Modeling Post-Harvest Pathogens in Apple Fruit

181 Pages·2012·7.28 MB·English

MODELING POST-HARVEST PATHOGENS IN APPLE FRUIT
by
KATRINA ANNE WILLIAMS
B.Sc., Carleton University, 2010
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
in
THE COLLEGE OF GRADUATE STUDIES
(Interdisciplinary Studies)
THE UNIVERSITY OF BRITISH COLUMBIA
(Okanagan)
December 2012
© Katrina Anne Williams, 2012
Abstract
Post-harvest disease of apple fruit causes significant loss of fruit during and after
storagewithaconsiderableeconomicimpact. Studyingthefactorsthatcontribute
to post-harvest disease and developing predictive models may help growers and
packing house workers to make more informed decisions on disease forecasting
and duration of storage for apples. Data for three major post-harvest pathogens,
Penicillium expansum, Botrytis cinerea and Mucor piriformis, which were moni-
tored and quantified in four orchards over three years during the growing season
and then in storage, were available. Contrary to expectation, it was found that
environmental data provided little to no explanation of the trends in inoculum de-
tection. It was hypothesized that this lack of relationship between the amount of
inoculum present and the environmental factors was due to the manner in which
the data were collected. In contrast, it was found that a large proportion of the
variation in storage disease outcomes (R2=0.506, p=0.000) could be predicted by
the duration of storage, temperature and rainfall two weeks before storage, and
the quantity of pathogen DNA detected on the plant tissue at harvest. In order
to better understand the relationship between environmental factors and spore
detection in the orchard, a Gaussian plume model was developed for describing
spore dispersal. Model results had good qualitative agreement with the data that
were collected in the field, suggesting that a high level of variability would be
expected when only using one receptor location due to the dynamics of spore
movement based on wind conditions. The model predicted that increasing the
number of receptors, especially when they were evenly placed around the orchard,
would decrease the variability of detection results. Based on the model outcomes,
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it was concluded that five receptors would give the most reasonable results for
the least expenditure. This research develops the first predictive model for post-
harvest apple disease outcomes in storage based on pre-storage factors, and gives
new insight into the dispersal of fungal spores in an orchard setting, providing
recommendations for improving future data collection and modeling work.
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Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Review of Relevant Literature . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.2 Phyllosphere Microbial Dynamics . . . . . . . . . . . . . . 3
1.1.3 Post-Harvest Diseases of Pome Fruit . . . . . . . . . . . . 10
1.1.4 Pre-Harvest Factors Influencing Disease Outcomes . . . . . 12
1.1.5 Harvest Factors Influencing Disease Outcomes . . . . . . . 17
1.1.6 Post-Harvest Factors Influencing Disease Outcomes . . . . 18
1.1.7 Control Techniques . . . . . . . . . . . . . . . . . . . . . . 20
1.1.8 Mathematical Modeling . . . . . . . . . . . . . . . . . . . 24
1.2 Research Goals and Hypotheses . . . . . . . . . . . . . . . . . . . 36
1.2.1 Determine Relationships between Spore Detection and En-
vironmental Conditions . . . . . . . . . . . . . . . . . . . . 36
1.2.2 Pre-Storage Model for Incoming Infection Risk . . . . . . . 37
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1.2.3 Combining the Pre-Storage and During-Storage Models . . 37
1.2.4 Circulation/Probability Modeling of Inoculum Contact . . 38
2 Data Collection and Experimental Set-up . . . . . . . . . . . . . 40
2.1 Synopsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.2 Field Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.2.1 Experimental Set-up . . . . . . . . . . . . . . . . . . . . . 40
2.2.2 Data Collection Techniques . . . . . . . . . . . . . . . . . 41
2.2.3 Descriptions of Orchards . . . . . . . . . . . . . . . . . . . 42
2.2.4 Data Collected by Year . . . . . . . . . . . . . . . . . . . . 44
2.2.5 Description of Data . . . . . . . . . . . . . . . . . . . . . . 45
2.3 Storage Experiments . . . . . . . . . . . . . . . . . . . . . . . . . 61
