STUDIES ON MECHANISMS OF RESISTANCE IN DIFFERENT HOST PLANTS AGAINST COTTON , PHENACOCCUS SOLENOPSIS TINSLEY (: PSEUDOCOCCIDAE)

By

MUHAMMAD RAFIQ SHAHID Reg. No. 2000-ag-1364 M.Sc. (Hons.) Agri. Entomology

A thesis submitted in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY IN ENTOMOLOGY

DEPARTMENT OF ENTOMOLOGY FACULTY OF AGRICULTURE UNIVERSITY OF AGRICULTURE, FAISALABAD (PAKISTAN) 2015

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To, The Controller of Examinations, University of Agriculture, Faisalabad.

We, the Supervisory Committee, certify that the contents and form of thesis submitted by Mr. Muhammad Rafiq Shahid, Regd. No. 2000-ag-1364 have been found satisfactory and recommend that it be processed for evaluation by the external examiner(s) for the award of Ph. D degree.

SUPERVISORY COMMITTEE:

CHAIRMAN: (Prof. Dr. Muhammad Jalal Arif)

MEMBER: (Dr. Muhammad Dildar Gogi)

MEMBER: (Prof. Dr. Nazir Javed)

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In the name of ALLAH The Most Beneficent The Most Merciful

This Humble Effort is Dedicated to

HOLY PROPHET HAZART MUHAMMAD (Peace Be Upon Him)

The Ocean of Knowledge and The greatest reformer,

My Beloved

PARENTS

BROTHERS, SISTERS AND MY WIFE

Their hands always rose in prayer for me and are forever with me to feel the bud of their wishes and prayers, Blooming into a flower.

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DECLARATION

I hereby declare that the contents of the thesis” Studies on mechanisms of resistance in different host plants against cotton mealybug, Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) are product of my own research and no part has been copied from any published source (except the references, standard mathematic or genetic models/equations/protocoals etc.). I further declare that same work has not been submitted for award of any other diploma/degree. The University may take action if the information provided is found inaccurate at any stage (in case of any default the scholar will be proceeded as against as per HEC plagiarism policy).

MUHAMMAD RAFIQ SHAHID (2000-ag-1364)

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ACKNOWLEDGMENT

First of all I would like to bow my head before “ALMIGHTY ALLAH” the Gracious, the Merciful, the Beneficial Who presented me in a Muslim community and also bestowed and blessed me with such a lucid intelligence as I could endeavor my services towards this manuscript. Countless salutations are upon the HOLY PROPHET MOHAMMAD (Peace Be Upon Him), the fountains of knowledge, who has guided his “Ummah” to seek knowledge from cradle to grave.

This work was made possible by a mealybug Project funded from the Higher Education Commission of Pakistan. I had served as senior Research Associate in that project. I am extremely delighted to convey my deepest sense of gratitude to Principal investigator of the project and my supervisor, Dr. Muhammad Jalal Arif, Professor and Chairman at Department of Entomology, University of Agriculture, Faisalabad (UAF) for his masterly pieces of advice, inspiring attitude, kind cooperation, dexterous guidance, constructive criticism and valuable suggestions in the completion of this research work and compilation of thesis treatise. I am also obliged and pledged for all the enthuastic and sincre efforts of Prof. Dr. Muhammad Jalal Arif extended for the provision of required inputs, personnels and scholarly reasoning from experimental layout to writeup of thesis.

I am also highly obliged to supervisory Committee especially Dr. Muhammad Dildar Gogi, (Assistant Professor) for his technical and moral guidance and suggestions throughout my study period. I also extend my sincere thanks to Dr. Nazir Javed, for his cooperation in completion of this manuscript. I am thankful to Dr. Yasin Ashraf, Principal Scientific Officer at NIAB and Mr. Allah Nawaz, ARO at Ayub Research Institute, they both helped me in plant analysis. I also oblige the expertise of Dr. Muhammad Sufian (Assistant Professor, Entomology, Ph. D Germany), Dr. Fatima Mustafa, Dr. Ahmad Nawaz and Dr. Kashif Riaz (Plant Pathology, UAF) for reviewing my thesis.

The moral support of my mother and father Mr. Allah Ditta (Rtd. Senior Head Master High School) is also acknowledged who always appreciated and prayed for my success. I am also thankful to my wife Memoona Aziz, my children Muhammad Osaid Shahid and Muhammad Ashhad Malik, my other blood related members Muhammad Zahid, Dr. Amir Shafiq, Saif Ullah, Sanwal and Awais who had to suffer the absence of the care and affection they deserved during my absence from home.

MUHAMMAD RAFIQ SHAHID

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CONTENTS

CHAPTER NO. TITLE PAGE

1 INTRODUCTION 1

2 REVIEW OF LITERATURE 6

3 OBJECTIVE -1 20

4 OBJECTIVE -2(a,b) 40,67

5 OBJECTIVE -3 101

6 OBJECTIVE -4 158

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TABLE OF CONTENTS CH. # TITLE Page No. DECLARATION iv ACKNOWLEDGEMENT v LIST OF FIGURES xi LIST OF TABLES xviii ABSTRACT xx SUMMARY xxi 1 Chapter 1: INTRODUCTION 1 2 Chapter 2: REVIEW OF LITERATURE 2.1 Economic importance of Phenacoccus solenopsis 6 2.2 Geographical distribution of P. solenopsis 6 2.3 Population dynamics of P. solenopsis 6 2.4 Polyphagous feeding and invasive nature 7 2.5 Nature of damage of P. solenopsis 8 2.6 Life history parameters 8 2.7 Host plants of mealybug in Pakistan 8 Drawbacks of chemical control for the management of P. 2.8 9 solenopsis 2.9 Importance of host plant resistance 9 2.10 Mechanisms of resistance 10 2.11 Antixenosis mechanism 12 2.12 Antibiosis mechanism 13 2.13 Tolerance mechanism 16 2.14 Effect of plant resistance on P. solenopsis 17

