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ABSTRACT
ESTDHATING THE PRODUCTIVITY OF MICHIGAN SOILS

by'William Herbert Miller

The productivity of different kinds of soil under defined management
conditions is of interest for determining optimum input levels, expected
net returns with given management systems, land evaluation, and for
resource inventory and planning work.

Obtaining data upon which to base productivity estimates has been
a major problem. The data obtained for this study was obtained from
two sources: (1) growers selected from those cooperating with the Michigan
State University Telfarm.project, and (2) growers cooperating with the
Ionia County 1966 Corn Profit Club. Both sources were fairly satisfactory,
the second being the more satisfactory.

The methods used for gathering management practice data were found
to be potentially useful for ascertaining the extent to which various
management practices are being applied by the better Michigan growers.

Methods for evaluating the crOps and soils management programs used
by the growers has been another problem. A scoring method based on crop
requirements and soil conditions was used in this study. The method is
designed so that, using codes and card formats similar to those presented
in this thesis, 8 computer can be given raw data and from them can com-
pute a management evaluation score. The management scoring system was
found to give fairly consistent results when it was evaluated by com—

paring yields on the 2.5a (well drained loam) management group of soils.

‘William Herbert.Miller

The need for.more precise evaluation of good management for high yields
on the various groups of soils is evident.

Average yields for each soil management group were found to differ
with comparable management. The trend of differences in general is the
same as that found in other studies. However, some exceptions indicate

the need for additional research.

ESTIMATING THE PRODUCTIVITY OF MICHIGAN SOIIS

By
William Herbert Miller

A THESIS

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

MASTER OF SCIBJCE

Department of Soil Science

1967

ACKNOWLEDGEMENTS

The author wishes to express his sincere appreciation to Dr.
E. P. Whiteside for his guidance throughout this study. Advice
from the faculty and staff members of the Departments of Soil Science,
Crop Science, and Agricultural Economics is also much appreciated.

A great debt is owed the (Michigan) Cooperative Extension Service
without whose cooperation this study could not possibly have succeeded.
Dr. W. A. Tinsley and Mr. L. H. Jepson were especially helpful in the
collection of the data.

Special thanks go to the growers who so willingly gave of their

time to provide the information used in this study.

ii

TABLE OF CONTENTS

Page

INTROUJCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . l
LITERATUREREVIEM............. ...... 3
METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Factors Considered . . . . . . . . . . . . . . . . . . . . . . 6
Collection of Data . . . . . . . . . . . . . . . . . . . . . . 7
Evaluation of Data . . . . . . . . . . . . . . . . . . . . . . 15
RESULTS AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . 30
SUMMARY AND CONCIUSIONS . . . . . . . . . . . . ..... . . . . . 67

LITERANRE CITE O O O O O O O 0 O O O O O O O O O O O O O O O O O 68

iii

LIST OF TABLES

Numerical codes of some management practice variables

Variable names and corresponding IBM card column
numbers . . . . . . . . . . . . . . . . . . . . . .

Codes for soil management group and unit symbols . .

Response of growers to correspondence program . . . .

Summary of 1966 management practice data . . . . . . . . .

Average corn yields for different soil management
groups or soil management units, under two
management levels . . . . . . . . . . . . . . . .

Average yields for some management practices for two

groups of observations . . . . . . . . . . . . . . . .

iv

Page
16

l7
19

33
36

53

58

LIST OF FIGURES

Figure Page
1. August rainfall compared to adjusted yield for Ionia Co. . . 31
2. Yield compared to original management score on 2.5a soils . . 6l
3. Yield compared to revised management score on 2.5a soils . . 62

INTRODUCTION

The primary functions of a soil survey are to define soil types,
locate them on a map, describe the taxonomic and mapping units, and
Observe their relationships to land use and management for various
purposes. The information provided by a soil survey often needs to
be interpreted by relating the taxonomic and mapping units to other
information available about the properties of these units. The re-
sponses of these units to various uses and management practices in
various climatic, social, and technologic situations are important
interpretations of soil survey information.

This thesis presents some methods that may be used to acquire
and present'basic information on the productivity of soils for various
craps under defined systems of management. This productivity infor-
mation, as well as related information, is needed to interpret soil
survey information for various groups interested in agriculture.

Sole illustrations of these methods and their application in southern
Michigan are presented.

Many of the physical and chemical properties of the soil that
vary from place to place are plant growth factors. A soil type is
an attempt to meaningfully group these factors. (As used herein,
soil type includes soil types and phases of soil types.) If these
groupings are in fact meaningful, and if plants do in fact reSpond
differently from one group of properties to another, then plant growth
should be different from one soil type to another.

Yield per acre is the plant growth criterion of greatest interest
to agriculturalists. Yield, however, is the composite result of:

(1) soil factors, (2) weather factors, (3) management factors,

1

2

(1;) unknown and/or uncontrollable factors, and (S) interactions among
these factors. In order to determine the effect that the soil factors
have on.yield, the effect that the other, non-soil,factors have on
yield must be accounted for as completely as possible.

Soil productivity, as used here, is defined as the average capacity
of the soil to produce a given crop or a given sequence of crOps under
defined management conditions in a given environment. Therefore,
average yields for any given soil and management combination are a
measurement of the soil's productivity if the non-soil factors are
adequately accounted for, or their variations are represented in the

data on which the averages are based.

LITERATURE REVIEW

The capacity of the soil to produce crops, and.the associated
production practices necessary to achieve this capacity are items
of information that are useful to a great many groups. For example,
the evaluation of agricultural land by bankers, farmers, tax asses-
sors, and land buyers can'be based to a large extent on such infor-
mation, according to Anderson gt_gl (1938) and Priest (1963). Far-
mers, conservationists, public land agencies, other public agricul-
tural agencies, and agricultural industries find productivity infor-
mation.helpful in planning Operations. Soil taxonomists can use pro-
ductivity information to eliminate errors in the classification of
soils (Ableiter‘gt_gl, 1950; Blagidov, 1960).

Obtaining productivity estimates can be done two different
ways according to Visser (1950). One method is to differentiate as
accurately as possible between soil profile types, then use yield
history to assign productivity figures to each profile type. A
second method is to use yield history and individual soil preper-
ties to determine the properties influencing productivity. Then
productivity figures are assigned to the different soil bodies on
the basis of the degree to which these properties are present.

Using yield history to determine the properties influencing
productivity, then assigning productivity figures to soil bodies on
the basis of the degree to which these properties are present is a
method strongly advocated by Butler (196h). Butler takes this ap-

proach for two reasons: 1) He rejects the hypotheses that the
morphological properties of a soil necessarily correlate with the
soil factors responsible for plant growth. 2) He hypothesizes that

3‘

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differences in yields can be correlated with differences in only a

few soil properties such as pH. Northkote (19614), on the other hand,
states that accumulated evidence shows that there is a constant and
consistent relation beWeen the physical and chemical properties and
the morpholog of the principal profile form. He further says that
plant growth factors may correlate with groups of soil properties.
Blagidov (1960) says that it is incorrect to appraise a soil for
separate properties, then to appraisethe soil as a whole by ensuring
up the appraisal data. He cites the example that a table of humus
effects cannot be elaborated unless other soil properties are also
taken into account. Blagidov consequently advocates that soil pro-
ductivity appraisal be based on a specific conbination of soil
properties.

The relative productivity of each profile type can be assessed
two ways according to Avery (1962). The first is to obtain yield
measurements on two or more soil types within the same field. The
second is to collect yield data on soil types which occur on scat-
tered sites or fields.

Tripp (1961;) in a study concerning the effects of slope and
erosion on corn yields in Ingham County, Michigan, compared the
yields obtained on adjoining soil types in the same field. Odell
(1950) compared corn yield differences between Tame and Swygert
series and various phases thereof in North Central Illinois by har-
vesting adjoining plots in the same field. '

Collecting yield data from scattered sites or fields has been
a more prevalent method of obtaining such data. Odell (1958) sug-

gested three methods for obtaining information from scattered sites:

S
l) by survey, 2) from farm records, and 3) from experimental plot
data. Anderson g_t_.__a_1_ (1938), Met'tert (1961), and Priest (1963)
used land use records from different parts of a single county to
estimate the productivities of the soils being studied. Odell and
Smith (1910), Odell (19M), and Rust and Odell (1957) used records
fro. individual farms .to assess the productivities of some Illinois
soils. Information from individual farms has been used by Mettert
(1961), Gonzalez (1963), and Search (1961;) to estimate the produc-
tivities of some Michigan soils. 'Ihis is essentially the method
used in this study.

METHODS

Factors Considered

 

Since crop and soil management factors have such a large effect on
yield, as pointed out by Kellogg (1955), Schrader gt_gl (1957),

Aahndahl (1960), and Avery (1962), a system for assessing these factors
was devised. In devising this system several points were considered.
First, the factors employed in the system had to be judged to have a
significant effect on yield. Secondly, the factors had to be related to
practices commonly employed. Third, the system had to rely on factors
about which information could be obtained. Fourth, the information ob-
tained had to have a degree of accuracy which was known or which could
be assessed. Fifth, the infermation had to be quantitative or quanti-
fiable. Sixth, the system had to have potential relation to future pro-
ductivity and had to be adaptable to assessing the crop and soil manage-
ment factors in the future (see Aahndahl, 1960). Seventh, the informa-
tion had to be able to be stored for future analyses.

Not all of the relationships and considerations mentioned above
were known when this project was begun. Two methods were employed to
determine the crop and soil.management practices to include in a system
fer assessing crop and soil management. First, infonnation in COOpera-

tive Extension Service bulletins and similar publications, as well as
theses, journal articles, and papers was used. Secondly, agricultural
specialists at Michigan State University were consulted.

Since weather, as pointed out by Dale (1965) and Range (1966), is
such an important factor in.determining yield, an attempt was made to

evaluate it. Amount of rainfall was the weather component used.

6

Collection of Data

Several groups of growers were considered as potential cooperators
with this project. In view of Odell's (19h?) experience, farm.0perators
who keep'business records in cooperation with the Hfichigan State Univer-
sity Department of Agricultural Economics Telfarm project were considered
to be among the most promising potential cooperators. Other groups of
potential cooperators considered were farmers cooperating with various
County Cooperative Extension projects, those c00perating with Soil Con-
servation‘Districts, and those cooperating with projects sponsored by
agricultural companies.

