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This is to certify that the

dissertation entitled

The Construction, Validation, and Behavior of a Pol-

lination and Fruit Set Model for 'Delicious Apples
presented by

Gloria DeGrandi-Hoffman

has been accepted towards fulfillment
of the requirements for

Ph. D Entomology

degree in

 

 

 

fl ,Majovérofes

Date October 24, 1983

 

MSU is an Affirmative Action/Equal Opportunity Institution 0-12771

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THE CONSTRUCTION, VALIDATION, AND BEHAVIOR OF A

POLLINATION AND FRUIT SET MODEL FOR 'DELICIOUS' APPLES
BY

Gloria DeGrandi-Hoffman

A DISSERTATION

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

DOCTOR OF PHILOSOPHY
Department of Entomology

1983

ABSTRACT

THE CONSTRUCTION, VALIDATION, AND BEHAVIOR OF A

POLLINATION AND FRUIT SET MODEL FOR 'DELICIOUS' APPLES

By

Gloria DeGrandi-Hoff man

A computer based, interactive, simulation model has been developed to
predict pollination and fruit set in 'Delicious' apples. Predictions are based upon
updates on the number of honey bees cross-pollinating apple blossoms, and the
probabilities that blossoms in various age classes will set fruit if cross-
pOllinated. The rate Of blossom aging is based on temperature, while the size of
the cross-polinating honey bee pOpulation is a function Of temperature, wind,
solar radiation, honey bee population size, and stage of the apple bloom.

During the model's construction, field estimates on the size of the honey
bee population carrying cross pollen were needed to validate this component of
the program. Field data indicated that this population was of considerable size.
Previously, pollen from unrelated apple varieties was thought to be transferred
by honey bee movement from tree to tree due to competition for nectar. Our
simulations predicted that competition for nectar could not create a cross-
pollinating population as large as that found in the field, and that these bees

were originating from another source. It has been concluded that honey bees

were transferring compatible pollen in the hive through contact between
nestmates. The model bases its predictions on the size of the pollinator
population on both competition for nectar, and in-hive pollen transfer.

The pollination and fruit set model (REDAPOL) demonstrated that the
strongest effects on fruit set were weather and the availability of compatible
pollen. Weather infulenced both the intensity of honey bee foraging activity and
the duration Of 'Delicious' and pollinizer bloom. The latter affect the degree of
bloom overlap and the number of Open 'Delicious' and pollinizer blossoms at any
given time. Blossom number affected the availability of compatible pollen, as
did orchard design and the ratio Of 'Delicious' fruit set under the widest range of
weather conditons was predicted to occur in orchards with one-to-one ratios of
'Delicious' and pollinizer trees. The arrangement Of trees did not strongly

influence fruit set according the the model's predictions.

ACKNOWLEDGMENTS

The author wishes to express sincere appreciation to her advisor, Dr. Roger
A. Hoopingarner for his invaluable assistance and support throughout this
project. Special thanks are also extended to Mr. Ron Pulcer for contributing his
talents and expertise in writing the computer program. Dr. Karen K. Baker is
also gratefully acknowledged for her contributions in the electron microscopy
sections of this thesis, and the advances in this work that can be attributed to
her contribuiton.

The author would like to thank her committee members Drs. Stuart Gage,
Mark E. Whalon, Martin J. Bukovac, and Frank G. Dennis for their valuable input
and discussions. Appreciation is also extended to Mr. Ken Dimoff for his
assistance in experimental design and data analysis, and Ms. Connie Crancer and
Mr. Mke Dunlap for their excellent technical support. I also wish to express my
graditude to Dr. James E. Bath (department chair) for his tremendous support of
this project, and his advice and encouragement.

The author would also like to thank the growers who cooperated in this
study. These include Jerry Stanek, James Embsen, Don and Kevin Herman, and
John and Jeanne Ashby. I would also like to thank Dr. Stanley Flegler for his
assistance in Operating the scanning electron microscope, and Ms. Genevieve
Macomber for technical assistance in the preparation of the photographic plates.

I am most grateful to my husband, Rich, for his moral support during this
project and for his assistance in bringing this work to completion. I would also

like to thank my family for their constant encouragement and support.

ii

TABLE OF CONTENTS

Page
List of Tables vi-vii
List Of Figures viii-x
General Introduction 1
Literature Review 5
Data Compilation Leading to the Development
of a Pollination and Fruit Set Model for 'Delicious' 14
Introduction 15
Materials and Methods 17
General Features of the Model's Development 17
Predicting Blossom Density per Tree 18
Defining Bloom Curves for 'Delicious' and 'McIntosh' Varieties 18
Nectar Secretion and Replacement 18
Measurements of Flight Activity Using Erickson-Waller Traps 18
Pollen Analysis Using Light Microscopy 19
Sampling for Cross Pollen on Honey Bees and Apple Stigmata 19
Honey Bee Foraging Activity on Trees 19
SEM Analysis Of Pollens on Honey Bees and Floral Stigmata 20
Relationship Between Flower Density and Final Fruit Set 20
Effect of Distance from the Pollinizer on Fruit Set 21
Seed Number in Retained and Abscissed Fruit 21
Results 21

General Flow Diagram of the Model and Explanation of Subroutines

iii

TABLE OF CONTENTS, continued

Calculating Blossom Number per Tree
Predicting the Progression of Bloom Using
Accumulated Degree Days
Nectar Secretion and Replacement
The Effects Of Bloom on Honey Bees Foraging on Apple
Predicting Honey Bees per Tree
Analysis of Pollens on Apple Foragers and Blossom Stigmata
Effects Of Blossom Density on Fruit Set
Effects of Distance from the Pollinizer on Fruit Set
Seed Number on Retained and Abscissed Fruit
Discussion
Literature Cited
Identifying Factors that Influence Fruit Set in 'Delicious' Apples
Using REDAPOL Simulations
Introduction
Materials and Methods
Initialization of Orchard Parameters
Construction of Weather Tapes
Assumptions and Framework of the Model
Results

The Influence of Orchard Design on Fruit Set

33
37
40
45
51
67
78
78
82

91

94
95
98
98
99
100
103

103

The Influence of the 'Wandering Honey Bee' Population on Fruit Set 104

iv

TABLE OF CONTENTS, continued

The Influence of Tree Size on Fruit Set
The Influence of Weather on Fruit Set
The Influence Of Colony Number and Orchard Design on Fruit Set
The Influence of Flower Viability and Colony Number on Fruit Set
The Influence of Flower Quality and Weather on Fruit Set
The Influence of Colony Density on Fruit Set Under Various
Weather Conditions
Discussion
Literature Cited
Defining the Pollinating Population in an Apple Orchard Using Scanning
Electron Microscopy
Introduction
Materials and Methods
The Influence of Distance from the Pollinizer on Fruit Set
Analysis of Pollens on Honey Bees and Apple Stigmata
Results
Effect Of Distance from the Pollinizer on Fruit Set
SEM Analysis of Pollens on Honey Bees and Blossom Stigmata
Discussion
Literature Cited

General Thesis Summary

111
114

116

114
122

128

129
I30
132
132
132
134
134
134
149
152

154

LIST OF TABLES

Data Compilation Leading to the Development of a Pollination and Fruit Set

Model for Delicious

Table Page
1. Average volume of nectar in apple blossoms on their day Of anthesis 39

2. Percentages of self-, cross-, and non-apple pollens on the bodies Of

honey bees foraging apple blossoms at the MSU Horticulture Farm 59
3. Percentages of 'Delicious' and 'McIntosh' stigmata containing self-,

cross-, and non-apple pollens at the MSU Horticulture Farm 63
4. Percent Of flowers becoming fruit on 'Delicious' trees various

distances from the pollinizer 79
5. Number Of seeds per fruit on 'Delicious' trees various distances from

the pollinizer 80
6. Seed number on retained and abscissed fruit collected from 1982

orchard sites 81

Identifying Factors that Influence Fruit Set in 'Delicious' Apples Using

REDAPOL Simulations

Lane; 2222
1. The influence of orchard desigi on fruit set 105
2. Fruit set contribution by wandering honey bees 107
3. The influence of tree size on fruit set 109
4. The influence of weather on fruit set 112

vi

LIST OF TABLES, confirmed

Titre 22g:
5. The influence of orchard design and colony number on fruit set 113
6. The influence of blossom viability and colony number on fruit set 115
7. The influence of blossom quality and weather conditions on fruit set 118

8. The influence of colony density on fruit set under various weather

conditions 1 1 9

Defining the Pollinating Population in an Apple Orchard Using Scanning Electron

Microscopy
1% Reg:
1. The influence Of distance from the pollinizer row on 'Delicious'

fruit set in two Michigan orchards 135
2. Number Of seeds per fruit on 'Delicious' trees various distances

from the pollinizer 136
3. Percentages Of honey bees carrying cross-, self-, and non-apple

pollen while foraging 'Delicious' and 'McIntosh' trees 142
4. Percentages of various pollen types carried by honey bees foraging

apple 145
5. Percentages Of apple blossom stigmata with self-, cross-, and non-

apple pollens 148

vii

LIST OF FIGURES

Data Compilation Leading to the Development Of a Pollination

and Fruit Set Model for 'Delicious'

Figge
1. The sequence of subroutines comprising the pollination and fruit

10.

11.

12.

13.

14.

set program

Sequence of operations in the "Initial" subroutine

Sequence of operations in the "Predict" subroutine

Sequence of Operations in the "Nectar" subroutine

Sequence of operations in the "Forage" subroutine

Sequence of Operations in the ”Pollprt" subroutine

Proposed 'Delicious' and 'McIntosh' bloom curves derived from 1981
field data

Comparisons of actual and predicted bloom curves for 'Delicious'
Comparisons of actual and predicted bloom curves for 'McIntosh'
Predicted relationship between state of bloom and foraging activity
on 'Delicious'

Predicted relationship between state of bloom and foraging on
'McIntosh' trees

Predicting honey bee flight response to solar radiation based upon
time of day

The predicted foraging response to temperature and wind speed
Actual and predicted honey bees per tree during a nine hour forag-

ing period

viii

22
23
25
27
29

31

34

35

38

43

48

49

52

LIST OF FIGURES, continued

Risers figs
15. Scanning electron micrographs Of apple pollen grains 54
16. Scanning electron micrographs of pollen from species blooming in

concert with apple 56

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

Scanning electron micrographs of pollens carried by honey bees foraging
'McIntosh' trees at the Michigan State University Horticulture Farm 58
Scanning electron micrographs Of pollinated apple blossom stigm ata 62
Sequence of operations in the "In-Hive" subroutine 65
Predicted in-hive pollen transfer rate as a fmetion of the cumula-

tive honey bees leaving the hive during the day 66
The relationship between blossom density and fruit set in 'Delicious'
(M.S.U. Horticulture Farm, 1981) 68
The relationship between blossom density and fruit set in 'McIntosh'
(M.S.U. Horticulture Farm, 1981) 69
The relationship between blossom density and fruit set in 'Delicious'
(M.S.U. Horticulture Farm, 1982) 71
The relationship between blossom density and fruit set in

(M.S.U. Horticulture Farm, 1982) 72
Flowering to fruiting percentages as a function of blossom density

on 'Delicious' trees (Ashby's Orchard Site) 74
Flowering to fruiting percentages as a function of blossom density

on 'Empire' trees 75
Ideal initial fruit set (i.e., fruit set goal) based upon blossom

density for 'Delicious' 76

ix

LIST OF FIGURES, continued
Linus £232
28. Ideal initial fruit set (i.e., fruit set goal) based upon blossom

density for 'McIntosh' 77
29. Flow diagram of the components considered in the pollination and fruit

set model for 'Delicious' apples 83

Identifying Factors that Influence Fruit Set in 'Delicious'

Apples Using REDAPOL Simulations

Figge Page
1. Predicted 'Delicious' fruit set percentages under various colony/
hectare and simulated weather conditions 120

2. Predicted 'McIntosh' fruit set percentages under various colony/

hectare and simulated weather conditions 121

Defining the Pollinating POpulation in an Apple Orchard Using

Scanning Electron Microscopy

Figge Page
1. Scanning electron micrographs of apple pollens 138

2. Scanning electron micrographs of pollens from species blooming

in concert with apple 141
3. Scanning electron micrographs Of pollens carried by honey bees

foraging 'McIntosh' trees at the Michigan State University Horticul-

ture Farm 144

4. Scanning electron micrographs of pollinated apple blossom stigma 147

GENERAL THESE INTRODUCTION

Like many other biological processes, insect mediated pollination can be
viewed as a system whose end product (fruit set) is a ftmction of several
components. Some Of these include weather, flower attractiveness and repro-
ductive state, and the size Of the honey bee population capable of cross
pollinating blossoms. By defining the relationships between these components
and updating their values over time, it may be possible to predict fruit set rates
under a broad range of circumstances. To test this, a pollination and fruit set
model was prOposed for 'Delicious' apples.

Because pollination and fruit set have never been examined using a systems
approach, colony/hectare requirements for commercial fruit set in numerous
crops have remained undefined. This information gap may indeed be partially
responsible for the inconsistent set often associated with 'Delicious' apples. In
the east and midwest 'Delicious' production is only about 40% of its potential,
and in the midwest this represents an annual crOp loss in excess of $85 million
(Anonymous 1978). Still, if growers seek advice on the rate Of colony
introduction needed in their orchard to insure adequate cross pollination, the
recommendations they receive will be based more on past experience than
controlled experimental findings (McGregor 1976). In addition, recommendations
for 'Delicious'-pollinizer tree arrangements in orchards, to insure sufficient
compatible pollen also have not been adequately tested.

A pollination and fruit set model could generate recommendations for

colony/hectare requirements, and predict maidmum fruit set rates for various

'Delicious'-pollinizer tree arrangements. Colonies/hectare and arrangements of

'Delicious' and pollinizer trees could be simulated with the model, and potential
fruit set predicted under various weather conditions. The model could also
predict how long colonies would be needed in an orchard. This could be
accomplished by setting a fruit set goal for a grower based upon blossom density.
The goal would be expressed as the ideal percentage of blossoms needed to
develop into fruit for a commercial set to be achieved. Because the model would
deliver daily fruit set predicitions, it could alert the grower when during the
period bloom a fruit set goal had been achieved, so that colonies could be
removed and oversetting could be prevented. The model could also be pro-
grammed to predict potential fruit set 48 hours into the future (based on input
weather predictions) and report to the grower if a particular fruit set goal could
be achieved with the number of colonies that have been introduced.

In addition to agricultural applications, pollination and fruit set models
could be used to study the interactions of honey bees and flowering plants.
Currently, the mechanism by which honey bees acquire a second apple variety's
pollen, when their foraging area is Often a single tree, is not well understood.
Although movement of honey bees between trees has been used to explain fruit
set in self-incompatible sterile varieties (Butler 1944, Free 1962, Free 1966,
McGregor 1976), it does not account for oversets on self-incompatible trees
planted in solid blocks or at remote locations from a compatible pollen source.
During the development and validation Of this model, defining the source Of
honey bees carrying compatible pollen was a critical factor in predicting the rate
of fruit set.

In the model, fruit set predictions were essentially a combination of

updates on the size of the honey bee population capable of cross-pollinating

blossoms (pollinators), and the probabilities of fruit set in blossoms whose age
had also been updated. Currently information on changes in fruiting potential
with regard to weather, blossom age, and state of bloom is limited, but does
indicate a trend where a blossom's fruit set potential declines with time. By
combining updated estimates on blossom fruit set probabilities with numbers Of
cross-pollinations, approximations could be made on the number of fruit that had
been set at any time in bloom.

Ultimately, pollination and fruit set models may afford a "total picture"
perspective on the relationship between honey bees and flowering plants. With
the model, various orchard designs subjected to different weather conditions and
colony densities could be simulated and evaluated for their fruit set potentials.
This information could generate recommendations for 'Delicious'-pollinizer ar-
rangements that would enhance the colonies' cross-pollinating potential, and
produce colony/hectare recommendations that would be specific for the year and
orchard site.

Before a pollination model could be built, the source of honey bees in a
cross—pollinating state (pollinators) had to be defined. Because the model would
have to generate predictions on the size of this population before fruit set
predictions could be made, defining the source of pollinators had to be viewed as
a pivotal point in the model's construction. A systems approach in conjuction
with field experiments was used to define the pollinator population. The
sequence of events leading to the acquisition of compatible pollen can be
simulated, and through sampling, the field population's size could be estimated.
By synthesizing this information, an explanation on the source of pollinators
could possibly be Obtained, which would afford new possibilities for the

management of pollination and fruit set.

LITERATURE CITED

Anonymous. 1978. Delicious problem is growing. Amer. Fruit Grower 98(2):15,
29, 32.

McGregor, S. E. 1976. Insect Pollination of Cultivated Crop Plants. U.S.D.A.
Agrucultural Handbook NO. 496. pp 81-88.

Butler, C. G. 1944. Work on bee repellents. Management of colonies for
pollination. Ann. Appl. Biol. 30:195-196.

Free, J. B. 1962. The effect of distane from the pollinizer varieties on the fruit
set on trees in plum and apple orchards. J. Hort. Sci. 37:262-271.

Free, J. B. 1966. The foraging areas of honey bees in an orchard of standard
apple trees. J. Appl. Ecol. 3:261-268.

LITERATURE REVIEW

Although 'Delicious' is America's number one apple variety, it is also the
most inconsistant producer especially in the east and midwest (Howlett 1928,
Roberts 1947, Gardner et al 1949). Delicious is a totally self-sterile variety and
requires unrelated cultivars (pollinizers) to be planted nearby to serve as a
compatible pollen source. Insects, particularly honey bees, are necessary for the
transfer of pollen from the pollinizers to 'Delicious' trees (Roberts 1945a, Free
1960, McGregor 1976).

As a variety 'Delicious' has numerous problems that all tmdoubtedly contri-
bute to its erratic fruit set. 'Delicious' flower buds are also less resistant to low
temperatures than other varieties, both before and during bloom (Hartman and
Howlett 1954). Compared to other varieties 'Delicious' exhibits exceptionally
strong apical dominance, so that fruit set on lateral spurs is significantly
depressed by the presence Of fruit on the terminals (Howlett 1928). Detjen
(1929) stated that the terminallflower on a cluster base was "better constituted
and better situated" and usually gave a higher percent set over the laterals. In
'Delicious' the positioning of lateral flowers also affects their quality. Laterals
that are not situated in the axil of a leaf do not set as well as those lateral
flowers with subtending leaves (Howlett 1932).

Although 'Delicious' ovaries (and most other apple varieties) have the
potential to set 10 seeds, it is not unusual for these blossoms to open with less
than a full complement of ovules. Hough (1947) stated that in the development

of 'Delicious' ovules, the most frequent abnormality was either tardy initiation of

the megaspore mother cell, or a slower development rate of megaspores and

embryo sacs. Such retarded embryo sacs are seldom expected to develop fully in
time for fertilization. Other apparently normal embryo sacs degenerate soon
after anthesis, significantly shortening the effective pollination period for the
variety. Hartman and Howlett (1954) stated that delayed development and early
degeneration of the embryo sac nuclei at and subsequent to anthesis has a
genetic basis in the variety.

In addition to the loss of fruiting potential from ovule degeneration,
Hartman and Howlett (1954) found that fertilization was greatly decreased when
pollination was delayed for 48 hours after anthesis. The reduction in fruiting
potential was attributed largely to a loss of stigma receptivity. Another fruit
set constraint in 'Delicious' is related to the time during bloom when a particular
blossom opens, which seems to influence its probability of setting fruit if cross-
pollinated. Lapins and Arndt (1974) reported that during cool weather 'DeliciOus'
blossoms pollinated the first few days of bloom set fruit while those pollinated
later did not.

The morphology of 'Delicious' blossoms may further reduce their chances Of
setting fruit, because honey bees can remove nectar without contacting the
stigma. Consequently, these foragers often do not cross-pollinate blossoms.
This occurs because 'Delicious' blossoms are characterized by short pistils and
upright staminal filaments, which allows bees to extract nectar without touching
the stigma in a majority of cases (Roberts 1945a,b. Robinson 1979). In addition,
gaps exist at the bases of the staminal filaments around the nectaries. This
allows honey bees to stand on the petals and extract nectar without contacting
the stigma. Only 'Northern Spy' has basal gaps comparable to 'Delicious', and has

a higher percentage of bees visiting blossoms without touching the stigma

(Robinson 1979). In light of this information the importance of basal gaps on fruit
set is questionable, since 'Northern Spy' does not have fruit set problems.

Weather is the common denominator between flowering plants and their
pollinators, because the effects on one are invariably felt by the other.
Pollinator activity can be directly affected by weather conditions, or indirectly
by their influence on the crop (Ribbands 1953 cited by Williams and Sims 1977).
Insect flight, flower quality and attractiveness are all affected by temperature,
wind, relative humidity, and solar radiation.

Lundie (1925) reported that the threshold temperature for honey bee flight
varied with the time of year and weather conditions. In April the threshold
temperature ranged between 120 and 14°C, while in May it rose to 160 to 18°C.
On cloudy days the threshold was 20 higher. After a certain threshold
temperature is achieved, flight activity is further influenced by light intensity.
Under normal conditions optimum temperatures occur later in the day than
Optimum light, but morning bee comts regularly give higher numbers than
afternoon counts at the same temperature. This is caused by the higher light
values that exist in the morning hours. Light intensity, especially in the ultra-
violet range, declines rapidly in the afternoon, and although temperature may
remain stationary or even rise, bee counts gradually recede with fading light
(Brittain 1933, Szabo 1980).

