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POPULATION DYNAMICS, MOLECULAR CHARACTERIZATION AND MANAGEMENT OF CODLING , POMONELLA (LINNAEUS) (; TORTRICIDAE)

BY

HAYAT ZADA

A dissertation submitted to the University of , Peshawar in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY IN AGRICULTURE ( PROTECTION)

DEPARTMENT OF PLANT PROTECTION FACULTY OF CROP PROTECTION SCIENCES THE UNIVERSITY OF AGRICULTURE PESHAWAR-PAKISTAN FEBRUARY, 2015

POPULATION DYNAMICS, MOLECULAR CHARACTERIZATION AND MANAGEMENT OF APPLE , CYDIA POMONELLA (LINNAEUS) (LEPIDOPTERA; TORTRICIDAE)

BY

HAYAT ZADA

A dissertation submitted to The University of Agriculture, Peshawar in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY IN AGRICULTURE (PLANT PROTECTION)

Approved by:

______Supervisor/Chairman Supervisory Committee Prof. Dr. Ahmad-Ur-Rahman Saljoqi

______Co-Supervisor Prof. Dr. Abid Farid University of Haripur

______Member (Major Field) Prof. Dr. Farman Ullah

______Member (Minor Field) Prof. Dr. Imtiaz Ali Khan Department of Entomology

______Chairman & Convener Board of Studies Prof. Dr. Farman Ullah

______Dean Faculty of Crop Protection Sciences Prof. Dr. Saifullah

______Director Advanced Studies & Research Prof. Dr. Muhammad Jamal Khan

DEPARTMENT OF PLANT PROTECTION FACULTY OF CROP PROTECTION SCIENCES THE UNIVERSITY OF AGRICULTURE, PESHAWAR-PAKISTAN FEBRUARY, 2015

TABLE OF CONTENTS

ABBREVIATIONS...... i

LIST OF TABLES...... ii

LIST OF FIGURES...... vi

LIST OF APPENDICES...... vii

ACKNOWLEDGEMENTS...... x

ABSTRACT ...... xi

CHAPTER - 1: GENERAL INTRODUCTION...... 1

1.1. and Interaction...... 1 1.2. Importance of Apple ...... 1 1.3. World Apple Production ...... 2 1.4. Codling moth as a Serious ...... 3 1.5. Population dynamics of C. pomonella ...... 4 1.6. Molecular Studies of C. Pomonella ...... 5 1.7. Chemical Control and Resistance of C. pomonella to Insecticides ...... 6 1.8. Habitat manipulation for the management of C. pomonella ...... 7 1.9. Importance of the study ...... 8 1.10. OBJECTIVES ...... 9 LITERATURE CITED...... 10 CHAPTER - 2: POPULATION DYNAMICS OF CYDIA POMONELLA (L) IN SWAT VALLEY...... 10

2.1. INTRODUCTION ...... 15 2.2. REVIEW OF LITERATURE ...... 17 2.3. MATERIALS AND METHODS ...... 21 2.3.1. Study parameters and location ...... 21 2.3.2. Statistical Analysis ...... 22 2.4. RESULTS ...... 24 2.4.1. Meteorological parameters and C. pomonella population at Matta Swat during years 2012 and 2013 ...... 24 2.4.2. The correlation matrix of C. pomonella population with weather parameters over a period of time at Matta during year 2012 ...... 26 2.4.3. The correlation matrix of C. pomonella population with weather parameters over a period of time at Matta during year 2013 ...... 28

2.4.4. Meteorological parameters and C. pomonella population at Madyan Swat during year 2012 and 2013 ...... 29 2.4.5. The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2012 ...... 32 2.4.6. The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2013 ...... 33 2.4.7. Meteorological parameters and C. pomonella population at Kalam Swat during year 2012 and 2013 ...... 35 2.4.8. The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2012 ...... 38 2.4.9. The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2013 ...... 39 2.4.10. The correlation matrix of C. pomonella population with weather parameters over a period of time in Swat during year 2012-13 ...... 41 2.5. DISCUSSION ...... 44 2.5.1. Meteorological parameters and C. pomonella population at Matta, Madyan and Kalam Swat during year 2012 and 2013 ...... 44 2.5.2. The correlation matrix of codling moth C. Pomonella population with weather parameters over a period of time in Swat during the years 2012 and 2013 ...... 45 2.6. CONCLUSIONS...... 48 2.7. RECOMMENDATIONS ...... 48 LITERATURE CITED...... 49 CHAPTER -3: MOLECULAR CHARACTERIZATION OF THE CYDIA POMONELLA IN SWAT VALLEY...... 49

3.1. INTRODUCTION ...... 52 3.2. REVIEW OF LITERATURE ...... 56 3.3. MATERIALS AND METHODS ...... 61 3.3.1. C. pomonella Specimen collection ...... 61 3.3.2. Genomic DNA Extraction...... 61 3.3.3. Polymerase Chain Reaction and Gel Electrophoresis ...... 62 3.3.4. Statistical Analysis ...... 62 3.4. RESULTS ...... 64 3.4.1. Primer B12...... 64 3.4.2. Primer D16 ...... 65 3.4.3. Primer C04 ...... 66 3.4.4. Primer C13 ...... 67 3.4.5. Primer B04 ...... 68 3.4.6. Primer H02 ...... 69

3.4.7. Primer E09 ...... 71 3.4.8. Primer F01 ...... 72 3.4.9. Primer A19 ...... 73 3.4.10. Primer D08 ...... 74 3.4.11. Primer G11 ...... 75 3.4.12. Primer F07 ...... 76 3.4.13. Primer E18 ...... 78 3.4.14. Primer H14 ...... 78 3.4.15. Primer B15 ...... 80 3.4.16. Primer C16 ...... 81 3.4.17. Primer C02 ...... 82 3.4.18. Primer H03 ...... 83 3.4.19. Primer F04 ...... 84 3.4.20. Primer H13 ...... 85 3.4.21. Primer G02 ...... 86 3.4.22. Nei’s unbiased measures of genetic identity and genetic distance ...... 88 3.4.23. RAPD primers used for molecular characterization of C. pomonella at Swat during the year 2012-2013 ...... 89 3.5. DISCUSSION ...... 92 3.6. CONCLUSIONS...... 96 3.7. RECOMMENDATIONS ...... 96 LITERATURE CITED...... 97 CHAPTER-4: MANAGEMENT OF C. POMONELLA (LEPIDOPTERA; TORTRICIDAE)...... 97

4.1. INTRODUCTION ...... 102 4.1.1. Use of Insecticides for the Management of Cydia pomonella ...... 102 4.1.2. Impact of Intercropping on Biological Control Agents and Pest ...... 104 4.1.3. Biological Control Agents of C. pomonella ...... 105 4.2. REVIEW OF LITERATURE ...... 108 4.2.1. Use of Insecticides for the Management of C. pomonella ...... 108 4.2.2. Impact of Intercropping on Biological Control Agents and Pest ...... 109 4.2.3. Biological Control Agents Associated with C. pomonella ...... 111 4.3. EXPERIMENT-1: MANAGEMENT OF C. POMONELLA THROUGH SELECTED NOVEL PESTICIDES ...... 114 4.3.1. MATERIALS AND METHODS ...... 114 4.3.2. RESULTS ...... 118 4.3.4. DISCUSSION ...... 127

4.3.5. CONCLUSIONS...... 133 4.3.6. RECOMMENDATIONS ...... 133 4.4. EXPERIMENT-2: MANAGEMENT OF C. POMONELLA THROUGH INTERCROPPING ...... 134 4.4.1. MATERIALS AND METHODS ...... 134 4.4.2. RESULTS ...... 137 4.4.3. DISCUSSION ...... 146 4.4.4. CONCLUSIONS...... 152 4.4.5. RECOMMENDATIONS ...... 152 4.5. EXPERIMENT- 3: SYNCHRONIZED COMPARISON OF THE BEST INSECTICIDE AND INTERCROP ...... 153 4.5.1. MATERIALS AND METHODS ...... 153 4.5.2. RESULTS ...... 156 4.5.3. DISCUSSION ...... 162 4.5.4. CONCLUSIONS...... 167 4.5.5. RECOMMENDATIONS ...... 168 OVERALL CONCLUSION & RECOMMENDATIONS ...... 169 FUTURE CHALLENGES ...... 171 SUMMARY ...... 172 LITERATURE CITED...... 172 APPENDICES ...... 186

ABBREVIATIONS

AFLP Amplification Fragment Length Polymorphisms

ANOVA Analysis of Variance

Bt thuringiensis

CM Codling Moth

CpGv Cydia pomonella Granular

DBM Diamond Back Moth

DNA Deoxyribo Nucleic Acid dNTP Deoxiribos Nucleotide Triphosphate

EDTA Ethylene Diamine Tetra Acetic acid

IBGE Institute of Bio-Technology and Genetic Engineering

IGR Growth Regulator

IPM Integrated Pest Management

PCR Polymerase Chain Reaction

RAPD Randomly Amplified Polymorphic DNA

RCBD Randomized Complete Block Design

RF Rainfall

RFLP Randomly amplified Fragment Length Polymorphism

RH Relative Humidity

SE Standard Error

SMW Standard Meteorological Week

TB Tris Borate

TE Tris EDTA

UPGMA Unweighted Pair Group of Arithmetic Means

LIST OF TABLES

Table-2.1: Standard Meteorological Weeks (SMW)...... 23

Table-2.2: Weekly averaged weather parameters and C. pomonella population on apple at Matta during 2012 & 2013...... 25

Table-2.3: The correlation matrix of Cydia pomonella population with weather parameters over a period of time at Matta during year 2012...... 27

Table-2.4: The correlation matrix of C. pomonella population with weather parameters over a period of time at Matta during year 2013...... 29

Table-2.5: Multiple regression equations for C. pomonella population at Matta during year 2012 & 2013...... 29

Table-2.6: Weekly averaged weather parameters and C. pomonella population on apple at Madyan during year 2012 & 2013...... 31

Table-2.7: The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2012...... 33

Table-2.8: The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2013...... 34

Table-2.9 Multiple regression equations for C. pomonella population at Madyan during year 2012 and 2013...... 35

Table-2.10: Weekly averaged weather parameters and C. pomonella population on apple at Kalam during year 2012 & 2013...... 37

Table-2.11: The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2012...... 39

Table-2.12: The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2013...... 41

Table-2.13: Multiple regression equations for C. pomonella population at Kalam during year 2012 and 2013...... 41

Table-2.14: The correlation matrix of C. pomonella population with weather parameters over a period of time in Swat during year 2012 and 2013...... 43

Table-3.1: Name, sequence, size and molecular weight of RAPD primer used for molecular characterization of C. pomonella...... 63

Table-3.2 Gene frequency, diversity and Shannon information index for RAPD primer GLB-12...... 64

Table-3.3 Gene frequency, diversity and Shannon information index for RAPD primer D16...... 65

Table-3.4 Gene frequency, diversity and Shannon information index for RAPD primer C04...... 66

Table-3.5 Gene frequency, diversity and Shannon information index for RAPD primer C13...... 68

Table-3.6 Gene frequency, diversity and Shannon information index for RAPD primer B04...... 69

Table-3.7 Gene frequency, diversity and Shannon information index for RAPD primer H02...... 70

Table-3.8 Gene frequency, diversity and Shannon information index for RAPD primer E09...... 71

Table-3.9 Gene frequency, diversity and Shannon information index for RAPD primer F01...... 72

Table-3.10 Gene frequency, diversity and Shannon information index for RAPD primer A19...... 73

Table-3.11 Gene frequency, diversity and Shannon information index for RAPD primer D08...... 75

Table-3.12 Gene frequency, diversity and Shannon information index for RAPD primer G11...... 76

Table-3.13 Gene frequency, diversity and Shannon information index for RAPD primer F07...... 77

Table-3.14 Gene frequency, diversity and Shannon information index for RAPD primer E18...... 78

Table-3.15 Gene frequency, diversity and Shannon information index for RAPD primer H14...... 79

Table-3.16 Gene frequency, diversity and Shannon information index for RAPD primer B15...... 80

Table-3.17 Gene frequency, diversity and Shannon information index for RAPD primer C16...... 82

Table-3.18 Gene frequency, diversity and Shannon information index for RAPD primer C02...... 83

Table-3.19 Gene frequency, diversity and Shannon information index for RAPD primer H03...... 83

Table-3.20 Gene frequency, diversity and Shannon information index for RAPD primer F04...... 85

Table-3.21 Gene frequency, diversity and Shannon information index for RAPD primer H13...... 86

Table-3.22 Gene frequency, diversity and Shannon information index for RAPD primer G02...... 87

Table-3.23 Nei’s unbiased measures of genetic identity (Above diagonal) and genetic distance (Below diagonal) for C. pomonella populations collected from three geographically distant region Swat based on 21 RAPD primers analysis...... 88

Table-3.24 Mean Gene frequency, diversity and Shannon information index for RAPD primers used for molecular characterization of C. pomonella at Swat during the year 2012-13...... 91

Table-4.1: Treatments applications with respective doses and active ingredients for C. pomonella management during the year 2012 and 2013...... 117

Table-4.2: Mean fruit drop of apple after application of different insecticides during the year 2012 and 2013...... 118

Table-4.3: Mean percent infestation of apple fruit caused by C. pomonella application of different insecticides during the year 2012 and 2013...... 120

Table-4.4: Mean parasitism of Ascogester quadridentata after application of different insecticides during the year 2012 and 2013...... 122

Table-4.5: Mean parasitism of Hyssopus pallidus after application of different insecticides during the year 2012 and 2013...... 123

Table-4.6: Biological efficacy of different insecticides for the control of apple codling moth Cydia pomonella during the year 2012 and 2013...... 124

Table-4.7: Comparison of the means values for the data regarding apple yield (kg/tree) at the time of harvest after application of different insecticides during the year 2012 and 2013...... 125

Table-4.8: Treatment combinations for intercropping in the apple orchard during the year 2012 and 2013...... 136

Table-4.9: Mean dropped of apple fruit in apple orchard having different intercropping during the year 2012 and 2013...... 138

Table-4.10: Mean percent infestation of apple fruit caused by C. pomonella in apple orchard having different intercrops during the year 2012 and 2013...... 139

Table-4.11: Mean C. pomonella catches in apple orchard having different intercrops during the year 2012 and 2013...... 141

Table-4.12: Mean percent parasitism of A. quadridentata in apple orchard having different intercrops during the year 2012 and 2013...... 142

Table-4.13: Mean percent parasitism of H. pallidus in apple orchard having different intercrops during the year 2012 and 2013...... 143

Table-4.14: Comparison of the mean values for the data regarding yield (kg/tree) at the time of harvest in apple orchard having different intercrops during the year 2012 and 2013...... 144

Table-4.15: Treatments combinations of insecticide and intercropping for management of C. pomonella during the year 2013...... 155

Table-4.16: Mean fruit drop in apple orchard for different treatments during the year 2013...... 156

Table-4.17: Mean infestation of apple fruit caused by C. pomonella in apple orchard for different treatments during the year 2013...... 157

Table-4.18: Mean C. pomonella catches through pheromone traps in apple orchard for different treatments during the year 2013...... 158

Table-4.19: Mean percent parasitism of A. quadridentata in apple orchard for different treatments during the year 2013...... 158

Table-4.20: Mean percent parasitism of H. pallidus in apple orchard having different treatments during the year 2013...... 159

Table-4.21: Comparison of the mean values for the data regarding yield (kg/tree) at the time of harvest in apple orchard having different treatments during the year 2013...... 160

LIST OF FIGURES

Fig. 1.1. Worldwide distribution of C. pomonella (Courtisy: Published by Iowa State University USA, 2001)...... Error! Bookmark not defined.

Fig. 2.1. Population dynamics of C. pomonella in Swat during 2012 & 2013...... 26

Fig. 3.1: Electrophoreogrm showing PCR based amplification products of Codling moth Cydia pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers B-12, D-16 and C-04...... 67

Fig.3.2. Electrophoreogrm showing PCR based amplification products of Codling moth Cydia pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers C-13, B-04 and H-2...... 70

Fig. 3.3: Electrophoreogrm showing PCR based amplification products of Codling moth Cydia pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers E-19, F-01 and A-19...... 74

Fig.3.4. Electrophoreogrm showing PCR based amplification products of Codling moth C. pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers D-08, G-11 and F-07...... 77

Fig.3.5. Electrophoreogrm showing PCR based amplification products of C. pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers E-18, H-14 and B-15...... 81

Fig.3.6. Electrophoreogrm showing PCR based amplification products of C. pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers C-16, C-02 and H-03...... 84

Fig.3.7. Electrophoreogrm showing PCR based amplification products of C. pomonella population collected from three regions (Matta, kalam and Madyan) of District Swat by using RAPD primers F-04, H-13 and G-02...... 88

Fig. 3.8. Dendrogram constructed on the basis of similarity index among three populations of C. pomonella (Matta, Madyan and Kalam) based on RAPD data using UPGMA and Nei’s genetic index...... 89

Fig.4.1: Experimental design/Layout of the Experiment in Matta Swat...... 117

Fig. 4.2. Mean percent parasitism of A.quadridentata and H. pallidus after insecticides application during 2012 and 2013...... 121

LIST OF APPENDICES

Appendix-1: Analysis of variance table for linear multiple regression of means for C. pomonella at Matta Swat during the year 2012...... 186

Appendix-2: Analysis of variance table for linear multiple regression of means for C. pomonella at Matta Swat during the year 2013...... 186

Appendix-3: Analysis of variance table for linear multiple regression of means for C. pomonella at Madyan Swat during the year 2012...... 186

Appendix-4: Analysis of variance table for linear multiple regression of means for C. pomonella at Madyan Swat during the year 2013...... 186

Appendix-5: Analysis of variance table for linear multiple regression of means for C. pomonella at Kalam Swat during the year 2012...... 186

Appendix-6: Analysis of variance table for linear multiple regression of means for C. pomonella at Kalam Swat during the year 2013...... 187

Appendix-7: Analysis of variance table for mean fruit drop after insecticides application during year 2012...... 187

Appendix-8: Analysis of variance table for mean percent infestation after insecticides application during year 2012...... 187

Appendix-9: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata after insecticides application during year 2012...... 187

Appendix-10: Analysis of variance table for mean percent parasitism of Hyssopus pallidus after insecticides application during year 2012...... 187

Appendix-11: Analysis of variance table for average yield of apple in kg/tree after insecticides application during year 2012...... 188

Appendix-12: Analysis of variance table for mean fruit drop after insecticides application during year 2013...... 188

Appendix-13: Analysis of variance table for mean fruit infestation after insecticides application during year 2013...... 188

Appendix-14: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata after insecticides application during year 2013...... 188

Appendix-15: Analysis of variance table for mean percent parasitism of Hyssopus pallidus after insecticides application during year 2013...... 188

Appendix-16: Analysis of variance table for average yield of apple in kg/tree after insecticides application during year 2013...... 189

Appendix-17: Combined analysis of variance table for mean fruit drop in apple orchard after insecticides application during year 2012 & 2013...... 189

Appendix-18: Combined analysis of variance table for mean percent infestation in apple orchard after insecticides application during year 2012 & 2013...... 189

Appendix-19: Combined analysis of variance for mean percent parasiotism A. quadridentata in apple orchard after insecticides application during year 2012 & 2013...... 189

Appendix-20: Combined analysis of variance table for mean percent parasiotism H. pallidus in apple orchard after insecticides application during year 2012 & 2013...... 190

Appendix-21: Combined analysis of variance table for average yield of apple in kg/tree after insecticides application during year 2012 & 2013...... 190

Appendix-22: Analysis of variance table for mean fruit drop in apple orchard having different intercrops during year 2012...... 190

Appendix-23: Analysis of variance table for mean percent infestation in apple orchard having different intercrops during year 2012...... 190

Appendix-24: Analysis of variance table for mean moth catches in apple orchard having different intercrops during year 2012...... 190

Appendix-25: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata in apple orchard having different intercrops during year 2012...... 191

Appendix-26: Analysis of variance table for mean percent parasitism of Hyssopus pallidus in apple orchard having different intercrops during year 2012...... 191

Appendix-27: Analysis of variance table for average yield of apple in kg/tree having different intercrops in apple orchard during year 2012...... 191

Appendix-28: Analysis of variance table for mean fruit drop in apple orchard having different intercrops during year 2013...... 191

Appendix-29: Analysis of variance table for mean percent infestation in apple orchard having different intercrops during year 2013...... 191

Appendix-30: Analysis of variance table for mean moth catches in apple orchard having different intercrops during year 2013...... 192

Appendix-31: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata in apple orchard having different intercrops during year 2013...... 192

Appendix-32: Analysis of variance table for mean percent arasitism of Hyssopus pallidus in apple orchard having different intercrops during year 2013...... 192

Appendix-33: Analysis of variance table for average yield of apple in kg/tree having different intercrops in apple orchard during year 2013...... 192

Appendix-34: Combined analysis of variance table for mean fruit drop in apple orchard different intercrops during year 2012 & 2013...... 192

Appendix-35: Combined analysis of variance table for mean percent infestation in apple orchard different intercrops during year 2012 & 2013...... 193

Appendix-36: Combined analysis of variance table for mean percent parastism of A. quadridentata in apple orchard having different intercrops during year 2012 & 2013...... 193

Appendix-37: Combined analysis of variance table for mean percent parasitism of H. pallidus in apple orchard having different intercrops during year 2012 & 2013...... 193

Appendix-38: Combined analysis of variance table for mean moth catches in apple orchard having different intercrops during year 2012 & 2013...... 193

Appendix-39: Combined analysis of variance table for yield (kg/tree) in apple orchard having different intercrops during year 2012 & 2013...... 194

Appendix-40: Analysis of variance table for mean fruit drop in apple orchard having different treatments during year 2013...... 194

Appendix-41: Analysis of variance table for mean percent infestation in apple orchard having different treatments during year 2013...... 194

Appendix-42: Analysis of variance table for mean moth catches in apple orchard having different treatments during year 2013...... 194

Appendix-43: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata in apple orchard having different treatments during year 2013...... 194

Appendix-44: Analysis of variance table for mean percent parasitism of Hyssopus pallidus in apple orchard having different treatments during year 2013...... 195

Appendix-45: Analysis of variance table for average yield of apple in kg/tree having different treatments in apple orchard during year 2013...... 195

ACKNOWLEDGEMENTS

All praises to Almighty "ALLAH" alone, the most Merciful and the most Compassionate and His Holy Prophet "Muhammad" (PBUH), the most perfect and exalted ever born on this earth, who is, forever a symbol of guidance and knowledge for the humanity.

This whole study was sponsored by Higher Education Commission of Pakistan (HEC) under indigenous Scholarship PIN Code 106-1703-Av6-084 and a six month foreign visit under IRSIP scheme to the University of Queensland Australia, I appreciate and acknowledge the support and on time response of HEC throughout the study period.

I wish to express my gratitude to my supervisor Prof. Dr. Ahmad -Ur- Rahman Saljoqi, Professor, Department of Plant Protection, The University of Agriculture Peshawar, for his relevant guidance, encouragement and cooperation during my research work.

Special thanks to Prof. Dr. Abid Farid, University of Haripur, who has provided his considerable talent and ever present encouragement of this study. Heart felt thanks are expressed for his painstaking efforts to improve the clarity and readability of the study.

I fell highly indebted to express my thanks to Prof. Dr. Imtiaz Ali Khan, Department of Entomology, for his cooperation during this study, Prof. Dr. Yousaf Hayat for his help in statistical analysis and Dr. Ijaz Ali (IBGE) who fully cooperate and assisted me in molecular studies.

Thanks are offered to Prof. Dr. Farman Ullah, Chairman, Department of Plant Protection, The University of Agriculture, Peshawar for his affections and sincere help during the study.

I would like to express gratitude and thanks to my friends Dr. Bashir Ahmad, Dr. Hayat Badshah, Dr. Muhammad Naeem (ARI-N) and Dr. Ahmad Khan who provide every support during my research work and arrangements.

I also thank to my affectionate parents, family members, brothers and sisters for their moral support which they extended to me during my study.

Hayat Zada

POPULATION DYNAMICS, MOLECULAR CHARACTERIZATION AND MANAGEMENT OF APPLE CODLING MOTH, CYDIA POMONELLA (LINNAEUS) (LEPIDOPTERA; TORTRICIDAE) BY Hayat Zada and Ahmad-Ur-Rahman Saljoqi Department of Plant Protection, The University of Agriculture, Peshawar-Pakistan

ABSTRACT

The studies were carried out regarding population dynamics, molecular characterization and management of apple codling moth (Cydia pomonella L.) (Lepidoptera; Tortricidae) at District Swat during 2012-13. First adults of C. pomonella were trapped during 17th to 18th standard meteorological week (SMW) at Matta, Madyan and Kalam. The first peak population was recorded during 25th to 30th SMW and second peak population were observed during 31st to 35th SMW, so maximum two peak populations were observed during studies. The correlation matrix between C. pomonella population and weather parameters disclosed that mean maximum and minimum temperature exhibited a highly significant (p<0.01) positive correlation with C. pomonella population build up. Total rainfall and relative humidity (morning and evening) had non- significant negative effect on the population build up of C. pomonella. Regression analysis explained 68.8-83.4% variability due to meteorological parameters in the population dynamics of C. pomonella at all three areas. Molecular characterization of the C. pomonella through RAPD markers explained higher genetic distances among the isolates from Kalam and Madyan (97.9%) as compared to those from Matta and Madyan (35.6%). Likewise, higher genetic similarity (70.1%) was resided by the C. pomonella population at Matta and Madyan, while the low level of identity (37.6%) were examined in isolates from Madyan and Kalam. These studies about genetic variation among C. pomonella populations may help for its efficient management. The efficacy of different novel insecticides were tested against C. pomonella and Match insecticides proved very effective for the management of C. pomonella during current studies in reducing the pest infestation (23.1%). The said chemical proved safer for its two associated larval parasitoids Ascogaster quadridentata (26.4%) and Hyssopus pallidus (27.6%) compared to other chemicals. Maximum average yield (86.81±0.42 kg/tree) was also attributed to Match which was significantly higher than all the treatments. Habitat manipulation through Trifolium (Trifolium alexandrinum) (Fabacae) intercropped in the apple orchard had a profound effect on the fruit drop (2.87), percent infestation (57.2%), biological control agents and yield of the orchard. The said treatment was found comparatively the most appropriate combination of those tested for the attraction of its associated parasitoids A. quadridentata (40.1%) and H. pallidus (30.1%) and increasing the yield (76.62±1.11 kg/tree) of apple fruit. The combined effect of intercropping trifolium followed by application of Match insecticide proved highly superior in reducing the occurrence of C. pomonella and enhancing and sustaining the associated parasitoids A. quadridentata (32.8%) and H. pallidus (34.7%). The said treatment was also having an insightful impact in curtailing mean fruit drop (2.07), percent infestation (36.4%) and adult moth catches (1.30) through pheromone traps. These findings further confirmed that the said treatment afforded high average yield (94.75±0.62 kg/tree) and the losses avoided were 39.1% and gain in yield due to control measures were 64.1%.

CHAPTER - 1: GENERAL INTRODUCTION

1.1. Insects and Plants Interaction

Studies that contribute towards elucidating insect-plant relationships are of crucial relevance for various reasons. The taxa of plants and insects are the most diverse groups, representing 50% of all known multicellular (Strong et al., 1984). Plants and plant feeding herbivores are considered to largely account for the present natural diversity of plants and and they are therefore central to biodiversity conservation (Schoonhoven et al., 2005). Another aspect of general concern is pest associated yield losses in agriculture, estimated at 14% of the total agricultural production (Oerke et al., 1994). Besides direct loss due to herbivores, insects are vectors of plant diseases. In the context of the predicted increase of the population to 10 billion by the year 2050, insects may have increased significance (Schoonhoven et al., 2005).

An is determined as a pest when it interferes with for the same resources (Pedigo, 2006). Particularly this is most noticeable in agricultural production systems where cause serious economic losses (Pimentel, 1997). The term pest is sometimes not only constricted to arthropods, but also to plant parasitic , microbial and viral plant pathogens, weeds and vertebrates (Prokopy and Croft, 1994). The various structures of an apple tree provide food or shelter for a large number of arthropod pests (Schoonhoven et al., 2005). Direct pests of fruits have the most visible impact on yield because only slight infestation makes the product unmarketable (Beers et al., 2003).

1.2. Importance of Apple

Swat valley is famous for apple fruit in Pakistan and is located at 34034' to 350 55' of latitude North and 720 08' to 720 50' of longitude East in the North West of Khyber Pakhtunkhwa at an altitude of 1136 meters from the sea level and is endowed with rich natural resources such as fertile land, rivers and varieties of fruits such as apple, pear, , apricot, plum and persimmon. The annual rainfall is 1000-1200 mm and temperature ranges from -2 to 37 0C (Barinova et al.,2013).

There is no other fruit in temperate climates of this region that is so universally appreciated and extensively cultivated like apple. Many ancient myths and

1 stories describe apple as a symbol of life, immortality, love and fertility (Laudert, 1998). In the middle ages, apple was used as a sign of terrestrial power for emperors (Laudert, 1998). Nowadays, the symbol of apple has changed from this rather mythological meaning to representing commercial product (Laudert, 1998). In advertisements for cosmetics the apple stands for health. The city of New York is well known as 'Big Apple'. The computer company Apple Macintosh uses apple as a symbol for global networks.

Apples as fruit are admired by all humans because of the many ways that they can be consumed (e.g. fruit, juice, vinegar, apple crumble and cake) and because of their convenience and durability (Morgan and Richards, 1993). Last but not the least, what would William tell (drama by Friedrich Schiller, 1804) be without apple, and what would Switzerland be without William Tell? (Laudert, 1998). The common domesticated apple is putatively an inter specific hybrid complex, usually designated domestica Borkh. (Luby, 2003). are members of the Malus Miller, which is placed in the subfamily Maloideae of the family Rosaceae. Pears, quinces and hawthorns are further members of the Maloideae. The origin and ancestry of the M. domestica complex remain unknown. However, (Ledeb.) is hypothesized as the key species at its origin (Juniper et al., 1999). M. sieversii is widespread in the mountains of central Asia. (Brown, 1992).

According to Luby, (2003) apple is very important for health point of view and comprised Potassium and Phosphorus in a large quantity that help in controlling the blood pressure and ultimatley decreasing heart diseases. Further, it also contain vitamin 'B' Complex which is useful for life.

1.3. World Apple Production

Pakistan is world’s 10th largest country with 1.335 million tones of apple production. World’s production is 64 million tons in which Belgium, France, Italy, America and Chilly are prominent and has been increasing since the Second World War (O'Rourke, 2003), mainly due to the expansion of production in China and the successful spread into warmer climates (Luby, 2003).

The estimated world production of apples for the year 2006, was 64 million tones (http://faostat.fao.org), ranking in 4th position behind bananas (71 million

2 tones), grapes (69 million tones) and oranges (65 million tones). With 26 million tone, China produces 40% of the world production. China is followed by the USA (4.6 million tones). China’s apple production rapidly increased with the introduction of the cultivar 'Fuji'. It is believed that apple production in China could exceed 35 million tones in 2010 as many of the trees are not yet at full bearing maturity (O'Rourke, 2003).

1.4. Codling moth as a Serious Pest

Many lepidopterans, especially tortricids, attack apple fruit. The codling moth (Cydia pomonella Linnaeus.) is considered as the key species in apple orchards worldwide and infestation levels have even increased within the last years (Blommers, 1994; Prokopy and Croft, 1994; Dorn et al., 1999). Besides apples, it attacks the fruits of pears, quinces, apricots, and walnuts (Alford, 2007). The damage which may be up to 20 to 90% is caused by the larvae, which burrow into the fruit to feed on the flesh and seeds. A small red-ringed cavity hole filled with dry frass is an indication for larval penetration (Baggiolini et al., 1992). After few weeks, and passing through five instars, the mature larvae leave the fruit to spin a cocoon for pupation in the crackes and cravices (Geier, 1963). In northern Europe, usually the last larval instar overwinters and pupation occurs in spring. Five to six generations have been recorded in warmer regions (Audemard, 1991). The first appear in spring (Beers et al., 1993). After mating, eggs are laid singly on leaves and fruits during warm evenings (above 15°C). The new larvae hatch after 10-14 days.

C. pomonella is a severe pest of apple crops throughout the world. Originating in Kazakhstan, the C. pomonella has spread to all temperate regions where apples are grown except for Japan, parts of China, India, Pakistan and Western Australia (Fig. 1.1, Blue colour shows the presence of C. pomonella) (Pedigo, 2006). In 1750, C. pomonella was first recorded in New England, USA. By 1868, it was present throughout Ontario and by 1905, even it is present in the west coast of Canada.

C. pomonella commonly infesting apple and pear, but also observed in, quince, plum, apricot, peach, hawthorm, walnut, cherry and crabapple. While not all varieties of apple are equally susceptible to attack by C. pomonella, none is resistant (Cutright and Morrison, 1935). C. pomonella is considered the "key" insect pest in most apple-growing regions. Damage is inflicted as a larva burrows into the apple

3 fruit, eating seeds and vacating the fruit thereafter. The hits are left with holes surrounded by frass, making them unmarketable and unacceptable for the consumers. Even if first instar larvae begin but do not continue feeding on the fruit, they leave superficial penetrations (stings), consequesntly apple will be downgraded. Damage to the hit as a result of larval feeding also renders the apples more susceptible to secondary infestation. Damage from C. pomonella can be extensive. In untreated orchards with more than one generation of this moth 75-95% of the losses has been recorded. Major efforts to exterminate C. pomonella using the sterile insect technique (Dyck and Gardiner, 1992; Brown, 1992) or pheromone based mating disruption are currently underway. Biological control agents could serve as important components in an integrated management system for C. pomonella (Brown, 1992) when organophosphates are replaced by more benign management techniques.

1.5. Population dynamics of C. pomonella

Population dynamics of C. pomonella has been studied by various authors e.g. different aspects of the population dynamics of C. pomonella (Audemard, 1991). Population dynamics of C. pomonella was simulated by using mathematical methods (Lischke, 1990 and 1992). Other studies have been carried out to verify the fecundity and mortality of the various life stages of the C. pomonella as an important part of the modeling of the population (Ferro et al., 1975).

Pheromone traps are one of best effective monitoring and sampling tools for flying adult lepidopterious insects. The use of sex pheromones for monitoring insect pests is recently being used in many countries. Several entomologist and scientists has been reported that pheromones are very helpful for determining seasonal adults moth activity of pests species. (Tamhankar et al., 1989; Singh and Sachan, 1991; Patil et al., 1992). Data/information taken through pheromone trap collections in any locality for a long period of time can be used for development of models to predict the seasonal pests incidence for the effective management of that pest.

Before the study of Shaffer and Gold (1985), no researcher worked recording population dynamics and phenology of this pest. They presented a generalized model of both numbers of moths and phenology corelating with temperature and other environmental factors. They presented in their study a generalized models of insect population dynamics, together with details of its parameterization and its evaluation

4 for C. pomonella in apple orchard with close relation to weather parameters (Shaffer and Gold, 1985). The development and survival of C. pomonella in apple orchard was tested to compare C. pomonella development in organic and traditionally managed apples, and to determined the impact of abiotic factors on adults flights (Hansen, 2002).

1.6. Molecular Studies of C. Pomonella

It has been reported that C. pomonella populations differentiated in to many strains with different characterictics of their biology and physiological relation due to change in climatic conditions and indiscrimainate use of pesticides (Franck et al., 2010). Bues et al. (1995) studies genetic structure of C. pomonella populations by using allozyme markers. Further, Timm et al. (2006) used AFLP markers and found out substaintail differences among population of C. pomonella at small and nearer locations. Nonetheless, studies showed that isoenzyme polymorphism is low level as molecular marker (Thaler et al., 2008).

Timm's et al. (2006) study was corroborated by Thaler et al. (2008) who also used AFLP markers to study the molecular phylogeny and genetic structure of C. pomonella. Franck et al. (2007) used these microsatellites to estimate the level of genetic variation found among C. pomonella populations from France. The application of mitochondrial genetic markers has led to identification of recent evolutionary history of C. pomonella from the Pleistocenic splitting of the C. pomonella into two refugial clades to the interbreeding of mitochondrial haplotypes in the Holocene and finally to human-aided complete intermixing and splitting of populations into many locally adapted populations (Thaler et al., 2008). Amazingly, despite the high polymorphism of microsatellite loci, the results showed low genetic variations among populations and a marginal effect of insecticide treatments on the allelic richness of C. pomonella. Recently, Franck et al. (2005) and Zhou et al. (2005) isolated more applicable co-dominant microsatellite markers from C. pomonella. Likewise, low genetic variation was recorded among populations sampled in neglected orchards and production orchards in Chile (Fuentes-Contreras et al., 2008).

Franck and Timm (2010) used male adult moths for genetic analyses collected from pheromone traps from two locations of apple orchards situated at a distance of 30 km away from each other and low genetic distances among the population.

5

Pajac et al. (2011) also used microsatellite markersfor studying genetic distances among the population of adults male moth in Croatia and found low level of molecular variation among the population (70-96%). However, high level of genetic variation was found among the adult male moth population sampled on the same host within distance of 10 km using microsatellite markers as Franck et al. (2005) and Zhou et al. (2005).

Deverno et al., (1998) used randomly amplified polymorphic DNA (RAPD) technique to the genetic distances among the population by using PCR amplification of genomic DNA. This technique offer no need of DNA sequences by using random primers and one of the best method and easy method to find out diversity within and between the population. Its cost is low and developing large number of DNA in a small time (Bardakci, 2001; Delaat et al., 2005). This method can be used for insect phylogeny like finding the genetic variation among the population of closely related species of insects (Benecke, 1998; Lima et al., 2002).

1.7. Chemical Control and Resistance of C. pomonella to Insecticides

Many researchers worldwide have tried to control C. pomonella by a number of pesticides, but effective control could not be achieved because of well known facts using pesticides without considering proper time of application and their impact on the non-target species resulting in many environmental problems. Recently, several researchers have worked and reported that pheromone traps are an effective tool used throughout the world to monitor its population dynamic and suppress the pest population by applying insecticides at right time. Traps baited with synthetic female sex pheromone are widely used to forecast the timing of insecticide sprays against C. pomonella (Ledee et al., 1993).

Malik et al. (2002) provided a bibliographic review of the investigation about C. pomonella control around the world. Control methods generally could be categorized as biological control including mating disruption, sterile insect technique, classical biological control, cultural control, conservational control, chemical control, control based on the molecular studies, encouraging and enhancement of the natural enemies through intercropping, options for the organic control and integrated pest management system. Each technique has its own recompense and demerits ( and Huber, 1991).

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Indiscriminate use of pesticides are not only harmful to the biotic and abiotic factors of environment but also have adverse effect on biological control agents. So as a result the C. pomonella has developed resistance to different group of chemicals (Sauphanor et al., 2000; Boivin et al., 2001; Bouvier et al., 2001; Brun-Barale et al., 2005). Resistance has also documented in C. pomonella populations from Italy (Ioriatti et al., 2000, 2005).This problem can be overcome by introducing new and safe insecticides for the effective management of this pest. Cross resistance has also been recorded C. pomonella populations in South-Eastern France by Sauphanor and Bouvier (1995) and Sauphanor et al. (2000).

Farming community mostely relying on the used of insecticides for the management of C. pomonella and other pest (Lacey et al., 2008). IPM techiques emphasis more on the use of safe and novel control strategies which is mostly acceptable and feasible for the farmers (Ciglar, 1998; Maceljski, 2002). Different methods of control such as intercropping, conservation biological control and biological control C. pomonella though various biological agents such as , mites, , insects and particularly the parasitoids are very effective for the management of this pest (i.e. parasitic from the families Braconidae and ) (Lacely et al., 2003; Lacey and Unruh, 2005).

1.8. Habitat manipulation for the management of C. pomonella

Beneficial insect diversity can be increased within agro-ecosystem though different methods such as habitat manipulation through intercropping for conservational biological control and potential pest management (Vandermeer, 1989; Theunissen, 1994). Different crops can be manipulated in apple orchard such as as clovers, mustard, , buckwheat etc for the survival of natural enemies and their abundance in the agro-ecosystem (Theunissen, 1994). So polyculture have maximum diversity of natural enemies and will be more stable for the pest and diseases interaction (Altieri and Nicholls, 2004). Beizhou et al. (2011). They also reported that intercroping the apple orchard can significantly cutailed the pest population and natural enemies population will be enhanced. In the diverse system there is complex food web for the pest and natural enemies providing maximum resourses for all the Hence, intercropping the apple orchard with aromatic plants led to

7 improved insect pest management by enhancing the activity of the insect natural enemy community. (Pekaer and Kocourek, 2004; Simon et al., 2007).

1.9. Importance of the study

As no baseline studies was available regarding population dynamics and molecular studies for this insect pest in Pakistan, particularly in Khyber Pakhtunkhwa, this studies will provide basic information in future for researchers and entomologists. In Pakistan, no research has been conducted regarding molecular variation in C. pomonella. This study is the first step to collect genetic information and pattern of genetic diversity and variation among the population of C. pomonella at various altitude and different topographic condition of the major apple growing areas of District Swat. It was expected that if this pest is not properly handled and managed, it will not only caused huge economic losses to the apple growers but in near future, apple orchard will be completely replaced by peach in Swat. Therefore, this research will be of great importance for the farming community of Pakistan.

