INTERNSHIP REPORT - Pakistan Research Repository

POPULATION DYNAMICS, MOLECULAR CHARACTERIZATION

AND MANAGEMENT OF APPLE CODLING MOTH, 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)

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 CODLING MOTH, 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. Insects and Plants Interaction.......................................................................... 1

1.2. Importance of Apple ....................................................................................... 1

1.3. World Apple Production ................................................................................. 2

1.4. Codling moth as a Serious Pest ....................................................................... 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


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


parameters over a period of time at Madyan during year 2012 ........... 32


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


parameters over a period of time at Kalam during year 2012 ............. 38


parameters over a period of time at Kalam during year 2013 ............. 39


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


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


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


INTERCROPPING .................................................................................. 134


4.4.2. RESULTS .......................................................................................... 137

4.4.3. DISCUSSION .................................................................................... 146

4.4.4. CONCLUSIONS................................................................................ 152


4.5. EXPERIMENT- 3: SYNCHRONIZED COMPARISON OF THE BEST

INSECTICIDE AND INTERCROP ........................................................ 153


4.5.2. RESULTS .......................................................................................... 156

4.5.3. DISCUSSION .................................................................................... 162

4.5.4. CONCLUSIONS................................................................................ 167


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 Bacillus thuringiensis

CM Codling Moth

CpGv Cydia pomonella Granular viruses

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 Insect 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


Madyan during year 2012 & 2013.....................................................................31


over a period of time at Madyan during year 2012...........................................33


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


Kalam during year 2012 & 2013.......................................................................37


over a period of time at Kalam during year 2012..............................................39


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


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


D16....................................................................................................................65


C04.....................................................................................................................66


C13.....................................................................................................................68


B04.....................................................................................................................69


H02....................................................................................................................70


E09.....................................................................................................................71


F01.....................................................................................................................72


A19....................................................................................................................73


D08..................................................................................................................75


G11..................................................................................................................76


F07...................................................................................................................77


E18...................................................................................................................78


H14..................................................................................................................79


B15...................................................................................................................80


C16...................................................................................................................82


C02...................................................................................................................83


H03..................................................................................................................83


F04...................................................................................................................85


H13..................................................................................................................86


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


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


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



Swat by using RAPD primers C-16, C-02 and H-03.......................................84



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

file:///C:/Users/Toshiba/Desktop/Hayat%20PhD%20dissertation,final,17.03.15.docx%23_Toc414891542



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


pomonella at Matta Swat during the year 2013...............................................186


pomonella at Madyan Swat during the year 2012...........................................186


pomonella at Madyan Swat during the year 2013...........................................186


pomonella at Kalam Swat during the year 2012..............................................186


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


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


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



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


intercrops during year 2013.............................................................................191






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


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


treatments during year 2013............................................................................194


different treatments during year 2013.............................................................194


different treatments during year 2013.............................................................194


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


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 35

th 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%.

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 species (Strong et al.,

1984). Plants and plant feeding herbivores are considered to largely account for the

present natural diversity of plants and animals 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

human population to 10 billion by the year 2050, insects may have increased

significance (Schoonhoven et al., 2005).

An arthropod is determined as a pest when it interferes with humans for the

same resources (Pedigo, 2006). Particularly this is most noticeable in agricultural

production systems where arthropods cause serious economic losses (Pimentel, 1997).

The term pest is sometimes not only constricted to arthropods, but also to plant

parasitic nematodes, 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 35

0

55' of latitude North and 720 08' to 72

0 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, peach, 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

2

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

Malus domestica Borkh. (Luby, 2003). Apples are members of the genus 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, Malus sieversii (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

3

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, peaches 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 moths 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

4

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

5

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.

6

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 (Falcon

and Huber, 1991).

7

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 spiders,

mites, birds, insects and particularly the parasitoids are very effective for the

management of this pest (i.e. parasitic wasps from the families Braconidae and

Ichneumonidae) (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, soybean, 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

organisms Hence, intercropping the apple orchard with aromatic plants led to

8

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:

9

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.

10

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diversification an overview. Pestic. Sci.42: 65-68.