From among these, two groups of potential cooperators were chosen.
The first group chosen were certain farm Operators cOOperating with the
Telfarm project and the second group were growers participating in the
Ionia County 1966 Corn Profit Club. ‘

The particular individuals selected from the Telfarm.project were
chosen on two bases: (1) their Telfarm.FORM 9 record sheets indicated
a possible high degree of interest in crops and soils, and/or (2) they
reported crop enterprise information as part of a special phase of the
Telfarm.project. Individuals in nine counties were chosen on this
basis. Lists of these individuals and samples of the form on which the
crop and soil management practices were to be recorded were sent to the
respective COOperative Extension agents in order that the agent's
epinion.could be used to determine whom.ehould be contacted. Finally,
on the basis of the agents' opinion, the decision on whom.to contact
was made. Accordingly, forms for recording the information and letters

of introduction were sent to these growers. The information requested

was the 1965 season crop and soil management practices.

8

Three methods of contacting these growers were used. In the first,
a letter and one sample form were sent. A return postcard‘which the
grower could use to request more forms if he elected to cooperate was
enclosed. This same postcard could be used to indicate his election
not to cooperate. The second method used was similar save that the
number of recording forms sent was equal to the number of fields the
grower had in corn in 1965. In the third method, selected growers in
Jackson and Eaton Counties were contacted personally at their homes by
the author with the aid of the respective Cooperative Extension agents.

The experience gained in the program used to request information on
1965 season practices was used to help design a more effective program
for requesting 1966 season practices. ‘With the help of interested
growers, a form.for recording 1966 season crop and soil management prac-
tices was designed.

The respective Cooperative Extension agents were then contacted
again. The following letter explaining the proposed 1966 program» examp
plea of the 1966 season practice recording form, lists of the growers
who coOperated in reporting 1965 season practices, and those growers
being considered for contact in 1966 were sent to them. The agents were
again requested to give their Opinion on whom it would be beneficial to
contact, and when the contacts would best be made. On the basis of
their advice, most of the forms were sent out in mid-June, after the
heavy spring work was done. Along with the forms were sent the fol-
lowing letter, the following example of a form already filled out, and
the following explanation of the various items on the form. The growers
so contacted were given a deadline by which to return the forms. In most

cases, this deadline was approximately three weeks later than the date

9
MICHIGAN STATE UNIVERSITY EAST LANSING

 

DEPARTMENT OF AGRICULTURAL ECONOMICS

Hr. John.Doe May 13, 1966
Extension Agricultural Agent

123 Courthouse Square

Somewhere, Michigan

Dear Mr. Doe:

Telfarm and the Soil Science Department are continuing their joint crop
and soil analysis project. As you know, the agent is the key to success
in this project. Your past cooperation is greatly appreciated.

Enclosed you will find materials relating to our '66 program. Cooperating
farmers will receive: (1) a letter; (2) a postcard addressed to Telfarm
for questions and comments; (3) a "REFERENCE FOR FILLING IN PRINT-OUTS";
(u) a sample filled-out sheet; (5) a number of sheets equal to the number
of fields owned in '65, not to exceed 20.

The letter will encourage the cooperator to fill out one sheet per field
for fields that have been soil-mapped, and that are devoted to the
following crops: corn, oats, wheat, alfalfa hay, field beans, soybeans,
and sugar beets. Cooperators would be asked to send in planting infor-
mation with May and June Telfarm Reports.

We will then send back these forms to be filled in with harvest information.
The cooperator will receive these sheets back at the end of the year all
nicely printed out far his records.

Enclosed is a list of cooperators to whom you suggested we send the 1965
FORM A Questionnaires as well as cooperators who kept crop enterprise

reports in 1965. We plan to send these forms out to these cooperators
unless you suggest we add or delete some names from the list. Please

advise.

Your questions and comments will be appreciated.

Dre. Tinsley and Kyle have been discussing this program with the District
Extension Farm Management Agents.

Sincerely,

Bill Miller
Department of
Soil Science
BH:lk

Enclosures

10
COOPERATIVE EXTENSION SERVICE

MICHIGAN STATE UNIVERSITY ° EAST LANSING ° MICHIGAN 48823

Agricultural Economics

 

AND U.S. DEPARTMENT OF AGRICULTURE COOPERATING Agriculture Hall

Kr. James Snith J 11:16 13, 1966

3.3. 1
Crossroads , Mich.

Dear Mr. Smith:

This is a follow-up letter concerning the crop analysis project being under-
taken by Telfarm and the Soil Science Department. The system for reporting
information has been simplified.

If you are interested in cooperating, we need your assistance now. Please
fill in the enclosed printout forms, one per field. An explanation of terms,
for reference purposes only, is also enclosed. Of special interest are corn,
wheat, oats, sugar beets, alfalfa hay, soybeans, and field beans grown in
fields where the soil has been mapped.

At this time, we need to know general field condition and crop planting
information. Send these forms to us with your Telfarm reports, or use the
enclosed envelope. These will be returned to you to be completed at harvest
time. At the end of the year, a summary of the project will be sent to you.
Ybu will also have these forms for your own records.

The success of this project is dependent upon your close cooperation. There-
fbre we say a sincere "thank you" for making it possible.

For further infermation, contact us or your Extension Agents.

Sincerely,

0“
ewe d as 357/7144 (3W) fi/Mm
Leonard R. kyle Lynn 8. Robertson
Extension Specialist in Extension Specialist in
Agricultural Economics Soil Science
1k
Enclosures

P. 8. Please return the postcard as soon as possible.

 

 

 

 

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12
REFERENCE FOR FILLING IN PRINT%OUTS

General
2. Fill in information at the right of the designation as on sample. Where

there is a choice, circle the number or the choice if no number. If
information doesn't apply, leave blank.

 

3. Be sure to fill in your name and farm number.

k. Abbreviations USed:

MEMT. - MANAGEMENT LBS - POUNDS LI - LIQUID PD - PLOW DUNN
G - GOOD BU - BUSHELS lfl- MANGANggg PLA - PLANTING
F - FAIR ROT. - ROTARY Z - ZINC SD -SIDE DRESS
P - POOR ACR - ACRE B - BORON TD - TOP DRESS
PL. - PLANTING BA - BANDED O - OTHER CWT—HUNDRED WEIGHT
POP - POPULATION BR - BROADCAST .AT PLANT - AT PLANTING
Specific

 

5. Fill in the crOp, the number of the field on your 1965 Form 9 farm map,
the township and section number the field is in. The ENTERPRISE NO.
and LOT NO. are to use if you keep CrOp Enterprise Reports.

6. *SOIL TYPES, SLOPE, ... Leave this Space blank. The Soil Science Dept. will
fill this in if your Form* 9 farm map is accurate enough to locate the field
accurately on—E soil map. If this field has 223 been soil-mapped, please
indicate under *REMARKS.

7. *LIME Ignore the code numbers l- and 2- in front of TONS and YARDS. Fill in
amount used at right of proper units. Name kind used if you circle h OTHER.

8.*DRAINAGE USe your judgement to describe drainage condition of field.

9. *LAST MANURE APPLICATION Refers to barnyard manure, not whether field was pastured.
We need only information for l965 and7or l966. For— your own records you may
fill in for earlier years. Estimate amount applied.

lO. *PRIOR COVER CROP Refers to crops like rye, clover, etc. sown between rows or
after harvest for 1965- 66‘winter cover or green manure and which'was plowed
down Spring of '66. Name kind of crop used. Describe stand.

'Ll.*INTERILLED FORAGE, LATE OR POST-SEASON COVER CROP Refers to either of two
situations. (I) Refers to crOps such as alfalfa seeded in wheat, oats, etc.,
to establish the stand. (2) Refers to crOps seeded in l966 between the rows
or after harvest for winter cover or green manure over Winter of l966-67.

- 2 _ 13

l2.*PRE-SEASON MOISTURE Refers to'Winter and early Spring moisture status of
the soil before planting. Use your judgement.

13.*INCHES This is strictly extra. If you keep rainfall records, we would
RAIN appreciate your including them on one of these sheets.

lh.*PROJECTED YIELD, ATTAINED YIELD Leave these blank. 'We'll fill in.

lS.*VARIETY 'Write in variety or varieties used on field. Circle whether seed
certified or not.

l6.*SEEDING RATE/ACRE OR POP GOAL Ignore the code numbers 1-, 2-, and 3- in
front of LBS, BU, and POP. Fill in amount at right of prOper units.
CONDITION OF FORAGE STAND refers to hay crops like alfalfa or clover.
USe your judgement to rate stand.

l7.*PLANTING DATE Fill in dates you started and finished planting field. If
field was planted in one day, fill in the day after START. YEAR is only for
crOps not planted in'66 (Fall '65 or old forage stands).

l8.*TILLAGE Circle when field was plowed. If plowed twice, circle last time.
NO. OF TRIPS AFTER PLOWING, BEFORE PLANTING. One trip is one pass over
field with a tractor and tillage tool. For example, if you plow, then
plant the next day, you'd circle "0."

l9.*HERBICIDES, ETC. Any chemical treatments against weeds, insects, worms, or
other pests should be entered here. Enter actual lbs. of chemical applied.
Circle whether BAnded or BRoadcast. If field was Spot treated, write SP
to right of ER.

20.*SOIL TESTED BY If a fertilizer company took the samples or tested, circle
l-FERT CO. no matter where the company sent the soil for testing. Please
write the name of the company. If you can, write year of test and the
sample number that applies to this field. Circle whether or not you
fertilized by test.

2l.*FERTILIZER If fertilizer was liquid, circle LI. If Manganese, Zinc, or
Boron was included in analysis, circle appropriate letter or letters.
If some other micronutrient was included in analysis, circle "0". Write
its name in front of ANAL. Fill in amount of fertilizer and circle time
of application. If you heavily fertilized a previous cover crop, denote
by circling l-PD.

22.*HARVEST DATE Use same procedure as for PLANTING DATE.