3 CHAPTER 3 20 Determination of natural incidence of P. solenopsis on different 3.1 host plants under cotton and central mixed zone of Punjab, 20 Pakistan Percentage infestation of cotton mealybug on the tested host 3.2 25 plants 3.3 Population of cotton mealybug on the tested host plants 26 Instar wise proportion of mealybug among selected plant 3.4 27 species Categorizing cultivated host plants of cotton mealybug into 3.5 30 incidental and susceptible hosts Categorizing uncultivated host plants of mealybug into 3.6 30 incidental and susceptible hosts District wise infestation and population of mealybug on 3.7 31 different plant species Infestation of cotton mealybug on the tested host plants in 3.8 31 selected districts 3.9 Population of cotton mealybug on the tested host plants 32 Seasonal population dynamics of mealybug on selected plant 3.10 33 species 3.11 Cluster analysis among plant species on the basis of mealybug 36

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population and infestation 3.12 Principal component analysis 37 4 CHAPTER 4 40 Assessment of antixenosis mechanisms of resistance in 4.1 40 different plant species for P. solenopsis Physico-morphic based antixenosis mechanism of resistance in 4.1.1 40 selected host plants for P. solenopsis 4.1.2 Colony culture of cotton mealybug 42 4.1.3 Plant material 42 Determination of attractiveness index of different instars of P. 4.1.4 42 solenopsis 4.1.5 Determining physic-morphic traits of selected plant species 44 4.1.6 Thickness of leaf lamina (µm) 44 4.1.7 Leaf area (cm2) 45 4.1.8 Trichome density and trichome length (µm) 45 Attractive index of first instar of P. solenopsis for different 4.1.9 46 plant species at 2, 4 and 8 hours post-release intervals Attractive index of second instar of P. solenopsis for different 4.1.10 48 plant species at 2, 4 and 8 hours post-release intervals Attractive index of third instar of P. solenopsis for different 4.1.11 50 plant species at 2, 4 and 8 hours post-release intervals 4.1.12 Morphological plant Characters 53 Trichome density and its association with attractiveness index 4.1.13 53 of P. solenopsis Trichome length in tested plant species and its association with 4.1.14 56 attractiveness index of mealybug Leaf area of tested plant species and its association with 4.1.15 59 attractiveness of mealybug Leaf thickness of selected plant species and its association with 4.1.16 61 attractiveness index of mealybug 4.1.17 Cluster analysis among studied traits 63 4.1.18 Principal component analysis 66 Biochemical based antixenosis mechanism of resistance in 4.2 67 different host plants against cotton mealybug Determination of Biochemical factors/ Antibiotic factors in 4.2.1 69 leaves of selected plant species Biochemical leaf traits of host plants, attractiveness index of P. 4.2.2 75 solenopsis and their nature of association Phosphorus contents and its association with attractiveness 4.2.3 75 index of P. solenopsis Potassium contents and its association with attractiveness index 4.2.4 78 of P. solenopsis Nitrogen contents and its association with attractiveness index 4.2.5 80 of P. Sodium contents and its association with attractiveness index of 4.2.6 82 P. solenopsis Total soluble sugar percentage and its association with 4.2.7 85 attractiveness index of P. solenopsis 4.2.8 Reducing sugar percentage and its association with 87

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attractiveness index of P. solenopsis Crude protein contents and its association with attractiveness 4.2.9 89 index of P. solenopsis Chlorophyll concentration percentage and its association with 4.2.10 91 attractiveness index of P. solenopsis 4.2.11 Cluster analysis among studied traits 93 4.2.12 Principal component analysis 94

5 CHAPTER 5 101 Determination of antibiosis mechanism of resistance in selected 5.1 101 plant species for P. solenopsis 5.1.1 Plant species 103 5.1.2 Maintenance of mealybug colony 103

5.1.3 Experimental layout for determining the antibiosis mechanism 103 of resistance in different host plants 5.1.4 Determining Biochemical traits of selected plants 104 5.2 Effect of plant species on life parameters of P. solenopsis 105 Effect of plant species on the longevity of 1st, 2nd and 3rd instar 5.2.1 105 nymphs of P. solenopsis Effect of plant species on the mortality of 1st, 2nd and 3rd instar 5.2.2 107 nymphs of P. solenopsis Effect of different plant species on some biological parameters 5.2.3 109 of female P. solenopsis Biochemical contents and its association with biological 5.3 110 parameters of P. solenopsis Association of phosphorus contents of plant species with 5.3.1 112 various biological parameters of P. solenopsis Association of potassium contents of plant species with various 5.3.2 117 biological parameters of P. solenopsis Association of nitrogen contents of plant species with various 5.3.3 120 biological parameters of P. solenopsis Association of crude protein contents of plant species with 5.3.4 125 various biological parameters of P. solenopsis Association of total soluble sugar contents of plant species with 5.3.5 130 various biological parameters of P. solenopsis Association of reducing sugar contents of plant species with 5.3.6 135 various biological parameters of P. solenopsis Association of sodium percentage of plant species with various 5.3.7 140 biological parameters of P. solenopsis Association of chlorophyll contents of plant species with 5.3.8 145 various biological parameters of P. solenopsis 5.3.9 Cluster analysis among studied traits 150 5.3.10 Principal component analysis 150 6 CHAPTER 6 158 Determination of tolerance mechanism of resistance in host 6.1 158 plant of P. solenopsis 6.1.1 Establishment of mealybug culture and experimental detail 160

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6.1.2 Determination of tolerance level 160 6.1.3 Biochemical analysis of plant species 161 Tolerance percentage in different plant species toward P. 6.1.4 161 solenopsis Biochemical changes in plants in response to different densities 6.2 162 of P. solenopsis Effect of different densities of P. solenopsis on nitrogen 6.2.1 163 contents of plant species Effect of different densities of P. solenopsis on phosphorus 6.2.2 164 contents of plant species Effect of different densities of P. solenopsis on potassium 6.2.3 165 contents of plant species Effect of different densities of P. solenopsis on crude protein 6.2.4 166 contents of plant species Effect of different densities of P. solenopsis on sodium contents 6.2.5 167 of plant species Effect of different densities of P. solenopsis on chlorophyll 6.2.6 168 contents of plant species Effect of different densities of P. solenopsis on total soluble 6.2.7 169 sugar contents of plant species Association between mealybug density and biochemical 6.2.8 170 contents of the selected plant species 6.2.9 Cluster analysis among studied traits 174 6.2.10 Principal component analysis 175 LITERATURE CITED 179