In view of above background, the current study focuses on to conduct a detailed research work on the management of C. pomonella, using different IPM techniques and their interactions to develop an IPM package for the effective management of C. pomonella for the farming community of the area. The study will determines the assessment of population dynamics, molecular characterization, identification of C. pomonella associated parasitoids and management of C. pomonella in Swat valley with the following main objectives:

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1.10. OBJECTIVES

i. To study population dynamics of C. pomonella in three major apple growing areas having different altitudes and climatic conditions including Matta, Madyan and Kalam of Swat Valley.

ii. Molecular characterization of the C. pomonella collected from above target areas having different altituds of Swat Valley. iii. To know the effect of management techniques including safe insecticides and intercropping individually and their interactions against the C. pomonella and their associated available natural enemies. iv. Evaluation of best insecticide and intercrop individually and their interaction for the effective management of this pest to have a best IPM package.

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CHAPTER - 2: POPULATION DYNAMICS OF CYDIA POMONELLA (L) IN SWAT VALLEY

2.1. INTRODUCTION

The C. pomonella is the most widely distributed pest of cultivated pome fruits and walnuts in the world, except in Japan and in the western part of Australia where it has been eliminated, being a key pest in most situations. Its origin is Eurasian. The most important C. pomonella hosts are apple and even other Prunus species like sweet cherry and almonds (Barnes, 1991).

Pheromone traps present one of the best and effective monitoring and sampling device for flying adult male lepidopterious moth especially C. pomonella. The use of sex pheromones for monitoring insect pests has been introduced recently. It has been reported by several workers that pheromone traps can be very efficient for determining seasonal moth activity of pest species (Tamhankar et al., 1989; Singh and Sachan, 1991; Patil et al., 1992). On the basis of pheromone trap collections in any area for a fairly long period of time can be used for development of models to predict the seasonal pests infestation. Trap catches may provide meaningful index for estimating population densities of the pests. Trap catches in relation to field infestation and environmental factors (such as temperature, relative humidity and rainfall) are crucially important for decision making process. If a consistent coorelation exists among the catch traps population of pest and environmental factors then the pheromone traps could be used to specify when the apple orchard should apply control measures in IPM program (Dent and Pawar, 1988).

A detailed understanding of the exact relationship between the change in environmental factors and those in the pest population may not only help to predict the pest losses to the in crop, but also help to avoid them through some well timed pest control measure (Aasman, 2001). Abiotic factors like temperature, relative humidity and rainfall play a vital role in the development of insect pests fluctuation of these causes variation in the population of the insect pest.

Trans-8, trans-10-dodecadien-1-01 is a powerful sex attractant of the C. pomonella, has been identified and proposed as the sex pheromone (Roelofs, 1971). This ribber septa when placed in traps has been used for detecting moth emergence and timing pesticide applications with comparable accuracy and less effort than was necessary with previously available methods (Batiste, 1973). Paradis and Comeau (1972) also recorded a good

15 correlation between male captures and the number of damaged apples in orchards of southwestern Quebec. By relating pheromone trap catches of male moths to subsequent larval infestation levels in fruit, several workers studied the use of pheromone traps for estimating C. pomonella population levels in fruit orchards (Wong, 1971) and successfully based seasonal control programs on pheromone catch interpretation (Madsen and Vakenti, 1973).

Among abiotic factors relative humidity (Jindal and Brar, 2005) temperature and rainfall (Singh and Sekhon, 1998) play an important role in population buildup or decline of leaf hoppers. Besides, weather parameters, varietal preference also play significant role in population sizing.

Currently, pheromone traps for monitoring are widely used and they allow an easy pest monitoring for determining treatment need and timing. The most tolerance thresholds are based on weekly and fortnightly male captures in the trap baited sex pheromone. These threshold depends on the fruit species, geographical situation and time of the season. Threshold in apple in Catalonia is 3 moths/trap/week, from petal falling to mid-June and 2 moths/trap/week, from mid June to harvest (Tora et al., 1995)

The current studies were therefore undertaken to know about the population dynamics and trends of the C. pomonella in three major apple growing areas of Swat i.e. Matta, Madyan and Kalam having different altitudes and climatic conditions by adults male moth catches through pheromone traps and correlated them with temperature (maximum, minimum), relative humidity (morning, evening) and total rainfall. Multiple regression models were constructed to determine treatments needed and timing of their applications for its proper and effective management.

16

2.2. REVIEW OF LITERATURE

Different sex pheromones as attractant baits containing insecticides but mostely used for the population dynamic of some pest. This technique are used for so many years for the management of pest. Those insects attracted to pheromones can be easly killed by this methods. Commercial formulations of pheromones for both the pest and natural enemies are now possible in all parts of the world. Most insect pheromones are very expensive due to multy component and precise ratios of components. IPM is the best method for the effective management of garden pest through pheromones traps (Riedl and Croft, 1974).

Ebesu (2003) studied sex pheromone trap as a quantitative sampling device in a biological monitoring scheme for C. pomonella populations in Michigan apple orchards. By correlating seasonal male moth catches to absolute infestation levels at harvest, it was possible to indicate the density response of male moth catches in the pheromone trap. Factors influencing trap efficiency and the relationship of trap catch to adult moth density and the overall seasonal dynamics of C. pornonella. Catch response was non-linear and the trap ceased to be indicative of higher infestation levels when accumulative catch exceeded about 100 moths/trap. Of many factors influencing trap catch size, the number of moth productive trees serviced by a trap (trap/tree ratio) and temperature were shown to be of critical importance.

Mandal et al. (2006) reported the effect of meteorological parameters on population buildup of red mite, T. telarius in okra crop at Bhiar India during summer seasons of 2000-01. Results showed that the activity of the insect confirmed non-significant negative correlation with maximum temperature and positive correlation with minimum temperature. Morning and afternoon relative humidity explained a significant positive correlation with the activity of mites. Regression analysis explained 78-85 percent variability due to meterorological parameters in the population of red .

The effect of weather parameters were studies on the population dynamics of leaf hopper on four cultivars of crop (Sultan, Sadaf, Neelam and Akbar) and the results revealed that highest population was noticed when the temperature was 36.5 oC and relative humidity (R.H) was 68%. The population showed declined at temperature 31.5oC and R.H at 75%. Highest infestation of Chilo partelous (Lepidoptera) was recorded when the 32.5oC R.H at 68% whilst its population was lowest when the temperature reached to 32.5oC and R.H at 50%. These findings confirmed that weather parameters (Temperature

17 and relative humidity) has a substantial effect on the population dynamics of insects pests of maize, while total rainfall showed non significant effect (Zulfiqar et al., 2010).

The influence of weather parameters were also investigated on the incidence and development of Spodoptera litura (Lepidoptera) at five different dates of sowing on three varieties of cotton. The population of S. litura gradually built up from 1st week of April and attained its peak in the 1st week of May. Highest population (25.46%) was noticed at temperature ranges from 26.0°C to 35.1°C, R.H ranges from 62-89% and zero rainfall. Population of S. litura explained positive correlation with R.H, sunshine hours and dewfall, whereas wind velocity showed negative correlation with population build up. This study is essential for the effective pest management of S. litura in cotton. The said research work wil be use for forecasting outbreaks of S. litura and also for its effective management (Selvaraj et al., 2010).

Laskar and Chatterjee (2010) examined pheromone sex attractant "Cue lure" for trapping Bactrocera cucurbitae (Coq.) (Diptera : Tephritidae) round the year for the effective management of this pest. A great variation regarding occurrence of the pest was noticed during the period of studies. The pest population was highest and more active during warm and rainy months (At 25-37oC), however its population was lowest in dry and winter months. Weather parameters such temperature disclosed positive correlation (r) of the fly incidence was noted with minimum (r = +0.7596) and maximum temperature (r = +0.7376), and relative humidity (r = -0.5481). Rainfall showed positive (r = +0.4367) correlation with the fly infestation. Results of the present survey may be utilized in chalking out sustainable pest management strategy in the agro-ecological system under consideration.

Prasannakumar et al. (2011) studied the influence of weather parameters on the pheromone trap catches on different pest of different crops such as fruit borer (Hubner), okra shoot and fruit borer Earias insulana Boisduval, Brinjal Shoot and fruit borer (BSFB) Leucinodes orbonalis Guenee, cutworm Spodoptera litura Fabricius and Diamond back moth (DBM) Plutella xylostella (L.) during rabi, 2007 at Bangalore India. The tomato borer attained its peak population level during 47th sandard meteriological week (SMW) (7.10 moths/trap) and had a positive but non-significant relationship with morning (r = 0.07) and afternoon relative humidity (r = 0.18). Okra shoot and fruit borer attained their peak population (7.52 moths/trap) in 48th SMW and Brinjal shoot

18 and fruit borer (44.13 moths/trap) in 41st SMW. These moth catches had a positive non significant correlation with morning ((r = 0.18 and 0.44) and afternoon relative humidity (r = 0.45 and 0.45) respectively. However, maximum temperature showed statistically significant (p<0.05) correlation with population built up for the siad pest. The population of S. litura was 47.21 moths/trap in 45th SMW and combined effect of all the weather parameters influenced trap catches. Maximum population (31.23 moths/trap) of P. xylostella (Lepidoptera) was observed at 37th SMW with postive correlation with minimum temperature (r = 0.21), morning (r = 0.43) and afternoon relative humidity (r = 0.48) and rainfall (r = 0.32).

Karuppaiah and Sujayanad (2012) investigated that due to climate change, globle average temperature and rainfall pattern has completely changed world wide. These kind of changes definitely ultimatley effect the population dynamics of the insect pest. Among all these abiotic factors, temperature greatly effect the population trend of the insect pest. Thus temperature play an indispensable role for the population dynamics of the pests and as a result change can occured in their population.

Anjali et al. (2012) observed find out the effect of weather parameters on the incidence of major insect pest of brinjal crop. Maximum pest infestation of leaf hopper (Amrasca biguttula Biguttula) was recorded during 52nd SMW while its population was lowest during 12th SMW. Highest infestation of White fly (Bemisia tabaci) was recorded during January (2nd SMW) and lowest was during March (12th SMW). These pests showed significant negative correlation with both maximum and minimum temperature, whilst a positive correlation was noticed with mean relative humidity and total rainfall. The first peack population of shoot and fruit borer, Leucinodes orbonalis Guenee was observed during 6th and 7th SMW and the percent shoot damage was positively related with temperature, wind speed and rainfall whilst negetively effect was observed for relative humidity. These studies showed that weather parameters has a profound effect on the insect pest fluctuation. Thus management technique should be applied from November for the effective management of brinjal pests.

Sharma and Singh (2012) recorded the population of leaf hopper (Amrasca devastans Distant) on processing varieties of potato and its correlation with weather parameters, studies were carried out at, Modipuram in early, main and spring crops. Comparison of mean leaf hopper population during three different crop seasons revealed that early crop planted during September favoured highest development of leaf hoppers

19 followed by main and spring crops. A distinctive varietal difference was observed in appearance and flare up of leaf hoppers. Multiple regression equation based on temperature, relative humidity, wind velocity, sunshine duration and rainfall could explicate leaf hopper population variation from 50-96%.

Eight Bt and five non-Bt cotton genotypes were evaluated against and whitefly and correlated their population fluctuation with weather parameter at Multan during 2010 and 2011. Maximum infestation were observed on Bt genotype whilst non Bt genotype was resistance to the attack of whitefly and thirps. However, in the proceeding year the effect of all these factors were non significant and parallel trend was recorded for thrips population on Bt variety. Minimum temperature showed strong positive correlation with thrips population builtup. Nonethless, whitefly showed significant change in their population on Bt varieties in the experiment. Thus weather parameter play a great role in the population dynamics on insect pest (Akram et al., 2013).

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2.3. MATERIALS AND METHODS

2.3.1. Study parameters and location

These experiments were conducted at three main apple growing areas of Swat Pakistan (340 34' to 350 55' of latitude North and 720 08' to 720 50' of longitude East in the North West of Khyber Pakhtunkhwa) i.e., Matta (350 55' 19.11" of latitude North and 720 30' 37.52" of longitude East), Madyan (350 08' 0.00" of latitude North and 720 32' 0.00" of longitude East) and Kalam (350 28' 41.66" of latitude North and 720 34' 18.61" of longitude East) which were located at an altitude of 920.30, 1333.84 and 2092.30 meters respectively above the sea level.

Population dynamics of C. pomonella were studied throughout two consecutive seasons during the years 2012 and 2013 in the above three areas. Four synthetic pheromone traps were installed per field in four apple orchards of the red delicious variety in the farmer's orchard at all the three places. The size of the apple orchard was 2.5 ha, comprised 250 apple trees and were 12 years old. The experiments were carried out in randomized complete block design (RCBD) and the adult moth catches replicated four times during both the seasons. The plant to plant and row to row distance between apple trees were 5.53 x 5.53 square meters.

Ruber capsule (Septa) having 1 mg codlemone synthetic pheromone for attracting the C. pomonella were suspended in the above upper plastic lid of the trap (Supplied by Shani Enterprise Multan Pakistan). The traps were fixed in the apple orchard randomly in the centre for attracting the male moth at four site in the field at height of 2.5 meters. Each time as traps were checked, C. pomonella were counted and removed on weekly basis. Pheromone traps were only attracting male moth of C. pomonella and attraction and capturing of other insect were insignificant throughout the season. Codlemone-charged rubber septa were replaced twice within a month with fresh septa to insure maximum attraction.

The observations on moth catches, weekly averaged maximum and minimum temperature percent relative humidity (morning, 0300Z and evening 1200Z) and total rainfall were taken on weekly basis. For this experiment Reidl and Croft (1974) procedures were followed with some minor modification suitable to the prevailing conditions of the apple orchard in Swat Pakistan.

Standard agricultural practices were used in the apple orchard i.e., normal weeding, irrigation practices, application of fertilizers and sanitation etc. The apple orchard was allowed with C. pomonella infestation and no control measures were applied. The Standard

21

The data regarding adult moth catches were taken with respect to the Standard meteorological week (SMW) which starts from 1st January - 07th January and so on, while the traps were placed in the apple orchard in the 13th SMW (Table-2.1). The data regarding weather were starts from 14th SMW (Start from April) to 38th SMW (end of September) of Tehsil Matta, Madyan and Kalam were taken from Pakistan meteorological department Swat and was correlated with the trap catches.

2.3.2. Statistical Analysis

All the data regarding population fluctuation and dynamics of C. pomonella catches in the pheromone traps with respect to weather parameters such as, temperature (maximum, minimum), percent relative humidity (morning and evening) and total rainfall of the week were subjected to correlation (Pearson) and linear multiple regression analysis through computer statistical software Statistix (version 8.1.) The coefficient of determination (R2) was also determined through multiple regression models (Bowden and Morris, 1995).

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Table-2.1: Standard Meteorological Weeks (SMW) SMW# Dates SMW# Dates 1 01 Jan - 07 Jan 27 02 Jul - 08 Jul 2 08 Jan - 14 Jan 28 09 Jul - 15 Jul 3 15 Jan - 21 Jan 29 16 Jul - 22 Jul 4 22 Jan - 28 Jan 30 23 Jul - 29 Jul 5 29 Jan - 04 Feb 31 30 Jul - 05 Aug 6 05 Feb - 11 Feb 32 06 Aug - 12 Aug 7 12 Feb - 18 Feb 33 13 Aug - 19 Aug 8 19 Feb - 25 Feb 34 20 Aug - 26 Aug 9* 26 Feb - 04 Mar 35 27 Aug - 02 Sep 10 05 Mar - 11 Mar 36 03 Sep - 09 Sep 11 12 Mar - 18 Mar 37 10 Sep - 16 Sep 12 19 Mar - 25 Mar 38 17 Sep - 23 Sep 13 26 Mar - 01 Apr 39 24 Sep - 30 Sep 14 02 Apr - 08 Apr 40 01 Oct - 07 Oct 15 09 Apr - 15 Apr 41 08 Oct - 14 Oct 16 16 Apr - 22 Apr 42 15 Oct - 21 Oct 17 23 Apr - 29 Apr 43 22 Oct - 28 Oct 18 30 Apr - 06 May 44 29 Oct - 04 Nov 19 07 May - 13 May 45 05 Nov - 11 Nov 20 14 May - 20 May 46 12 Nov - 18 Nov 21 21 May - 27 May 47 19 Nov - 25 Nov 22 28 May - 03 Jun 48 26 Nov - 02 Dec 23 04 Jun - 10 Jun 49 03 Dec - 09 Dec 24 11 Jun - 17 Jun 50 10 Dec - 16 Dec 25 18 Jun - 24 Jun 51 17 Dec - 23 Dec 26 25 Jun - 01 Jul 52** 24 Dec - 31 Dec * Week No. 9 will be 8 days during leap year ** Week No. 52 will always have 8 days

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2.4. RESULTS

2.4.1. Meteorological parameters and C. pomonella population at Matta Swat during years 2012 and 2013 The data pertaining to the mean population of C. pomonella disclosed that the population varied significantly in different weeks of cropping season during 2012 and 2013. The pest population was observed significantly from 17th standard meteorological week (SMW) and increased progressively with sharp rise and fall at the subsequent interval up to 38th (SMW) (Table 2.2). The data regarding mean adult moth catches in the traps with respect to the weather parameters of the current season of the apple orchard during both the years of studies disclosed that the first flight of C. pomonella population was observed in 17th SMW (Where mean population were 1.00±0.40 per trap) during 2012 and 2013, respectively. The population of C. pomonella gradually showed increase in the 20th SMW where it reached to 7.00±0.81 and 3.00±1.08 per trap respectively in both years of studies. Afterwards, mean population of C. pomonella attained its maximum level during the 25th SMW (11.25±1.25/trap) during the year 2012 and 15.75±1.65 per trap in the 26th SMW in the second year. Then the mean population fluctuation of C. pomonella again gradually showed decline and reached to 7.00±1.29 and 8.00±1.22 per trap during both the proceeding years in 29th SMW. After sharp rise and fall in the population, again attained its maximum level (12.00±0.81 and 13.00±0.81 per trap) in the 31st and 32nd SMW during the years 2012 and 2013 respectively (Fig. 2.1). The lowest mean population of C. pomonella was recorded in the 38th SMW (0.25±0.25 and 1.00±0.70/ trap) respectively during both the years of studies (Table. 2.2). As it is evident from the results of this experiment that the change in the weather parameters such as temperature, relative humidity and rainfall can substantialy effect the population fluctuation of the this pest and can be concluded that this pest can complete two generation per season of the apple orchard.

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Table-2.2: Weekly averaged weather parameters and C. pomonella population in apple orchard at Matta during 2012 & 2013 2012 2013 1 SMW Mean Catches R.H% R.H% Total R.F4 Mean Catches Temp range R.H% R.H% Total R.F Temp range (0C) ±SE (0300Z)2 (1200Z)3 (mm) +SE (0C) (0300Z) (1200Z) (mm) 14 0.00±0.00 14.36-30.07 53.57 39.00 2.20 0.00±0.00 14.86-27.39 57.86 28.5 2.73 15 0.00±0.00 12.34-24.79 71.71 38.14 52.2 0.00±0.00 14.70-26.17 68.29 33.22 21.49 16 0.00±0.00 13.40-25.79 73.14 49.00 33.7 0.00±0.00 14.17-24.47 71.14 49.56 31.43 17 1.00±0.40 13.93-23.93 75.57 57.71 55.6 1.00±0.40 14.30-25.14 59.71 55.23 46.41 18 2.50±0.64 14.07-26.43 64.29 39.85 5.00 2.00±0.40 14.71-25.07 65.29 40.62 13.93 19 3.75±0.85 16.36-29.36 64.57 33.00 12.0 1.00±0.40 16.29-28.77 67.29 39.45 12.11 20 7.00±0.81 15.70-31.36 61.14 34.28 16.6 3.00±1.08 16.90-30.43 57.00 39.81 2.87 21 5.00±0.57 16.79-30.86 51.57 30.42 3.60 2.00±0.40 18.23-29.87 56.29 29.66 7.77 22 6.00±1.40 19.71-36.29 40.71 25.42 1.20 4.00±0.57 21.57-32.57 47.14 31.89 0.00 23 5.50±2.02 19.50-34.14 45.43 29.42 0.10 3.00±1.22 20.36-33.10 47.14 31.90 2.52 24 8.25±0.75 19.79-37.14 40.43 21.71 0.00 9.25±1.54 20.51-33.29 50.86 23.00 2.10 25 11.25±1.25 21.93-37.29 36.43 21.42 0.00 10.75±1.37 21.79-35.43 37.29 27.00 3.50 26 11.0±1.29 22.07-37.29 37.43 30.28 0.00 15.75±1.65 22.43-34.64 45.14 31.91 0.00 27 10.5±1.19 22.21-36.86 66.00 42.71 60.0 13.0±1.47 22.79-35.86 62.14 39.00 2.13 28 9.00±1.08 21.21-34.39 70.86 45.71 38.3 9.00±0.81 20.29-33.59 72.00 41.80 39.41 29 7.00±1.29 21.71-35.64 64.29 40.14 1.70 8.00±1.22 21.36-34.07 65.57 39.83 2.17 30 9.00±0.91 23.07-37.00 61.43 46.57 8.10 8.00±1.22 23.43-36.73 63.00 49.70 7.91 31 12.0±0.81 22.07-33.86 83.57 57.28 96.4 10.25±1.25 23.24-34.64 78.71 54.00 51.03 32 7.00±1.15 14.14-33.50 76.14 50.71 44.6 13.0±0.81 21.79-33.29 77.43 49.80 16.17 33 4.00±0.81 22.86-34.14 79.57 52.85 0.40 7.00±1.22 21.57-33.29 78.71 51.43 3.08 34 3.25±0.85 23.00-31.29 85.57 66.71 38.1 4.00±0.81 23.36-31.29 84.29 61.45 42.77 35 0.50±0.28 21.79-32.93 77.14 54.14 16.0 2.00±0.81 21.79-32.64 77.00 56.80 3.22 36 0.25±0.25 19.50-29.24 86.57 71.71 62.5 1.00±0.40 20.81-27.21 83.71 69.70 67.20 37 0.50±0.28 19.64-30.99 88.57 66.42 30.4 1.00±0.40 20.21-31.27 87.29 62.51 23.52 38 0.25±0.25 14.81-28.14 80.57 50.85 37.7 1.00±0.70 15.53-28.50 82.57 52.75 28.42 1SMW: Standard Meteorological Week, 2R.H.(0300Z): Relative Humidity on 8:00 am (Morning), 3R.H. (1200Z): Relative Humidity on 5:00 pm (Evening), 4R.F.(mm): Total Rainfall of the week 25

14

12

10

8 Matta 6 Madyan

Population/trap 4 Kalam

2

0 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Standard Meteriological Weeks (SMW)

Fig. 2.1. Population dynamics of C. pomonella in Swat during 2012 & 2013

2.4.2. The correlation matrix of C. pomonella population with weather parameters over a period of time at Matta during year 2012

Table 2.3 indicates that during the month of April 2012, C. pomonella population showed non-significant negative relation (r = -0.54) with mean maximum temperature. Similarly mean minimum temperature, mean relative humidity (0300Z), mean relative humidity (1200Z) and total rainfall (mm) had also a non-significant positive relation (r = 0.32, r = 0.46, r = 0.81 and r = 0.53 respectively) with C. pomonella population. C. pomonella population showed non-significant positive relation with mean maximum and minimum temperature (r = 0.90 and r = 0.48) in the month of May. Contrary to this, mean relative humidity (0300Z) and mean relative humidity (1200Z) showed non-significant negative relation (r = -0.38 and r = -0.52) with C. pomonella population build up. Similarly total rainfall also explained non-significant positive correlation with population of C. pomonella in the month of May. During the month of June, C. pomonella population showed non-significant positive correlation (r = 0.76 and r = 0.92) with mean maximum and minimum temperature while R.H (0300Z), R.H (1200Z) and total rainfall showed non- significant negative relation (r = -0.88, r = -0.84 and r = -0.57) with C. pomonella population. Similarly in the month of July, C. pomonella population elucidated non- significant positive correlation (r = 0.55 and r = 0.22) with mean maximum and minimum temperature. Likewise, non-significant negative relation (r = -0.54 and r = -0.42) were recorded for mean RH (0300Z) and R.H (1200Z), However, C. pomonella population exhibited non-significant positive relation (r = 0.32) with total rainfall during the month of

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July. During the month of August, the C. pomonella population exhibited non-significant positive relation (r = 0.49, r = 0.037, r = 0.88 and r = 0.007) with mean maximum, minimum, R.H (0300Z) and total rainfall. Contrary to this R.H (1200Z) explained non- significant negative relation (r =-0.26) with C. pomonella population. During the month of September, C. pomonella population confirmed positive non-significant relation with mean maximum and minimum temperature (r = 0.78 and r = 0.33 respectively), whilst non- significant negative correlation was shown by mean R.H (0300Z), mean R.H (1200Z) and total rainfall (r = -0.38, r = -0.29 and r = -0.80) respectively.

During the year 2012 at Matta, the population of C. pomonella illustrated a significant relation (p < 0.05) with mean maximum temperature (r = 0.79) compared to the mean minimum temperature (r = 0.44) which also explained significant (p < 0.05) relation with C. pomonella population. Similarly mean R.H (0300Z) and mean R.H (1200Z) also showed a significant (p < 0.05) negative correlation (r = -0.46 and r = -0.42) with C. pomonella population, contrary to this, total rainfall, showed non-significant negative correlation (r = -0.00) with C. pomonella population during the year 2012.

Table-2.3: The correlation matrix of Cydia pomonella population with weather parameters over a period of time at Matta during year 2012

Weather Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 2012 Mean max temp -0.541 0.906 0.767 0.559 0.493 0.787 0.799* (0C)

Mean min temp 0.323 0.480 0.925 0.221 0.037 0.335 0.448* (0C)

Mean R.H. 0.467 -0.384 -0.888 -0.546 0.007 -0.385 -0.462* (%) (0300Z) Mean R.H. 0.846 -0.529 -0.841 -0.421 -0.269 -0.298 -0.427* (%) (1200Z) Total rainfall 0.536 0.626 -0.572 0.327 0.885 -0.807 -0.002 (mm) * = Significant at 5% level of probability

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2.4.3. The correlation matrix of C. pomonella population with weather parameters over a period of time at Matta during year 2013 The data in Table-2.4 explained that in the month of April 2013, C. pomonella population showed non-significant negative correlation with mean maximum and mean minimum temperature (r = -0.34 and r = -0.42). Likewise R.H (0300Z) also showed non- significant negative correlation (r = -0.46) with C. pomonella population. C. pomonella population showed non-significant positive correlation with mean R.H (r = 0.70) and total rainfall (r = 0.76). During the month of May, C. pomonella population showed non- significant positive relationship (r = 0.28 and r = 0.17) with mean maximum and mean minimum temperature, while non-significant negative relation (r = -0.74) was noted for the mean R.H (0300Z) and non-significant positive correlation (r = 0.02) was found for mean R.H (1200Z) and negative relation (r = -0.76) for the total rainfall in the current month.

The C. pomonella population showed non-significant positive relationship with mean maximum, mean minimum temperature and total rainfall (r = 0.77, r = 0.33 and r = 0.57), while a non-significant negative relation were observed for mean R.H (0300Z) and mean R.H (1200Z) for the C. pomonella population (r = -0.45 and r = -0.84) during the month of June. During the month of July, C. pomonella population showed a non-significant positive relationship with mean maximum temperature (r = 0.02), while with the mean minimum temperature, mean R.H (1300Z), mean R.H (1200Z) and total rainfall showed non-significant negative relationship with C. pomonella population (r = -0.27, r = -0.82, r = -0.81 and r = -0.40). During the month of August, C. pomonella population showed non- significant positive relationship with mean maximum temperature (r = 0.68), while with the mean minimum temperature, mean R.H (1300Z), mean R.H (1200Z) and total rainfall showed non-significant negative relationship with C. pomonella population (r = -0.41, r = - 0.86, r =-0.81 and r = -0.18). During the month of September, C. pomonella population showed non-significant positive relationship with mean maximum temperature and mean minimum temperature (r = 0.72 and r = 0.55), while with the mean R.H (1300Z), mean R.H (1200Z) and total rainfall showed a non-significant negative relationship with C. pomonella population (r = -0.30, r = -0.06 and r = -0.48).

In the current experiment during the year 2013 at Matta, the C. pomonella population showed a highly significant (p<0.01) positive correlation with mean maximum temperature (r = 0.79) followed by the mean minimum temperature (r = 0.42). Non- significant negative relationships were recorded for the C. pomonella population against

28 weather parameters like mean R.H (0300Z) (r = -0.28), mean R.H (1200Z) (r = -0.24) and total rainfall (r = -0.22). The multiple regression analysis revealed that weather parameters contributed for 82.73 and 68.78 percent of total variation in the population of C. pomonella at Matta during the years 2012 and 2013, respectively (Table. 2.5).

Table-2.4: The correlation matrix of C. pomonella population with weather parameters over a period of time at Matta during year 2013

Weather Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 2013

Mean max temp (0C) -0.341 0.281 0.779 0.022 0.6874 0.722 0.795* Mean min temp (0C) -0.424 0.170 0.331 -0.277 -0.4171 0.559 0.423* Mean R.H (%) (0300Z) -0.468 -0.745 -0.451 -0.824 -0.8673 -0.300 -0.284NS Mean R.H (%) (1200Z) 0.708 0.028 -0.847 -0.813 -0.8114 -0.069 -0.244NS Total rainfall (mm) 0.760 -0.765 0.579 -0.400 -0.1833 -0.484 -0.227NS * = Significant at 5% level of probability NS = Nonsignifican

Table-2.5: Multiple regression equations for C. pomonella population at Matta during year 2012 & 2013

Year Regression Equations R2 Value

2012 Y1= -14.984+0.742X1+0.039X2-0.017X3-0.127X4+0.081X5 82.73%

2013 Y2= -26.593+1.164X1-0.019X2-0.011X3-0.110X4+0.0822X5 68.78%

Where, Y1 and Y2 – C. pomonella population, X1 - Maximum temperature (°C), X2 - Minimum temperature (°C), X3 - Relative humidity (%) at 0300 hrs (8.00 am Morning), X4 - Relative humidity (%) at 1200 hrs (5.00 pm Evening) and X5 - Total Rainfall (mm)

2.4.4. Meteorological parameters and C. pomonella population at Madyan Swat during year 2012 and 2013 The mean population of C. pomonella at Madyan varied significantly in different weeks of cropping season of apple orchard during the years 2012 and 2013. The first pest population flight was observed significantly from 17th standard meteorological week (SMW) and increased progressively with sharp rise and fall at the subsequent interval up to 38th (SMW)

29

(Table- 2.6). The data regarding population fluctuation of C. pomonella collected in the traps with respect to the abiotic factors of environment during different SMWs disclosed that the first adult male moth was observed in 17th SMW (Where mean population were 0.25±0.25 per trap) during 2012 and 2013, in both the year of studies. The population of C. pomonella gradually showed increase in the 26th SMW where it reached to 8.00±1.25 each mean C. pomonella population per trap respectively in both years of studies. Afterwards, mean population of C. pomonella reached to its maximum level during the 27th SMW (11.00±1.03 moth/trap) and in 29th SMW (10.25±0.8 moths/trap) during the years 2012 and 2013 respectively (Fig. 2.1). Then the mean population fluctuation of C. pomonella again gradually showed decline and reached to 2.50±0.85 and 2.00±0.85 moths/ trap during both the proceeding years in 31st SMW. After sharp rise and fall in the population, again reached to its maximum level (10.25±0.9 and 9.00±0.7 moths/ trap) in the 33rd and 35th SMW during the years 2012 and 2013 respectively. The lowest mean population of C. pomonella was recorded in the 37th SMW and 38th SMW (0.00±0.00 and 0.50±0.7 moths/ trap) respectively during both the years of studies (Table. 2.6). The change in the population dynamics of this pest is definitely due to change in the abiotic factors of environment and has ultimatly effect the adult male moth activities in the traps at Madyan. So it is concluded from the result of this experiment that this pest can partially complete two generation in Madyan area.

30

Table-2.6: Weekly averaged weather parameters and C. pomonella population in apple orchard at Madyan during year 2012 & 2013 2012 2013 1 SMW Mean Temp range R.H% R.H% Total R.F Mean Temp range R.H% R.H% Total RF Catches±SE (0C) (0300Z)2 (1200Z) 3 (mm) 4 Catches±SE (0C) (0300Z) (1200Z) (mm) 14 0.00±0.00 11.36-27.29 62.00 28.50 11.97 0.00±0.00 12.14-25.93 56.00 27.50 11.97 15 0.00±0.00 9.14-22.57 73.57 40.10 9.52 0.00±0.00 10.86-24.36 74.71 39.22 4.48 16 0.00±0.00 10.57-23.64 7.30 51.60 2.03 0.00±0.00 11.36-24.21 74.71 49.37 7.77 17 0.25±0.25 10.57-22.29 79.14 60.10 45.99 0.25±0.25 11.64-24.00 76.29 55.98 26.81 18 0.00±0.00 11.71-23.50 64.71 40.43 6.02 0.00±0.00 12.93-25.21 66.00 41.40 8.19 19 0.50±0.29 12.93-26.00 68.86 39.47 4.97 1.00±0.41 13.07-26.36 65.43 42.44 5.60 20 2.00±0.71 11.36-25.91 67.57 38.08 10.5 2.00±0.81 12.71-26.50 67.29 41.43 4.20 21 2.50±0.63 12.50-27.07 53.29 32.88 3.99 3.00±0.41 12.29-26.50 59.57 33.11 6.30 22 2.25±0.71 15.36-29.64 52.71 29.97 2.10 2.00±1.08 15.36-29.29 53.43 30.89 0.98 23 4.00±0.41 13.70-30.45 50.00 29.32 0.98 2.00±0.81 14.27-28.21 51.14 25.91 1.12 24 6.00±0.63 16.57-31.07 50.71 27.33 0.00 6.00±0.40 17.36-29.57 54.43 30.44 13.23 25 6.25±0.82 14.00-30.07 47.29 28.08 0.98 6.00±0.70 15.00-29.86 48.57 31.09 0.00 26 8.00±1.25 18.29-31.36 49.57 32.66 0.00 8.00±0.40 17.36-29.86 50.29 29.44 1.33 27 11.0±1.03 19.36-32.07 60.86 45.02 1.23 8.00±0.81 19.86-32.29 61.00 47.32 1.28 28 7.25±1.25 18.21-30.36 68.00 47.77 4.66 9.00±0.81 17.07-30.07 71.86 49.97 3.99 29 6.75±0.29 19.14-31.43 64.71 42.21 2.67 10.25±0.8 18.79-31.43 64.43 40.02 1.00 30 5.75±1.41 21.64-32.57 71.00 51.40 7.00 7.25±0.85 21.14-31.36 68.00 48.78 1.67 31 2.50±0.85 19.36-28.56 77.71 59.32 27.79 2.00±0.85 19.50-30.71 78.14 56.34 18.41 32 6.00±0.48 18.29-31.00 73.43 51.76 7.00 5.00±0.81 19.29-30.64 73.14 54.22 18.41 33 10.25±0.9 20.00-31.56 79.29 54.90 2.66 4.75±1.22 19.43-29.86 77.14 53.7 6.51 34 8.75±0.58 20.00-29.07 79.00 67.88 3.01 6.00±1.65 20.07-29.21 80.43 60.2 31.29 35 3.75±0.00 18.57-26.98 70.57 56.71 34.79 9.00±0.70 18.43-30.12 71.14 54.61 3.57 36 1.50±0.00 17.07-26.23 79.14 71.71 67.48 7.00±1.08 17.36-27.89 79.57 69.66 29.47 37 0.00±0.00 17.50-24.50 77.14 68.93 28.77 2.00±1.08 17.00-25.43 76.14 62.82 51.80 38 0.00±0.00 13.43-24.86 74.43 49.53 25.70 0.50±0.70 14.05-24.93 77.86 51.00 25.62 1SMW: Standard Meteorological Week, 2R.H.(0300Z): Relative Humidity data Taken at 8:00 am (Morning), 3R.H. (1200Z): Relative Humidity data taken at 5:00 pm (Evening), 4R.F.(mm): Total Rainfall of the week 31

2.4.5. The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2012

Data presented in Table-2.7 disclosed that C. pomonella population showed a non- significant negative relationship with mean maximum temperature (r = -0.47), while a positive non-significant relations were observed for mean minimum temperature (r = 0.11) mean R.H (0300Z) (r = 0.67) and mean R.H (1200Z) (r = 0.72) during the month of April. Likewise, total rainfall showed significant (p < 0.05) negative correlation with C. pomonella population. The C. pomonella population showed a non-significant positive relationship with mean maximum temperature (r = 0.81) and total rainfall (r = 0.15), while a negative non-significant relations were observed for mean minimum temperature (r = -0.07) mean R.H (0300Z) (r = -0.60) and mean R.H (1200Z) (r = -0.87) during the month of May. The C. pomonella population showed a non-significant positive relationship with mean maximum temperature (r = 0.63) and mean minimum temperature (r = 0.06) while a negative non-significant relations were recorded for mean R.H (0300Z) (r = -0.78), mean R.H (1200Z) (r = -0.93) and total rainfall (r = - 0.83), during the month of June.

The C. pomonella population showed a non-significant positive correlation with mean maximum temperature (r = 0.04) while total rainfall (r = 0.67), mean minimum temperature (r = -0.36) mean R.H (0300Z) (r = -0.46), and mean R.H (1200Z) (r = -0.25) showed negative non-significant relations with C. pomonella population during the month of July. The pest population exhibited a non-significant positive correlation with mean maximum temperature (r = 0.69) and mean minimum temperature (r = 0.35) mean R.H (0300Z) (r = 0.24 ), mean R.H (1200Z) (r = 0.01) while a negative significant relations were recorded for total rainfall (r = -0.97) during the month of August. The C. pomonella population showed a significant (p < 0.05) positive relationship with mean maximum temperature (r = 95) and non-significant positive relation with mean minimum temperature (r = 0.66) while a negative non-significant relations were recorded for mean R.H (0300Z) (r = -0.61 ), mean R.H (1200Z) (r = -0.07), while total rainfall showed non- significant positive relation (r = 0.25) with C. pomonella population during the month of September.

During the current experiment C. pomonella population showed a highly significant (p < 0.01) positive relationship with mean maximum temperature (r = 0.85)

32 and mean minimum temperature (r = 0.73), while a non-significant negative relations were recorded for mean R.H (0300Z) (r = -0.19), mean R.H (1200Z) (r = -0.02) and total rainfall (r = -0.21) showed significant (p < 0.05) negative correlation with C. pomonella population at Madyan Swat during the year 2012.

Table-2.7: The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2012

Weather Apr-12 May-12 Jun-12 Jul-12 Aug-12 Sep-12 2012 Mean max Temp (0C) -0.479 0.816 0.632 0.047 0.691 0.954* 0.857** Mean min Temp (0C) 0.115 -0.074 0.066 -0.364 0.356 0.663 0.739** Mean R.H (%) (0300Z) 0.670 -0.601 -0.781 -0.460 0.241 -0.612 -0.197NS Mean R.H (%) (1200Z) 0.728 -0.872 -0.938 -0.254 -0.009 -0.068 -0.021NS Total rainfall (mm) -0.976* 0.156 -0.829 -0.677 -0.972* 0.253 -0.441* NS = Non-Significant * = Significant at 5% level of probability ** = Significant at 1% level of probability

2.4.6. The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2013 C. pomonella population showed a non-significant negative relation with mean maximum temperature (r = 0.47) and significant (p < 0.05) negative correlation with total rainfall (r = -0.95), while positive non-significant relations were recorded for mean R.H (0300Z) (r = 0.40), mean minimum temperature (r = 0.17) and mean R.H (1200Z) (r = 0.69) with C. pomonella population in the month of April depicted in Table 2.8.

During the month of May, C. pomonella population showed a non-significant positive correlation with mean maximum temperature (r = 0.82) and in the same way mean minimum temperature (r = -0.86), mean R.H (0300Z) (r = -0.65), mean R.H (1200Z) (r = -0.76) and total rainfall (r = -0.54) exhibited non-significant negative relation with C. pomonella population in the month of May. During the month of June, C. pomonella population showed a non-significant positive relation with mean maximum temperature (r = 0.77) and mean minimum temperature (r = 0.59) and mean R.H (0300Z) showed non-significant negative relation with C. pomonella population (r = -0.17). Mean R.H (1200Z) (r = 0.55) showed a non-significant positive relation, while total rainfall (r =

33

-0.51) showed significant (p < 0.05) negative relation with C. pomonella population in the month of June. During the month of July, C. pomonella population showed a non- significant negative relation with mean maximum temperature (r = -0.05), mean minimum temperature (r = -0.45), mean R.H (1200Z) (r = -0.10) and total rainfall (r = - 0.06) exhibited non-significant negative relation with C. pomonella population in the month of July, while mean R.H (0300Z) showed non-significant positive relation with C. pomonella population (r = 0.21). During the month of August, C. pomonella population showed a non-significant negative relation with mean maximum temperature (r = -0.72), but non-significant positive relation were found among mean minimum temperature (r = 0.42), mean R.H (0300Z) (r = 0.02) mean R.H (1200Z) (r = 0.26) and total rainfall (r = 0.31) showed non-significant positive relation with C. pomonella population in the month of August.

During the month of September, C. pomonella population showed a highly significant (p < 0.01) positive relation with mean maximum temperature (r = 0.98) and mean minimum temperature (r = 0.85) , but non-significant positive relation were found in mean R.H (1200Z) (r = 0.28) while mean R.H (0300Z) (r = 0.47) and total rainfall (r = -0.65) exhibited non-significant negative relation with C. pomonella population in the month of September.