23.*YIELD/ACRE THIS FIELD Ignore code numbers 1-, 2-, and 3- in front of EU,
TON, and CWT. Fill in yield at ri ht of proper units. For hay, fill in each
cutting (2-TON3.5,4%for example . Fill in percent moisture of crop' that
yield was computed a Please indicate how measurements were taken (counting
silo rings, dryer batches, scale weights, crib measurements, wagon loads,
etc.

2h.*REMARKS. Use this Space to fill in any information you feel has an important
bearing on condition of field such as recent tiling, clearing from woodland,
burying stone piles, land levelling, burying old buildings, oil leaks from
wells, and so on. Also fill in anything you think had a significant bearing
on yields such as insect damage, wind damage, irrigation, and so on.

on which the forms were sent.

The soils in each field were ascertained in a nunber of different
ways. In counties where soil survey reports were available, the soil
types and the extent of each was determined where possible by using the
Telfarn FORM 9 farm sketch and comparing it to the soil map. The acre-
ages of soil types in each field were usually determined by using a dot
grid counter. In counties where soil survey reports were not available,
soil naps made as part of a Soil Conservation District "Soil and Water
Conservation Plan" were used. Where feasible, an area calculator
manufactured by the Martin-Kuykendall Company of Albuquerqe, New Mexico,
was used to estimste acreages of the various soil types in a field.
ibis machine is an electric device designed to rapidly count unit areas.

Growers cooperating with the Ionia County 1966 Corn Profit Club
were also provided with copies of the crop and soil management practice
forms through the Ionia County agent, Lance Jepson, who was responsible
for conducting the corn club. He and cOOperating Ionia County vocational
agriculture teachers personally interviewed the participating growers
during the sumr of 1966. During these interviews, nearly all of the
practice data were recorded. The data sheets were then sent to Michigan
State University to be coded and readied for keypunching onto standard
eighty column IBM cards. At harvest time, yields on each field were
determined by hand harvesting the corn from a single soil mapping unit
as shown on the recent soil maps made of Ionia County by the National
Cooperative Soil Survey. These yield figures were then sent to Michigan
State University to be included in the analysis.

15

Evaluation of Data

 

1. Evaluation of crop and soil management:

A method for evaluating crop and soil.management programs was
designed so a computer could be used for this work if desired. To
facilitate matters, all of the factors used in evaluating management
programs were given numerical codes. Elements of block coding and
group classification coding (Vincent, 1965) were used in assigning the
code numbers. Table 1 shows the code numbers given some of the variables.
Those crop varieties that were considered the best were given the
lowest numbers in the category.

The format of data representation on IBM cards is shown in
Table 2. It is compatible with the Telfarm card format inasmuch as the
first 15 columns represent the same variables. The format is based to
some extent upon the data in Table S. The consequent format design
enables it to handle nearly every field situation on the three data
cards. If necessary, however, additional pesticide or fertilizer
applications can be put on separate cards.

The soil mapping units were given, where possible, code numbers
based on the (Michigan) State Legend for Series to be Used in New
Progressive Soil Surveys, August, l96h, as revised. Soi1.management
group symbols were given codes as shown in Table 3. Each soil.mapping
unit name, its code number, and soil management group symbol codes were
punched on a standard eighty column IBM card according to the format
in Table 3. These cards enabled certain errors in assigning code
numbers and management group symbols to be eliminated. The cards
could also be used to assign soil management groups to the respective

soil series in a computerized program to evaluate crop and soil

16

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17

Table 2. Variable names and corresponding IBM card column numbers

 

 

 

 

 

 

 

001. 00]..
Variable Nos. variable Nos.
IdentifyingIEnformation 1-18 First data card (contgl
on all data cards
Cardffiumber 1-2 Symbol for additional 58
State B-h units which do not
County* 5-? appear as a continuation
Farm 8-11 of first data card
Owner 12-13
Year lh-lS Year lime applied 59.60
Field 16-18 Amount of lime applied 61-62
(001. 62 is tenths)
Kind of lime 63
First data card (No. 7;)
Portion of field tiled 6h
Acres in field l9-21 Condition of tile 65
(001. 21 is tenths) ‘Wet spots present that 66
delay operations
Soil mapping unit #1 22q30 wet spots present that 67
Series No. 22-2h hurt yields
Surface texture 25
Slaps 26
Erosion 27 Second data card (No.72)
[ores 28q30
(Col. 30 is tenths) Crop 19-22
Soil mapping unit #2 31-39 Tbns manure applied 23.2h
Series No. 31’33 Time 25
Surface texture 3h Year 26-27
Slope 35
Erosion 36 Prior cr0p 28.31
Acres 37-39
(Col. 39 is tenths) Prior cover crop 32-33
Kind 32
Soil mapping unit #3 110-148 Condition of stand 33
Series No. hO-lfi
Surface texture h3 Intertilled forage 3h-36
Slope hh and/or cover crap
Erosion hS Time planted 3h
Acres 116-148 Kind 35'
(Col. h8 13 tenths) Condition of stand 36

Soil mapping unit #1: 119-57

Series No. h9-51
Surface texture 52
Slope 53
Erosion Sh
Acres 55-57

(001.57 is tenths)

 

Table 2. (Canto)

18

 

 

 

 

C010 C010
Va riable Nos . Variable Nos 0

Second data card (contQ Third data card (No. 731
Variety 37-h]. Place soil tested 19
Maturity class 37 Extent to which test 20
Yield class 38 recommendations followed

Kind 39-h0

Certification Fertilizer application #1 21-33

% N 21-22

Seeding rate, etc. b2-5’1 % P205 23.21;
Units h2 1 K20 25.26
Rate 143-115 Liquid fertilizer and/or 27.29

(Col. 115 is tenths) micronutrienta

Row width 1464;? lbs. fertilizer per acre 30-32
Condition of forage stand 118 Tims applied 33
Actual percent or 149-51

papulation harvested Fertilizer application #2 3km;

z N 3 -3

Planting date 52-57 g p 05 36-37
Month planted 52-53 g Kgo 38.39
Day planted Sis-55 Liquid fertilizer and/or tic-M
Year planted 56 micronutrient?

N00 01' days between 57 Lbs. fertilizer per acre 113-945
start and finish Tina applied 146
Tillage 58-59 Fertilizer application #3 147-69
Season plowed 58 z N h7Ji8
No. of trips between 59 % p205 19.50

plowing and planting a: K20 51-52
Liquid fertilizer and/or 53-55
Weeding 60-62 micronutrients
N00 rotary 110911183 60 lbs. fertilizer per acre 56-58
No. cultivations 61 Time applied 59
No. other weedings 62
Pesticide application #1 63-68 Harvest
Kind 63-61; Month harvested 60-61
Rate 65.66 Day harvested 62-63
(Col. 66 is tenths) Units 624
Placement 67 Yield 65-72
Results 68 First hay cutting 65-66
Second hay cutting 67-63
Pesticide application #2 69-711 Third hw cutting 69-70
Kind 69-70 Fourth hay cutting 71-72
Rate 71-72 % moisture 73 ~71:
(Col. 72 is tenths) No. of fields yield 75
Placement 73 based on
Results ' 7h Method of measuring yield 76-77

19

Table 3. Codes for soil management group and unit symbols

 

 

 

Symbols IBM card
Category Standard Coded column Nos. Meaning_
Special L- 9 hS-hé lowland or alluvial soil
—a 2 53-5h extremely acid soil
-b 3 53-Sh soil calcareous at or near
surface
-h h SB-Sh soil having a hardpan
Textural
Upper story —- -- h7.h8 --
Lower story -- -- h9.50 --
O 01 fine clay (over 60% clay)
I 10 clay
1.5 15 silty clay loam - clay loam
2 20 clay loam - loam
2.5 25 ‘loam - silt loam
3 3O sandy loam
h to loamy sand
5.0 50 sand
5.3 53 very drouthy sand
5.7 57 extremely drouthy sand
G 60 gravelly or stony soils
R 70 bedrock or extremely rocky
soils
M 80 muck or peat
m 83 marl
Natural drainage a 1 well drained
b 2 imperfectly drained (some-
what poorly drained)
0 3 poorly or very poorly drained
c S underwater
Slope A 1 0-2 %
B 2 2-6 %
C 3 6-12%
D h 12-18%
E 5 18-25%
F 6 25-15%
G 7 16% K
Erosion 0 0 none
1 l slight
2 2 moderate
3 3 severe
h h very severe

 

20
management, as well as for other programs where such a transfer of
infomation would be useful.

The management evaluation system was based on the crop characteris-
tics and requirements, and on the soil characteristics of the crops and
soils studied. The proportion of different kinds of soils in a farm
field was taken into consideration. The evaluation system was designed
so that the one system could handle any cr0p and soil combination under
study. A scoring system was designed so that each field was given a
numerical management score. Each management factor was scored separ-
ately, the score being based on the crOp and soil combination. The man-
agement score for the field was the sum total of the scores for each of
the individual management factors. Thus, no interactions among the

management factors were considered.

General

1. The percent of the field occupied by each of the three natural
drainage classes of soils was determined. These percents were
designated as "total a," "total b," and "total c," respectively.

2. The percent of the field occupied by each soil management group
and byeach soil management unit was determined. These percents
were designated as ”total soil management groups" and "total soil
management units ," and given corresponding names such as utotal
2.5 a," and “total 2.5a02.”

3. The percent of the field occupied by the —a (extremely acid) soils,
by -c (extremely limy soils), and by -h (hardpan soils) was determined.
These percents were labeled "total -8," "total -b," and "total -h,”

respectively.

21

Evaluation of lime

 

A perfect score 10 could be obtained if any one or more of the following

conditions were met:

1.

2.

S.

6.

The crop was corn, wheat, or cats.
The crop was soy beans, navy beans, or sugar beets, and lime had been
applied within the last 10 years.
The crop was alfalfa,and.lime had been applied within 2 years of the
year that the field was planted.
The crop was soybeans, navy beans, or sugar beets, and
("total c ,1 'total b" __ 60
or ('total b“) __50
or ("total c") _ to

The crop was alfalfa,and (”total c” / "total b") _ 90
or ("total c") _ 80.