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LIST OF FIGURE

Sr. No Title Page # Geographic location of studied districts in the Map of Pakistan and plate 3.1.1 23 showing the studied area Mealybug infestation (%±SE) among selected plant species. Standard error 3.2.1. bars above indicate significant differences (Tukey HSD test; P<0.05) in 26 mealybug infestation among plant species Mealybug population (n±SE=mealybug i.e., number±standard error) 3.2.2 among selected plant species. Bars above indicate significant differences 27 (Tukey HSD test; P<0.05) in mealybug popution among plant species Instar wise mealybug population (n±SE) among selected plant species. 3.2.3 Standard error bars above indicate significant differences (Tukey HSD test; 29 P<0.05) in mealybug population among plant species Month wise average mealybug population (n±SE) and mealybug 3.2.4 30 supporting period by tested plant species (cultivated) Month wise average mealybug population (n±SE) and mealybug 3.2.5 31 supporting period by tested plant species (un-cultivated) Mealybug infestation (%±SE) in selected districts. Bars above indicate 3.2.6 32 significant differences (Tukey HSD test; P<0.05) in mealybug infestation Mealybug population (n±SE) in selected districts. Bars above indicate 3.2.7 33 significant differences (Tukey HSD test; P<0.05) in mealybug population 3.2.8 Seasonal occurrence of mealybug population on selected plant species 36 Cluster diagram of the selected plant species on the basis of infestation and 3.2.9 37 population of mealybug 4.1.1 Host preference wheel 44 Attractive index (means±SE) of first instar of P. solenopsis for different 4.2.1 47 plant species at 2 hours post-release interval Attractive index (means±SE) of first instar of P. solenopsis for different 4.2.2 47 plant species at 4 hours post-release interval Attractive index (means±SE) of first instar of P. solenopsis for different 4.2.3 48 plant species at 8 hours post-release interval Attractive index (means±SE) of second instar of P. solenopsis for different 4.2.4 49 plant species at 2 hours post-release interval Attractive index (means±SE) of second instar of P. solenopsis for different 4.2.5 50 plant species at 4 hours post-release interval Attractive index (means±SE) of second instar of P. solenopsis at 8 hours 4.2.6 50 after release for different plant species Attractive index (means±SE) of third instar of P. solenopsis at 2 hours after 4.2.7 52 release for different plant species Attractive index (means±SE) of third instar of P. solenopsis at 4 hours after 4.2.8 52 release for different plant species Attractive index (means±SE) of third instar of P. solenopsis at 8 hours after 4.2.9 53 release for different plant species 4.2.10 Trichome density of tested plant species for P. solenopsis 54

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Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.11 (r) and scatter diagram showing the fitted simple regression line of Ŷ 55 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Trichome density/cm2) 4.2.12 Trichome length of tested plant species for P. solenopsis 57 Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation 4.2.13 (r) and scatter diagram showing the fitted simple regression line of Ŷ 58 (attractiveness index of first (D), second (E) and third instar (F) nymphs of P. solenopsis) on X (Trichome length µm ) 4.2.14 Leaf area of tested plant species for P. solenopsis 59 Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.15 (r) and scatter diagram showing the fitted simple regression line of Ŷ 60 (attractiveness index of first (G), second (H) and third instar (I) nymphs of P. solenopsis) on X (Leaf area cm2) 4.2.16 Leaf thickness of tested plant species for P. solenopsis 62 Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.17 (r) and scatter diagram showing the fitted simple regression line of Ŷ 63 (attractiveness index of first (J), second (K) and third instar (L) nymphs of P. solenopsis) on X (Leaf thickness µm) Cluster analysis regarding similarity between morphological traits versus 4.3 64 attractiveness index of P. solenopsis 4.2.18 Phosphorus (%) of tested plant species for P. solenopsis 76 Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.19 (r) and scatter diagram showing the fitted simple regression line of Ŷ 77 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Phosphorus %) 4.2.20 Potassium (%) of tested plant species for P. solenopsis 79 Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.21 (r) and scatter diagram showing the fitted simple regression line of Ŷ 80 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Potassium %) 4.2.22 Nitrogen (%) of tested plant species for P. solenopsis 81 Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.23 (r) and scatter diagram showing the fitted simple regression line of Ŷ 82 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Nitrogen %) 4.2.24 Sodium (%) of tested plant species for P. solenopsis 83

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Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.25 (r) and scatter diagram showing the fitted simple regression line of Ŷ 84 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (sodium %) 4.2.26 Total soluble sugar (%) of tested plant species for P. solenopsis 85 Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 4.2.27 (r) and scatter diagram showing the fitted simple regression line of Ŷ 86 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Total soluble sugar %) 4.2.28 Reducing sugar (%) of tested plant species for P. solenopsis 88 Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation 4.2.29 (r) and scatter diagram showing the fitted simple regression line of Ŷ 89 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Reducing sugar %) 4.2.30 Crude protein (%) of tested plant species for P. solenopsis 90 Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation 4.2.31 (r) and scatter diagram showing the fitted simple regression line of Ŷ 91 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Crude protein %) 4.2.32 Chlorophyll content (mg/gm) of tested plant species for P. solenopsis 92 Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation 4.2.33 (r) and scatter diagram showing the fitted simple regression line of Ŷ 93 (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Chlorophyll contents %) Cluster analysis regarding similarity between biochemical traits versus 4.4 95 attractiveness index of P. solenopsis 5.2.1. Nymphal duration of first instar of P. solenopsis among tested plant species 106 Nymphal duration of second instar of P. solenopsis among tested plant 5.2.2 106 species Nymphal duration of third instar of P. solenopsis among tested plant 5.2.3 107 species Mortality percentage of first instar of P. solenopsis among tested plant 5.2.4 108 species Mortality percentage of second instar of P. solenopsis among tested plant 5.2.5 108 species Mortality percentage of third instar of P. solenopsis female among tested 5.2.6 109 plant species 5.2.7 Pre-oviposition period of P. solenopsis female among tested plant species 110 5.2.8 Oviposition period of P. solenopsis female among tested plant species 110 5.2.9 Crawler density of P. solenopsis among tested plant species 111