The foraging population is also affected by wind speed. Because honey bees
fly at speeds of about 6.3 m/sec, it is reasonable to assume that wind speeds
greater than or equal to that average affect foraging activity (Williams and Sims
1977). Rashad (1957) found that wind speeds of 4.9 m/sec reduced pollen

gathering activity, and at winds greater than 9.4 m/sec honey bees stayed in the

hive. Pollinator activity on apple blossoms was greatest at wind speeds of .44
m/sec (1 mph), but steadily decreased to 1/7 that number at speeds of 3.1 m/sec
(Brittain 1933 cited by Free 1960). From these data it was concluded that even
light winds affect the size of the foraging population.

Aside from effects on honey bee foraging, weather also influences the
attractiveness and quality of apple blossoms. The duration Of the apple bloom is
apparently temperature dependent. When the weather is warm, bloom will last
for about five to seven days while cooler temperatures can prolong bloom to
almost two weeks. Individual flowers will not Open if temperatures are below
10°C (Free 1960, McGregor 1976). Because apple blossoms are dish-shaped and
have exposed nectaries, their attractiveness (in terms of caloric reward to a
forager) can also be strongly influenced by weather. Rain or dew dilutes nectar
making blossoms less attractive to nectar foragers. High temperatures and wind
concentrate the nectar and allow blossoms to regain their attractiveness (Butler
1944, Roberts 1945a).

Weather can also effect the chances that a cross-pollination will cause
fertilization and fruit set. Pollen germination and pollen tube growth are both
temperature dependent, and low temperatures can prevent fertilization even if
adequate masses of pollen are placed on the stigma (Martin 1972). In addition,
slow pollen tube growth has a compomding affect in reducing fruit set, because
the stigma and ovules continue degenerating while the pollen tube is growing
(Hartman and Howlett 1954).

Because 'Delicious' is self-incompatible, unrelated apple varieties (pol-
linizers) must be planted nearby to act as a compatible pollen source . Some

varieties are better pollinizers than others because they possess certain char-

acteristics. For instance, ideal pollinizers flower annually and bloom two or
three days before the 'Delicious' blossoms open. The pollinizer should also
produce large amounts of viable and compatible pollen (i.e. the pollinizer must
be a diploid variety) and remain attractive for the duration of the 'Delicious'
bloom. Recommendations for the best pollinizer varieties are area dependent
because a pollinizer that may have an overlapping bloom with 'Delicious' in one
region may not in another (Dennis 1979). For example 'Northern Spy' and 'Golden
Delicious' are listed by Roberts (1947) as being excellent pollinizers for
‘Delicious', but in Michigan both varieties flower after 'Delicious's king blossoms
have lost their attractiveness and probably their receptivity. Based upon yields
Of 'Delicious', 'Rome Beauty,‘ 'Northwestern Greening,’ 'Wealthy,‘ 'Jonathan,‘
'Golden Delicious' and 'Northern Spy' are reported to be the best pollinizers in
various sections of the U. S. (Roberts 1947). In Michigan 'Jonathan' is
considered the best 'Delicious' pollinizer (Anonymous 1978), although 'McIntosh',
'Empire', and 'Golden Delicious' are also used.

In addition to environmental and genetic factors limiting fruit set, honey
bee behavior also exerts a strong influence. Honey bees choose to forage a crop
for nectar because it consistently gives a caloric return greater than that
expended in the reward's search and extraction (Heinrich and Raven 1972). In
the case of apple, a large tree with heavy flowering will prompt individual honey
bees to restrict their foraging areas to a single tree, and continue to visit it on
successive trips (Butler 1944, MacDaniels 1931, Roberts 1956). In an orchard of
standard trees, at best, honey bees will visit an average of two trees per foraging
trip (Free 1966). In dwarf tree hedge row arrangements, honey bees have been

found to work along a hedge row, and probably restrict their foraging areas to

10

about 3m sections of a row during one trip. Nearly all honey bees that do move

to other rows move to an adjacent row, which possibly explains why more fruit is

sometimes set on trees next to the pollinizer rows (Williams 1959, Free and
Spencer-Booth 1964b). Honey bees also appear to discriminate between
varieties, and exhibit cultivar fidelity (Free 1966). Because Of these foraging
behaviors, it is recommended that to insure maximum pollination, pollinizer
varieties should be planted as every fifth tree in rows of main variety trees (Free
and Spencer- Booth 1964a).

Although a majority of honey bees appear to have established foraging
areas, superimposed upon this p0pulation is another of wandering bees which may
be responsible for cross-pollination in orchards (Butler 1944, McGregor 1976).
Wanderers have no set foraging areas, and can work several trees on the same
trip from the hive. This wandering population could be the result of competition
for nectar which causes bees to drift from one area to another. Young bees
which have not yet acquired definite habits or foraging areas could also
contribute to this population (Butler 1944).

Although honey bees have been observed to move from tree to tree,
pollinators that arise from this situation may be only part of the total pollinating
population. In 1954, Karma and Vickery speculated that honey bees could
possibly pick up pollen in the hive from contact with nest mates, and hence carry
pollen on their bodies from species or varieties that they never visited. This
source of cross pollinators could explain why isolated self-incompatible trees set.
fruit. Other investigators have also fOImd that honey bees carry viable pollen
from several plant species from one foraging trip to the next (Kendall 1973).

Additional investigations showed the viability of insect-borne fruit pollen was

11

usually similar to that Of pollen from blossoms taken from the orchard in which

the insects were collected (Kendall 1973, Kendall and Solomen 1973). From this

information, it is apparent that individual honey bees may be leaving the hive
carrying pollen from flowers that they never visited.

Whether or not inconsistent set in 'Delicious' is pollination related is still
Open to speculation. When the weather before, during, and immediately after
bloom is favorable, 'Delicious' set is so heavy it needs to be thinned. Only 5-
10% of the blossoms are required to develop into fruit for a full commercial set,
but the chances of fruit set occurring are best early in the bloom period. Conse-
quently, a good commercial set should result if ovules are viable and flight

weather is favorable at this time.

LITERATURE CITED

Brittain, W. H. 1933. Apple pollinatin studies in the Annaplis Valley, N.S.
Canada. 1928-1932. Bull. Dept. Agric. Can. New Ser. no. 162.

Butler, C. G. 1944. Work on bee repellents. Management of colonies for
pollination. Ann. Appl. Biol. 30(2):195-196.

Dennis, F. G. 1979. Factors affecting yeild in apple with emphasis on
'Delicious.‘ p.395-422. In J. Janick (ed.) Horticultural review AVI. West-
port, Conn.

Detjen, L. R. 1929. The effects of nitrogen on the set of apple flowers situated
variously on the cluster base. Proc. Amer. Soc. Hort. Sci. 25:153-157.

Free, J. B. 1960. The pollination of fruit trees. Bee World. 41(6):14l-
151;(7):169-186.

Free, J. B. 1966. The foraging areas of honey bees in an orchard of standard
apple trees. J. Appl. Ecol. 3:261-268.

Free, J. B., and Y. Spencer-Booth. 1964a. The foraging behavior of honey bees
in an orchard of dwarf apple trees. J. Hort. Sci. 39:78-83.

Free, J. B., and Y. Spencer-Booth. 1964b. The effect of distance from the
pollinizer varieties on the fruit set of apple, pear and sweet cherry trees.
J. Hort. Sci. 39:54-60.

Gardner, V. R., T. A. Merrill, and W. Toenjes. 1949. Fruit setting in the
Delicious apple. Mich. Agr. Exp. Sta. Spec. Bul. 358.

Hartman, F. O. and R. S. Howlett. 1954. Fruit setting of the Delicious apple.
Ohio Agric. Exp. Sta. Bul. 745. 64 pp.

Heinrich, B. and P. H. Raven. 1972. Energetics and pollination ecology.
Science. 176(4035):597-602.

Hough, L. F. 1947. A comparative study of the life history of the Arkansas
Delicious and Grimes Golden apples with respect to the variations in

fruitfulness shown by these varieties. PhD Thesis. Univ. of Illinois.

Howlett, F. S. 1928. Fruit setting in the Delicious apple. Proc. Amer. Soc.
Hort. Sci. 25:143-148.

Howlett, F. S. 1932. Partial defloration in relation to 'Delicious' fruit setting.
Ohio Agric. Exp. Sta. Bul. 745. 64pp.

Karmo, E. A. and V. R. Vickery. 1954. The placement of honey bees in orchard
pollination. Mimeogr. Circ. N.S. Dept. Agric. Mktg. No. 67.

12

13

Kendall, P. A. 1973. The viability and compatability of pollen on insects visiting
apple blossoms. Appl. Acol. 10:627-643.

Lapins, K. 0., and H. Arndt. 1974. Main causes of low fruit set in 'Delicious'
apples in 1974. Brit. Columbia Orchardist 14:8-9.

Lundie, A. E. 1925. The flight activities of the honey bee. U. S. Dept. of
Agric., Bull. No. 1328.

MacDaniels, I... H. 1931. Further experience with the pollination problem. Proc.
NOY. Ste Hort. SOC. 76:32.37.

McGregor, S. E. 1976. Insect pollination of cultivated crop plants. USDA
Agricultural Handbook No. 496:81-88.

Martin, E. C. 1972. Pollination of fruit crops. Dept. of Entomol., Mich. State
Univ., East Lansing, MI

Ribbands, C. R. 1953. The Behavior and Social Life of Honeybees. London: Bee
Research Association.

Roberts, R. H. 1945a. Blossom structure and setting of Delicious and other
apple varieties. Proc. Amer. Soc. Hort. Sci. 46:87-90.

Roberts, R. H. 1945b. Bee pollination of Delicious. Amer. Fruit Grower.
65(4):16.

Roberts, R. H. 1947. Notes on the setting of Delicious, 1946. Proc. Amer. Soc.
Hort. Sci. 50:85-94.

Roberts, D. 1956. Sugar sprays aid fertilization of plums by bees. N. Z. J.
Agric. 93:206-207, 209, 211.

Robinson, W. S. 1979. Effect of apple cultivar on foraging behavior and pollen
transfer by honey bees. J. Amer. Soc. Hort. Sci. 104(5):596-598.

Williams, R. R. 1959. The effective distance of a pollen source in a cider apple
orchard. Rep. Long Ashton Res. Stat. for 1958. 61-64.

Williams, R. R., and F. P. Sims. 1977. The importance of weather and
variability in flowering time when deciding pollination scheme for Cox's
Orange Pippin. Expl. Hort. 29:15-26.

DATA COMPILATION LEADING TO THE DEVELOPMENT

OF A POLLINATION AND FRUIT SET MODEL FOR 'DELICIOUS'

14

INTRODUCTION

The rate of fruit set in an apple orchard is a variable whose value depends
upon weather, orchard design, flower quality and pollinator population size. If
accurate fruit set predictions are to be made, they must incorporate these
factors and their changing influence on the fruit set rate over time. A systems
science approach could be used to estimate the rate of fruit set because it
permits both flexibility in analysis of various orchard designs, and the ability to
update fruit set rates as the bloom and foraging population change. With this in
mind, a simulation model for 'Delicious' apple was constructed to predict
pollination and fruit set during the bloom period. The model's predictions are
based upon the specific orchard parameters input by the grower, and weather
conditions existing during bloom.

The essence of the model's fruit set predictions is the ability to update the
fruit set rate as weather conditions change during bloom. All the parameters
that affect the rate of fruit set including the number Of Open blossoms,
attractiveness and quality of blossoms, size of the foraging population (after the
number of colonies introduced per acre has been considered), and the probability
that cross-pollination will lead to fruit set are tied to weather conditions.
Significant honey bee flight occurs only if days are warm, sunny, and calm.
Nectar secretion and sugar concentration, which dictate blossom attractiveness,
are also weather dependent. Finally, temperature influences the fruit set
potential of blossoms in terms of their stigma receptivity, rate of pollen tube
growth, and ovule receptivity. These factors ultimately effect the probability of

cross pollination leading to fertilization and fruit set.

15

16

During the model's construction, predictions on the source and size of the

pollinator population (i.e. honey bees working 'Delicious' blossoms while carrying

compatible pollinizer pollen on their bodies) were seen to be a pivotal point on
which fruit set predictions could be made. The origin Of this population has
never been definitively described. Several authors have reported that pollinators
could arise from competition for nectar on the pollinizer, which would prompt
foragers to wander between trees and hence cross pollinate blossoms (Butler
1944, Free 1962, Free 1966, McGregor 1976). Another source of pollinators was
reported by Karmo and Vickery in 1954. These investigators speculated that
pollen collected during the day could be transferred among nest mates through
contact in the hive. Consequently, honey bees could be leaving the hive carrying
pollen from plant species that they had never visited. Although it is logical to
assume that both sources of pollen transfer exist, their contribution to the
pollinator population size under different weather and orchard conditions has
never been investigated. During the construction and validation of this model, it
was possible to better define this pOpulation, and how it changes with orchard

and weather conditions.

MATERIALS AND METHODS

General Features of the Model's Development

The model's program was written in Fortran-IV and input on a CDC series
170 model Cyber 750. The model is programmed to use weather data
(temperature, wind speed, solar radiation, and relative humidity) collected by a
Campbell Scientific CR-21 micrologger.* Various field experiments were
conducted in two sites in 1981 and 1982. In 1981 the Michigan State University
Horticulture Farm (located in East Lansing, Ingham County) and Stanek and Sons'
Orchard in Traverse City (Leelanau County) were used. In 1982 the same sites
were used again and in addition Herman's Orchards Of Sutton's Bay (Leelanau
County) and John and Jeanne Ashby's Orchards in Jonesville. These sites were
chosen for their orchard design and geographical significance.

In 1981 temperature was recorded on a hygrothermograph in both sites. In
1982 temperature was again recorded on a hygrothermagraph, but at Stanek and
Sons' orchard a Campbell Instrument CR-21 Micrologger was used. Temperature,
wind, relative humidity, and solar radiation were recorded using this instrument.

Predicting Blossom Density Per Tree

 

In 1982 groups of 'Delicious‘ (at Stanek and Sons' and Ashby's orchards),
'Empire' (at Ashby's only) and 'McIntosh' (at Stanek and Sons only) trees were
chosen after stratifying the orchards into 3 sections. Tree height and width were
measured, and the distance between the ground and first main branch recorded.
Flowering spurs were counted on meter long branch sections, and average spurs
per meter was calculated. Finally the flowering spurs on the entire tree were
counted. The data from these trees was also used in experiments to test the

effects of floral density on fruit set.

* Campbell Scientific Inc., P.O. Box 551, Logan, Utah 84321

17

18

Defining Bloom Curves for 'Delicious' and 'McIntosh' Varieties

 

In 1981 and 1982 open blossoms on 'Delicious' and 'McIntosh' trees (at the

MSU Horticulture Farm and Stanek and Sons' Orchards) were counted daily on
1m branch sections beginning on the first day of bloom. Daily flower counts
were taken only at the Horticulture Farm in 1982. Counts were made from the
same branches throughout the blooming period. Four counts were taken per
tree, one COImt from each side.

Nectar Secretion and Replacement

 

Nectar samples were taken from "blossoms on their day Of anthesis in 1981
at both orchard sites. Blossoms were enclosed in nylon mesh bags while in the
'balloon stage' to protect against nectar removal by foragers. Samples then were
taken by placing a Drummond microcap (one-microliter size) between the
staminal filaments and dabbing the nectary tissue. In experiments to determine
nectar replacement rates blossoms were sampled, then depetaled to decrease
their chances of being foraged during the sampling interval. Nectar volume was
calculated by measuring the amount of nectar within the tube to the nearest
millimeter, and then converting this to microliters.

Measurements of Flight Activity Using Erickson-Waller Traps

 

At the MSU Horticulture Farm in 1981 the entrances of two colonies were
equipped with Erickson-Waller traps to measure foraging activities (Erickson et
a1. 1975). Hourly pollen samples were taken from these traps and frozen
(separately) for later analysis. Relative flight activity and percentage of pollen
collectors (i.e. honey bees with pollen loads in their corbiculae) in the foraging

population were also recorded hourly using these traps.

19

Pollen Analpis Usinggght Microscopy

 

 

One gram samples of pollen collected in Erickson-Waller traps were

acetolyzed (according to the procedure of Faegri and Iversen (1964)) and stained
with 1 ml of 0.01% solution of methylene blue* (to facilitate identification).
Pollen was identified as being either apple or non-apple using light microsCOpy.
Calculations on the percentage of apple pollen in the sample were made using a
Lovins micro-slide field finder, and counting apple and non-apple pollen grains in
30 fields.

Sampling for Cross Pollen on Honey Bees and Apple Sggmata

 

In 1982 at the MSU Horticulture Farm and Stanek and Sons' Orchards honey
bees working apple trees and competitive plants were sampled periodically
during the day. Honey bees were removed from the flowers they were foraging,
put in individual vials, and frozen. The pollen on the body of these insects would
later be removed and examined using scanning electron microscopy (SEM).

In 1982 'Delicious' and 'McIntosh' blossom stigmata were removed at the
end of the flight day from all orchard locations, except Herman's and Ashby's.
Samples were kept frozen tmtil examined for cross-pollen using SEM. Finally,
pollen samples were taken from apple varieties and competitive plants that were
in bloom with the 'Delicious' and 'McIntosh' trees. These samples would be used
for comparisons with pollens found on honey bee bodies, and apple stigm ata.

Honey Bee Foragi_n_g Activity on Trees

 

 

At the MSU Horticulture Farm in 1981 and 1982 honey bees were counted
hourly on 8 'Delicious' (Millerspur sport) and 8 'McIntosh' (Macspur) trees.

Because standard sized trees were used, honey bee counts were made simul-

*Methylene blue, C. I. 52015, 91% dye content

20

taneously by two Observers stationed on either side of the tree. Each Observer
counted the honey bees seen on their half of the tree during a 45 second interval.

At Stanek and Sons' orchards semi-dwarf 'Delicious' (Red-Chief) and
'McIntosh' (Macspur) trees were used for hourly honey bee counts. Because these
trees were small, all the honey bees on a tree (seen in a 45 second interval) were
counted by one Observer. Eight trees were used in each hourly sample.

SEM Analysis of Pollens on Honey Bees and Floral Stigmata

 

Body pollen of frozen honey bee samples was removed by rolling the
insect's body over an aluminum SEM stub coated with adhesive. The sample was
sputter-coated with gold for three minutes. Non-germinated pollen grains were
identified as self-, cross-, or non-apple pollen using a JEOL JSM-35C scanning
electron microscope operated at 15kV. This method of identifying varieties of
fruit pollen using SEM was first reported by Fogel (1977 a,b).

Floral stigmata were prepared for SEM examination by placing them on an
aluminum stub pretreated with an adhesive. The stigmata were then Sputter
coated with gold for 3 minutes and examined for self-,cross-, and non-apple
pollens.

Relationship Between Flower Density and Final Fruit Set

In 1981 monthly fruit counts were conducted on branches Of 'McIntosh'
trees (at the MSU Horticulture Farm) used earlier to derive the flowering curves
for this variety. 'Delicious' trees at the MSU Horticulture Farm with sparse
flowering were also used in the experiment. All the flowers on these 'Delicious'
trees were counted, and the resulting fruit recorded monthly.

In 1982 trees used to predict blossom density (from various tree para-

meters) were also used to monitor the percentage of blossoms setting fruit.

21

During bloom, flowering spurs on the entire tree were counted at the Traverse

City and Jonesville sites. Monthly fruit counts were then made until harvest.

Effect of Distance from the Pollinizer on Fruit Set

 

In 1982 at the Sutton's Bay Orchard site 1m branch sections on four sides of
'Delicious' and 'McIntosh' trees were chosen for evaluation of fruit set. In this
experiment, trees various distances from the pollinizer were selected. Monthly
fruit set counts were performed at the site until harvest.

Seed Number in Retained and Abscissed Fruit

 

In 1982, seed counts were made on fruit retained on the tree and those
abscised during 'June drop' at all orchard sites. Fruit was chosen at random from
'Delicious', 'McIntosh', and 'Empire' (at Ashby's and MSU Horticulture Farm only)

trees throughout the orchard. Abscised fruit under the trees was also sampled.

RESULTS

General Flow Diagram of the Model and Explanation of Subroutines

The flow diagram indicating the subroutine sequence is diagrammed in
Figure 1. The first subroutine called in the main program is "Initial" (Figure 2).
In this subroutine all values for variables and arrays are set for the beginning of
the simulation. Before leaving the subroutine, blossom age is updated and
matricies containing rates of nectar replacement and probability of fertilization
leading to fruit (based on the number Of receptive ovules) are generated, for
each age class of apple blossom.

The interactive portion of the simulation begins within the "Orchard"
subroutine. The user is asked to provide details about the orchard's acreage,

'Delicious'-pollinizer block planting pattern, tree characteristics and spacing,

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23

INITIAL

I

INITIALIZE
VARIABLES

 

 

 

 

SET UP
ARRAYS

I

GENERATE

RATE AND
PROBABILITY
VALUES

I

I RETURN ]

 

 

 

 

 

 

 

 

Figure 2. Sequence of Operation in the "Initial" subroutine.