Table-2.8: The correlation matrix of C. pomonella population with weather parameters over a period of time at Madyan during year 2013

Weather Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 2013 Mean max temp (0C) -0.472 0.828 0.773 -0.050 -0.726 0.981** 0.824** Mean min Temp (0C) 0.174 -0.864 0.596 -0.457 0.426 0.851 0.755** Mean R.H (%) (0300Z) 0.405 -0.657 -0.173 0.210 0.029 -0.473 0.125NS Mean R.H (%) (1200Z) 0.695 -0.768 0.554 -0.109 0.264 0.285 0.122NS Total rainfall (mm) -0.950* -0.549 -0.511 -0.062 0.315 -0.653 -0.239NS NS = Non Significant * = Significant at 5% level of probability ** = Significant at 1% level of probability

The correlation coefficient showed that a highly significant (p < 0.01) positive relation exist among C. pomonella population and mean maximum temperature (r = 0.82)

34 and mean minimum temperature (r = 0.75). Similarly mean R.H (0300Z) (r = -0.09) and mean R.H (1200Z) (r = 0.12) showed non-significant positive relation with C. pomonella population in traps. The total rainfall (r = -0.24) showed a non-significant negative correlation with C. pomonella population caught in the traps in growing season of the apple orchard during the year 2013 at Madyan. The multiple regression analysis revealed that weather parameters contributed for 72.34 and 83.42 percent of total variation in the population of C. pomonella at Madyan during the years 2012 and 2013, respectively as depicted in Table.2.9.

Table-2.9: Multiple regression equations for C. pomonella population at Madyan during year 2012 and 2013

Year Regression Equations R2 Value

2012 Y1= -27.456+1.145X1-0.287X2-0.062X3+0.191X4-0.069X5 83.42%

2013 Y2= -14.135+0.638X1+0.201X2-0.147X3+0.0167X4-0.056X5 72.34%

Where, Y1 and Y2 – C. pomonella population, X1 - Maximum temperature (°C), X2 - Minimum temperature (°C), X3 - Relative humidity (%) at 0300 hrs (8.00 am Morning), X4 - Relative humidity (%) at 1200 hrs (5.00 pm Evening) and X5 - Total Rainfall (mm)

2.4.7. Meteorological parameters and C. pomonella population at Kalam Swat during year 2012 and 2013 The mean population of C. pomonella at Kalam varied significantly in different weeks of cropping season of apple orchard during the years 2012 and 2013. The pest population flight was observed significantly from 16th and 17th (During the years 2012 and 2013 respectively) standard meteorological week (SMW) and increased progressively with sharp rise and fall at the subsequent interval up to 38th (SMW) (Table-2.10). The data regarding mean population of C. pomonella catches in the traps with respect to the weather factors during both the years of studies clearly disclosed that the first adult male moth activities of C. pomonella population (1.25±0.47 moths/trap) was observed in 16th SMW during 2012 and in the 17th SMW, the population was 1.00±0.57 moths/trap during the year 2013. The population of C. pomonella gradually showed increase in the 26th and 27th SMW where it were reached to 5.75±0.85 and 7.25±1.25 moths/trap respectively in both years of studies. Afterwards, mean population of C. pomonella attained its maximum level during the 29th SMW (8.25±0.62 moths/trap) and in 30th SMW (7.500±0.95

35 moths/trap) during the years 2012 and 2013 respectively. Then the mean population fluctuation of C. pomonella again gradually showed decline and reached to 2.00±1.08 moths/trap in 30th SMW and 5.5±1.04 moth/trap in 32nd SMW the both the proceeding years. After sharp rise and fall in the population, again attained its maximum level (9.25±0.86 and 5.00±1.78 moths/ trap) in the 33rd SMW during the years 2012 and 2013 respectively (Fig. 2.1). The lowest mean population of C. pomonella was recorded in the 38th SMW and 36th SMW (0.00±0.00 and 0.00±0.00 moths/ trap) respectively during both the years of studies. (Table-2.10). The results disclosed that variations in temperature, relative humidity and rainfall during the crop growth and pest overlapping generations, which showed that this pest can partially complete two generation in Kalam area.

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Table-2.10: Weekly averaged weather parameters and C. pomonella population in apple orchard at Kalam during year 2012 & 2013 2012 2013 1 SMW Mean Temp range R.H% R.H% Total R.F Mean Temp range R.H% R.H% Total RF Catches±SE (0C) (0300Z)2 (1200Z) 3 (mm) 4 Catches±SE (0C) (0300Z) (1200Z) (mm) 14 0.00±0.00 5.34-19.83 82.86 49.14 21.28 0.00±0.00 5.84-5.84 81.57 39.45 12.60 15 0.00±0.00 4.86-16.29 71.14 56.00 6.51 0.00±0.00 6.14-17.07 79.29 51.34 11.90 16 1.25±0.47 6.14-20.21 60.00 40.71 21.00 0.00±0.00 6.50-21.64 70.00 42.70 18.97 17 0.00±0.00 6.60-15.40 85.43 65.00 13.79 1.00±0.57 6.47-17.69 82.57 61.20 0.00 18 0.00±0.00 5.29-20.50 65.57 56.00 0.00 0.00±0.00 6.89-19.57 66.43 54.70 0.00 19 0.00±0.00 6.79-21.00 66.86 61.40 14.00 0.00±0.00 7.50-23.07 63.86 59.80 5.81 20 0.00±0.00 5.79-19.29 80.00 67.14 59.30 0.00±0.00 6.14-20.71 76.29 61.76 0.00 21 1.00±0.40 6.93-25.40 65.43 64.57 21.49 3.00±0.40 6.29-25.23 65.57 60.54 28.21 22 3.75±1.10 10.10-26.86 54.43 24.71 3.99 4.25±0.85 10.21-26.69 57.43 29.23 21.63 23 3.75±1.25 8.86-25.66 50.29 42.28 2.03 3.00±0.81 9.14-25.99 49.29 47.90 3.43 24 4.00±0.40 10.00-26.67 54.14 39.14 0.00 5.25±0.85 10.00-27.45 53.86 32.87 0.00 25 5.50±1.32 11.43-27.60 61.43 41.28 3.11 5.50±1.44 11.29-27.77 61.00 43.9 1.22 26 5.75±0.85 10.69-27.33 60.71 31.42 0.98 6.25±1.25 11.29-28.14 64.14 32.81 1.36 27 4.00±1.31 14.36-28.04 67.14 45.42 0.98 7.25±1.25 13.86-29.89 66.14 43.90 0.00 28 6.50±1.04 15.36-27.87 62.00 51.22 1.22 6.25±1.25 14.64-27.36 62.00 52.60 0.00 29 8.25±0.62 12.21-29.55 62.00 60.14 0.00 6.50±1.04 12.43-26.21 66.71 59.22 0.00 30 2.00±.08 13.91-27.49 67.29 50.42 0.49 7.50±0.95 14.14-27.57 67.14 51.43 0.98 31 3.00±0.81 15.90-26.29 74.29 47.00 2.11 6.75±0.62 16.5-29.01 72.14 49.72 1.22 32 6.25±0.85 12.00-27.22 78.00 48.85 0.00 5.50±1.04 13.14-28.25 74.14 51.90 0.00 33 9.25±0.86 14.76-29.76 79.57 61.28 0.00 5.00±1.78 14.11-26.21 66.71 62.71 0.00 34 5.25±0.85 16.93-26.24 85.43 63.28 0.00 4.25±1.54 16.79-27.00 82.57 59.21 0.00 35 4.00±0.86 13.13-25.88 80.29 59.57 7.10 2.00±.08 13.00-26.14 82.14 60.33 0.00 36 2.00±0.85 13.36-22.29 84.71 71.00 34.23 0.00±0.00 13.71-23.31 83.57 69.77 15.98 37 1.00±0.64 12.5-22.64 80.00 64.57 14.63 0.00±0.00 12.86-23.64 75.86 59.30 14.80 38 0.00±0.00 6.14-18.83 81.14 61.72 41.30 0.00±0.00 8.14-21.10 81.29 58.88 12.00 1SMW: Standard Meteorological Week, 2R.H.(0300Z): Relative Humidity data Taken at 8:00 am (Morning), 3R.H. (1200Z): Relative Humidity data taken at 5:00 pm (Evening), 4R.F.(mm): Total Rainfall of the week 37

2.4.8. The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2012 C. pomonella population showed a non-significant positive correlation with mean maximum temperature (r = 0.62), mean minimum temperature (r = 0.34) and total rainfall (r = 0.50). Non-significant negative relation were shown by both R.H (300Z) (r = -0.84) and R.H (1200Z) (r = -0.77) with C. pomonella population catches during the month of April (Table-2.4.10). In the month of May C. pomonella population showed a significant (p < 0.05) positive relationship with mean maximum temperature (r = 0.96), mean minimum temperature (r = 0.61) and mean R.H (1200Z) (r = 0.31). Non-significant negative relation was shown by both mean R.H (0300Z) (r = -0.38) and total rainfall (r = - 0.05) with C. pomonella population catches during the month of May. During the month of June C. pomonella population showed a non-significant positive relationship with mean maximum temperature (r = 0.77), mean minimum temperature (r = 0.86), mean R.H (0300Z) (r = 0.92) and mean R.H (1200Z) (r = 0.40). Non-significant positive relation was shown by total rainfall (r = 0.20) with C. pomonella population catches during the month of June.

The C. pomonella population trap catches during the month of July, revealed non- significant positive relationship with mean maximum temperature (r = 0.64) and mean R.H (0300Z) (r = 0.17). Similarly non-significant negative relations were recorded for mean R.H (1200Z) (r = 0.60), mean minimum temperature (r = -0.14) and total rainfall (r = 0.02) for C. pomonella catches in the traps during the month of July. The C. pomonella trap catches revealed non-significant positive relation with mean maximum temperature (r = 0.88), mean R.H (0300Z) (r = 0.34) and mean R.H (1200Z) (r = 0.55), while non- significant negative relationship were observed for the mean minimum temperature (r = - 0.38) and total rainfall (r = -0.80) for the C. pomonella catches in the traps during the month of August. During the month of September, C. pomonella traps catches revealed that non-significant positive relation were observed for all the weather parameters such as mean maximum and mean minimum temperature (r = 0.80 and r = 0.35 respectively) while the rest of weather parameters such as mean R.H at morning and R.H at evening (r = -0.38 and r = 0.62 respectively) total rainfall which showed non-significant negative relation (r = -0.71) with C. pomonella population during the month of September.

38

The combined analysis of all the months revealed that C. pomonella traps catches during season 2012 at Kalam Swat, exhibited highly significant (p < 0.01) positive correlation with mean maximum temperature (r = 0.85) and mean minimum temperature (r = 0.67). In the same way, mean R.H at morning (r = -0.28) and mean R.H at evening (r = - 0.34) and total rainfall (r = -0.62) showed non-significant negative relations with C. pomonella trap catches during the growing season of crop and pest flying activities.

Table-2.11: The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2012

Weather Apr May Jun Jul Aug Sep 2012 Mean max temp (0C) 0.621 0.963* 0.778 0.648 0.887 0.802 0.859** Mean min temp (0C) 0.345 0.615 0.869 -0.148 -0.384 0.357 0.672** Mean R.H (%) (0300Z) -0.846 -0.381 0.929 0.177 0.340 -0.382 -0.287NS Mean R. H (%) (1200Z) -0.776 0.318 0.401 -0.600 0.559 -0.623 -0.346NS

Total rainfall (mm) 0.509 -0.058 0.202 -0.015 -0.803 -0.713 -0.629** NS = Non-Significant * = Significant at 5% level of probability ** = Significant at 1% level of probability

2.4.9. The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2013

Data presented in Table- 2.12 disclosed that in the beginning of flying activities of C. pomonella trap catches showed non-significant negative relation with mean maximum temperature (r = -0.42) and total rainfall (r = -0.91), while mean R.H (0300Z) (r = 0.48), mean R.H (1200Z) (r = 0.85) and mean minimum temperature (r = -0.49) showed non- significant positive relation with C. pomonella population in the month of April. During the month of May, C. pomonella population showed non-significant positive relationship with mean maximum temperature (r = 0.81) and mean R.H (1200) (r = 0.28) while non- significant negative correlation were recorded for mean minimum temperature (r = -0.44) and mean R.H (0300Z) (r = -0.29) with C. pomonella population. Likewise, significant (p < 0.05) positive relation with C. pomonella catches in the traps, was recorded for total rainfall (r = 0.97) with C. pomonella population in the month of May. In the month of June, C. pomonella population showed highly significant (p < 0.01) positive relations with mean maximum temperature (r = 0.99) weaker than mean minimum temperature (r = 0.83)

39 and with mean R.H (0300Z) (r = 0.76). Likewise, C. pomonella population showed non- significant negative correlation with mean R.H (1200Z) (r = -0.35) and total rainfall (r = - 0.26).

During the month of July, C. pomonella trap catches revealed that the relation with meteorological parameters such as mean maximum temperature (r = 0.42), mean minimum temperature (r = 0.45), mean R.H at morning (r = 0.73), R.H at evening (r = 0.12) and total rainfall (r = 0.04) exhibited non-significant positive relation with C. pomonella population. In the month of August, C. pomonella population showed non-significant positive relation with weather parameters such as mean maximum temperature (r = 0.81), mean minimum temperature (r = 0.02), and total rainfall (r = 0.87). Likewise, R.H at morning (r = -0.45) and R.H at evening (r = -0.79) showed non-significant negative relation with C. pomonella catches in the traps for the population dynamics studies in the month of August. During the month of September, C. pomonella population showed non-significant positive relation with weather parameters such as mean maximum temperature (r = 0.83), mean minimum temperature (r = 0.28) and mean R.H at morning (r = 0.28). In the same month C. pomonella population showed non-significant negative relation with weather parameters such as R.H at evening (r = -0.22) and significant (p < 0.05) negative correlation with total rainfall (r = -0.97).

The overall effect of the weather parameters on the population of C. pomonella revealed that C. pomonella population showed a highly significant (p < 0.01) positive correlation with mean maximum temperature (r = 0.88) and mean minimum temperature (r = 0.68). Likewise, percent relative humidity at morning (r = -0.49) exhibited non- significant negative relation on the population build up of C. pomonella. The C. pomonella population also showed non-significant negative relation with R.H at evening (r = -0.36) and significant (p < 0.05) negative relation with total rainfall (r = -0.43) during the current studies.

The multiple regression analysis revealed that weather parameters contributed for 77.36 and 83.24 percent of total variation in the population of C. pomonella at Kalam during the years 2012 and 2013, respectively (Table.2.13).

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Table-2.12: The correlation matrix of C. pomonella population with weather parameters over a period of time at Kalam during year 2013

Weather Apr May Jun Jul Aug Sep For 2013 Mean max temp (0C) -0.4257 0.8159 0.9927** 0.4180 0.8150 0.8375 0.8817** Mean min temp (0C) 0.4981 -0.4454 0.8384 0.4522 0.0266 0.2801 0.6866** Mean R.H (%) (0300Z) 0.4894 -0.2935 0.7676 0.7334 -0.4552 0.2818 -0.4888NS Mean R. H (%) (1200Z) 0.8572 0.2875 -0.3513 0.1274 -0.7947 -0.2244 -0.3639NS Total R.F. (mm) -0.9156 0.9789* -0.2699 0.0358 0.8724 -0.9737* -0.4324* NS = Non-Significant * = Significant at 5% level of probability ** = Significant at 1% level of probability

Table-2.13: Multiple regression equations for C. pomonella population at Kalam during year 2012 and 2013

Year Regression Equations R2 Value

2012 Y1= -13.622+0.616X1-0.101X2+0.0556X3-0.015X4-0.042X5 77.36%

2013 Y2= -6.29+0.505X1+0.108X2-0.022X3-0.042X4-0.066X5 83.24%

Where, Y1 and Y2 – C. pomonella population, X1 - Maximum temperature (°C), X2 - Minimum temperature (°C), X3 - Relative humidity (%) at 0300 hrs (8.00 am Morning), X4 - Relative humidity (%) at 1200 hrs (5.00 pm Evening) and X5 - Total Rainfall (mm)

2.4.10. The correlation matrix of C. pomonella population with weather parameters over a period of time in Swat during year 2012-13

Correlation coefficients were worked out between population buildup of C. pomonella and mean weather parameters during proceeding months of observations for the data of 2012 and 2013 at Matta (Table-2.14). During the current studies of population dynamics of C. pomonella, the correlation between C. pomonella population and weather parameters revealed that mean maximum temperature showed significant (p < 0.05) positive correlation (r = 0.79 and 0.79) during both year of studies, likewise mean minimum temperature also explained a significant (p < 0.05) positive relation with C. pomonella population build up (r = 0.44 and 0.42). Similarly mean R.H at morning also confirmed a significant (p < 0.05) negative relation (r = -0.46) with C. pomonella

41 population during the year 2012 and non-significant negative correlation (r = -0.28) with C. pomonella population during the year 2013. In the same way, a significant (p < 0.05) negative correlation were recorded for the C. pomonella population with mean relative humidity at evening (r = -0.42) during the year 2012 and non-significant negative relation was recorded for the R.H at evening (r = -0.24) in the second year whilst total rainfall illustrated non-significant negative relationship ( r = -0.00 and -0.22) with C. pomonella population during both the years at Matta Swat.

The population fluctuation of C. pomonella in the trap catches during both the years of studies at Madyan revealed that during the years 2012 and 2013, mean maximum temperature demonstrated a highly significant (p < 0.01) positive relation (r = 0.85 and 0.82) with C. pomonella population fluctuation during both the years of studies. Likewise, C. pomonella population also exhibited highly significant (p < 0.01) positive relation with mean minimum temperature (r = 0.73 and 0.75) during both proceeding years. Mean R.H at morning showed a non-significant negative relation (r = -0.19 and -0.12) with C. pomonella population during both the years of studies. Similarly, mean R.H at evening showed a non-significant negative relation (r = -0.02) with C. pomonella population during the year 2012 and also during the year 2013 (r = -0.12) at Madyan, whilst total rainfall showed a significant (p < 0.05) negative correlation (r = -0.44) during the year 2012 and non-significant negative correlation (r = -0.23) with C. pomonella population during the year 2013.

During both the years of studies of C. pomonella population fluctuation in the trap catches revealed that the C. pomonella population at Kalam exhibited a highly significant (p < 0.01) positive correlation with mean maximum temperature (r = 0.85 and 0.88), Similarly C. pomonella population also expressed a highly significant (p < 0.01) positive relation with mean minimum temperature (r = 0.67 and 0.68) during the years 2012 and 2013. Mean relative humidity at morning and evening confirmed a non-significant negative relation (r = -0.28 and -0.34) with C. pomonella population during the year 2012 and significant (p < 0.05) negative relation (r = -0.48 and -0.36) with C. pomonella population in the forthcoming year. Likewise, total rainfall showed a highly significant (p < 0.01) negative correlation (r = -0.62) with the C. pomonella population during the year 2012 and a significant (p < 0.05) negative correlation (r = -0.43) with C. pomonella population in the second year.

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Table-2.14: The correlation matrix of C. pomonella population with weather parameters over a period of time in Swat during year 2012 and 2013

Correlation coefficient for C. pomonella population Weather Matta Madyan Kalam 2012 2013 2012 2013 2012 2013 Max temp 0.799* 0.795* 0.857** 0.824** 0.859** 0.881** (0C) Min temp 0.448* 0.423* 0.739** 0.755** 0.672** 0.686** (0C) Mean R.H -0.462* -0.284 NS -0.197 NS 0.125 NS -0.287 NS -0.488 NS (%)(0300Z) Mean R. H -0.427* -0.244 NS -0.021 NS 0.122 NS -0.346 NS -0.363 NS (%) (1200Z) Total R.F. -0.002 NS -0.227 NS -0.441* -0.239 NS -0.629** -0.432* (mm) * = Significant at 5% level of probability ** = Significant at 1% level of probability NS = Non-Significant

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2.5. DISCUSSION

2.5.1. Meteorological parameters and C. pomonella population at Matta, Madyan and Kalam Swat during year 2012 and 2013

The results pertaining to population dynamics of C. pomonella revealed that mean population of C. pomonella varied significantly in different weeks of cropping season at Matta, Madyan and Kalam during the years 2012 and 2013. The pest population was observed significantly from 16th to 17th standard meteorological week (SMW) and increased progressively with sharp rise and fall at the subsequent interval up to 38th (SMW) at all the three locations in Swat.

The data regarding mean adult male moth population of C. Pomonella collected in the pheromone traps with respect to weather abiotic factors during SMWs, in cropping seasons of apple orchard during both the years of study disclosed that the first flight activity of adult male moth of C. Pomonella population was observed in 14th to 17th SMWs in Matta, Madyan and Kalam during 2012 and 2013. In Matta, the first flight of C. Pomonella (1.00±0.40 moths/trap) was observed in 17th SMW, whilst at Madyan the first flight of C. Pomonella was noticed in 16th and 14th SMW in years 2012 and 2013 respectively, however at Kalam C. Pomonella first trapped in 16th and 17th SMW during the years 2012 and 2013 respectively. Mean population of C. Pomonella (11.25±1.25 moths/trap) reached to its maximum level during the 25th SMW during the year 2012 and 15.75±1.65 moths/ trap in the 26th SMW in the second year at Matta, whilst at Madyan, peak populations of C. Pomonella (11.00±1.03 and 10.25±0.80 moth/trap) were recorded in 27th and 29th SMW during 2012 and 2013 respectively.

In case of Kalam, maximum population (8.25±0.62 and 9.0±0.95 moth/trap) were observed in 29th and 30th SMW during both the years of studies. Then the mean population fluctuation of C. Pomonella again gradually showed decline and then attained their maximum levels again at all the three locations. After sharp rise and fall in the population, maximum population levels (12.00±0.81 and 13.00±0.81 moths/ trap) were observed in the 31st and 32nd SMW during the years 2012 and 2013 at Matta Swat, while in case of Madyan, the slight increase in adult trap (10.25±0.92 and 9.00±0.70 moth /trap) was noticed in 33rd and 35th SMW. But in case of Kalam, the second peak population of C. Pomonella (9.25±0.86 and 6.25±1.25 moth/ trap) in the trap was noticed in 33rd SMW during both the years. The lowest mean population (0.25±0.25 and 0.00±0.00 moths/ trap)

44 of C. pomonella was recorded in the 38th SMW during both the years of studies at Matta Swat, while at Madyan the population (0.00±0.00 and 1.00±0.40 moth/trap) of C. Pomonella declined in 37th and 38th SMW. Likewise, at Kalam the lowest mean population (0.00±0.00 moth/ trap each) of C. Pomonella was recorded in 38th and 36th SMW in both the year of studies. This population fluctuation of pest attributed to abiotic factors of environment which ultimately influenced the change in the population dynamics of C. pomonella in the pheromone traps which further confirmed that this pest can easily complete two generation in this region. Tamhankar et al. (1989), Singh and Sachan (1991) and Patil et al. (1992) reported that pheromone traps are an effective tools for monitoring adults male moth activities of most of the lepidopterious pest in the orchards, vegetables and other cearal crops for applying control strategy for their effective management.

Prasannakumar et al. (2011) also used standard meteorological weeks (SMW) for monitoring the insect pests of tomato, Okra and brinjal. He reported that the tomato borer attained peak during 47th standard week (7.10 moths/trap), Okra shoot and fruit borer attained peak (7.52 moths/trap) and Brinjal shoot and fruit borer (44.13 moths/trap) in 48th standard week and 41st standard week, respectively. The results disclosed that moth activity increased with the increase in temperature. As the temperature increased the pheromonal compounds might have evaporated and hence, increase moth catches in the traps. Besides female moths oviposit on fruits, hence the maximum male moth coming for the mating with female catches in the traps during peak summer season. (Krishnakumar et al., 2004). The results are not agreed with Gedia et al. (2007), who reported that besides from temperature, relative humidity and rainfall, wind speed and dew drops on the plant has a profound effect on the population dynamics of moths and their oviposition.

2.5.2. The correlation matrix of codling moth C. Pomonella population with weather parameters over a period of time in Swat during the years 2012 and 2013

The study of Correlation coefficients were worked out between population buildup of C. pomonella and mean weather parameters during observations for the data at Matta, Madyan and Kalam during the years 2012 and 2013. During the current studies of population dynamics of C. pomonella, the correlation between C. Pomonella population and weather parameters revealed that mean maximum temperature showed significant (p<0.05) positive correlation with C. pomonella population during both year of studies and adults moth catches increases with raise in temperature at all the three locations, likewise

45 mean minimum temperature also showed a significant (p<0.01) positive relation with C. pomonella population build up. These results are in agreement with findings of Agrawal et al. (2004) who find out that population growth rates of insects may be higher where temperatures are raising. However mean R.H at morning showed statistically significant (p<0.05) negative relation with C. pomonella population at the study location. In the same way, a significant (p<0.05) negative correlation were recorded for the C. pomonella population with mean relative humidity at evening during the year 2012 and then did not showed any significant negative correlation with C. pomonella population at Madyan and Kalam. C. pomonella population exhibited non-significant negative correlation with total rainfall at Matta during both the years of studies, but explained significantly (p<0.05) negative correlation at Madyan during first year of studies and non-significant negative relation during 2013. At Kalam during first year of studies C. pomonella population showed highly significant (p<0.01) negative correlation during the first year and significant negative relation during the second year. The multiple regression models indicated that total rainfall, maximum temperature and relative humidity contributes maximum towards the incidence of C. pomonella in the pheromone traps at all the three locations. These analysis further revealed that weather parameters contributed for 82.73 (R2) and 68.78 (R2) percent of total variation in the population of C. pomonella at Matta, 72.34 (R2) and 83.42 (R2) percent at Madyan and 77.36 (R2) and 83.24 (R2) percent at Kalam during the years 2012 and 2013, respectively.

Present findings of this experiment are comparable with the finding of Sabir et al. (2006), who reported that rainfall, average temperature and relative humidity are vital abiotic factors which greatly influenced the population dynamics of most of lepidopterious pest in the field. Nonetheless, Calora and Ferino (1968) observed no clear-cut correlation between a single climatic factor and the frequency of different lepidopterious pests, even the populations fluctuation were usually higher during rainy months and at low temperature of the prevailing season. Likewise, results regarding relative humidity are not agreed to those presented by Emura and Kojima (1974) who reported that a relative humidity of less than 60% caused high mortality of the larvae of rice pest insect. Decisively, this feature needs more detailed, comprehensive and continued studies involving different agro-ecological areas of apple orchard.

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All abiotic factors of environment particularly temperature contribute significantly toward population fluctuation of C. pomonella trapped with the help of sex attractant pheromone. Lui and Yeh (1982) find out positive and highly significant correlation of Dacus zonatus incidence with minimum and maximum temperature in different crops, these results are in conformity with our studies. The results pertaining to the population dynamics of C. pomonella are related to Hasyim et al. (2008), who reported that the number of flies and moths captured with pheromones traps correlated positively with all three abiotic factors, i.e. temperature, humidity and rainfall. Similar observations regarding the influence of weather parameters on the occurrence of melon fly was also reported earlier by different workers in different parts of the world (Gupta and Bhatia, 2000, Shukla and Prasad, 1985 and Su, 1984, Mahmood et al., 2002).

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2.6. CONCLUSIONS

The correlation matrix between C. pomonella population and weather parameters disclosed that mean maximum and minimum temperature exhibited a highly significant (p<0.01) positive correlation with C. pomonella population build up, whilst relative humidity did not expressed any significant effect on adult moth catches in the traps. Nonetheless, rainfall showed non-significant negative relationship in the current studies except in Kalam. Regression analysis explained 68.78-83.42% change in the population of this pest due to abiotic factors of environment in all three areas during both the years of studies.

2.7. RECOMMENDATIONS

The above findings lead to the following recommendations.

1) Change in temperature might change population dynamics of insect pests differently in different agro-ecosystem and ecological zones. 2) These studies may offer an insight on the possible impact of weather parameters on population dynamics of this pest and insecticide applications based on trap captures can significantly reduce the number of sprays needed for C. pomonella management. 3) Nevertheless, further study should be carried out in this perspective to assess the change in the population dynamics of C. pomonella due to other abiotic factors of environment as well. 4) Developing prediction models and studying evolutionary changes under modified environment would be useful to face the future challenges.

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Akram, M., F. Hafeez, M. Farooq, M. Arshad, M. Hussain, S. Ahmed, K. Zia and H.A.A. Khan. 2013. A case to study population dynamics of Bemisia tabaci and Thrips tabaci on Bt and non-Bt cotton genotypes. Pak. J. Agri. Sci. 50(4): 617-623.

Anjali, M., N.P. Singh, M. Mahesh and S. Swaroop.2012. Seasonal incidence and effect of abiotic factors on population dynamics of major insect pests on brinjal crop. J. Environ. Res. Dev. 7(1): 431-435.

Barnes, M.M. 1991. Codling moth occurrence, host race formation, and damage. Totricid Pests: their Biology, Natural Enemies and Control (ed. by L P S van der Geest & E Evenhuis), Elsevier, Amsterdam. pp. 313-328.

Batiste, W.C. 1973. Codling moth: estimating time of first egg hatch in the field - a supplement to sex-attractant traps in integrated control. Environ. Entomol. 2: 387-391.

Bowden, J. and M.G. Morris. 1995. The influence of moon light on catches of insects in light traps in Africa. Part III. The effective radius of nursery vapour light trap and the analysis of the trap catches using effective radius. Bull. Entomol. Res. 65(2): 303-348.

Calora, F.B. and M.P. Ferino. 1968. Seasonal fluctuation of stem borers, thrips and leaf folders of rice in the Philippines. Philipp. Entomol. 1(2): 149-160.

Dent, D.R. and C.S. Pawar. 1988. The influence of moon light and weather on catches of Helicoverpa armigera (Hubner) in light and pheromone traps. Bull. Entomol. Res. 78: 365-377.

Ebesu, R. 2003. Integrated Pest Management for Home Gardens: Insect Identification and Control. Insect Pests 13: 1-11.

Emura, K. and A. Kojima. 1974. On some environmental factors for development of rice green caterpillar Naranga aenescens Moore. In. Influence of humidity on the occurrence (in Japanese, English summary). J. Niigata Agric. Exp. Stn. 23: 27-36.

Gedia, M.V., H.J Vyas and M.F. Acharya. 2007. Influence of weather on Spodoptera litura male moth catches in pheromone trap and their ovipositional in castor. Indian J. Plant. Prot. 35(1): 118-120.

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Gupta, D. and R. Bhatia. 2000. Population fluctuation of Bactrocera spp. in sub mountainous mango and guava orchards. J. Appl. Hort.1(2): 101-102.

Hasyim, A., W. Muryati and J. de Kogel. 2008. Population fluctuation of the adult males of the fruit fly, Bactrocera tau Walker (Diptera: Tephritidae) in passion fruit orchards in relation to abiotic factors and sanitation. Indonesian J. Agric. Sci. 9 (1): 29-33.

Jindal, J. and D.S. Brar. 2005. Population dynamics of sucking pests on Hirsutum cotton hybrids in relation to weather factors. Indian. J. Ecol. 32(1): 58-60.

Karuppaiah, V. and G.K. Sujayanad. 2012. Impact of Climate Change on Population Dynamics of Insect Pests. World J. Agric. Sci. 8 (3): 240-246.

Krishnakumar, N.K., R. Venugopal, P.N. Krishna Moorthy, B. Shivakumara and H.R. Ranganath. 2004. Influence of weather factors on the attraction of male shoot and fruit borer, Leucinodes orbonalis Guenee to synthetic sex pheromone in south India. Pest Manage. Hort. Ecosyst. 10(2): 161-167.

Laskar, N. and H. Chatterjee. 2010. The Effect of Meteorological Factors on the Population dynamics of Melon fly, Bactrocera cucurbitae (Coq.) (Diptera: Tephritidae) in the foot hills of Himalaya. J. Appl. Sci. Environ. 14(3) 53-58.

Lui, Y.C. and C.C. Yeh.1982. Population fluctuation of the oriental fruit fly, Dacus dorsalis Hendel. in sterile fly release and control area. Chin. J. Entomol. 2:57- 70.

Madsen, H. F. and J.M. Vakenti. 1973. Codling moth: use of Codlemone baited traps and visual detection of entries to determine need of sprays. Environ. Entomol. 2: 677-679.

Mahmood, T., S.I. Hussain, K.M. Khokhar and M.A. Hidayatullah. 2002. Studies on methyl eugenol as a sex attractant for fruit fly, Dacus zonatus (Saund) in relation to abiotic factors in peach orchard. Asian J. Plant Sci. 4: 401-402.

Mandal, S.K., A. Sattar and S. Banerjee.2006. Impact of Meteorlogical Parameters on Population Build up of Red Spider Mite in okra, Abelmoschus esculentus L. under North Bhiar condition. J. Agric. Phys. 6(1): 35-38.

Paradis, R.O. and A. Comeau. 1972. Pikgeage de la pyrale de la pomme, Lospeyresia pornonella (L.), dans le vergers du sud-ouest du QuCbec au moyen d'une pheromone sexuelle synth6tique. Annu. Soc. Entomol. Qu Pb. 17: 7-19.

Patil, B.V., Nandihalli, B.S. Hugar and P. Somashekar. 1992. Influence of weather parameters on pheromone trap catches of cotton bollworms. Karnataka J. Agric. Sci. 5: 46-350.

Prasannakumar, N.R., A.K. Chakravarthy, A.H. Naveen and N. Narasimhamurthy. 2011. Influence of weather parameters on pheromone traps catches of selected lepidopterous insects pests on vegetable crops. J. Curr. Biotica. 4(4): ISSN: 0973-4031.

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Riedl, H. and B.A. Croft. 1974. A study of pheromone trap catches in relation to codling moth (Lepidoptera: Olethreutidae) damage. Can. Entomol. 106: 525- 537.

Roelofs, W.L.1971. Sex attractant of the codling moth: characterization with electro antennogramm technique. J. Sci. 174: 297-299.

Sabir, A. M., S. Ahmad, M. Hassan and A. Qadir. 2006. Pest weather interaction of major insect pests in rice ecosystem. SAARC. J. Agric. 4: 203-212.

Selvaraj, S., D. Adiroubane, V. Ramesh and A.L. Narayanan.2010. Impact of ecological factors on incidence and development of tobacco cut worm, Spodoptera litura Fabricius on cotton. J. Biopest. 3(1Special Issue) 043-046.

Sharma, V. and B.P. Singh. 2012. Effect of varieties, seasons and weather on population buildup of leaf hopper (Amrasca devastans Distant) on potato crop. Potato J. 39(1): 23-30.

Shukla, R.P. and V.G. Prasad. 1985. Population fluctuation of the oriental fruit fly, Dacus dorsalis Hendel in relation to host and abiotic factors. Trop. Pest Manage.31: 273-275.

Singh, J. and B.S. Sekhon. 1998. Population build up of cotton Jassid, Amrasca biguttula (Ishida) on different varieties of cotton. J. Insect. Sci. 11: 53-55.

Singh, K.N. and G.C. Sachan. 1991. Assessment of the use of sex pheromone traps in the management of Spodoptera litura. Indian J. Proc. 21(1): 7-13.

Su, C.Y. 1984. The study on the relationship between seasonal succession of male adult of melon fly, D. cucurbitae and the meteorological factors. J. Agric. Forensic. 32: 105-109.

Tamhankar, A.J., K.K. Guthi and G.W. Rahalkar. 1989. Responsiveness of Earaias vitella and Earias insulana males to their female sex pheromone. Insect Sci. Appl. 10(5): 625-630.

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Zulfiqar, M.A., M.A. Sabri, M.A. Raza, A. Hamza, A. Hayat and A. Khan. 2010. Effect of Temperature and Relative Humidity on the Population Dynamics of Some Insect Pests of Maize. Pak. J. life. soc. Sci. 8(1): 16-18.

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CHAPTER -3: MOLECULAR CHARACTERIZATION OF THE CYDIA POMONELLA IN SWAT VALLEY

3.1. INTRODUCTION

The C. pomonella is the major pest damaging apple, throughout the world. Besides apple this pest cause serious infestation in different crops and causing a huge economic losses in different fruit production (Ciglar, 1998). The pest was first recorded in Eurasia, but now it is present in all parts of the world where the cultivation of apples and pears practiced (Franck et al., 2007). It has achieved a almost worldwide distribution, being one of the most unbeaten pest species known today (Thaler et al., 2008). Currently, C. pomonella is present in Australia, South America, South Africa, New Zealand, North America, India, Pakistan and Afghanistan (Franck et al., 2007).

The C. pomonella is one of the important pests of apple orchards, introduced as a key pest that causes direct damage. Acquaintance with genetic variation within C. pomonella populations is necessary for their efficient control and management. Molecular studies provide new methods and ways to study population variation to differentiate closely related species and strains (Deverno et al., 1998; Williams et al., 1990).

It has acclamatized itself effectively to different habitats by forming various strains and ecotypes in its populations, which are not closely identical to each other in several physiological features, developmental and morphology (Meraner et al., 2008). The first scientific information on C. pomonella about its origin and description of the damage it causes on fruit has been documented long time ago. Theophrastus portrayd it 371 years before Christ (cit. Balachowsky and Mesnil, 1935).

Population genetic studies of agricultural pests have highlighted the significance of migration and diversity in integrated pest management (Han and Caprio, 2004; Endersby et al., 2006; Scott et al., 2005, 2006; Zhou et al., 2000; Leniaud et al., 2006). Because populations of such pest species are mostely affected by the application of phyto-protection measures, such as insecticides and transgenic crops, genetic population structure of the insects are mostely affected due to resistance against insecticides (Carriere et al., 2004; Caprio 1998, 2001).

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C. pomonella is the most important pest of pome fruits in temperate areas worldwide. Despite its economic importance, little research has been done on its molecular aspect regarding genetic structure and patterns of gene flow at the local and regional scale, which are important features for establishing an area wide control strategy (Faust, 2003; Calkins and Dorn et al., 1999). Pest management strategies of C. pomonella include regular insecticide treatments, which are known to select for resistance to several insecticide groups (Knight et al., 1994, Sauphanor et al., 1998; Dunley and Welter, 2000). Therefore, a comprehensive and detailed study of the population molecular studies of this pest could be indispensable in its management decisions (Timm et al., 2006).

Population variations of the insect pest may be influenced by different factors within the landscape (Keyghobadi et al., 2005; Peterson and Denno, 1998). Hence, inherent insect uniqueness such as adult flight capability, as well as biological factors related to habitat, shape the genetic architecture of traits in insect populations. In agroecosystems particularly, anthropogenic factors, for example, pest management, can further add to insect population disturbance in different parts of the world (Dorn et al., 1999).

According to Bardakci, (2001) and Delaat et al. (2005) polymerase chain reaction (PCR) techniques propose increased understanding and speed for the identification and characterization of species to find out variation in populations. The randomly amplified polymorphic DNA (RAPD) technique has been developed to detect genetic variation and diversity by PCR amplification of genomic DNA by using short, random primers and thus does not require prior knowledge of a DNA sequence. (Deverno et al., 1998). Molecular studies and research provide new methods to study population diversity as well as to discriminate closely related species (Williams et al., 1990; Deverno et al., 1998). RAPD primers are very well suited for use in insect phylogeny areas like the detection of genetic diversity among populations as well as the detection of closely related species and ecotypes (Benecke, 1998; Lima et al., 2002). Thus it is low cost, efficient in developing a large number of DNA markers in a less time and the less complicated equipment that it requires has made RAPD primer a useful technique for findin out population variation among the insects.

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By using allozyme markers, little genetic differentiation between C. pomonella populations was reported from different parts of the world (Pashley, 1983). Likewise, low variation was found between different location and different host plants in France and Switzerland (Bues and Toubon 1992; Bues et al., 1995). Significant differentiation between populations at the regional and local scales were obtained in South Africa using amplified fragment length polymorphisms (AFLPs) (Timm et al., 2006). More powerful markers (co-dominant), such as microsatellites, have been introduced for C. pomonella (Franck et al., 2005; Zhou et al., 2005). These markers have been applied by Franck et al. (2007) to evaluate the population structure of C. pomonella from France. Low molecular variation were recorded in this later study, whilst the insecticide applications were no pressure on the population variations (Franck et al., 2007).

C. pomonella has been traditionally regarded as a rather inactive pest, likely to develop genetic isolation between geographical regions. However, laboratory evidence suggests that some ecotypes and strains of this pest have the ability to fly several kilometers (Keil et al., 2001). Moreover, other means of mobility, such as anthropogenic activities i.e. harvest bin and cartons containing the diapausing larvae of C. pomonella between packing facilities and orchards, could signify an important source of distribution for this pest (Higbee et al., 2001).

C. pomonella is regarded as a inactive species and different studies showed that males can fly and disperse within range of 60-80 meters, but some of the adult mnale moth can flight upto several kilometers. (Mani and Wildbolz, 1977; Keil et al., 2001). Laboratory studies confirmed similar flight capacity for males and females moths (Schumacher et al., 1997). This variation is may be adaptive, as it provides chances for the adult moth for survival in cases of habitat destruction (Schumacher et al., 1997; Keil et al., 2001) and along with transportation of infested fruit (Hibgee et al., 2001), might have essential inferences of genetic variation between populations. Studies with allozyme (Buès et al., 1995) and DNA (Timm et al., 2006; Franck et al., 2007; Thaler et al., 2008; Chen and Dorn, 2010) primers studies on populations from various regions of the world have disclosed inconsistent outcomes (Franck and Timm, 2010).

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RAPD primers are very efficient and affective tools to find out the variability among and between populations of C. pomonella in Italy (Gomez et al., 2004; Gomez et al., 2005). Bayar et al. (2006) investigated population variation of Aeolothrips intermedius, and found population-specific RAPD primers for their differentiation. Deverno et al. (1998) distinguished two closely related sympatric species of lepidopterious moths using seventeen species-specific RAPD primers. Previousely, RAPD primers have used successfully for studying the population variation of the Hessian fly, Mayetiola destructor and the stem sawfly, Cephus cinctus, in Syria and America, respectively (Lou et al., 1998; Naber et al., 2000).

