 .>0:0.0E0 0>0.0E. 0. 0:0 0.0.003 .0 5.00: 0:. 0. 0:0:
0N.E.:.:. 0. 0:.... :. 00.E0:00.0 :..3 0.00.0...03 0:. :0.0000~.

..00.0... 0:0 000.0: 000.0. 0.0E.:0 ...03 0:0 0.0.00..
.0...00..0. 0.0.00.. .0..00 00 :000 ..:0.0 0:...000 0:. 0. ..0..
0:. .0 0000:0.. 0:. .0. 5000.. .0 00050:. 0>..0E0..0 00:

..0.. 00.0022 0:. .o 0.000 026.05.
0:0 .0.00.E0:0 0:.»:00E0000 0:. 0:0 00000.0 .0 00.. ..00 .0
00:0:0.:.0E .0.:00.000 .0 :0..:0>0.0 ..000. .0 50005080
..0020: .0 0000 0.:0.0 5:0. .0 :0..0:.E..0 .053. .0 0.0300.
00>00.... 0. 000 :0. 0:0. 0:. :. 00005 0. .0: 020:00x0
0.0... 2.0...:. 0. 0050:. 0.: 10 09.0.0.0 ..00000 .0..00 ..0.0:.

 

.80
004.

300
00<

>00
00<

000
00<

 

 

3.000. wxmi .wmmxmog moaowm O... wwo....0<m0

 

 

00000

 

 

 

259

 

00..—08.0.0. .000...000 5.3 0.00.0000 0. 000 0.00.0.0 .050 05 .3 0008 0000000000 05 00.008800 0. 85.00.8000 03.
.000. .0 00.. ..00.0. 0.0>0 00502 20.09 05 00.00 0..—000.0 05 0: 0008 0000050000 05 ..0 880000800 0 0. 8000.0 .000. 0..... 000. 00 0002

0.0.002 0000000 .< 0.0... .00. .0 .00 8.0000 .0053 0.0000 0 00.40 0.000 00 00.00005 003.0000... 080.000 000002 0.0.0 000002 .0 00000<

.0 05% 0000.0: 0 002 0.000 00 00.800380. 800.020.00.— 0. 00 0.0008... 40080000 05 08.0. 003 3.20.0 05 5.... 000.0030... ..0 0.00.. 0:... "00000.3.

 

o ww4m<.m<> w:0.>mm0
00000.00 toaxm .0. 02.00090 000000 000009.. 0 < z. 05.50.25.200 .02 ww0F0<m0 ...(KMZMO 0000

 

000.50 .000. .0 000 05 505.3 00.0..000: 0.0 0.00.88
.00.... 0:0..0.:0.0 05 5.3 0.:0800:0..0 .00..0 0>0:
0:0 0.02.03 .0 005.8800 80:08.00 0 :000.:. 0:0...0:00
02.003 05 20502.00 0.0..000: 0.02.03 .0 0.0008 0:.:

02200.00 0>..00..00 :000.:. 0000020

0.00.800 0>0: 0:0..0.:0.0 0:. .0 30. < 0.02.03 0:. .0
00:00.0 05.0 008.. 0:08 00.50 .000. 2. 00.:0080000
280000.. 0.03 .0:. 000000: 0.00.0000 .00. 00.0
0>0: 080800.00 02200.0: 0>..00..00 .0:0..0.000 ..05
5.3 .:0.:000.0 .0.0:00 0. 000 .0300 .00. 0>0: 0:2:3
020.05.00sz 0005

wmo...b<%mm 000...... oz< .3000 mmzho .0I000

 

0:25 .000. 000.90
.0 .0. 0.050000 .0: 00 0.0.0.05 0:0 :0..0.:0.0 0:.
5.3 0:0..0..000: .000. :. 0.00.2000 .0: 00 0:0..0~.:00.0
000: 0. 0.0 .0208 0:0 00:.>00 .0. 0:0..0.00000
0>0: 0:0..0~.:00.0 2:00:00 .0053 0:0..0.:0.0
080.0 02.00.00. 0:0 0.00:0: 0.02.03 .0. 0005.888
.:0.0...0 0>0: 0:0..0.00000 3002.00 .0 0.0008
0:... 0.00.0000 00:.00 0>0: 0:0..0.00000 0...00..0w

wzo...<N.z<OmO 0005

 

 

 

 

 

ww0....0<m0 mp9) DZ< ..<.000 .5100 0R00

 

260

 

 

ma 2.. .3 00.001.000.03. 000.225 .800 .0.00500..>00 - 00 030.