24

blossom counts and viability, and numbers of introduced honey bee colonies.

From this data the subroutine calculates orchard parameters that will influence
the rate of cross pollination and the number of available blossoms. With the
exception of additional input of honey bee colonies, this subroutine is called only
once during a run of the program.

Hourly weather data is next entered into the program from data collected
on a Campbell Instrument CR-Zl micrologger. Calculations on the number of
open blossoms, their nectar content and viability, and the size of the foraging
population are all weather based. For this reason, weather must be input before
predictions can be made.

If a grower chooses to see predictions on future fruit set (24-48 hours into
the future) with the current number of colonies per acre, the program will enter
the "Predict" subroutine (Figure 3). Possible fruit set over a 24-48 hour interval
is reported to the grower using weather predictions based upon daily high and low
temperature, wind velocity, and probability of precipitation. The grower is
warned that these are only predictions, not actual occurrences, and fruit set
predictions are only as accurate as the input weather predictions.

After the program passes through the "Predict" subroutine, the next step is
to update the time elements. The model runs on two distinct time units,
chronological and physiological, both of which are stepped through simul-
taneously. Components that run on chronological time are weather, bee flight
activity, and fruit set reports. They are updated hourly. The state of the bloom,
and age of the flowers are described in physiological time (accumulated degree
days).

After time is updated, the "Bloom" subroutine is called. "Bloom" is called

once each hour, and updates the number of newly opened blossoms based on

25

PREDICT

      
 

DO YOU WANT
PREDICTION

Y
o

SAVE CURRENT
STATE DATA

 

SWITCH TO

PREDICTED
WEATHER

I

INPUT HOURS

FOR PRED.
WEATHER

I

INPUT ADDITIONAL
BEES (IF DESIRED)

 

 

 

 

 

 

 

RETURN

 

Figure 3. Sequence Of operation in the "Predict" subroutine.

26

accumulated heat units. New flowers are placed in appropriate positions within
an array named 'Full'. 'Full' contains only those flowers which currently contain
a nectar load, and are attractive to honey bees. Another array called 'Empty' is
the counter part to 'Full.' 'Empty' contaim all flowers which currently have been
visited that hour, and are unattractive to honey bees. The values in 'Full' and
'Empty' always sum to the total number of blossoms open that hour.

Following the update of flower number, the "Nectar" subroutine is called
(Figure 4). This subroutine is called hourly to monitor the secretion of nectar in
'Delicious' and pollinizer blossoms. "Nectar" updates the total amount of
available nectar in blossoms of each accumulated degree day age class. A honey
bee visit or rainfall greater than .254cm during any hour is assumed to remove
all nectar from the blossoms. Nectar is replaced after a bee visit or rain storm
based upon the age class of the flower (as calculated in the "Initial" subroutine),
and the hour's weather conditions (Figure 4).

Once the amount of nectar within a class of empty flowers is replenished
to the attractiveness level, the blossoms are removed from the 'Empty' array and
returned to the 'Full' array. This subroutine is called once each hour. It is
assumed that blossoms open with a full complement of nectar.

After blossom number and attractiveness are updated, the size of the
foraging population an apple is calculated in the "Forage" subroutine (Figure 5).
This subroutine is called hourly, but will return to the main program if proper
honey bee flight conditiom are not met. Factors used to calculate the percent
of the foraging force leaving the hive each hour include temperature, wind, solar
radiation, and rain less than .127cm/ln. After the foraging population is

calculated, a portion of it is lost to competitive plants based on the state of the

27

NECTAR

    

 

UPDATE

REMAIN
&
EMPTY

 
 

 

 

I

 

 

 

 

 

 

 

 

 

 

 

ALL
BLOSSOMS CALC-
INTO EMPTY NECTAR
I REPLACEMENT
ZERO OUT
UPDATE REMAIN,
REPLACE
EMPTY,REPLACE

 

 

 

 

 

 

I

 

Ema

Figure 4. Sequence of operations in the "Nectar" subroutine.

28

Figure 5. Sequence of Operations in the "Forage" subroutine.

 

FORAGE

29

 

 

NO
VISITS

 

 

I

 

 

RETURN

 

 

8A
TO
N 8PM 7
Y
Y
N
N
Y

 

 

CALCULATE
HEAT&WIND
FUNCTIONS

I

LOSE BEES
TO COMP.
PLANTS

 

 

 

 

 

 

CALC.
PROPORTION

OF EMPTY
BLOSSOMS

I

CALC.
WANDERING

BEES

I

DISTRIBUTE
BEES ON
BLOSSOMS

I

 

 

 

 

 

GENERATE
VISITS

 

 

 

I

 

 

RETURN

 

 

30

apple bloom. Competition for nectar among the honey bees on apple is
calculated next, using the ratio of blossoms in the 'Full' array to those in 'Empty'.
It is assumed that the portion of apple foragers finding five empty blossoms in a
row will leave the tree. This population is referred to as "wandering bees.” The
"Forage" subroutine distributes the foraging and wandering bee population on to
available blossoms, and generates the number of blossoms which have been
visited in each age class. This information is then placed in the 'Visit' array, and
control is returned to the main program.

Just as the foraging and wandering pOpulation size is updated hourly, so is
blossom quality in terms of the probability of fruit set (if cross pollinated).
Ovules are predicted to degenerate as the blossoms age (as a function of
accumulated degree days), while the number of receptive ovules on the day of
anthesis is predicted to be a function of the period of opening during bloom.
King blossoms are predicted to open with a full complement of ovules and a .999
probability of setting fruit if cross pollinated on their day of anthesis. As the
bloom ages, the probability of setting fruit on the day of anthesis decreases, so
that the fruit set rate is greatest during the first few days of bloom. Because
there is no data on ovule degeneration based upon accumulated degree days, the
actual probabilities of cross pollination leading to fruit set at various blossom
ages and period of anthesis has not been ”hard coded" in the model. Currently
different probabilities are being tested through model simulations to find which
numbers result in the most realistic fruit set predictions.

The final subroutine called in the program is "Pollprt" (Figure 6). This
subroutine integrates the values in the 'Visit' array, the number of wandering

bees, details of the orchard, and values for ovule receptivity by age class

31

POLLPRT

I

CALCULATE

 

POLLINATIONS

I

DISTRIBUTE
TO
CLASSES

I

CALCULATE

SUCCESSFUL
FERTILIZATIONS

I

UPDATE. DAILY
&
TOTAL FRUIT

I A

PRINT RESULTS
AND STATUS

T. I e
[RETURN]

Figure 6. Sequence of operations in the "Pollprt" subroutine.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

32

established in the "Initial" subroutine. By multiplying predictions on the number
of blossoms cross-pollinated per hour (by age class) by their probabilities of fruit
set, ”Pollprt" calculates the number of cross pollinations which have resulted in
fruit set. This subroutine is called hourly when honey bee flight is occurring.
”Pollprt" updates the daily fruit set totals, and reports to the grower total fruit
set which has occurred since the simulation began.

Calculatirg Blossom Number per Tree

 

In the programs first subroutine ("Initial"), the number of blossoms that will
open during bloom is calculated from user input of various tree parameters.
These include tree height, width, trunk height from the ground to the first limb
of fruiting wood, and average number of flowering spurs (or flower clusters) per
meter of branch. In the original program, the flowering part of a tree was
equated to a sphere whose radius was one half the tree height minus the portion
that was trunk. This information was then used to calculate the volume of a
sphere using the equation: sphere volume = 4/3 (radius)3. It was then assumed
that only two-thirds of the sphere volume was fruiting wood. The number of
blossom clusters per tree was then approximated by multiplying the estimated
volume of fruiting wood by the average number of flowering spurs per meter of
branch. The number of blossoms per tree was then calculated by multiplying the
estimate of blossom clusters per tree by 6 (McGregor 1976). Unfortunately when
this method was tested against actual tree parameters, predictions of blossom
clusters per tree were not good even after varying blossoms per spur and the
percentage of the tree's volume that was flowering wood.

In 1982 at Stanek and Sons' and Ashby's Orchards 28 trees were selected

and their height, width, trunk height, average number of flowering spurs/meter

33

of branch, and the number of flowering spurs on the entire tree were measured.
A multiple regression was performed regressing tree height, width, trunk height,
and average number of spurs/meter of branch on total flowering spurs per tree.
These parameters were found to be highly correlated to the number of spurs on
the entire tree with the regression equation: (Total number of flowering spurs =
4.68 (Average spurs/meter of branch) + 36.6 (tree height) +106.0 (tree width) -
398.0 (trunk height) having a correlation coefficient of .975. The total number
of spurs/tree was then multiplied by 5.5 to calculate the total number of
blossoms per tree.

Although the regression equation had a high correlation coefficient, and is
currently being used in the model, how well it actually predicts the total number
of spurs/tree will need at least another year's data for validation. The 5.5
blossoms/spur is also an assumption based upon field observation while taking
blossom counts, and could also have its accuracy increased through additional
measurements.

Predictifl the Progression of Bloom Using Accumulated Degree Days

 

Data from 'Delicious' and 'McIntosh' blossom counts taken in 1981 at the
MSU Horticulture Farm and Stanek and Son's Orchard are plotted on accumu-
lated degree days (DDS) 5°C threshold in Figure 7. Bloom for both varieties has
been divided into two periods; before and after peak bloom, and separate
equations were used to describe them.
Equations derived from 1981 data of 'Delicious' and 'McIntosh' blossom
counts were used to predict the progression of bloom at the MSU Horticulture
Farm in 1982. The actual pre-peak bloom curve for 'Delicious‘ is compared to

that predicted from 1981 data in Figure 8a. In 1982 'Delicious' peak bloom

FLOWER FREQUENCY

O S

0.4

0.2

O O
L T I

I
0.0 0.2 0.4 0.6 0.8 1.0

34

 

 

T ‘rih
BLOOH PERIOD

Proposed 'Delicious' and 'McIntosh' bloom curves

Figure 7.
derived from 1981 field data. (RDA = 'Delicious')

35

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occurred at 45 DD which was only 2.6 DD later than the average (42.4 DDS)

5 5
used for the predictive curve. The model has been programmed to use the
integral of the predictive equation: (percentage of open blossoms = -.211 + 3.29
(Accumulated degree days/115) to calculate the number of new blossoms opening
each hour. This equation is used by the model from the start of bloom Lmtil 60
DD 5 have accumulated.

After peak bloom a second equation is used to predict the progression of
bloom: Percentage of total blossoms = [(DD5/115)-2*.2605I -.3267. This
equation was derived from 1981 flower counts at both orchard sites. The
comparison of the actual progression of post-peak bloom in 1982 (at the MSU
Horticulture Farm) and that predicted by the model is shown in Figure 8b.

In 1981, (at both orchard sites) blossom counts were also made on
'McIntosh' trees, because this variety is often used as a pollinizer for 'Delicious'.
Although the general shapes of the 'McIntosh' bloom curves were similar in 1981
and 1982, the percentage of open blossoms at various degree day intervals was
quite different using a 5°C base. In 1981 peak bloom occurred at 33.2 DD and

5

37.9 DD at the MSU Horticulture Farm and Stanek and Son's Orchards

5
respectively. In 1982 peak bloom at the Horticulture Farm did not occur Lmtil
43.0 DDS' Because of the variance in accumulated degree days for peak bloom
between the two years, and because the curves for 'McIntosh' derived from 1981
data resulted in such poor estimates for the progression of bloom at a base
temperature of 5°C, other base temperatures were tried in an attempt to derive
more predictive curves.

At a base temperature of 1.00C peak bloom in 1981 was found to occur at

52.3DD, at the MSU Horticulture Farm and 49.1DD, at Stanek and Son's orchard.

37

At the MSU Horticulture Farm in 1982 peak bloom for 'McIntosh' occurred at

54.1 DDl' Because of the relative similarity of accumulated degree days for

peak bloom at the 1.0°C base, and the closer correspondence between the two
years in the progression of bloom it is assumed that 'McIntosh' has a lower
threshold temperature than 'Delicious', at least for the expression of bloom.
From the 1981 pre-peak bloom data, an equation was derived (using a 1°C
base) to predict the progression of bloom in 1982 at the MSU Horticulture Farm.
Comparisons of the actual pre-peak bloom curves for 1981 and 1982 with that
predicted by the equation are shown in Figure 9a. Peak bloom was predicted to

occur at 50.8 DD which is the average of the accumulated degree days for peak

1!
bloom for both 1981 and 1982 data.

After 50.9 DD have accumulated, the progression of bloom is predicted by

1
the equation: Percent Bloom = ((DD)-z * .1526) - .148. Comparisons between
bloom curves from this predictive equation and those derived from field data are
shown in Figure 9b. With the exception of one point (at 54.5% of the bloom
period), the predictive curve lies between or directly in line with the 1981 and
1982 data. As in the case of the 'Delicious' bloom equation, the model uses the
integral of these equations to calculate the number of newly opened blossoms

during each degree day interval.

Nectar Secretion and Replacement

 

The average volume of nectar in 'McIntosh' flowers was found to be
significantly greater than in 'Delicious' blossoms at both orchard sites in 1981
(Table-1). At Stanek and Sons' orchards 'Delicious' blossoms averaged about
0.024 ml of nectar, while the mean 'McIntosh' nectar secretion was 0.225 ml of

nectar per blossom. At the MSU Horticulture Farm 'Delicious' blossoms

38

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39

Table 1.

Average volume of nectar in apple blossoms on their day of
anthesis.

 

 

Sample Average volume
Variety Site Size of nectar

'Red Delicious' MSU Horticulture 20 .121 :_.08 a
(Millerspur) Farm
'McIntosh' MSU Horticulture 20 '337.i.-07 b
(MACSPur) Farm
'Red Delicious' Stanek & Sons' 44 .026 i .049 a
(Red Chief)
'McIntosh' Stanek & Sons' 48 .225 i .042 b
(MACspur)

 

 

 

 

 

Means followed by the same letter are not significantly
different at the 5% level as determined by Fisher's LSD.
Comparisons in nectar volume between sites was not made.

 

4O

averaged .121 ml of nectar while 'McIntosh' averaged 0.337 ml of nectar per
blossom.

The rate of nectar replacement in both varieties was not related to
temperature, wind speed, or relative humidity. Although nectar was not
secreted at air temperatures below 10°C, the rate nectar was replaced was not
found to be a function of increasing temperatures. Even when relative humidity
and wind speed, in combination with temperature were used to define the
relationship, correlation coefficients for the rate of nectar replacement as it
relates to temperature and relative humidity still were less than 0.05 in both
varieties.

Originally it was assumed that blossoms would be revisited when their
nectar was replaced, and this was predicted to be a function of weather
conditions and blossom age. Because this assumption was not supported in the
field, blossoms now are predicted to be attractive again 30 minutes after being
visited. This assumption is based upon the dissipation time of the ”marker"
phenomone deposited on blossoms by visiting honey bees (Ribbands 1955).
Blossoms are rarely visited by other foragers immediately after a visit, because
this pheromone is apparently interpreted as existing exclusively on non-reward-
ing blossoms. When the pheromone dissipates the blossom can be foraged again
and in the case of apples may have replaced all, or none of its original quantity
of nectar (according to our data).

The Effects of Bloom on Honey Bees Foraging on Apple

The foraging population response to state of bloom was defined using pollen

samples from Erickson-Waller traps (collected in 1981 at the MSU Horticulture

Farm), and hourly counts of honey been on 'Delicious' and 'McIntosh' trees (taken

41

at Stanek and Sons' Orchards in 1982). The curves expressing the relationship
between state of bloom (expressed in degree days) and foraging activity are
shown in Figures 10d and 11d. Each of these curves is actually a combination of
three separate functions whose use is dependent upon the degree day interval
(Figures 10 a-c, 11 a-c).

From the start of bloom until just past the bloom peak (i.e. 63% of the
'Delicious' and 40% of the 'McIntosh' bloom expressed) a Michaelis-Menton
function best described the foraging response (Figures 10a, 11a). These curves
simulate the rapid increase in apple foraging activity after colony introduction
as evidenced by Erickson-Waller pollen trap samples. The percentage of apple
pollen collected after the first full day of flight averaged 46.4% for four colonies
(the percentages of apple and non-apple pollen in the trap was assumed to reflect
the percentage of the foraging force on apple). Apple pollen continued to make
up about 50% of the pollen in the trap samples as the 'Delicious' and 'McIntosh'
trees approached their bloom peaks.

Data from pollen samples were no longer used to predict foraging activity
after peak bloom, because later blooming apple varieties ('Golden Delicious' and
'Northern Spy’) at the MSU Horticulture Farm were opening at this time, and
were being actively foraged. Pollen from trap samples was not identified to
variety, therefore these samples could not reflect the decline in foraging
activity with the waning of 'Delicious' and 'McIntosh' blooms.

After peak bloom the percentage of the foraging force working 'Delicious'
and 'McIntosh' trees was estimated from hourly counts of honey bees on trees at
Stanek and Sons' Orchards in 1982. After estimating honeybees/hectare based

upon weather and colonies /hectare, the proportion of the foraging force on

42

Figure 10. Predicted Relationship Between State of Bloom
and Foraging Activity on 'Delicious' (A=Pre-Peak
Bloom response, B=Post-Peak Bloom Transition
response, CBPOSt-Peak Bloom Response, D=C0mbined
Response Curves).

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Proportion of A0000 Forogoro on 'Hclntoon' 1r000

Proportion of A0000 Foroq0r0 on 'McIntooh' Inn

44

  
 

 

 

 

 

  
 

 

 

 

 

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Proportion of totol Bloom 009r00 (JoyaR Proportion of Iotoi Boom 000m Donn
Figure 11. Predicted Relationship Between State of Bloom and

Foraging on 'McIntosh' Trees (A=Pre-Peak Bloom
Response, B=Post-Peak Bloom Transition Response,
c-Post-Peak Bloom Response, D=Combined Response curves)-

45

apple was solved for by testing various percentages until the best predictive
curves were acquired. This was accomplished by dividing the post-peak bloom
response into two stages; a transition response (for the interval just after peak
bloom) and a late bloom response from the end of the transition interval until
final petal fall) (Figures 10 b,c and 11 b,c).

Observations of honey bees on 'Delicious' and 'McIntosh' trees after peak
bloom showed a decline in the foraging population that was best described using
linear fimctions (Figure 10b and 11b). During this transition interval (defined as
the time when 64-70% of the 'Delicious' and 41-59% of the 'McIntosh' bloom was
expressed) the bloom was still apparently attractive to a high percentage of field
bees, but fractions of the foraging population were abandoning their foraging
areas on apple each day.

In the late stages of bloom (the remaining 30% of the 'Delicious' and 41%
of the 'McIntosh' bloom), forging activity decreased rapidly on both varieties.
The decline in the foraging population on 'McIntosh' was possibly augmented by
the proximity of 'Delicious' trees whose bloom was 1-2 days behind 'McIntosh' in
its decline. Honey bee working 'McIntosh' trees probably switched to the
'Delicious' rows as the 'McIntosh' bloom declined, and hence brought about an
earlier decrease in the foraging population on this variety. The late bloom
foraging response for 'Delicious' and 'McIntosh' which gave the best predictions
of honey bees 0n the trees is shown in Figures 10c and 110.

Predictigng Honej Bees per Tree

In 1982 at Stanek and Sons' honey bees were counted (hourly) on 'Delicious'

and 'McIntosh' trees, while temperature, solar radiation, and wind speed were

recorded. Because of tree size, it was possible to count the bees on the entire

46

tree. An analysis was then conducted to express the influence of weather
parameters and state of bloom (expressed in degree days) on honey bee foraging
activity on 'Delicious' and 'McIntosh' trees.

Initially a multiple regression was performed on the field data to test if a
regression equation could predict foraging activity on apple trees. Although the
regression equations for both varieties showed a high degree of correlation
between weather, bloom, and bee activity (R2 values in excess of .85), these
equations were not predictive.

The model's original program contained equations derived from the litera-
ture describing the influence of temperature, wind, solar radiation, and state of
bloom on foraging activity (Jorgensen and Markham 1946, Lundie 1925, cited by
Williams and Sims 1977, Free 1960). Honey bees/acre 0n apple was predicted by
removing portions of the maximum possible foraging population using equations
derived from these reports. Temperature and solar radiation were reported to
have a positive influence on foraging while wind speed had negative affects.
State of bloom was reported to positively influence the foraging population
before peak bloom and negatively affect it after the bloom peak.

The original program was built on the assumption that a colony during
apple bloom averaged 20,000 bees, 8,000 of which were foragers. Predictions of
honey bees/tree were made by combining updates on apple foragers/acre (based
on weather and state of bloom), and trees of each variety/acre. Comparisons
were then made between model output on honey bees/tree using weather data
collected at Stanek and Son's Orchard (1982), and actual honey bees/tree at that
site under the same weather conditions and degree degree day interval. Unfor-
tunately model predictions were inaccurate and it became apparent that

adjustments would have to be made in the equation and assumptions.