The current studies were therefore undertaken to know about the molecular variation among the population of C. pomonella collected from three major growing apple areas of Swat i.e. Matta, Madyan and Kalam (Having different altitudes, climatic conditions and geographical locations) through randomly amplified polymorphic DNA (RAPD) in the Institute of Biotechnology, The University of Agriculture, Peshawar, Pakistan.

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3.2. REVIEW OF LITERATURE

Garner and Siavice (1996) reported that the Asian gypsy moth (Lymantria dispar L.) brought into North America and genetic markers were used to differentiate Asian moths from the established North American population. They used RAPD-PCR to identify a DNA length polymorphism that is analytical for the two moth strains. DNA sequence analyses showed that Asian and North American forms enabled development of locus-specific primers so that this primers, designated FS-1, will be useful for strain and various ecotypes detection under varying situations in different laboratories.

Boivin et al. (2002) investigated that adaptive variation in populations encountering a new environment are often constrained by deleterious pleiotropic interactions with ancestral physiological functions. Some insecticides application on repeated basis may cause variation in the population of various insects. The novel set of selective forces after removal of insecticide pressure led to the decline of the frequencies of resistant phenotypes over time, suggesting that the insecticide-adapted genetic variants were selected against the absence of insecticide.

Timm et al. (2006) examined gene flow and genetic variation mong geographic and host populations of C. pomonella (L.) in South Africa is lacking, among gene flow in the population, the importance of control practices such insecticides application and biological control, often influence the variation in the population. Some results disclose that population from different host were not closely related but some population showed differentiation collected from orchard situated at adistance of 1 km apart. But due to limited moth flight extensive gene flow may be noticed among the population from different host, however gene flow among local species of C. pomonella may be limited.

Thaler et al. (2008) studied that AFLP markers elucidate the genetic structure of C. pomonella strains collected from different apple orchard of Central European. Individual genetic variation within population was low but ahigh degree of molecular variation was recorded between the population even at a small distance. One of the main reason was responsible for variation was limited gene flow among closely related populations. Besides, ecological, microclimatic and geographic constraints may favour developing C. pomonella into many local strains and populations. In

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Central European fruit orchards C. pomonella is under great pressure due to insecticides usage. As no evidence has been recorded for having a relation between insecticide resistance and geographic or genetic distances among populations, AFLP markers do not have a prophetic value for having an outbreak of pesticide resistance in the field. The case of C. pomonella is a great example for having globally successful pest species due to developing strain and ecotypes among its population.

Fuentes-contreras et al. (2008), reported that C. pomonella is the major pest of apple orchard throughout the world. Molecular studies were carried out using microsatellites for 11 C. pomonella populations in the two major apple cropping regions in central Chile. Only 0.2% of the genetic variability was found among the populations. Geographically structured genetic variation was independent of apple orchard management. It can be concluded that a high genetic changes of C. pomonella between orchards, possibly mediated by human activities attributed to fruit production.

Razowski et al. (2010) examined DNA variation in a 606 bp fragment of COI mtDNA obtained from 23 species of Tortricini and two representatives of other tribes in Croatia. The position of Spatalistis, Tortrix, Aleimma and Acleris and some groupings of species within Acleris were confirmed by molecular data, including the synonymization of Croatia and Phylacophora were also confirmed by molecular data. This studies confirmed the variation in population of all these species through moecular COI DNA analysis.

Chen and Dorn (2010) also reported that little work has been carried out regarding molecular studies in populations of insect species that have a high genetic variability in dispersal. Larvae (5th instar) of C. pomonella were collected from three orchards of stone fruits, pome fruits and nut trees from Switzerland and from six other orchards in the country. Significant genetic variation in the population was noted among the populations from apple, apricot and walnut in the Valais region. Besides, among the eight populations sampled from apple in different geographic regions throughout Switzerland. These results showed that a discrete prevailing feature, in the current study the sedentary behaviour of the moth, can form change in the population of insect.

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Frank and Timm (2010) reported that studying the population genetic structure of the insect pest population dynamics is a key aspect for understanding in agriculture scenario. They further described the role of hosts, time and geography in the genetic structure of C. pomonella. However, level of molecular variation among the population were not significant based on variation in the Na channel and microsatellite loci. It is concluded that phytosanitary measures are held responsible for creating variation among the population of C. pomonella geographical and temporal scale. They further added the relative importance of natural and dispersal of insect with respect to the anthropogenic activities affecting C. pomonella population genetics and highlight population genetic research needs in order to design more efficient and affective pest management programs in future.

Pajac and Baric (2011) reported that C. pomonella is a severe pest inmost of apple producing areas of the world. He wrote a review regarding its biology, damages, morphology, resistance to insecticides, genetic control though molecular ways and population genetic structure of this pest. This has the capability to adopt itself to diferent climatic and weather conditions and has developed resistance to different groups of pesticides used against this pest. That's the reason that this has developed man ecotypes in their population having various biological and physiological conditions required for its development.

Khaghaninia et al. (2009) used RAPD primers for investagating population genetic variation in the population of 13 geographically different population colleted from northwestern Iran during 20113 and 2004. They found useful information regarding genetic and geographic distance matrices through Mantel test. The banding pattern in the Mughan and Zunuz populations were ranges from 169 to 206 respectively. However, AMOVA disclosed significant variation within and between population of C. pomonella. Between different populations diversity was 14.44% and within the population the total variation was 85.56%. Cluster analysis regarding molecular data for C. pomonella populations assigned in to two groups. First group was consisted Mughan population only and canonical correlation analysis disclosed high significant relation between RAPD primers and the topographic condition of that area. Further, analysis explained that high relation between geographic populations and validated the outcome of the previous cluster analysis.

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Kil (2011) examined the molecular variations among the various population of C. pomonella by using three types of microsatellite loci and find out the genetic variation indices. He also determined number of alleles per locus and heterozygosity, etc. He recorded a substantial variations in the molecular structure in the population of C. pomonella collected from Russia were completely different from the population collected from Ukraine durin the studies.

Voudouris et al. (2012) reported that C. pomonella (L ) in the most destructive and severe pest of apple orchard through Europe. They collected nine samples from pear, apple, and wallnut for genetic analysis from various location of mainland Greece by using 11 microsatellite loci. Some samples were also collected from southern France for comparison. Genetic analysis revealed and seperated the C. pomonella samples in to two groups. The genetic variation among the samples collected within the population was low detected by FST statistics i.e 0.009 in Greek samples. While in the French samples the variation in the population was 0.0150 compared to the global value 0.050 among all the samples collected from all these regions having different climatic comditions and topography. Nonetheless, climate and host species has not so much effect on genetic structure of C. pomonella populations within each country. But anthropogenic activities may play avital role in the gene flow even at a long distances in a particular country.

Men et al. (2013) investigated that C. pomonella is the most dangerous among the insect pest causing a huge economic losses in China to apple orchard. No research has been conducted till now regarding molecular genetic structure of this pest in China. They reported sequential loss of the genetic variation and the reason of its distributions but no correlation was recorded between genetic diversity and topographic conditions of northwestern populations. No variation on molecular basis were recorded regarding its population. The results further explained that genetic diversity might be due to repeated colonization of of the founder populations. However, population of C. pomonella having week flight capacity and human added dispersal disclosed high level of genetic variation in their population rather than topographic conditions.

Chinnapandi et al. (2013) studied the variability of genetic structure within a specific sampling site of tobacco armyworm moth, Spodoptera litura. Armyworm

59 moths were collected from castor fields on a ten sampling sites in India. A total of 82 scorable DNA fragments ranging from 0.25 kb to > 2.0 kb were amplified by Random Amplification of Polymorphic DNA. The percentage of polymorphism detected in RAPD analysis was as high as 90-100%, suggesting the existence of strong genetic polymorphism among S. litura samples occurring on different geographical locations in South India. Statistical analyses showed significant levels of genetic variations among the ten geographically distinct populations. Jaccard similarity index, values fell in a range of 0.17-0.83, 0.3-0.9 and 0.3-0.8. Their results about intrapopulational genetics are therefore discussed in regards to variations of sensitivity to biocontrol agents such as Bacillus thuringiensis and several common insecticides of S. litura.

Kil and Basedina (2013) observed the molecular genetic structure of C. pomonella and pest populations was described and its variability under influence of insecticides, varying climatic conditions and geographic location is studied. Genetic diversity of C. pomonella populations was shown to depend mainly on genetic features of the populations, but not on the insecticide load or weather conditions. The intra-population genetic diversity by two microsatellite loci was estimated in pests from the gardens with different insecticide press.

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3.3. MATERIALS AND METHODS

3.3.1. C. pomonella Specimen collection

Female larvae trapped and collected by single face cardboard tie up around the apple tree at a distance of 30 cm from the ground following the procedures of Fritsch et al. (2005) with some modifications. In each population, 30 overwintering female larvae were randomly selected for DNA isolation to minimize DNA contamination by endoparasites (Landry et al., 1999) in autumn from Matta (350 55' 19.11" of latitude North and 720 30' 37.52" of longitude East) (920.30 meters), Madyan (350 08' 0.00" of latitude North and 720 32' 0.00" of longitude East) (1333.84 meters) and Kalam (350 28' 41.66" of latitude North and 720 34' 18.61" of longitude East) (2092.30 meters). To eliminate the effect of host association in discrimination of populations, all of the specimens were collected from "Red Delicious" apple orchards. The specimens were washed and stored in 96% alcohol (Ethanol) prior to analysis in the Health laboratory of Institute of Bio-Technology and Genetic Engineering (IBGE), The University of Agriculture, Peshawar Pakistan.

3.3.2. Genomic DNA Extraction

For Genomic DNA extraction, Spinklean Genomic DNA Extraction Kit (Thermoscientific® USA) was used and the procedure of Zimmerman et al. (2000) was followed with some necessary modifications. The specimens were crushed in liquid nitrogen. DNA was extracted using manufacture’s manual. Briefly, TL Buffer (250ul) was added to crushed larvae for tissue lysis. The samples were then vortexed to properly mix. 199 units of enzyme was added and mixed thoroughly. Lysis buffer of 220 µl was added to the solutions and mixed thoroughly. A volume of 560 µl Buffer TB was then added to each eppendorf tube and mixed comprehensively through vortex to get a homogeneous solution followed by incubation for 10 minutes at 65oC. Then 200 µl absolute ethanol was added. Sample mixtures were passed through column, assembled in clean collection tube by centrifuging at 8000 Xg for 1 minute. Column was washed twice with 750 µl wash buffer ‘PS’ and centrifuged at 8000 Xg for 1 minute. For removing traces of ethanol the column was centrifuged again at 10000 Xg for another one minute.

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About 200 ul of pre heated TE buffer was added to the column membrane in new tubes, incubated at room temperature for 2min and centrifuged at 10000xg for 1min to get DNA which was then stored at -20C.

3.3.3. Polymerase Chain Reaction and Gel Electrophoresis

The entire polymerase chain reaction (PCR) reactions was carried out in 25 µl reaction containing total genomic DNA (150 ng), 0.25 mM of RAPD primers

(Genlink, USA), 200 µM of each dNTP, 50 mM of KCL, 10 mM Tris, 1.5 mM MgCl2 and 2.5 unite of Taq polymerase (Thermoscientific). Optimized amplification conditions were: initial denaturation step of 4 minutes at 94oC followed by 40 cycles each consisting of a denaturation step of 50 second at 94oC, annealing step of 1 min 280C extension of 1 min at 720C, was followed by final extension of 10 min at 72oC. All the amplification reactions were performed using gene amp PCR system 2700 programmable thermo cycler. The amplification products were then detected on 2% agarose gel and stained with Ethidium Bromide using UV transilluminator. Images were recorded and stored in computer.

3.3.4. Statistical Analysis

For statistical analysis of randomly amplified polymorphic DNA (RAPD), every scorable band was considered as a single locus/allele. The loci were scored as present (1) or absent (0). Bivariate 1-0 matrix was generated. Genetic distances was calculated using “Unweighted Pair Group of Arithmetic Means” (UPGMA) procedure described by Nei and Lie (1979).

GD=1-dxy/dx+dy-dxy, where GD=Genetic Distance between two Genotypes, dxy = Total no. of common loci (bands) in two genotypes, dx = Total no. of loci (bands) in genotype 1 and dy = Total no. of loci (bands) in genotypes.

The DNA amplification profiles were analyzed using online software program for genetic analysis (Pop Gene version 3.1) available on www.ncbi.org. RAPD Primers used in this experiment are presented in Table.3.1.

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Table-3.1: Name, sequence, size and molecular weight of RAPD primer used for molecular characterization of C. pomonella

S.No Primer Sequence Size(bp) Tm M.wt % GC 1. GL Decamer B-12 CCTTGACGCA 10 29.5°C 2987.98 60 2. GL Decamer D-16 AGGGCGTAAG 10 29.5°C 3117.04 60 3. GL Decamer C-04 CCGCATCTAC 10 29.5°C 2947.96 60 4. GL Decamer C-13 AAGCCTCGTC 10 29.5°C 2987.98 60 5. GL Decamer B-04 GGACTGGAGT 10 29.5°C 3108.04 60 6. GL Decamer H-02 TGTAGCTGGG 10 29.5°C 3099.04 60 7. GL Decamer E-09 CTTCACCCGA 10 29.5°C 2947.96 60 8. GL Decamer F-01 ACGGATCCTG 10 29.5°C 3028.00 60 9. GL Decamer A-19 CAAACGTCGG 10 29.5°C 3037.00 60 10. GL Decamer D-08 GTGTGCCCCA 10 33.6°C 3003.99 70 11. GL Decamer G-11 TCCCCGTCGT 10 33.6°C 2994.99 70 12. GL Decamer F-07 CCGATATCCC 10 29.5°C 2947.96 60 13. GL Decamer E-18 GGACTGCAGA 10 29.5°C 3077.02 60 14. GL Decamer H-13 GACGCCACAC 10 33.6°C 2981.97 70 15. GL Decamer B-15 GGAGGGTGTT 10 29.5°C 3139.06 60 16. GL Decamer C-16 CACACTCCAG 10 29.5°C 2956.96 60 17. GL Decamer C-02 GTGAGGCGTC 10 33.6°C 3084.03 70 18. GL Decamer H-03 AGACGTCCAC 10 29.5°C 2996.98 60 19. GL Decamer F-04 GGTGATCAGG 10 29.5°C 3108.04 60 20. GL Decamer H-13 ACCAGGTTGG 10 29.5°C 3068.02 60 21. GL Decamer G-02 GGCACTGAGG 10 33.6°C 3093.03 70 22. GL Decamer* A-06 GGTCCCTGAC 10 33.6°C 3003.99 70 23. GL Decamer* A-07 GAAACGGGTG 10 29.5°C 3117.04 60 24. GL Decamer* B-16 TTTGCCCGGA 10 29.5°C 3019.00 60 25. GL Decamer* D-10 GGTCTACACC 10 29.5°C 2987.98 60 26. GL Decamer* F-11 TTGGTACCCC 10 29.5°C 2978.98 60 27. GL Decamer* G-13 CTCTCCGCCA 10 33.6°C 2923.95 70 28. GL Decamer* G-15 ACTGGGACTC 10 29.5°C 3028.00 60 29. GL Decamer* H-05 AGTCGTCCCC 10 33.6°C 2963.97 70 30. GL Decamer* H-10 CCTACGTCAG 10 29.5°C 2987.98 60 * Indicates the RAPD markers giving no results (Bands). With Result (Bands): 21, Without Result (Bands): 09

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3.4. RESULTS

3.4.1. Primer B12.

Results revealed that a total of 8 detectable alleles were amplified in the three populations of C. pomonella during the current research by the primer B-12. The banding pattern confirmed that population from Matta and Kalam were amplified and that of Madyan was not amplified (Fig. 3.1). Maximum of 4 alleles were amplified in isolates of Kalam. The allele frequency on the basis of amplification further explicated that among all the C. pomonella (Table-3.2) population, allele 2 and 4 were found in the minimum number of variation (f = 0.3333) and allele 5, 6, 7 and 8 were afforded the maximum number of variation in the C. pomonella population (f = 0.667).

Table-3.2: Gene frequency, diversity and Shannon information index for RAPD primer GLB-12

Allele Allele Size Gene Frequency Gene Diversity S.I.I* (h) (bp) (f) (I)

B12-01 10000 0.0000 0.0000 0.0000 B12-02 2500 0.3333 0.4444 0.6365 B12-03 2000 0.0000 0.0000 0.0000 B12-04 1500 0.3333 0.4444 0.6365 B12-05 1000 0.6667 0.4444 0.6365 B12-06 750 0.6667 0.4444 0.6365 B12-07 700 0.6667 0.4444 0.6365 B12-08 250 0.6667 0.4444 0.6365

Mean 250-10000 0.4166 0.3333 0.4773 * Shannon Information Index

The genetic diversity among the different populations of C. pomonella at each allele further revealed (Table-3.2) that the maximum diversity was observed for allele no 8 (I = 0.4444), nevertheless, Shannon information index (h) for each allele of primer B-12 explained that maximum information of the Shannon information index were recorded for allele B12-02, B12-04 and up to B12-08 (h=0.6365), whilst allele no B12-01 and B12-03 (h=0.000) were not amplified and as result given no banding pattern.

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3.4.2. Primer D16

The data pertaining to detectable scores/alleles elucidated that a total of 8 detectable bands were amplified in the three populations of C. pomonella used during the current experiment by the primer D-016 as depicted in Table-3.3. The banding pattern shows that populations from Matta and Kalam were amplified and that of Madyan did not show polymorphism (Fig. 3.1). Maximum of 4 alleles were amplified in isolates of Kalam. The allele frequency on the basis of amplification further revealed that allele 6 and 8 were found in the minimum number of variation (f = 0.334) and allele 5 and 7 were amplified in the maximum number of distinction in the C. pomonella population (f = 0.667).

Table-3.3: Gene frequency, diversity and Shannon information index for RAPD primer D16

Allele Allele Size (bp) Gene Frequency Gene Diversity (I) S.I.I* (h) (f) D16-01 10000 0.0000 0.0000 0.0000 D16-02 2500 0.0000 0.0000 0.0000 D16-03 2000 0.0000 0.0000 0.0000 D16-04 1500 0.0000 0.0000 0.0000 D16-05 1000 0.6667 0.4444 0.6365 D16-06 750 0.3333 0.4444 0.6365 D16-07 700 0.6667 0.4444 0.6365 D16-08 250 0.3333 0.4444 0.6365 Mean 250-10000 0.25 0.2222 0.3182 * Shannon Information Index

The genetic diversity among the different populations of C. pomonella for each allele depicted in the Table-3.3. The results disclosed that the maximum multiplicity was observed for allele no 5, 6, 7 and 8 (I = 0.445). The Shannon information index (h) for each allele of primer D-16, explained further that the Shannon information index were high for allele D16-05, up to D16-08 (h=0.637), whilst alleles D16-01-04 (h=0.000) were not amplified and as result given no Shannon Index.

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3.4.3. Primer C04

The results related to alleles amplification showed that maximum of 6 alleles were amplified in the three populations of C. pomonella used during the amplification by the primer C-04 (Table-3.4). The banding pattern proved that populations from Matta and Kalam were amplified and that of Madyan did not offer the banding pattern (Fig. 3.1). Maximum of 5 alleles were amplified in isolates of Kalam. The allele frequency on the basis of amplification further explained that the allele frequency among all populations, allele 4 and 5 were found in the minimum number of deviation (f = 0.334) and allele 1, 2 and 6 were amplified in the maximum number of distinction in the C. pomonella population (f = 0.667).

However, the genetic diversity (I) among the different populations of C. pomonella at each allele further revealed that the maximum diversity was disclosed for allele no 5, 6, 7 and 8 (I = 0.445). The Shannon information index (h) for each allele of primer C-04 explicated that maximum Shannon information index (h) were noted for all six alleles (h=0.637).

Table-3.4: Gene frequency, diversity and Shannon information index for RAPD primer C04

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) C04-01 10000 0.6667 0.4444 0.6365 C04-02 2500 0.6667 0.4444 0.6365 C04-03 2000 0.6667 0.4444 0.6365 C04-04 1500 0.3333 0.4444 0.6365 C04-05 1000 0.3333 0.4444 0.6365 C04-06 750 0.6667 0.4444 0.6365 Mean 750-10000 0.5555 0.4444 0.6365 * Shannon Information Index

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Fig. 3.1: Electrophoreogrm showing PCR based amplification products of Codling moth Cydia pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers B-12, D-16 and C-04

3.4.4. Primer C13

The results revealed that a total of 8 detectable scores/alleles were amplified in the three populations of C. pomonella used during the current experiment by the primer C-13 as depicted in Table 3.5. The banding pattern explained that populations from Matta and Kalam were amplified and that of Madyan was not amplified by using RAPD markers C-13 in the electrophoresis (Fig. 3.2). Maximum of 7 alleles were amplified in isolates of Kalam, whilst minimum of 6 alleles were amplified in the Matta population. The allele frequency on the basis of amplification further revealed that allele 08 was found in the maximum number of dissimilarity (f = 3.334) and allele 1, 2 and 3 and 5, 6 and 7 were amplified in the minimum number of deviation in the C. pomonella population (f = 0.667), while the allele 4 was zero frequency noted (Fig. 3.2).

Furthermore, the genetic diversity (I) among the different populations of C. pomonella at each allele explained that the maximum assortment was observed for allele no 1, 2, 3 and 5, 6, 7 and 8 (I = 0.445). The Shannon information index (h) for each allele of primer C-13, elucidated that more information of the Shannon information index (h) were noted for all alleles except allele 4 (h=0.637).

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Table-3.5: Gene frequency, diversity and Shannon information index for RAPD primer C13

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I*(h) (bp) (f) C13-01 10000 0.6667 0.4444 0.6365 C13-02 2500 0.6667 0.4444 0.6365 C13-03 2000 0.6667 0.4444 0.6365 C13-04 1500 0.0000 0.0000 0.0000 C13-05 1000 0.6667 0.4444 0.6365 C13-06 750 0.6667 0.4444 0.6365 C13-07 500 0.6667 0.4444 0.6365 C13-08 250 3.3333 0.4444 0.6365 Mean 250-10000 0.9166 0.3888 0.5569 * Shannon Information Index

3.4.5. Primer B04

The results revealed that a total of 11 detectable scores were amplified in the three populations of C. pomonella used during the current experiment by the primer B-05 (Table-3.6). The banding pattern disclosed that population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers B-05 (Fig. 3.2). Maximum of 8 alleles were amplified in isolates of Kalam, whilst no alleles were amplified in the Matta and Madyan populations. The allele frequency on the basis of amplification expounded that 08 alleles were set up in the maximum number of gene frequency (f = 0.334) and alleles 1, and 5, 6 were minimum in the gene frequency (f = 0.000) in the C. pomonella population.

Nevertheless, the genetic diversity (I) among the different populations of C. pomonella at each allele explained that the maximum assortment was observed for all the alleles (I = 0.445) except alleles 1, 5 and 6 (I=0.000). The Shannon information index (h) for each allele of primer B-05, revealed that maximum Shannon information index (h) were observed for all alleles (h=0.637) except allele 1, 5 and 6. (h=0.000).

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Table-3.6: Gene frequency, diversity and Shannon information index for RAPD primer B04

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) B04-01 4500 0.0000 0.0000 0.0000 B04-02 4000 3.3333 0.4444 0.6365 B04-03 3500 3.3333 0.4444 0.6365 B04-04 3000 3.3333 0.4444 0.6365 B04-05 2500 0.0000 0.0000 0.0000 B04-06 2000 0.0000 0.0000 0.0000 B04-07 1500 3.3333 0.4444 0.6365 B04-08 1000 3.3333 0.4444 0.6365 B04-09 750 0.3333 0.4444 0.6365 B04-10 500 0.3333 0.4444 0.6365 B04-11 250 0.3333 0.4444 0.6365 Mean 250-4500 1.6666 0.3232 0.4629 * Shannon Information Index 3.4.6. Primer H02

Results depicted in Table-3.7 explicated that a total of 10 detectable alleles were amplified in the three populations of C. pomonella by the RAPD primer H-02. The banding pattern confirmed that population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers H-02 (. Fig. 3.2). Maximum of 3 alleles were amplified in isolates of Kalam, whilst no alleles were amplified in the Matta and Madyan populations. The allele frequency on the basis of amplification further explained that 03 alleles in the Kalam population were found in the maximum number of gene frequency (f = 0.334) whilst the rest of the alleles were zero gene frequency in the C. pomonella population in all the three regions (f = 0.000).

Besides, the genetic diversity (I) among the different populations of C. pomonella at each allele revealed that maximum diversity was observed for all the alleles 7, 9 and 10 (I = 0.445) whilst the rest of the alleles were gene diversity (I=0.000). The Shannon information index (h) for each allele of primer H-02 expounded that maximum Shannon information index (h) were recorded for the alleles 7, 9 and 10 (h=0.637) whilst other alleles were zero Shannon information index (h=0.000) for the RAPD primer H-02.

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Table-3.7: Gene frequency, diversity and Shannon information index for RAPD primer H02

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) H02-01 4500 0.0000 0.0000 0.0000 H02-02 4000 0.0000 0.0000 0.0000 H02-02 3500 0.0000 0.0000 0.0000 H02-03 3000 0.0000 0.0000 0.0000 H02-04 2500 0.0000 0.0000 0.0000 H02-05 2000 0.0000 0.0000 0.0000 H02-06 1500 0.0000 0.0000 0.0000 H02-07 1000 3.3333 0.4444 0.6365 H02-08 750 0.0000 0.0000 0.0000 H02-09 500 3.3333 0.4444 0.6365 H02-10 250 3.3333 0.4444 0.6365 Mean 250-4500 0.9999 0.1333 0.1909

Fig.3.2. Electrophoreogrm showing PCR based amplification products of Codling moth Cydia pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers C-13, B-04 and H-2.

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3.4.7. Primer E09

The results presented in the Table-3.8 disclosed that a total of 08 detectable alleles were amplified in the three populations of C. pomonella exploited in experiment by the RAPD primer E-09. The banding pattern clarify that populations from Matta and Kalam were amplified and that of Madyan were not amplified by using RAPD markers E-09 (Fig. 3.3). Maximum of 2 alleles in Matta population and 5 alleles were amplified in isolates of Kalam, whilst no alleles were amplified in Madyan population. The allele frequency on the basis of amplification explained that 03 alleles in the Kalam population were found in the maximum number of gene frequency (f = 0.667) whilst the rest of the alleles were minimum gene frequency in the C. pomonella population in all the three regions (f = 0.334), however, two alleles were zero gene frequency for the C. pomonella population by using RAPD primer E- 09.

Furthermore, the genetic diversity (I) among the different populations of C. pomonella at each allele revealed that the maximum diversity was observed for all the alleles 2, 3, 5, 7 and 8 (I = 0.445) while the rest of the alleles were gene diversity (I=0.000). The Shannon information index (h) for each allele of RAPD primer E-09 explicated that maximum Shannon information index (h) were noted for the aforementioned alleles (h=0.637) whilst other alleles 1, 4 and 6 were zero Shannon information index (h=0.000) by using the RAPD primer E-09.

Table-3.8: Gene frequency, diversity and Shannon information index for RAPD primer E09

Allele Allele Size Gene Frequency (f) Gene Diversity S.I.I* (h) (bp) (I) E09-01 10000 0.0000 0.0000 0.0000 E09-02 2500 0.6667 0.4444 0.6365 E09-03 2000 0.6667 0.4444 0.6365 E09-04 1500 0.0000 0.0000 0.0000 E09-05 1000 3.3333 0.4444 0.6365 E09-06 750 0.0000 0.0000 0.0000 E09-07 500 3.3333 0.4444 0.6365 E09-08 250 3.3333 0.4444 0.6365 Mean 250-10000 1.4166 0.2777 0.3978

71

3.4.8. Primer F01

The results illustrated in the Table-3.9. elucidated that a total of 02 detectable scorable alleles were amplified in the three populations of C. pomonella used during the experiment by the RAPD primer F-01. The banding pattern discosed that population from Matta were amplified and that of Kalam and Madyan were not amplified by using RAPD markers F-01 in the current experiment (Fig. 3.3). Maximum of 2 alleles in Matta population and zero alleles were amplified in isolates of Madyan and Kalam. The allele frequency on the basis of amplification pattern revealed that 02 alleles in the Matta population were found in the maximum number of gene frequency (f = 0.334) whilst the rest of the alleles were zero gene frequency in the C. pomonella population in all the three regions (f = 0.000), for the C. pomonella population by using RAPD primer F-01. Nevertheless, the genetic diversity (I) among the different populations of C. pomonella at each allele portrayed that the maximum diversity was observed for the alleles 5 and 6 (I = 0.445) in Matta area whilst the rest of the alleles were zero gene diversity (I=0.000). The Shannon information index (h) for each allele of RAPD primer F-01 explicated that maximum Shannon information index (h) were recorded for aforementioned alleles (h=0.637) whilst other alleles were zero Shannon information index (h=0.000) for the said RAPD primer.

Table-3.9: Gene frequency, diversity and Shannon information index for RAPD primer F01

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) F01-01 1000 0.0000 0.0000 0.0000 F01-02 1500 0.0000 0.0000 0.0000 F01-03 1000 0.0000 0.0000 0.0000 F01-04 750 0.0000 0.0000 0.0000 F01-05 500 0.3333 0.4444 0.6365 F01-06 250 0.3333 0.4444 0.6365 Mean 250-1000 0.1111 0.1481 0.2121 * Shannon Information Index

72

3.4.9. Primer A19

The results showed in Table-3.10. disclosed that a total of 10 detectable scorable alleles were amplified in the three populations of C. pomonella used during the experiment by the RAPD primer A-19. The banding pattern explained that populations from Matta and Kalam were amplified and that of Madyan were not amplified by using RAPD markers A-19 in the experiment (Fig. 3.3). Maximum of 8 alleles in Kalam population and 7 alleles were amplified in isolates of Matta population. The allele frequency on the basis of amplification pattern further explained that alleles no 1, 2, 4, 6, 7, 8 and 10 in the population were found in the minimum number of gene frequency (f = 0.667) while the alleles no 9 was maximum gene frequency in the C. pomonella population (f = 3.333) and only one allele i.e., 3 was gene frequency zero for the C. pomonella population by using RAPD primer A- 19.

Table-3.10: Gene frequency, diversity and Shannon information index for RAPD primer A19

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) A19-01 10000 0.6667 0.4444 0.6365 A19-02 2500 0.6667 0.4444 0.6365 A19-03 2000 0.0000 0.0000 0.0000 A19-04 1500 0.6667 0.4444 0.6365 A19-05 1000 0.0000 0.0000 0.0000 A19-06 750 0.6667 0.4444 0.6365 A19-07 600 0.6667 0.4444 0.6365 A19-08 500 0.6667 0.4444 0.6365 A19-09 300 3.3333 0.4444 0.6365 A19-10 250 0.6667 0.4444 0.6365 Mean 250-10000 0.8000 0.3555 0.5092 * Shannon Information Index

The genetic diversity (I) among the different populations of C. pomonella at each allele elucidated that the minimum assortment was observed for the alleles 3 and 5 (I = 0.000) whilst the rest of the alleles were maximum gene diversity (I=0.445). The Shannon information index (h) for each allele of RAPD primer A-19 expounded that maximum Shannon information index (h) were noted for the above

73 aforementioned alleles (h=0.637) whilst other two alleles i.e., 3 and 5 were zero Shannon information index (h=0.000) by using the RAPD primer A-19.

Fig. 3.3: Electrophoreogrm showing PCR based amplification products of Codling moth Cydia pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers E-19, F-01 and A-19.

3.4.10. Primer D08

The results depicted in Table-3.11. revealed that a total of 09 detectable scorable alleles were amplified in the three populations of C. pomonella used during the current experiment by the RAPD primer D-08. The banding pattern disclosed that populations from Matta and Kalam were amplified and that of Madyan were not amplified by using RAPD markers D-08 in the current experiment (Fig. 3.4). Maximum of 6 alleles in Kalam population and 4 alleles were amplified in isolates of Matta population. The allele frequency on the basis of amplification pattern disclosed that alleles no 3 and 8 in the population were found in the maximum number of gene frequency (f = 3.334) whilst the alleles no 5, 6, 7 and 9 were minimum gene frequency in the C. pomonella population (f = 0.667) and alleles no 1, 2 and 4 were gene frequency zero for the C. pomonella population in three regions by using RAPD primer D-08.

Furthermore, the genetic diversity (I) among the different populations of C. pomonella at each allele elucidated that the maximum diversity was observed for all the alleles (I = 0.445) whilst the rest of the alleles i.e., 1, 2 and 4 were zero gene

74 diversity (I=0.000). The Shannon information index (h) for each allele of RAPD primer D-08 explained that maximum Shannon information index (h) were noted for the above aforementioned alleles (h=0.637) whilst other three alleles i.e., 1, 2 and 4 were zero Shannon information index (h=0.000) by using the RAPD primer D-08.

Table-3.11: Gene frequency, diversity and Shannon information index for RAPD primer D08

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) D08-01 3500 0.0000 0.0000 0.0000 D08-02 3000 0.0000 0.0000 0.0000 D08-03 2500 3.3333 0.4444 0.6365 D08-04 2000 0.0000 0.0000 0.0000 D08-05 1500 0.6667 0.4444 0.6365 D08-06 1000 0.6667 0.4444 0.6365 D08-07 750 0.6667 0.4444 0.6365 D08-08 500 3.3333 0.4444 0.6365 D08-09 250 0.6667 0.4444 0.6365 Mean 250-3500 1.0370 0.2962 0.4243 * Shannon Information Index

3.4.11. Primer G11

The results pertaining to the amplification pattern revealed that a total of 08 detectable scorable alleles were amplified in the three populations of C.pomonella used during the current experiment by the RAPD primer G-11 as depicted in the Table-3.12. The banding pattern shows that population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers G-11 in the current experiment (Fig. 3.4). Maximum of 5 alleles in Kalam population and 0 alleles were amplified in isolates of Matta and Madyan population. The allele frequency on the basis of amplification revealed that all the alleles in the population were found in the maximum number of gene frequency (f = 3.334) except alleles no 4, 5 and 6 were zero gene frequency in the C. pomonella population (f = 0.000) for the C. pomonella population in three regions by using RAPD primer G-11.

Nevertheless, the genetic diversity (I) among the different populations of C. pomonella at each allele disclosed that the maximum diversity was observed for all

75 the alleles (I = 0.445) whilst the rest of the alleles i.e., 4, 5 and 6 were zero gene diversity (I=0.000). The Shannon information index (h) for each allele of RAPD primer G-11 explicated that maximum Shannon information index (h) were recorded for the above aforementioned alleles (h=0.637) whilst other three alleles i.e., 4, 5 and 6 were zero Shannon information index (h=0.000) by using the RAPD primer G-11.

Table-3.12: Gene frequency, diversity and Shannon information index for RAPD primer G11

Allele Allele Size Gene Gene Diversity (I) S.I.I* (h) (bp) Frequency (f) G11-01 3500 3.3333 0.4444 0.6365 G11-02 2500 3.3333 0.4444 0.6365 G11-03 2000 3.3333 0.4444 0.6365 G11-04 1500 0.0000 0.0000 0.0000 G11-05 1000 0.0000 0.0000 0.0000 G11-06 750 0.0000 0.0000 0.0000 G11-07 500 3.3333 0.4444 0.6365 G11-08 250 3.3333 0.4444 0.6365 Mean 250-3500 2.0833 0.2777 0.3978 * Shannon Information Index 3.4.12. Primer F07

The results related to the amplification pattern disclosed that a total of 09 detectable alleles were amplified in the three populations of C. pomonella used during the experiment by the RAPD primer F-07 as illustrated in the Table-3.13. The banding pattern shows that population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers F-07 in the experiment (Fig.3.4). Maximum of 5 alleles in Kalam population and 0 alleles were amplified in isolates of Matta and Madyan populations.

The allele frequency on the basis of amplification expounded that all the alleles in the population were found in the maximum number of gene frequency (f = 3.334) except alleles no 1, 3, 5 and 7 were zero gene frequency in the C. pomonella population (f = 0.000) for the C. pomonella population in three regions by using RAPD primer F-07.

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Table-3.13: Gene frequency, diversity and Shannon information index for RAPD primer F07

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) F07-01 4000 0.0000 0.0000 0.0000 F07-02 3000 3.3333 0.4444 0.6365 F07-03 2500 0.0000 0.0000 0.0000 F07-04 2000 3.3333 0.4444 0.6365 F07-05 1500 0.0000 0.0000 0.0000 F07-06 1000 3.3333 0.4444 0.6365 F07-07 750 0.0000 0.0000 0.0000 F07-08 500 3.3333 0.4444 0.6365 F07-09 250 3.3333 0.4444 0.6365 Mean 250-4000 1.8518 0.2468 0.3536 * Shannon Information Index

Nonetheless, the genetic diversity (I) among the different populations of C. pomonella at each allele explicated that the maximum diversity was observed for all the alleles (I = 0.445) whilst the rest of the alleles i.e., 1, 3, 5 and 7 were zero gene diversity (I=0.000). The Shannon information index (h) for each allele of RAPD primer F-07 explained that maximum Shannon information index (h) were recorded for all aforementioned alleles (h=0.637) except three alleles i.e., 1, 3, 5 and 7 were zero Shannon information index (h=0.000) by using the RAPD primer F-07.

Fig.3.4. Electrophoreogrm showing PCR based amplification products of Codling moth C. pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers D-08, G-11 and F-07.

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3.4.13. Primer E18

The results relate to amplification pattern revealed that a total of 8 detectable bands were amplified in the three populations of C. pomonella used during the experiment by the RAPD primer E-18 (Table-3.14). The banding pattern disclose that populations from Kalam and Madyan were amplified and that of Matta was not amplified by using RAPD markers E-18 in the experiment (Fig. 3.5). Maximum of 8 alleles in Kalam population and 2 alleles were amplified in isolates of Madyan population, whilst zero alleles were amplified in the population of Matta. The allele frequency on the basis of amplification pattern described that all the alleles in the population were found in the maximum number of gene frequency (f = 3.334) except alleles no 6 and 8 having minimum gene frequency in the C. pomonella population (f = 0.667) for the C. pomonella population in three regions by using RAPD primer E- 18.

However, the genetic diversity (I) among the different populations of C. pomonella at each allele explained that the maximum diversity was observed for all the alleles (I = 0.445) in the C. pomonella population in three regions. Likewise, the Shannon information index (h) for all the allele of RAPD primer E-18, was also explicated maximum Shannon information index (h) for all alleles (h=0.637) by using the RAPD primer E-18.

Table-3.14: Gene frequency, diversity and Shannon information index for RAPD primer E18

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) E18-01 3000 3.3333 0.4444 0.6365 E18-02 2500 3.3333 0.4444 0.6365 E18-03 2000 3.3333 0.4444 0.6365 E18-04 1500 3.3333 0.4444 0.6365 E18-05 1000 3.3333 0.4444 0.6365 E18-06 750 0.6667 0.4444 0.6365 E18-07 500 3.3333 0.4444 0.6365 E18-08 250 0.6667 0.4444 0.6365 Mean 250-3000 2.6666 0.4444 0.6365 * Shannon Information Index

78

3.4.14. Primer H14

The results revealed that a total of 6 detectable alleles were amplified in the three populations of C. pomonella used during the current experiment by the RAPD primer H-14 as depicted in Table-3.15. The banding pattern shows that population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers H-14 in the experiment (Fig. 3.5). Maximum of 5 alleles were amplified in isolates of Kalam population, while zero alleles were amplified in the populations of Matta and Madyan. The allele frequency on the basis of amplification pattern explained that all the alleles in the population were found in the maximum number of gene frequency (f = 3.334) except alleles no 2 having zero gene frequency in the C. pomonella population (f = 0.000) for the C. pomonella population in three regions by using RAPD primer H-14.

Furthermore the genetic diversity (I) among the different populations of C. pomonella at each allele was further elucidated that the maximum diversity was afforded for all the alleles (I = 0.445) in the C. pomonella population in three regions except allele 2 having zero genetic diversity in the C. pomonella population. Likewise, the Shannon information index (h) for all the allele of RAPD primer E-18 explained that maximum information of the Shannon information index (h) were noted for all alleles (h=0.637) except allele 2 having zero information by using the RAPD primer H-14.

Table-3.15: Gene frequency, diversity and Shannon information index for RAPD primer H14

Allele Allele Size Gene Gene Diversity S.I.I* (h) (bp) Frequency (f) (I) H14-01 3000 3.3333 0.4444 0.6365 H14-02 1500 0.0000 0.0000 0.0000 H14-03 1000 3.3333 0.4444 0.6365 H14-04 750 3.3333 0.4444 0.6365 H14-05 500 3.3333 0.4444 0.6365 H14-06 250 3.3333 0.4444 0.6365 Mean 250-3000 2.7777 0.3703 0.5304 * Shannon Information Index

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3.4.15. Primer B15

The results related to banding pattern of C. pomonella elucidated that a total of 9 detectable alleles were amplified in the three populations of C. pomonella exploited during the current experiment by the RAPD primer B-15 (Table-3.16). The banding pattern shows that populations from Matta and Kalam were amplified and that of Madyan were not amplified by using RAPD markers B-15 in the experiment. (Fig. 3.5). Maximum of 7 alleles were amplified both in the isolates of Matta and Kalam populations, while zero alleles were amplified in the population of Madyan.