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Coefficient of determination (R²), linear regression equation, various regression parameters (df, F values and P values), coefficient of correlation 5.2.10 (r) and scatter diagram showing the fitted simple regression line of Ŷ (pre- 113 oviposition period of female (A), oviposition (B) and crawlers per ovisac (C) of P. solenopsis) on X (Phosphorus%) Coefficient of determination (R²), linear regression equation, various regression parameters (df, F values and P values), coefficient of correlation 5.2.11 (r) and scatter diagram showing the fitted simple regression line of Ŷ 115 (nymphal mortality of first (D), second (E) and third instars (F) of P. solenopsis) on X (Phosphorus%). Coefficient of determination (R²), linear regression equation, various regression parameters (df, F values and P values), coefficient of correlation 5.2.12 (r) and scatter diagram showing the fitted simple regression line of Ŷ 116 (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Phosphorus%) Coefficient of determination (R²), linear regression equation, various regression parameters (df, F values and P values), coefficient of correlation 5.2.13 (r) and scatter diagram showing the fitted simple regression line of Ŷ (pre- 118 oviposition period of female (A), oviposition (B) and crawlers per ovisac (C) of P. solenopsis) on X (Potassium%) Coefficient of determination (R²), linear regression equation, various regression parameters (df, Fvalues and P values), coefficient of correlation 5.2.14 (r) and scatter diagram showing the fitted simple regression line of Ŷ 119 (nymphal mortality of first (D), second (E) and third instars (F) of P. solenopsis) on X (Potassium%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.15 (r) and scatter diagram showing the fitted simple regression line of Ŷ 121 (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Potassium%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.16 (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre- 122 oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Nitrogen%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.17 (r) and scatter diagram showing the fitted simple regression line of Ŷ 124 (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Nitrogen%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.18 (r) and scatter diagram showing the fitted simple regression line of Ŷ 125 (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Nitrogen%)

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Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.19 (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre- 126 oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Crude protein%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.20 128 diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Crude protein%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.21 129 diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Crude protein%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.22 diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period 131 (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Total soluble sugar%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.23 133 diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Crude protein%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.24 134 diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Total soluble sugar%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.25 diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period 136 (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Reducing sugar%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter 5.2.26 138 diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Reducing sugar%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.27 (r) and scatter diagram showing the fitted simple regression line of Ŷ 139 (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Reducing sugar%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.28 (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre- 141 oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Sodium%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.29 (r) and scatter diagram showing the fitted simple regression line of Ŷ 143 (mortality % of first (A), second (B) and third instar (C) of P. solenopsis) on X (Sodium%)

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Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.30 (r) and scatter diagram showing the fitted simple regression line of Ŷ 144 (Nymphal duration of first (A), second (B) and third instar (C) of P. solenopsis) on X (Sodium%) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.31 (r) and scatter diagram showing the fitted simple regression line of Ŷ (pre- 146 oviposition (A), oviposition duration (B) and crawlers per ovisac (C) of P. solenopsis) on X (Chlorophyll mg/gm) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.32 (r) and scatter diagram showing the fitted simple regression line of Ŷ 148 (Nymphal mortality of first (A), second (B) and third instar (C) of P. solenopsis) on X (Chlorophyll mg/gm) Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation 5.2.33 (r) and scatter diagram showing the fitted simple regression line of Ŷ 149 (Nymphal duration of first (A), second (B) and third instar (C) of P. solenopsis) on X (Chlorophyll mg/gm) Cluster analysis regarding similarity between biochemical traits versus 5.2.34 151 biological paramters of P. solenopsis Effect of different densities of P. solenopsis on tolerance percentage of 6.2.1 162 different plant species Effect of different densities of P. solenopsis on variation in nitrogen 6.2.2 163 concentration in selected plant species Effect of different densities of P. solenopsis on variation in phosphorus 6.2.3 165 concentration in selected plant species Effect of different densities of P. solenopsis on variation in potassium 6.2.4 166 concentration in selected plant species Effect of different densities of P. solenopsis on variation in crude protein 6.2.5 167 concentration in selected plant species Effect of different densities of P. solenopsis on variation in sodium 6.2.6 168 concentration in selected plant species Effect of different densities of P. solenopsis on variation in chlorophyll 6.2.7 169 concentration in selected plant species Effect of different densities of P. solenopsis on variation in total soluble 6.2.8 170 concentration in selected plant species Nature of association between phosphorus contents in plant species and 6.2.9 171 different densities of P. solenopsis Nature of association between nitrogen contents in plant species and 6.2.10 171 different densities of P. solenopsis Nature of association between potassium contents in plant species and 6.2.11 172 different densities of P. solenopsis Nature of association between crude protein contents in plant species and 6.2.12 172 different densities of P. solenopsis Nature of association between sodium contents in plant species and 6.2.13 172 different densities of P. solenopsis

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Nature of association between total soluble sugar contents in plant species 6.2.14 173 and different densities of P. solenopsis Nature of association between reducing sugar contents in plant species and 6.2.15 173 different densities of P. solenopsis Nature of association between chlorophyll contents in plant species and 6.2.16 174 different densities of P. solenopsis Cluster analysis regarding similarity between biochemical traits at different 6.2.17 175 densities of P. solenopsis