2.3.1 Experimental Set-up . . . . . . . . . . . . . . . . . . . . . 61
2.3.2 Data Collection Techniques . . . . . . . . . . . . . . . . . 61
2.3.3 Descriptions of Storage Techniques . . . . . . . . . . . . . 62
2.3.4 Data Collected by Year . . . . . . . . . . . . . . . . . . . . 63
2.3.5 Description of Data . . . . . . . . . . . . . . . . . . . . . . 64
3 Predicting Post-Harvest Disease Outcomes . . . . . . . . . . . . 69
3.1 Synopsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.2 Data Analysis Techniques . . . . . . . . . . . . . . . . . . . . . . 69
3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.3.1 Orchard Variables . . . . . . . . . . . . . . . . . . . . . . . 69
3.3.2 Storage Variables . . . . . . . . . . . . . . . . . . . . . . . 78
3.4 Comparison with Expectation . . . . . . . . . . . . . . . . . . . . 90
3.5 Pre-Storage Predictive Model . . . . . . . . . . . . . . . . . . . . 91
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4 A Model for Dispersal of Fungal Spores in an Orchard . . . . . 94
4.1 Synopsis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.2 Model Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
4.3 Structure of Simulated Orchard . . . . . . . . . . . . . . . . . . . 99
4.4 Sources of Spores . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
4.5 Incorporating Wind Direction and Angle . . . . . . . . . . . . . . 104
4.6 Model Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
4.6.1 One Receptor . . . . . . . . . . . . . . . . . . . . . . . . . 107
4.6.2 Multiple Receptors . . . . . . . . . . . . . . . . . . . . . . 111
4.6.3 Location of Receptors . . . . . . . . . . . . . . . . . . . . 123
4.6.4 100 Receptor Profiles . . . . . . . . . . . . . . . . . . . . . 132
4.6.5 Varying Numbers of Sources . . . . . . . . . . . . . . . . . 136
4.7 Quantification of Results . . . . . . . . . . . . . . . . . . . . . . . 145
4.8 Comparison with Experimental Data . . . . . . . . . . . . . . . . 145
5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
5.1 Analysis of Post-Harvest Disease Prediction Results . . . . . . . . 148
5.2 Analysis of Dispersal Modeling Results . . . . . . . . . . . . . . . 150
5.3 Overall Contributions of this Research . . . . . . . . . . . . . . . 151
5.4 Strengths and Limitations . . . . . . . . . . . . . . . . . . . . . . 152
5.5 Potential Applications and Future Research Directions . . . . . . 153
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
Appendix A Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
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List of Tables
1.1 Spotts and Gastagnoli’s (2010) relative risk model for pear fruit . 25
2.1 Orchard labels and locations. . . . . . . . . . . . . . . . . . . . . 43
2.2 Apple cultivars for studied orchards . . . . . . . . . . . . . . . . . 44
3.1 Average pathogen DNA on I-rods. . . . . . . . . . . . . . . . . . 71
3.2 Average pathogen DNA on plant tissue. . . . . . . . . . . . . . . . 71
3.3 Correlations of I-rod DNA and temperature. . . . . . . . . . . . . 72
3.4 Correlations of plant tissue DNA and temperature. . . . . . . . . 73
3.5 Correlations of I-rod DNA and rainfall. . . . . . . . . . . . . . . . 74
3.6 Correlations of plant tissue DNA and rainfall. . . . . . . . . . . . 75
3.7 Correlations of I-rod DNA and wind. . . . . . . . . . . . . . . . . 76
3.8 Correlations of plant tissue DNA and wind. . . . . . . . . . . . . 77
3.9 Correlations between disease incidence and timing of storage. . . . 79
3.10 Percentage of apples infected by year. . . . . . . . . . . . . . . . . 80
3.11 Percent of infected apples by orchard. . . . . . . . . . . . . . . . . 81
3.12 Percentage of apples infected by cultivar. . . . . . . . . . . . . . . 83
3.13 Percent of apples infected by if wounding occured . . . . . . . . . 83
3.14 Percentage of apples infected by storage type. . . . . . . . . . . . 85
3.15 Correlations of percentage infected with temperature. . . . . . . . 86
3.16 Average temperature by year. . . . . . . . . . . . . . . . . . . . . 87
3.17 Correlations of percentage infected with rainfall. . . . . . . . . . . 88
3.18 Correlations of percentage infected with pathogen DNA levels. . . 89
4.1 Empirical constants for stability classes. . . . . . . . . . . . . . . 97
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List of Figures
1.1 Visual description of the Gaussian plume model solutions. . . . . 30
2.1 Map of the Okanagan Valley. . . . . . . . . . . . . . . . . . . . . . 41