Table-3.16: Gene frequency, diversity and Shannon information index for RAPD primer B15

Allele Allele Size Gene Gene Diversity (I) S.I.I* (h) (bp) Frequency (f) B15-01 3000 0.6667 0.4444 0.6365 B15-02 2700 0.0000 0.0000 0.0000 B15-03 2500 0.6667 0.4444 0.6365 B15-04 2000 0.0000 0.0000 0.0000 B15-05 1500 0.6667 0.4444 0.6365 B15-06 1000 0.6667 0.4444 0.6365 B15-07 750 0.6667 0.4444 0.6365 B15-08 500 0.6667 0.4444 0.6365 B15-09 250 0.6667 0.4444 0.6365 Mean 250-3000 0.5185 0.3456 0.4950 * Shannon Information Index

The allele frequency on the basis of amplification further disclosed that all the alleles in the population were established in the maximum number of gene frequency (f = 0.667) except alleles no 2 and 4 having zero gene frequency in the C. pomonella population (f = 0.000) for the C. pomonella population in three regions by using RAPD primer B-15.

Besides, the genetic diversity (I) among the different populations of C. pomonella at each allele disclosed that maximum diversity was observed for all the alleles (I = 0.445) in the C. pomonella population in three regions except alleles 2 and 4 having zero genetic diversity in the C. pomonella population. Likewise, Shannon information index (h) for all the allele of RAPD primer B-15 further explicated that

80 more information of the Shannon information index (h) were witnessed for all alleles (h=0.637) except alleles 2 and 4 having zero information by using RAPD primer B- 15.

Fig.3.5. Electrophoreogrm showing PCR based amplification products of C. pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers E-18, H-14 and B-15.

3.4.16. Primer C16

The results pertaining to the amplification pattern of the C. pomonella revealed that a total of 3 detectable alleles were amplified in the three populations of C. pomonella used during the current experiment by the RAPD primer C-16 (Table- 3.17). The banding pattern disclosed that populations from Matta and Kalam were amplified and that of Madyan were not amplified by using RAPD markers C-16 in the experiment (Fig. 3.6). Utmost 3 alleles were amplified in isolates of Matta population and minimum of 2 alleles were amplified in the population of Kalam whilst zero alleles were amplified in the population of Madyan. The allele frequency on the basis of amplification pattern disclosed that the maximum number of gene frequency (f = 3.334) whilst alleles no 1 and 3 having gene frequency in the C. pomonella population (f = 0.667) for the C. pomonella population in three regions by using RAPD primer C- 16.

Nevertheless, the genetic diversity (I) among the different populations of C. pomonella at each allele of the primers illustrated that the maximum diversity was

81 recorded for all the alleles (I = 0.445) in the C. pomonella population in three regions. Likewise, the Shannon information index (h) for all the allele of RAPD primer C-16 further explicated that more information of the Shannon information index (h) were recorded for all alleles (h=0.637) by using RAPD primer C-16.

Table-3.17: Gene frequency, diversity and Shannon information index for RAPD primer C16

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) C16-01 1500 0.6667 0.4444 0.6365 C16-02 1000 3.3333 0.4444 0.6365 C16-03 750 0.6667 0.4444 0.6365 Mean 750-1500 1.5555 0.4444 0.6365 * Shannon Information Index

3.4.17. Primer C02

In Table.3.18 the data pertaining to the gene frequency disclosed that a total of 5 detectable alleles were amplified in the three populations of C. pomonella exploited during the current experiment by the RAPD primer C-02. The banding pattern explaine that populations from Matta and Kalam were amplified and that of Madyan were not amplified by using RAPD markers C-02 in the experiment (Fig. 3.6). Maximum of 3 alleles were amplified both in the isolates of Kalam population and 1 allele was amplified in the population of Matta, whilst zero alleles were amplified in the population of Madyan. The allele frequency on the basis of amplification pattern revealed that all the alleles in the population were found in the maximum number of gene frequency (f = 0.667) except alleles no 1 and 2 having zero gene frequency in the C. pomonella population (f = 0.000) for the C. pomonella population in three regions by using RAPD primer C-02.

Nonetheless, the genetic diversity (I) among the different populations of C. pomonella at each allele (Table-3.18) revealed that the maximum diversity was observed for all the alleles (I = 0.445) in the C. pomonella population in three regions except alleles 1 and 2 having zero genetic diversity in the C. pomonella population. Similarly the Shannon information index (h) for all the allele of RAPD primer C-02 explained that more information of the Shannon information index (h) were recorded

82 for all alleles (h=0.637) except alleles 1 and 2 having zero information by using RAPD primer C-02.

Table-3.18: Gene frequency, diversity and Shannon information index for RAPD primer C02

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I1 (h) (bp) (f) C02-01 1500 0.0000 0.0000 0.0000 C02-02 1000 0.0000 0.0000 0.0000 C02-03 750 3.3333 0.4444 0.6365 C02-04 500 3.3333 0.4444 0.6365 C02-05 250 0.6667 0.4444 0.6365 Mean 250-1500 1.4666 0.2666 0.3819 * Shannon Information Index

3.4.18. Primer H03

The data in Table-3.19 disclosed that a total of 4 detectable alleles were amplified in the three populations of C. pomonella used during the current experiment by the RAPD primer H-03. The banding pattern shows that only population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers H-03 in the experiment (Fig. 3.6). Maximum of 2 alleles were amplified in the isolates of Kalam population and zero alleles were amplified in the population of Matta and Madyan. The allele frequency on the basis of amplification pattern expounded that maximum number of gene frequency (f = 3.333) except alleles no 1 and 3 having zero gene frequency in the C. pomonella population (f = 0.000) for the C. pomonella population in three regions by using RAPD primer H-03.

Table-3.19: Gene frequency, diversity and Shannon information index for RAPD primer H03

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) H03-01 1500 0.0000 0.0000 0.0000 H03-02 1000 3.3333 0.4444 0.6365 H03-03 750 0.0000 0.0000 0.0000 H03-04 500 3.3333 0.4444 0.6365 Mean 500-1500 1.6666 0.2222 0.3182

83

Nevertheless, genetic diversity (I) among the different populations of C. pomonella at each allele revealed that the maximum diversity was scrutinized for all the alleles (I = 0.445) in the C. pomonella population in three regions except alleles 1 and 3 having zero genetic diversity in the C. pomonella population. Likewise, the Shannon information index (h) for all the allele of RAPD primer H-03 disclosed that maximum Shannon information index (h) were observed for all alleles (h=0.637) except alleles 1 and 3 having zero information by using RAPD primer H-03.

Fig.3.6. Electrophoreogrm showing PCR based amplification products of C. pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers C-16, C-02 and H- 03.

3.4.19. Primer F04

The results showed that a total of 7 detectable alleles were amplified in the three populations of C. pomonella used during the experiment by the RAPD primer F- 04 as illustrated in Table-3.20. The banding pattern confirmed that only population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers F-04 in the experiment (Fig. 3.7). Maximum of 3 alleles were amplified in the isolates of Kalam population and zero alleles were amplified in the population of Matta and Madyan. The allele frequency on the basis of elucidated that all the alleles in the population were afforded the maximum number of gene frequency (f = 3.333) except alleles no 1, 2, 4 and 5 having zero gene frequency (f = 0.000) in the C. pomonella population in three regions by using RAPD primer F-04.

84

The results further revealed that the genetic diversity (I) among the different populations of C. pomonella at each allele was variable and the (Table-3.20) maximum diversity was observed for all the alleles (I = 0.445) in the C. pomonella population in three regions except alleles 1, 2, 4 and 5 having zero genetic diversity in the C. pomonella population. Similarly the Shannon information index (h) for all the allele of RAPD primer F-04 explained that more information of the Shannon information index (h) were noted for all alleles (h=0.637) except alleles 1, 2, 4 and 5 having zero information by using RAPD primer F-04.

Table-3.20: Gene frequency, diversity and Shannon information index for RAPD primer F04

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) F04-01 2500 0.0000 0.0000 0.0000 F04-02 2000 0.0000 0.0000 0.0000 F04-03 1500 3.3333 0.4444 0.6365 F04-04 1000 0.0000 0.0000 0.0000 F04-05 750 0.0000 0.0000 0.0000 F04-06 500 3.3333 0.4444 0.6365 F04-07 250 3.3333 0.4444 0.6365 Mean 250-2500 1.4284 0.1904 0.2727 * Shannon Information Index 3.4.20. Primer H13

The results showed that a total of 6 detectable alleles were amplified in the three populations of C. pomonella used during the current experiment by the RAPD primer H-13 (Table-3.21). The banding pattern shows that only populations from Kalam and Madyan were amplified and that of Matta were not amplified by using RAPD markers F-04 in the experiment (Fig. 3.7). Maximum of 6 alleles were amplified in the isolates of Kalam population and only one allele was amplified in the population of Madyan while zero alleles were amplified in the population of Matta. The allele frequency on the basis of amplification was computed in all the apple C. pomonella population. When the allele frequency of the whole population was determined, all the alleles in the population were afforded the maximum number of gene frequency (f = 3.333) for the C. pomonella population in three regions by using RAPD primer H-13.

85

Besides, the genetic diversity (I) among the different populations of C. pomonella at each allele was also determined. The results explained that the maximum diversity was detected for all the alleles (I = 0.445) in the C. pomonella population in three regions for the C. pomonella population. Likewise, the Shannon information index (h) for all the allele of RAPD primer H-13 was also calculated and more information of the Shannon information index (h) were noted for all alleles (h=0.637) except alleles 6 having zero information by using RAPD primer H-13.

Table-3.21: Gene frequency, diversity and Shannon information index for RAPD primer H13

Allele Allele Size Gene Gene Diversity (I) S.I.I* (h) (bp) Frequency (f) H13-01 2000 3.3333 0.4444 0.6365 H13-02 1500 3.3333 0.4444 0.6365 H13-03 1000 3.3333 0.4444 0.6365 H13-04 750 3.3333 0.4444 0.6365 H13-05 500 3.3333 0.4444 0.6365 H13-06 250 3.3333 0.4444 0.0000 Mean 250-2000 3.3333 0.4444 0.5304 * Shannon Information Index 3.4.21. Primer G02

The results related to the amplification pattern disclosed that a total of 8 detectable alleles were amplified in the three populations of C. pomonella used during the current experiment by the RAPD primer G-02. The banding pattern confirmed that only population from Kalam were amplified and that of Matta and Madyan were not amplified by using RAPD markers G-02 in the experiment (Fig. 3.7). Maximum of 4 alleles were amplified in the isolates of Kalam population and zero alleles were amplified in the population of Matta and Madyan. The allele frequency on the basis of amplification was calculated in all the apple C. pomonella population. When the allele frequency of the whole population was determined, the alleles 3 in the population were found in the maximum number of gene frequency (f = 3.333) whilst rest of alleles were gene frequency (f=0.333) except alleles no 1, 2, 4 and 6 having zero gene frequency (f = 0.000) in the C. pomonella population in three regions by using RAPD primer G-02 (Table-3.22).

86

Table-3.22: Gene frequency, diversity and Shannon information index for RAPD primer G02

Allele Allele Size Gene Frequency Gene Diversity (I) S.I.I* (h) (bp) (f) G02-01 3000 0.0000 0.0000 0.0000 G02-02 2500 0.0000 0.0000 0.6365 G02-03 2000 3.3333 0.4444 0.0000 G02-04 1500 0.0000 0.0000 0.0000 G02-05 1000 0.3333 0.4444 0.6365 G02-06 750 0.0000 0.0000 0.0000 G02-07 500 0.3333 0.4444 0.6365 G02-08 250 0.3333 0.4444 0.6365 Mean 250-3000 0.5416 0.2222 0.3978 * Shannon Information Index

The data pertaining to the genetic diversity (I) among the different populations of C. pomonella at each allele in depicted in Table-3.22. The results disclosed that the maximum diversity was observed for all the alleles (I = 0.445) in the C. pomonella population in three regions except alleles 1, 2, 4 and 6 having zero genetic diversity in the C. pomonella population. Similarly the Shannon information index (h) for all the allele of RAPD primer G-02 was also calculated and more information of the Shannon information index (h) were recorded for all alleles (h=0.637) except alleles 1, 2, 4 and 6 having zero information by using RAPD primer G-02 (Table-3.22).

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Fig.3.7. Electrophoreogrm showing PCR based amplification products of C. pomonella population collected from three regions (Matta, Kalam and Madyan) of District Swat by using RAPD primers F-04, H-13 and G-02.

3.4.22. Nei’s unbiased measures of genetic identity and genetic distance

Table-3.23. pertaining to the Nei's genetic identity (above diagonal) and genetic distance (below diagonal) among the three population of C. pomonella. Higher genetic distance was observed among the isolates from Kalam and Madyan (97.87 %) whereas low genetic distance (35.58%) was calculated from the C. pomonella isolates from Matta and Madyan, which indicates that the population of C. pomonella in both the regions has not so variation/diversity as compared to population in Kalam. Similarly the Nei's genetic identity revealed that higher genetic similarity (70.06%) was resided by the C. pomonella population at Matta and Madyan while the low level of identity (37.58%) were examined in isolates from Madyan and Kalam (Fig: 3.8).

Table-3.23: Nei’s unbiased measures of genetic identity (Above diagonal) and genetic distance (Below diagonal) for C. pomonella populations collected from three geographically distant region Swat based on 21 RAPD primers analysis

Population Matta Kalam Madyan

Matta ...... 0.5732 0.7006

Kalam 0.5564 ...... 0.3758

Madyan 0.3558 0.9787 ......

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Cydia pomonella (Matta Population)

Cydia pomonella (Madyan Population)

Cydia pomonella (Kalam Population)

0 10 20 38

Fig. 3.8. Dendrogram constructed on the basis of similarity index among three populations of C. pomonella (Matta, Madyan and Kalam) based on RAPD data using UPGMA and Nei’s genetic index.

3.4.23. RAPD primers used for molecular characterization of C. pomonella at Swat during the year 2012-2013

The results pertaining to gene frequency of the RAPD primers divulged that out of 30 RAPD primers, 21 primers gave the banding pattern for finding out the molecular characterization of the C. pomonella in three locations namely Matta, Kalam and Madyan of District Swat during the year 2012 and 2013 (Table-3.24). Highest gene frequency on the basis of amplification pattern was observed for RAPD primer H-13 (3.33) followed by H-14 (2.77), E-18 (2.66), G-11 (2.08), F-07 (1.85), H- 03 and B-04 (1.66) each, C-16 (1.55), C-06 (1.55), C-02 (1.46), E-09 (1.41), F-04 (1.42) and D-08 (1.03), whilst the rest of RAPD primers depict the allele frequency below 0.99. The overall mean of the genetic frequency among three populations of C. pomonella calculated was 1.33.

On the basis of amplification pattern, the genetic diversity of the three populations of the C. pomonella expounded that highest genetic diversity was recorded for the RAPD primers C-02, E-18 and C-16 (0.44 each), followed by C-13 (0.38), H-14 (0.37), A-19 (0.35), B-15 (0.34), B-12 (0.33) and B-04 (0.32), whilst the rest of the RAPD primers explicated below 0.29 genetic diversity among three

89 populations of the C. pomonella. The overall mean of the genetic diversity of the three populations was 0.29.

The results pertaining to Shannon's information index for each allele of the primers revealed that maximum Shannon information index were observed for C-04, E-18 and C-16 (0.63), followed by C-13 (0.55), H-13 (0.53) and A-19 (0.50), whilst the rest of the primers were less than 0.49 Shannon's information index values. The overall mean of the Shannon's information index was 0.44.

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Table-3.24: Mean Gene frequency, diversity and Shannon information index for RAPD primers used for molecular characterization of C. pomonella at Swat during the year 2012-13 S. No RAPD Primers Total Alleles Range of Allele size G. F (f)1 G. D (I)2 S. I. I. (h)3 used Amplified (bp) 1. B-12 08 250-10000 0.4166 0.3333 0.4773 2. D-16 08 250-10000 0.2500 0.2222 0.3182 3. C-04 06 750-10000 0.5555 0.4444 0.6365 4. C-13 08 250-10000 0.9166 0.3888 0.5569 5. B-04 11 250-4500 1.6666 0.3232 0.4629 6. H-02 10 250-4500 0.9999 0.1333 0.1909 7. E-09 08 250-10000 1.4166 0.2777 0.3978 8. F-01 06 250-10000 0.1111 0.1481 0.2121 9. A-19 10 250-10000 0.8000 0.3555 0.5092 10. D-08 09 250-3500 1.0370 0.2962 0.4243 11. G-11 08 250-3500 2.0833 0.2777 0.3978 12. F-07 09 250-4000 1.8518 0.2468 0.3978 13. E-18 08 250-3000 2.6666 0.4444 0.6365 14. H-14 06 250-3000 2.7777 0.3707 0.5304 15. B-15 09 250-3000 0.5185 0.3456 0.4950 16. C-16 03 750-1500 1.5555 0.4444 0.6365 17. C-02 05 250-1500 1.4666 0.2666 0.3819 18. H-03 04 500-1500 1.6666 0.2222 0.3182 19. F-04 07 250-2500 1.4284 0.1904 0.2727 20. H-13 06 250-2000 3.3333 0.4444 0.5304 21. G-02 08 250-3000 0.5416 0.2222 0.3978 Mean --- 07 250-10000 1.33618 0.30467 0.4372 1.Gene frequency (f) 2. Genetic Distance (I) 3. Shannon Information Index (h) .

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3.5. DISCUSSION

A very limited research work has been carried out regarding genetic differentiation and molecular characterization of C. pomonella (Franck et al., 2007). The current studies on molecular characterization of C. pomonella, was consequently undertaken to know about the genetic differentiation and gene flow among C. pomonella population through RAPD primers. The results disclosed that out of 30 randomly amplified polymorphic DNA (RAPD) primers used for the molecular characterization of C. pomonella, 21 primers amplified the banding pattern for finding out the molecular characterization and distinction in the population of C. pomonella in three locations namely Matta, Kalam and Madyan of District Swat on the basis of samples collected during the year 2012-13. On the basis of amplification pattern, highest gene frequency (f) was evaluated for RAPD primer H-13 (f = 3.33) followed by H-14 (f = 2.77), E-18 (f = 2.66), G-11 (f = 2.08), F-07 (f = 1.85), H-03 and B-04 (f = 1.66) each, C-16 (f = 1.55), C-06 (f = 1.55), C-02 (f = 1.46), E-09 (f = 1.41), F-04 (f = 1.42) and D-08 (f = 1.03), whereas the rest of RAPD primers depicted the allele frequency below 0.99. The overall mean of the genetic frequency among three populations of C. pomonella observed was 1.33. These results are in close conformity with findings of Lei Men et al., (2012) who reported that the mean number of alleles per locus ranged from f = 4.3 to f = 12.6 and two populations of C. pomonella from Heilongjiang Province in northeastern China had the largest number of alleles (f = 12.6 and f = 10.6). Of populations from northwestern China, one population showed the highest value of mean number of alleles (f = 9.6), followed by the second population (f = 8.6) and third population (f = 8.4). Nevertheless, the gene frequency of null alleles ranged from 0.010 to 0.203, values typical for lepidopterans (Megle'cz et al., 2004; Dakin and Avise, 2004), which further confirmed these results.

On the basis of intensification pattern, the genetic diversity (I) of the three populations of the C. pomonella disclosed that highest genetic variation was detected for the RAPD primers C-02, E-18 and C-16 (I = 0.44 each), followed by C-13 (I = 0.38), H-14 (I = 0.37), A-19 (I = 0.35), B-15 (I = 0.34), B-12 (I = 0.33) and B-04 (I = 0.32), while the rest of the RAPD primers elucidated below 0.29 genetic diversity among three populations of the C. pomonella. The overall mean of the genetic diversity of the three populations was 0.29. These results are in close concordance with findings of Khaghaninia et al. (2009). They found out that by using RAPD

92 primers genetic diversity within population of C. pomonella based on Nie's gene index ranged from 0.228 to 0.281 at Shabestar and Zunuz populations, respectively. They also observed the maximum (0.14) and minimum (0.04) genetic distances between the population of C. pomonella at different geographical locations in Iran. Contrary to our results regarding genetic diversity among the population of C. pomonella, Bues et al. (1995), observed low genetic differentiation between sampled populations of C. pomonella by using allozyme markers. Chen and Dorn (2010) reported important genetic differentiation at local geographic scale (even less than 10 km), which they mostly attributed to the sedentary behaviour of C. pomonella through microsatellite study on populations from Switzerland.

The highest Shannon's information index (h) for each allele of the primers C- 04, E-18 and C-16 were h = 0.63, followed by C-13 (h = 0.55), H-13 (h = 0.53) and A-19 (h = 0.50), whereas the rest of the primers were less than 0.49 Shannon's information index (h) values. The overall mean of the Shannon's information index (h) was 0.44. These results are closely corroborated with findings of Timm et al. (2006) who reported that genetic variation among the population of C. pomonella was 0.18 in South Africa. However, only three were monomorphic and resulting 98.60% polymorphism in the population. They further concluded that genetic diversity within C. pomonella population in England and Canada were variable which were ranges from h =0.046 and 0.052 respectively.

The results pertaining to the Nei's genetic identity and genetic distance among the three populations of C. pomonella was also worked out. Higher genetic distance was resided among the isolates from Kalam and Madyan (97.87%) whereas low genetic distance (35.58%) was observed in the C. pomonella isolates from Matta and Madyan, which indicates that the population of C. pomonella in both the regions has not so multiplicity as compared to population at Kalam. Khaghaninia et al. (2009) observed the maximum and minimum genetic distances between the population of C. pomonella at different geographical locations in Iran and significant correlation was noticed between genetic and geographic distance matrices in the population of C. pomonella revealed by Mantel test. It is assumed that due to chaange in the climatic conditions and frequent application of insecticide, C. pomonella populations separated into many strains and ecotypes having different biological and physiological

93 requirements related to their development (Thaler et al., 2008). These results contrast with those obtained for C. pomonella populations from France and Switzerland, by using allozyme analysis disclosed highly significant genetic similarity between and among geographic populations (Bue's and Toubon, 1992).

Likewise, the Nei's genetic identity was also found. The higher genetic similarity (70.06%) was dwelled by the C. pomonella population at Matta and Madyan whilst the low level of identity (37.58%) was examined in isolates from Madyan and Kalam. Timm et al. (2006) used AFLP markers and successfully ascertained differences among sampled C. pomonella populations even at small geographic distances. Besides, Timm's et al. (2006) study was back up by Thaler et al. (2008) who also used AFLP markers to study the molecular phylogeny and genetic diversity of C. pomonella population.

Different methods of C. pomonella control such as use of carbamate, hydrocarbons, organophosphates, pyrethroids and even avermectin have created history in fruit production for their expansion. Indiscriminate use of chemical has created an alarming situation as the pest developed resistance to different groups of chemical. But biotechnical and biological means of protection are indispensable for pest management having limited approaches on mass field level. The changes in the insect populations might be definitely associated with the change in the envirinmental factor such as temperature and insecticides application. Now more emphasis are given on the use of new ways and methods such as use of genetic studies on molecular level of their population. It is evident from various research that the survival and expansion of C. pomonella is mostely relate to maximum genetic variation of its population and more resistance ecotypes and strains in their population. For effective methods of control are dire need of the time for the management and control of C. pomonella, otherwise pest will be out of control for ever as described by Boivin et al. (2001). According to Hoy (2003) attractive alternative to chemical control in terms of safety, specificity, and limited negative environmental impact is application of genetic control (the sterile insect technique or SIT) and biological control.

According to Higbee et al. (2001) C. pomonella populations from South Africa, collected from regions situated close together geographically were not necessarily more closely related genetically than those situated further apart. This

94 pattern of genetic variation could be because of human intervention in the form of fruit and seedling transport as well as the movement of bins, which may have played an important role in the mixing of populations from distant geographic regions.

According to Frank et al. (2005) two populations suggest that C. pomonella populations may vary over relatively short periods of time. The data add to a body of evidence indicating that insecticide application is one important factor shaping temporal genetic deviation among populations. Insecticide use has also been shown to be a significant factor in structuring C. pomonella populations over local geographic scales (Franck et al., 2007).

These results may have important implications for practices used for managing population levels of C. pomonella, because tactics such as chemical control (IGR), pheromone mating disruption, and Sterile Insect Technique (SIT) are affected by insect dispersal and genetic diversity among populations.

95

3.6. CONCLUSIONS

RAPD markers are efficient tools for assessing the population variation in insect pests and knowledge of the genetic variation within C. pomonella populations is necessary for their efficient control and management, thus such studies may offer an insight on the possible resistance to insecticides. Higher genetic distance was observed among the isolates from Kalam and Madyan (97.87 %) whereas low genetic distance (35.58%) was calculated from the C. pomonella isolates from Matta and Madyan. Similarly higher genetic similarity (70.06%) was resided by the C. pomonella population at Matta and Madyan, while the low level of identity (37.58%) were examined in isolates from Madyan and Kalam. Higher genetic distances among the populations of C. pomonella could be attributed to climatic conditions of the studied areas, geographical locations and elevations.

3.7. RECOMMENDATIONS

The above findings lead to the following recommendations.

1) Knowledge of the genetic variation within C. pomonella populations is necessary for their efficient control and management, RAPD markers are therefore, can be efficiently used for assessing the population variation in C. pomonella. 2) Besides RAPD primers, gene specific primers and methods like AFLP and RFLP can also be used for molecular variation among the population of C. pomonella and other lepidopterious pests. 3) Nonetheless, further study should be carried out in this perspective to assess the molecular variation among the population of this pest more effectively.

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Zimmermann, M., N. Wahlberg and H. Descimon. 2000. Phylogeny of Euphydryas Checkerspot Butterflies (Lepidoptera: Nymphalidae) based on mitochondrial DNA sequence data. Annu. Entomol. Soc. Am. 93: 347-55.

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CHAPTER - 4: MANAGEMENT OF C. POMONELLA (LEPIDOPTERA; TORTRICIDAE)

4.1. INTRODUCTION

4.1.1. Use of Insecticides for the Management of Cydia pomonella

The C. pomonella is a serious pest of apple throughout the world (Bajwa, 1993) including subcontinent (Croft and Penman, 1989). It is generally control with prophylactic use of broad-spectrum insecticides. The superfluous and repeated use of these insecticides has been alluded to many undesirable side effects namely environmental pollution, destruction of useful predators and parasites, poison hazard to man and livestock and consequently domination of secondary pests, development of resistance to insecticides and increase expensis of the farming community. One frequent consequence of chemical application against C. pomonella is the rapid elimination of bioogical control agents allowing other pest species to resurge. It may lead to the need for extra pesticide application. As a response to these flaws, over the past two decades, alternate methodologies have been investigated (Croft and Penman,1989; Lacey and Unrih, 2005). The alternate approach includes using selective, environment friendly and safe pesticides and to enhance use of biological control agents (Croft and AliNiazee, 1996).

Permutation of microbial and chemical insecticides is a way of curtailing the environmental contamination caused by using chemical insecticides alone while still maintaining an effective pest control program. Most insecticides are compatible with microbial insecticides with little or no adverse effect on biological control agents. Among microbial insecticides, granular viruses is the most versatile use in pest management systems mainly because of its selective activity against many lepidopterous pest insects (Ignoffo and Gregory, 1972) and its compatibility with many chemical pesticides (Benz, 1971; Chen et al., 1974). However, information on toxicity and interaction of various combination of these products and sub lethal dosages of chemical insecticide against C. pomonella is limited. It is possible that the approach based on using low rates of registered chemical insecticides with microbial insecticides may not only afford an effective control of the C. pomonella but also prolong the effective life of insecticides and ensure preservation of the key predatory insects.

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Several research efforts to develop substitute control techniques providing both pest suppression and reduction of the negative side effects of the pesticide approach have been undertaken for the management of C. pomonella. The techniques which confirmed some success include the use of reduced insecticide dosages (Bastiste, 1972; Barnett et al., 1977), the use of insect growth regulators (Westigard, 1979; Burts, 1983; Westigard and Gut 1986; Moffitt et al., 1988), mating disruption (Howell et al., 1992; Barnes et al., 1992), biological control with viruses (Jaques and Morris, 1981; Glen and Payne, 1983), release of sterile adults (Proverbs et al., 1966) and utilization of low dosage mixtures of microbial and chemical insecticides (Tomova and Ragelova, 1977).

In spite of relatively large number of insecticides available for control of this pest, the C. pomonella continues to facade a serious peril, especially because of development of resistance to various groups of insecticides in many parts of the world (Pasquier and Charmillot, 2003). Resistance is a relatively recent problem in Europe and appeared first in the early nineties of the past century (Charmillot et al. 1999; 2000). The laboratory studies carried out by Becid (1997) in France have confirmed the development of resistance and cross-resistance to all insecticides used for conventional control. Eeven though increase in use of insecticides, damage caused by C. pomonella in Bulgarian apple orchards has steadily increased from 2002 till 2007.

Different methods of control have been used against the C. pomonella. Chemical control has been the most broadened method for a long time. After appearing resistant to DDT, the typical compounds used have been organophosphates and carbamates. But the pest has been developed resistance to azinphomethyl and other organophosphates in California and Washington (Croft and Riedl, 1991). Avermectin, a fermentation by product from avermitilis, also can be effective, especially in the start of a season against the neonates in the orchards (Croft and Riedl, 1991).

For the management of C. pomonella control farming community mostly rely on use of of broad spectrum insecticides. This kind of control leads to many environmental and health related issues. Nowadays, pheromone traps for monitoring of pest are widely used and the most easy way to monitor the pest and time of application of management strategies. The use of more selective insecticides such as insect growth regulator (IGR) is recommended but still organophosphate are mostly used in diffeerent of the world. Careful control strategies must be adopted to circumvent the appearance of resistant

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population to insecticides, as it has already been reported (Charmillot et al., 1999). It is essential to blend insecticides with different mode of action, or to combine insecticides with intercrops and examine its impact on biological control agents and ultimately on the yield (Avilla et al.,1996).

4.1.2. Impact of Intercropping on Biological Control Agents and Pest

Intercropping is the cultivation of more than one crop within the same field for the attraction of natural enemies by providing more food and shelter for the insect diversity within agro ecosystem (Vandermeer, 1989; Theunissen, 1994). Flowering species of plants such as clovers, mustard, soybean etc can provide suitable environment for the biological control agents to survive and reproduce compared to the field having single crop within that agro ecosystem (Theunissen, 1994). Hence, the habitate having polycultures will be more stable and will be less pest infestation and diseases attack compared to monocroping environment (Altieri and Nicholls, 2004).

The biological, chemical, structural and climatic factors in fact representd resistance which possibly reduce the pest infestation (Alteri et al., 1978). The reduction of pest infestation was widely noted in early reviews on intercropping (Risch et al., 1983; Vandermeer, 1989; Litsinger and Moody, 1976), avoidance of dispersal (Altieri, 1987) production of adverse stimuli, olfactory stimuli camouflaged by main crop, presence of natural enemies (Russell, 1989) and openness of food (Fukai and Trenbath, 1993). Research in diversified agro-ecosystem articulateed that these systems tend to support less herbivores load than in monoculture system (Altieri and Letourneau,1982).

The association between various climate uneven and insect pests and biological control agent is significant and there is a need to enumerate them in a different cropping systems. The research studies are to be conducted in a systematic way to come out with a workable IPM strategy (Rao and Rao, 1996 and Srinivasa Rao et al., 1999). Intercropping is one of the best and effective cultural practice in pest management, which is based on the principle of curtailing insect pests by rising the diversity of an agro ecosystem (Letourneau and Altieri, 1983; Risch et al., 1983).

Supplying food suplements and resources within crops will be very essential for increasing natural enemies abundance especially the parasitoids and predators in the field (Kruess and Tscharntke, 1994; Landis et al., 2000; Tscharntke et al., 2005). This

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techniques can slo provide overwintering sites for the beneficial insects as well as to the alternate host in the field (Tscharntke et al., 2005; Wackers et al., 2005). Majority of the insect such as lacewings, , spiders and parasiotoids are mostlt feeding on the plants materials (Duso et al., 2004) and for some insects food materials are vital for their survival during their life cycel (Sommaggio, 1999). Examples of such insect are from the dipteran families Syrphidae (MacLeod,1999) and Tachinidae (Platt et al.,1999) which can increase their population in the presence of flowering plants in the fieled which can provide them pollen and nectors as source of food for their survival (Jervis et al., 1993; Patt et al., 1997; Begum et al., 2006; Stephens et al., 2006).

Several scientists studied that in nthe presence of flowering plants biological control of a particular pest can easly be achieved within an agro ecosystem (Hickman and Wratten, 1996; Hooks and Johnson, 2003; Gurr et al., 2004; Ponti et al., 2007). Through potential pest management techniques the infestation of cabbage aphids were reduced (Hooks and Johnson, 2003). Likewise, intercropping corn and soybean enhanced the occurance of carabid predators and utilization of Ostrinia nubilalis (Hubner) (Lepidoptera; Crambidae) pupae used as sentinel prey (Tillman et al., 2004; Prasifka et al., 2006). Nonetheless, when the parasitoid and predators ratio increase in the field thtrough intercrops may not essentially control the pest if the both of then not synchronized (Baggen and Gurr, 1998).

4.1.3. Biological Control Agents of C. pomonella

Natural enemies such as parasitoids are considered as the most effective biological control agent for the management of different pest in thye apple orchard. Several authors demonstrated the influence of flowering plants on beneficial insects which provide them protein and carbohydrates food in the pollen and nectors for their longivity, fertility and fecundity of the adults parasitoids in the field (Foster and Ruesink, 1984). Leius (1960). Some parasitoids mostly rely on the species as source of food for their survival. C. pomonella parasitization and their relation with flowering plants in the unsprayed apple orchard was previously studied (Leius, 1960).

Ascogastor quadridentata (Wesmaels) (Hymenoptera: Braconidae) is a biological control agent that shows promise for reducing C. pomonella populations. By ovipositing into eggs of C. pomonella, A. quadridenata is able to circumvent the protection of larvae received once they are inside the apple and are no longer accessible to attack. In Eurasia,

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where C. pomonella is believed to have originated, A. quadridentata is one of the most common parasitoids collected from overwintering C. pomonella larvae (Brown and Reed-Larsen, 1991).

According to Clausen (1978) A. quadridentata was released in South Africa in the 1920s, and was recovered in selected locations as late as 1936. A. quadridentata was released in New Zealand, Australia, Peru and West Pakistan between the 1930s and 1960s with undetermined or less success in some orchards (Rao et al., 1971; Clausen, 1978).

Hyssopus pallidus (Askew) (Hymenoptera: Eulophidae) is another gregarious etoparasitoid of the late 5th larval instars of C. pomonella, a widely distributed major fruit pest (Brown, 1996). It can lower the infestation level of its host to a level that allows the successful application of any safe control measure for the effective management of C. pomonella. (Mattiacci et al., 1999). Judd et al. (1997) reported that good control of C. pomonella was achieved in British Columbia with combination of mating disruption, tree banding and post harvest fruit removal of infested fruit in the orchard. (Kyamanywa and Tukahirwa, 1988; Ogenga-Latigo et al., 1993; Abate et al., 2000).

Natural enemies of C. pomonella play a key role in the effective pest control both in organic or IPM regimes and their suppression by chemicals can be source of problems in plant protection. One of the possibilities to enhance activity of predators and parasitoids in crops is to increase diversity of plant species (Andow, 1991). Higher plant species diversity influences nature enemies due to more favorable microclimate (Dyer and Landis, 1996), owing to presence of alternative hosts or pray in polyphagous parasitoids and due to production of nectar, pollen, shelter and honeydew (Winkler et al., 2006). A positive influence of nectariferous plants on the fitness of beneficial in a lot of studies has been reported by various authors (English-Loeb et al., 2003; Lee et al., 2004; Berndt and Wratten, 2005).

The tremendous biodiversity of parasitoids in apple orchards has been observed and wide research has been performed on their isolation, identification and significance as biological control agents both in different countries of the world. (Atanassov et al., 1997; Balevski, 2009; Pluciennik and Olszak, 2010). Astonishingly, there have been no

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attempts to follow emergence of biological control agents and estimated their role for suppression pest lepidopteran populations in new planted apple orchards.

The response of biological control agent populations to habitat exploitation depends upon their ability to use or exploit one or more of the plant components of the agro-ecosystem (Altieri and Nicholls, 2004). Crop systems that are dominated by a single plant species only provide resources to those selected organisms that can exploit that single plant species. (Altieri and Nicholls, 2004). Consequently, monocultures are an example of agro-ecosystems with low diversity and may be more susceptible insect infestation than the poyculture (Theunissen, 1994; Altieri and Nicholls, 2004).

The current studies were therefore undertaken to discern the efficacy of novel insecticides against C. pomonella, impact of prevailed practices of different intercropping on the management of C. pomonella, its associated available parasitoids, combination of insecticide and intercropping and their ultimate impact on the yield of apple orchard in Matta Swat Pakistan during the year 2012 and 2013.

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4.2. REVIEW OF LITERATURE

4.2.1. Use of Insecticides for the Management of C. pomonella

Traditionally, insecticides have been employed to accomplish this, but the development of resistance in C. pomonella to different groups of chemicals (Brown, 1993), the registration of many insecticides and the harmful impact of insecticides on beneficial organisms and the environment (Putman, 1963; Dolstad, 1985; Brown, 1993) have generated great interest in alternative controls for C. pomonella. Great efforts to eradicate C. pomonella using the sterile male technique or pheromone-based mating disruption, use of microbial insecticides (reviewed in Riddick and Mills, 1994) are currently under way. Biological control agents could be important components in an integrated pest management program for C. pomonella (Brown, 1993; Lacey et al., 2008) when organophosphates are replaced by more benign alternative controls such as use of microbial insecticides.

Lethmayer et al. (2009) studied that control of C. pomonella is not feasible in the current situation due to development of resistance to different group of chemicals, change in the climatic factors of environment and non availability of effective plant protection measures for this pest. All the products gave up to biological efficacy of up to 64% and not mnore than it. Different alternative controlo methods are been carried out in Australia in 2007 and finally concluded that efficient control of this pest is still the dire need of the time. More emphasis should be given on integrated management for this pest. The products which were used during the experiments were accrording to the EPPO standard. The total infestation rate in the control plots was 75%.

Doerr et al. (2012) reported that Azinphos-methyl (AZM) has been mostly used for the management of pest in apple production in the United States since the late 1960s, primarily as a control for the key pest of apple (Malus domestica Borkh.), C. pomonella L. It was obvious that new insecticides could not provide fruit protection superior to protection provided with AZM. The most successful techniques working insecticides that targeted both eggs (ovicides) and larvae (larvicides). Field experiments were carried out from 2004 to 2008 to inspect new application timings and strategies that integrated insecticides with different modes of action and different life stages.

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Pluciennik (2012) conducted a series of experiments aimed at testing the usefulness of the new insecticide chlorantraniliprole in the control of C. pomonella L. during the year 2006 and 2007. The product was applied in various doses for the management of this pest. The control treatments were applied 2 or 3 times, depending on pest threat. It was observed that there was a significant cutback in the amount of fruit the C. pomonella larvae were able to damage in all the conducted experiments. Very good results in C. pomonella control were obtained after application of the tested product at a dose of more than 0.125 liter/ha.

4.2.2. Impact of Intercropping on Biological Control Agents and Pest

Cultivating two or more crop species within the same agro ecosystem is called intercropping is a new method to enhance relative abundance and diversity of the natural enemies for the management of pest (Vandermeer, 1989; Theunissen, 1994). This technique can provide favourable environment for the various biological control agents for their survival on flowering plants for the effective management of different pest in the system (Theunissen, 1994). Hence, these methods are fantastics for increasing the ratio of natural enemies and reducing the pest species in the prevailed field conditions (Altieri and Nicholls, 2004; Beizhou et al.,2011). New research proved that by intercropping pear orchards with aromatic plants can substantially reduced the pest species compared the plots having natural grasses or with out grasses. Further, maximum number of the natural enemies were recorded in the intercropped orchard.

Bhatnagar and Davies (1979) studied that pests are significant yield reducers in various crops and hence pest management was widely addressed by researchers. Crop- crop diversity is possible when crop plant species can be arranged in space by intercropping, inter-planting and mixed-row cropping. The monocultures or sole cropping systems, although highly productive and efficient, have been criticized because of their genetic uniformity resulting into continuous pest susceptibility.

Altieri (1995) reported carrot family have small open flowers which more suitable and attractive for the natural enemiesfor pollen and nectors having short probosci such as and parasitoids wasps in most of agro ecosystem. This practices can be applied in the apple orchard for the efftive and efficient control of C. pomonella and leafroller caterpillars through parasioids. Some time flower strips of other plants species such as borage, clover, chamomile, yarrow and cornflower can be useful for attarcting the natural

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enemies. Other plant species such as leaves and seed of nastutium limiting the activities of C. pomonella through providing food for the bio control agents in the system.

.Kienzle et al. (1997) explored the population dynamics and fluctuation of tortricid pest with respect to their parasitoids ratio in eight ecological apple orchard having intercrops. Different parasitoids such as Cotesia xanthostigma Hal. or Meteorus ictericus Nees were found relative in maximum number as compared to other species in the apple orchard which were relative in small number for the effective management of apple pest. Hence, polyculture environment is more favourable for the benefical insect as compared to monoculture system of crop.

Srinivasa Rao, et al. (2002) investigated the percent population and relative abundanc of several pest were reduced in the presence of crop-crop diversity through intecropping in the field. Pulses are mostly intecropped in the crops which benefit the selected crop. Natural enemies are often benefited from polyculture environment. So the role of microclimatic cindition is more significant for increasing the beneficial insect population in the agro ecosystem. However, more care should be taken regarding the selection of crop to be cultivated as in the main crop for the attraction of natural enemies.