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LIST OF TABLES Sr. No Title Page # 1.1 List of plant species selected during study 24 ANOVA parameters regarding infestation level of P. solenopsis on 3.2.1 25 twenty five selected plant species in different districts ANOVA parameters regarding population of P. solenopsis on twenty 3.2.2 27 five selected plant species in different districts Analysis of variance regarding mealybug infestation and population 3.2.3 31 among the selected districts ANOVA parameters for cluster and cluster membership among 3.2.4 infestation and population of P. solenopsis among selected host 37 plants 3.2.5 D2 distance among different clusters 38 Principal component analysis regarding population and infestation of 3.2.6 38 P. solenopsis among selected host plants ANOVA parameters regarding food preference of P. solenopsis at 4.2.1 different intervals toward twenty five selected plant species under 46 multi-choice laboratory experiment Analysis of variance regarding morphological traits of tested plant 4.2.2 53 species toward P. solenopsis ANOVA parameter for cluster and cluster membership among 4.2.3 morphological traits of some host plants toward attractiveness index 65 of P. solenopsis D2 distance among different clusters among morphological traits of 4.2.4. 65 some host plants toward attractiveness index of P. solenopsis Principal component analysis of morphological traits in different 4.2.5. 66 plant species of P. solenopsis ANOVA regarding biochemical contents of leaf and attractiveness 4.2.6. 75 index of P. solenopsis ANOVA parameter for cluster and cluster membership among 4.2.7. biochemical traits of some host plants toward attractiveness index of 96 P. solenopsis D2 distance among different clusters among different clusters among 4.2.8. biochemical traits of some host plants toward attractiveness index of 96 P. solenopsis Principal component analysis of biochemical traits in different plant 4.2.9. 96 species of P. solenopsis ANOVA parameters regarding the effect of twenty five host plant 5.2.1 species (treatments) on the biological parameters of P. solenopsis 105 under laboratory ANOVA parameter for cluster and cluster membership among 5.2.2 biochemical traits of some host plants toward biological parameters 152 of P. solenopsis D2 distance among different clusters among different clusters among 5.2.3 biochemical traits of some host plants toward biological parameters 153 of P. solenopsis

xviii

Principal component analysis of biochemical traits in different plant 5.2.4 153 species of P. solenopsis ANOVA parameters regarding effect of different densities of P. 6.2.1 162 solenopsis on chemical contents of twenty five selected plant species 6.2.2 D2 distance among different clusters 175 Principal component analysis regarding biochemical changes in plant 6.2.3 176 species at different densities of P. solenopsis

xix

ABSTRACT Plants species possess different morphological and biochemical properties, which resultantly induce in them different mechanisms of resistance. Present studies were carried out to investigate the mechanism of resistance in different host plants against Phenacoccus solenopsis. The results revealed a significant variation in tested plant species for percentage infestation and population of P. solenopsis. On the basis of field data, Digeria arvensis, Launea nudicaulis and Conyza bonariensis plants were ranked as incidental host plant species of P. solenopsis as they supported mealybug for < 3 months. The resuls of physico-morphic based antixenosis study revealed that attractiveness of first, second and third instars of P. solenopsis had positive correlation with trichome density (r= 0.56, 0.65, 0.41), trichome length (r= 0.26, 0.30, 0.33), leaf area (r=0.38, 0.44, 0.26) and leaf thickness (0.50, 0.57, 0.50). The resuls of biochemical based antixenosis also demonstrated association between attractiveness of first, second and third instar nymphs of P. solenopsis with phosphorus (r=0.05, 0.27 and 0.03), potassium (r= 0.03, 0.27, 0.03), nitrogen (r= 0.12, 0.07, 0.12), sodium (r= 0.21, 0.47, 0.27), total soluble sugar (r= 0.01, -0.12, 0.06), reducing sugar (r= 0.10, 0.1, 0.06), crude protein (r= 0.12, 0.07, 0.12) and chlorophyll (r= 0.29, 0.36,0.12) contents, respectively. The results of biochemical based antibiosis revealed that phosphorus, potassium and sodium had positive association with nymphal mortality, nymphal durations, pre- oviposition and oviposition periods of the female but had negative association with crawlers density. Nitrogen, total soluble sugar, chlorophyll and crude protein had positive association with crawler density but negative with nymphal duration, nymphal mortality and reproductive periods. Sodium had negative association with crawler density. Coefficient of determination values (R2) exhibited that phosphorus explained 27.5, 29.3, 49.3, 27.78, 31.6, 33.9, 45.2, 52.9 and 68.8%; potassium demonstrated 21.7, 30.8, 11.3, 21.3, 26.4, 24.1, 14.6, 7.5 and 18.07%; nitrogen attributed 8.2, 9.6, 9.1, 2.5, 4.9, 4.4, 6.5, 0.15 and 17.38%; crude protein contributed 8.2, 9.6, 9.1, 2.5, 4.9, 4.4, 6.5, 0.1 and 17.3%; total soluble sugar explained 27.8, 7.9, 8.6, 26.0, 12.8, 17.34, 8.8, 20.4 and 25.4%; reducing sugar described 0.01, 0.3, 3.18, 0.1, 1.2, 0.2, 1.68, 1.37 and 1.48%; sodium demonstrated 31.4, 22.2, 39.2, 25.2, 37.2, 38.0, 52.3, 30.4, 33.6% and chlorophyll attribiuted 12.0, 12.0, 4.4, 7.9, 5.96, 10.0, 0.3, 2.3 and 1.8% of total variation in preoviposition- period, oviposition-period, crawlers/ovisac, mortality of 1st, 2nd and 3rd instars and nymphal duration of 1st, 2nd and 3rd instars, respectively. The results of biochemical based tolerance mechanisms exhibited that nitrogen, crude protein, sodium, total soluble sugar and chlorophyll were negatively correlated with mealybug density, but phosphorus, reducing sugar and potassium were positively correlated. The tolerance level was affected at higher density (100 CMB/plant). As a tolerance mechanism, plants exhibited reduction in nitrogen, crude protein sodium, total soluble sugar and chlorophyll contents while demonstrated an increase in phosphorous, reducing sugar and potassium contents when infested with different densties of P. solenopsis.The pairwise Mahalanobis distances among three clusters established for 25 plant species revealed that members of cluster-2 demonstrated the maximum diversity against cluster-1 for infestation and population incidence of P. solenopsis (D2=96.0) and for antixenosis and morphological traits (D2=208.9). Cluster-2 established maximum diversity against cluster-3 for antixenosis and biochemical traits (D2=25.3). Cluster-1 expressed the maximum diversity against cluster-3 for antibiosis and biochemical traits (D2=55.2) and against cluster-2 for tolerance and biochemical traits (D2=18). The results of Principal components (PCs) explained that 82% of the total variability in infestation and population of P. solenopsis and 55.2% of the total variability in antibiosis and biochemical traits of the selected plant species were explained by PC1. The results also revealed that 73% of the total variability in antixenosis and morphological traits and 99% of the total variability for tolerance and biochemical traits of the selected plant species was explained by PC1 and PC2 commutatively. On the basis of antixenosis, antibiosis and tolerance mechanism of resistance, it was observed that D. arvensis plant exhibited resistance due to provision of different morphological and biochemical traits against P. solenopsis.