261

 

262

0022.00

000.>0.0 ..0 00.0>00 .0: 0.00000. - 00.00.... C

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

82
x.
80 0.8 0.00 0... .00 ..0. 0.00 0.0. 0.0. 8.8 8.8 8.8 8.8 8.0. 8.8 8.0. 8.8 02 8.8 8.8 000.02
a...
8. 0.... 0.8 0.0. .8 0.. 0.8 u..- 0.0 8.... 8... 8.8888880. 8.88.8 02 8.0. 8.9 059..
.0
8m .8 ..8 0.0. 0.8 0.0. 0.0.. 0... 0.0 8.8 8.8 8.8 8.8 8.8 8.8 8.8 8.8 02 8.0. 8.9 802.8
.0
80 0.8 0.00 0.: 0.00 S. ..0 0L ..0. 80.10 8.0 8.8 8.8 8.8 8.8 8.8 8.8 02 8.8. 8.8 00200.0
88 C 0900.2
0..
80 0.8 0.3 ..o. 0.0 0.0 ..00 0.- 0.... 8.8 8.8 8.0. 8.8 8.8 8.8 8.0. 8.0. 8.8 8.8 8.8 .000 .02
0..
8. 0.... 0.8 0.0 0.8 0.0. 0.8 0.0- E. 80. 8.98.0. 8.8 8.8 8.88.8 8.8 8.8 8.0. 8.8 0.3:.
0..
8~ «.8 ..8 0.. 0.8 8 .8 ...o. 0.2 8.8 8.8 8.0 8.8 8.8 8.8 8.8 8.8 8.88.8 8.8 502.8
.0
80 0.8 0.8 ..0. 0.00 0.0 0... 0.0- 0.0. 8.00 8.8.8.8 8.8 8.2 8.8 8.8 8.8 8.8 8.8 8.8 M0208
c200.

 

€0.50. 0. 2.. E ..0.0:. 0.8.20 80.2.35 .800 .0.00500..>00 - 8 as...

 

263

 

mu. 2: E 832 .3833. 820:3... 08:0 380 - 00 0.00.0

264

«£83525 6...;
0:86:00 a $8850 x8>> AL
$0308

.E00
.E00

 

265

The following tables show the mean values substituted into the design
matrix.

266

Table 38 - Mean Values Subtituted in Equation to Calculate SPI

INDEXES NPI
EXPERT NUM
5 7 11
0. 0 0.4 . . 0. . . . .
0.4 .559 0.600 .5 5 .600 0.550 0.480 . . 0.451 0.
0.200 0.515 0.600 0.430 0.600 0.200 0.280 0 0.200
0. .463 0.600 0. 1 . 0 40 .100 . 0.1 .
0.200 0.460 0.600 0.363 0.600 0 0. .314 0.200 .1 0.
0.265 0.391 0.600 0.584 0.600 . . . 5
0.2 .21 0. .48 .600 . 0.440 0.1
0. .
0. 0.51 .
1.1

0.

0. . .

0. . . 0. .

. .654 . . 0.

0.780 0.702 . 0.570 1.000

0. 0. . . . . 5
0. . 1 . . 1 .856 .7

.525
. 0.448 1. .760 . . .800 . 0. 1
0.660 .385 0.900 0.660 0.760 0.681 .800 0.855 0.701
.4 . 0. . . . . 7 0.

 

Table 38 (Cont’ — Mean Values Subtituted in

N B

BAP 3

0.980 0.800 0.57
2be 0.800 0.300 0.604

0.820 0.660 0.608
Mean 0.867 0. 7 0.597

R
INDEXES ENPI
E

BAP 1 3
20a 0.980 0.
0. 0.

2CC 0.940 0.740
. 0.
0.