The soil was tested within the last lC>years and at least the amounts

of lime recommended were applied.

Otherwise, the score was 0.

Evaluation of drainage

 

A perfect score 10 could be obtained if any one or more of the fol-

lowing conditions were met: .

1. 'Total a“‘_ 90.

2. l'T'otal a" _.80 and "total c‘l_ 5.

3. The field was entirely tile drained.

h. The crOp was corn, alfalfa, wheat, oats, or sugar beets, and the
field was partially tiled if ("total 0" ; "total b") __ 15.

S. The crop was soybeans or navy beans and "total c"‘_ 20.

Otherwise, the score was 0.

22

Evaluation of manure

 

For each ton of manure applied for the crOp, credits of 6 lbs. N,
3 lbs. P205, and 12 lbs. K20 were given. These amounts were added to

the amounts of nutrients applied by the use of commercial fertilizer.

Evaluation of variety

 

A perfect score 10 could be obtained if any one or more of the following

conditions were met:

1. The crop was sugar beets.

2. The crop was wheat, and Genesee, Avon, Dual, or Monon was planted.

3. The crop was oats, and Ausable, Clintland 60, Clintland 6h, Garry,
Rodney, or Cbachman was planted.

h. The crop was alfalfa, and Vernal or Dupuits was planted.

S. The crop was navy beans, and Sanilac, Gratiot, Seaway, Michelite,
Michelite 62, or Saginaw was planted.

6. The crop was soybeans, and Blackhawk, Chippewa, Chippewa 6h,
Harasoy, Harasoy 63, Hawkeye, or Lindarin 63 was planted.

If the crop was corn, the score was assigned as follows:

 

 

Maturity’ Yield class
class high medium low
early 10 7 2
late 9 6 0

If data on maturity and yielding ability were not available for a

particular variety, the variety was not scored.

23
Evaluation of seeding rate

 

The most extensive soil management group in the field was used to

assign one of three soil classes to the field as follows:

 

 

Texture
NW H0,1,1.5,1.5/R,2,2/R,2.5,3 ,3/1,3/2,3/R,h,h/1,h/2 ,b/R,Sl{S/2,G,R
a - 2 2 1 1 1 1 1 2 1 1 2 2 2 2 3 3 3 3 3
b - l 1 l l' l l 1 l l l 2 2 2 2 3 3 3 3 3
c l l l l 1 l l l l l l 2 2 l l 2 3 3 3 3

 

‘17VND means natural soil drainage.

.2/ M includes all types of'muck.

‘3/ 5 includes 5.3 and 5.7.

A perfect score 10 could be obtained if the planting rate fell within
the ranges indicated below, or if the crop was alfalfa and the condition
of the stand was good. All seeding rates are in terms of pounds of seed

per acre, except for corn which is in terms of population goal or actual

population if data on actual population were available.

 

 

Soil class
Crop l 2 3
Corn 16.2 2000 11:16560 11.1115 CO
Wheat 100-12 0 90—110 80-100
Oats 70-80 65 -75 60-70
Soy beans 50-60 bS-SS hO-SO
Navy beans 37-h5 30-b0 25-35
Sugar beets 1-2 1-2 1-2

Otherwise, the score was 0.

2h

Evaluation of planting date

 

A perfect score 10 could be obtained if the crop was planted within

the ranges indicated below, or if the crop was alfalfa.

 

 

Range
Crap from to
(brn May 1 May 31
Wheat Sept. 10 Sept. 25
Oats April 1 May 1
Soy beans May 20 June 10
Navy beans May 25 June 25

Sugar beets April 1 April 30
Otherwise, the score was 0.
If a time of four days or less was used to plant the field, it was
ignored and the date planting was started was used as planting date.
If a time lapse of greater than four days was used to plant the field,
the date midway between date planting was started and the date it was

finished was used as the planting date.

Evaluation of tillage

 

A perfect score 10 could be obtained if the crop was alfalfa, wheat, or
cats. If the crOp was corn, soy beans, navy beans, or sugar beets, a
score was assigned, as shown below, on the basis of the number of tillage
operations (T.O.) between plowing and planting. A pass over the field
with a tractor and one or more tillage implements was considered a
tillage operation.

No. T.O. Score

10
10

S
2

r o

 

rwmwo

25

Evaluation of weed control

 

A perfect score 10 could be obtained if the crop was alfalfa, wheat, or
cats. If the crop was corn, soy beans, navy beans, or sugar beets, the
score was assigned according to the number of points given the weed con-
trol program. Each weed control operation was given the number of points
shown below.

One herbicide application : 3 points

One cultivation : 2 points

One rotary hoeing = 1 point

One "other" weed con-
trol operation

1 point

The number of points given the weed control program was the sum of the
number of points given each Operation times the number of times the
operation was performed. This sum was used to assign a weed control

score as follows:

 

Points Score
6 ,t 10
11-5 6
2-3 3
0-1 0

26

Evaluation of fertilizer

 

In the discussion below, "nutrients" is the sum of nutrients supplied

by application of both manure and commercial fertilizer (gf. Evaluation

 

of manure). A perfect score 20 could be obtained if the soil was tested
and at least the amounts of nutrients recommended as a result of the

test were applied. If the soil was not tested, the amounts of nut-

rients applied were compared to a standard ("5" in the table below),

and scores assigned accordingly, as shown below. The standards for N,
P205, and K20 were the average amounts of each nutrient applied by all of
Athe observations having the same most extensive soil management group

in the field as the observation in question, (or the same most extensivesoil
class (cgp23iinthe field if there were three or fewer soil management

group observations on which to base the standard), to which were applied
at least the amounts of nutrients recommended as the result of a soil test.
Similarly, if one or more minor elements were applied for a particular
crop in a county group (3f. Table 5., footnote 1/) to half or more of

the most extensive soil management group (or soil class, pf. above) in

the field observations as the observation in question, to which were
applied at least the amounts of nutrients recommended as the result of

a soil test, then the use of the minor element(s) was used as a standard.
If there were more than one such.minor elements, all suchrminor elements
together were considered as a single standard. Scores were assigned as

shown on the following page.

27

 

’ Minor
N P 0 K O
2 S 2 elements
(8 Zs (S 18 (S :8 (S :8 Score
X X X X 20
X X X X 16
X X X X 8
I X X x 8
X X X X 8
X X X X 6
X X X X 6
X X X X 6
x x x x l.
x x x x h
x x x x b
X X X X 2
X X X X 2
X X X X 2
X X X X 0
X X X X 0

Evaluation of missing data

Where management practice data necessary for computing the management
score were missing, an attempt was made to obtain them by contacting
the grower or Extension agent. If the data were not thus obtained, but
they could be estimated with reasonable accuracy, the estimates were
used. If the data could not be obtained or estimated with sufficient
accuracy, the observation was not included when the average yields for
different kinds of soil were computed if the management score for the
observation due to other factors was 65-7h. Otherwise, the observation

was included.

28

Evaluation of field management score

 

The highest possible score that could be obtained was 90. If the
field management score 275, the field was placed in the ”good"
management category. Otherwise, the field was placed in the "fair”

management category.

~ EValuation of field soil_pattern
If there were two or'more soil.management groups in the field, a yield
was assigned to each soil management group by solving for Y1, Y2, Y3...

in the equations below.
Yf'Af
El°Al fE2°A2 / E3'A3

 

k:

Y1 2 k'El; Y2 : k°E23 Y3 = k'E3
where Yf : yield for the field. Y1, Y2, Y3... are the yields assigned
to each soil management group. El, E2, E3... are the estimated yields
assigned to soil management groups by the Cooperative Extension Service,
Michigan State University (l966) in Extension Bulletin E-SSO, "Fertilizer
Recommendations for.Michigan Vegetables and Field crOps." Af is the
acreage of the field, and A1, A2, A3... are the acreages occupied by

each of the "total soil management groups.”

29

Standard units

 

Yields were converted to the standard units shown below if they were not
reported in standard units. Percent moisture was assumed to be standard
if it was not reported, except for corn. If percent moisture was not
reported for corn, it was treated as missing data (£5. Evaluation of

missing data.

 

Crop Unit % moisture
Corn bushel 1§?§W
Alfalfa ton ----
Wheat bushel 13.0
Oats bushel 13.0
Soy beans bushel 13.0
Navy beans bushel 13.0
Sugar beets ton ----

2. Evaluation of weather:

An attempt was made to evaluate weather by trying to correlate
inches of rainfall during the growing season months with yield. The
average corn yields for Ionia County from 1950 through l96h were
obtained from Michigan Agricultural Statistics (1951-1965), published
by the Michigan Department of Agriculture cooperating with the U.S.

Department of Agriculture.

RESULTS AND DISCUSSION

The adOption of better technology by growers in Ionia County has
caused the average county corn yield to increase with time. The influence
that this adoption of technology has had on yields was evaluated by
obtaining the linear regression of yield on time. The equation so
obtained was:

Yield : 30.5 ,t 1.23 (year - 1950)
The average county yields were standardized by subtracting 1.23 X (year—1950)
from the average county yield for a particular year. These standardized
yields were then plotted against the average inches of rainfall of the
six precipitation recording stations nearest or in Ionia County, 212.
Grand Ledge, Greenville, Hastings, Ionia, Lowell, and St. Johns. These
averages were computed from precipitation data published by the weather
Bureau of the U. S. Department of Commerce in the publication Climatological
Data (1950-19614). The first rainfall parameter used was that of total
rainfall during May, June, July, and August; the second parameter was
June plus July rainfall; the third parameter July plus August rainfall;
the fourth parameter August rainfall. This last parameter, August
rainfall, gave the best correlation with.yield (Figure 1.). Consequently,
a fifth parameter, inches of August rainfall reported from the Ionia
station only, was plotted against standardized yield. This fifth
parameter, however, did not correlate as well with standardized yield
as did the rainfall average of the six stations mentioned above.

The 1966 standardized yield and August rainfall value is very near
the midpoint in Figure 1. This indicates that 1966 was a near normal
year for corn production in Ionia County. However, with the improved

technology used, the actual average Ionia County corn yield was

30

31

 

Average inches of August rainfall for six weather stations, l9SO-l9éh inclusive

 

. t t :
30 no 50 60

Average corn yield (bu. per acre) in Ionia 00., l9SO-l96b
inclusive, adjusted for trend with time

Figure 1. August rainfall compared to adjusted yield for Ionia Co.