Timm, A.E., H. Geertsema and L. Warnich. 2006. Gene flow among Cydia pomonella

(Lepidoptera: Tortricidae) geographic and host populations in South Africa. J.

Econ. Entomol. 99 (2): 341-348.

Vandermeer, J.H. 1989. The ecology of intercropping. Cambridge University Press, ISBN

9780521346894, Cambridge. pp. 237.

Zhou, Y., H. Gu and S. Dorn. 2005. Isolation of microsatellite loci in the codling moth,

Cydia pomonella (Lepidoptera: Tortricidae). Mol. Ecol. Notes 5: 226-227.

15

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

16

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.

17

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 spider 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 spider mite.

The effect of weather parameters were studies on the population dynamics of leaf

hopper on four cultivars of maize crop (Sultan, Sadaf, Neelam and Akbar) and the results

revealed that highest population was noticed when the temperature was 36.5 o

C 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

18

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 tomato fruit borer

Helicoverpa armigera (Hubner), okra shoot and fruit borer Earias insulana Boisduval, Brinjal

Shoot and fruit borer (BSFB) Leucinodes orbonalis Guenee, Potato 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

19

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

20

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 thrips 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).

21

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 72

0 08' to 72

0 50' of longitude East in the North West of

Khyber Pakhtunkhwa) i.e., Matta (350 55' 19.11" of latitude North and 72

0 30' 37.52" of

longitude East), Madyan (350 08' 0.00" of latitude North and 72

0 32' 0.00" of longitude East)

and Kalam (350 28' 41.66" of latitude North and 72

0 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

22

The data regarding adult moth catches were taken with respect to the Standard

meteorological week (SMW) which starts from 1st January - 07

th 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).

23

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

24

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 32

nd 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.

25

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

SMW1

2012 2013

Mean Catches

±SE Temp range (

0C)

R.H%

(0300Z)2

R.H%

(1200Z)3

Total R.F4

(mm)

Mean Catches

+SE

Temp range

(0C)

R.H%

(0300Z)

R.H%

(1200Z)

Total R.F

(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

26

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

0

2

4

6

8

10

12

14

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

Pop

ula

tion

/tra

p

Standard Meteriological Weeks (SMW)

Matta

Madyan

Kalam

27

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

(0C)

-0.541 0.906 0.767 0.559 0.493 0.787 0.799*

Mean min temp

(0C)

0.323 0.480 0.925 0.221 0.037 0.335 0.448*

Mean R.H.

(%) (0300Z)

0.467 -0.384 -0.888 -0.546 0.007 -0.385 -0.462*

Mean R.H.

(%) (1200Z)

0.846 -0.529 -0.841 -0.421 -0.269 -0.298 -0.427*

Total rainfall

(mm)

0.536 0.626 -0.572 0.327 0.885 -0.807 -0.002

* = Significant at 5% level of probability

28



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

29

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



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


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)

30

(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.

31

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

SMW1

2012 2013

Mean

Catches±SE

Temp range

(0C)

R.H%

(0300Z)2

R.H%

(1200Z) 3

Total R.F

(mm) 4

Mean

Catches±SE

Temp range

(0C)

R.H%

(0300Z)

R.H%

(1200Z)

Total RF

(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

32


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)

33

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.




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 1% level of probability


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 =

34

-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.




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



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)

35

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



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%


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


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

36

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.

37

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

SMW1

2012 2013

Mean

Catches±SE

Temp range

(0C)

R.H%

(0300Z)2

R.H%

(1200Z) 3

Total R.F

(mm) 4

Mean

Catches±SE

Temp range

(0C)

R.H%

(0300Z)

R.H%

(1200Z)

Total RF

(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

38


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.

39

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.


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**





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)

40

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).

41


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*




Table-2.13: Multiple regression equations for C. pomonella population at Kalam



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)


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


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%

42

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.