xx

SUMMARY

Cotton mealybug (CMB), P. solenopsis Tinsley (Hemiptera: Pseudococcidae) is an important sucking pest with polyphagous feeding nature. Present studies were carried out at Integrated Pest Management Laboratory, University of Agriculture Faisalabad and farmers fields to determine incidence of P. solenopsis among 25 different plant species in cotton and mixed cropping zone of Punjab, Pakistan. Significant variations in plant species were recorded for population and infestation of P. solenopsis. Infestation of mealybug among the tested plant species ranged from 5.0 to 51.5 percent. Least infestation was observed on D. arvensis and C. album that was at par with C. morale, C. didimus, A. aspera, Eclipta prostrate and C. bonariensis. High infestation (51.5%) was observed on T. partulacastrum that was at par with both P. oleraceae and Euphorbia prostrate (45%) followed by G. hirsutum (39.0%). Population density ranged from 11.6 /6cm twig on D. arvensis that was at par with A. aspera (16.0 CMB/6cm twig), whereas maximum population (141.0 CMB/6cm twig) were recorded on T. partulacastrum that was at par with H. rosa-sinensis (140.0 CMB/6cm twig), W. somnifera (137.7 CMB/6cm twig), S. melongena (137.0), E. prostrate (132.7) and P. oleraceae (131.0 mealybugs/6cm twig). On the basis of seasonal population attractive plants of P. solenopsis were L. camara, H. rosa-sinensis, C. inerme, G. hirsutum, C. morale, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. album, A. spinosus, T. portulacastrum, P. oleracea, T. terrestris, E. prostrate and P. hysterophorus because they supported cotton mealybug for >3 months. Remaining plant species were considered as incidental plant species because they supported mealybug for <3 months. Clusters were made on the basis of infestation and population level of P. solenopsis among the selected plant species. Cluster-1 comprised of 13 plant species including H. annuus, H. rosa-sinensis, A. spinosus, W. somnifera, S. melongena, A. esculentus, T .terrestris, C. frutescens, E. prostrate, G. hirsutum, L. camara, P. oleracea and T. partulacastrum showed similarity with each other for mealybug infestation and population. Cluster-2 consisted of a group of three plant species including C. arvense, C. inerme and P. hysterophorus while cluster-3 possessed plant species including D. arvensis, E. prostrate, C. arvensis, C. didimus, C. bonariensis, C. album, C. morale, L. nudicaulis and A. aspera respectively. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-2 demonstrated maximum diversity (96.0) against the members of cluster-1 for infestation

xxi and population of P. solenopsis. In this study, first Principal component (PC) was taken having Eigen values ≥1. Results depicted that first PC expressed 82% of the total variability amongst the selected plant species of P. solenospsis as compared with second PC (18%). Mealybug infestation and population demonstrated positive factor loadings on PC1. On PC2 infestation expressed positive but population established negative factor loadings. In order to investigate the antixenosis mechanism of resistance in plant species, morphological traits of the selected plant species and attractiveness index of P. solenopsis were investigated. Significant variations among tested plant species toward the attractiveness of P. solenopsis (P < 0.05) were determined. G. hirsutum, E. prostrate, H. annuus, P. oleraceae, W. somnifera, L. camara and P. hysterophrous were categorized as attractive (attractive index ≥1) while D. arvensis, C. bonariensis and L. nadicaulis proved resistant plant species toward P. solenopsis as compared with H. rosa-sinensis kept as standard control. Physico-morphic traits of the selected plant species revealed that trichome density, trichome length, leaf area and leaf thickness had a positive correlation with mealybug attractiveness. Cluster analysis revealed that cluster-1 comprised of three plant species including L. camara, H.annuus and G. hirsutum demonstrating final cluster center readings of 225.0 trichomes/cm2, 1.12 µm, 62.3 cm2, 2.6 µm and 0.95 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively. Cluster-2 consisted of eight plant species including C. inerme, C. arvensis, C. didimus, H. rosa-sinensis, S. melongena, W. somnifera, A. esculentus and T.terrestris describing final cluster center readings of 22.3 trichomes/cm2, 1.04 µm, 12.2 cm2, 1.7 µm and 0.53 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively; while cluster-3 possessed a group of fourteen plant species including E. prostrate, A. spinosus, P. hysterophorus, E. prostrate, P. oleracea, T. portulacastrum, C. frutescens, L. nudicaulis, C. arvense, C. morale, C. album, A. aspera, C. bonariensis and D. arvensis with cluster center readings of 2.8 trichomes/cm2, 0.6 µm, 0.45 cm2, 0.77 µm and 0.29 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-2 demonstrated maximum diversity (D2= 208.9) against the members of cluster-1 for the most of the studied morphological traits. Principal component analysis results depicted that first two PCs expressed 73% of the total variability amongst the selected plant species for P. solenospsis while other PCs contributed only about 27% of the total variability. PC1 xxii contributed maximum variability (52%) following PC2 (20%), PC3 (12%), PC4 (12%) and PC5 (3.4%). The morphological traits like trichome density, leaf thickness, leaf area and trichome length explained positive factor loadings on PC1. These morphological explained positive factor loadings on PC2 but trichome density and trichome length demonstrated negative factor loadings on PC2 and leaf thickness, leaf area and trichome length explained negative factor loadings on PC3. A significant variation was also observed among biochemical traits in selected plant species. Biochemical contents comprising of nitrogen, phosphorus, potassium, crude protein, reducing sugar, total soluble sugar and chlorophyll contents were investigated in 25 selected plant species to determine their effect on attractiveness of P. solenopsis. Correlation coefficients demonstrated association between attractiveness of first, second and third instar nymphs of P. solenopsis with mineral contents including phosphorus contents (0.05, 0.27 and 0.03), potassium (0.03, 0.27, 0.03), nitrogen (0.12, 0.07, 0.12), sodium (0.21, 0.47, 0.27), total soluble sugar (0.01, -0.12, 0.06), reducing sugar (0.10, 0.1, 0.06), crude protein (0.12, 0.07, 0.12) and chlorophyll contents (0.29, 0.36,0.12) Cluster analysis for biochemical traits showed that Cluster-1 comprised of twelve plant species including L. camara, H. rosa-sinensis, H. annuus, P. hysterophorus, W. somnifera, E. prostrate, P. oleracea, S. melongena, T. portulacastrum, G. hirsutum, A. esculentus and C. frutescens having final cluster center readings of 1.72, 0.72, 0.5, 0.25, 0.06, 1.16, 0.1, 0.95 and 7.5% for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, chlorophyll, attractiveness index and crude protein respectively. Cluster-2 consisted of a group of five plant species including C. arvensis, E. prostrate, A. spinosus, C. inerme, and T. terrestris demonstrating final cluster center readings of 2.5, 0.64, 0.63, 0.7, 0.19. 1.42 0.3, 0.078 and 13.8% for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, attractiveness index, chlorophyll and crude protein respectively while cluster-3 possessed eight plant species including L. nudicaulis, C. didimus, C. arvense, C. morale, C. album, A. aspera, C. bonariensis and D. arvensis demonstrating final cluster center readings of 2.8, 0.6, 0.45, 0.77, 0.29, 2.1, 0.6, 0.057 and 16.3 for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, attractiveness, chlorophyll and crude protein respectively. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster 2 demonstrated maximum diversity (D2=25.3%) against the members of cluster 3 for the most of the studied traits. Principal component analysis results depicted