32
61.5 bu. per acre (estimated from Michigan Crop Reporting Service data).
The equation on page 30 predicts an average yield of 62.2 bu. per acre
for 1966, again indicating that 1966 was a near normal year for corn in
Ionia County.

The methods used to collect 1965 season management practice data
were not very effective. As shown in Table h, only 17% of those con-
tacted by correspondence responded. The three major reasons for the
.lack of SUCCeSS'With the program for obtaining 1965 season management
practice data are: (l) the form.used to record the practices was long
mageldy and consequently most of the growers to whom it was sent
found it difficult to use, (2) the request for information was made at
the wrong time of year, both because the growers were busy with
preparation for the 1966 season and because the time lapse since the
practices were applied was long enough so that some growers had difficulty
in recalling the information, and (3) the author was inexperienced in
interviewing crop growers and had difficulty in obtaining reliable
information from the growers interviewed in Eaton and Jackson counties.

Response to the program of 1966 data collection was much more
rewarding. As Table b shows, nearly four times as many and over twice
as great a percentage of growers responded to the 1966 data collection
program as to the 1965 data collection program. The probable reasons for
this success are: (l) the growers contacted were those most likely to
cooperate, (2) the time of contact coincided with n.1ull in their farm
vwork, (3) the form on which the management practices were recorded was
fairly simple, understandable, and easy to fill out (3f. page 11 for an

illustration), (h) the growers contacted in the 1965 data collection

33

Table h. Response of growers to correspondence program

Season for which data were sought

 

 

 

 

1965 1966

No. con- No. res- % res- No. con- No. res-‘ % res-
Cbunty tacted ponded ponse tacted ponded ponse
Calhoun 6 l 17 9 2 22
Eaton -- -- ' -- S h Bol/
Gratiot 6 O O 6 O O
Ionia 6 l 17 -.2/ -- --
Jackson .-~ -- -- h 3 751/
Lapeer 6 1 l7 9 3 33
Lenawee -- -- -- 13 8 62
Saginaw 16 h 25 18 6 33
Sanilac 7 2 29 5 2 b0
St. Clair 12 2 17 12 5 L2
St. Josephl/ l -- 11 h 36
Shiawassee -- -- —- 25 6 2b
Tuscola 12 l 8 13 h 31
Total 71 12 17 130 h? 36

 

l/ Growers were contacted by personal interview for 1965 data. This
prObably explains the high rate of response for'l966 data.

“2/ Only 1966 Corn Profit Club growers were contacted.

2/ Growers were contacted by the Extension agent for 1965 data. Infor-
mation on how many were contacted is not available. County is not
included in totals for 1965.

3h
prOgram who were not interested in c00perating with the project were
not contacted in the 1966 data collection program, (5) many of the
Cooperative Extension agents and growers were familiar with the data
collection project because of their contact with the 1965 data collection
program, (6) some of the growers in Lapeer, Lenawee, Sanilac, and St. Clair
counties were contacted personally by telephone by the author and
encouraged to fill out the data forms, and (7) in the case
of the Ionia County 1966 Corn Profit Club, the growers were personally
interviewed by experienced personnel in connection with an activity
in progress.

The highest rate of response obtained in the 1965 data collection
program was from Sanilac County. Both of the growers who responded
were contacted by the author by telephone and encouraged to fill out the
data froms sent them. The second highest rate of response was from
Saginaw Jounty. The fact that growers in Saginaw County generally have
a high interest in crOp and soil management compared to other Michigan
growers probably helps explain part of this comparatively high rate of
response.

The two highest rates of response obtained in the 1966 data collec-
tion program were from Eaton and Jackson counties. The greatest single
reason that the response was so high is the fact that these growers
had been personally introduced to the project by the author cooperating
with the respective COOperative Extension agents. The fact that the agents
were also thus introduced to the project also favored the high rate of
reaponse obtained. In both counties these agents were requested

to enc0urage the growers to fill out the data forms.

35
Both of the agents did so. In Lenawee County 62% of the growers res-
ponded. The two factors which are probably most reaponsible for this
high rate are: (1) most of the growers were contacted by the author by
telephone, and (2) the Extension agent was extremely cooperative and did
a great deal to encourage.the growers to fill out the data forms.
Sanilac and St. Clair counties also had above average rates of response.
The personal contact by telephone was probably the reason that the res-
ponse was so high.

Personal contact is evidently the most successful method of introduc-
ing growers to this kind of data collection project if the data in Table
h are significant. An initial personal contact with a follow up by
correspondence such as used in Eaton and Jackson Counties seems to elicit
a very high rate of response. Encouragement given the growers by the
Extension agent seems to also be a big factor in determining whether or
not a correspondence program is successful. '

The kind of information obtained from the responding growers is an
important criterion in determining how successful the data collection
program was. Table 5 shows to some extent how successful the 1966
management practice recording form and accompanying "REFERENCE FOR FILL-
ING IN PRINT-OUTS” (2;: pages 11-13) were as vehicles for obtaining crop
and soil management information.

Prior cover crop was reported for 18% of the fields planted to corn
in Group 1 and 2 counties, yet an intertilled crop was reported for only
l% of these same fields. An intertilled crop was reported for no field
in Ionia County. There's a good possibility that these figures should be

more nearly equal than indicated by Table 5.

36

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hh

Since the request for information was made before some of the cover
crops were sown in 1966, some of his difference may thus be accounted for.
Confusion for the grower concerning this item may have been a more
important reason these differences occur.

Variety is an item.which should have been reported on every field.
On the average, it was reported from 89% of the fields, with neither county
group being consistently higher than the other, and no crop being far
above average. Whether the variety used was certified or not was repor-
ted for 87% or more of the fields for either county group, except in the
case of the alfalfa fields, from which certification was reported more
often than was variety. Fields for which certification was reported and
for which'variety was not can perhaps be assumed to be the same variety
reported for another field sown to the same crop by the same grower.

Seeding rate was reported for 9h% or more of all the fields, except
those sown to wheat or alfalfa, for which the tate was reported for only
86% and 73% of the fields, respectively. Row width was reported for 87%
or'more of the fields, save fer soy bean fields in Group 2 counties, for
which row width was reported for only 83% of the fields. The condition
of the forage stand was reported on the average for only 65% of the alfalfa
fields. The position of this item on the data form.may help account for
the low'responsec Row width, however, should be even less noticeable by
reason of its position, yet a high rate of response was obtained for this
item. Table 5 shows that, in general, crop management information on
alfalfa was reported in fewer cases than such information for any other
crop. This may help explain the low rate of response concerning condition

of the forage stand.

1:5

Planting date was reported for 89% or more of all the fields in
either county group save for fields planted to corn and wheat in Group 2
counties which reported planting date for only 8C% of the fields.

The number of tillage trips between plowing and planting was reported
for fewer fields than some other management practices. The "REFERENCE
FOR FILLING IN PRINT-OUTS," Item 2, states, "If the information doesn't
apply, leave blank." Since some growers did not plow before planting
wheat, and even more did not plow before seeding oats, they may naturally
have assumed that this information did not apply. The number of tillage
trips was reported for only 75% of the sugar beet fields. Some of these
fields were plowed in the fall. Consequently, some of the growers may
have experienced difficulty in recalling the information. ‘Wheat, oats,
and sugar beets are the earliest planted crops in Michigan. Difficulty
in recalling the information may explain why an item such as number of
tillage trips was not reported on a high percentage of fields sown to
these crops. It is more difficult to explain why the number of tillage
trips was reported for so few (69%) of the soy bean fields. Growers
seem to have little interest in soy beans compared to their interest in
other crops. Table 5 shows that few soy bean fields received more than
one fertilizer application. Also, only 59% of the fields planted to soy
beans reported a pesticide application, whereas 8h% or more of the fields
planted to Other row crops reported a pesticide application. This seeming
lack of interest in soy bean culture may explain why the growers did not
report this item for this crop.

Information concerning whether the soil was tested or not was not
reported as often as some of the other practices. Except for Ionia County,

for no crop was such information reported for 90% or more of the fields.

1.6
Item 2 on the “REFERENCE FOR FILLING IN PRINT—OUTS" probably accounts for
a great deal of this lack of response, since some growers may not have had
their soil tested, and therefore left this item blank. Whether or not at
least the amounts of fertilizer recommended by soil test results were
applied was reported in comparatively few cases, excepting Ionia Cbunty.
The highest response obtained for this item was for corn for which it was
reported for only 59% of the fields. The way this item was worded on the
management practice recording form may have contributed to this lack of
response (93.- page II). Item 2 on the "REFERENCE FOR FILLING IN PRINT-
OUTS" might also have discouraged the growers who applied less than the
recommended amounts of fertilizer from reporting this item.

Alfalfa and wheat are the crops about which the least information
was obtained. These same crops have the longest time lapse between plant-
ing time and the time information was requested. This may indicate that
the information obtained from this correspondence program may have been
recalled chiefly fromzuemory rather than from written records. The
accuracy of the information.may be questioned on this account.

The most effective method of obtaining data was that used by the
Ionia County l966¢Corn Profit Club. This method, however, requires the
cooperation of trained personnel. The extent to which this cooperation
may be relied on at future times is not known. For corn, except for
information regarding soil test, every other item in Table 5 was reported
by the growers in the correspondence program for at least 9C% of the fields.
Using this response as a criterion, the method of data collection by
correspondence appears to be worthwhile to be considered for future data
collection, at least for corn.

The data in Table 5 can be used to some extent as survey data to

h?
help determine what practices are being applied by the growers of the
crops studied. The growers who supplied this information are generally
conceded to be some of the better growers in.Michigan. It may be possible
to consider the data in Table 5 as representative of the practices applied
by the better growers in.Michigan. Shown below is a comparison between the
percentage of all fields reported from Group 1 and 2 counties devoted to
each crop studied and the percent of harvested Michigan field crop land
devoted to each such crop in 1965 according to Michigan Agricultural

Statistics (1966).