1

0. 0 0.
0.660 0.500
0. 0 0.360
0.

267

0.51 .900
0.361 0.600
0.483 0.700
0.45 0.733

0.

0.62 .

0.540 0.495
503

0. .

0. .557
0.840 0.549
0. .554 . . 4

0.665

0.720 0.600 .
0.740 0.662 0.800 . 0.
0.727 0. 0. 0.91 0.7

to Calculate SPI

0.626 0.

0.655 0. . .

0.715 .800 N .735
.945 . 0.

0. 0.

. 0.
.600 0.500 0.
. . 0.
.600 0.800 .568

0 5

0.77 0.720 0.250 0.

0. .575

 

268

Table 38 (Cont’d) - Mean Values Subtituted in to Calculate SPI

 

   

BAP 1
0. .
0.595 0.700

INDEXES

BAP
. 0 0. . . . . . . .
.860 0.600 0.668 0.620 0. 0. 0.7 0.760 .885
0. 0.770 0. 0.640 0. 0.920 .750

.770
0.770 . . . .
0.675 0.630 0. .568 0.
0.640 0.62 0.

0. 9 0.

.19 0. .495 . .
0.629 0. 0.612 0.952 0.712

Table 38 (Cont’d) - Mean Values Subtituted in Equation to Calculate SPI __ _
[7be [0.870 [0.640 [0.636 [0.920 [0.594 [0.952 [0.668 [0.580 [0.723 [0.800 [0.738 [

 

 

ca

700 .
70d 0.675

06 0. 5
7 0.

(>9
7

ct
CV
CW

0.731 0.61 o. 0.72
FIELD PRACTICES
CPP 1

3
a . 0.
1b

0. 0.904 0.788
0. 17 0.592

.745

.800 0.
.800 0.

 

270

Table 38 (Cont’d) - Mean Values Subtituted in to Calculate SP1

0 0. O.

. 0. . . .
7e . 0. . 0.600 0.
0 . . .

FIELD PRACTICES
ER
BAP

0.
0.699 0.696 0:

0. 4 0.662 0.
. .4
. 4

0.707 .7

0. . 0.

0.514 0.591 0. 0.608
. 0. . . .
0. 1 0.712 0. 0.501 0.

 

.605 0.

271

Table 38 to Calculate SPI

 

     

d) - Mean Values Subtituted in
' 0.65 . 0: 1 . . 0.
. . 0. .44 . 1
08 . 0.698 0. 0.
0. . 0. . .
.553 . 0.65 0.574 0.581
PACKING

BAP

HIERING PRACTICES
BAP
ac

ae

FRINGE BENEFITS

BAP

272

Table 38 (Cont’d) - Mean Values Subtituted in Equation to Calculate SPI
RMAN E IN

E IPE

RISK PREVENTION

BAP 1

7ca . 5
0.

76C 0 5

7Cd

0.501
0.600
0.584
0.502
0.
0.405
0.557
0.
0.
0.
0.601

5

.550
0.575
0.
0.480
0.508
0.603
0.
0.803

0.
0.602

(

0. 5
0.590
0.585
0.585
0.590
0.595
0.590

0608
o.
0.619

.47
0.
0.527
0.
0.579
0.600
0.505
0. 7

0.589 0. .

0. 0.600 0.600
0. . .
0.590 0. . 1
0. 0. 1 .595
0. . .
0.585 0.809 0.

0.
.55

 

BIBLIOGRAPHY

BIBLIOGRAPHY

Allenby, B. 1996. A Design for Environment Methodology for Evaluating
Materials. Total Quality Environmental Management. New York, N. Y.:
John WIley & Sons, Inc. Volume 5, Number 4. Summer 1996.

Altieri, M. 1983. Agroecology: the Scientific Basis of Alternative Agriculture.
Berkeley, California: Division of Biological Control, University of California.

Altieri, M. 1987. Agroecology: The Scientific Basis of Alternative Agriculture.
Boulder: Westview Press.

ANAPROBAN. 1995. lntemal document.

Axinn, G. .1993 Class Notes. RD 876 International Community and
Organization Development, A Comparative Perspective, Oct. 19,1993.