43


parameters over a period of time in Swat during year 2012 and 2013

Weather

Correlation coefficient for C. pomonella population

Matta Madyan Kalam

2012 2013 2012 2013 2012 2013

Max temp

(0C)

0.799* 0.795* 0.857** 0.824** 0.859** 0.881**

Min temp

(0C)

0.448* 0.423* 0.739** 0.755** 0.672** 0.686**

Mean R.H

(%)(0300Z) -0.462* -0.284

NS -0.197

NS 0.125

NS -0.287

NS -0.488

NS

Mean R. H

(%) (1200Z) -0.427* -0.244

NS -0.021

NS 0.122

NS -0.346

NS -0.363

NS

Total R.F.

(mm) -0.002

NS -0.227

NS -0.441* -0.239

NS -0.629** -0.432*




44

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 32

nd 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)

45

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

46

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 (R

2) percent of total variation in the population of C. pomonella at Matta,

72.34 (R2) and 83.42 (R

2) percent at Madyan and 77.36 (R

2) and 83.24 (R

2) 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.

47

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).

48

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.

49

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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.

Tora, R., J. Sio, M.J. Sarasua and J. Avilla. 1995. Control integrado de plagas en

huertos d manzanoy de peral en Cataluna. Frut. Prof. 70: 36-51.

Wong, T.Y. 1971. Populations of codling moths on Washington Island, Wisconsin, in

1970. 1. Econ. Entomol. 64: 1410-1411.

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.

52

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).

53

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.

54

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).

55

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 wheat 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.

56


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

57

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.

58

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.

59

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

60

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.

61

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 72

0 32' 0.00" of longitude East) (1333.84

meters) and Kalam (350 28' 41.66" of latitude North and 72

0 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.

62

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 72

0C, was followed by final extension of 10 min at 72

oC.

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.

63

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

64

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

(bp)

Gene Frequency

(f)

Gene Diversity

(I)

S.I.I* (h)

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.

65

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).


RAPD primer D16

Allele Allele Size (bp) Gene Frequency

(f)

Gene Diversity (I) S.I.I* (h)

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


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.

66

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).


RAPD primer C04

Allele Allele Size

(bp)

Gene Frequency

(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


67

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).

68


RAPD primer C13

Allele Allele Size

(bp)

Gene Frequency

(f)

Gene Diversity (I) S.I.I*(h)

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


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).

69


RAPD primer B04

Allele Allele Size

(bp)

Gene Frequency

(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


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.

70


RAPD primer H02

Allele Allele Size

(bp)

Gene Frequency

(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



C-13, B-04 and H-2.

71

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.


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.


RAPD primer E09

Allele Allele Size

(bp)

Gene Frequency (f) Gene Diversity

(I)

S.I.I* (h)

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

72

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.


RAPD primer F01

Allele Allele Size

(bp)

Gene Frequency

(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


73

3.4.9. Primer A19

The results showed in Table-3.10. disclosed that a total of 10 detectable


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.


RAPD primer A19

Allele Allele Size

(bp)

Gene Frequency

(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


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

74

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



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


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.


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

75

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.


RAPD primer D08

Allele Allele Size

(bp)

Gene Frequency

(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


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.


pomonella at each allele disclosed that the maximum diversity was observed for all

76

the alleles (I = 0.445) whilst the rest of the alleles i.e., 4, 5 and 6 were zero gene


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.


RAPD primer G11

Allele Allele Size

(bp)

Gene

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


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.

77


RAPD primer F07

Allele Allele Size

(bp)

Gene Frequency

(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


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


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


D-08, G-11 and F-07.

78

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.


RAPD primer E18

Allele Allele Size

(bp)

Gene Frequency

(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


79

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.


RAPD primer H14

Allele Allele Size

(bp)

Gene

Frequency (f)

Gene Diversity

(I)

S.I.I* (h)

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


80

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.


RAPD primer B15

Allele Allele Size

(bp)

Gene

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


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.


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

81

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.


pomonella at each allele of the primers illustrated that the maximum diversity was

82

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.


RAPD primer C16

Allele Allele Size

(bp)

Gene Frequency

(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


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

83

for all alleles (h=0.637) except alleles 1 and 2 having zero information by using

RAPD primer C-02.


RAPD primer C02

Allele Allele Size

(bp)

Gene Frequency

(f)

Gene Diversity (I) S.I.I1 (h)

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


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.