Z land devoted to each crop

 

 

Table 5 Mich. Agr.
Crop data Stat. data
All corn h6 31
All hay 17 27
'Winter wheat 12 13
Cats 6 8
Soy beans 7 7
Dry beans 9 10
Sugar beets 5’ l

The figures are comparable for wheat, oats, soy beans, and dry beans.
There are considerable differences for corn, hay, and sugar beets. Since
the growers were requested for information on alfalfa fields only, this
may explain some of the variance between the figures. These growers are
generally situated on better land, as evidenced by the relatively high
proportion of land devoted to sugar'beets. This probably accounts for the
relatively high proportion of land in corn. It may thus be assumed that
the data in Table 5 are biased toward better growers situated on better

land 0

he

Table 5 shows that the highest percentage (52%) of fields limed
are those devoted to alfalfa in Group 1 counties. This is the trend
expected since Group 1 counties include a large prOportion of relatively
acid soils. Comparatively few fields were reported as limed in Group 2
counties, except those devoted to wheat (27% limed). The soils in
Group 2 counties are generally quite basic and do not need lime. Since
wheat is an upland crop, it tends to be grown on the better drained
(and consequently'mmrekcid) soils requiring lime. It thus seems that
lime is being applied where most needed.

Relatively little manure was applied in Group 2 counties compared
to Group 1 counties, except for corn fields, for which it was applied
to 18%. Many of the farms in Group 2 counties have no livestock from
which to obtain manure. Since the growers seem to exhibit such a high
degree of interest in corn culture, it would be expected they would apply
what manure was available on corn land.

The high percentage (61%) of navy bean fields for which a prior cover
crOp was reported is difficult to explain. The data concerning prior
cover crop mg be quite inaccurate as explained above.

As expected, an intertilled crop was reported for the most part for
wheat and oats. For both crops, the percentage of fields in Group 2
counties reporting an intertilled crop was twice as great as the percentage
in Group 1 counties. It mmy'be surmised that one of the chief reasons
wheat and oats are grown in Group 2 counties is to establish a sod crop
such as alfalfa, while in Group 1 counties these crops are grown primarily
for the sake of the harvest from the crOp itself.

varieties other than those for which a perfect score was given in the

1:9

management evaluation program were reported for 15% or fewer of the fields,
except for alfalfa (37%) and corn, for which.variety data was not sum-
marized. This indicates that perhaps more varieties ought to be included
in the perfect score category for alfalfa, since it would seem growers
planting the better varieties of other crops would plant the better
varieties of alfalfa.

All of the alfalfa fields for which certification was reported were
sown to certified seed. It can be seen that certified seed tended to
be used in a greater percentage of cases in Group 2 counties than in
Group 1 counties. Half soy bean fields, slightly less than half of the
oat fields, and only 39% of the wheat fields were reported town to
certified seed, whereas 81% of the navy bean fields were reported sown to
certified seed. Cbrn, wheat, oats, and soy beans tended to be planted at
rates higher than those indicated on page 23, whereas navy beans and sugar
beets tended to be planted at rates comparable to those on page 23.

Narrow row widths for corn (32 inches or less) are reported for
h3% of the fields in Group 2 counties, for only 12% of the fields in the
Group 1 counties, and Only 15% of the fields in Ionia County. Since
growers in Group 2 counties have narrow row equipment for navy beans and
sugar beets, and since narrow rows for corn are becoming more popular,
this can be expected. The high cost of converting to narrow row equip-
ment in Group 1 counties explains why comparatively few corn fields from
this group were reported as having narrow rows. 8

In general, planting dates reported for corn, oats, soy beans, and
navy beans were comparable to the ranges on page 2h. A large proportion,

(about 30%), of the wheat fields were reported planted outside the range

50
shown on page 2h. For sugar beet fields, 31% were reported as planted
outside the range shown on page 2h. A very late spring in l966 helps
explain this. It is interesting to note that only h5% of the oat fields
in Group 1 counties were reported planted before April 20, whereas 92%
of the oat fields in Group 2 counties were reported planted before this
date. In general, the growing season starts about ten days later in Group
2 counties than in Group 1 counties. This early planting of oats in
Group 2 counties may reflect on the timeliness with which the growers in
each group perfOrm their operations.

Minimum tillage seems to be in general use Only for sugar beets
and for corn. .Only 7—28% of the fields sown to other row crops reported less
than two tillage trips between plowing and planting.

Despite the heavy use of herbicides reported, over half of the fields
devoted to row crops are still cultivated. The fact that.l7% of the
fields in Group 1 and Group 2 counties reported insecticide applications
is indicative of the concern growers have for corn culture. The fact
that not less than 56% of any group of row crop fields were reported as
having no pesticide applied shows that chemical pest control is much
favored by this group of growers.

' In general, no soil test agency compared to another is overwhelmingly
used by any group of growers. An exception is the use of county
facilities by the Ionia County group. It is striking that such a large
percentage of fields in the Ionia County group did not apply at least the
amounts of fertilizer recommended, especially considering the fact that
they were involved in a contest. Since profit was one of the criteria by

which the contestants were judged, many may have tried to cut back on

51
fertilizer expense.

Over 50% of the fields planted to corn were reported to have received
an application of plowed down fertilizer, and an application of side dressed
fertilizer, except for the Ionia group. The fact that only 38% of the
fields in the Ionia group were reported to have received a side dressing
tends to support the cost cutting hypothesis above. Liquid fertilizer
is more popular in Group 2 counties than in Group 1 counties. This fact
along with some of the observations mentioned above shows that the growers
in Group 2 counties are applying more recent innovations than growers in
Group 1 counties. This is the trend expected and may help to support a
hypothesis that Table 5 data is representative for large groups of
Michigan growers.

The high percentage of navy bean and sugar beet fields reported to
have received micronutrients shows that the growers responding from Group
2 counties tend to apply the most current recommended management prac-
tices. The high percentage (33%) of soy bean fields in Group 2 counties
for which manganese and zinc were reported helps discredit the hypothesis
that growers generally lack concern where soy beans are concerned.
Pessibly some of these fields were for foundation seed. That 5C% of the
oat fields in Group 2 counties were reported to have received manganese
can "‘ '3 be explained by the fact that five fields of foundation seed
are included in this figure. One might expect that boron should be
applied for more alfalfa fields in Group 1 counties than were reported

since such a large proportion of acid soils are present in these counties.

The influence that some of these management practices seem to have

had on corn yield for fields involved in the Ionia County 1966 Corn Profit

52
{nub will be discussed later.

The primary reason for the collection of management practice data
was in order that the management factors on each kind of soil might be
accounted for as much as possible so that the influence of the soil
factors on yield might be assessed. Table 6 shows some average corn
yields obtained on different kinds of soil under different management
levels. The yield figures are based on observations from the Ionia
County 1966 Corn Profit Club.

The yields for the soil.management groups under good management
are in general the yields predicted by the Cooperative Extension
Service in Bulletin E—550. Except for the yields on the 3s and the ba
groups, the yields obtained are within 10% of the yields given in
Bulletin E-SSO. The yields vary according to the general pattern
found in other studies. The average yields increase as the soil becomes
less naturally well drained; they are highest for the 2.5 soils and
decrease as the texture becomes coarser or finer. There are two notable
exceptions to this pattern. Yields are higher on the 2.5a group (116 bu.
per acre) than on the 2.5b group (lCh bu./acreg and they are higher
on the he group (111 bu./acre) than on the 3a group (8h bu./acre). This
latter discrepancy occurs because the yields are much higher than
expected for the ha group and much lower than expected for the 3a group.

The average yields achieved under fair'management vary in the same
way with texture and natural drainage. Exceptions are the higher than
expected yield on the Be soil aid the lower than expected yield on the
2.5b soil. Only three out of eight soil management groups, the 2.5a,

the 3/2a, and the Be groups are within 10% of the yields predicted in

Table 6 o

53

Average corn yields for different soil management groups or

soil management units, under two management levels (Numbers
in parentheses refer to number of observations on which
average is based.)

 

 

 

 

 

Soil Soil Soil
mgt. mgt. mgt.
group group group
or Mgt. level or Mgt. level or Mgt. .1919]-
Category unit Good Fair unit Good Fair unit Good Fair
501]. 1.5a
met. 02 11h(1) 85(1)
unit 1 B2 97(1 .....
yields-J Al 117(1) --....
2.5a 2.5b 2.5c
02 111(1) -----
82 115 3 107(2)
Bl 116(12) 102(2) Bl 91(2) 101(k)
A1 ------- ------ Al 127(3) 95(5) Al 121(k) 112(3)
2.5a / 3/2a
C3 106(1) ......
Bl 110(3) ......
Al lhl(l) ......
3/2a . 3/2b
132 ....... 109(2)
A1 ------- 87(1) A1 113(1) ......
33 3c
02 95(1) ......
32 72(1) 75(1)
B1 ....... 102(5)
hAl ....... 97(1 Al 111(1) 131(1)
a
32 111(1) ......
Bl ------- 93(1)
Soil 1.5s 101:0) 85(1)
mgt. 2.5a 116(16) loh(h) 2.5b 111(5) 98(9) 2.5c 120(h) 112(3)
group 1 2.5a I 3/2a
yields—/ 116(5) ------
3/2a - ----- 102(3) 3/2b 113 (1) ......
38 8h(2) 97(7) 3c 111(1) 131(1)
ha 111(1) 93(1)
Soil 1a 95 lb 110 1c 12o
mgt. 2a 110 2b 120 2c 130
group 3/2a 105 3/2b 115 3/2c 120
yieldsa/ 3a 95 3b 105 3c 110
ha 15 hb 80 he 90

 

1 Data taken from Ionia County 1966 Corn Profit

_/ Yields taken from Bulletin 13.550, Table 3

Club

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Bulletin E—SSO. The range in management scores for the observations under
fair management was h0-7b, about twice as great as the range for the
observations under good management.

The fact that so many of the soil management groups under good
management and so few of the groups under fair management are within
10% of the yields given in Bulletin E-SSO indicates that the definition
of management presented in this thesis coincides fairly well with the
definition used by the authors of Bulletin E-SSO. The similarities
between the yields in Table 6 and those in Bulletin E-SSO furnish
additional evidence that 1966 was a nonnal season for corn in Ionia county.