2.2 Pathogen DNA in Orchard 1, 2007 . . . . . . . . . . . . . . . . . 47
2.3 Pathogen DNA in Orchard 2, 2007 . . . . . . . . . . . . . . . . . 48
2.4 Pathogen DNA in Orchard 3, 2007 . . . . . . . . . . . . . . . . . 49
2.5 Pathogen DNA in Orchard 4, 2007 . . . . . . . . . . . . . . . . . 50
2.6 Pathogen DNA in Orchard 1, 2008 . . . . . . . . . . . . . . . . . 51
2.7 Pathogen DNA in Orchard 2, 2008 . . . . . . . . . . . . . . . . . 52
2.8 Pathogen DNA in Orchard 3, 2008 . . . . . . . . . . . . . . . . . 53
2.9 Pathogen DNA in Orchard 4, 2008 . . . . . . . . . . . . . . . . . 54
2.10 Pathogen DNA in Orchard 1, 2010 . . . . . . . . . . . . . . . . . 55
2.11 Pathogen DNA in Orchard 2, 2010 . . . . . . . . . . . . . . . . . 56
2.12 Pathogen DNA in Orchard 5, 2010 . . . . . . . . . . . . . . . . . 57
2.13 Pathogen DNA in Orchard 6, 2010 . . . . . . . . . . . . . . . . . 58
2.14 2010 average temperature and rainfall data . . . . . . . . . . . . . 59
2.15 2010 wind speed and direction data . . . . . . . . . . . . . . . . . 60
2.16 2007 storage disease incidence. . . . . . . . . . . . . . . . . . . . . 66
2.17 2008 storage disease incidence. . . . . . . . . . . . . . . . . . . . . 67
2.18 2010 storage disease incidence. . . . . . . . . . . . . . . . . . . . . 68
3.1 Regression plot of percentage infected with year and duration of
storage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
3.2 Regression plot of percentage infected with orchard and duration
of storage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
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3.3 Regression plot of percentage infected with wounding and duration
of storage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
3.4 Regression plot of percentage infected with storage type and dura-
tion of storage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
3.5 Spotts and Gastagnoli’s (2010) relative risk model for pear fruit . 91
4.1 Vertical cross-section of plume with heights marked. . . . . . . . . 98
4.2 Contour plots for a single point source. . . . . . . . . . . . . . . . 99
4.3 Photograph of orchard. . . . . . . . . . . . . . . . . . . . . . . . . 100
4.4 Representative orchard layout for simulation. . . . . . . . . . . . . 102
4.5 Vertical cross-section with heights and tree. . . . . . . . . . . . . 103
4.6 Wind and source coordinate systems. . . . . . . . . . . . . . . . . 105
4.7 Contour plots for two point sources. . . . . . . . . . . . . . . . . . 106
4.8 Contour plots for two point sources with trees. . . . . . . . . . . . 107
4.9 Three trials for a single receptor with two sources. . . . . . . . . . 109
4.10 Average concentration for a single receptor. . . . . . . . . . . . . . 110
4.11 Average concentration for 100 receptors. . . . . . . . . . . . . . . 117
4.12 Normalized wind speed and average concentration. . . . . . . . . 118
4.13 Average detection for varying receptor numbers. . . . . . . . . . . 119
4.14 Range of detection for varying receptor numbers. . . . . . . . . . 120
4.15 Maximum values for increasing numbers of receptors. . . . . . . . 121
4.16 Percentage non-zero for varying receptor numbers. . . . . . . . . . 122
4.17 Locations of Receptors . . . . . . . . . . . . . . . . . . . . . . . . 124
4.18 Average detection for varying receptor locations. . . . . . . . . . . 128
4.19 Range of detection for varying receptor locations. . . . . . . . . . 129
4.20 Average maximum detection for varying receptor locations. . . . . 130
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4.21 Percentage non-zero detection for varying receptor locations. . . . 131
4.22 Day 1, trial 10 results. . . . . . . . . . . . . . . . . . . . . . . . . 134
4.23 Day 10, trial 20 results. . . . . . . . . . . . . . . . . . . . . . . . . 135
4.24 Highest maximum results. . . . . . . . . . . . . . . . . . . . . . . 135
4.25 Average maximum results. . . . . . . . . . . . . . . . . . . . . . . 136
4.26 Average spore detection varying location and numbers. . . . . . . 139
4.27 Range of spore detection varying location and numbers. . . . . . . 140
4.28 Highest maximum spore detection varying location and numbers. 141
4.29 Average maximum spore detection varying location and numbers. 142
4.30 Lowest maximum spore detection varying location and numbers. . 143
4.31 Percentage non-zero spore detection varying location and numbers. 144
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