RAPD primer H03

Allele Allele Size

(bp)

Gene Frequency

(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

84

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.



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.

85

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.


RAPD primer F04

Allele Allele Size

(bp)

Gene Frequency

(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


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.

86


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.


RAPD primer H13

Allele Allele Size

(bp)

Gene

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


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).

87


RAPD primer G02

Allele Allele Size

(bp)

Gene Frequency

(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


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).

88



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 ........

89

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

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.

90

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.

91

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

used

Total Alleles

Amplified

Range of Allele size

(bp)

G. F (f)1 G. D (I)

2 S. I. I. (h)

3

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) .

92

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

93

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

94

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

95

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.

96

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


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.

97

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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 Streptomyces 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, beetles, 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 beetle predators and utilization of European corn borer 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 flowering plant 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

107

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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4.2.1. 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.

109

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

hoverflies 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

110

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, fennel Foeniculum vulgare (Apiaceae),

111

Fagopyrum esculentum (Polygonaceae), white mustard Sinapis alba (Brassicaceae),

yarrow Achillea millefolium (Asteraceae), buckwheat and fenugreek Trigonella foenum-

graecum (Fabaceae). 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 Trifolium repens 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.

112

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 wasp 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-

113

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.

114


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).

115

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

116

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.

117

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

Ingredients

Class Dosage

(per 200 L ha-1

)

Match® 50 % EC Lufenuron IGR 200 ml

Madex® 3x10

13 viruses/ litre C. pomonella

granulovirus

Granulovirus 50-100 ml

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

118

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

119

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,

120

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 (%)


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

*


* 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

121

(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).

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.

0

5

10

15

20

25

30

35

40

Match Madex Delegate Assail Timer Control

Me

an p

erc

en

t p

aras

itis

m (

%)

Chemical insecticides

AQ

Hp

122

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 (%)


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)

Interaction Y * T

9.84

NS

9.58 6.85


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

123

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

Treatments Percent Parasitism (%)

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)

Interaction Y x T 12.61

*

10.55

8.20

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.

124

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

Treatments Biological Efficacy (%)


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

125

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


Treatments

Mean yield (kg/tree) ± SE Gain in yield

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)

Interaction Y x T

3.76

*

4.66

2.87

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

126

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).

127

4.3.3. DISCUSSION


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 virus

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

130

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

131

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.

132

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


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.

134


INTERCROPPING


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 Brassica 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:


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).


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:


Total No, of overwintering larvae in corrugated bands

135


The effect of these different intercrops were also evaluated on another associated


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




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.

136


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


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

138

(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


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.

Cropping system

Mean Dropped

Mean Year 2012 Year 2013

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)

Interaction Y* T

1.34

NS

1.30

0.93

139

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


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

Cropping system Percent Infestation (%)


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)

Interaction Y * T

12.88

NS

11.71

8.67

140

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.

141

Table-4.11: Mean C. pomonella catches in apple orchard having different intercrops


Cropping system Mean C. pomonella Catches


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)

Interaction Y * T

1.38

NS

1.70

1.09


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

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

Cropping system Percent Parasitism (%)


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)

Interaction Y x T

9.92

NS

8.36

6.80

143

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

Means sharing similar letter(s) in a column are not significantly different by Fischer's LSD test at α = 0.05,

NS: Non-Significant

Cropping system Percent Parasitism (%)


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)

Interaction Y * T

8.61

NS

8.59

6.07

144


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

Cropping System Mean Yield (kg/tree) ±SE Avoidable

losses (%)

Gain

(%) Year 2012 Year 2013 Mean

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)

Interaction Y * T

5.03

NS

5.21

2.34

--

--

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.

146

4.4.3. DISCUSSION


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 citrus 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.


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

147

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, rye and barley 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.

149

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.

150

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

151

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.

152

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.



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.

153

4.5. EXPERIMENT- 3: SYNCHRONIZED COMPARISON OF THE BEST

INSECTICIDE AND INTERCROP


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:


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).

154


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:


Total No, of overwintering larvae in corrugated bands


The effect of intercrops and IGR was also evaluated on another associated


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




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.