Axinn, G. 1988. lntemational Technical Interventions in Agriculture and Rural
Development: Some Basic Trends, Issues and Questions. Agriculture and
Human Values. VWnter-Spring, pp. 6-15.

Babbie, E. 1983. The Practice of Social Research. Third Edition. Belmont,
California: Wadsworth, Inc.

Bailey, P. and Soyca, P. 1996. Environmental Accounting— Making it Work for
Your Company. Total Quality Environmental Management. New York, N.
Y.: John WIley & Sons, Inc. Volume 5, Number 4. Summer 1996.

Banco Central de Costa Rica. 1993. Statistics.

Beus, C. and Dunlap, R. 1990. Conventional versus Alternative Agriculture: The
Paradigmatic Roots of the Debate. Rural Sociology 55(4). pp. 590-616.

Boillot, J. 1997. The Drift Coalition. Agricultural Aviation. May/June pp. 20-21.

Bourgois, P. l. 1989. Ethnicity at Work: Divided Labor on a Central American
Banana Plantation. Baltimore: Johns Hopkins University Press.

Brown, H. 1996. Pragmatic Ethics and the New Consultant. Total Quality
Environmental Management. New York, N. Y.: John WIIey & Sons, Inc.
Volume 5, Number 4. Summer 1996. pp. 1 6.

Brown, Lester R. 1993. "The New Era Unfolds" State of the World 1993. Ed.
Starke, Linda. New York: W. W. Norton & Company.

Casey Gaspar, J. 1979. Limon, 1880-1940: Un Estudio de la lndustria Bananera
en Costa Rica. San Jose, Costa Rica: Editorial Costa Rica.

273

274

Castillo, L. August 21, 1997. Presencia de Agroquimicos en Canales de Drenaje
y Riesgo Ambiental. Simposio lnternacional Sobre Riego y Drenaje en
Banano. EARTH, Costa Rica: Programa de Plaguicidas: Desarrollo,
Salud y Ambiente, Universidad Nacional, Heredia, Costa Rica. (Oral
presentation and writtern unpublished material).

Churchman, C. West. 1968. The systems approach. New York: Dell Publishing
Co., Inc.

Colby, M. 1990. Environmental Management in Development: The Evolution of
Paradigms. World Bank Discussion Paper.

Comisién Ambiental Bananera (CAB). 1997. Analisis y Comentarios del Sector
Bananero al “Diagnostico Ambiental de la Actividad Bananera en
Sarapiqul, Tortuguero y Talamanca en Costa Rica 1990-1992”. San Jose,
Costa Rica: Corporacion Bananera Nacional.

Committee on Sustainable Agriculture and the Environment in the Humid Tropics
(CSA). 1993. Sustainable Agriculture and the Environment in the Humid
Tropics. National Research Council. Washington DC: National Academy
Press.

Cunnigham, W. P. and Saigo, B. 1990. Environmental Science. Dubuque, Iowa:
Wm. C. Brown Publishers.

Daly, H. 1991. Steady-state Economics. Washington, D. C.: Island Press.
Daly, H. and Cobb, J. 1989. For the Common Good. Becom Press.

del Camino, R. y Muller, S. 1993, Sostenibilidad de la Agricultura y Ios Recursos
Naturales: Base para Estableoer lndicadores. San Jose, Costa Rica:
Deutsche Geselischaft fur Technische Zusammenarbeit (GTZ) y Instituto
lnteamericano de Cooperacién para la Agricultura (IICA).

Deutsche Gesellschaft Fur Technis Che Zusammenarbeit (GTZ) and Institute
lnteramericano de Cooperacion para la Agricultura (IICA). 1996.
Evaluacion y Seguimiento del lmpacto Ambietal en Proyectos de Inversion
para el Desarrollo Agricola Rural: Una Aproximacion al Tema. San Jose,
Costa Rica.

Easterbrook, G. 1995. A Moment on the Earth: The Coming Age of
Environmental Optimism. New York, New York: Penguin Books.