xxiii that first three PCs expressed 83% of the total variability amongst selected plant species. PC1 contributed maximum variability (40%) following PC2 (26%) and PC3 (17%). Antibiosis mechanism of resistance studies revealed that biological parameters of P. solenopsis were highly influenced by the plant species. Results revealed that significant variation in nymphal duration and mortality, crawlers per ovisac, pre- oviposition and oviposition period of P. solenopsis was determined for host plant species (treatments) (P <0.05). The higher number of crawlers per ovisac (>70 but <101 crawlers/ovisac) were produced when mealybug female was fed on H. rosa- sinensis, G. hirsutum, H. annuus, E. prostrate, W. somnifera and T. partulacastrum as compared with the other tested plant species. D. arvensis demonstrated more antibiosis effects in studied biological paramters of P. solenopsis. The female P. solenopsis fed on D. arvensis produced less number of crawlers (41.3 crawlers/ ovisac) and exhibited higher pre- oviposition period (5.6 days), higher mortality (75, 45 and 30%) and longer nymphal durations (6.67, 6.67 and 7.5 days) in 1st, 2nd and 3rd instar nymphs of P. solenopsis. Biochemical analysis of plant species revealed that phosphorus, potassium and sodium had positive association with nymphal mortality, nymphal durations, pre-oviposition and oviposition periods of the female but had negative association with crawlers density. Nitrogen, total soluble sugar, chlorophyll and crude protein had positive association with crawler density but negative with nymphal duration, nymphal mortality and reproductive periods. Sodium had negative association with crawler density but positive with nymphal mortality, nymphal and reproductive duration. Coefficient of determination values (R2) exhibited that phosphorus explained 27.5, 29.3, 49.3, 27.78, 31.6, 33.9, 45.2, 52.9 and 68.8%; potassium demonstrated 21.7, 30.8, 11.3, 21.3, 26.4, 24.1, 14.6, 7.5 and 18.07%; nitrogen attributed 8.2, 9.6, 9.1, 2.5, 4.9, 4.4, 6.5, 0.15 and 17.38%; crude protein contributed 8.2, 9.6, 9.1, 2.5, 4.9, 4.4, 6.5, 0.1 and 17.3%; total soluble sugar explained 27.8, 7.9, 8.6, 26.0, 12.8, 17.34, 8.8, 20.4 and 25.4%; reducing sugar described 0.01, 0.3, 3.18, 0.1, 1.2, 0.2, 1.68, 1.37 and 1.48%; sodium demonstrated 31.4, 22.2, 39.2, 25.2, 37.2, 38.0, 52.3, 30.4 and 33.6%; chlorophyll attribiuted 12.0, 12.0, 4.4, 7.9, 5.96, 10.0, 0.3, 2.3 and 1.8% of total variation in preoviposition-period, oviposition-period, crawlers/ovisac, mortality of 1st, 2nd and 3rd instars and nymphal duration of 1st, 2nd and 3rd instars, respectively. The results of cluster analysis and dendrogram reveal that plant species were categorized into three clusters and cluster-1 demonstrated maximum diversity against the members of cluster-3 for the most of the studied biochemical traits and biological parameters of P. solenopsis. PCA explained first four PCs which xxiv commutatively expressed 81% of the total variability among the slelected plant species for the biological parameters of P. solenopsis with maximum contribution of PC-1 (52%). In weeds, tolerance studies were based on biochemical variations because yield of plant species other than economic crops (weeds and ornamental plants) is not required. Results revealed that cotton mealybug (CMB) densities had significant effect on the biochemical contents of the tested plants. At low density (50 CMB/plant), studied plant species including L. camara, C. arvensis, P. hysterophorus, C. didimus, T. portulacastrum, T. terrestris, A. esculentus, C. frutescens, E. prostrate, S. melongena, C. album, H. annuus and G. hirsutum exhibited tolerance (0.08-0.1%) while rest of the plant species exhibited no tolerance. However at a density level of 100 CMB/plant, none of the selected plant species exhibited tolerance against P. solenopsis. Nitrogen contents were 2.5, 1.3, 1.2, 1.5, 2.8, 3.1, 2.2, 3.1, 2.5, 2.5, 3.1, 2.5, 3.1, 1.6, 2.7, 2.1, 1.8, 2.6, 3.1, 2.5, 2.1, 1.1, 2.1, 2.3 and 4.7% at 0 CMB/plant, but 3.2, 2.9, 2.8, 3.2, 2.5, 3.8, 2, 2.8, 3, 2.1, 4.5, 4.3, 2.8, 4.4, 2.4, 3.6, 3.5, 2.3, 2.6, 2, 4, 3.5, 2.3, 2 and 3.7% at density of 50 CMB/ plant whereas contents were decreased to 2.1, 0.5, 1.0, 1.2, 2.2, 2.0, 1.8, 2.3, 1.5, 1.6, 2.5, 2.0, 2.6, 1.0, 2.7, 1.6, 1.6, 2.3, 2.7, 1.8, 1.5, 1.8, 2.1, 1.9 and 3.7% at density of 100 CMB/ plant in L. camara, C. morale, H. rosasinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus respectively. Cluster analysis revealed that cluster-1 comprised of fourteen plant species including L. camara, C. arvensis, H. annuus, T. terrestris, L. nudicallis, S. melongena, C. bonariensis, C. inerme, C. arvense, A. spinosus, P. oleracea, E. prostrate, E. prostrate and C. frutescens. Cluster-2 consisted of a group of three plant species including C. morale, H. rosa-sinensis and D. arvense, while cluster-3 possessed eight plant species including W. somnifera, A. aspera, A. esculentus, T. partulacastrum, P. hysterophorus, C. didimus, G. hirsutum, and C. album. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-1 demonstrated 18% and 0.08% diversity against the members of cluster-2 and cluster-3 for the most of the studied biochemical traits, respectively. The members of cluster-3 exhibited 10.3% diversity against the members of cluster-2 for the most of the plant biochemical traits and tolerance.A principle component analysis (PCA) established to examine the relationship between leaf nutrients and different density of P. solenopsis depicted that, first two out of eight Principal components (PCs) having xxv