Srinivasa Rao et al. (2002) also reported that the successes of pest control by intercropping/ crop-crop diversity techniques among the various possible factors which are responsible for this pest reduction, the role of biological control agents and change in microclimate is significant. These are the plausible and obvious reasons to explain the lower incidence of pests in intercropping systems. It can be therefore wrap up that for successful control of a given pest by crop- crop diversity the creation of the diversity should match the condition of the pest. Besides, a clear understanding of change in crop structure, microclimate change and associated entomo fauna should be considered. Nonetheless, all attempts may not lead to successful restrain of insect pests at all cases. Repetition through years and locations will add credibility and relevance to the results.

Nicole et al. (2009) examined that intercrops have the capability to attaract maximum number of natural enemies for the effective management of pest and as result chemical usage will be reduced. Appropriate plant species should be selected which will not compete for food, water and shelter within main crop. The cover crops tested- Queen Anne’s lace, chicory Cichorium intybus, Foeniculum vulgare (Apiaceae),

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Fagopyrum esculentum (Polygonaceae), white mustard Sinapis alba (), yarrow Achillea millefolium (Asteraceae), buckwheat and fenugreek Trigonella foenum- graecum (). However, they recorded no evidence for suppressing the population of pest in the apple orchard and as result pest activity were maximum in the field having no intecrop.

Beizhou et al. (2011) recently reported that relative abundance and occurance of natural enemies can be enhanced through intecropping which can curtailed the pest infestation compared to the orchard having no intercrop or sole orchard. Hence aromatic plants can attarct significant number of natural enemies for the management of C. pomonella.

Wan et al. (2014) conducted two years field experiment at two sites in eastern China, examining the effects of the ground cover by L.on the biocontrol services in peach orchards. The results indicated that compared to those in control areas, the abundances of aphids and Grapholitha molesta decreased, respectively, by 31.4% and 33.3% in Shanghai and by 30.1% and 33.3% in Jiangsu, while the abundance of generalist arthropod predators increased by 116.7% in Shanghai and by 115.8% in Jiangsu in ground cover areas in China. Compared to that in control areas, the ratio of generalist predator abundance to aphid abundance and to G. molesta abundance increased, respectively by 260.0% and 384.2% in Shanghai and by 213.3% and 253.1% in Jiangsu in ground cover areas. These studies revealed that the ecological engineering of ground cover by T. repens promoted biological control services in peach orchards.

4.2.3. Biological Control Agents Associated with C. pomonella

Glen, (1982) reported new species of the parasitoids were introduce in to the pear orchard in California from Central Asia, China and Europe. Three parasitoids species such as Mastrus ridibundus, Hyssopus pallidus and Liotryphon caudatus were maintained in the laboratory for further realease in to the field. H. pallidus is the larval parasitoid and has the potential to management the pest, Microdus rufipes is a solatary larval parasitoid that is mostly goes in to the overwintering in the cocoon of C. pomonella were also released to field. Results showed that both of the natural enemies increased their population in the pear orchard and were recoverd from the same field later on.

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Charmillot et al. (1997) examined that Ascogaster quadridentata Wesmaels that belong to the genus Trichogramma (Braconidae) is the most important parasitoid of C. pomonella eggs and the natural enemy with a bigger potential in IPM programs. The adult female laid the eggs in the C. pomonella egg and the larva develops during the egg and larval stages of the host. With low population levels of the C. pomonella, it achieves parasitism levels up to 5%, which shows its parasitism in searching behavior by the adult female. Furthermore, as host levels increase, the percentage of parasitism also rises.

Charmillot et al. (1997) investigated that H. pallidus (Eulophidae) is a gregarious ectoparasitoid of late instar C. pomonella. The small parasitoid adults enter infested fruit to find their hosts and will attack all later larval instars of the C. pomonella. The host larva is paralyzed and then a series of eggs are laid externally on the host. This parasitoid species can readily be reared on larger C. pomonella larvae and does not require the presence of the host plant to secure host attack in captivity. Development of the parasitoid Trichomma enecator Rossi is completed inside the host pupa under the bark. Nonetheless, success in rearing T. enecator on thinning apples infested with C. pomonella larvae has so far been limited. It seems unlikely that this species can be reared in sufficient numbers to secure field establishment for the effective management of C. pomonella.

MacLellan (1999) studied a maximum of 82.5% parasitism of A. quadridentata Wesmaels. The intensity of parasitism by this egg parasitoid depends on the stage of embryonic development of the eggs: he also observed, at 25°C and 70-80% RH, that the maximum degree of parasitism was when eggs were 2-4 days old.

Mattiacci et al. (1999) reported that most of the parasitoid depends on the location behavoiur of their host and H. pallidus (Askew) is a good example for host searaching is regarded as a potential parasitoid. Female is more active and efficient for their host location and enter in to the fruit, parasitising the host inside. Some of the parasitoids are more careful during parasitising the host that is already parasitised having frass around it. Hence H. pallidus is more capable for searching it host and play more effective role for the control and management of C. pomonella in different countries.

Velcheva et al. (2012) observed that the gradual increase in the rate of insect parasitism on externally feeding lepidopterious larvae developing on buds, flowers, leaves and fruits of young apple trees in an orchard located in West Bulgaria from 2005-

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2009. During the five year survey, 19 parasitoid species belonging to 6 families were identified. Species of family ichneumonidae were dominant (42.1%), followed by braconidae (31.6%). Two tachinid flies were isolated, corresponding to 10.5% of the complex. Dibrachys cavus (Walker) was the first parasitoid observed during the investigation and was found as cocoons on the leaves. Scirtetes robustus (Woldstedt) parasitized Orthosia cerasi (Fabricius) in the second year after planting of the orchard. Hedya nubeferana (Haworth), The percentages of parasitism reached to 25% for the first two pests and 22% for O.brumata. The rate of parasitism of C. pomonella collected in the young orchard was low: 5.3% in 2008 and 0.9% in 2009. Liotryphon caudatus (Ratzeburg) and A. quadridentata (Wesmael) were the first species ascertained to infest the larvae of the pest.

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4.3. EXPERIMENT-1: MANAGEMENT OF C. POMONELLA THROUGH SELECTED NOVEL PESTICIDES

4.3.1. MATERIALS AND METHODS

The experiment was conducted in Matta, Swat during the year 2012 and 2013 and was laid down in the randomized complete block design (RCBD) with single factor having six treatments including control and were replicated four times. Blank spray was done to determine the required amount of spray solution for each tree. All the orchard were "Red Delicious" variety of the same size and age i.e. 12 years old in this experiment. Four rows with six plants in each row having 5.53 x 5.53 meters row to row and plant to plant distance were selecte for the treatments application. Five plant protection products (Novel insecticides) Match® , Madex® , Delegate® , Assail® and Timer® with Lufenuran, CpGv, Spinetoram, Acetamiprid and Abamectin as active ingredients respectively were used in their respective doses for the spray application against C. pomonella (Table-4.1). For this experiment Lethmayer et al. (2009) procedures were followed with some necessary modifications.

The first spray of aforementioned insecticides were applied when 80 percent petals fall (First week of May) and the second spray was applied 20 days after the first spray for control of first generation of C. pomonella. A total of four sprays were applied and the last two sprays were applied at the interval of 30 days each for the control of second generation of C. pomonella through power spray machines. Four rows were selected having six trees in each row for treatments application. The percent infestation rate with C. pomonella larvae were assessed fortnightly by counting the number of all infested and not infested dropped fruits per replicate and treatment by using the following formula:

Percent infestation (%) = Infested fruit with C. pomonella larvae x 100 Total dropped fruit

The effect of these insecticides were evaluated on two associated biological control agents i.e. egg-larval parasitoid Ascogastor quadridentata (Hymenoptera: Braconidae) and gregarious ectoparasitoid Hyssopus pallidus (Hymenoptera: Eulophidae).

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4.3.1.1. Ascogaster quadridentata

All the treated trees in the block were banded with corrugated cardboard bands having opening less than 1/20 inch (1.3 mm) with the folds facing down to collect parasitized C. pomonella larvae migrating down the trunk to pupate in Mid July and at the end of September during the year 2012 and 2013. Bands were wrap around the trees trunk at a distance of 2-3 feet from the ground and were replaced weekly. Corrugated bands along with overwintering larvae of C. pomonella were kept in a wooden rearing cages (45x45x45cm3) at 25±2 0C and 60-70% relative humidity (R.H) (Tomkins, 1984). The cages were checked weekly for possible emergence of pest and A. quadridentata and percent parasitism of adult parasitoids were determined by using following formula:

Percent Parasitism (%) = No, of parasitoid emerged from parasitized larvae x 100 Total No, of overwintering larvae in cardboard bands

4.3.1.2. Hyssopus pallidus

The effect of these insecticides were also evaluated on another associated biological control agent i.e. gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae). For this purpose, the dropped infested fruits with C. pomonella larvae were brought to the laboratory and were put them in the wooden rearing cages (45x45x45cm3) on 25±2 0C and 60-70% relative humidity (R.H). The cages were checked weekly for the possible emergence of this parasitoids and it's percent parasitism in the respective treatments were computed by using the following formula:

Percent Parasitism (%) = No, of parasitoid emerged from infested fruit x 100 Total infested fruit by C. pomonella larvae

4.3.1.3. Biological Efficacy

To know the biological efficacy of each treatment, after completion of infestation data and crop harvest, the percent decrease over control was calculated through following formula in control and other sprayed plots for their biological efficacy (Abbott, 1925).

Percent (%) decrease over control (Biological Efficacy) = A-B/A * 100 where, A= Pest infestation or damaged fruits in control plots B= Pest infestation or damaged fruits in treated plots

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4.3.1.4. Yield data and total gain in yield over control

Yield data (kg/tree) was taken in each replicate after harvest of fruits following the procedures of Saljoqi et al. (2003) with some necessary modifications. The total gain in yield over control due to insecticides application were calculated by the following formula (Sathi et al., 2008).

Gain in Yield (%) =

Where,

T = Yield obtained from treated plot (protected plot) C = Yield obtained from Control plot (Unprotected)

4.3.1.5. Statistical Analysis

All the replicated data were statistically analyzed by using analysis of variance technique suitable for randomized complete block design (RCBD) by using Steel and Torrie, (1980) procedures and via a statistical software “Statistics 8.1®” version. The significant means were split by LSD test at α 0.05% level of probability. All the replicated data regarding fruit drop, mean infestation and relative occurrence of the parasitoids were square root transformed (√0.5+X) prior to statistical analysis.

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Table-4.1: Treatments applications with respective doses and active ingredients for C. pomonella management during the year 2012 and 2013

Trade Name Formulation (%) Active Class Dosage Ingredients (per 200 L ha-1) Match® 50 % EC Lufenuron IGR 200 ml Madex® 3x1013 viruses/ litre C. pomonella Granulovirus 50-100 ml granulovirus Delegate® 25% WG Spinetoram Spinosyn 5-10 gm Assail® 1.8 % EC Acetamiprid Neonicotinoid 100-200 gm Timer® 1.9 % EC Abamectin Avermectin 25-30 gm Control ------

Fig.4.1: Experimental design/Layout of the Experiment in Matta Swat

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4.3.2. RESULTS

4.3.2.1. Mean Fruit Drop

The ANOVA related to the fruit drop caused by the C. pomonella after application of different types of biorational and novel insecticides, are given in appendix-7. The data regarding the fruit drop after application of insecticides for the management of C. pomonella, revealed highly significant differences among the different treatment means and were compared by Fischer's Proteted LSD test, at P = 0.05 (Table-4.2). Minimum mean fruit drop (2.80) was observed for Match and was statistically different from all the treatments. However, Madex (4.07), Delegate (3.70) and Timer (4.55) were statistically at par with each other in the mean fruit drop but differed significantly from control (7.82) and Match (2.80) treatments. During the year 2012, minimum and maximum fruit drop were recorded for Match and Control which ranged from 2.80 and 7.82 respectively.

Table-4.2: Mean fruit drop of apple after application of different insecticides during the year 2012 and 2013

------Mean Drop ------Treatments Year 2012 Year 2013 Mean Match 2.80 (1.75) 2.20 (1.50) 2.50 d (1.62) Madex 4.55 (2.22) 4.62 (2.21) 4.58 c (2.21) Delegate 3.70 (1.99) 3.90 (2.04) 3.80 c (2.01) Assail 5.37 (2.40) 5.40 (2.38) 5.38 b (2.39) Timer 4.07 (2.09) 4.15 (2.10) 4.11 c (2.09) Control 7.82 (2.86) 7.82 (2.84) 7.82 a (2.85) Mean (Years) 4.72 a 4.68 a

LSD (p<0.05) 0.75 0.94 0.60

Interaction Y * T NS Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in parenthesis are square root transformed (√0.5+X), NS: Non-Significant

The ANOVA related to the fruit drop caused by the C. pomonella after application of different insecticides, during the year 2013 are given in Appendix-12. The data regarding fruit drop after application of insecticides for the management of C. pomonella, revealed highly significant differences among the different treatments (Table-4.2; column- 3). Minimum mean fruit drop (2.21) was observed for Match and was statistically different from all the rest of the treatments. Maximum mean fruit drop was recorded for the control plot (7.82) which was significantly different from all the

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treatment means. Mean fruit drop with Madex treated plants was 4.62 which was statistically at par with that of Delegate (3.90), Assail (5.40) and Timer (4.15) but differed significantly from treatments i.e., Match and control having mean fruit drop 2.21 and 7.82 respectively. During the year 2013, minimum fruit drop was observed for match treated plants (2.20), while control had the maximum fruit drop (7.82). Combined data analysis explained that minimum mean fruit drop (2.50) was observed for Match treated plants which were significantly different from all other treatments including control. The data further revealed that mean fruit drop of both the years were not statistically different from each other and interaction between years and treatments were also non-significant.

4.3.2.2. Percent Infestation

The ANOVA pertaining to the percent infestation caused by the C. pomonella during the year 2012, after application of different insecticides, are given in appendix-8. The data regarding mean and percent infestation after application of insecticides for the management of C. pomonella, revealed highly significant differences among the different treatments and the percent means infestation compared by Fischer's LSD test at P = 0.05 (Table-4.3). Minimum mean percent infestation (24.83%) was observed for Match and was statistically different from all the treatments. However, Madex, and Timer were not statistically at par with each other having mean percent infestation 58.22 and 57.76% respectively. The said treatments differed significantly from Match, Assail and control having mean infestation 24.83, 57.76 and 76.32% respectively. During the year 2012, minimum mean percent infestation were observed for Match followed by Delegate and Timer and maximum mean percent infestation were recorded for control followed by Assail and Madex.

The ANOVA regarding means percent infestation caused by the C. pomonella during the year 2013, after application of different insecticides are given in Appendix-13. The data regarding mean and percent infestation after application of insecticides for the management of C. pomonella, revealed highly significant differences among the different treatments (Table-4.3; Column- 3). Minimum mean percent infestation was observed for Match having percent infestation 21.39% and was statistically different from all the treatments. Nonetheless, mean percent infestation of Madex (63.37%) and Timer (48.37%) and Delegate (37.67%) and were statistically at par with each other and differed significantly from Match (21.39%) and control plots (80.44%). During the year 2013,

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minimum and maximum mean percent infestation were recorded for treatment such as Match and Assail (21.39%) and (66.56%) respectively, while high mean infestation was recorded foe control plot (80.44%). Combined data analysis further confirmed that lowest mean infestation (23.11%) was observed in Match treated plants followed by Delegate (40.62%) and Timer (52.75%) which were significantly different from all other treatments including control. The data also revealed that mean percent infestation caused by C. pomonella during both the years were statistically at par with each other and interaction between years and treatments were significant. (Tab.4.3)

Table-4.3: Mean percent infestation of apple fruit caused by C. pomonella application of different insecticides during the year 2012 and 2013

Percent Infestation (%) Treatments Year 2012 Year 2013 Mean Match 24.83 21.39 23.11 e Madex 58.22 63.37 60.79 b Delegate 43.57 37.67 40.62 d Assail 69.46 66.56 68.01 b Timer 57.76 48.37 52.75 c Control 76.32 80.44 78.38 a Mean (Years) 54.93 a 52.97a

LSD (p<0.05) 11.16 11.22 7.89

Interaction Y x T * Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. * Significant

4.3.2.3. Percent parasitism of Ascogaster quadridentata

The ANOVA pertaining to the mean percent parasitism of egg-larval parasitoid Ascogastor quadridentata (Hymenoptera: Braconidae) of the C. pomonella during the year 2012, after application of different insecticides, are given in appendix-9. The data regarding mean population of the aforementioned natural enemy after application of insecticides for the management of C. pomonella, revealed highly significant differences among the different treatments (Table-4.4; Column- 2). The mean population was compared by Fischer's Protected LSD test, at P = 0.05. Maximum percent parasitism (23.88%) of A. quadridentata were recorded for Match which were statistically at par with Delegate (15.41%) and Madex (4.12%) and differed significantly from control. Percent parasitism (4.12%) of Madex was statistically at par with that of Assail (4.87%) but differed significantly from Timer (19.79%) and control (28.99%). However, Delegate

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(15.41%) was statistically at par with Timer (19.79%), but differed significantly from control plot.

The effect of insecticides such as Assail, Timer and control on the parasitism of A. quadridentata were significantly different from all the treatment during the current experiment. During the year 2012, minimum to maximum percent parasitism of A. quadridentata were recorded for treatments such as Madex and Assail followed by Timer, Delegate, Match and control. (Fig. 4.2).

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35 30 25 20 AQ 15 Hp 10

5 Mean percentMeanparasitism(%) 0 Match Madex Delegate Assail Timer Control Chemical insecticides

Fig. 4.2. Mean percent parasitism of A.quadridentata and H. pallidus after insecticides application during 2012 and 2013

Table-4.4; column- 3, shows the data pertaining to the mean population of egg- larval parasitoid Ascogastor quadridentata of the C. pomonella during the year 2013, after application of different insecticides, and ANOVA given in appendix-14. The data regarding mean population of the aforesaid parasitoid after application of insecticides for the management of C. pomonella, revealed highly significant differences among the different treatments. Statistical analysis regarding percent parasitism of A. quadridentata explained that mean parasitism in Match (0.87 and 28.99%) was statistically at par with that of Delegate (19.40%) and Madex (5.41%). Further, Madex and Asail (1.12%) were also statistical at par with each other but differed significantly from all other treatments including control. Nevertheless, Delegate and Time were statistically at par with each other having percent parasitism of A. quadridentata 19.40% and 16.66% respectively.

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During the year 2013, mean population in increasing order of A. quadridentata for treatments was Assail, Madex, Timer, Delegate, Match and Control, having mean population of A. quadridentata 1.12, 5.41, 16.66, 19.40, 28.99 and 28.99% respectively. Combined data analysis confirmed that Match insecticide is safe and afforded maximum percent parasitism (26.43%) of A. quadridentata among all other treatments except control. The data also revealed that mean percent parasitism during both the years were statistically at par with each other and interaction between years and treatments were also non-significant (Tab.4.4).

Table-4.4: Mean parasitism of Ascogester quadridentata after application of different insecticides during the year 2012 and 2013

Percent Parasitism (%) Treatments Year 2012 Year 2013 Mean Match 23.88 28.99 26.43 a Madex 4.12 5.41 4.77 c Delegate 15.41 19.40 17.41 b Assail 4.87 1.12 3.00 c Timer 19.79 16.66 18.22 b Control 32.28 28.99 30.63 a Mean (Years) 16.77 a 16.73 a

LSD (p<0.05) 9.84 9.58 6.85

Interaction Y * T NS Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. NS: Non Significant

4.3.2.4. Percent parasitism of Hyssopus pallidus

Table-4.5 shows the data pertaining to the mean population of gregarious ectoparasitoid Hyssopus pallidus (Hymenoptera: Eulophidae) of the C. pomonella during the year 2012, after application of different insecticides, and ANOVA given in appendix- 10. The data regarding mean population of the aforementioned natural enemy after application of insecticides for the management of C. pomonella, revealed that highly significant differences were found among the different treatments and mean population as compared by Fischer's LSD test, at P = 0.05 (Table-4.5). Minimum mean percent parasitism was observed for Assail having percent parasitism 0.67% and Madex (5.73%) which was statistically at par with each other and with that of Delegate (23.91% ) and

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Timer (23.95%), but differed significantly from control and plants treated with Match (34.79%). However, Madex and Match were significantly different from each other having percent parasitism of H. pallidus 5.73% and 34.79% respectively. During the year 2012, mean population in increasing order of H. pallidus for treatments was Assail, Madex, Timer, Delegate, Match and control. During the year 2013, (Appendix- 15) maximum percent parasitism of H. pallidus was recorded both in control (29.61%) and Match treated plots (29.12%) followed by Timer (22.25%), Delegate (14.16%) whilst Madex (6.39%) and Assail (3.22%) treated plants had lower number of H. pallidus parasitism. Combined data analysis explained that Match proved useful and safe for H. pallidus occurrence (27.65%) among all other treatments after control in the current experiment (Fig. 4.2). The data also disclosed that mean percent parasitism during both the years were statistically at par with each other and interaction between years and treatments were significant (Tab.4.5).

Table-4.5: Mean parasitism of Hyssopus pallidus after application of different insecticides during the year 2012 and 2013

Percent Parasitism (%) Treatments Year 2012 Year 2013 Mean Match 26.18 29.12 27.65 a Madex 5.73 6.39 6.06 c Delegate 23.91 14.16 19.03 b Assail 0.67 3.22 1.94 c Timer 23.95 22.2 23.07 ab Control 34.79 29.61 32.2 ab Mean (Years) 19.21 a 16.41 a

LSD (p<0.05) 12.61 10.55 8.20 Interaction Y x T *

Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05 * Significant

4.3.2.5. Biological Efficacy of Insecticides

Table-4.6 illustrates the data regarding the effectiveness of different insecticides sprayed for the management of apple C. pomonella during the year 2012 and 2013 in Matta Swat. The data in the table-5 column- 2 revealed that during the first year of studies, the Match afforded high percent efficiency (85.17%) for the management of C.

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pomonella followed by Delegate (70.01%), Timer (57.99%), Madex (53.04%) and Assail (37.39%) which were less effective for the management of C. pomonella.

In the proceeding year of studies i.e. 2013, (Table-4.6; Column-3) pertaining to the efficiency of different insecticides used for the management of said pest, almost similar trend of effectiveness of insecticides were observed for all the products. Match exhibited high biological efficacy (88.18%) followed by Delegate (73.22%), Timer (64.25%), Madex (51.96%), while Assail (41.73%) showed the lowest biological efficacy among all the products for the management of apple C. pomonella during the current studies. The pooled mean showed that higher efficacy was observed for Match (86.67%) followed by Delegate (71.61%), Timer (61.12%), Madex (52.50%), Assail (39.56%) and Control (61.13%).

Table-4.6: Biological efficacy of different insecticides for the control of Cydia pomonella during the year 2012 and 2013

Biological Efficacy (%) Treatments Year 2012 Year 2013 Mean Match 85.17 88.18 86.67 Madex 53.04 51.96 52.50 Delegate 70.01 73.22 71.61 Assail 37.39 41.73 39.56 Timer 57.99 64.25 61.12 Control ------

4.3.2.6. Average Yield (kg/tree)

Table-4.7 elucidates comparison of mean values for the data regarding yield (kg) per tree after application of different insecticides at the time of harvest during the year 2012 and 2013 (Appendix- 11 & 16). In Table-4.7 and column-2 shows that high mean yield (kg/tree) was recorded for apple plants treated with Match (86.50±0.62kg/plant) insecticide followed by Delegate (79.12±1.24 kg/tree), Timer (75.25±1.33 kg/tree), Assail (68.12±1.32 kg/tree), Madex (67.00±1.30 kg/tree), and Control (56.25±1.96 kg/tree). Statistical analysis disclosed that Assail and Madex were significantly at par with each other but differed significantly from all other treatments. However, Match displayed significantly more yield followed by Delegate and Timer. The mean yield per tree

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obtained from the control plants were significantly lower than all the treated plants in the current experiment.

Likewise, during the year 2013, the data regarding yield (kg/tree) after application of insecticides at the time of harvest of apple fruit, Table-4.7; Column-3 revealed that statistically high yield (87.12±0.87 kg/tree) was obtained from the plants treated with Match product, followed by Delegate (79.50±0.73 kg/tree), Timer (73.37±0.65 kg/tree), Madex (69.87±0.51 kg/tree), Assail (61.75±3.19 kg/tree) and Control (50.50±1.30 kg/tree). Statistical analysis showed that minimum yield was produced by plants treated with Assail insecticides, which were significantly different from all the yield produced by different plants treated with different insecticides. The yield produced by plants treated with Madex and Timer were significantly at par with each other and differed significantly from all the treated and control plants. The statistical analysis further revealed that the yield (86.81 kg/tree) obtained from Match sprayed plants was significantly higher than all the treated and untreated plants during both the years of studies.

Table-4.7: Comparison of the means values for the data regarding apple yield (kg/tree) at the time of harvest after application of different insecticides during the year 2012 and 2013

Mean yield (kg/tree) ± SE Gain in yield Treatments over control Year 2012 Year 2013 Mean (%) Match 86.50±0.62 87.12±0.87 86.81±0.42 a 62.66 Madex 67.00±1.30 69.87±0.51 68.43±0.73 d 28.22 Delegate 79.12±1.24 79.50±0.73 79.31±0.37 b 48.60 Assail 68.12±1.32 61.75±3.19 64.93±2.14 e 21.66 Timer 75.25±1.33 73.37±0.65 74.49±0.74 c 39.24 Control 56.25±1.96 50.50±1.30 53.37±1.30 f -- Mean (Years) 72.04 a 70.35 a

LSD (p<0.05) 3.76 4.66 2.87

Interaction Y x T * Means (±SE) sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. * Significant The combined data analysis explicated that higher yield (86.81±0.42 kg/tree) was obtained from Match treated plants which was statistically different from all other treatments including control. However, the yield (64.93± 2.14 kg/tree) obtained from plants treated with Assail was statistically at par with Madex (68.43±0.73 kg/tree) but

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differed significantly from Timer (64.93±2.14 kg/tree) and Delegate (79.31± 0.37 kg/tree). Lower yield (53.37±1.30 kg/tree) was recorded for the control plants. The gain in yield over control were in the order of Match (62.66%) > Delegate (48.60%) > Timer (39.24%) > Madex (28.22%) > Assail (21.66%). The data also divulged that mean yield during both the years were statistically at par with each other and interaction between years and treatments were significant (Tab.4.7).

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4.3.3. DISCUSSION

4.3.3.1. Mean Fruit Drop

The data pertaining to mean fruit drop after application of different types of biorational and novel insecticides revealed that minimum mean fruit drop (2.80 and 2.20) were observed for the apple plants treated with Match insecticides during the year 2012 and 2013. Highest mean fruit drop (7.82 and 7.28) were recorded in the control plants followed by Assail (5.37 and 5.40), Madex (4.55 and 4.62), Timer (4.07 and 4.15) and Delegate (3.70 and 3.90) during the year 2012 and 2013 respectively. Consequently among all other insecticides, Match insecticides show a good efficacy in reducing the mean fruit drop (2.50) in apple orchard and was more effective in minimizing the mean infestation of C. pomonella. Racette et al. (1992) reported that the damage of C. pomonella is usually characterized by oviposition scars on the fruit surface, however it also causes damage due to larval feeding and premature drop of internally damaged fruit occurrence can be curtailed by the application of inset growth regulator. Saljoqi et al. (2003) reported that insect growth regulators (IGRs) such as Match and Decis afforded 2.60% of fruit drop was due to C. pomonella infestation at two different altitudes in Swat Pakistan. Geier (1999) reported that 12-98% of premature fruit drop in the apple orchard was observed after spraying of different insecticides for the management of C. pomonella in Australia. Holb (2004) also reported similar results regarding fruit drop and control strategies through insect growth regulators.

4.3.3.2. Percent Infestation

Similarly minimum mean percent infested fruit among the dropped fruit were observed in the plants sprayed with Match insecticide having percent infestation 24.83 and 21.39% in the year 2012 and 2013 respectively. According to previous workers (Pollini, 2000; Tunaz and Uygun, 2004) who stated that insect growth regulator has high level of efficiency in reducing the infestation of C. pomonella by affecting freshly laid eggs. Highest percent infestation (76.32 and 80.44%) were noticed in the untreated plants followed by Assail (69.46 and 66.56%), Madex (58.22 and 63.37%), Timer (57.76 and 48.37%) and Delegate (43.57 and 37.68%) in 2012 and 2013 respectively. Nonetheless, Match afforded least infestation of the C. pomonella among all other insecticides used in both the years of studies. According to Miletic et al. (2011) maximum infestation of C.

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pomonella after treatment of IGRs was 27.8% and for the control plot the infestation was 56.1%, these findings are in close agreement with our results. Brunner et al. (2008) also reported that among the insecticides IGR has a great influence on reducing the infestation of C. pomonella and acting as ovicides and effect molting process in insects. But if the imagoes flying out in the succession and the presence of newly laid and almost hatched eggs at the same time make impossible the use of insect growth regulator, which proved highly efficient in the control of C. pomonella first generation. (Miletic and Tamas, 2009). According to Racette et al. (1992) C. pomonella damage ranged from 3 to 63% and averaged 33% in the untreated apple orchard and these finding are in close conformity with our results.

However according to the findings of Croft and Riedle (1991) insecticides control is the application of chemicals especially the IGRs selective methods and granulosis for the effective management of C. pomonella. Nevertheless, new product has been introduced in to the martket for widely used for the effective management of this pest in integrated management, but some of these control methods have some demerats in their usage (Blommers, 1994; Dorn et al., 1999). According to other scientists (Carde´ and Minks, 1995; Dorn, 1993) if the infestation is low then the insecticides application will be more effective. Besides, a wide range of control tactics which has been applied for the management of this pest, their control is still out of one's limit (Carde´ and Minks, 1995).

Shah (2008) reported that IGRs do not harm populations of beneficial insects and that IGRs persist on foliage much more effectively than organophosphates did. C. pomonella Larvae emerging from eggs begin to perish as soon as they start feeding on the growth regulators. He further stated that IGRs are ovicidal as well as larvicidal and not toxic to predatory/beneficial insects. The beneficial effects of the application of growth regulators can be seen one to two days after application.

4.3.3.3. Impact on Biological Control Agents

During the current studies, the impact of insecticides application on natural enemies was also weighed up. Pesticides spray has a great influence on natural enemies survival. Besides, killing of pest, majority of the natural enemies such as predator and parasitoids are also killed. The current studies also focused to know the impact of these insecticides on two naturally occurring parasitoids i.e. egg-larval parasitoid A.

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quadridentata (Hymenoptera: Braconidae) and gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae). In Eurasia, where C. pomonella is believed to have originated, A. quadridentata is one of the most common parasitoids collected from over wintering C. pomonella larvae (Brown and Reed-Larsen, 1991).

During the year 2012 and 2013, maximum mean percent parasitism was observed in the Match treated and control plants. It was due to the fact that on the untreated plants there were more infestation and more abundance of the natural enemies, unlike in treated plants, comparatively minimum number of the A. quadridentata emerged from the infested fruit, either been killed during spray application or due to deterrency effect or non-availability of the appropriate number of host. Consequently, due to spray applications, Match afforded the maximum number of A. quadridentata and H. pallidus. In case of Match insecticide gave effective result in reducing infestation and among all dropped infested fruit, the percent A. quadridentata emerged were 23.88 and 28.99% in the year 2012 and 2013 respectively. Delegate also proved effective and afforded minimum infestation and percent occurrence of A. quadridentata was 15.41 and 19.40% followed by Match (23.88 and 28.99%), Control (32.99 and 28.99%), whilst lowest number of A. quadridentata observed in the Madex treated plants (4.12 and 5.41%) during both the years of studies.

Weedle et al. (2009) reported that natural enemies of C. pomonella can reduce its population, but their efficiency often does not have any practical value and with insecticides application its population is affected. Nonetheless, A. quadridentata may contribute to the area-wide control of C. pomonella populations by reducing the number of adult moths that may potentially cause a substantial damage to the unmanaged orchards. (Brown and Reed-Larsen, 1991).

Likewise, maximum number of H. pallidus were observed from the infested fruits in the untreated (Control) plants (34.79 and 29.61%) in both the year of studies. This was followed by Match (26.18%), Delegate also afforded maximum number of H. pallidus (23.91%) almost same to Timer (23.95%). Lowest population of H. pallidus was recorded for Assail (0.67%) in the year 2012. Whilst in the year 2013, almost similar trend of the percent occurrence of H. pallidus was noticed in all the treatments including control plants. Mattiacci et al., (1999) reported 27% parasitism of H. pallidus in apple orchard. Boucek and Askew (1968) also reported that Hyssopus pallidus is very effective for the

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control and management of C. pomonella and can occasionally parasitised Cydia molesta and as result can curtailed the pest population in any agro ecosystem. Once this natural enemy is released in to the field then it is self perpetuating and there is no ned for their further release for the effective control of lepidpterious pest in the field.

According to Brown (1996) in other Eulophidae, H. pallidus has a high lifetime fecundity, a rapid rate of pre adult development, and a strongly female-biased sex ratio and very efficient for C. pomonella control. These results are also corroborated by previous workers (Dorn, 1996; Pijls, 1996) who reported that parasitoids contribute to sustainable agriculture through their ability to regulate populations of C. pomonella. Harder (2008) reported that insect growth regulators (IGR) do not adversely affect biological control agents to any high degree. Rather, IGRs are relatively specie-specific and cause target larvae to mature earlier than normal before the larvae are physiologically ready and so die before the time. Now the awareness has ben created among the farming community about the importance of natural enemies and parasitoids can be predicted through ecological research, by testing and evaluating percent parasitism which determine the efficacy and reliability of a species as a biological control agent.

4.3.3.4. Biological Efficacy of Insecticides (%)

High level of efficiency (85.17 and 88.18%) with mean 86.67% were shown by Match insecticides in reducing the infestation of C. pomonella in both the years of studies. As Match is insect growth regulator (IGR) mostly acting as ovicides and larvicides, so proved very effective in reducing the infestation of C. pomonella. Miletic et al. (2011) reported that insect growth regulator such as Novaluran and Pyriproxifen showed high efficiency level 97.6% and 95.1% respectively in the control of C. pomonella. Delegate was also efficient next to Match and its level of biological efficacy was 70.01 and 73.22% in reducing the infestation of C. pomonella in the year 2012 and 2013 respectively. These results are in close concordance with finding of Lethmayar et al. (2009) who reported that the efficacy of the four mainly used insecticides (IGR) was 64% while in control plot it was 75%. The level of efficacy for Timer was 57.99 and 64.25% and for Madex 53.04 and 51.96% in the year 2012 and 2013 respectively. As Madax product was used for the first time in Swat and comprised live granular viruses bodies, so some technical problem might have occurred in its handling and more application of

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Madex required instead of four sprays. So it was not found as efficient as used in other countries giving tremendous results in controlling the C. pomonella.

The level of efficiency of Assail was inferior (37.39 and 41.73%) among all other insecticides used for the management of C. pomonella. During the entire period of investigation, Assail had a poorest efficiency against C. pomonella ranging from 37.39 to 41.73% in both the years of studies. Considering the history of its application and very high efficiency during first year of its use (Hagley and Chiba, 1980), it could be presumed that there is a strong indication of reduced susceptibility of C. pomonella population at this locality i.e. resistance development. The resistance of C. pomonella to different insecticides including organophosphates was also confirmed at numerous production localities worldwide. (Satara et al., 2006). The changes in topographic conditions and geographical location of C. pomonella should also be considered due to weather parameters changes as stated by Rafoss and Saethre (2003). These results showed that more effective management strategies still have to be developed to effectively control the C. pomonella, especially in integrated production.

4.3.3.5. Average yield (kg/tree)

During the current experiments, yield data of all treated and control plants were recorded at the time of harvest of fruit in both the years of studies. Maximum yields (86.50±0.62 and 87.12±0.82 kg/tree) were produced by plants treated with Match insecticides. Delegate was next to Match and afforded sufficient quantity of fruit (79.12±1.24 and 79.50±0.78 kg/tree), followed by Timer (75.25±1.33 and 73.37±0.65 kg/tree), Madex (67.00±1.30 and 69.87±0.50 kg/tree), Assail (68.12±1.32 and 61.75±3.19 kg/tree) and lowest yield was attributed to control (56.25±1.96 and 50.50±1.30 kg/tree) plants. Combined mean explicated that Match insecticides afforded maximum average yield (86.81±0.42 kg/tree) followed by Delegate (79.31±0.37 kg/tree) and Timer (74.49±0.74 kg/tree) whilst all other treatments were inferior in yield including control (53.37±1.30 kg/tree). These results are closely supported by the findings of Racette et al. (1992) who reported that mean yield per tree ranged from 44 kg/plant of fruit in 1991- 1994 in the untreated apple orchard in Southwestern Michigan which is comparatively less than our results. These results are also in concordance with findings of Saljoqi et al. (2003) who reported that after application of insect growth regulator on apple orchard, the average yield per tree obtained was 59.71 kg/tree at the time of harvest.

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Clark and Gage (1997) also found a highly significant negative association between percent damage caused by C. pomonella and yield of apple crop. But the actual yield loss due to fruit drop were properly determined because its occurence was coincides with some other factors such as "June Drop" and the relation between pest infestation and yield loss was variable from one year to the other year. But loss in the yield was slo due to the infestation of this pest in the prevailed studying years as high number of C. pomonella were observed during the trails. (Racette et al., 1992). Nevertheless, Holb (2004) reported that the incidence of C. pomonella play an important role in the yield loss and also provide favorable conditions for secondary pests inoculums. Furthermore, the gain in yield over control due to insecticides application were in the order of Match (62.66%) followed by Delegate (48.60%), Timer (39.24%), Madex (28.22%) and Assail (21.66%). Hence, Match proved effective in more gain (62.66%) ) in yield over control in both the years of studies.

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4.3.4. CONCLUSIONS

These studies revealed that only four sprays of each chemicals (Match, Madex, Timer, Delegate and Assail) were applied per season for C. pomonella management. Match insecticide proved very effective for the control of C. pomonella during current studies. The said chemical proved safer for its two associated parasitoids A. quadridentata and H. pallidus compared to other chemicals. Maximum average yield (kg/tree) was attributed to Match chemical which was significantly higher than all the treatments. Hence, insect growth regulator (IGR) has a profound effect in curtailing the C. pomonella infestation, comparatively more safer for the associated parasitoids and enhancing the yield/tree and can be effectively used for the management of C. pomonella and other lepidopterious pests alone or in combination with other control tactics.

4.3.5. RECOMMENDATIONS

The above findings lead to the following recommendations.

1. Among the tested foliar insecticides, Match is more effective than all other insecticides tested during the experiment. 2. Foliar insecticides has negative impact on natural enemies of C. pomonella, however, natural enemies alone fails to suppress the C. pomonella population below threshold level, as the yield obtained from control was significantly lower than the insecticide treated plants. 3. Reduced dose of foliar insecticides against C. pomonella should be tested than the standard dose as mentioned on the labele to have lesser adverse impact on the natural enemies. 4. Insect growth regulator (Match) had a profound effect in curtailing the C. pomonella infestation, more safer for its associated parasitoids and enhancing the yield and can be effectively used for the management of C. pomonella. 5. Nevertheless, its safety should be tested for other biological control agents in apple orchard or in other agro ecosystems.

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4.4. EXPERIMENT-2: MANAGEMENT OF C. POMONELLA THROUGH INTERCROPPING 4.4.1. MATERIALS AND METHODS

This experiment was carried out at Matta Swat in a randomized complete block design (RCBD) with single factor having five treatments including control and was replicated four times during the year 2012 and 2013. Mustard campestris (Brassacicacae), Soybean Glycine max (leguminacae), Trifolium Trifolium alexandrinum (Fabaceae) and wheat + Triticum aestivum (Poaceae) were intercropped with apple. Five apple orchards of a "Red Delicious" variety having same size and age were selected in same nearer locality. Each orchard were consisted of 25-30 plants having plant to plant and row to row distance 5.53 x 5.53 meters. Three rows of apple trees were kept as buffer zone between each replicate and treatment. The intercrops were sown between the rows on their appropriate time of sowing. Observations were recorded on number of percent infested dropped fruits on fortnightly basis by using the following formula:

Percent infestation (%) = Infested fruit with C. pomonella larvae x 100 Total dropped fruit

The effect of these intercrops were evaluated on two associated biological control agents i.e. egg-larval parasitoid Ascogastor quadridentata (Hymenoptera: Braconidae) and gregarious ectoparasitoid Hyssopus pallidus (Hymenoptera: Eulophidae).

4.4.1.1. Ascogaster quadridentata

All the apple trees in the respective intercrops were banded with corrugated cardboard bands having opening less than 1/20 inch (1.3 mm) with the folds facing down to collect parasitized C. pomonella larvae migrating down the trunk to pupate in Mid July and at the end of September during the year 2012 and 2013. Bands were wrapped around the trees trunk at a distance of 2-3 feet from the ground and were replaced weekly. Corrugated bands along with overwintering larvae of C. pomonella were kept in a wooden rearing cages (45x45x45cm3) at 25±2 0C and 60-70% relative humidity (R.H) (Tomkins, 1984). The cages were checked weekly for possible emergence of A. quadridentata and percent parasitism of adult pest and parasitoids were determined by using following formula:

Percent Parasitism (%) = No, of parasitoid emerged from parasitized larvae x 100 Total No, of overwintering larvae in corrugated bands

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4.4.1.2. Hyssopus pallidus

The effect of these different intercrops were also evaluated on another associated biological control agent i.e. gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae). For this purpose the dropped infested fruits with C. pomonella larvae were brought to the laboratory and were put in the wooden rearing cages (45x45x45cm3) on 25±2 0C and 60-70% relative humidity (R.H). The cages were checked weekly for the possible emergence of this parasitoids and its percent parasitism in the respective treatments were computed by using the following formula:

Percent Parasitism (%) = No, of parasitoid emerged from infested fruit x 100 Total infested fruit by C. pomonella larvae

Furthermore, pheromone traps were also fixed in each replicate to know male adults moth activities and catches with percent drop and infestation for the effectiveness of these intercrops on fortnightly basis following the procedures of Sigsgaard (2011) with some necessary modifications.