47

After unsuccessful attempts to obtain good prediction using a single
equation throughout the day for the honey bee response to solar radiation, it was
concluded that the response was dependent upon time of day (i.e. the sun's
position on the horizon). This factor apparently influences how positively the
foraging population responds to increasing light values. The best foraging
population predictions occurred when curves were developed to describe the
solar radiation response in the morning, mid-day and afternoon (Figure 12 a,b,c).
In the morning (800-1200 hrs daylight savings time (DST)) a linear function with a
positive slope, and negative y-intercept (indicating a threshold effect) gave the
best honeybees/tree predictions. Between 1300-1400 hrs (DST) the foraging
response to solar radiation differed markedly from that in the morning or later
afternoon, even when temperature and wind speed remained fairly constant. To
account for this, a transition solar radiation curve was derived (Figure 12b), and
is used to predict the foraging response during this interval. Finally, a third
solar radiation curve was derived to predict foraging activity on apple from 1300
hrs until the end of the flight day (Figure 12c). Field data indicated that the
response to light values in the later afternoon differed from those occurring at
mid-day (1300-1400 hrs.), and prompted the derivation of this curve.

The foraging response to temperature also required adjustments, and the
response function now used in the model is shown in Figure 13a. The program
uses a threshold temperature of 10°C to initiate honey bee foraging on apple.
This value was chosen because honey bees were seen foraging apple trees at this
temperature, and 10°C is the threshold for nectar secretion in apple as indicated
by our nectar studies. After a temperature of 26°C, it is predicted that honey

bee flight no longer is limited by temperature at this time of year.

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The curve expressing the relationship between wind speed and foraging on
apple is a hybrid of our data and literature values (Figure 13b). Originally a
negative exponential curve was fitted to the literature data, but was found to
severely underestimate flight activity. The linear function shown in Figure 14b
gave far more accurate predictions of honey bees/ tree when used in concert with
the temperature and solar radiation curves. The lower and upper limits of the
curve are from literature reports, while values in between are a product of field
data and simulation runs (Brittain 1933 cited by Free 1960, Rashad 1957).

It was initially assumed that a colony contained about 8,000 foragers, but
the accuracy of this assumption needed testing. At Stanek and Sons' Orchard 56
colonies (54 rented colonies and two from the University apiary) were introduced
at a density of .11 colonies/hectare. Colonies were composed of two standard
depth hive bodies, and were a combination of overwintered colonies and early
spring starts from packaged bees. Taking into account colony density/hectare, a
series of calculations were performed to approximate the number of
foragers/colony. The combination of hourly counts of honey bees/tree and
number of trees per hectare was used to estimate the number of honey bees
working apple/hectare. Using the percentages of apple and competitive plant
pollen coming into the hive from pre-peak bloom pollen sample data (from the
Erickson-Waller traps), the approximate portion of the total honey bees/acre
foraging apple was calculated for a particular degree day interval. Possible
apple foragers per acre was then calculated by correcting for the decrease in the
foraging population due to weather (during the sampling period). The total
number of foragers per colony was then estimated by adding the portion of the

total foraging population on apple to the remaining percent on competitive

51

plants and dividing by .11 colonies/hectare. Estimates of foragers/colony were
made by repeating this procedure at various sampling intervals. From our data is
was estimated that colonies had between 4500-4600 bees in their foraging
population.

Comparisons of actual honey bees on 'Delicious' and 'McIntosh' trees (under
monitored weather conditions) and those predicted by the model are shown in
Figures 14a,b. On both 'Delicious' and 'McIntosh' trees, predictions of bee
activity during the morning and late afternoon are by far the most accurate:
(actual 'Delicious' honeybees-predicted)Z = 0.511, (actual ‘McIntosh‘ honey bees -
predicted).Z = .208). Only from 1300-1400 hrs do the predictions become less
precise: (actual 'Delicious' honey bees -predicted)Z = 0.626, (actual 'McIntosh'
honey bees - predicted)Z = 0.420).

Analysis of Pollens on Apple Foragers and Blossom Stigmata

 

Pollen from various apple varieties and competitive plants blooming
concurently with 'Delicious' and 'McIntosh' trees could be identified by size and
exine pattern using SEM (Figures 15 and 16). Pollen samples collected from the
bodies of apple foragers were compared to those collected from 'Delicious' and
'McIntosh' trees. Pollen types were then identified as being self-, cross-, or non-
apple pollen relative to the tree (or plant) from which the bee was collected. In
1982 every honey bee captured while working 'Delicious' or 'McIntosh' trees (at
the MSU Horticulture Farm) was carrying pollen from other apple varieties and
in some instances pollen from other plant species (Figure 17) (Table 2). Three
honey bees captm-ed while foraging dandelion flowers were also fmmd carrying
pollen types other than dandelion.

'Delicious' foragers captured both in the morning (900-1200 hrs DST) and

afternoon (1300-1750 hrs DST) were found to have significantly more compatible

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53

Figure 15. Scanning electron micrographs of apple pollen grains.

A - Millerspur 'Delicious' (1800x), B - Macspur 'McIntosh'

(1800x), C = 'Gallia' (l800x), D 8 'Rhode Island Greening'
(1800x).

 

 

 

 

 

54

 

Figure 16.

55

Scanning electron micrographs of pollen from species blooming
in concert with apple. A = Tart Cherry (720x), B - Stanely
Plum (720x), C = Bartlett Pear (1800x), D - Bosc Pear (660x),
E = Dandelion (Taraxacwn spp) (440x), F 8 Yellow rocket
(Barbarea spp) (l300x).

56

 

57

Figure 17. Scanning electron micrographs of pollen carried by
honey bees foraging 'McIntosh' trees at the Michigan
State University Horticulture Farm.

58

 

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60

pollen (i.e. pollen from an unrelated variety) than self-pollen on their bodies
(Table 2). Honey bees captured while working a solid block of 'McIntosh' trees
(at the MSU Horticulture Farm) were also carrying both self and compatible
pollen, but in different proportions in the morning and afternoon (Table 2).
Compatible pollen was predominant during afternoon hours only on these
'McIntosh' foragers, and was present in approximately equivalent amounts to
self— and non-apple pollen in the morning.

Although significantly more compatible pollen was found on both 'Delicious'
and 'McIntosh' foragers, the small sample sizes warrant conservative conclusions,
concerning the mean percentages of pollen types. At the very least though,
honey bees captured on both varieties were found to be in a condition where
cross pollination was possible if at least some of the pollen on the bee's body was
viable. Even when trees were planted in a solid block arrangement (as in the
case of the 'McIntosh' trees), honey bees were carrying pollen on their bodies
from apple varieties that were located several hundred meters away. When all
samples were combined, compatible pollen was found to comprise the majority of
pollen types carried on a forager's body in both the morning and afternoon (Table
2).

The foragers ability to transfer compatible pollen was evidenced by its
presence on the stigma (Figure 18). In these samples the stigmatic surface was
often heavily coated with pollen, so that only those grains on the outer most
surface could be counted. All pollinated stigmata collected from 'Delicious' and
'McIntosh' trees at both the MSU Horticulture Farm and Stanek and Sons'
Orchards were found to contain compatible pollen graim (Table 3). Whether

compatible pollen actually existed directly on the stigmatic surface, and hence

61

Figure 18. Scanning electron micrographs of pollinated apple blossoms stigma:
A and B from 'McIntosh' blossoms, while C and D are from 'Delicious'.

62

 

 

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64

was in a position to germinate and ultimately fertilize ovules could not be
determined with the SEM procedure.

From these field results, a new subroutine called "In Hive" was added to
the model to predict the number of pollinators arising from pollen transfer
among nestmates in the hive. The flow diagram describing this subroutine is
shown in Figure 19. The number of honey bees leaving the hive carrying pollen
that could set fruit on 'Delicious' or 'McIntosh' trees is predicted to be a fimction
of uninterrupted foraging intensity (number of honey bees leaving the hive)
during the previous hours as described by the equation: % of honey bees with
mixed pollen (in the current hour) = .213 * log1 0 (number of foragers leaving the
hive the previous hour) (Figure 20). The number of possible cross pollinators (at
time (t)) is then obtained by multiplying the percentage of bees with mixed
pollen by the number of foragers leaving the hive that hour.

Although honey bees may acquire pollen in the hive, unless it is from a
variety that is compatible with either the pollinizer or 'Delicious', these bees
cannot be added to the pollinator population. The potential pollinator population
is predicted to be a ftmction of both foraging intensity and the percentage of the
foraging population working either 'Delicious' or pollinizer trees. The percentage
of the foraging population on these varieties (as predicted by accumulated
degree days and state of bloom) is assumed to reflect the percentage of pollen
types coming into the hive, and hence the probabilities of an apple forager
leaving the hive with compatible pollen. Consequently as the number of foragers
on the pollinizer and 'Delicious' trees increases, the amount of these pollens
entering the hive increases, raising the probability that apple f oragers will obtain

compatible pollen within the hive by contact with nestmates.

65

 

.2131” log“? at foragers

leaving the hive):

 

 

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mixed pollen) = Possible
cross pollinators
(POSXPOL)

 

 

 

 

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(XPOLAM or PM) :

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7

 

 

 

 

 

 

 

Figure 19. Sequence in the "In Hive" Subroutine.

66

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Y = .213 I: log,.(x)

 

0.50

Proportion of Honey Bees Leov
0.25

 

D0.00

I l i l
. 10000. 20000. 30000. 40000.
Cumulative Honey Bees Leaving the Hive
Figure 20. Predicted In-Hive Pollen Transfer Rate as a Function

of the Cumulative Honey Bees Leaving the Hive During
the Day.

67

Honey bees were timed while working 'Delicious' and 'McIntosh' trees to

determine the average number of blossoms visited per hour. After accounting

for travel time and transfer of pollen and nectar loads to bees in the hive,
foragers were estimated to be visiting an average of 100 apple blossoms/hour.
The possible cross pollinating visits in an hour is then predicted to be the number
of cross pollinating bees (i.e. foragers that have acquired compatible pollen in
the hive or by moving from tree to tree) estimated that hour multiplied by 100
visits.

Because pollen was shed primarily in the morning in the orchards used in
this study, compatible pollen acquired in the hive would be more rapidly diluted
by self-pollen during this time if foragers were working a single variety (either
'Delicious' or pollinizer). Consequently, although a honey bee may visit about
100 blossoms per foraging trip, she probably only cross pollinates a variable
percentage based upon time of day. Finally the total pollinating visits occurring
in an hour is predicted to be the sum of those performed by wandering bees
moving from the pollinizer to the 'Delicious' trees (or 'Delicious' trees to the
pollinizer), and visits by honey bees that have acquired compatible pollen in the
hive.

Effect of Blossom Density on Fruit Set

 

In 1981 at the MSU Horticulture Farm, 'Delicious' trees with sparse
flowering had a July fruit set (Fruit/Blossom) that ranged between 0.35 and 0.83
depending upon blossom density (Figure 21a) 'McIntosh' trees had a higher
blossom density than 'Delicious', and had lower initial fruit sets (0.042 - 0.174)
(Figure 22a). In both varieties there was an inverse relationship between blossom

density and initial fruit set that resembled a negative exponential ftmction.

68

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70

Throughout the 1981 season, 'McIntosh' trees continued to self thin, thus
reducing their initial fruiting percentages. Thinning occurred in 'Delicious' trees
too, but to a much lesser extent, especially in trees with very few flowers. By
harvest time the 'Delicious' flowering to fruiting curve had not changed in shape
(Figure 21b). In contrast, 'McIntosh' trees considerably reduced their initial fruit
set so that the final fruit set curve appeared linear (with the exception of one
point) with fruit set percentages ranging between 0.03 and 0.08 (Figure 22b)

In 1982 this experiment was repeated at the MSU Horticulture Farm and
Ashby's Orchard using trees of different blossom densities. Again there was a
trend where an inverse relationship existed between initial set and flower density
in both 'Delicious' and 'McIntosh' trees (Figures 23 and 24). 'Delicious' blossom
density (at the MSU Horticulture Farm) ranged between 82 and 143
blossoms/meter, and had a respective initial fruit set range of 0.18-0.34 (Figure
23a). Blossoms per meter of branch on 'McIntosh' trees ranged between 52 and
126, and had an initial fruit set range of 0.06-0.24 (Figure 24a).

Self-thinning occurred in both varieties throughout the season so that final
fruit set ranges for 'Delicious' and 'McIntosh' at the MSU Horticulture Farm
were 0.11-0.21 and 0.04-0.13 respectively (Figures 23b and 24b). Final fruit set
rates in both varieties did not appear to be as strongly influenced by blossom
density in 1982 as 1981 particularly in the 'Delicious' trees. This could have
occurred because blossom density on 'Delicious' trees in 1981 was much lower
than in 1982 (in 1981 blossoms on the entire 'Delicious' tree were counted for this
experiment, while in 1982 this was not feasible because of the higher blossom
density). At very low blossom density levels flowering could have a more

pronmmced effect on both initial and final fruit set, while in instances when all

71

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73

trees have comparatively high blossom density, the resulting fruit set range is
considerably narrower.

Further testimony is added to this conclusion by considering the data
collected at Ashby's orchard in 1982. Trees at this site were only 2-3 m tall so
blossoms on the entire tree could be counted. Flowering was relatively dense on
both 'Delicious' and 'Empire' trees (relative to their size), and ranged between
200-980 blossoms/tree on 'Delicious' and 800-1830 blossoms/ tree on the 'Empire.‘
Initial and final fruit sets on 'Delicious' ranged between 0.018-0.072 and 0.012-
0.066 respectively, but did not show a marked influence of blossom density on
the fruit set rate (Figure 25). Even in the 'Empire' trees where there was a
comparatively wide range in blossom density between trees, initial (0.048-0.066)
and final (0.036-0.066) fruit set rates did not. show an influence of blossom
density on final fruiting (Figure 26) The trend of trees with lighter flowering
showing less thinning did hold true for this site though, as it did for data
collected at the MSU Horticulture Farm.

Results from these experiments were incorporated into the model to
establish initial fruit set goals for the grower. At both Ashby's Orchards and the
MSU Horticulture Farm, thinning sprays were not applied, and final fruit size
was suitable in size for fresh market. When growers using the model input
blossom density/meter of branch (on their 'Delicious' trees), an ideal fruit set
percentage based upon the equation: fruit/blossom = e-0.002(blossoms/m) -
0.4503 (Figure 27) is established as a pollination goal for this variety. If
'McIntosh' is used as a pollinizer the equation used to establish the fruit set goal

-0.001 8(blossoms/ m)

is: fruit/blossom = e -0.70 (Figure 28).

74

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Figure 27.

l 1 I
50. 100. 150. 200.

'DELICIOUS' Blossoms per Meter

Ideal Initial Fruit Set (i.e., Fruit Set Goal)
Based Upon Blossom Density for 'Delicious'.

Fruit per Blossom

0-36

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0.18

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Figure 28.

77

I I 1
$0. 100. 150-
'Mclntosh' Blossoms per Meter

Ideal Initial Fruit Set (i.e., Fruit Set Goal)
Based Upon Blossom Density for 'McIntosh'.

 

1
200-

78

Effect of Distance from the Pollinizer on Fruit Set

 

In 1982 the percentage of blossoms initially setting fruit at Herman's
Orchard (in Sutton's Bay) did not differ significantly with respect to distance
from the pollinizer ('McIntosh') (Table 4). Initial percentages of blossoms setting
fruit ranged between 12.9% (3 rows away, west side of the pollinizer) and 17.9%
(next to the west side of the pollinizer).

Seed number per fruit (initial set) was also counted at Herman's in 1982 and
analyzed for differences with respect to distance from the pollinizer ('McIntosh')
(Table 5). Only trees adjacent to the east side of the pollinizer had significantly
more seeds than trees in other rows. Seeds per fruit ranged between 3.70 (three
rows away, east side of the pollinizer) and 6.89 seeds per fruit (next to the east
side of the pollinizer).

Seed Number on Retained and Abscissed Fruit

 

Seed number was not significantly different in retained and abcised
'Delicious' fruit at the MSU Horticulture Farm in 1982 (Table 6). Apples retained
on the tree averaged 6.41 seeds/fruit, while those abscised during 'June drop'
averaged 6.23 seeds/fruit. The Macspur 'McIntosh' trees at this site, though did
have a significantly greater number of seeds in retained versus abscised fruit.
Retained 'McIntosh' fruit averaged 6.63 seeds while dropped fruit averaged 4.56
seeds. The 'Empire' variety at the MSU Horticulture Farm also had a significant-
ly larger number of seeds in retained (8.28 Seeds/ fruit) versus abscised fruit (6.95
seeds/fruit). Seed number in retained 'Empire' apples was also significantly
greater than in retained 'McIntosh' or 'Delicious' fruit at this site.

At Herman's Orchard where 'Delicious' trees were arranged in a near solid

block design, a significantly greater number of seeds were contained in retained

79

TABLE 4

Percent of flowers becomming fruit on

'Red Delicious' trees
various distances from the pollinizer.*

 

 

Rows from Mean X of flowers
Pollinizer Direction N becoming fruit :.SD
4 Away E 8 .167 : .079a

3 Away E 8 .167 + .761 a

3 Away W 8 .129 j: .037 a

2 Away E 8 .175 i- .023 a

2 Away W 8 .165 i .034 a

1 Away E 8 .163 _-l_- .081 a

1 Away W 8 .136 i .058 a
Next To B 8 -148.i.-042 a
Next To W 8 .179 1;.057 a

 

 

 

 

 

Means followed by the same letter are

not significantly

different at the 5% level as determined by the F-test.

*Pollinizer ='McIntosh'

 

80

TABLE-5

Number of seeds per fruit on 'Rcd Delicious' Trees Various
Distances from the Pollinizer*

 

 

 

Rows from Mean number of seeds
Pollinizer Direction N per fruit :’ SD.
4 Away E 20 4.75 :_1.77a

3 Away E 20 3.70 :1.89a

3 Away W 20 3.90 11.86a

2 Away E 20 3.80 : 2.12a

2 Away W 20 4.05 i 1.733

1 Away E 19 4.53 : 2.20a

1 Away W 20 4.90 i 2.173
Next to E 19 6.89 :.3-201’
Next to W 20 5.30 : 2.62a

 

 

 

 

 

Means followed by the same letter are not significantly
different at the 5% level as determined by Tukey's W method.

81

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82

(5.69 seeds/fruit) as opposed to dropped fruit (3.59 seeds/fruit) (Table 6).
'McIntosh' trees at this site though, did not have significantly more seeds in
retained fruit. Apples held on 'McIntosh' trees averaged 8.78 seeds/fruit while
dropped fruit averaged 7.91 seeds. At this site, 'McIntosh' fruit had a
significantly greater number of seeds in both retained and abscised fruit
compared to the number of seeds in retained 'Delicious' fruit.

At Stanek and Sons' orchard, 'Delicious' fruit retained on the trees did not
have a significantly greater number of seeds per fruit than those that were
abscised (Table 6). Retained fruit averaged 7.09 seeds while abscised fruit
averaged 5.84 seeds. 'McIntosh' fruit at this site also did not differ significantly
in the number of seeds in retained versus dropped fruit (7.63 seeds/fruit and 7.28
seeds/fruit respectively). In this orchard no significant differences in seed
number existed between retained 'Delicious' and 'McIntosh' fruit.

At Ashby's orchard seed number in retained 'Delicious' fruit did not differ
significantly from fruit that was dropped. 'Delicious' apples on the tree averaged
5.78 seeds/fruit while those abscised averaged 5.88 seeds/fruit. Retained Empire
fruit also did not differ significantly in seed number from those that were
abscised. Retained 'Empire' apples contained 8.00 seeds/fruit while those
abscised contained 7.97 seeds/fruit. At this site 'Empire' fruit, both retained on
the tree and abscised, had significantly more seeds than 'Delicious' apples held on

the trees.

DISCUSSION
The system flow diagram used to define the interactions leading to cross

pollination and fruit set is shown in Figure 29. Weather factors (temperature,

83

 

 

 

 

 

 

 

 

 

 

WEATHER
v V
Number Foraging
at Apple Population
Flowers

 

 

 

 

V

 

Colony
‘ Conditions

 

 

 

 

 

 

V V

 

Foragers on Apple

 

 

 

V

 

 

Within Hive

\

 

 

Competitive Plants

 

 

 

 

 

 

l

—:
I

 

7

 

 

Orchard
Design

 

 

Pollen Transler ‘

 

.l

 

Pollinator Population

 

 

 

l

V

A

#L
'

 

 

Wandering

 

 

 

A

 

 

Available Nectar

 

 

 

 

 

L

 

 

Visits

 

Cross Pollinating

 

 

 

[:tigma Receptivity

 

 

 

V

 

 

4 Pollen Tube Growth

 

 

Figure 29.

Age of Flowers

 

 

 

1

 

Fertilization

 

 

 

 

 

lvaule Receptivity

fruit set model for 'Delicious' apples.

 

 

Fruit Set

 

Flow diagram of the components considered in the pollination and

 

84

wind, solar radiation, and rain) are perceived to be the major stimuli to the
system because they influence the size of the foraging population, colony
conditions, number and quality of blossoms, and nectar availability. Although
the state of the bloom affects the size of the foraging population on apple which
ultimately influences the rate of fruit set, this is actually a secondary response.
The size of the foraging population is first related to weather conditions; the
portion foraging apple is then a function of state of bloom.