155

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)


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

156

4.5.2. RESULTS


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


Data in the parenthesis are square root transformed (√0.5+X).


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

157

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

Treatments

Mean Infestation Percent Infestation

(%)

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




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.

158

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



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

Treatments

Mean Population of A.

quadridentata

Percent parasitism

(%)

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



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

159

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

Treatments Mean population of H.

pallidus

Percent Parasitism

(%)

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.


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,

160

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).


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

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

Treatments

Mean yield (kg/tree)

(±SE)

Avoidable loss in yield

(%)

Gain in yield

(%)

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 --- ---

161

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.

162

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

163

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.


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

164

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).

165


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

166

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.

167

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.

168



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.

169

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 35

th 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.

170

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.


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


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.

171

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.


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


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.

172

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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).

184

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

185

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.

186

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


C. pomonella at Matta Swat during the year 2013


Regression 5 403.176 80.6351 10.32* 0.0001

Residual 19 148.434 7.8123

Total 24 551.610



C. pomonella at Madyan Swat during the year 2012


Regression 5 269.671 53.9343 20.13* 0.000

Residual 19 53.581 2.6791

Total 24 323.252



C. pomonella at Madyan Swat during the year 2013


Regression 5 199.953 39.9905 9.94* 0.0001

Residual 19 76.462 4.0243

Total 24 276.415



C. pomonella at Kalam Swat during the year 2012


Regression 5 156.280 31.2560 12.98* 0.000

Residual 19 45.735 2.4071

Total 24 202.015


187


C. pomonella at Kalam Swat during the year 2013


Regression 5 167.331 33.4662 18.88* 0.000

Residual 19 33.684 1.7729

Total 24 201.015


Appendix-7: Analysis of variance table for mean fruit drop after insecticides

application during year 2012


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


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 %


quadridentata after insecticides application during year 2012


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


Appendix-10: Analysis of variance table for mean percent parasitism of Hyssopus

pallidus after insecticides application during year 2012


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%

188




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


Appendix-12: Analysis of variance table for mean fruit drop after insecticides

application during year 2013


Replication 3 2.0857 0.69523 --

Treatment 5 38.8046 7.76093 30.71* 0.0000

Error 231 58.3758 --

Total 239 99.2661


Appendix-13: Analysis of variance table for mean fruit infestation after



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



quadridentata after insecticides application during year 2013


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



pallidus after insecticides application during year 2013


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


189




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


Year Year*Rep (E)

1

6

0.192

2.518

0.1916

0.4197

0.46

0.5244

Treatment Year*Trt

Error

5

5

462

66.861

1.132

94.756

13.3721

0.2264

0.2051

65.20*

1.10

0.0000

0.3575

Total 479 165.458


Appendix-18: Combined analysis of variance table for mean percent infestation in

apple orchard after insecticides application during year 2012 & 2013


Year Year*Rep (E)

1

6

0.84

9.696

0.841

1.6160

0.05

0.8271

Treatment Year*Trt

Error

5

5

462

104.538

0.511

108.841

20.9075

0.1021

0.2356

88.75*

0.43

0.0000

0.8252

Total 479 223.669


Appendix-19: Combined analysis of variance for mean percent parasiotism A.

quadridentata in apple orchard after insecticides application during year 2012 &

2013


Year Year*Rep (E)

1

6

0.0032

11.7603

0.00325

1.96005

0.00

0.9689

Treatment Year*Trt

Error

5

5

462

28.8315

0.2004

47.0663

5.76629

0.04007

0.10188

56.60*

0.39

0.0000

0.8534

Total 479 87.8617


190

Appendix-20: Combined analysis of variance table for mean percent parasiotism

H. pallidus in apple orchard after insecticides application during year 2012 & 2013


Year Year*Rep (E)

1

6

0.0131

2.3650

0.01308

0.39417

0.03

0.8641

Treatment Year*Trt

Error

5

5

462

17.9688

0.2882

52.9213

3.59375

0.05765

0.11455

31.37*

0.50

0.0000

0.7738

Total 479 73.5564


Appendix-21: Combined analysis of variance table for average yield of apple in

kg/tree after insecticides application during year 2012 & 2013


Year Year*Rep (E)