4.4.1.3. Yield data and percent gain and loss in yield

Yield data (kg/tree) was taken in each replicate and treatments after harvest of fruits following the procedures of Saljoqi et al. (2003) with some necessary modifications. Combined mean yield of plots treated with various treatment during the year 2012 and 2013 were calculated. Finally the percent gain due to intercrops and avoidable loss in yield of apple fruit caused by C. pomonella in each plot were determined following the procedures of Sathi (2008) with some necessary modifications;

Loss in Yield (%) =

Gain in Yield (%) =

Where, T = Yield obtained from treated plot (Protected) C = Yield obtained from Control plot (Unprotected)

Standard agronomic orchard practices were used in the apple orchard, i.e., normal weeding, irrigation practices, fertilization and sanitation etc. The apple orchard was not treated with insecticides for the management of C. pomonella and was relied only on different intercrops for habitat manipulation and conservational biological control.

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4.4.1.4. Statistical Analysis

All the replicated data were statistically analyzed by using analysis of variance technique fitting for randomized complete block design (RCBD) (Steel and Torrie, 1980) by using a computerised statistical package “Statistics 8.1®” version. All the significant means were separated by LSD test at α 0.05% level of probability. All the replicated data regarding fruit drop, mean infestation, adult moth catches and percent parasitism of the parasitoids were square root transformed (√0.5+X) prior to statistical analysis.

Table-4.8: Treatment combinations for intercropping in the apple orchard during the year 2012 and 2013

S.No Treatments Cropping System Time of Sowing 1. T1 Apple + Mustard (Brassica campestris) 10th February 2. T2 Apple + Soybean (Glycine max) 4th May 3. T3 Apple + Trifolium (Trifolium alexandrinum) 10th December 4. T4 Apple + Wheat (Triticum aestivum) 25th November 5. T5 Apple (Sole) - Control ----

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4.4.2. RESULTS

4.4.2.1. Mean Fruit Drop

The ANOVA related with fruit drop caused by the C. pomonella in the apple orchard having different intercrops, at various dates of observations are given in appendix- 22. The data regarding fruit drop in apple orchard having different intercrops for the management of C. pomonella, revealed highly significant differences among the different treatment means were separated by Fischer's LSD test, at P = 0.05 (Table-4.9). It is evident from the results depicted in the Table- 4.9 that lower mean fruit drop (2.57) was observed in the Apple + Trifolium which was statistically at par with mean fruit drop in Apple + Mustard (3.85) but differed significantly from the treatments Apple + Wheat (5.55), Apple + Soybean (5.10) and Apple sole (7.77). Likewise, mean fruit drop in Apple + Soybean was also statistically at par with fruit drop in Apple + wheat. In the same way, fruit drop in Apple + Mustard was also statistically at par with that of Apple + Soybean. During the year 2012, highest mean fruit drop was recorded for the apple sole while Apple + Trifolium contributed significantly in the reducing the mean fruit drop due to infestation of C. pomonella.

The ANOVA pertaining to the fruit drop caused by the C. pomonella in the apple orchard having different intercrops, at various dates of observations are given in appendix-28. The data regarding fruit drop in apple orchard having different intercrops for the management of C. pomonella, revealed highly significant differences among the different treatments (Table-4.9). It is obvious from the results (Table-4.9) that a lower mean fruit drop was noted for the treatment Apple + Trifolium (3.17) which was significantly at par from the mean fruit drop in Apple + Mustard (4.45) but was statistically different from the rest of the treatments except mean fruit in Apple + Mustard intercrop. High fruit drop (9.12) was recorded for the control (Apple sole) followed by 6.82, 5.70, 4,45 and 3.17 in the Apple + Wheat, Apple + Soybean, Apple + Mustard and Apple + Trifolium respectively. However, mean fruit drop in Apple + Trifolium was statistically at par with that of Apple + Mustard. Apple + Soybean and Apple + Wheat, Apple + Mustard and Apple + Soybean were statistically at par with each other but differed significantly from the rest of the treatments. It is obvious from the results that in both the years of studies, Apple + Trifolium contributed efficiently in curtailing mean fruit drop in apple orchard. Combined data analysis elucidated that lowest mean fruit drop

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(2.87) was attributed to the Apple + Trifolium cropping system which was statistically different from all the treatments including Apple sole. The data in Table.4.9 further revealed that mean fruit drop during both the years were statistically different from each other and interaction between years and treatments were non-significant.

Table-4.9: Mean dropped of apple fruit in apple orchard having different intercropping during the year 2012 and 2013

Mean Dropped Cropping system Year 2012 Year 2013 Mean Apple + Mustard 3.85 (1.96) 4.45 (2.13) 4.15 c (2.04) Apple + Soybean 5.10 (2.24) 5.70 (2.41) 5.40 b (2.32) Apple + Trifolium 2.57 (1.62) 3.17 (1.83) 2.87 d (1.71) Apple + Wheat 5.55 (2.38) 6.82 (2.64) 6.18 b (2.51) Apple sole (Control) 7.77 (2.81) 9.12 (3.03) 8.44 a (2.92) Mean (Years) 4.97 b 5.85 a LSD (p<0.05) 1.34 1.30 0.93 Interaction Y* T NS Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X), NS: Non Significant

4.4.2.2. Mean Percent Infestation

The ANOVA associated with mean and percent infestation of the fruit caused by the codling moth during the year 2012, in the apple orchard having different intercrops, are depicted in appendix-23. The data regarding mean percent infestation in the apple orchard having intercrops for the management of C. pomonella, revealed highly significant differences among the different treatments and percent means infestation compared by Fischer's LSD test, at P = 0.05 (Table-4.10). It is obvious from the results that lower mean percent infestation (60.09%) was observed for the treatment having Apple + Trifolium which was statistically at par with the treatments Apple + Mustard (64.85%) but differed significantly from the treatment having Apple + Wheat (76.73%) and Apple sole (Control) (88.91%). However, mean infestation in Apple + Trifolium and Apple + Mustard, Apple + Soybean and Apple + Mustard were significantly at par with each other but differed significantly from the rest of the treatments. It is evident from the results that Trifolium intercropped in apple orchard has great influence in the reduction of C. pomonella infestation.

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In the proceeding year of studies 2013 (Appendix-29) (Table-4.10; Column-3) the data regarding mean percent infestation of apple fruit caused by the C. pomonella in the apple orchard having different intercrops revealed that lower mean infestation was recorded for the treatment having Apple + Trifolium having mean percent infestation 60.90% which was statistically at par with Apple + Mustard (64.85%) but differed significantly from plot having Apple + Soybean (66.37%), Apple + Wheat (76.73%) apple alone without intercrops (88.91%). However, Apple + Trifolium and Apple + Mustard, Apple + Soybean and Apple + Mustard were significantly at par with each other in curtailing the mean infestation of C. pomonella. It is pertinent to mention that in both the years of studies the Apple + Trifolium played a vital role in cutting back the apple fruit infestation caused by C. pomonella as compared to the rest of intercrops particularly the apple sole. Further, pooled mean explicated that minimum infestation (57.19%) was recorded for Apple + Trifolium which was statistically different from all the treatments including control. The data in Table.4.10 further revealed that mean percent infestation during both the years were statistically at par with each other and interaction between years and treatments were non-significant.

Table-4.10: Mean percent infestation of apple fruit caused by C. pomonella in apple orchard having different intercrops during the year 2012 and 2013

Percent Infestation (%) Cropping system Year 2012 Year 2013 Mean Apple + Mustard 64.85 65.53 65.19 bc Apple + Soybean 66.37 68.26 67.31 b Apple + Trifolium 60.90 53.48 57.19 c Apple + Wheat 76.73 77.87 77.31 a Apple sole (Control) 88.91 82.83 85.87 a Mean (Years) 71.55 a 69.59 a LSD (p<0.05) 12.88 11.71 8.67 Interaction Y * T NS Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. NS: Non Significant

4.4.2.3. Mean C. pomonella Catches

The ANOVA pertaining to the adult moth catches through traps in the apple orchard having different intercrops, are given in appendix-24. The data regarding adult moth catches through traps in apple orchard having different intercrops for the

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management of C. pomonella, revealed significant differences among the different treatment means, compared by Fischer's LSD test, at P = 0.05 for significance (Table- 4.11). The data depicted in the result table revealed that the lower mean moth population (1.32) was trapped in the treatment having Apple + Trifolium which was statistically at par with Apple + Mustard (2.42) but differed significantly from Apple + Wheat (4.40) and Apple sole (Control) (6.60). However, mean moth catches in Apple + Mustard and Apple + Soybean were statistically at par with each other. It is evident from the experiment that more moth activities were observed in the apple orchard having no intercrop, whereas Trifolium and Mustard intercrops in the apple orchard had a significant influence on the mean moth population restrained by increasing biodiversity for the natural enemies.

The ANOVA regarding adult moth catches through pheromones traps in the apple orchard having different intercrops, during the year 2013 is given in Appendix-30. The data regarding adult moth catches through traps in apple orchard having different intercrops for the management of C. pomonella, revealed significant differences among the different treatments (Table-4.11; column-3). The data concerning the adult moth catches through pheromone traps in the apple orchard illustrated that lower moth catches (1.60) were noticed for the treatment having Apple + Trifolium which was statistically at par with Apple + Mustard (2.60) but differed significantly from the treatment having Apple + Wheat (4.62) and apple sole (7.47). Apple + Wheat (4.62) was statistically at par with Apple sole and all the rest of the treatments. However, mean moth catches in Apple + Soybean (3.62) and Apple Mustard (2.60) were statistically at par with each other and differed significantly from all the treatments including control. It is evident from combined means data analysis that comparatively lower numbers of adult moth (1.46) were captured in the orchard through traps having Trifolium as intercrops with apple while apple sole attracted maximum number of the adults moth (7.03) for infestation, whilst all other treatments had comparatively higher number of adults moth catches.

The data in Table.4.11 further revealed that mean C. pomonella catches during both the years were statistically at par with each other and interaction between years and treatments were non-significant.

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Table-4.11: Mean C. pomonella catches in apple orchard having different intercrops during the year 2012 and 2013

Mean C. pomonella Catches Cropping system Year 2012 Year 2013 Mean Apple + Mustard 2.42 (1.55) 2.60 (1.53) 2.51 c (1.54) Apple + Soybean 2.42 (1.73) 3.62 (1.76) 3.02 bc (1.74) Apple + Trifolium 1.32 (1.21) 1.60 (1.27) 1.46 d (1.24) Apple + Wheat 4.40 (2.03) 4.62 (1.98) 4.51 b (2.00) Apple sole (Control) 6.60 (2.48) 7.47 (2.57) 7.03 a (2.52) Mean (Years) 3.60 a 3.98 a LSD (p<0.05) 1.38 1.70 1.09 Interaction Y * T NS Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X), NS: Non Significant

4.4.2.4. Percent parasitism of Ascogaster quadridentata

The ANOVA pertaining to the mean percent population of egg-larval parasitoid A. quadridentata (Hymenoptera: Braconidae) of the codling moth during the year 2012, having different intercrops in apple orchard are depicted in appendix-25. The data regarding mean percent population of the A. quadridentata for the management of C. pomonella, revealed significant differences among the different treatment means and percent population , compared by Fischer's LSD test, at P = 0.05 for significance (Table- 4.12). The results revealed that more A. quadridentata (42.57%) was attracted to the plot having Apple + Trifolium followed by Apple + Mustard (23.5%) which differed significantly from Apple sole (1.35%), Apple + Wheat (2.64%) and Apple + Soybean (5.22%). Nonetheless, mean percent parasitism in the Apple + Soybean, Apple +Wheat and Apple sole were statistically at par with each other. It is evident from the results that comparatively a substantial number of A. quadridentata was recorded in the plot having Trifolium as intercrop with apple while an inferior number of the said biological control agent was recovered from the infested larvae in the rest of intercrops including control (Apple sole).

During the year 2013, similar trend of A. quadridentata parasitism was observed in the apple orchard having the same intercrops. The results in the Table-4.12 (Column- 3) described that Apple + Trifolium exhibited higher number of A. quadridentata having percent parasitism 37.65% followed by Apple + Mustard (20.12%) which were

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statistically different from Apple + Soybean (6.64%), Apple + Wheat (5.45%) and Apple sole (Control) (2.55%). Nevertheless, mean parasitism of A. quadridentata in Apple + Soybean, Apple + Wheat and Apple sole were statistically at par with each other.

It is apparent from the results of both the years of studies that the percent parasitism of A. quadridentata (40.11%) was comparatively higher in the orchard having Trifolium as intercrops compared to the orchards having other intercrops or apple sole and was significantly different from all other treatments. The data further explained that percent parasitism of A. quadridentata was statistically at par with each other during both the years of studies and interaction between the years and treatments was also non significant.

Table-4.12: Mean percent parasitism of A. quadridentata in apple orchard having different intercrops during the year 2012 and 2013

Percent Parasitism (%) Cropping system Year 2012 Year 2013 Mean Apple + Mustard 23.95 20.12 22.04 c Apple + Soybean 5.22 6.64 5.93 c Apple + Trifolium 42.57 37.65 40.11 a Apple + Wheat 2.64 5.45 4.05 c Apple sole (Control) 1.35 2.55 1.95 c Mean (Years) 15.15 a 14.48 a LSD (p<0.05) 9.92 8.36 6.80 Interaction Y x T NS Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05 NS: Non Significant

4.4.2.5. Percent parasitism of Hyssopus pallidus

Table- 4.13 illustrates the data pertaining to the mean percent parasitism of gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae) of the codling moth in the apple orchard having different intercrops during the year 2012 (Appendix-26). The data regarding mean percent occurrence of the H. pallidus for the management of C. pomonella, revealed significant differences among the different treatments and The mean percent population, compared by Fischer's LSD test, at P = 0.05 for significance (Table- 4.13). The results disclosed that maximum number of H. pallidus (28.77%) emerged from the infested fruits in the orchard having Apple + Trifolium which was statistically

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different from Apple + Soybean (5.77%) and Apple + Mustard (11.20%), Apple + Wheat intercrops (5.60%) and the orchard having no intercrops, i.e., Apple sole (0.41%). However, the mean and percent parasitism of H. pallidus in Apple + Mustard, Apple + Soybean, Apple + Wheat and Apple sole were statistically at par with each other.

The results in Table-4.13 (Column- 3) showing the mean and percent parasitism of the H. pallidus during the year 2013 (Appendix-32) in apple orchard having different intercrops. Maximum parasitism (31.51%) of the H. pallidus was explained by Apple + Trifolium intercrops which was significantly different from all other intercrops. The mean and percent occurrence of H. pallidus in Apple + Wheat (5.59%) was significantly at par with Apple + Soybean (6.84%) and Apple sole (1.39%).

It is obvious from the results of combined data analysis that Apple + Trifolium having maximum parasitism (30.09%) of the H. pallidus followed by Apple + Mustard (11.19%) and a minimum number was recorded for the apple sole (Control) (0.90%) having no intercrops. So Apple + Trifolium has a great influence on the percent abundance of H. pallidus in the apple orchard. All other intercrops afforded minimum number of H. pallidus than Apple + Trifolium.

The data further disclosed that percent parasitism of H. Pallidus was statistically at par with each other during both the years of studies and interaction between the years and treatments was also non significant.

Table-4.13: Mean percent parasitism of H. pallidus in apple orchard having different intercrops during the year 2012 and 2013

Percent Parasitism (%) Cropping system Year 2012 Year 2013 Mean Apple + Mustard 11.20 11.18 11.19 b Apple + Soybean 5.77 6.84 6.31 bc Apple + Trifolium 28.67 31.51 30.09 a Apple + Wheat 5.60 5.59 5.59 bc Apple sole (Control) 0.41 1.39 0.90 c

Means (Years) 10.34 a 12.11 a LSD (p<0.05) 8.61 8.59 6.07 Interaction Y * T NS Means sharing similar letter(s) in a column are not significantly different by Fischer's LSD test at α = 0.05, NS: Non-Significant

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4.4.2.6. Average Yield (kg/tree)

Table-4.14 disclosed comparison of mean values for the data regarding yield (kg/tree) in apple orchard having different intercrops at the time of harvest during the year 2012 and 2013. The data regarding mean yield (kg/tree) (Appendix- 27 & 32) revealed significant differences among the different treatments (Table-4.14; Column-2). High yield (77.00±1.30 kg/tree) was exhibited by the Apple + Trifolium which was statistically different from Apple + Mustard (70.87± kg/tree) followed by Apple + Soybean (67.12±1.23 kg/tree), Apple + wheat (64.00±0.84 kg/tree) and the minimum yield was recorded for Apple sole (Control) (53.75±0.72 kg/tree). However, average yield in Apple + Soybean and Apple + wheat were statistically at par with each other and differed significantly from all other treatments.

Table-4.14: Comparison of the mean values for the data regarding yield (kg/tree) at the time of harvest in apple orchard having different intercrops during the year 2012 and 2013

Mean Yield (kg/tree) ±SE Avoidable Gain Cropping System Year 2012 Year 2013 Mean losses (%) (%) Apple + Mustard 70.87±1.02 69.50±1.59 70.18±1.30 b 24.13 31.80 Apple + Soybean 67.12±1.23 66.75±0.47 66.93±0.84 c 20.45 25.70 Apple + Trifolium 77.00±1.30 76.25±0.96 76.62±1.11 a 30.51 43.90 Apple + Wheat 64.00±0.84 61.47±1.11 62.73±0.92 d 15.12 17.81 Apple sole 53.75±0.72 52.75±1.23 53.25±0.64 e -- -- Mean (Years) 66.55 a 65.34 a LSD (p<0.05) 5.03 5.21 2.34 -- -- Interaction Y * T NS

Means (±SE) sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. N:S Non Significant

Likewise, in the year 2013, maximum yield was obtained from the plot having Apple + Trifolium (76.25±0.96 kg/tree) which was statistically different from the yield in Apple + Mustard (69.50±1.59 kg/tree), Apple + soybean (66.75±0.47 kg/tree), Apple + wheat (61.47±1.11 kg/tree) and Apple sole (Control) 52.75±1.23 kg/tree). The yield in Apple + Mustard and Apple + Soybean was statistically at par with each other but differed significantly from Apple + Wheat, Apple + Trifolium and Apple sole. The results also revealed that maximum losses were avoided by the intercrops Apple + Trofolium (76.62%) followed by the intercrop Apple + Mustard (70.18%), Apple + Soybean

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(66.93%) and Apple + Wheat (62.73%). Highest gain in the yield (43.90%) due to intercrops were noticed for the intercrop Apple + Trifolium followed by Apple + Mustard (31.80%), Apple + Soybean (25.70%) and Apple + Wheat (17.81%). It is evident from the results of both the years of studies that high yield (76.62±1.11 kg/tree) was obtained from Apple + Trifolium which was significantly different from all other treatments.

The data further explained that mean yield was statistically at par with each other during both the years of studies and interaction between the years and treatments was also non significant.

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4.4.3. DISCUSSION

4.4.3.1. Mean Fruit Drop

The results pertaining to the mean drop of apple fruit disclosed that maximum mean fruit drop was recorded for apple sole (8.44), whilst the lowest mean fruit drop (2.87) was observed for the intercrop Apple + Trifolium. Apple + Mustard also proved effective in reducing the mean fruit drop of apple (4.15) and ranking second after Apple + Trifolium in the current experiment. Nonetheless, intercrops such as Apple + Wheat and Apple + Soybean demonstrated as inferior (6.18 and 5.40 respectively) among all other intercrops in curtailing the mean fruit drop of apple fruit during the year 2012 and 2013. These results are in close concordance with the findings of Abdel- Aziz et al. (2008) who reported that the fruit drop was decreased with the cover crop such as clovers treatments in the orchard as compared to fallow orchard. These results are also corroborated with the findings of Lovat (1990) who reported the reasons of flower and immature fruit drop, including lack of pollination or fertilization, drought and frost, lack of sufficient resources, defoliation, and seed and fruit loss due to insects infestation.

4.4.3.2. Mean Percent Infestation

The data related to mean percent infestation due to C. pomonella revealed that maximum percent infestation of C. pomonella was observed in the Apple Sole (88.91 and 82.83%), whilst minimum percent infestation was noticed for the intercrop Apple + Trifolium (60.90 and 53.48%) and consequently exhibited very effective in curtailing the mean percent infestation of C. pomonella during the current experiments. Nevertheless, the intercrops such as Apple + Wheat (76.73 and 77.87%) and Apple + Soybean (66.37 and 68.26%) proved comparatively less effective in reducing the mean percent infestation of C. pomonella during the year 2012 and 2013. According to Thies and Tscharntke (1999) who reported that in structurally complex landscapes, parasitism of the C. pomonella larvae were higher and infestation due to pest was lower than in apple sole having simple landscapes. Carlsen and Fomsgaard (2008) also reported that intercropping with white clover in apple and peach orchards increased arthropod community diversity and the numbers of natural enemies, reducing herbivore pest infestation incidence. However, according to Shaw (2008), In California, IGRs should be used in May, but the timing needs to be verified by phenological monitoring using pheromone traps for adult

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males, so that the flare up and infestation of C. pomonella may be minimized. According to Harcourt (1986) the monitoring of the pest can helpto find out the density of the pest and percent parasitism of the natural enemies in agro ecosystem. But weather paly a vital role in monitoring of the pest activity through pheromone traps and pest damage can be redicated on the basis of this monitoring. In the hot weather conditions, majority of the pests can developed faster and hence monitoring can be frequently done during warm weather conditions. Hence, the results further clarified that minimum mean infestation were afforded by intercrops Apple + Trifolium among all other intercrops including apple sole in these studies.

4.4.3.3. Mean Catches of C. pomonella Adults

The results related to mean catches of C. pomonella disclosed that mean maximum number of C. pomonella catches (6.60 and 7.47) were witnessed in Apple Sole whilst the most effective intercrop was Apple + Trifolium where minimum number of C. pomonella adults (1.32 and 1.60) were caught in the traps during both the years of studies. Nonetheless, the intercrop such as Apple + Mustard was also efficient in curtailing the adult moth catches in the trap (2.42 and 2.60). The intercrop such as Apple + Wheat and Apple + Soybean were least effective in the management of C. pomonella and reducing the moth catches (4.40 and 4.62; 2.42 and 3.62 respectively) during both the years of studies. According to Altieri (1995) intercropping of Trifoium in apple orchard has a substantial effect on the incidence of C. pomonella and providing nectar and pollen to beneficial insects with short probosci including parasitoid wasps and hoverflies. Holmgren (2002) reported that intercropping legumes with apple has the potential to attract natural enemies such as predators and parasitoid and consequently reducing the target pest incidence in the apple orchard. It is further evident from the results that low number of adults moth (1.46) were captured in the traps having Apple + Trifolium as intercrop due to abundant number of its parasitoids available in the field for curtailing its population.

4.4.3.4. Impact on the Biological Control Agents

The results pertaining to the percent parasitism of A. quadridentata disclosed that maximum parasitism (42.57 and 37.65%) of A. quadridentata were noticed in the intercrops such as Apple + Trifolium, whilst lower number (1.35 and 2.55%) of A.

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quadridentata were noticed in Apple Sole. Apple + Mustard also showed good performance in attracting good number of A. quadridentata (23.95 and 20.12%) during the current experiment. However, other intercrops such as Apple + Wheat and Apple + Soybean were inferior in attracting maximum number of A. quadridentata (2.64 and 5.45% ; 5.22 and 6.64% respectively) for the effective management of C. pomonella during the year 2012 and 2013. These results are in close concordance with the findings of Velcheva et al., (2012) who reported that percent occurrence of A. quadridentata from the family Braconidae was 31.6% in Bulgaria having Trifolium as intercrop in the young apple orchard. Haynes (1980) also reported that several legumes crops lana vetch, Trifolium and Medicago spp and grasses such as brome, and have been recommended to be sown annually in the orchard in the fall or early spring for attracting natural enemies such as predators and parasitoid to feed on pollen and nectar and provide them shelter for the effective management of C. pomonella. Sigsgaard (2014) reported that there was increased predation activity and increased mortality of C. pomonella larvae from near flower strips that could be predator or parasitoids induced. According to previous workers (Jervis et al., 1993; Landis et al., 2000) considerations have combined to produce an expectation that biological control can be improved by the incorporation of flowering cover crops as intercrops or other sources of sugar to parasitoids in the apple field for the effective management of C. pomonella. Wan et al. (2014) also reported that when peach orchards were covered with Trifolium repens the abundances of aphids and G. molesta decreased, respectively, by 31.4% and 33.3% and by 30.1% and 33.3% at two different orchard. Moreover, the abundance of generalist predators increased by 116.7% and by 115.8%. It is obvious from these results that Apple + Trifolium encouraged maximum number of A. quadridentata (1.16) higher among all other intercrops including Apple sole.

The data revealed that mean maximum (28.67 and 31.51%) parasitism of H. pallidus occurred in the intercrop Apple + Trifolium and proved very effective in parasitizing C. pomonella population during both the years of studies, whilst the lower number (0.41 and 1.39%) of H. pallidus was observed in the Apple sole. Nevertheless, the cropping system such as Apple + Wheat and Apple + Soybean demonstrated inferior and attracted least mean percent number of H. pallidus (5.60 and 5.59% ; 5.77 and 6.84% respectively) during both the years of studies. Leius (1967) found that the presence of wild flower in the apple orchard resulted in five times increase in the parasitism of C.

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pomonella larvae by different larval parasitoids. Rieux et al. (1999) reported that different plants cover sown in the alleys provides a higher richness and diversity of the natural enemies such as predators and parasitoids for the effective management of pests of apple and pear compared with a bare ground. As for as natural enemies percent occurrence are concerned, our results are also supported by natural enemies hypothesis which states that predators and parasitoids are more diverse and abundant, and more effective at controlling herbivore populations in the intercropped habitats compared with monoculture habitats, because of the increased availability of alternate prey, nectar sources, and suitable microhabitats (Root, 1973, Russell, 1989). Similar results were also observed in other systems, for instance, the aphid abundance decreased and the abundance of the major predator of aphids, Chrysoperla rufilabris increased in response to ground cover in pecan orchards (Smith et al., 1996). Hence these results divulged that maximum H. pallidus (0.91) were encouraged by Apple + Trifolium among all other treatments in the current studies.

4.4.3.5. Average yield (kg/tree)

The data pertaining to the yield (kg/tree) of the apple orchard having different intercrops revealed that maximum yield (77.00±1.30 and 76.25±0.96 kg/tree) was obtained from the Apple + Trifolium during the year 2012 and 2013, whilst the lowest yield (53.75±0.72 and 52.75±1.23 kg/tree) was recorded for the Apple Sole. However, Apple + Mustard also showed maximum performance (70.87±1.02 and 69.50±1.59 kg/tree) and ranking second after Apple + Trifolium in increasing the yield of apple. Nonetheless, the cropping system such as Apple + Wheat and Apple + Soybean were inferior and comparatively gave less yield (64.00±0.84 and 61.47±1.11 ; 67.12±1.23 and 66.75±0.47 kg/tree respectively) during both the year of studies. However, influence of intercropping in term of enhancement in yield of marketable apple fruit were found to be in order of : Apple + Trifolium > Apple + Mustard > Apple + Soybean > Apple + Wheat > Apple sole (Having no intercrop), which are amounting to be in order of: 77.00±1.30 and 76.25±0.96 > 70.87±1.02 and 69.50±1.59 > 67.12±1.23 and 66.75±0.47 > 64.00±0.84 and 61.47±1.11 > 53.75±0.72 and 52.75±1.23 kg/tree respectively in both the years of studies. According to previous workers (Boller et al., 2004; Debras et al., 2007) increasing plant biodiversity in the orchard may definitly influence insect communities inside that habitate for wide range of resources such as habitate, food, water and shelter.

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Such kind of multy dimensional and wide resources can benefite the orchard pest, polyphagus and disease vector insects, predators and some potenstial parasitoid can ultimatly enhanced the yield of that crop in aparticular agro ecosystem.

Agreda et al. (2006) also found out the importance of the leguminous crops in the traditional fruit orchard by improving its ecological stability and performace. Soil mulching with leguminous crops can enhanced the fertility of the soil and can further benefit the beneficial insect population in the field.

Yield was highest in combination with Phaseolus acutifolius (9.13 t/ha) and Cajanus cajan (7.42 t/ha). Additionally, more abundance and diversity of insect population was observed when intercropping leguminous crops between the mango trees. Abdel- Aziz et al. (2008) reported the impact of two legume cover crops (Egyptian clover) plus the fallow as control. The results showed that fruit set and fruit yield were enhanced and fruit drop was decreased with the cover crop treatments. Intercropping cultivation methods with the Egyptian clover gave the best results regarding yield and soil fertility in the citrus orchard. It is also apparent from the results that maximum yield (76.62±1.11 kg/tree) was obtained from the Apple + Trifolium treatment, whilst all other treatments were inferior in producing substantial yield.

The results further showed that maximum yield losses (31.51%) were avoided by the intercrop Apple + Trifolium and gain in the yield (43.90%) over control was also attributed to the same intercrop, while all other intercrops were inferior in avoiding the yield loses and gain. According to Sathi et al. (2008) percent avoidable losses and gain in the yield for the management of lepidopterus pest by habitat manipulation through intercrops in India.

The results divulged that in all cropping system, adults moth catch were directly proportional to the fruit drop and infestation and inverse relationship were observed for the biological control agents and yield. Habitat manipulation through different prevailed practice of intercropping in the apple orchard were a profound effect on the fruit drop, infestation, biological control agents and yield of the orchard. Thus we conclude that trifolium is the most appropriate plant species of those tested for the attraction of its associated parasitoids A. quadridentata and H. pallidus. Mustard and soybean also showed potential for attracting the said parasitoid. Different crops may be intercrop in the

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apple orchard for the effective management of C. pomonella by increasing agricultural biodiversity for the biological control agents until and unless they may not uphold the pests. To increase natural enemies abundance early in the apple orchard, it may be possible to plant trifolium alongside mustard and soybean; trifolium and mustard will produce large amounts of flowers early in the crop cycle, while soybean will continue to flower and attract the parasitoid and other biological control agents throughout the season. Further studies are needed that look at the potential role of competition in influencing the usefulness of flowering strips in attracting the parasitoids and other natural enemies.

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4.4.4. CONCLUSIONS

The results divulged that among all cropping system, adults moth catch were directly proportional to the fruit drop and infestation while inverse relationship were observed for the biological control agents and yield. Habitat manipulation through different prevailed practice of intercropping in the apple orchard were a profound effect on the fruit drop, infestation, biological control agents and yield of the orchard. Thus we conclude that trifolium is the most appropriate plant species of those tested for the attraction of its associated parasitoids A. quadridentata and H. pallidus. Mustard and soybean also showed good potential for attracting the said parasitoids.

4.4.5. RECOMMENDATIONS

The above findings lead to the following recommendations.

1. Different crops may be intercrop in the apple orchard for the effective management of C. pomonella by increasing agricultural biodiversity for the biological control agents until and unless they may not uphold the pests. 2. To increase natural enemies abundance early in the apple orchard, it may be possible to plant trifolium alongside mustard and soybean; trifolium and mustard will produce large amounts of flowers early in the crop cycle, while soybean will continue to flower and attract the parasitoid and other biological control agents throughout the season. 3. Further studies are needed that look at the potential role of competition in influencing the usefulness of flowering strips in attracting the parasitoids and other natural enemies.

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4.5. EXPERIMENT- 3: SYNCHRONIZED COMPARISON OF THE BEST INSECTICIDE AND INTERCROP

4.5.1. MATERIALS AND METHODS

In the previous experiment, the effect of intercropping such as Apple + Mustard, Apple + Soybean, Apple + Trifolium and Apple + Wheat were studied and the best intercropping was identified on the basis of C. pomonella infestation, natural enemie's abundance and yield of apple. Similarly the best biorational and novel insecticide was also determined on same criteria. In this experiment synchronized comparison was made of the best insecticide (Match), best intercrop (Apple + Trifolium), combined effect of both treatments (apple + Trifolium + Match) and their interaction was compared with control (Apple sole) at Matta Swat during the year 2013.

Four sprays of the Match insecticides were applied. First spray after 80% patal fall, second spray after 20 days of the first spray for the management of first generation of C. pomonella and the remaining two sprays were applied at the interval of 30 days each for control of second generation of C. pomonella. Trifolum were sown on its respective time of sowing in between the rows (5.53 x 5.53 m2) of the apple orchard. This experiment was carried out in the apple orchard having "Red Delicious" variety of same size and age i.e. 12 years old, in randomize complete block design (RCBD) and were replicated in four apple orchards which were at a distance of 1 km from each other in the same locality. The data recording mean fruit drop, percent infestation due to C. pomonella, adult moth catche through pheromone traps and percent parasitism of the two associated parasitoids in treated and control plots were taken on fortnightly basis following the procedures of Prasad (2001) with some necessary modifications. Percent infestation was determined by using the following formula:

Percent infestation (%) = Infested fruit with C. pomonella larvae x 100 Total dropped fruit

The effect of these intercrops and IGR were evaluated on two associated biological control agents i.e. egg-larval parasitoid A. quadridentata (Hymenoptera: Braconidae) and gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae).

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4.5.1.1. Ascogaster quadridentata

All the apple trees in the respective intercrops and IGR treated were banded with corrugated cardboard bands having opening less than 1/20 inch (1.3 mm) with the folds facing down to collect parasitized C. pomonella larvae migrating down the trunk to pupate in Mid July and at the end of September during the year 2013. Bands were wrapped around the trees trunk at a distance of 2-3 feet from the ground and were replaced weekly. Corrugated bands along with overwintering larvae of C. pomonella were kept in a wooden rearing cages (45x45x45cm3) at 25±2 0C and 60-70% relative humidity following the procedures of Tomkins, (1984) with some necessary modifications. The cages were checked weekly for possible emergence of Ascogaster quadridentata and percent parasitism of adult pest and parasitoids were determined by using the following formula:

Percent Parasitism (%) = No, of parasitoid emerged from parasitized larvae x 100 Total No, of overwintering larvae in corrugated bands

4.5.1.2. Hyssopus pallidus

The effect of intercrops and IGR was also evaluated on another associated biological control agent i.e. gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae). For this purpose the dropped infested fruits with C. pomonella larvae were brought to the laboratory and were put in the wooden rearing cages (45x45x45cm3) on 25±2 0C and 60-70% relative humidity (R.H). The cages were checked weekly for the possible emergence of this parasitoids and its percent parasitism in the respective treatments were computed by using the following formula:

Percent Parasitism (%) = No, of parasitoid emerged from infested fruit x 100 Total infested fruit by C. pomonella larvae

Furthermore, pheromone traps were also fixed in each replicate to know male adult moths activities and catches with percent drop and infestation, for the effectiveness of these intercrops on fortnightly basis, following the procedures of Sigsgaard (2011) with some necessary modifications.

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4.5.1.3. Yield data and percent gain and loss in yield

Yield data (kg/tree) was taken in each replicate and treatments after harvest of fruits following the procedures of Saljoqi et al. (2003) with some necessary amendments. Finally the percent gain due to control measures (intercrops + Insecticide) and avoidable loss in yield of apple fruit caused by C. pomonella in each plot were established following the procedures of Sathi et al. (2008) with some minor modification as:

Loss in yield (%) =

Gain in yield (%) =

Where, T = Yield obtained from treated plot (Protected plot) C = Yield obtained from control plot (Unprotected)

4.5.1.4. Statistical Analysis

All the replicated data regarding the fruit drop, mean infestation, adult moth catches and relative occurrence of the parasitoids were statistically analyzed by using analysis of variance technique suitable for randomized complete block design (RCBD) (Steel and Torrie, 1980) by using computer program “Statistics 8.1®” version. All the significant means were unconnected by LSD test at α 0.05% level of probability. All the replicated data regarding fruit drop, mean infestation, adult moth catches and relative occurrence of the parasitoids were square root transformed (√0.5+X) prior to statistical analysis.

Table-4.15: Treatments combinations of insecticide and intercropping for management of C. pomonella during the year 2013

S. # Treatments Treatments combinations 1. T1 Best Insecticide (Match) 2. T2 Best Intercropping (Apple + Trifolium) 3. T3 Best Insecticides + Intercropping (Apple + Trifolium + Match) 4. T4 Apple (Sole) – Control

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4.5.2. RESULTS

4.5.2.1. Mean Fruit Drop

The ANOVA pertaining to the fruit drop caused by the C. pomonella in the apple orchard having different treatments of chemical insecticide, intercrop and combined effect (T1+T2) are given in appendix-40. The data regarding fruit drop in apple orchard having different treatments for the management of C. pomonella, revealed highly significant differences among the different treatment means, compared by Fischer' LSD test, at P = 0.05 (Table-4.16). It is evident from the results depicted in the Table- 4.16 that apple plants which were left untreated (Control) had maximum mean fruit drop (8.9) and were statistically different from all other treatments except treatment T1 (Match). The lowest mean fruit drop was observed in the Apple + Trifolium + Match (T1+T2) (4.07) followed by Match (5.8) and Apple + Trifolium (6.52), which were statistically different from each other but T1 and T2 were statistically at par with each other. So that T1+T2 combined effect showed minimum fruit drop as compared to the individual effect of each treatment.

Table-4.16: Mean fruit drop in apple orchard for different treatments during the year 2013

Treatments Mean Fruit Drop Match 5.80 b (2.41) Apple + Trifolium 6.52 b (2.53)

Apple + Trifolium + Match (T1+T2) 2.07 c (2.03) Apple sole (Control) 8.90 a (2.96) LSD (p<0.05) 1.60 Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X).

4.5.2.2. Mean Percent Infestation

The ANOVA associated to the mean and percent infestation of the fruit caused by the C. pomonella in the apple orchard during the year 2013, as affected by different treatments, are depicted in appendix-41. The data regarding mean and percent infestation in the apple orchard having treatments for the management of C. pomonella, revealed highly significant differences among the treatments and percent means infestation were compared by Fischer's LSD test, at P = 0.05 (Table-4.17). It is obvious from the results that maximum mean infested fruit was observed in the untreated plant of apple (Apple

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sole) (6.67) having mean percent infestation 67.36% which was statistically higher than all other infestations in different treatments. The lowest mean infestation was recorded for the apple plant treated with Match having Apple + Trifolium intercropping (T1+T2)

(1.77) with mean percent infestation 36.41% followed by T1 (Match) having mean infestation 3.05 with mean percent infestation 46.74% which were statistically at par with each other. The treatment T2 (Apple + Trifolium) having mean infestation 4.17 with percent infestation 59.49% which significantly differed from T3 and T4. It is evident from the results that combination of best insecticide with best intercropping (T1+T2) has a profound effect on reducing the infestation of C. pomonella.

Table-4.17: Mean infestation of apple fruit caused by C. pomonella in apple orchard for different treatments during the year 2013

Mean Infestation Percent Infestation Treatments (%) Match 3.05 (1.17) 46.74 b Apple + Trifolium 4.17 (2.04) 59.49 a

Apple + Trifolium + Match (T1+T2) 1.77 (1.39) 36.41b Apple sole (Control) 6.67 (2.52) 67.36 a LSD (p<0.05) 1.25 11.33 Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X).

4.5.2.3. Mean C. pomonella Catches

The ANOVA pertaining to the adult moth catches through pheromone traps in the apple orchard as affected by different treatments, are given in appendix-42. The data regarding adult moth catches through traps in apple orchard under different treatments for the management of C. pomonella, revealed significant differences among the different treatment means, compared by Fischer's LSD test, at P = 0.05 for significance (Table- 4.18). The data depicted in the result table revealed that maximum mean adults moths were trapped in the untreated plants (Apple sole) (5.45) followed by plants having intercrops of Trifolium (T2) (3.15), plants treated with insecticide Match (2.22) while the lowest mean adult moth were caught in the apple orchard having Trifolium as intercrop and treated with Match (T1 + T2) (1.30). Statistical analysis regarding the adults moth catches showed that mean moth catches in T1 were statistically at par with T2 and T3 but differed significantly from among T3 and T4.

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Table-4.18: Mean C. pomonella catches through pheromone traps in apple orchard for different treatments during the year 2013

Treatments combinations Mean C. pomonella Catches Match (T1) 2.22 bc (1.47) Apple + Trifolium (T2) 3.15 b (1.68)

Apple + Trifolium + Match (T1+T2) (T3) 1.30 c (1.13) Apple sole (Control) (T4) 5.45 a (2.33) LSD (p<0.05) 1.04 Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X).

4.5.2.4. Percent Parasitism of A. quadridentata

The ANOVA regarding the mean and percent parasitism of egg-larval parasitoid A. quadridentata (Hymenoptera: Braconidae) of the C. pomonella during the year 2013, having different treatments in apple orchard are depicted in appendix-43. The data pertaining to the mean percent population of the A. quadridentata for the management of C. pomonella, revealed significant differences among the different treatments and mean populations were compared by Fischer's LSD test, at P = 0.05 for significance (Table- 4.19).