Although regression equations indicated that there was a high degree of
correlation between weather (temperature, wind, and solar radiation), bloom
state, and honey bee foraging on apple, the low predictive capabilities of the
equations implied that the relationship among these variables is neither additive
nor linear. The foraging response to weather and bloom variables was indeed
multiplicative, and only one response curve (wind) was fOtmd to have a linear
relationship with flight activity.

Several authors have found that the relationship between flight activity
and solar radiation just before, during, and immediately after the sun's zenith
could not be explained using the response equations derived from other hours of
the day (Lundie 1925, Wellington 1957, Frisch 1965 cited by Burrill and Dietz
1981, Gary 1975, and Burrill and Dietz 1981). Our attempts at defining the
foraging response to solar radiation when the aim is at its zenith also indicated
that the response was more random and indeed less predictable during this period
(probably from difficulty in honey bee orientation to the sun at this time) even
when temperature, wind, and state of bloom were considered.

In the program, the progression of bloom and rate of blossom aging are

predicted using accumulated degree days. An analysis of field data indicated

85

that the degree day base for Macspur 'McIntosh' was lower than 'Delicious'. This
could explain why 'McIntosh' always blooms before 'Delicious'. Whether varieties
blooming after 'Delicious', such as 'Golden Delicious' and 'Northern Spy' have
higher threshold tempertures for the expression of bloom could be the subject of
further studies. Certainly the degree day base for 'Delicious' and 'Macspur'
McIntosh require at least another year of validation and fine tuning, but if the
method used to predict base temperature for 'McIntosh' and 'Delicious' is indeed
valid, it could be used to define bloom threshold temperatures for other
varieties.

While collecting data to define the progression of bloom, areas of future
model sensitivity became apparent. Currently there is no incorporation of the
effects of wind and rain on petal retention and attractiveness of bloom.
Blossoms have reduced petal retention as they age (and probably after being
cross pollinated), and petal fall can be expediated by strong rains or high winds.
Because honey bees rely upon petals for direction to the nectaries, the bloom
may lose its attractiveness prematurely under these conditions. If blossoms
depetaled by wind or rain cease to be attractive and rewarding then the
influence of these weather factors on the size of the apple forager population
will have to be considered.

Predictions on the size of the apple foraging population are based upon
three factors: 1) the number of colonies introduced/hectare, Z) the state of the
apple bloom, and 3) the weather. Field data indicated that apple bloom is fairly
attractive even during king bloom, and by peak bloom may attract almost 50% of
the foraging population. The foraging population response to state of bloom was

different though for 'Delicious' and 'McIntosh'. This may have occurred because

86

these varieties were planted near each other, and had overlapping bloom periods
which may have caused their foraging populations to interact. 'McIntosh' blooms
before 'Delicious', and prior to its peak bloom was always more attractive than
the 'Delicious'. Conversely, after the 'McIntosh' peak bloom the foraging
population began to decline earlier than in 'Delicious', because at that time the
'Delicious' trees had more blossoms and were possibly attracting bees from the
'McIntosh'. Hence foraging activity on 'McIntosh' after peak bloom declined
more rapidly than on the 'Delicious'. Consequently, separate curves for each
variety were required to describe the foraging response to state of bloom.

From the onset of the model's development, the source of honey bees
foraging apple and carrying compatible pollen (that could hence initiate fruit set)
was seen to be a pivotal point in making accurate fruit set predictions. Results
from field data indicated that distance from the pollinizer had no effect on the
percentage of 'Delicious' flowers that set fruit in the years and orchards in which
this study was conducted (Table 4). If competition for nectar existed, and
prompted honey bees to leave a tree and visit another, the nearest tree would
most likely be the next one foraged. Observations of honey bees working apple
blossoms showed that a majority of bees that left a tree visited others in the
same row, and crossing between rows was an infrequent event, especially in
orchards with standard size trees (Free 1960). This behavior should have resulted
in a decrease in fruit set with distance from the pollinizer, as previously
reported to sometimes occur in fruit trees (Williams 1959, Free 1962, Spencer-
Booth 1964b), but our field data did not support this hypothesis. Furthermore,
honey bees foraging 'Delicious' and 'McIntosh' trees were found to be carrying

pollen from varieties and species that on some occasions was located several

87

hundred meters away from where the honey bee was captured. Honey bees
probably would not show a caloric profit with foraging areas as large as indicated
by the pollen types on their bodies, and a single tree probably has enough nectar
to satiate many bees. Still every forager examined in our experiment was
carrying several types of pollen, which makes the idea of pollen acquisition in
the hive appear to be a possible explanation.

If in hive pollen transfer is creating a large part of the pollinator
population, orchard design and choice of pollinizer variety could have a profound
influence on the fruit set rate. If the pollinizer variety blooms after 'Delicious'
and colonies are introduced when the 'Delicious' first blooms, the majority of
apple pollen in the hive would be 'Delicious'. Consequently, pollinizer pollen
could be significantly diluted throughout the period prior to 'Delicious' peak
bloom, and hence reduce the effectiveness of the pollinator population in terms
of their ability to cross pollinate 'Delicious' king blossoms with pollen acquired in
the hive. Whether blossoms can still set fruit if their stigmata are first coated
with self-or non-apple pollen and then later cross pollinated is a question that
requires further experimentation.

The ratio of pollinizer to 'Delicious' trees could also influence the
pollinator pOpulation created by in-hive pollen transfer. If 'Delicious' trees are
planted in near solid block arrangements and pollinizer trees are greatly
outnumbered, compatible pollen could be diluted and again possibly reduce the
effectiveness of the pollinator population. On the other hand solid block
arrangements of 'Delicious' could possibly produce good fruit set if a pollinizer
block (that blooms before 'Delicious') is located nearby, and has honey bee

colonies located within it.

88

The effectiveness of in hive pollen transfer may have other constraints in
addition to the ratio of pollinizer/‘Delicious' trees. It is possible that a certain
foraging population level must be obtained in a colony before sufficient contact
among nest mates occurs prompting an effective mixing of pollen. A minimum
time of uninterrupted foraging may also be necessary to achieve maximum pollen
exchange between nest mates. Finally, the distribution of the foraging
population on apple and competitive plant species undoubtedly influences the
effectiveness of in hive pollen transfer in the creation of a pollinator population.
If a majority of foragers are working competitive plants, this type of pollen
would predominate in the hive and possibly on the body's of apple foragers. This
could explain cases where some apple stigmata examined in this study had
relatively high percentages of yellow rocket and other competitive plant pollens.

The influence of available compatible pollen on fruit set and retention
could possibly explain the differences in seed number on retained and abscised
fruit at the various orchard sites. When 'Delicious' or 'McIntosh' trees were
planted in solid blocks ('McIntosh' at the MSU Horticulture Farm and 'Delicious'
at Herman's), there were significantly fewer seeds in fruit abscised during 'June
drop' than in those retained on the tree. Trees planted with an excess of
unrelated varieties nearby did not show this difference ('Delicious' and
'McIntosh' at the MSU Horticulture Farm and Stanek and Sons' Orchards). The
only exception was in 'Empire' trees at the MSU Horticulture Farm which
contained significantly fewer seeds in abscised versus retained fruit, although
they were not planted in solid block arrangements. This difference in seed
number was not repeated in the 'Empire' trees at Ashby's orchard though.

If compatible pollen is limited or greatly diluted, seed number may become

a significant constraint on fruit retention. It is possible that if sufficient

89

amounts of compatible pollen exists, and seed number among fruits is essentially
equivalent, other factors (spur location and vigor, degree of apical dominance in
the variety, fruiting the previous year, fruit to leaf ratio etc.) may have a
stronger influence on fruit retention. On the other hand, if compatible pollen is
limited and fruits differ significantly in their seed‘number, this factor may have
an influence on fruit retention.

Field data indicated that the transfer of compatible pollen was 'really not a
constraint on fruit set in the years and orchards in which this study was
conducted. If this is true, flower quality (in terms of a blossom's probability of
setting fruit if cross pollinated) may be the most important limiting factor in
fruit set. Currently flower quality (in terms of number of of receptive ovules) is
expressed as a function of time of opening in the bloom period and accumulated
degree days since anthesis. Updates on ovule receptivity are based on the
findings of Hartman and Howlett (1954) concerning ovule degeneration with
time, although their study did not specifically relate ovule receptivity with the
degree day interval when blossoms opened, blossom age in degree days, or
flowering spur position on the branch.

Additional experiments will be needed to validate the rate of ovule
degeneration with accumulated degree days for both 'Delicious' and pollinizer
varieties, but to truely define the state of flower quality, additional parameters
may be needed in the model. For example, ovule longevity has been associated
with tree vigor and available nutrients, but the model does not yet have
sensitivity to these factors (Williams 1965). Currently blossom viability,
determined by samples taken at I'tight cluster" stage, is the only factor

concerning flower quality considered in the model that is specific to a site.

90

Because results of our experiments indicated that the pollinator population (i.e.
honey bees carrying compatible pollen) can be quite large, and may not be the
severe constraint on fruit set as once supposed, incorporation of parameters that
can more accurately update blossom quality will certainly be a high priority area

of future research and model elaboration.

LITERATURE CITED

Anonymous. 1978. Delicious problem is growing. Amer. Fruit Grower 98(2):15,
29, 32.

Brittain, W. H. 1933. Apple pollination studies in the Annapolis Valley, N. S.
Canada. 1928-1932. Bull. Dept. Agric. Can. New Ser. No. 162.

Burrill, R. M. and A. Dietz. 1981. The response of honey bees to variations in
solar radiation and temperaturue. Apidologie 12: 319-328.

Butler, C. G. 1944. The influence of various physical and biological factors of
the environment on honeybee activity. An examination of the relationships
between activity and nectar concentraton and abundance. J. Exp. Biol.
21:5-12.

Dennis, F. G. 1979. Factors affecting yield in apple with emphasis on
'Delicious.‘ p. 395-422. In J. Janick (ed.) Horticultural review AVI.
Westport, Conn.

Detjen, L. R. 1929. The effects of nitrogen on the set of apple flowers situated
variously on the cluster base. Proc. Amer. Soc. Hort. Sci. 25:153-157.

Erickson, E. H., G. D. Waller, and L. O. Whitefoot. 1975. A modified trap design
for sampling pollen and incoming flight at the entrance of colonies of
honey bees. Amer. Bee J. 115:224-225,234.

Faegri, K., and J. Iversen. Textbook of Pollen Analysis. Hafner Publishing Co.
New York, 1964.

Fogle, H. W. 1977. Identification of clones within four tree fruit species by
pollen exine patterns. J. Amer. Soc. Hort. Sci. 102:552-560

. 1977. Identification of tree fruit species by pollen ultrastructure. J. Amer.
Soc Hort. Sci. 102: 548-551

Free, J. B. 1960. The pollination of fruit trees. Bee World. 41(6):l4l-151;(7):
169-186

. 1962. The effect of distance from the pollinizer varieties on the fruit set
on trees in plum and apple orchards. J. Hort. Sci. 37: 262-271.

. 1964. The effect of distance from pollinizer varieties on the fruit set of
apple, pear and sweet cherry trees. J. Hort. Sci. 39:54-60.

. 1966. The foraging areas of honey bees in an orchard of standard apple

91

92

and Y. Spencer-Booth. 1964a. The foraging behavior of honey bees in an
orchard of dwarf apple trees. J. Hort. Sci. 39:78-83.

, Y. Spencer-Booth. 1964b. The effect of distance from the pollinizer
varieties on the fruit set of apple, pear and sweet cherry trees. J. Hort.
Sci. 39:54-60.

Frisch, K. von 1965. Tanzsprache and Orientierung der Bienen. Berlin-
Heidelberg, Springer Verlag.

Gary, N. E. 1975 Activities and Behavior of Honey Bees. Chapter VII. The Hive
and the Honey Bee. Dadant and Sons Inc. Hamilton, 111. p.185

Hartman, F. O. and F. S. Howlett. 1954. Fruit setting of the Delicious apple.
Ohio Agric. Exp. Sta. Bul. 745. 64 pp.

Heinrich, B. and P. H. Raven. 1972. Energetics and pollination ecology. Science.
176(4035):597-602.

Howlett, F. S. 1928. Fruit setting in the Delicious apple. Proc. Amer. Soc.

. 1932. Partial defloration in relation to Delicious fruit setting. Ohio Agric.
Exp. Sta. Bul. 745. 64 pp.

J orgensen, C. and F. Markham 1946. Weather factors influences honey produc-
tion. MSU Agric. Exp. Sta. Special Bull. No. 340 22pp.

Karmo, E. A. and V. R. Vickery. 1954. The place of honey bees in orchard
pollination. Mimeogr. Circ. Nova Scotia Dep Agric. Mktg., No. 67.

Kendall, P. A. 1973. The viability and compatability of pollen on insects
visiting apple blossoms. Appl: Ecol. 10: 847-853.

, and Solomen, M. E. 1973. Quantities of pollen on the bodies of insects
visiting apple blossom. J. Appl. Ecol. 10: 627-634.

Lundie, A. E. 1925. The flight activities of the honey bee. U.S.Dept. of Agric.,
Bull. No. 1328.

MacDaniels, L. H. 1931. Further experience with the pollination problem. Proc.
N. Y. St. Hort. Soc. 76:32-37.

McGregor, S. E. 1976. Insect pollination of cultivated crop plants U.S.D.A.
Agric. Handbook No. 496:80-88.

Martin, E. C. 1972. Pollination of fruit crops. Dept. of But. Mich. State Univ.,
East Lansing, MI 48824-1115.

Ribbands, C. R. 1955. The scent perception of the honey bee. Proc. Roy. Soc.
B. 143 :.367-379

93

Rashad, S. E. 1957. Some factors effecting pollen collection by honey bees and
pollen as a limiting factor in brood rearing and honey production. Ph.D.
thesis, Kansas State College.

Roberts, R. H. 1945a. Blossom structure and setting of Delicious and other
apple varieties. Proc. Amer. Soc. Hort. Sci. 46:87-90.

_. 1945b. Bee pollination of Delicious. Amer. Fruit Grower. 65(4):16.

. 1947. Notes on the setting of Delicious, 1946. Proc. Amer. Soc. Hort. Sci.
50:85-94.

Robinson, W. S. 1979. Effect of apple cultivar on foraging behavior and pollen
transfer by honey bees. J. Amer. Soc. Hort. Sci. 104(5):596-598.

Szabo, T. I. 1980. Effects of weather factors on honey bee flight activity and
colony weight gain. J. Apic. Res. 19:164-171.

Wellington, W. G. 1957. The synoptic approach to studies of insects and
climate. Annu. Rev. of Entomol. 2:143:162.

Williams, R. R. 1959. The effective distance of a pollen source in a cider apple
orchard. Rep. Long Ashton Res. Stat. for 1958. 61-64.

. 1965. The effect of summer nitrogen application on the quailty of apple
blossom. J. Hort. Sci. 40:31-41.

, and F. P. Sims. 1977. The importance of weather and variability in

flowering time when deciding pollination scheme for Cox's Orange Pippin.

IDENTIFYING FACTORS THAT INFLUENCE FRUIT SET IN

'DELICIOUS' APPLES USING REDAPOL SIMULATIONS

94

INTRODUCTION

As simulation modeling has advanced the study of plant-pest relationships,
so it can increase the understanding of plant-pollinator relationships which
culminate in fruit set. A systems approach could predict fruit set by combining
predictions on cross pollination rates with updates on flower quality (in terms of
probability of setting fruit if cross pollinated). In addition to their use by
growers, fruit set models are excellent research tools because they allow
experimentation on fruit set parameter combinations that would be difficult or
costly to duplicate in the field. Furthermore, variation from site to site or year
to year that exists in field results could be eliminated using simulation models.
With this in mind, a pollination and fruit set model (REDAPOL) was constructed
for 'Delicious' apples.

In the 'Delicious' fruit set system, several parameters were suspected to
strongly influence fruit set predictions. Orchard design, in terms of the ratio,
size, and arrangement of 'Delicious' and pollinizer trees, was one such para-
meter. If availability of compatible pollen is limited because 'Delicious'
blossoms far outnumber those of the pollinizer, fruit set may be limited even if
flight weather is good and blossom quality is high. It is possible under these
circumstances that compatible pollen becomes so diluted that its presence on the
stigma is either rare or at so low a level, it is ineffective in setting fruit. To
test this assumption in the field, several different orchard designs would be
needed. However, even after statistical analysis the results would reflect some
conditions existing at a site that would be difficult to standardize (tree vigor,

previous fruiting history, tree age, rootstock, soil type, irrigation practices and

95

96

size of the honey bee population), so that the influence of orchard design alone
would be difficult to assess. This problem could be eliminated by analyzing
orchard designs using REDAPOL.

Another variable that most likely influences fruit set is the number of
honey bee colonies introduced per hectare. The ideal colony number is
undoubtedly specific for a particular orchard design and set of weather condi-
tions. Consequently, a blanket recommendation for the number of colonies
required per hectare to insure a commercial fruit set is not possible because the
number is not a constant, but a variable. Predictions on fruit set rates under
different colony/hectare densities, could be made for various orchard designs,
and weather conditions using REDAPOL, and hence direct colony rental deci-
sions.

In addition to predicting the number of colonies required for a commercial
fruit set, the time during bloom when honey bee colonies should be removed
could also be predicted with a pollination and fruit set model. If a fruit set goal,
based on blossom density is established at the beginning of the simulation, daily
fruit set predictions could report when that goal has been achieved. This could
prevent overset and the need for thinning sprays.

The conditions under which honey bees acquire compatible pollen and
initiate fruit set can possibly be defined using a pollination and fruit set model.
Currently there are two hypotheses used to explain a honey bee's acquisition of
compatible pollen. The first involves competition for nectar which forces some
bees to move from (tree to tree to acquire a full nectar load (Butler 1944). If the
honey bee happens to move from a pollinizer to a 'Delicious' tree, she will cross

pollinate blossoms. This hypothesis can be tested with REDAPOL because

97

competition for nectar and honey bee movement can be simulated, and hence the
size of the resulting pollinator population (i.e., honeybees carrying compatible
pollen) can be estimated along with its contribution to fruit set.

Another possible source of pollinators could be from contact among nest
mates in the hive, which results in the transfer of compatible pollen (Karmo and
Vickery 1954). Although not much is known about the constraints on "in hive
pollen transfer," some reasonable assumptions can be made in order to construct
a simulation of this event. For instance, the percentage of the total foraging
population leaving the hive the previous hour undoubtedly affects the quantity of
pollen coming into the hive and thelprobability of pollen exchange between nest
mates. The percentage of the foraging force on 'Delicious,‘ pollinizer, and
competitive plants probably also influences the size of the pollinator population
arising from in-hive pollen transfer, because it dictates the percentage of pollen
types entering the hive. REDAPOL simulations could help define the size on the
pollinator population arising from in-hive pollen transfer, and evaluate its
contribution to fruit set.

Flower quality, in terms of ovule receptivity, may also influence the rate
of fruit set during bloom. After anthesis, 'Delicious' blossoms have a probability
of setting fruit that decreases continuously as the open blossom ages. Hartman
and Howlett (1954) reported a linear decrease in fruit set if pollination was
delayed from 1 to 48 hours after anthesis, with the lowest values at 72 hours and
thereafter. Although previous reports on ovule degeneration have been ex-
pressed in chronological time, accumulated degree days may indeed be a better
parameter on which to predict a blossom's fruit set potential. The influence of

temperature on flowering is self-evident in its effects on bloom length. Apple

98

bloom can last up to 14 days if the weather is cool, but can be reduced to 5-7
days if temperatures are high. Decreasing probabilities of fruit set with blossom
aging can be simulated using REDAPOL, and hence be used to evaluate flower
quality's influence on the fruit set rate.

REDAPOL was developed because fruit set models can serve as both
research tools and integral parts of overall crop management programs. Simula-
tions were run using REDAPOL to test the influence of orchard design, weather,
colonies/hectare, flower viability, and rate of blossom aging on the fruit set
rate. The source of the honey bee population responsible for cross pollination
(i.e., movement from tree to tree or in-hive pollen transfer) was also examined

using simulations.

MATERIALS AND METHODS

Initialization of Orchard Parameters

 

In the model's initialization subroutine, various orchard characteristics are
required to set the stage for fruit set predictions. They include orchard size,
tree height, width, trunk height (from ground to first main limb), and number of
flowering spurs per meter of branch. The average number of blossoms per tree
and the ideal fruit set percentage (fruit/blossom* 100%) is then calculated from
this information. Additional input is required about the arrangement of
'Delicious' and pollinizer rows so that the orchard design's influence on fruit set
can be analyzed. Required input for this includes the distance between trees in a
row and between rows, the number of rows in the 'Delicious'/pollinizer pattern,
the number of solid 'Delicious' rows in the pattern, and the percentage of

pollinizer trees in the rows containing pollinizers. The user is also asked to

99

sample the orchard for the percentage of viable blossoms in each variety.
Finally, the first day of bloom and the number of colonies that will be introduced
(and their date and time of introduction) must be specified.