1

6

34.17

62.49

34.17

10.41

3.28

0.1200

Treatment Year*Trt

Error

5

5

30

5470.65

137.86

237.20

1094.13

27.57

7.91

138.38*

3.49

0.0000

0.0133

Total 47 5942.37


Appendix-22: Analysis of variance table for mean fruit drop in apple orchard

having different intercrops during year 2012


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


Appendix-23: Analysis of variance table for mean percent infestation in apple

orchard having different intercrops during year 2012


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 *


Appendix-24: Analysis of variance table for mean moth catches in apple orchard



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


191


quadridentata in apple orchard having different intercrops during year 2012


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



pallidus in apple orchard having different intercrops during year 2012


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


Appendix-27: Analysis of variance table for average yield of apple in kg/tree

having different intercrops in apple orchard during year 2012


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





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



orchard having different intercrops during year 2013


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


192




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



quadridentata in apple orchard having different intercrops during year 2013


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


Appendix-32: Analysis of variance table for mean percent arasitism of Hyssopus

pallidus in apple orchard having different intercrops during year 2013


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



having different intercrops in apple orchard during year 2013


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


Appendix-34: Combined analysis of variance table for mean fruit drop in apple

orchard different intercrops during year 2012 & 2013


Year Year*Rep (E)

1

6

1.271

11.980

1.2711

1.9967

0.64

0.4553

Treatment Year*Trt

Error

4

4

384

71.544

0.388

144.305

17.8859

0.0970

0.3758

47.60*

0.26

0.0000

0.9046

Total 399 229.488


193

Appendix-35: Combined analysis of variance table for mean percent infestation in

apple orchard different intercrops during year 2012 & 2013


Year Year*Rep (E)

1

6

0.14

289.1

0.1384

48.3179

0.00 0.9591

Treatment Year*Trt

Error

4

4

384

365.58

8.86

2461.92

91.3941

2.2144

6.4112

14.26*

0.35

0.0000

0.8472

Total 399 3126.40


Appendix-36: Combined analysis of variance table for mean percent parastism of

A. quadridentata in apple orchard having different intercrops during year 2012 &

2013.


Year Year*Rep (E)

1

6

0.00436

211.423

0.004

35.237

0.00 0.9915

Treatment Year*Trt

Error

4

4

384

987.051

9.49191

2236.57

246.763

2.373

5.824

42.37*

0.41

0.0010

0.8033

Total 399 3444.54


Appendix-37: Combined analysis of variance table for mean percent parasitism of

H. pallidus in apple orchard having different intercrops during year 2012 & 2013.


Year Year*Rep (E)

1

6

6.53

108.30

6.525

18.050

0.36 0.5697

Treatment Year*Trt

Error

4

4

384

519.38

5.01

2069.95

129.845

1.252

5.391

24.09*

0.23

0.0066

0.9201

Total 399 2709.17 6.8396


Appendix-38: Combined analysis of variance table for mean moth catches in apple

orchard having different intercrops during year 2012 & 2013.


Year Year*Rep (E)

1

6

6.53

108.30

6.525

18.050

0.36 0.5697

Treatment Year*Trt

Error

4

4

384

519.38

5.01

2069.95

129.845

1.252

5.391

24.09*

0.23

0.0000

0.9201

Total 399 2709.17 6.8396


194

Appendix-39: Combined analysis of variance table for yield (kg/tree) in apple

orchard having different intercrops during year 2012 & 2013.


Year Year*Rep (E)

1

6

14.52

20.11

14.520

3.352

4.33 0.0826

Treatment Year*Trt

Error

4

4

24

2435.98

5.42

123.67

608.995

1.355

5.153

118.18*

0.26

0.0000

0.8988

Total 39 2599.70



having different treatments during year 2013


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



orchard having different treatments during year 2013


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



having different treatments during year 2013


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



quadridentata in apple orchard having different treatments during year 2013


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


195


pallidus in apple orchard having different treatments during year 2013


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



having different treatments in apple orchard during year 2013


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


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INTERNSHIP REPORT - Pakistan Research Repository