Table-4.19: Mean percent parasitism of A. quadridentata in apple orchard for different treatments during the year 2013

Mean Population of A. Percent parasitism Treatments quadridentata (%) Match 0.22 (0.81) 5.30 c Apple + Trifolium 0.67 (1.03) 15.86 b

Apple + Trifolium + Match (T1 + T2) 0.92 (1.11) 32.83 a Apple sole (Control) 0.60 (0.98) 11.80 bc LSD (p<0.05) 0.28 10.10 Means sharing similar letter(s) are not significantly different by Fischer's LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X).

The results revealed that more A. quadridentata was attracted to the plot having combination of intercrop of Trifolium in the apple orchard and treated with Match insecticide (T1 + T2) (0.92) with mean percent occurrence 32.83% followed by Apple + Trifolium (0.67) having mean percent occurrence 15.86% differed significantly from Match treated plants having less number of A. quadridentata (0.22) with percent

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population of 5.30%. However, the effect of Match on the parasitism of A. quadridentata and apple sole were statistically at par with each other. The results further showed that the combined effect of Trifolium intercrop treated with Match insecticide (T1+ T2) attracted maximum number of A. quadridentata compared to all other treatments effect on the said biological control agent.

4.5.2.5. Percent parasitism of H. Pallidus

Table-4.20 illustrates the results pertaining to the mean percent parasitism of gregarious ectoparasitoid H. pallidus (Hymenoptera: Eulophidae) of the C. pomonella in the apple orchard during the year 2013, having intercrop and insecticide application and ANOVA depicted in appendix-44. The data regarding mean percent occurrence of the H. pallidus for the management of C. pomonella, revealed significant differences among the different treatments and mean percent population , compared by Fischer's LSD test, at P = 0.05 for significance (Table-4.20).

Table-4.20: Mean percent parasitism of H. pallidus in apple orchard having different treatments during the year 2013

Mean population of H. Percent Parasitism Treatments pallidus (%)

Match 0.22 (0.82) 5.58 b Apple + Trifolium 0.60 (0.99) 14.27 b

Apple + Trifolium + Match (T1 + T2) 0.85 (1.10) 34.66 a Apple sole (Control) 0.52 (0.93) 10.14 b LSD (p<0.05) 0.31 9.98 Means sharing similar letter(s) are not significantly different by Fischer' LSD test at α = 0.05. Data in the parenthesis are square root transformed (√0.5+X).

The results clearly indicates that mean maximum number of H. pallidus (0.85) emerged from the infested fruits in the orchard having Apple + Trifolium treated with spray application of Match insecticide having percent occurrence 34.66% which was statistically different from all other treatments except Apple + Trifolium which were statistically at par with each other. Treatment T2 (Apple + Trifolium) and T4 (Apple sole) were statistically at par with each other having mean occurrence of H. pallidus of 0.60 with percent occurrence 5.58% and 0.52 with percent occurrence 10.14% respectively, but differed significantly from T1 and T3 having mean and percent occurrence 0.22,

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5.58% and 0.85, 34.66% respectively. It is evident from the results that maximum mean percent H. pallidus were observed in the Apple + Trifolium treated with Match insecticide (T3).

4.5.2.6. Average Yield (kg/tree)

Table-4.21 demonstrates the comparison of mean values for the data regarding yield (kg/tree) in apple orchard having different treatments at the time of harvest during the year 2013 (Appendix-45). The data revealed significant differences among the different treatments. The results divulged that high yield (94.75±0.62 kg/tree) was recorded for the trees treated with Match insecticide having intercrop of Trifolium (T1+

T2) followed by plants treated with Match insecticide (T1) (83.75±1.19 kg/tree), Apple +

Trifolium (T2) (77.00±1.17 kg/tree) and Apple sole (T4) having average yield 57.75±0.14 kg/tree. Statistical analysis showed that all the means were statistically different from each other. It is further evident from the results that high yield was obtained from the treatments having Trifolium as intercrop and treated with Match insecticide.

Table-4.21: Comparison of the yield (kg/tree) at the time of harvest in apple orchard having different treatments during the year 2013

Mean yield (kg/tree) Avoidable loss in yield Gain in yield Treatments (±SE) (%) (%) Match 83.75±1.19 b 31.04 45.02 Apple + Trifolium 77.00±1.17 c 25.00 33.33 Apple + Trifolium + Match 94.75±0.62 a 39.05 64.07 Apple sole (Control) 57.75±0.14 d ------LSD (p<0.05) 2.90 ------Means (±SE) sharing similar letter(s) are not significantly different by Fischer's LSD test at α=0.05.

Table - 4.21 further revealed that total of 31.04% losses were expected in the Match treated plots which were avoided due to these control measures, Similarly, in Apple + Trifolium intercrops, 25.00% losses were avoided due to control measures. Nonetheless, maximum losses 39.05%) were avoided in the intercrops Apple + Trofolium + Match spray application. Likewise, gain in the yield was also calculated after application of Match sprays and habitat manipulation through intercrop of Trifolium. Maximum gain in the yield (64.07%) was observed for the Apple + Trifolium + Match

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combination over control plots, followed by Match spray applications having gain in the yield 45.05% and Apple + Trifolium intercrops were 33.33%. However, influence of intercropping and insecticides application in term of enhancement in yield of marketable apple fruit were found to be in order of : Apple + Trifolium + Match > Match spray Applications alone > Apple + Trifolium > Apple sole.

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4.5.3. DISCUSSION

4.5.3.1. Mean Apple Fruit Drop

The results pertaining to the mean fruit drop disclosed that maximum mean fruit drop (8.9) was observed in the apple sole (Control), whilst the lowest mean fruit drop were noticed for Apple + Trifolium + Match (2.07). However, Match treated plots were mean fruit drop 5.8 and did not curtailed the fruit drop alone comparatively in combination with intercropping. Apple + Trifolium (6.52) were inferior in reducing the fruit drop among all other treatments but was effective than apple sole. Consequently, Apple + Trifolium + Match (IGR) was effective in reducing and minimizing the fruit drop of apple fruit due to C. pomonella infestation. Shah (2008) reported that IGRs are ovicidal as well as larvicidal and not toxic to predatory/beneficial insects in the intercropping. The beneficial effects of the application of growth regulators can be seen one to two days after application and help in minimizing the fruit drop of apple. According to Abdel- Aziz et al. (2008) the fruit drop was substantially reduced with the intercrops clovers treatments in the citrus orchard as compared to sole orchard.

4.5.3.2. Mean Percent Infestation of C. pomonella

The data pertaining to mean percent infestation of C. pomonella explicated that highest mean percent infestation (67.36%) was witnessed in the control plot with mean, whilst the lowest mean infestation (36.41%) was observed for Apple + Trifolium + Match with. Nonetheless, in Match treated plot the mean infestation was 3.05 with mean percent infestation 46.74% while in the Apple + Trifolium, mean infestation was 4.17 with percent mean infestation 59.49% and were comparatively inferior in reducing the infestation of C. pomonella. The combined effect of Apple + Trifolium + Match treatment proved very effective among all other treatments in reducing the infestation of C. pomonella. According to Irvin et al., (2008) that with no monitoring or treatments and if C. pomonella and Epiphyas postvittana were uncontrolled other than by naturally occurring Trichogramma or other beneficial insects and organisms, the maximum damage caused by Epiphyas postvittana and C. pomonella would be more than one percent or less of crops. Sathi et al. (2008) reported that the combination of intercropping with insecticides reduces the pest incidence in cauliflower for the effective management of Plutella xylostella. Almost similar findings were reported by Prasad (2001) who

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investigated that intercropping in combination with safe insecticide has a great impact on the insect pest incidence and play a vital role in curtailing their infestation.

4.5.3.3. Mean C. pomonella Catches

Harcourt (1986) investigated that monitoring pest density and incidence of the parasitism by biological control agents can play effective role in the pest management program. During monitoring of pest activity and the pest damage pheromone traps are world wide used with respect to the weather factors. So during warm weather conditions, insect population are developing faster as compared to cool weather condition, so in hot days monitoring should be frequently carried out for determining pest activity. Hence, the data pertaining to mean C. pomonella catches through pheromone traps elucidated that maximum number of adult moths were trapped in the control plot (5.45) having no spray application and intercrops, whilst the lower number of moths (1.30) were caught in the Apple + Trifolium + Match spray applications in the pheromone trap. Nevertheless, Apple + Trifolium treatment proved inferior and a substantial moth catches (2.22) were observed followed by Match spray application proved effective in curtailing the C. pomonella adult catches (3.15) in the pheromones traps. Consequently, best result were offered by the combination of Apple + Trifolium + Match spray in reducing the adult moth catches and reducing the flare up of the said pest. These results are corroborated with findings of Harder (2008) who reported the researchers and extension workers are mostly using the pheromone sticky traps for the monitoring of Light brown apple moth (Epiphyas postvittana) and C. pomonella populations in New Zealand for the prevention of pest flare up which was based on timely application of insect growth regulator (IGR) and pest monitoring data. According to Shaw (2008), in California, IGRs should probably be applied in May, but the timing needs to be verified by phenological monitoring using pheromone traps for adult males.

4.5.3.4. Impact on the Biological Control Agents

During the current experiment, the percent occurrence of A. quadridentata fluctuated with different treatments. Mean maximum number (0.92) of the A. quadridentata were examined in the Apple + Trifolium + Match sprayed plots having percent occurrence 32.83%. Besides, Apple + Trifolium also attracted substantial number (0.67) of the A. quadridentata having percent occurrence 15.86% comparatively higher

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than the control plot (0.60) with percent occurrence 11.30%, whilst Match spray application proved inferior and the lowest number (0.22) of A. quadridentata were noticed in the growing crop season having percent occurrence 5.30%. Nonetheless, in the current experiment, the results revealed that Apple + Trifolium + Match spray application demonstrated good results and encouraged A. quadridentata population in the management of C. pomonella. Begaum et al. (2008) reported that it is worth noting that in New Zealand, intercropping has shown to promote beneficial insect populations, resulting in near-complete Epiphyas postvittana and C. pomonella population suppression to below thresholds for use of control measures.

The results pertaining to the mean percent occurrence of H. pallidus revealed that mean maximum number (0.85) of H. pallidus were discerned in the Apple + Trifolium + Match spray application having mean percent occurrence 34.66%, whilst the lowest mean number (0.22) of H. pallidus were recovered from the plots treated with Match IGR spray applications having mean percent occurrence 5.58%. Nevertheless, Apple + Trifolium also supported and encouraged maximum number (0.60) of H. pallidus with mean percent occurrence 14.27%. H. pallidus were also observed in the Apple sole plots (0.52) with mean percent occurrence 10.14%. Consequently, among all other treatments including apple sole, Apple + Trifolium + Match spray applications established a good impact for encouraging the natural enemies particularly H. pallidus in the current experiment.

Harder (2008) reported that beneficial insects are more effective for the management of leaf rollers and C. pomonella if the floral sources are present inside the filed for the survival of these natural enemies. Further, he added that insect growth regulators (IGR) which are derived from natural resources are very effective for the management of leaf roller and C. pomonella control in New Zealand orchards. These results are also supported by the previous workers, (Jervis and Kidd, 1996). They reported that floral and extrafloral nectar and pollen are essential sources of carbohydrates and proteins for many parasitoids and are therefore crucial for their fitness. Many studies have shown that access to these floral resources increases survival and reproduction of parasitoids for effective management of particular pest in the field. (Wackers et al., 2005; Wade and Wratten, 2007).

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4.5.3.5. Average Yield (kg/tree)

The efficacy of respective intercropping combination and insecticides (Match) were found to have mutually enhanced the yield of the marketable apple fruit particularly when both the intercrop and Match (IGR) application were adopted together. The results illustrated that maximum yield (kg/tree) of apple was obtained from the Apple + Trifolium + Match spray applications (94.75±0.62 kg/tree), whilst the yield in control plot were the lowest (57.57±0.14 kg/tree) among all other treatments. Nonetheless, Match treated plots afforded comparatively higher yield (83.75±1.19 kg/tree) than Apple + Trifolium treatment having mean yield 77.00±1.17 kg/tree. Consequently, Apple + Trifolium + Match afforded good performance in boosting up the yield of apple fruit. Further, it also avoided maximum percent yield losses (39.05%), leading to gain in the yield (64.07%) among all other treatments. Sathi et al. (2008), reported that when Cauliflower + Intercrop + Insecticides applied in combination, consequently reduced the Plutella xylostella population and substantial enhancement in the yield were recorded as compared to the control plot having no intercrops and insecticides applications. However, influence of intercropping and insecticides application in term of enhancement in yield of marketable apple fruit were found to be in order of : Apple + Trifolium + Match > Match spray Applications alone > Apple + Trifolium > Apple sole (Having no intercrop and insecticides application). Almost similar results were obtained by Prasad (1998 and 2001) and Prasad et al. (2007) who found out significant interactive effect of the intercropping and insecticides that resulted to reduction in pest incidence and enhancement in the yield. It is also noteworthy to infer that the eco- friendly approach of management of C. pomonella comprising of Trifolium grown as intercrop along with apple coupled with Match spray applications emerged as highly effective insecticide which boosted yield of apple as compared to unprotected apple sole.

The interactive effect of intercropping trifolium (T. alexandrinum) (Fabacae) coupled with application of insecticide i.e. Match proved highly effective in minimizing the incidence of C. pomonella and maximizing and upholding the associated parasitoids A. quadridentata, H. pallidus. It is also note worthy to infer that the eco friendly approach of management of C. pomonella comprising trifolium as intercrop along with apple orchard coupled with four foliar sprays of Match emerged as highly effective environment friendly insecticide which give rise to increase the yield of apple compared

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to the untreated sole apple orchard. Habitat manipulation through intercropping of T. alexandrinum (Fabacae) in the apple orchard accompanied by IGR spray application for the management of C. pomonella were a profound impact in curtailing mean fruit drop, percent infestation and adult moth catches through pheromone traps. Nevertheless, positive relations were observed for percent parasitism of A. quadridentata, H. pallidus and average yield of apple due to synchronized effect. Further research may be carried out for other potential safe insecticides and intercrops for the effective management of C. pomonella and its impact on associated natural enemies and ultimately on yield.

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4.5.4. CONCLUSIONS

The interactive effect of intercropping trifolium (T. alexandrinum) (Fabacae) coupled with application of insecticide i.e. Match proved highly effective in minimizing the incidence of C. pomonella and maximizing and upholding the associated parasitoids A. quadridentata and H. pallidus. It is also note worthy to infer that the eco friendly approach of management of C. pomonella comprising trifolium as intercrop along with apple orchard coupled with four foliar sprays of Match emerged as highly effective environment friendly insecticide which give rise to increase the yield of apple compared to the untreated sole apple orchard. Habitat manipulation through intercropping of T. alexandrinum (Fabacae) in the apple orchard accompanied by IGR spray application for the management of C. pomonella were a profound impact in curtailing mean fruit drop, percent infestation and adult moth catches through pheromone traps. Nevertheless, positive relations were observed on percent parasitism of A. quadridentata, H. pallidus and average yield of apple due to synchronized effect.

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4.5.5. RECOMMENDATIONS

The above findings lead to the following recommendations.

1. The interactive effect of intercropping trifolium (T. alexandrinum) (Fabacae) coupled with application of insecticide i.e. Match proved highly effective in minimizing the incidence of C. pomonella and maximizing and upholding the associated parasitoids A. quadridentata and H. pallidus.

2. The said treatment was also having a profound impact in curtailing mean fruit drop, percent infestation and adult moth catches through pheromone traps.

3. From the results of this research, it is recommended that farmers can use Match and intercropping Trifolium in apple orchard to manage C. pomonella infestation.

4. Further research may be carried out for other potential safe insecticides and intercrops for the effective management of C. pomonella and its impact on associated natural enemies and ultimately on yield.

5. This is the first kind of its research against this insect pest in Swat Khyber Pakhtunkhwa, therefore, these basic informations regarding population dynamics, genetic variations and various methods of management of this pest will be of great importance for the farming community to manage C. pomonella and to save the apple crop from extinction in Swat.

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OVERALL CONCLUSION & RECOMMENDATIONS

1. First adults of C. pomonella trapped during 17th to 18th SMW in all the three locations.

2. The first peak population recorded during 25th to 30th SMW, therefore, steps are required in this month to minimize losses.

3. Second peak population were observed & trapped during 31st to 35th SMW, so maximum two peak populations were observed during studies.

4. Temperature had highly significant positive effect on C. pomonella catches.

5. Total rainfall & R.H (morning & evening) had non significant negative effect on the population build up of C. pomonella.

6. Thus such studies may offer an insight on the possible impact of weather parameters on population dynamics of this pest and insecticide applications based on trap captures can significantly reduce the number of sprays needed for C. pomonella management.

7. RAPD markers are efficient tools for assessing the population variation in insect pests and knowledge of the genetic variation within C. pomonella populations is necessary for their efficient control and management.

8. Higher genetic distances among the populations of C. pomonella could be attributed to climatic conditions of the studied areas, geographical locations, elevations and indiscriminate use of insecticides.

9. Besides, RAPD primers, gene specific primers and methods like AFLP and RFLP can also be used for molecular variation among the population of C. pomonella and other lepidopterious pests.

10. Insect growth regulator (Match) has a profound effect in curtailing the C. pomonella infestation, more safer for its associated parasitoids and enhancing the yield and can be effectively used for the management of C. pomonella.

11. Nevertheless, its safety should be tested for other biological control agents in apple orchard or in other agro ecosystems.

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12. Likewise, habitat manipulation through different prevailed practice of intercropping particularly Trifolium in the apple orchard had a profound effect on the fruit drop, infestation, biological control agents and yield of the orchard.

13. Trifolium is the most appropriate plant species of those tested for the attraction of its associated parasitoids Asogaster quadridentata and Hyssopus pallidus.

14. Further studies are needed that look at the potential role of competition in influencing the usefulness of this intercrop and other flowering strips in attracting the parasitoids and other natural enemies.

15. It is also note worthy to infer that the eco friendly approach of management of C. pomonella comprising Trifolium as intercrop in apple orchard coupled with foliar sprays of Match emerged as highly effective environment friendly insecticide which give rise to increase the yield of apple compared to other treatments.

16. Further research may be carried out for other potential safe insecticides and intercrops for the effective management of C. pomonella and its impact on associated natural enemies and ultimately on yield.

17. This is the first kind of its research against this insect pest in Swat Khyber Pakhtunkhwa, therefore, these basic information regarding population dynamics, genetic variations and various methods of management of this pest will be of great importance for the farming community to manage C. pomonella and to save the apple crop from extinction in Swat.

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FUTURE CHALLENGES

1. Further studies are needed to discern the impact of meteorological parameters on the population dynamics of C. pomonella in various geographical locations.

2. Degree Day (DD) methods needs to be used for population trends and phenology of this pest.

3. Molecular studies are efficient tools for knowing genetics variations among the population of this pest, so further studies are needed to find out biodiversity in various populations in different geographical locations even countries.

4. Besides, RAPD primers, gene specific primers and methods like AFLP and RFLP can also be used for molecular variation among the population of C. pomonella and other lepidopterious pests.

5. Match insecticides (IGR) had a profound effect in curtailing the C. pomonella infestation, safer for its associated parasitoids and enhancing the yield, nevertheless, its safety needs be tested for other biological control agents in apple orchard or other agro ecosystems.

6. Further studies are needed that look at the potential role of competition in influencing the usefulness of Trifolium as intercrop and other flowering strips in attracting the parasitoids and other natural enemies in the apple orchard.

7. Field research may further be carried out for other potential safe insecticides and intercrops for the effective management of C. pomonella and its impact on associated natural enemies and ultimately on yield.

8. The various management tools studied in this research study needs to be measured for their negative impact on C. pomonella and its natural enemies up to few generation levels.

9. The suitability, applicability and sustainability of findings/recommendations of this research study needs to be assessed in joint teamwork with extension field staff and research departments of the said province.

10. Feedback from the farming community about the impediments in launching the new technologies is required and would enable us to design experiments as per their approach, vision and ground realities.

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SUMMARY

The studies were carried out on the population dynamics, molecular characterization and management of C. pomonella at District Swat during the year 2012 and 2013. The main objectives of the studies were to study the population dynamics of C. pomonella in three main apple growing areas and also to find out the influence of abiotic factors, like relative humidity (R.H) at morning (0300Z) and at evening (1200Z), maximum and minimum temperature and total rainfall on the population fluctuations of adults male C. pomonella catches in the pheromones traps by using Standard Meteorological Weeks (SMW) through correlation and multivariate regression models. Furthermore, molecular characterization of the C. pomonella was studied to detect variation in the population of C. pomonella on molecular level in different samples collected from aforementioned three locations, in addition to checking out the biological efficacy of different insecticides against C. pomonella alone and in integration with growing of different intercrops for a successful management of the C. pomonella and their impact on its associated parasitoids such as egg larval parasitoid A. quadridentata (Hymenoptera; Braconidae) and gregarious ectoparasitoid H. pallidus (Hymenoptera; Eulophidae). In the synchronized effect, the results of best insecticide, intercrop and their synchronized effect were evaluated for the management of C. pomonella and its impact was studied on its associated parasitoids and yield of apple fruit. The data on post- treatment regarding fruit drops and percent infestation were recorded fortnightly after the application of various treatments. The data on yield in kg per plant were, however, recorded at the time of harvest for each experiment and percent avoidable losses in yield and gain in the yield due to protection measures were also calculated.

The first peak population of C. pomonella observed at Matta, Madyan and Kalam were 11.25±1.25, 11.0±1.03 and 8.25±0.62 moths/trap in 25th, 27th and 29th SMW respectively, whilst the second peak population were 12.0±0.81, 10.25±0.9 and 9.25±0.86 moths/trap in all the three locations in 33rd SMW during the year 2012. During the year 2013, the first and second peak population at Matta were 15.75±1.65 & 13.0±0.81 moths/trap in 26th and 32nd SMW, at Madyan, 10.25±0.81 & 9.00±0.70 moths/trap in 29th and 35th SMW and at Kalam were, 7.25±1.25 & 7.50±0.95 moths/trap in 27th and 30th SMW respectively. Correlation matrix revealed that C. pomonella showed positive significant correlation with both maximum and minimum temperature, whilst nonsignificant negative correlation with percent relative humidity (Morning and evening).

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Nonetheless, C. pomonella showed significantly negative association with total rainfall except in Matta. Multiple regression models explained 68.78 to 83.42% variability due to meteorological factors in the population dynamics of C. pomonella at all the three locations at Swat during the year 2012 and 2013.

Population variation in C. pomonella was studied by using RAPD markers on three geographical populations i.e. Matta, Madyan and Kalam from Swat Pakistan. Genomic DNA was extracted from 30 overwintering larvae of each population. Out of 30 tested primers, 21 amplified 157 polymorphic bands in three populations. The mean gene frequency (f), gene diversity (I) and Shannon's information index (h) for three populations were 1.33, 0.30 and 0.43 respectively. Nei’s unbiased measures of genetic identity and genetic distance revealed that higher genetic distance (97.87%) was observed among the isolates from Kalam and Madyan whereas low genetic distance (35.58%) was calculated for C. pomonella isolates from Matta and Madyan. Similarly the Nei's genetic identity divulged that higher genetic similarity (70.06%) was resided by the C. pomonella population at Matta and Madyan whilst the low level of identity (37.58%) were examined in isolates from Madyan and Kalam.

The results pertaining to the efficacy of different novel insecticides (Match®, Madex®, Delegate®, Timer® and Assail®) divulged that Match insecticides afforded less mean fruit drop (2.50) and minimum percent infestation due to C. pomonella (21.39%) compared to all other treatments including control. The said treatments also proved effective and safe for the two associated parasitoids under studies i.e. A. quadridentata (Hymenoptera: Braconidae) and H. pallidus (Hymenoptera: Eulophidae) having mean percent parasitism 26.43% and 27.89% respectively, whilst the rest of the treatments were encouraged minimum number of biological control agents. Higher biological efficacy (86.67%) was recorded for the Match insecticide whilst the lowest were calculated for Assail (39.56%). Similarly, highest yield (kg/tree) were obtained from Match treated plots (86.81±0.42), which were significantly higher than all the treatments including control plots during both the years of studies. Likewise, maximum gain in the yield (62.66%) over control was attributed to Match insecticide which was significantly higher than the rest of the treatments including control.

Habitat manipulation through intercropping [(Brassica campestris, Brassacicacae), Glycine max, leguminacae), Trifolium alexandrinum, Fabaceae) and

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Triticum aestivum, Poaceae)], had a substantial effect on all parameters studied in the apple orchard for the management of C. pomonella. Minimum mean fruit drop (2.87) were recorded for the intercrop Apple + Trifolium which were significantly lower than all the other intercrops including control (Apple sole). Likewise, minimum percent infestation (57.19%) was observed for the Apple + Trifolium, whilst maximum 85.86% was noticed in the Apple sole. Same intercrop had also good impact not only on the C. pomonella in curtailing its mean moth catch (1.46) through traps but also maximized percent parasitism of A. quadridentata (Hymenoptera: Braconidae) (40.11%) and H. pallidus (Hymenoptera: Eulophidae) (30.09%) in the same intercrop during both the years of studies. Similarly, highest yield (kg/tree) were produced by the plots having Apple + Trifolium intercrops (76.62±1.11), whilst minimum yield were recorded for Apple + Wheat (61.47±1.11) followed by apple sole (52.75±1.23). The results further showed that maximum yield losses (31.51%) were avoided by the intercrop Apple + Trifolium and gain in the yield (43.90%) over control was also attributed to the same intercrop, whilst all other intercrops were inferior in avoiding the loses and gain in the yield.

Studies regarding the synchronized effect of best insecticide and intercrops were also evaluated during the year 2013. The results disclosed that Apple + Trifolium ® (Trifolium alexandrinum) + Match (T3) afforded minimum mean fruit drop (2.07) and ® lower percent infestation (36.41%), followed by Match (T1) (46.74%), Apple +

Trifolium (T2) (59.49%) and maximum was in control plot (T4) (67.36%). Likewise, minimum mean number of C. pomonella adults (1.30 moths/traps) was monitored in the ® Apple + Trifolium + Match (T3), whilst all other treatments including control had the maximum number of C. pomonella adults catch in the traps. The percent parasitism of A. quadridentata and H. pallidus ` were significantly higher in T3 had 32.83 and 34.66% respectively. Maximum yield were recorded by T3 (94.75±.62 kg/tree) followed by T1

(83.75±1.19 kg/tree), T2 (77.00±1.17 kg/tree) and Apple sole (T4) (57.75±0.14 kg/tree).

Maximum losses (39.05%) were avoided in T3, whilst the percent gain in yield (64.07%) due to control measures was also attributed to T3.

It can be concluded from these studies that Match (IGR) can be used in integration with intercrop in the apple orchard for the effective management of C. pomonella which is safe for the natural enemies and has a profound effect on the yield. The use of these techniques may play a more prominent role in integrated control of C. pomonella in future.

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APPENDICES

Appendix-1: Analysis of variance table for linear multiple regression of means for C. pomonella at Matta Swat during the year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Regression 5 333.898 66.7795 19.61* 0.000 Residual 19 64.717 3.4062 Total 24 398.615 * = Significant at α =0.01

Appendix-2: Analysis of variance table for linear multiple regression of means for C. pomonella at Matta Swat during the year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Regression 5 403.176 80.6351 10.32* 0.0001 Residual 19 148.434 7.8123 Total 24 551.610 * = Significant at α =0.01

Appendix-3: Analysis of variance table for linear multiple regression of means for C. pomonella at Madyan Swat during the year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Regression 5 269.671 53.9343 20.13* 0.000 Residual 19 53.581 2.6791 Total 24 323.252 * = Significant at α =0.01

Appendix-4: Analysis of variance table for linear multiple regression of means for C. pomonella at Madyan Swat during the year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Regression 5 199.953 39.9905 9.94* 0.0001 Residual 19 76.462 4.0243 Total 24 276.415 * = Significant at α =0.01

Appendix-5: Analysis of variance table for linear multiple regression of means for C. pomonella at Kalam Swat during the year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Regression 5 156.280 31.2560 12.98* 0.000 Residual 19 45.735 2.4071 Total 24 202.015 * = Significant at α =0.01

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Appendix-6: Analysis of variance table for linear multiple regression of means for C. pomonella at Kalam Swat during the year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Regression 5 167.331 33.4662 18.88* 0.000 Residual 19 33.684 1.7729 Total 24 201.015 * = Significant at α =0.01

Appendix-7: Analysis of variance table for mean fruit drop after insecticides application during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 0.4319 0.14395 -- Treatment 5 29.1870 5.83739 37.07* 0.0000 Error 231 36.3778 0.15748 -- Total 239 65.9967 * = Significant at α =0.01 CV = 17.84%

Appendix-8: Analysis of variance table for mean percent infestation after insecticides application during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 2.132 0.71073 -- Treatment 5 48.312 9.66242 41.48* 0.0000 Error 231 53.804 0.23292 -- Total 239 104.248 * = Significant at α =0.01 CV = 25.03 %

Appendix-9: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata after insecticides application during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 3.2892 1.09640 -- Treatment 5 14.5450 2.90899 27.03* 0.0000 Error 231 24.8630 0.10763 -- Total 239 42.6972 * = Significant at α =0.01 CV = 28.20%

Appendix-10: Analysis of variance table for mean percent parasitism of Hyssopus pallidus after insecticides application during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 0.5806 0.19353 -- Treatment 5 10.4820 2.09640 17.43* 0.0000 Error 231 27.7800 0.12026 -- Total 239 38.8426 * = Significant at α =0.01 CV= 27.88%

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Appendix-11: Analysis of variance table for average yield of apple in kg/tree after insecticides application during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 38.88 12.958 -- Treatment 5 2238.58 447.717 71.83* 0.0000 Error 231 93.50 6.233 -- Total 239 2370.96 * = Significant at α =0.01 CV= 3.47%

Appendix-12: Analysis of variance table for mean fruit drop after insecticides application during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 2.0857 0.69523 -- Treatment 5 38.8046 7.76093 30.71* 0.0000 Error 231 58.3758 -- Total 239 99.2661 * = Significant at α =0.01 CV = 23.02%

Appendix-13: Analysis of variance table for mean fruit infestation after insecticides application during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 7.560 2.5201 -- Treatment 5 56.727 11.3453 47.62* 0.0000 Error 231 55.031 0.2382 -- Total 239 119.318 * = Significant at α =0.01 CV = 28.31 %

Appendix-14: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata after insecticides application during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 8.4741 2.82471 -- Treatment 5 14.4903 2.89806 30.13* 0.0001 Error 231 22.2167 0.09618 -- Total 239 45.1811 * = Significant at α =0.01 CV = 28.01%

Appendix-15: Analysis of variance table for mean percent parasitism of Hyssopus pallidus after insecticides application during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 1.7859 0.59528 -- Treatment 5 7.7787 1.55573 14.28* 0.0003 Error 231 25.1616 0.10892 -- Total 239 34.7261 * = Significant at α =0.01 CV = 27.36%

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Appendix-16: Analysis of variance table for average yield of apple in kg/tree after insecticides application during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 23.61 7.872 -- Treatment 5 3369.93 673.985 70.35* 0.0000 Error 15 143.70 9.580 -- Total 23 3537.24 * = Significant at α =0.01 CV= 4.40 %

Appendix-17: Combined analysis of variance table for mean fruit drop in apple orchard after insecticides application during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 0.192 0.1916 0.46 0.5244 Year*Rep (E) 6 2.518 0.4197 Treatment 5 66.861 13.3721 65.20* 0.0000 Year*Trt 5 1.132 0.2264 1.10 0.3575 Error 462 94.756 0.2051 Total 479 165.458 * = Significant at α =0.01 CV = 11.69 %

Appendix-18: Combined analysis of variance table for mean percent infestation in apple orchard after insecticides application during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 0.84 0.841 0.05 0.8271 Year*Rep (E) 6 9.696 1.6160 Treatment 5 104.538 20.9075 88.75* 0.0000 Year*Trt 5 0.511 0.1021 0.43 0.8252 Error 462 108.841 0.2356 Total 479 223.669 * = Significant at α =0.01 CV = 12.99 %

Appendix-19: Combined analysis of variance for mean percent parasiotism A. quadridentata in apple orchard after insecticides application during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 0.0032 0.00325 0.00 0.9689 Year*Rep (E) 6 11.7603 1.96005 Treatment 5 28.8315 5.76629 56.60* 0.0000 Year*Trt 5 0.2004 0.04007 0.39 0.8534 Error 462 47.0663 0.10188 Total 479 87.8617 * = Significant at α =0.01 CV = 26.49 %

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Appendix-20: Combined analysis of variance table for mean percent parasiotism H. pallidus in apple orchard after insecticides application during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 0.0131 0.01308 0.03 0.8641 Year*Rep (E) 6 2.3650 0.39417 Treatment 5 17.9688 3.59375 31.37* 0.0000 Year*Trt 5 0.2882 0.05765 0.50 0.7738 Error 462 52.9213 0.11455 Total 479 73.5564 * = Significant at α =0.01 CV = 34.75 %

Appendix-21: Combined analysis of variance table for average yield of apple in kg/tree after insecticides application during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 34.17 34.17 3.28 0.1200 Year*Rep (E) 6 62.49 10.41 Treatment 5 5470.65 1094.13 138.38* 0.0000 Year*Trt 5 137.86 27.57 3.49 0.0133 Error 30 237.20 7.91 Total 47 5942.37 * = Significant at α =0.01 CV= 3.95%

Appendix-22: Analysis of variance table for mean fruit drop in apple orchard having different intercrops during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 2.487 0.82913 -- Treatment 4 32.054 8.01345 17.98* 0.0006 Error 192 85.575 0.44570 -- Total 199 120.116 * = Significant at α =0.01 CV = 28.25%

Appendix-23: Analysis of variance table for mean percent infestation in apple orchard having different intercrops during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 6.355 2.11847 -- Treatment 4 32.840 8.21006 20.55* 0.0001 Error 192 76.720 0.39958 -- Total 199 115.915 * * = Significant at α =0.01 CV = 27.02 %

Appendix-24: Analysis of variance table for mean moth catches in apple orchard having different intercrops during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 26.911 8.97027 -- Treatment 4 37.225 9.30614 16.78* 0.0000 Error 192 106.507 0.55473 -- Total 199 170.643 * = Significant at α =0.01 CV = 31.33 %

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Appendix-25: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata in apple orchard having different intercrops during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 1.5651 0.52171 -- Treatment 4 6.5581 1.63951 19.12* 0.0000 Error 192 16.4675 0.08577 -- Total 199 24.5906 * = Significant at α =0.01 CV = 29.63 %

Appendix-26: Analysis of variance table for mean percent parasitism of Hyssopus pallidus in apple orchard having different intercrops during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 1.3152 0.43841 -- Treatment 4 3.1574 0.78936 11.31* 0.0000 Error 192 13.3978 0.06978 -- Total 199 17.8704 * = Significant at α =0.01 CV = 23.29 %

Appendix-27: Analysis of variance table for average yield of apple in kg/tree having different intercrops in apple orchard during year 2012

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 6.55 2.183 -- Treatment 4 1194.32 298.581 60.14* 0.0000 Error 12 59.58 4.965 -- Total 19 1260.45 * = Significant at α =0.01 CV= 3.35 %

Appendix-28: Analysis of variance table for mean fruit drop in apple orchard having different intercrops during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 0.513 0.17102 -- Treatment 4 34.516 8.62891 23.34* 0.0000 Error 192 70.978 0.36968 -- Total 199 106.007 * = Significant at α =0.01 CV = 25.19%

Appendix-29: Analysis of variance table for mean percent infestation in apple orchard having different intercrops during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 5.625 1.87495 -- Treatment 4 39.092 9.77288 27.76* 0.0000 Error 192 67.585 0.35201 -- Total 199 112.301 * = Significant at α =0.01 CV = 28.44 %

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Appendix-30: Analysis of variance table for mean moth catches in apple orchard having different intercrops during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 38.030 12.6765 -- Treatment 4 39.165 9.7914 12.37* 0.0010 Error 192 151.979 0.7916 -- Total 199 229.174 * = Significant at α =0.01 CV = 31.69 %

Appendix-31: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata in apple orchard having different intercrops during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 2.4999 0.83331 -- Treatment 4 4.7941 1.19854 14.95* 0.0000 Error 192 15.3885 0.08015 -- Total 199 22.6826 * = Significant at α =0.01 CV = 29.15 %

Appendix-32: Analysis of variance table for mean percent arasitism of Hyssopus pallidus in apple orchard having different intercrops during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 0.9041 0.30136 -- Treatment 4 3.1571 0.78927 9.96* 0.0072 Error 192 15.2216 0.07928 -- Total 199 19.2828 * = Significant at α =0.01 CV = 29.22 %

Appendix-33: Analysis of variance table for average yield of apple in kg/tree having different intercrops in apple orchard during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 13.56 4.521 -- Treatment 4 1247.07 311.768 58.37* 0.0000 Error 12 64.10 5.341 -- Total 19 1324.73 * = Significant at α =0.01 CV= 3.54 %

Appendix-34: Combined analysis of variance table for mean fruit drop in apple orchard different intercrops during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 1.271 1.2711 0.64 0.4553 Year*Rep (E) 6 11.980 1.9967 Treatment 4 71.544 17.8859 47.60* 0.0000 Year*Trt 4 0.388 0.0970 0.26 0.9046 Error 384 144.305 0.3758 Total 399 229.488 * = Significant at α =0.01 CV = 30.20%

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Appendix-35: Combined analysis of variance table for mean percent infestation in apple orchard different intercrops during year 2012 & 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 0.14 0.1384 0.00 0.9591 Year*Rep (E) 6 289.1 48.3179 Treatment 4 365.58 91.3941 14.26* 0.0000 Year*Trt 4 8.86 2.2144 0.35 0.8472 Error 384 2461.92 6.4112 Total 399 3126.40 * = Significant at α =0.01 CV = 16.87 %

Appendix-36: Combined analysis of variance table for mean percent parastism of A. quadridentata in apple orchard having different intercrops during year 2012 & 2013.

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 0.00436 0.004 0.00 0.9915 Year*Rep (E) 6 211.423 35.237 Treatment 4 987.051 246.763 42.37* 0.0010 Year*Trt 4 9.49191 2.373 0.41 0.8033 Error 384 2236.57 5.824 Total 399 3444.54 * = Significant at α =0.01 CV = 39.79 %

Appendix-37: Combined analysis of variance table for mean percent parasitism of H. pallidus in apple orchard having different intercrops during year 2012 & 2013.

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 6.53 6.525 0.36 0.5697 Year*Rep (E) 6 108.30 18.050 Treatment 4 519.38 129.845 24.09* 0.0066 Year*Trt 4 5.01 1.252 0.23 0.9201 Error 384 2069.95 5.391 Total 399 2709.17 6.8396 * = Significant at α =0.01 CV = 38.82%

Appendix-38: Combined analysis of variance table for mean moth catches in apple orchard having different intercrops during year 2012 & 2013.

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 6.53 6.525 0.36 0.5697 Year*Rep (E) 6 108.30 18.050 Treatment 4 519.38 129.845 24.09* 0.0000 Year*Trt 4 5.01 1.252 0.23 0.9201 Error 384 2069.95 5.391 Total 399 2709.17 6.8396 * = Significant at α =0.01 CV = 26.04%

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Appendix-39: Combined analysis of variance table for yield (kg/tree) in apple orchard having different intercrops during year 2012 & 2013.

S.O.V. D.F. S.S. M.S. F. Value P-Value Year 1 14.52 14.520 4.33 0.0826 Year*Rep (E) 6 20.11 3.352 Treatment 4 2435.98 608.995 118.18* 0.0000 Year*Trt 4 5.42 1.355 0.26 0.8988 Error 24 123.67 5.153 Total 39 2599.70 * = Significant at α =0.01 CV = 3.11%

Appendix-40: Analysis of variance table for mean fruit drop in apple orchard having different treatments during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 1.731 0.57689 -- Treatment 3 17.657 5.88559 10.83* 0.0003 Error 153 83.129 0.54333 -- Total 159 102.516 * = Significant at α =0.01 CV = 22.64%

Appendix-41: Analysis of variance table for mean percent infestation in apple orchard having different treatments during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 12.624 4.20786 -- Treatment 3 27.052 9.01746 19.55* 0.0000 Error 153 70.558 0.46117 -- Total 159 110.234 * = Significant at α =0.01 CV = 20.87 %

Appendix-42: Analysis of variance table for mean moth catches in apple orchard having different treatments during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 38.943 12.9810 -- Treatment 3 30.659 10.2198 27.77* 0.0002 Error 153 56.313 0.3681 -- Total 159 125.915 * = Significant at α =0.01 CV = 31.62 %

Appendix-43: Analysis of variance table for mean percent parasitism of Ascogestor quadridentata in apple orchard having different treatments during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 5.9626 1.98755 -- Treatment 3 2.0218 0.67393 8.57* 0.0000 Error 153 12.0357 0.07866 -- Total 159 20.0201 * = Significant at α =0.05 CV = 27.41 %

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Appendix-44: Analysis of variance table for mean percent parasitism of Hyssopus pallidus in apple orchard having different treatments during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 2.3988 0.79959 -- Treatment 3 1.6003 0.53343 5.37* 0.0015 Error 153 15.2122 0.09943 -- Total 159 19.2112 * = Significant at α =0.01 CV = 32.04 %

Appendix-45: Analysis of variance table for average yield of apple in kg/tree having different treatments in apple orchard during year 2013

S.O.V. D.F. S.S. M.S. F. Value P-Value Replication 3 4.06 1.354 -- Treatment 3 2897.19 965.729 292.77* 0.0000 Error 9 29.69 3.299 -- Total 15 2930.94 * = Significant at α =0.01 CV= 2.32 %

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