The same orchard design and parameters were used in simulations to test
the effects of weather, tree size, flower quality, colony/hectare density, and
source of the pollinator pOpulation on fruit set. The orchard was composed of
'Delicious' trees (4.0m high, 2.5m wide with 0.5m of trunk) and 'McIntosh'
pollinizer (5.0m high, 3.0m wide, with 0.5m of trtmk) arranged in a pattern where
three rows of 'Delicious' were followed by three rows of 'McIntosh.‘ Trees were
spaced 6.1m apart between rows and 4.6m apart within a row. 'Delicious' trees
averaged 25 flowering spurs/m of branch while 'McIntosh' averaged 30. Flower
viability at anthesis averaged 90% for both varieties. Unless otherwise noted,
colonies were introduced at a density of 2.5/hectare (l colony/ acre).
Construction of Weather Tapes

When REDAPOL is used for predictions of actual fruit set rates, weather is
input from data collected by a Campbell Instrument CR-21 micrologger.*
Temperature, relative humidity, wind speed, and solar radiation sensors are
required. For the purpose of simulating the influence of various weather
scenarios on fruit set though, weather tapes were assembled so that they would
contain specific conditions. The tapes were constructed by inputting a single
day's weather and then duplicating it (unless otherwise specified) for the entire
bloom period.

In order to compare differences in fruit set rates when weather conditions
deviate from the optimum, an 'ideal flight weather' tape was constructed. This

tape contains eleven hours of optimum flight weather each day during bloom

*Campbell Scientific Inc., P.O. Box 551, Logan, Utah 84321.

100

(800-1900 hrs.) with temperatures ranging between 210-3100, calm winds, and no
cloud cover. The 'good flight weather' tape contains conditions that will cause a
reduced level of foraging compared to the tape of 'ideal flight weather.‘ The
'good flight weather' tape contains daylight temperatures between 10°-16°c,
winds between 21-26 km/hr, and slightly overcast skies (i.e., solar radiation
values between 19-30 microamps/ 1000 watts/m-Z).

To examine the influence of rain and interruptions in flight, weather tapes
were constructed which contain periodic rain storms. Under the conditions of a
tape named 'warm rain,‘ each day has only three hours of flight weather which
occur between 1200-1400 hrs. During the day temperatures range between 9°-
31°C with the highest temperatures occurring during the flight interval. Wind
speeds during the non-rain period range between 11-14 km/hr, and the skies are
almost clear (i.e., solar radiation values are between 27-39 microamps/1000
watts/m-Z).

Finally, a tape was constructed to examine the amount of fruit that would
set if flight weather was restricted (due to rain) to one day during bloom.
Several of these tapes were assembled differing only in the day during bloom
when flight weather occurs. On the day of flight, ideal conditions were
programmed to exist, while on the rainy days temperatures were set high enough
so the bloom would continue to age (i.e., temperatures are always higher than
5°C) even though flight weather did not exist. With this tape, the maximum
amount of fruit that can be set on a single day during bloom could be discerned.

Assumptions and Framework of the Model

 

REDAPOL‘s fruit set predictions are based upon updates on the honey bee

population in a potential cross-pollinating state, and blossoms whose age and

101

probabilities of fruit set have likewise been updated. REDAPOL was designed to
rim on two discrete time systems: physiological (accumulated degree day; DD)
and chronological time. State of bloom, forager population size, number of
cross-pollinating visits and accumulated fruit set are updated hourly. The actual
number of open blossoms and their probabilities of fruit set if cross pollinated
are updated using state equations which have accumulated degree days as their
time element. Based upon field data, the threshold temperature for the
progression of 'Delicious' bloom is 5°C while for 'McIntosh' it is 1°C.

In REDAPOL the probabilities of cross pollination leading to fruit set are
updated in two dimensions. The first involves the blossoms period of opening
during bloom (i.e., king blossom, early lateral, later laterals). The second
addresses the number of degree days that have accumulated since the blossom's
day of anthesis. Based upon reports that king bloom is composed of the highest
quality blossoms, and laterals have a relatively lower potential fruit set
especially if the king blossom sets fruit (Detjen 1929); the probabilities of fruit
set on the day of anthesis are greatest for king blossoms. The probability of
cross pollination leading to fruit set then declines as the number of accumulated
degree days since anthesis increases. This is based on reports of reduced fruit
set rates in blossoms where cross pollination is delayed for 48 hrs or more after
anthesis (Hartman and Howlett 1954). Based on these assumptions then, the fruit
set rate is always highest during the early part of bloom.

Another group of assumptions used in the construction of REDAPOL
relates to the source of honey bees with cross pollinating potential (pollinators).
In the model, pollinators occur from two sets of conditions. The first involves

competition for nectar, which forces honey bees to move from tree to tree to

102

acquire a full nectar load (Butler 1944). If movement occurs between trees of
unrelated varieties, cross pollination is predicted to occur. REDAPOL is
programmed so that the direction honey bees move when leaving a tree is a
function of distance to the next tree. As distance between trees increases, the
probability of a honey bee moving that distance decreases. This assumption is
based on the conservative nature of honey bee movement in apple orchards.
Honey bees have been reported to generally remain on the same tree for much, if
not all, of a foraging trip, and when movement occurs, it is most likely to the
next tree in a row. Movement between rows is a less frequent event in both
standard and dwarf tree plantings (Free and Spencer-Booth 1964 a,b; Free 1966).
An additional means of acquiring compatible pollen is through its transfer
among honey bees in the hive (Karmo and Vickery 1954). Our field data has
indicated in-hive pollen transfer may indeed be making a large contribution to
the pollinator population. This conclusion was drawn from data which indicated
that honey bees were working apple blossoms while carrying pollen from several
apple varieties (and in some cases, other plant species). Although constraints on
this pollinator source have not been documented in the field, in order to simulate
in-hive pollen transfer and predict its contribution to fruit set, the following
relationships were assumed:
I) In-hive pollen transfer increases logarithmically with the size of the
foraging population.
2) In-hive transfer of viable pollen does not occur unless there is at least
two hours of continuous flight.
3) Apple foragers (and perhaps foragers of other plant species) can leave
the hive with enough compatible pollen to cross-pollinate a varying

percentage of blossoms.

103

4) The number of blossoms an apple forager can cross-pollinate with in-
hive pollen is lower during the hours of peak pollen dehiscence (900-
1300 hrs) than at other times of the day.

5) Pollen in the hive loses its viability overnight.

When the number of cross pollinating visits from tree to tree movement
and in-hive pollen transfer are totaled for the hour, the visits are distributed to
open blossoms. Estimates of fruit set are then made by multiplying the
probability of fruit set for each blossom age group by the number of blossoms in
that group that have received across pollinating visit. Because pollen grains
must germinate and grow down the style before fertilization can occur, a delay
of 30 DD5 for 'Delicious' and 40 DDl for 'McIntosh' is assumed between cross
pollination and fruit set (i.e., fertilization is assumed to occur 48 hrs after cross
pollination if temperatures average 21°C). Consequently, the number of
receptive ovules that exist at the time when pollen tubes have entered the ovary
is the point from which fruit set probabilities are calculated. It is assumed that

an ovary must have at least 4 fertilized ovules (i.e., seeds) to set a fruit of

desirable size.

RESULTS

The Influence of Orchard Design of Fruit Set
In this analysis two general types of orchard designs were examined for
their influence on fruit set. The first is a pattern where one pollinizer row is
separated from the next by several rows of 'Delicious.‘ Plantings in our analysis
ranged from alternating pollinizer and 'Delicious' rows, to a pollinizer row

followed by five rows of 'Delicious.‘ In these plantings, average 'Delicious' fruit

104

set decreased as the number of trees between two pollinizer rows increased
(Table l).

Forty-three percent of the 'Delicious' blossoms set fruit by the end of
bloom for an every other row 'Delicious'/pollinizer arrangement, while 22.9%
fruit set was predicted for a one pollinizer/five 'Delicious' arrangement. These
fruit set predictions are based upon 'ideal flight weather' in an orchard of semi-
dwarf trees (2.44m 'Delicious' and 3.05m 'McIntosh'). Based upon blossom density
on the 'Delicious' trees, the ideal commercial fruit set goal of 14.8% (i.e., 14.8%
of the blossoms should set fruit) was met during the second day of bloom in all of
these plantings under the described conditions.

A second set of orchard designs contained variations of a one-to-one ratio
of 'Delicious' and pollinizer trees. Comparisons were made between plantings of
alternate rows of both varieties, and increasingly larger blocks of 'Delicious' and
pollinizer trees still at a one-to-one ratio. Fruit set did not decrease signifi-
cantly under 'ideal flight weather' conditions as blocks of 'Delicious' increased
(50.01-47.2%, Table 1), and the 'Delicious' fruit set goal (14.8%) was met in all
cases on the second day of 'Delicious' bloom.

In contrast, 'McIntosh' set was considerably lower than the 'Delicious' when
planted in a one-to-one ratio no matter what the pattern. 'McIntosh' fruit set
increased though, as the ratio of 'Delicious' to 'McIntosh' increased. When
'McIntosh' trees were outnumbered by 'Delicious,‘ 'McIntosh' trees were predicted
to overset and would have required thinning.

The Influence of the 'Wandering Honey Bee' Population on Fruit Set
In the version of REDAPOL used in these simulations, the fruit set by

honey bees moving from pollinizer to 'Delicious' trees was recorded separately

 

105

Table l

The influence of orchard design on fruit set. *

 

 

Petal Fall Fruit Set Fruit Set Relative to Alternate
(Fruit /Blossom * 100) Row Planting (Fruit Set/Alternate
Row Fruit Set) * 100
Orchard Design 'Delicious' 'McIntosh' 'Delicious' 'McIntosh'
xxx
oxo 13.9 51.3 27.8 766
xxx
xoxo 50.0 6.7 100 100
xxxo 25.6 20.6 51.2 308
xxxxo 26.2 34.9 52.4 521
xxxxxo 22.9 42.2 45.8 630
xxoo 48.4 6.8 96.8 101
xxxooo 47.9 6.9 95.8 103
xxxxoooo 47.7 6.9 95.4 103
xxxxxooooo 47.5 6.9 95.0 103
xxxxxxoooooo 47.4 6.9 94.8 103
xxxxxxxooooooo 47.2 6.9 94.4 103

 

 

 

* Constant parameters in the Simulations
Tree Size: Semi-dwarf
Colony Density: 2.5 colonies/hectare
Weather Tape: Ideal flight weather
x = 'Delicious'
0 = 'McIntosh'

 

106

from cross pollinations resulting from compatible pollen acquired in the hive.
Honey bees were predicted to move from a tree if they repeatedly encountered
empty (i.e., nectarless) blossoms. The probability of moving to an tmrelated tree
was then predicted to be a function of the distance to the unrelated tree versus
the distance to the next tree in the same row. In all simulations, trees in the
same row were always closer than trees in adjacent rows. The "wandering honey

bee population was updated hourly in the program when flight conditions
existed, and essentially its size depended on available rewarding blossoms and
the size of the foraging population.

In all orchard designs tested in these simulations the fruit set contribution
of wandering honey bees was found to be extremely small (i.e., less than 1%)
(Table 2). When RDA trees were planted in equal numbers with the pollinizer,
total fruit set ranged between 47.21%-50.01% (i.e., percentage of flowers that
set fruit if colonies remained in the orchard until petal fall) (Table 2). In these
arrangements, only about 0.01% of the total fruit set was predicted to result
from honey bee movement from tree to tree. 'Delicious' fruit set by wandering
bees increased when pollinizer rows were spaced between two, three, or four
rows of 'Delicious,‘ or if pollinizers were interplanted in 'Delicious' rows. The
range of fruit set percentages resulting from these simulations represented rows
closest to (high value) and furthest from (low value) the pollinizer.

In addition, there was limited fruit set contribution by wandering honey
bees on the pollinizer trees. The highest amOtmt of fruit set by wanderers
occurred when pollinizers were planted as every third tree in every third

'Delicious' row. This planting also resulted in the largest pollinizer total fruiting

percentage when compared to all other tree arrangements.

107

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In these simulations the difference between petal fall fruit set by wand-
erers and total petal fall fruit set was due to cross pollinations by honey bees
that acquired compatible pollen in the hive. This source of pollinators was
responsible for the majority of cross pollinations, especially in orchard designs
that simulated solid block plantings. When 'McIntosh' rows were input between
rows of 'Delicious,’ the fruit set contribution by wanderers increased but was still
quite small in relation to total petal fall fruit set (Table 2).

The Influence of Tree Size on Fruit Set

 

It has been reported that dwarf and semi-dwarf apple plantings out-produce
orchards with standard trees, because smaller trees have more fruiting wood per
hectare (McGregor 1976, Westwood 1978). The model was tested for this
behavior by inputting trees with standard, semi-dwarf, and dwarf dimensions.
Weather ('ideal flight weather' conditions), blossom density per meter of branch,
and colonies/hectare were identical for all simulations. Based upon tree size and
spacings in the simulations, there were 363 standard trees, 1725 semi-dwarfs,
and 2435 dwarf trees per hectare.

Results of the simulations showed that the model did predict that dwarf
trees out produce both standard and semi-dwarf plantings (Table 3). The highest
'Delicious' and 'McIntosh' fruit set rate (fruit/blossom) occurred in the orchard of
standard trees, even though less fruit was produced (compared to the dwarf
plantings). Fruit set in 'McIntosh' did not increase, as it did in the case of
'Delicious,‘ when semi-dwarf trees were substituted for standard. 'McIntosh'
fruit set did increase by 60% though, when simulations were conducted with

'McIntosh' trees on dwarf rootstock.

 

109

Table 3. The influence of tree size on fruit set.

 

 

*
Petal Fall Fruit Set Bushels / Hectare *
(Fruit/Blossom * 100%)
Tree size 'Delicious' 'McIntosh' 'Delicious' 'McIntosh'
Standard 41.9 6.1 1877-2502 ° 402-535
Semi-Dwarf 37.2 3.5 2511-3348 402-536
Dwarf 24.8 5.3 3122—4165 670-895

 

 

 

 

*Constant parameters in the simulation's
Colony Density: 2.5 colonies/hectare
Weather Tape: Ideal flight weather
Orchard Design: xxxooo
x - 'Delicious'
0 8 'McIntosh'

xx
Range of bushels is dependent upon size of apples

110

The Influence of Weather on Fruit Set

 

Final fruit set predictions were compared among orchards that differed
only in weather conditions during bloom. Weather tapes used in this group of
simulations differed greatly from one another in terms of their ability to
promote foraging. Under 'ideal flight weather' conditions, the foraging popula-
tion increased throughout the morning (beginning at 800 hrs) and peaked at 1300
hrs, about 99% of its potential per colony. The foraging population then slowly
decreased until 2000 hrs when foraging stopped because of low light intensity.

Under 'good flight weather' conditions the foraging population also con-
tinued to increase Imtil 1300 hrs, but at a slower rate than under 'ideal flight
weather' conditions. The foraging population peaked (at 1400 hrs) at about 40%
of its potential. Under conditions of 'warm rain,‘ flight was restricted to a three
hour period (1300-1500 hrs) each day. During this time, foraging increased
during the first two hours as the rainstorm dissapated and then decreased to zero
in the third hour as the next rainstorm entered the orchard.

The next set of simulations involved weather tapes that permitted only one
day of flight weather during bloom (continuous rain occurred on all other days).
Six weather tapes were constructed for these tests. The tapes differed only in
the day during 'Delicious' bloom when flight weather occurred. During the day of
flight, weather conditions were programmed to be ideal (i.e., they were identical
to any one day on the 'ideal flight weather' tape) for this activity.

Based upon blossom density of the 'Delicious' and 'McIntosh' trees, the fruit
set goal (i.e., fruit/blossom *100) in all simulations was predicted to be 10.2%
and 8.2% respectively. Under conditions of 'ideal flight weather' and 'warm rain,‘

the 'Delicious' fruit set goal was met at various times during the third day of

111

bloom (approximately 41 DD5 or 53 DD1)' Under 'good flight weather' conditions
the 'Delicious' goal was met on the ninth day of bloom (about 50 DD5 or 86 DDl).
The optimum fruiting percentage was met on 'McIntosh' trees only under 'ideal
flight weather' conditions and then not until the end of bloom (Table 4). As
expected, final fruit set on both varieties was highest under 'ideal flight weather'
conditions. The lowest final fruit set occurred in 'Delicious' under 'warm rain'
conditions, while in 'McIntosh' 'good flight weather' produced the lowest set
(Table 4).

When flight weather was restricted to one day during bloom, the highest
fruit set values were predicted when flight occurred on the sixth day of
'Delicious' bloom. In this group of simulations, final fruit set percentages for
'Delicious' ranged between 0.19% (flight on day-1 of 'Delicious' bloom; about 0-
16DD5) and 15.15% (flight on day -6 of 'Delicious' bloom; about 75-91 DDS)
(Table 4). 'McIntosh' fruit set ranged between 0.02% (flight on day-2 of
'McIntosh' bloom; about 19-37 DDl) and 3.85% (day-7 of 'McIntosh' bloom; about
114-132 DDl) (Table 4).

The Influence of Colony Number and Orchard Design on Fruit Set

Simulations were rim with various 'Delicious' and 'McIntosh' tree arrange-
ments to test if fruit set could be increased by introducing additional colonies.
Results of these simulations are summarized in Table 5. In all cases fruit set in
both varieties was increased by adding more colonies per hectare especially in
the 2.5-10 colonies/hectare range. The fruit set goal for 'Delicious' (10.2%) was
met in all orchard designs prior to petal fall with 2.5 colonies/hectare.
Essentially, the additional colonies were not really necessary then, and the fruit

would have required thinning to achieve good size. The maximum petal fall

112

Table 4

The influence of weather on fruit set

 

 

Petal Fall Fruit Set Percentage

 

Weather Tape (fruit/blossom * 100 )
'Delicious' 'McIntosh'
Ideal flight weather 47.7 8.7
Good flight weather 22.5 3.1
Warm rain 20.9 4.1
Flight on day - 2 0.19 0.02
Flight on day - 3 2.7 0.5
Flight on day - 4 9.3 1.7
Flight on day - 5 15.0 3.1
Flight on day - 6 15.1 3.8
Flight on day - 7 5.4 2.0

 

 

 

*Constant parameters in the shmulations
Colony Density: 2.5 colonies/hectare
Tree size: Semi-Dwarf

Orchard Design: xxxooo
x = 'Delicious' o=='McIntosh'

113

Table 5

The influence of orchard design and colony number on fruit set. *

 

 

 

Petal Fall Fruit Set
Orchard Design colonies/hectare 'Delicious' 'McIntosh'
oooxxx 2.5 22.5 3.1
10.0 25.0 8.3
20.0 25.0 10.5
30.0 25.0 10.9
xxo 2.5 20.5 8.1
10.0 24.3 18.1
20.0 24.4 19.9
30.0 24.4 20.0
xxxo 2.5 18.7 14.1
10.0 22.8 26.6
20.0 22.9 27 7
30.0 22.9 27 8
xxxxo 2.5 17.4 26.3
10.0 21.3 33 5
20.0 21.5 34 2
30.0 21.5 34.2
xxxxxo 2.5 16.3 26.3
10.0 20.1 39.4
20.0 20.2 39.6
30.0 20.2 39.7
W° 2.5 15.4 31.9
10.0 19.0 44.0
20.0 19.0 44.1
30.0 19.0 44.2

 

 

 

 

* Constant parameters in the simulations
Good flight weather

Weather Tape Used:

Tree size: Semi-Dwarf

x = 'Delicious'

0:

'McIntosh‘

 

114

'Delicious' percentages were achieved when trees were planted in a one 'Deli-
cious' to one 'McIntosh' ratio.

In 'McIntosh' trees, the fruit set goal (10%) was not met in orchards with a
one 'Delicious' to one 'McIntosh' tree ratio unless colonies were introduced at a
rate of 20/hectare (Table 5). In an orchard with a two 'Delicious' to one
pollinizer ratio, more than 2.5 colonies/hectare were needed to achieve the fruit
set goal. In all other orchard designs where 'McIntosh' trees were outnumbered by
more than a three-to—one ratio with 'Delicious,‘ the fruit set goal was met prior
to petal fall with colonies introduced at a rate of 2.5/hectare.

As in the case of 'Delicious,’ the greatest 'McIntosh' fruit set gains were
achieved with additional colonies in the interval of 2.5-10/hectare. In McIntosh,
the fruit set percentage increased as the ratio of 'Delicious' to 'McIntosh'
increased. The opposite effect occurred on the 'Delicious' trees (i.e., as the
'Delicious'/‘McIntosh' ratio increased, 'Delicious' fruit set decreased).

The Influence of Flower Viability and Colony Number on Fruit Set

Simulations were conducted to test if fruit set goals could be met in
'Delicious' and 'McIntosh' when flower viability was limited. The results of these
simulations are summarized on Table 6. With flower viability as low as 40% (i.e.,
only 40% of the blossoms had the potential to set fruit), the 'Delicious' fruit set
goal (10.8%) could be reached prior to petal fall with 2.5 colonies/hectare. The
'McIntosh' fruit set goal (10%) could be reached prior to petal fall with 2.5
colonies/hectare only if blossom viability was higher than 80%. 'McIntosh'
required 10 colonies/hectare to reach its fruit set goal of 10% prior to petal fall
when blossom viability was set at 40%.