In only two cases were yields Obtained under fair management greater
than those obtained under good management, zig., the Be and 3c soils.
The yields for the 3a.' soil.under fair management and the Be soil under
good management are within 10% of the yields in.lulletin E—SSO. The
yields for the 3a; soils under good management.were 95 and 72 bu./acre.
The field yielding 72 bu./acre scored well on every'management practice,
save variety. Information on the maturity and yielding ability of the
variety was not available. Some possible explanations for this low
yield might be: (1) a variety with poor yielding ability was used,
(2) the microclimate of this site was poor for corn growth, (3) the
site in question had a low level of productivity due to past treatment, or
(b) an unfavorable lime-nutrient interaction occurred. Three tons of lime
per acre were applied in 1966. The calcium may have made some of the
phosphate unavailable, or a high pH may have created a minor element

deficiency.

55

The unexpectedly high.yield obtained on the 3c soil with fair
management may possibly be explained by assuming that some data are
missing concerning the management program. Only 22 pounds per acre of
nitrogen were reported applied. This is more than 100 pounds less than
the average amount of nitrogen applied by all of the growers. One is
led to suspect that a sidedressing of nitrogen was not reported. This
field is partially tile drained, so it is doubtful that a high water
table was in reach of the corn roots to make possible this higher than
expected yield.

The yields on the ha soils are much higher than expected. Since
1966 was a normal season for corn, these yields can perhaps be obtained
with some regularity on these soils. The 111 bu./acre yield was obtained
with.the help of 156 pounds of K20 per acre applied via the use of
commercial fertilizer and manure. There is nothing particularly striking
about the management program used to Obtain the 93 bu./acre yield.
There‘wms another he yield which was excluded from.Table 6 because
information on the maturity and yielding ability of the variety was
not available. The yield Obtained was 113 bu./acre. The grower who
obtained this yield is a seed dealer and can possibly be assumed to
have used a variety with a high degree of’yielding ability. He applied
210 pounds of K20 per acre. The ha soils generally have physical
characteristics favorable for plant growth. The infiltration of air
and water into these soils is generally more rapid than it is into
finer textured soils. With natural infertility overcome by the
addition of fertilizer, these higher than expected yields do not seem
unreasonable.

The yields for the 2.5 toposequence of soils are the best documented

56
yields in Table 6. That the yields on the imperfectly drained soil
should be lower than on the well drained soil is difficult to explain.
This may indicate that the productivity of these soils has been over
estimated in the past. When the yields from 2.5b observations are
compared on the basis of whether lime was reported applied or not, the
yields for the unlimed fields were much higher than for the limed fields,
for'both the good and the fair management levels. These yields are

shown below.

 

 

Yield
Lime Good *Fair
reported Mgt. Mgt.
Yes 102 86
No 118 , 103

The yield 118 bu./acre makes the 2.5b yields fit into the pattern
expected for the tOposequence. It may be very possible that these
2.5b soils are overlimed. The 2.5b soils often occur in the same field
with better drained soils for which lime may be needed. These
imperfectly drained soils may be limed, not because they need it, but
because they happen to be in thesame field.with soils requiring lhne.
If this supposition is in fact the case, it shows how im ortant it is that
the differences in soil within a field be considered when various
management practices are applied.

Table 6 also shows a striking similarity between the yields obtained
under good management on the 2.5a I 3/2a soils and between the 2.5b
soils and the 3/2b soils. The 2.5 soils and the 3/2 soils are apparently
quite similar in their productivities. [A similar situation was noted
by Search (l96h). That these two soils should be similar in productivity
seems reasonable since both have a clay loam B horizon. The water

holding capacities of each soil and nutrient supplies ought to be

57
somewhat similar. This leads one to question how important the upper h2 inches
of these soils - ' is to productivity under present conditions of
technology. I

The deviations of the yields Obtained in 1966 from those expected
point out the need for yield information on many more fields in a number
of diffeeent years in order to evaluate the average yields for various
management levels on most of these soils.

It is interesting to note the economic implications of the differences
in yield between good and fair levels of management. Corn sold at the
elevator in January, 1967, brought an average price of $1.20 per bushel.
Using the 2.5 toposequence as an example, the differences in gross
income between good management and fair management are shown below.

Gross income_per acre

 

 

Good Fair
Soil mgt. mgt. Difference
2.5a $139 8125* $lh
2 .5b 8133 $118 $15
2.5 c $51M; $1314 810

While these figures represent gross rather than net income, they do give
some indication of the advantages the grower can realize by using good
management. It has been estimated by Mr. Lance Jepson, Ionia County
Extension Agricultural Agent, that 50% of the cost involved in growing
corn is fixed. This makes it very probable that a large percentage
of the above differences in gross income can be realized as net income.
The average yields obtained with some of the different management
practices are shown in Table 7. Neither row width or manure seems to
have much effect on yield. That one tillage trip between plowing and
planting is associated with such a high yield may show that one such
trip is necessary to make the surface of the soil even enough so that

a good stand can be obtained. Two such tripg,however, may excessively

58

Table 7. Average yields for some management practices for two
groups of observations (All data are from the Ionia
Cbunty 1966 Corn Profit Club. The number of obser-
vations on which average is based appears in paren-

 

 

 

 

theses.)

Averagegyield ‘—
2.5a soils All obser-
under good vations in

Management practice management corn club
Row width (inches)
30-36 115 (2) 111 (31)
38-110 117 (11) 107 (is)
Nhnure applied 115 (5) .......
Manure not applied 119 (8) .......
No. tillage trips between
plowing and planting
0 108 (b) .......
1 ’ 127 (6) .......
2' 110 (3) .......
Lime applied 111 (10) .......
Lime not applied 137 (3) .......
Planted on or before May 21 112 (7) 1C8 (39)
Planted later than May 21 128 (S) 111 (35)
Amount of fertilizer applied
compared to amount recommended
by soil test results
Less than recommended ------- 95 (13)
Same as recommended or more ------- 112 (h9)
Kind of variety usedl/
High yielding, late maturing ....... 122 (13)
High yielding, early maturing .- ...... 109 (9)
Medium yielding, late maturing ------- 109 (8)
Medium yielding, early maturing ....... 107 (13)

 

1/ Based only on observations for which maturity and yielding ability
of the variety was available

S9
compact . the soil.

That lime seems to be correlated with lower yields is very
difficult to explain. This is the third instance noticed in which lime
application is associated with low yields. More research on the effects
of lime and the frequency with which overliming occurs may be needed.

That higher yields seem to be associated with a later planting
date may be due to the fact that spring was very late in Ionia Cbunty
in 1966. A higher rate of seed mortality probably occurred on the
early planted fields compared to the later planted fields.

The difference in yield achieved between those growers who applied
at least as much fertilizer as recommended by soil test results and
those growers who did not apply as much fertilizer as recommended is
very striking. Part of the difference in yield may be accounted for
if it is assumed that yields increased with the amount of fertilizer
applied. Some of the growers who applied at least the recommended
amounts of fertilizer undoubtedly applied a great deal more fertilizer
than recommended. It might also be suspected that the growers who
applied at least the reCOmmended amounts of fertilizer had higher
management scores where other factors are concerned than did the other
growers. However, when average total management scores for the management
practices other than fertilizer application were compared for three
different groups of growers, there were not wide differences among the
groups. The average such score for those who did not apply at least
the recommended amounts of fertilizer was 56.5, for those who did
apply at least the recommended amounts, it was 59.2, and for those
who did not have their soil tested, the score was 62.b.

Table 7 also shows that the later maturing varieties tended to

60
yield higher than the earlier maturing varieties. The CbOperative
Extension Service cautions against using late maturing varieties.
It seems possible, however, that the late maturing varieties might
be used to advantage if the corn is intended for silage.

There is definitely a question concerning how adequately the influence
of the management factors on yield is accounted for by the management
evaluation system presented in this thesis. Especially, it must be
questioned how adequately the system accounts for the influence of
management factors on the coarser soils. Table 6 shows that over twice
as many observations on the 3a and be soils were placed in the fair
management category than were placed in the good management category,
whereas 16 times as many observations were placed in the good management
category as were placed in the fair'management category on soils with
a texture 3/2 or finer. Moreover, yields obtained with fair’management
on the 3a and 3c soils are higher than the yields Obtained under good
management. Much of the research on which the management evaluation
system is based was conducted on soils that had a texture of loam or
finer. It may be that research results attained on these finer textured
soils are not applicable, or at least not completely applicable, on
coarser soils. This may point to a need for agronomic trial to be
conducted on several different kinds of soils as suggested by Butler
(l96b). Kellogg (1955) very clearly points out the need for research
which is based on rec0gnized differences in soils.

Figure 2 shows how adequately the management evaluation system
accounts for variations in yield on 2.5a soils. That yield and manage-
ment score vary together as much as they do is encouraging, since only

two groups of factors, the management factors and the soil factors,

61

  
   

 

®
160 -1)-
<:) 'well drained soil
150 __ A moderately well drained soil CD
1110 -._
(D
13C) '1'-
Yield <E)
(bu. per well
acre) drained
120 —-— soil-Z
<9 A

    

110......

moderately
well drained
100 —1- soil

SO—

 

 

 

I 1 I l
1 7 f T 1
50 60 70 80 90

Original management score

Figure 2. Yield compared to original management score on 2.5a soils

62

 

 

 

 

‘4-
GD
160 +—
Q well drained soil C
150 A moderately well drained soil D
—u—
+ positive change from original score
—- negative change from original score
69
130 fi—
Yield "'
(bu. per " Q
acre) A
120
110
100
90 I ..
l f i l i A L
,1 ' I I g T
50 6O 7O 0 90

Revised management score '

Figure 3. Yield compared to revised management score on 2.5a soils

63
are accounted for in Figure 2. Moreover, considering that the management
evaluation system does not take into account interactions among
the factors, and that the weight given each factor and the scales used
to evaluate deviations from recommended levels are based on very
little research, the results shown in Figure 2 are especially encour-
aging. The standards against which the management factors were compared
were for the most part based on average conditions. Since 1966 appears
to have been a normal season for corn, part of the success obtained with
the use of the management evaluation system may thus be accounted for.