Edmunds, S. and Letery, J. 1975 Ordenamiento y Gestibn del Medio Ambiente.
Translated to Spanish by Hernandez, J. Instituto de Estuidos Superiores
de Administracion Local, Madrid. New York: MCGraw Hill Book Company.

 

 

275

Edwards, C.A., Grove, T.L., Harwood, RR, and Pierce Colfer, C.J. 1993. The
role of agroecology and integrated farming systems in agricultural
sustainability. Agricultural Ecosystems Environment 46: 99-121.

Escuela de Agricultura de la Region Tropical Humeda. 1991. Seminario—
Problematica ambiental relacionada con el cultivo de banano en Costa
Rica—Notes (Hernandez) regarding comments made by participants
during discussion session. San Jose, Costa Rica.

Expert Choice, Inc. 1995. Decision Support Software. Users Manual. ECPro for
Windows. Pittsburgh, Pennsylbania: Expert Choice Inc.

Fiksel, J. 1996. Achieving EceEfficiency Through Design for Environment.
Total Quality Environmental Management. New York, N. Y.: John WIIey &
Sons, Inc. Volume 5, Number 4. Summer 1996.

Flevin, C. and Young, J. 1993. "Shaping the Next Industrial Revolution". State
of the World 1993. Ed. Starke, Linda. New York: W. W. Norton &
Company.

Forc Industrial. 1994 (November 20). La Nacion. National Chamber of Industry.
San Jose, Costa Rica.

Gobierno de Costa Rica and Deutsche Gesellschaft Fur Technis Che
Zusammenarbeit (GTZ). 1991. Plan nacional de manejo de desechos de
Costa Rica. Infcrrne Final. PN 84.2084.6-30.106. San Jose, Costa Rica, p.
10.

Hall, C. 1990. Sanctioning Resource Depletion: Economic Development and
Nee-Classical Economics. The Ecologist, V20, N° 3 May/June 1990.

Hall, C., Cleveland, 0., and Kaufmann, R. 1992. Energy and Resource Quality:
The ecology of the Economic Process. Niwot, Colorado: John WIley &
Sons.

Hall, C.A.S. and Day, J.W. Jr. 1977. Ecosystem models in theory and practice:
An introduction with case histories. New York: John WIIey & Sons, p. 6-36.

Hernandez, C. and Witter, S. G. 1996. Evaluating and managing the
Environmental Impact of Banana Production in Costa Rica: A Systems
Approach. Journal of the Human Environment-AMBIO, Vol. 25(3). pp.171-
178.

Hilje, |., Castillo, J., Thrupp, L., and Wesseling, l. 1992. El uso de Ios Plaguicidas
en Costa Rica. San Jose, Costa Rica: EUNEO, Heliconia.

 

 

276

Huss, R. 1994. Economic Justice for Sustainable Health. In DEVELOPMENT -
The Journal of the Society for International Development. 1994: 3, pp.14-
23.

Instituto lnteramericano de Cooperacion para la Agricultura (IICA). 1991. Bases
para una Agenda de Trabajo para el Desarrollo Agropecuario Sostenible.
San José, Costa Rica: IICA

Janzen, DH. 1983. Costa Rican Natural History. Chicago: University of Chicago
Press.

Johannson. 1996. Total Quality Environmental Management. New York, N. Y.:
John WIIey & Sons, Inc. Volume 5, Number 4. Summer 1996.

Kachigan, K. 1986. Statistical Analysis: An Interdisciplinary Introduction to and
Multivariate Methods. New York, N. Y.: Radius Press.

Kepner, CD. 1935. The Banana Empire: A Case Study of Economic
Imperialism. New York: Vanguard Press.

Kohlman, 1B. 1997. Notes from Applied Ecology Course. Escuela de Agricultura
de la Region Tropical Humeda. Guacimo, Limon, Costa Rica

Langmore, J. 1994. Policy Reform and Poverty Reduction: are the two
compatible?. In DEVELOPMENT - The Journal of the Society for
lntemational Development. 1994: 3, pp. 53—56.

Lauer, W. 1989. Climate and Weather. In: Ecosystems of the World 143: Topical
Rain Forest Ecosystems. Lieth, H. and Werger, M. J. A. (eds).
Amsterdam: Elseviser Science Publishers. pp. 7-49.