When only 20% of the 'Delicious' blossoms had the potential to set fruit, 10

colonies/hectare were needed for the fruit set goal to be reached (prior to petal

 

115

Table 6

The influence of blossom viability and colony number on Fruit Set. *

 

'Delicious' and 'McIntosh'
Blossom viability

Colonies/Hectare

Petal Fall Fruit Set

 

 

'Delicious' 'McIntosh'
1002 2.5 19.8% 15.62
80% 2.5 18.42 12.92
60% 2.5 16.5% 10.0%
40% 2.5 13.52 7.02
10.0 18.5% 14.0%
20% 2.5 8.62 3.7%
10.0 13.02 7.92
20.0 13.42 8.32
25.0 13.42 8.3%
15% 2.5 6.72 2.92
10.0 10.72 6.2%
20.0 11.152 6.52
25.0 11.22 6.52

 

 

 

 

* Constant parameters in the simulations

Weather tape used = Good flight weather

Orchard Design - ooox

0 B 'Delicious' x 8 'McIntosh'

 

116

fall) (Table 6). Additional colony introduction up to 25/hectare could not prompt
enough cross pollinations to permit the 'McIntosh' fruit set goal to be reached
though. When blossom viability was set at 15%, 20 colonies/hectare were needed
to reach the 'Delicious' fruit set goal prior to petal fall. With 'McIntosh' blossom
viability set at 15%, again this variety's fruit set goal could not be reached
regardless of the number of colonies introduced per hectare.

The Influence of Flower Quality and Weather on Fruit Set

In the version of REDAPOL used in these simulations, the quality of
flowers, in terms of their probability of fruit set, could be initialized at the
beginning of the rim. An assumption used in the construction of the model was
that blossoms lose their ability to set fruit as they age because of ovule
degeneration. This assumption was based on the findings of Hartman and
Howlett (1954) and their work with flower quality in 'Delicious.' Late developing
blossoms were also predicted to have reduced probabilities of fruit set on their
day of anthesis. For instance, blossoms opening on the first day of bloom ('King
blossoms') were assumed to have a higher probability of fruit set (on their day of
anthesis) than lateral blossoms opening later in the bloom period.

The influence of flower quality on fruit set was tested by simulating
blooms that had decreasing versus constant flower quality. In the first group of
simulations, 'Delicious' and 'McIntosh' blossoms had decreasing probabilities of
fruit set with respect to their age (i.e., accumulated degree days since their day
of anthesis) and period of opening during bloom. A second group of simulations
was then conducted with blossoms having constant fruit set probabilities (0.999)
regardless of their age or period of opening. Comparisons were then made

between the resulting fruit sets under various weather conditions. In these

117

simulations, all other orchard parameters: tree height, width, spacing, flowering

spurs/meter of branch, and colonies/hectare were identical so that any differ-
ences in fruit set could be attributed to flower quality.

Under all weather conditions, final fruit set in both varieties was greater
when flower quality remained constant during bloom (Table 7). Flower quality
did not strongly influence the attainment of the 'Delicious' fruit set goal,
however. Under conditions of constant flower quality, the goal was met on the
same day as when flower quality was decreasing. The only exception was when
'ideal flight weather' conditions were simulated. In this case, the 'Delicious' fruit
set goal occurred a day earlier under conditions of constant flower quality.

Conversely, 'McIntosh' fruit set was strongly influenced by flower quality,
and final fruit set percentages increased greatly when flower quality remained
constant (Table 7). Under all three sets of weather conditions, the 'McIntosh'
fruit set goal could be met prior to petal fall if fruiting probabilities were
constant. When ovule degeneration was simulated using decreasing fruit set
probabilities though, 'McIntosh' fruit set was greatly reduced.

The Influence of Colony Density on Fruit Set Under Various Weather Conditions

Simulations were rim to test if 'Delicious' and 'McIntosh' fruit set rates,
under various weather conditions, could be increased by raising the number of
honey bee colonies per hectare. The results of these simulations are summarized
in Table 8 and Figures 1 and 2. In both 'McIntosh' and 'Delicious,‘ the fruit set
rate was increased most by additional colonies when 'ideal flight weather' existed
for the duration of bloom. The greatest increase in 'Delicious' fruit set occurred
in the interval of 0.62-7.4 colonies/hectare. After this point, additional colonies

did not significantly increase fruit set. At all colony/hectare densities and 'ideal

The influence

118

Table 7

of blossom quality and weather conditions on fruit set. *

 

Weather

Petal fall fruit set
constant fruiting
probabilities

'Delicious' 'McIntosh'

Petal fall fruit set
decreasing fruiting
probabilities

'Delicious' 'McIntosh'

 

Ideal flight
weather

Good flight
weather

Warm flight
weather

65.4 19.6
24.9 10.7
40.4 11.8

 

51.6 6.4
23.2 2.3
23.3 2.9

 

 

 

* Constant parameters in the simulations

Colony density:

Tree size: semi-dwarf
Orchard Design - xxxooo

x - 'Delicious'
0 - 'McIntosh'

2.5 colonies/hectare

 

119

 

 

 

 

 

Table 8
The influence of colony density on fruit set under various weather
conditions. *

Weather colonies/hectare Petal Fall Fruit Set (Fruit/Blossom * 100 )
'Delicious' 'McIntosh'

Good 0.62 14.95 0.94

1.2 19.30 1.75

2.5 22.49 3.14

5.0 24.34 5.36

7.4 24.87 7.00

10.0 25.04 8.32

12.3 25.00 9.27

Ideal 0.62 26.44 3.15

1.2 37.43 5.38

2.5 47.71 8.68

5.0 55.23 12.88

7.4 59.06 14.47

10.0 61.55 15.16

12.3 63.16 15.66

Warm rain 0. 62 11.05 1.48

1.2 16.64 2.56

2.5 20.86 4.08

5.0 26.06 5.33

7.4 29.47 6.01

10.0 30.46 6.32

12.3 31.02 6.54

 

 

 

 

* Constant parameters in the simulations
Tree size: S
Orchard design - oooxxx

emi-Dwarf

o - 'McIntosh'

x3

'Delicious'

 

Frult/ Blossom

 

120

 

O
(D
“3..
O
a ldeol Flight
a Weather
A
A
O
N
“2-
O
A
D
O
M
«5" A
I. III Good Flight
" Weather
3 ‘ " -
r...“ a a Warm Rain
0
E
El
I
a

O
O I
CI.

.5 I I I I 1
0 3 6 9 12 15
Colonies/Hooters
Figure 1. Predicted 'Delicious' Fruit Set Percentages Under

Various Colony/Hectare and Simulated Weather
Conditions.

Fruit/ Blossom

 

121

 

2
:37 A
a Ideal Flight
‘ Weather
A
.‘3
o.—
Good Flight
.3 ‘ Weather
9
0-i
O
. I
. Warm Rain
‘ a
'
9.. a
O
A a
I
I
a
O
O
c; I’ I I I “1
0 3 8 9 12 15
Colonies/Hectare
Figure 2. Predicted McIntosh Fruit Set Percentages Under

Various Colony/Hectare and Simulated Weather Conditions.

122

flight weather' conditions, the fruit set goal for 'Delicious' was met on the third
day of bloom (40.8 DDS). Consequently, the increase in fruit set with additional
colony introduction was essentially overset that would have required thinning to
achieve good fruit size. Conversely, the 'McIntosh' fruit set goal (10.4% of the
blossoms set fruit) was met under 'ideal flight weather' conditions at the end of
bloom only when colonies were introduced at a rate of five or more per hectare
(with the simulated orchard design) (Table 8).

Although fruit set in both varieties increased with additional colony
introductions under both 'good flight weather' and 'warm rain' conditions (where
flight weather was limited), the increase was not as great as under 'ideal flight
weather' conditions. In both varieties, the fruit set rate did not increase greatly
after more than 5 colonies/hectare were introduced. The fruit set goal in
'Delicious' was met on the eighth day of bloom under all colony/hectare densities
and 'good flight weather' conditions, and on the third day of bloom (45 DDS)
under 'warm rain' weather conditions. Although 'McIntosh' fruit set increased
with additional colony introduction, the fruit set goal (12% blossoms set fruit)
was not met at any colony density under 'good flight weather' or 'warm rain'

conditions.

DISCUSSION
According to our simulations, the factors most strongly affecting fruit set
are the availability of compatible pollen, and the size of the foraging population
on apples. Orchard design played an important role in attaining a desired fruit
set goal, and 'Delicious' and 'McIntosh' trees planted in a one to one ratio

resulted in the highest 'Delicious' fruit set values, even when planted in solid

123

blocks. Conversely, fruit set values for 'McIntosh' were lowest when planted in a
one-to-one ratio with 'Delicious.'

Predictions of low set on 'McIntosh' in one-to-one plantings can be
attributed to the progression of flowering in the two varieties. 'McIntosh' blooms
before 'Delicious' and has a lower degree day threshold for its progression of
bloom. As a result, 'McIntosh' has more Open blossoms during its pre-peak bloom
interval than 'Delicious' and in the simulations would be the predominant apple
pollen in the hive (during this interval). This would cause numerous cross
pollinations on 'Delicious' blossoms opening early in bloom but would limit fruit
set on 'McIntosh' (a self-incompatible variety) because of a dilution in compatible
('Delicious') pollen.

When simulations were run with higher 'Delicious' to 'McIntosh' ratios,
'McIntosh' fruit set increased to percentages more commonly encountered in the
field. In commerical orchards, 'McIntosh' trees are often planted in arrange-
ments with three or more times as many 'Delicious' trees so there is enough
compatible pollen to often overset the 'McIntosh' trees. Hence, it has been
concluded that 'McIntosh' does not have fruit set problems while in some
situations 'Delicious' does. In the field, when 'Delicious' are planted at greater
than three-to—one ratios with a pollinizer, 'Delicious' fruit set may in fact be
poor in some years due to a dilution of pollinizer pollen in the hive.

The model also displayed a behavior often seen in the field where dwarf
trees out produce semi-dwarf and standard plantings. Dwarf trees did not have
as high a fruiting percentage as semi-dwarf or standard trees but did produce
more bushels per hectare. The higher fruiting percentages predicted on the

larger trees was probably a result of the distribution of cross pollinations. In

124

standard or semi-dwarf orchards there were fewer trees per hectare and hence
more cross-pollinations per tree. In the dwarf orchard there were more trees,
each with comparatively fewer blossoms. Consequently, fewer cross pollinations
took place per tree, but yields were higher because there were more blossoms
per hectare.

Not surprisingly, weather was found to influence the rate of fruit set,
especially if flight weather was restricted to a single day during bloom. The
effects of weather on fruit set were exerted two ways. The first was progression
of bloom which especially affected 'McIntosh' trees. Fruit set was higher in this
variety under conditions of 'warm rain' than in 'good flight weather.’ This was
because higher temperatures programmed in the 'warm rain' tape progressed the
blooms faster so that when flight weather did exist, there were more 'Delicious'
blossoms open to serve as a compatible pollen source for the 'McIntosh'. The
same effect was seen in both varieties when flight was restricted to one day
during bloom. The conditions on the flight day were identical between weather
tapes, but the maximum number of open 'Delicious' and 'McIntosh' blossoms

occurred on day-6 of bloom (68-82 DD 88-106 DD.). At this time a commercial

SI
sized apple crop was predicted to occur with a single day of 'ideal flight
weather.’

Weather also affected fruit set because of its influence on honey bee
flight. Weather tapes that restricted flight (i.e., 'good flight weather,‘ 'warm
rain,’ etc.) resulted in lower fruit set predictions compared to those based upon
'ideal flight weather' during bloom. When conditions for flight are limited, many

blossoms do not receive cross pollinating visits for most if not all of their lives.

This would explain the lower petal-fall fruit set percentages. Under 'ideal flight

125

weather' conditions though, flight was not at all restricted, and the resulting
fruit set was totally a function of orchard design and the influence of weather on
the progression of bloom.

When honey bees were introduced at rates greater than 0.62 colonies/hect-
are, petal fall fruit set increased under all weather conditions. Adding more
colonies was not necessary though, if fewer numbers allowed a fruit set goal to
be achieved. This was because the time needed to reach the goal could not be
significantly shortened by adding more colonies. In these simulations the
additional fruit from introducing more colonies represented an overset that
would have required thinning to achieve good fruit size.

It has been reported that compared to other varieties, ’Delicious' is less
resistant to low temperatures just before and during bloom, and in some years
and sites a high percentage of blossoms lose their ability to set fruit (Hartman
and Howlett 1954). Although it has been suggested that this factor may be
partially responsible for low yields in 'Delicious,‘ our simulations predicted that a
full crop could be obtained with 2.5 colonies/hectare even if up to 60% of the
blossoms were non-viable. If only 20% of the blossoms had a probability of
setting fruit, a full crop could be achieved by introducing colonies at a rate of
10/hectare.

Although 'McIntosh' fruit set benefited more than 'Delicious' by additional
colony introduction, it also required more colonies per hectare to reach its fruit
set goal when blossom viability was low. Because 'McIntosh' bloom is chrono-
logically shorter than 'Delicious' in the model (due to its lower degree day
threshold temperature), the total time when cross-pollinations can occur in

'McIntosh' is more limited. When a high percentage of blossoms are non-viable,

126

even more need to be cross pollinated (in both varieties) for a fruit set goal to be
reached. Many 'McIntosh' blossoms were not cross pollinated at lower
colony/hectare densities, and those blossoms that were, probably had lower fruit
set probabilities (compared to 'Delicious') due to the rapid aging of ‘McIntosh'
bloom. Consequently more cross pollinations were needed for 'McIntosh' than
'Delicious' to set the same amount of fruit. This explains why 'McIntosh' fruit set
increased more than 'Delicious' with additional colony introdctions, and required
higher colony/hectare densities to reach a fruit set goal when blossom viability
was low.

The fact that most 'McIntosh' blossoms were not cross pollinated early in
bloom or on their day of anthesis was further evidenced by the results of
simulations with constant and decreasing blossom quality (i.e., fruit set probabil-
ities). When fruit set probabilities were held constant (at 0.999) for every
blossom over it entire life, 'McIntosh' fruit set increased more than 'Delicious'
regardless of the weather conditions. In the model, most cross pollination to
'Delicious' blossoms occur early in bloom and not long after their day of anthesis.
This is when fruit set probabilities are relatively high,and consequently
'Delicious' fruit set was not increased as much by constant high fruit set
probabilities as was 'McIntosh.‘

During the development and validation of REDAPOL, the source of honey
bees carrying compatible pollen (pollinators) was assumed to be the pivotal point
in predicting fruit set. Pollinators were reported to originate from competition
for nectar which forced some bees to move from tree to tree to obtain a full
nectar load (Butler 1944, McGregor 1976). When competition and tree to tree

movement were simulated using REDAPOL, the contribution to fruit set from

127

this pollinator source was predicted to be minimal (i.e., less than 1 % of total
fruit set), even when pollinizer trees were interplanted in 'Delicious' rows.

By far the greatest contributions to fruit set in our simulations, were
attributed to honey bees that had acquired compatible pollen in the hive. In the
field, this source of pollinators explains how fruit is set on self-sterile trees
planted in solid blocks or in rows a considerable distance from the pollinizer.
Our simulations predict that the majority of fruit set in both solid blocks and
those interplanted with pollinizers is by honey bees that have acquired compat-
ible pollen in the hive.

Results from these simulations could have profound implications with
regard to recommendations on orchard design. If indeed the majority of
pollinators are originating from pollen transfer in the hive, the ratio of
'Delicious' to pollinizer trees may be more important than their actual arrange-
ment in the orchard. Our simulations support this conclusion, and predict
Optimum commercial sets on 'Delicious' trees planted in solid blocks at a one to

one ratio with a pollinizer variety that blooms 1-2 days earlier.

LITERATURE CITED

Butler, C. G. 1944. Work on bee repellents: management of colonies for
pollination. Ann. Appl. Biol. 30(2):195-196.

Detjen, L. R. 1929. The effects of nitrogen on the set of apple flowers situated
variously on the cluster base. Proc. Amer. Soc. Hort. Sci. 25:153-157.

Hartman, F. O. and F. S. Howlett. 1954. Fruit setting of the Delicious apple.
Ohio Agric. Exp. Sta. Bul. 745. 64pp.

Free, J. B. 1966. The foraging areas of honey bees in an orchard of standard
trees. J. Appl. Ecol. 3:261-268.

Free, F. B. and Y. Spencer-Booth. 1964a. The foraging behavior of honey bees
in an orchard of dwarf apple trees. J. Hort. Sci. 39:78-83.

. 1964b. The effect of distance from the pollinizer varieties on

the fruit set of apple, pear, and sweet cherry trees. J. Hort. Sci. 39:54-
60.

 

Karma, E. A. and V. R. Vickery. 1954. The place of honey bees in orchard
pollination. Mimeogr. Circ. N. S. Dept. Agric. Mktg. No. 67.

McGregor, S. E. 1976. Insect. pollination of cultivated crop plants. USDA
Agricultural Handbook No. 496. pp81-88.

Westwood, M. N. 1978. Temperate Zone Pomolog. W. H. Freeman and Co. San
Francisco, CA 428pp.

128

DEFINING THE POLLINATING POPULATION IN AN APPLE ORCHARD

USING SCANNING ELECTRON MICROSCOPY

129

INTRODUCTION

Although the behavior of honey bees (Apis mellifera L.) foraging apple has

 

been the subject of considerable study (g. v. Free 1960, Free 1966, Free and
Spencer-Booth 1964, Robinson 1979), the sequence of events leading to the
formation of a cross-pollinating population (i.e., honey bees carrying pollen that
could initiate fruit set) has never been documented. Because apple craps
produced on self incompatible trees (i.e., varieties that require pollination by an
unrelated variety to initiate fruit set) are often quite large, it is evident that
this cross-pollinating population may be of considerable size. Most often though,
honey bees remain on the same tree during a foraging trip, and will return to it
throughout the day. In self-incompatible varieties, this behavior alone could not
initiate fruit set because cross-pollinations would not occur. Because when
honey bees leave a tree, the next one visited is often an adjacent one in the same
row (Free 1966, Free and Spencer-Booth 1964), recommendations concerning tree
arrangements in orchards with self-incompatible varieties have stressed inter-
planting pollinizer varieties in the main cultivar rows (Latimer 1931, Brittain
1933, Burrell and MacDaniels 1931, Free 1962). This practice increases the
chances of bee movement between trees of unrelated varieties, and reportedly
results in a significant increase in cross pollination.

If reported observations on honey bee movement truly reflect the behavior
of the foraging population, the transfer of pollen between two trees of unrelated
varieties should indeed be a rare event, especially in solid block plantings or in
isolated self-incompatible trees. Keeping in mind that only a varying percentage

of a hive's foraging force is working apple, and that population is further

130

131

subdivided into those finding adequate rewards on a single tree and remaining
there, and those moving between trees of the same variety, the population of
bees moving in cross pollinating directions (pollinators) is probably quite small.
Hence, fruit set should be limited on all self-incompatible varieties, and ought to
decrease significantly with distance from the pollinizer. However, this has not
been found to occur consistently, which suggests that the portion of the foraging
population with cross pollinating potential may be resulting from another set of
conditions other than tree to tree movement.

The possibility that pollen transfer in the hive from contact between
nestmates could be contributing to pollinator population was first suggested by
Karma and Vickery (1954). One way to test this would be to examine pollen
carried on the bodies of honey bees working apple blossoms. Because honey bees
show foraging fidelity to a single plant species, if pollen was not transferred in
the hive, foragers ought to be carrying primarily one species of pollen on their
bodies. To test this hypothesis, it would be necessary to accurately identify
specific grains of pollen from different apple varieties and other plant species
blooming in concert with apple, and then sample the pollens carried by honey
bees foraging apple.

Scanning electron microscopy (SEM) can be used to identify pollen from
different fruit varieties, because pollen grains have been found to differ in their
exine patterns from variety to variety (Fogle 1977 a,b). Using SEM, pollen from
different apple varieties and from non-apple species can be accurately identified
on the bodies of foragers working apple blossoms, and on apple blossom stigmata.
The purpose of this study was to define the pollinator population in an apple
orchard using SEM, and determine if the transfer of compatible pollen is a

constraint on fruit set in self-incompatible varieties.

MATERIALS AND METHODS
The Influence of Distance from the Pollinizer on Fruit Set

To test for the influence of distance from the pollinizer on fruit set, sites
were selected in Leelanau County, Michigan based upon their arrangement of
pollinizer and 'Delicious' trees. At Stanek and Sons' Orchard, three rows of
'Delicious' were followed by a row of 'McIntosh.’ This pattern was continued for
14 rows. At Herman's Orchard three rows of 'McIntosh' were adjacent to five
rows of 'Delicious' on their north side and four rows of 'Delicious' on their south.

During bloom at both sites, blossoms were counted on trees various
distances from the pollinizer. One meter branch sections on four sides of the
tree were chosen for these counts. After June drop (about three weeks after
petal fall) the resulting fruit was counted. Seed from retained fruit on
'Delicious' trees various distances from the pollinizer rows was also counted at
the Herman's Orchard.