As mentioned before, Table 7 shows that one tillage trip between
plowing and planting on 2.5a soils is associated with a higher yield
than other tillage practices are. It was also found that 2.53 soils
under good management which were cultivated at least once yielded twelve
bushels per acre more than the corresponding soils that were not
cultivated. ‘When going over the data, it was noticed that in.many cases
high yields were obtained despite the use of a population higher than the
upper limits given on page 23. A cultivation often improves the physical
condition of the finer textured soils, a tillage operation between
plowing and planting may be needed to help establish stands on such
soils, and populations higher than those commonly recommended might
be expected to give high yields under favorable weather conditions
providing other management practices are at high levels. Consequently,
scores for these practices were changed to see if a different system
of management evaluation would better account for variations in yield.
These changes were: (1) Zero tillage trips between plowing and planting

was given a score of five instead of ten, (2) failing to cultivate at

6h
least once was given a score of minus ten points, instead of zero, and
(3) the population achieved needed only to reach the minimum recommended
for the soil class instead of having to fall within the range specified
on page 23. Figure 3 shows how this second method of scoring seems to
better account for variations in yield on the 2.5a soils.

Figure 2 shows that the moderately well drained soils seem to
respond to management differently than do the well drained soils. In
Figure 3, much of this apparent difference is removed by the revised
scoring system. Whether or not the moderately well drained soils res-
pond to management to the same degree as do well drained soils may be an
area where additional research is needed.

Another interesting item shown by Figures 2 and 3 is that the
management evaluation systems account for about only half of the total
variation in yields if the oblique portion of the curves are taken to
be the actual yield-management functions. How the influence of the
management factors can be more precisely evaluated is a very important
area of needed research.

Some changes in the scales used to evaluate some of the individual
management practices may be in order. For example, the system for rating
drainage which assigns ten for adequate drainage and zero for inadequate
drainage may assign too low a value to inadequate drainage. Part of the
drainage factor is accounted for in the evaluation of planting date, since
a well drained soil can be planted earlier than a comparable soil which
is less well drained. The fact that a soil is planted probably indicates
a reasonable likelihood of achieving a reasonably good crop half .
or more of the time. A score of five might therefore be a better

alternative than zero for representing inadequate drainage.

65
A graduated scale for variety similar to that used for corn seems
more reasonable for other crops than the ten or zero system described _
on page 22. The relation between seeding rate and row width might be
considered when evaluating seeding rate, especially for a crop like
soy’beans.

Perhaps a better method of weighting the individual.management
factors is to use regression coefficients Obtained from a regression
equation which has yield as the dependent variable and the management
factors as independent variables. This could also be used to help
account for interactions between management factors.

Growers from whom to obtain the data necessary for future produc-
tivity studies are an important item for consideration. The response
from the Telfarm group for 1966 data is very encouraging. How accurate
the yield measurements of this group are has not yet been determined,
however. Many of these growers have scales on which they weigh their
harvest, and many sell their grain at elevators so that they may have
fairly accurate yield records. This is especially true for the cash
crops wheat, soy beans, and navy beans, and to a lesser extent for corn,
especially in Group 2 counties. Sugar beets, of course, are based on
scale measurements made at the sugar factory.

For the Telfarm group, however, the problem of soil identification
is a major one. Field boundaries are constantly changing. Soil
information can sometimes be obtained by requesting the grower to send
a "Soil and Water Ebnservation Plan" soil map along with the management
practice data forms. Even if he does this, however, it still must be
determined which areas on the map coincide with the areas being reported
on each data form. This is often quite difficult unless the grower

makes a special effort to point out the area that a given data form

66
refers to. ’

Many of the difficulties mentioned above can be overcome by
.asking c00peration only from growers who farm in counties which have
been block surveyed on aerial photographs. These growers could be
asked for management practice data for only those fields which have
but one or two soil types in them. He could be supplied with an
aerial photocopy of his land on which he could outline the fields
for which he is reporting the management practice data. This photocopy
could then be used to determine which areas on the soil map are covered
by a given data form. The difficulty of changing field boundaries
might be overcome by asking the grower to report on fields which he
expects to treat as a unit over the next several years. Variations in
yield measurement could be minimized by telling the grower there is no
desire for'yield information which is not based on scale measurements.

The advantages of using data from a project such as the Ionia County
1966 Cbrn Profit Club are obvious from the standpoint of data validity,
as well as soil identification. A great deal of time is required of
trained personnel, however.

The form of reporting management information can be simplified if
a reduction in the amount of data obtained is deemed satisfactory. A form
which could be keypunched from directly or which could be used for a
mark sensing scheme might be a good step in this direction.

Yield estimates are only part of the information needed to more
adequately farm Michigan soils. Research that helps shed light on
the interactions among soil factors, weather factors, and management

factors is badly needed.

SUMMARY AND CONCLUSIONS

The method used for evaluating soil productivity appears to have
definite potentialities in southern.Michigan. Carefully selecting the
growers from whom to obtain information concerning crop and soil
management practices elicits a high rate of response. Simplicity and
timeliness in requesting information are also important.

The gathering of crop and soil management information, as was done
in this study, has definite application for a survey of practices being
used by the better growers in Michigan.

The method for evaluating the crop and soil management prOgram
used by the growers appears to work well for corn on well drained loam
soils for yields up to 125 bushels per acre. Above 125 bushels per acre,
the wide spread in corn yields was not accounted for by management level
evaluations. This focuses the need for further research to evaluate
management influences on crop yields on various soils. Study of the
effects of interactions among management practices and weather factors
seems particularly necessary. The high corn yields on the well drained
loamy sand soils suggests the need for more basic yield and management
information, particularly on the sandy soils of Michigan.

Less than three observations on any one soil unit gave average
yields which did not fit the expected pattern. Five observations or
more per soil unit usually gave results which were consistent with
those expected (Table 6). The need fer more information on many soil

and management combinations on many sites is evident.

67

LITERATURE CITED

.Aahndahl, A. R. 1960. Soil productivity--concept and predictions.
Trans. Intern. Cong. of Soil Sci. 7th Cong. Madison. 5:365-70.

Ableiter, J. K., and Barnes, C. P. 1950. Soil productivity ratings.
Trans. Intern. Cong. of Soil Sci. 5th Cong. Amsterdam. 133604;.

Anderson, A., Nelson, A. P., Hayes, F. A., and wood, I. D. 1938. A
proposed method for classifying and evaluating soils on the basis
of productivity and use suitabilities. Neb. Agr. Exp. Sta.
special Bull. 98.

Avery, B. W} 1962. Soil type and crop performance. Soils and
Fertilizers. 25:3b1-h.

Blagidov. 1960. Principles of soil and land evaluation. Trans. Intern.
Cong. of Soil Sci. 7th Cong. Madison. 52357-6h.

Butler, E. E. 196A. Assessing the soil factor in agricultural pro-
duction. Austr. Inst. Agr., Sci. Jour. 30:232-h0.

Cooperative Extension Service. 1966. Fertilizer recommendations for
Michigan vegetables and field crops. Mich. State Univ. Bull. 8-950.

Dale, R. F. 1965. weather and technology, a critical analysis of their
importance to corn yields. Agr. Sci. Rev. h:25-3l.

Gonzalez, A. M. 1963. Yields of several crops on various soils with
different management levels. Paper for the Dept. of Soil Science.
Mich. State Univ.

KellOgg, C. E. 1955. Soil surveys in modern farming. Jour.. Soil and
Water Conserv. 10:271-7.

Mettert,'w. K. 1961. Crop yield, soil and management studies in Osceola
County, Michigan. M.S. Thesis, Mich. State Univ.

lHichigan Department of Agriculture, cooperating with the U.S. Department
of Agriculture. 1966. Michigan agricultural statistics. Lansing.

Northkote, K. H. l96h. Some thoughts concerning agronomy and soil
classification. Austr. Inst. Agr., Sci. Jour. 30:2hl-6

Odell, R. T. 19h7. How productive are the soils of Central Illinois?
Ill. Agro Exp. Sta. M10522.

Odell, R. T. 1950. Measurements of the productivity of soils under
various environmental conditions. Agron. Jour. h2:282-92.

68

69

Odell, R. T. 1958. Soil survey interpretation and yield prediction.
Soil Sci. Soc. of Amer. Proc. 22:157-60.

Odell, R. T., and Smith, R. S. 19h0. A study of crop yield records by
soil types and ratings. Soil Sci. Soc. of Amer. Proc. 5:316-21.

Priest, T. w., Uhiteside, E. P., and Heneberry, w. H. 1963. Use of
soil management groups and related information in evaluation of
farmlands and their utilization. Soil Sci. Soc. of Amer. Proc.
27:335-9-

Runge, E. C. A. 1966. 200 bushel corn. Is it possible on your soils?
Univ. of Ill. Coop. Ext. Serv. Giro. 928.

Rust, R. H., and Odell, R. T. 1957. Methods used in evaluating pro-
ductivity of some Illinois soils. Soil Sci. Soc. of Amer. Proc.
21:171.; 0

Schrader, W. D., Riecken, F. F., and Englehorn, A. V. 1957. Effect
of soil type difference on crop yields on Clarion4webster soil
in Iowa. Agron. Jour. h9g2Sb-7.

Search, C. W. 19614. Relationship of corn yields from five selected
soil types in Shiawassee Cbunty. Paper for the Dept. of Soil
Science. Mich. State Univ.

Tripp, L. E. 196A. A study of the yields of corn on C-slope, eroded
Miami loan as compared to the yield on the nearly level Miami loam
soil type just above the slope. Paper for the Dept. of Soil Science.
Mich. State Univ. ‘

Vincent, W. H. 1965. Coding farm accounting data. Federal Extension
Service and Dept. Agr. Econ. Mich. State Univ. Agricultural
Economics Report No. 7. ’

Visser, W. C. 1950. The quantitative basis of the evaluation of soil
producibility. Trans. Intern. Cong. of Soil Sci. 5th Cbng.
Amsterdam. 52373-7.

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