L0pez, M. 1992. Método de la Matriz de Leopold. Curso Regional sobre
Formulacion y Evaluacion de Proyectos de Desarrollo con Envasis en
Evaluacién de Impacto Ambiental. San José. Costa rica. R:R., ICAP,
ASDI, Contraloria General de la RepI'Jblica.

Mata, A. y Quevedo, F. 1990. Diccionario Didactico de Ecclogia. San Jose,
Costa Rica: Universidad de Costa Rica.

McCann, T. P. 1976. An American Company: The Tragedy of United Fruit. New
York: Crown Publishers.

McKenry, M. W. 1991. The Nature, Mode of Action, and Biological Activity of
Nematicides. In: CRC Handbook of Pest Management. Pimentel, D. (ed).
Boca Raton, FL:CRC Press. pp. 461-496.

Meadows, D., Meadows, D., and Randers, J. 1992. Beyond The Limits. Post
Mills, Vermont: Chelsea Green Publishing Company.

 

 

 

277

Metcalf, K., VIfilIiams, P., Minter, J. R., and Hobson, C. 1996. Environmental
Performance Indicators for Enhancing Environmental Management. Total
quality Environmental Management. New York, N. Y.: John VIfiIey & Sons,
Inc. Volume 5, Number 4. Summer 1996. pp. 7-11.

Miller, G. 1956. “The Magical Number Seven Plus or Minus Two: Some Limits
on Our Capacity for Processing Information.” Psychological Review 13:81-
97.

Ministerio de Ciencia y Tecnologia de la Republica de Costa Rica (MICIT). 1995.
Oportunidades para la Aplicacién de Tecnolgia Limpias en Costa Rica.

Ministerio de Recursos Naturales, Energia y Minas (MIRENEM). 1992. Estrategia
de conservacion para el desarroIIo scstenible de Ilanuras de tortuguero
(Unpublished). San Jose, Costa Rica.

Mitsch, W. 1993. Ecological Engineering: A cooperative Role with the Planetary
Life-Support System. American Chemical Society. Environmental
Science Technology. Vol 27. No. 3.

Mitsch, W. and Jorgensen, S. 1989. Ecological Engineering: An Introduction to
Ecotechnology. New York: John WIIey & Sons, Inc.

Naes, Arne. 1989. Ecology. Community, and Lifestyle: Outline of an ecosophy.
Cambridge: New York: Cambridge University Press.

National Research Council (US). Committee on Sustainable Agriculture and the
Environment in the Humid Tropics. Board on Agriculture and the
environment in the Humid Tropics, Board on Agriculture and Board on
Science and Technology for Intentional Development. 1992. Sustainable
Agriculture and the Environment in the Humid Tropics. Washington, DC:
National Academy Press. p. 5.

Nava, B. 1996. Manejo de Desechcs SCIidos en el Distrito de Tuis, Cantén de
Turrrialba, Costa Rica. Centro Agronomico Tropical de Investigacion y
Ensenanza. Subdireccion de Ensenanza. Area de Estudios de
Postgrado.

Nebel, B. J. 1990. Environmental Science: The Way the World Works, rd. de.
New York: Prentice-Hall, InC.

Peakall, D. 1992. Animal Biomarkers as Pollution Indicators. London: Chapman
and Hall.

Peet, J. 1992. Energy and the Ecological Economics of Sustainability.
Washington, D. C.: Island Press.

 

 

278

Piel, G. 1992. Only One World: Our own to make and to keep. New York: W. H.
Freeman Company.

Prance, GT 1989. American tropical forest. In: Ecosystems of the world 143:
Tropical rain forest ecosystems. Lieth, H. and Werger, M.J.A. (eds).
Amsterdam: Elsevier Science Publishers, p. 99-132.

Ragsdale, N. N. and Sisler, H. D. 1991. The Nature, Modes of Action, and
Toxicity of Fungicides. In: CRC Handbook of Pest Management. Pimentel,
D. (ed). Boca Raton, FL: CRC Press, pp. 461-496.

Recyplast, 1997. lnforrnation gathered during visit to the recycling plant in July
1997.