Data from fruit set and seeds per fruit in rows various distances from the
pollinizer were analyzed using an F-test. In cases where the F -test prompted a
rejection of the null hypothesis, a Tukey's W multiple comparison test was
performed (Tukey 1953).

Analysis of Pollens on Honey Bees and Apple Stigmata

Honey bees foraging 'Delicious' (Millerspur) and 'McIntosh' (Macspur)
blossoms at the Michigan State University Horticulture Research Farm (in East
Lansing, Michigan) were captured periodically during the day, placed in separate
vials and immediately frozen. 'Delicious' and 'McIntosh' blossom stigmata were

also sampled daily during bloom, stored separately in vials, and frozen until

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133

analyzed. Pollen was then collected from 'Delicious,‘ 'McIntosh,' and other fruit
trees and plants blooming in concert with apple to aid in the identification of
pollens on honey bees and blossom stigmata.

Millerspur 'Delicious' trees at the M.S.U. Horticulture Farm were planted
in solid rows (5-6 trees per row) and were approximately the size of standard
trees (i.e., more than 8 m high and 6 m wide). On one side of the Millerspur
'Delicious' was a row of Red Prince 'Delicious' (4 m away) and on the other, a row
of 'Spartan' trees (9 m away). The 'McIntosh' used in this study were planted in a
three row 32 tree solid block. These trees were also more than 8 m tall and were
spaced so closely the planting ressembled a hedge row The trees were bordered
on the east by flowering tart cherry, on the north by a road, on the south by a
meadow, and on the west by a young tart cherry planting that was not yet
flowering.

Pollen from the bodies of honey bees captured while working 'Delicious' and
'McIntosh' trees was sampled by rolling the insect's body over on aluminum SEM
stub coated with adhesive. The sample was sputter-coated with gold for three
minutes. Non-germinated pollen grains were then identified as self-, cross-, or
non-apple pollen by comparing their exine paterns with pollen samples collected
from fruit trees and other plants.

Frozen floral stigmata were prepared for SEM examination by placing them
on an aluminum stub pretreated with adhesive. The stigmata were then sputter
coated with gold for three minutes and examined for the presence of self-, cross-
and non-apple pollens. All samples were analyzed with a JEOL JSM-35 scanning

electron microscope operated at 15kV.

RESULTS
Effect of Distance from the Pollinizer on Fruit Set

At both orchard sites, fruit set did not differ significantly between
'Delicious' rows with respect to their distance from the pollinizer (Table 1). At
the Stanek and Sons' orchard 19.8% of the 'Delicious' blooms set fruit in rows
next to the pollinizer, while 16.5% set fruit on trees one row away. At Herman's
orchard percentages of blossoms setting fruit ranged between 14.8% (trees three
rows away from the pollinizer) and 17% (trees two rows away from the
pollinizer). Trees four rows away from the pollinizer had statistically equivalent
fruit set(l6.7%) to those adjacent to the pollinizer row (Table 1.).

Seeds per fruit (from 'Delicious' trees) was greatest on trees next to the
pollinizer (on the east side), although seed number did not decrease accordingly
with increasing distance from the pollinizer row (Table 2). Seeds per fruit
ranged between 3.70 (trees three rows away from the east side of the pollinizer)
and 6.89 (trees next to the pollinizer on the east side). Seeds per fruit on trees
four rows away from the pollinizer was not significantly different than in rows
next to the pollinizer (on the west side).

SEM Analysis of Pollens on Honey Bees and Blossom Stigmata

Pollen grains from different apple varieties and competitive plants could
be identified by size, shape, and exine patterns. Millerspur 'Delicious' pollen
grains were oblong, porous, and had a characteristic exine pattern (Figure 1A).
'McIntosh' (Macspur) pollen had the shallowest exine pattern of any apple variety
examined, and could be separated easily from several other varieties ('Delicious',
'Gallia Beauty', 'Rhode Island Greening') (Figure 1). Although pear, tart cherry,

and plum were also similar in shape to some apple varieties (and to each other)

134

 

135

Table l

The influence of distance from the pollinizer row on
'Delicious' fruit set in two Michigan orchards.

 

 

 

 

 

Site Rows away Sample Proportion of blossom
from pollinizer Size setting fruit
(Mean :.3. D.)
Stanek and Son'% 1 10 .165 i .043 a
Orchard Nexc to 15 .198 1 .03 a
Herman's N83“ to 16 .164 _-+_- .030 a
. Orchard 1 16 .150 i .030 a
2 16 .170 i_.028 a
3 16 .148 i .025 a
4 8 .167 i .041 a

 

 

 

 

Means followed by the same letter are not significantly different at the

.05-level as determined by the F-test.

 

136

TABLE 2

Number of seeds per fruit on 'Delicious' trees various
distances from the pollinizer.

 

 

Rows from Mean number of seeds
Pollinizer Direction N per fruit :_ SD.
4 Away E 20 4.75 -_l-_ 1.77a

3 Away 8 20 3.70 : 1.89a

3 Away W 20 3.90 : 1.86a

2 Away 1?. 20 3.80 : 2.12a

2 Away W 20 4.05 i 1.738

1 Away E 19 4.53 i 2.208

1 Away W 20 4.90 : 2.17s
Next to E 19 6.89 i 3.20b
Next to W 20 5.30 i 2.62 a

 

 

 

 

 

 

Means followed by the same letter are not significantly
different at the 52 level as determined by Tukey's W method.

Figure l.

137

Scanning electron micrographs of apple pollen grains.
A - Millerspur 'Delicious', B = Macspur 'McIntosh'

C - 'Gallia Beauty', D - 'Rhode Island Greening'.

All magnifications are 1800x

 

138

 

139

their exine patterns permitted them to be easily distinguished (Figure 2).
Dandelion and yellow rocket were also readily discerned by their characteristic
shape and exine patterns (Figure 2).

When pollen was removed from honey bees working 'Delicious' (Millerspur)
and 'McIntosh' trees, and non-germinated pollen grains were identified, every
apple forager examined was carrying at least some cross pollen, although in a
few cases (mostly in the afternoon hours) no detectable self-pollen. Non-apple
pollen was also found on a majority of honey bees (Table 3 and Figure 3).

Compatible pollen was found to comprise at least half of the pollen types
carried by foragers working either apple variety (Table 4). Non-apple pollens
comprised 30.2% of the types carried by 'Delicious' foragers, and 23.2% of those
working 'McIntosh.‘ These percentages varied widely though, during the day.
Self-pollen made up 15.0% and 20.6% of the types carried on 'Delicious' and
'McIntosh' foragers respectively, but these percentages also had a large variance.

When apple blossom stigmata were examined for the presence of compat-
ible pollen, grains could easily be identified and classified as cross-, self-, or
non-apple pollen (Figure 4). In both varieties, when pollen was found on the
stigma, a portion of it was always from an unrelated variety. Of all the
'Delicious' stigmata examined, 76.9% contained some cross-pollen (Table 5).
When 'McIntosh' stigmata from a three row 32 tree solid block arrangement
were examined, 91.3% were found to have cross-pollen. Self-pollen was also
found on a majority of 'Delicious' and 'McIntosh' stigmata (73.1% and 82.6%

respectively), and non-apple pollen was found in some instances (Table 5).

140

Figure 2. Scanning electron micrographs of pollen from species
blooming in concert with apple. A I Tart Cherry
(720x), B - Stanely Plum (720x), C - Bartlett Pear
(1800x), D - Bosc Pear (660x), E - Dandelion (Taraxa—

cum spp.) (440x), F - Yellow rocket (Barbarea app. 1
(1300x).

 

 

141

 

142

Table 3

Percentages of honey bees carrying cross-, self, and non-apple pollen
while foraging 'Delicious' and 'McIntosh' trees.

 

Variety

 

 

Sample 2 carrying . Z carrying Z carrying

Size compatible self-pollen .non-apple
cross-pollen pollen
'Delicious' I9 100: 84.2 89.5
'McIntosh' 15 1002 87.7 93.3
Total Honey Bees 34 1002 88.2 91.2

 

 

 

 

 

 

143

Figure 3. Scanning electron micrographs of pollens carried by
honey bees foraging 'McIntosh' trees at the Michigan
State University Horticulture Farm.

 

 

 

144

 

Percentages of various pollen types carried

145

Table 4

by honey bees foraging apple.

 

 

 

Variety Being Sample Size 2 Self 2 Cross 2 Nan-Apple

Foraged pollen pollen pollen
'Delicious' 19 15.0 i 7.6 51.6 i 10.3 30.2 i 11.4
'McIntosh' 15 20.6 1- 11.4 56.2 i 13.3

 

 

 

 

 

23.2 + 10.4
‘ J

 

146

Figure 4. Scanning electron micrographs of pollinated apple blos-
som stigma: A and B are from 'McIntosh' blossoms, while
C and D are from 'Delicious blossoms.

 

 

 

147

 

148

TABLE 5

Percentages of apple blossom stigmata with self-, cross-, and non-apple pollens.

 

 

 

Variety Sample Size Z with I with 2 with
self-pollen cross-pollen non-apple pollen
'Delicious' 26 73.1 76.9 77.7

'McIntosh' 23 82.6 91.3 17;4

 

 

 

 

 

 

DISCUSSION

Although honey bees are responsible for the majority of fruit set in apple
orchards especially those containing self-incompatible varieties (McGregor
1976), the size of the honey bee pOpulation capable of cross-pollinating blossoms
(pollinators) has never been determined. From our analysis of pollen from apple
foragers and blossom stigmata, it appears that this population may indeed be
larger than previously suspected. Furthermore, in our study the size of the
pollinator population on a tree did not seem to be strongly influenced by the
tree's distance from the pollinizer.

It has been assumed that honeybees cross pollinate blossoms while moving
from tree to tree in search of nectar. Several authors have shown decreases in
fruit set with distance from the pollinizer, and have explained their results using
this assumption (Williams 1959, Free 1962, Free and Spencer-Booth 1964).
Although some fruit must surely be set this way, tree to tree movement does not
explain how fruit is set in solid blocks of self-incompatible trees or in rows that
are a considerable distance from the pollinizer. Furthermore, a decrease in fruit
set has not been shown to consistantly occur, and often the differences in fruit
set with increased distance from the pollinizer are not great (Free and Spencer-
Booth 1964). These results in conjunction with our data suggest that cross-
pollinating honey bees must be originating from a source other than movement
from tree to tree.

Karma and Vickery's (1954) suggestion that pollen may be acquired by
foragers in the hive from contact among nestmates could help explain the wide
range of pollens found on apple foragers in this and other studies (Kendall and

Solomon 1970, Free and Williams 1972). In our investigation, the use of SEM to

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150

accurately identify apple pollens to variety provided a new perspective on the
pollen types carried by honey bees, and their approximate distance from the tree
being foraged. In many instances, varieties of pollen on honey bees were from
trees more than 30 m away from where the bee was captured. It is doubtful that
honey bees would have foraging areas that included several apple varieties and
unrelated plant species, because these insects have been reported to remain
primarily on the same tree when working apple and at best visit two trees during
a foraging trip (Free and Spencer-Booth 1964, Free 1966).

If honey bees carried pollen only from species they were foraging, the
apple foragers in our samples should have had only two species or varieties of
pollen on their bodies. These bees would also be relatively rare since a majority
of bees find adequate reward on a single variety and do not move from it. In our
study, every apple forager examined had some pollen from an unrelated apple
variety on her body. Although in a few cases we could not detect self-pollen, it
should be noted that only non-germinated grains were counted in these samples,
so self-pollen may have existed but in a germinated state.

Our results showing pollen from various plant species an apple foragers is
in agreement with earlier work by other authors (Kendall and Solomon 1970, Free
and Williams 1972). In previous studies, however, pollens (other than non-apple
types) were classified as "fruit pollen" (Kendall and Solomon 1970) or "predomi-
nant species" pollen (Free and Williams 1972) without regard to specific
varieties. Consequently, it was assumed that these pollens were from the main
species being foraged when in fact, they may have been from several different
varieties or even non-apple species.

The pollen grains found on honey bees are apparently located in areas

where contact with a blossom's reproductive structure is possible. In our

151

samples, there appeared was no shortage of compatible pollens on either
'Delicious' or 'McIntosh' stigmata. Even though some pollens directly on the
stigmatic surface were not visible, nor were pollen tubes or signs of fertilization,
in conjunction with our data on fruit set with distance from the pollinizer, it
appeared that some compatible pollen was fertilizing ovules regardless of the
tree's distance from the pollinizer.

Because tree to tree movement does not seem to be increasing fruit set in
all instances, interplanting pollinizer trees within blocks of the main variety may
not be necessary. What may be more important is the ratio of pollinizer to main
variety trees, and the timing of their blooms (DeGrandi-Hoffman 1983). Ideal
pollinizers would be those that bloom heavily before the main variety. This
would cause honey bees to establish foraging areas on the pollinizer first, so that
when the main variety bloomed, the existance of compatible pollen in the hive
would be assured. This could permit honey bees working the main variety to
acquire sufficient compatible pollen in the hive, and allow them to leave in a
potential cross pollinating state.

The use of SEM has given us the ability to identify pollen to species and
variety, and has lead us to conclude that a majority of honey bees working apple
are carrying compatible pollen. Furthermore, the distribution of cross-
pollinating honey bees is apparently not related to the trees' distance from the
pollen source. Even in solid block plantings ('McIntosh' trees at the MSU
Horticulture Farm) honey bees were fatmd carrying pollen from several other
apple varieties and species of plants. These results cannot be explained by tree
to tree movement of honey bees, which has lead us to conclude, as Karno and
Vickery (1954) did, that honey bees may be transferring pollen in the hive during

contact with nestm ates.

LITERATURE CITED

Brittain, W. H. 1933. Apple pollination studies in the Annapolis Valley, N. 8.
Canada. 1928-1932. Bull. Dept. Agric. Can. New Ser. No. 162.

Burrell, A. B. and L. H. MacDaniels. 1931. Further pollination studies with the
McIntosh apple in the Champlain Valley of New York. Amer. Soc. Hort.
Sci. Proc. 1930:374-385.

DeGrandi-Hoffman, G. 1983. Identifying factors that influence fruit set in
'Delicious' apples using REDAPOL simulations. In: The Construction,
Validation, and Behavior of a Pollination and Fruit Set Model for 'Delicious'
Apples. PhD thesis, Dept. of Entomol., Mich. State Univ.

Free, J. B. 1960. The pollination of fruit trees. Bee World. 41(6):141-151;
(7):169-186.

. 1962. The effect of distance from the pollinizer varieties on
the fruit set on trees in plum and apple orchards. J. Hort. Sci. 37:262-271.

 

. 1966. The foraging areas of honey bees in an orchard of
standard apple trees. J. Appl. Ecol. 3:261-268.

 

. and Y. Spencer-Booth. 1964. The effect of distance from the
pollinizer varieties on the fruit set of apple, pear, and sweet cherry trees.
Jo Hort. SCio 39:54-60.

 

. and I. H. Williams. 1972. The transport of pollen on the body
hairs of honey bees (Aphis mellifera L.) and bumblebees (Bombus spp. L.).
J. Appl. Ecol. 9:609-615.

 

 

Fogle, H. W. 1977a. Identification of clones within four tree fruit species by
pollen exine patterns. J. Amer. Soc. Hort. Sci. 102:552-560.

. 1977b. Identification of tree fruit species by pollen
ultrastructure. J. Amer. Soc. Hort. Sci. 102:548-551.

 

Karma, E. A. and V. R. Vickery. 1954. The place of honey bees in orchard
pollination. Mimeogr. Circ. N. S. Dept. Agric. Mktg. No. 67.

Kendall, P. A. and M. E. Solomon. 1970. Quantities of pollen on the bodies of
insects visiting apple blossoms. J. Apple. Ecol. 10:627-634.

Latimer, L. P. 1931. Pollination studies with the McIntosh apple in New
Hampshire. Amer. Soc. Hort. Sci. Proc. 1930:386-396.

McGregor, S. E. 1976. Insect pollination of cultivated crop plants. USDA
Agricultural Handbook No. 496, pp81-88.

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153

Robinson, W. S. 1979. Effect of apple cultivar on foraging behavior and pollen
transfer by honey bees. J. Amer. Soc. Hort. Sci. 104:596-598.

Tukey, J. W. 1953. The problem of multiple comparisons. Mimeographed.
Princeton, N.J.: Princeton University.

Williams, R. R. 1959. The effective distance of a pollen source in a cider apple
orchard. Rep. Long Ashton Res. Stat. for 1958. 61-64.

GENERAL THESIS SUMMARY

One of the stronger arguments supporting a systems approach to problem
solving is that during the phases of system description and validation, insights
and new perspectives on the relationships between the system's components are
inevitably gained. This argument has held true in the develoPment of REDAPOL,
because during this model's construction and validation, explanation on the
source of honey bees with cross-pollinating potential (pollinators) and the reasons
why 'Delicious' trees may under set in some years and sites have been obtained.
As a consequence, recommendations on 'Delicious' and pollinizer tree
arrangements to maximize fruit set have been derived, and colony/hectare
requirements and the timing of colony introduction that are specific to the
orchard and weather in a given year have also been developed.

The key to the model's ability to predict fruit set rates has to center
around predictions on the size of the pollinator population. Field studies and
simulations have indicated that the size of this population is far too large to be
explained by tree to tree movement alone, and that transfer of pollen among
bees in the hive may indeed be the primary source of pollinators. This finding has
created revised recommendations on choices of pollinizer varieties, and their
arrangement with 'Delicious' trees in orchards.

A large part of the problem with 'Delicious' fruit set may be the choice of
pollinizer variety and orchard design. When pollinizer trees bloom after
'Delicious', the predominate apple variety in the hive during the first days of
'Delicious' bloom has to be 'Delicious' pollen. This type of pollen will not set
fruit on 'Delicious' trees, and explains why king blossoms rarely set when 'Golden

Delicious' (which blooms after 'Delicious') is used as a pollinizer in Michigan

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155

orchards. If a pollinizer variety is chosen that blooms before 'Delicious', the
next constraint on fruit set may be the ratio of 'Delicious' to pollinizer trees in
the orchard. Simulations have shown that when one variety of tree greatly
outnumbers another (as often seen in 'Delicious' orchards), compatible pollen is
diluted in the hive and can limit fruit set. In 'Delicious' orchards the highest
fruit set percentages were obtained with simulations of one to one ratios of
'Delicious' and pollinizer trees planted in solid blocks.

During the development of REDAPOL the need to express the progression
of bloom in physiological time units (accumulated degree days) became apparent,
because of the variation in bloom length from year to year. Using the
accumulated degree days required for peak bloom in each variety as a fixed
point, threshold temperatures for 'McIntosh' (Macspur sport) and 'Delicious'
(Millerspur and Red Chief sports) were defined by minimizing the variance
between sites in the degree days needed to reach peak bloom. Although this
method needs further testing, it may be a means to describe threshold tempera-
tures for the progression of bloom in other apple varieties.

It has been concluded that although all apple varieties are related in some
way, their threshold temperatures for the progression of bloom probably differ.
For example, the threshold temperature for 'Delicious' bloom was determined to
be 5°C while for 'McIntosh' it was 1°C. This finding has interesting repercus-
sions with respect to the aging of bloom and the availability of compatible
pollen. In years when temperatures during bloom are low (2-4OC), 'McIntosh'
bloom will continue to progress while 'Delicious' bloom will not. As a
consequence, when temperatures rise and conditions become suitable for honey

bee flight, the availability of 'McIntosh' pollen may be a severe constraint on

156

'Delicious' fruit set. When weather tapes containing cooler temperatures were
used in simulations, REDAPOL demonstrated this behavior.

Because modeling pollination and fruit set systems permits crop size to be
predicted and managed, crops that rely on honey bees for cross-pollination and
seed set have a distinct advantage over other crops with regards to consistancy
and control of production. By establishing desired blossom to fruiting
percentages (fruit set goals), honey bee colonies can be introduced and removed
strategically so that crap size can be controlled. Further developments on honey
bee repellent sprays could be the next step in enhancing fruit set control,
because with them the effectiveness of colony removal to halt fruit set could be
increased, especially in orchards with relatively large indigenous bee populations.

It is often said that models are never really completed because they can
always be refined and elaborated upon. Future elaboration of REDAPOL will be
directed at further validation and means for grower implementation. Before the
model can be used by growers, sampling schemes will have to be developed so
that orchard parameters can be entered into the model consistantly. In some
orchards honey bee colonies are not introduced because feral bee populations (or
those from a neighbor's hive) are large enough to produce commercial sets.
REDAPOL could still be used in these orchards, by developing a plan to sample
trees for honey bees early in bloom (while monitoring weather conditions), and
then estimate indigenous colony/hectare densities by using the functions in the
model that predict honey bees/tree in reverse order.

Pollination and fruit set modeling could represent the future of applied
pollination research, because it can add a new consistancy in the production of

honey bee pollinated crops. Similar models could be construcfed for cotton,

157

sunflowers, soybeans, and any other crops requiring cross pollination by honey
bees. No longer will colony/hectare recommendations and timing of colony
introduction and removal for various crops be the product of guesswork and
previous practices. Instead, pollination and fruit set modeling will produce
recommendations that are specific for the year and site in question, and permit

pollination to be a compatible part of integrated crop management programs.