Risser, P., Lubchenco, J., Christensen, N., Dillon, P., Jacob, D., Johnson, P.,
Matson, P., Moran, N., and Rosswall, T. 1993. Ten-Year Review of The
National Science Foundation Long-Terrn Ecological Research (LTER)
Program. (Unpublished report)

Saaty, T. 1996. The Analytic Hierarchy Process: Planning, Priority Setting,
Resource Allocation. Pittsburgh, Pennsylvania: RWS Publications.

Saaty, T. and Keams, K. 1991. Analytical Planning: The organization of
Systems. The Analytic Hierarchy Process Series Vol. IV. Pittsburgh,
Pennsylvania: RWS Publications.

Saaty, T. and Vargas, L. 1991. The Logic of Priorities: Applications of the
Analytic Hierarchy Process in Business, Energy. Health and
Transportation. The Analytic Hierarchy Process Series Vol. III.
Pittsburgh, Pennsylvania: RWS Publications.

Saaty, T. and Vargas, L. 1994. Decision Making in Economic, Political, Social
and Technological Environments with the Analytic Hierarchy Process.
The Analytic Hierarchy Process Series Vol. VI. Pittsburgh, Pennsylvania:
RWS Publications.

Sénchez, L. 1996. “Impacto de aI Legislaciones Ambientales de Costa Rica y
Holanda Sobre el Accesc al mercado para Algunos Sectores Productivos
Bananeros de Costa Rica y Centro America.” Universidad de Costa Rica.

Sénchez, O. and Barrientos, E. (CORBANA). 1992. Inforrne Estadistico de
Exportaciones Bananeras 1970-1990. San Jose, Costa Rica: Corporacion
Bananera Nacional

Sanchez, 0. and Barrientos, E. 1992. Inforrne estadistico de Exportaciones
Bananeras 1970-1990. Corporacion National (CORBANA). San Jose,
Costa Rica.

 

 

 

279

Snedecor and Cochran, 1967. Statistical Methods. Ames, Iowa: The Iowa State
University Press.

Solérzano, R. del Camino, R., Woodward, R. Tosi, J., Watson, V., Vésquez, a.,
Villalobos, C., Jimenez, J., Repettc, R., and Cruz, W. 1991. Accounts
Overdue: Natural Resource Depreciation in Costa Rica. Tropical Science
Center, San José, Costa Rica and World Resource Institute, Washington, 4
DC.

Soto, M. 1994. Desarrollo Sostenible de la Actividad Bananera. Authors
personal notes for new book (Unpublished). San Jose, Costa Rica.

Soto, M. 1992. Bananos: Cultivo y Comercializacién. San Jose, Costa Rica:
Litografia e Imprenta LIL, S. A.

Tabora, P. 1991. Analysis and evaluation of agroforestry as a alternative
environmental design in the Philippines. Netherlands: KIuwer Academic
Publishers. Agrcforestry Systems 14: 39-63, 1991.

The Packer. Feb. 5, 1994. Special Report: Global Produce.

Union Mundial para la Naturaleza (UlCN/ORMA, 1991) Oficina Regional para
Mesoamérica., Evaluacion del Impacto Socioambiental de la Actividad
Bananera en Sarapiqui, Tortuguero y Talamanca. Draft Report. San
José, Costa Rica.

United States Department of Agriculture (USDA), Agricultural Research Services.
1966. Mean Separation by the Functional Analysis of Variance and
Multiple Comparisons. United States of America.

van den Bergh, J. and van der Straaten, J. 1994. Toward Sustainable
Development: Concepts, Methods, and Policy. Washington, DC.: Island
Press.

Veroutis, A. and Aelion, V. 1996. Design for Enviroment: An Implementation
Framework. Total Quality Environmental Management. New York, N. Y.:
John WIIey & Sons, InC. Volume 5, Number 4. Summer 1996.

Wackemagel, M., Onisto, O. and Mata, M. 1995. Earth Reports for People:
Inspiring New Visions to Make Sustainability a Reality. Earth Monitoring
and Reporting Program. San Jose, Costa Rica: The Earth Council. An
Earth Council Proposal. '