Eigenvalues ≥1 expressed 99% of the total variability amongst the selected plant species for P. solenospsis. Nitrogen, crude protein, sodium, total soluble sugar and chlorophyll were negatively correlated with mealybug density, but phosphorus, reducing sugar and potassium were positively correlated. Although, all tested biochemical contents were decreased at higher mealybug density (100 mealybug/plant) but tolerance/compensatory growth, phosphorus, potassium were increased at low density (50 mealybug/plant) than control (without mealybug) confirming that plants exhibited tolerance mechanism against P. solenopsis.

xxvi

CHAPTER 1 INTRODUCTION

Mealybugs are soft bodied belonging to family Pseudococcidae and order Hemiptera (Carver et al., 1991; Dhawan et al., 2010). They are soft-bodied insect pest, one of the mealybug species existing in Pakistan and other Asian countries is scientifically recognized as Phenacoccus solenopsis (Hemiptera: Pseudococcidae). It ranks among the polyphagous insect pests causing serious losses to different economic crops globally (Miller et al., 2002; Aijun et al., 2004). Both nymphs and adults of cotton mealybug cause damage by sucking cell sap, reducing its quality (Charleston et al., 2010) and affecting photosynthetic activity of plants due to development of sooty mold on honey dew secretions (Saeed et al., 2007). Infested plants show range of symptoms depending upon plant species and severity of attack but commonly damage is done by extracting sap from the plant, injection of toxic saliva and excretion of honey dews that serve as substrate for sooty mould development (Miller et al., 2002; Saeed et al., 2007) and defoliation of leaves and can serve indirectly as vectors of pathogens (Culik and Gulan, 2005). are known to be associated with mealybug because they transfer mealybug from one plant to the other (Jagadish et al., 2009) and feed on the sugary material released by the pest, in turn ants protect the mealybug from the attack of predators (Carver et al., 2007). Mealybug damaged cotton plants stay stunted and produce less number of bolls with a small size, leaves appear yellow and finally drop off from the infested plant (Mark and Gullan, 2005). P. solenopsis attacked both Bt and non-Bt cultivars of cotton (Dutt, 2007). Heavily infested plants look like sprayed with defoliator (Arif et al., 2006; Abbas et al., 2007; Arif et al., 2007). Mealybug feedings alter the physiological process in plants, because quantities of plant defensive biochemicals were changed and it also has capability to alter the genes transcribing thaumatin like protein species in cotton (Shafiq et al., 2014). Mealybug-infested leaves induce high amounts of proteins and sugars as compared to the amounts produced in normal leaves but declined the phenol concentration in infested plants of sunflower (Jagadish et al., 2009). After 38 days of P. solenopsis feedings reduced relative chlorophyll content of tomato plants by 57.3% but light utilization efficiency by 42.4%, however initial infestation by P. solenopsis caused no change in relative leaf chlorophyll content or light utilization efficiency that may be due to compensatory photosynthesis (Huang et al., 2013).

1

The average life cycle of P. solenopsis is from 25 to 38 days (Joshi et al., 2010). Oviposition in P. solenopsis lasted usually for 9-12 days (Hanchinal et al., 2010). It can complete many generations in a year. Adult females are ovoviviparous and produce ovisac that is composed of fuzzy, loose- wax strands (Lu et al., 2008) capable of producing 128 to 812 crawlers (Vinnila et al., 2010). First instar crawlers of P. solenopsis scatter to settle mostly on the leaves, leaf petioles, stems and bracts of cotton buds (Ben- Dov, 2010). Nymphs undergo three moults of female and 4 instars in male to become adult (Miller, 2005), however second instar of P. solenopsis had longer developmental period than other instars (Chong et al., 2003). Phenacoccus solenopsis remain active throughout the year in Pakistan and peak population of mealybug was recorded during August and September when temperature ranged 28-33.5˚C and respectively 59-78% humidity (Shahid et al., 2012). P. solenopsis has significant positive correlation with temperature and sunshine (Suresh and Kavitha 2008; Dhawan et al., 2009; Hanchinal et al., 2010; Shahid et al., 2012), rainfall exerted negative effect (Suresh and Kavitha, 2008), however location of the pest on plant appear to be influenced by humidity as P. solenopsis existed usually on roots and foliage near to dry areas of the soil (Hodgson et al., 2008). CMB is capable to tolerate temperatures exceeding from 0°-45°C, during climatic variations in the year (Sharma, 2007). Abiotic factors also affect the biological parameters of the pest. According to Vennila et al. (2010), all life stages of P. solenopsis completed their development within shorter period in summer season (at 23.3°C and 40.5% RH) while within longer period during winter season (at 16.8°C and 30.7% RH). Temperature plays an important role on the development and growth of P. solenopsis. Developmental duration of nymphal instars at 18°C was three times longer than at 30°C (Lu et al., 2011). In Pakistan it has been reported on 154 plant species including field crops, fruits, vegetables, weeds and ornamentals (Saini et al., 2009; Arif et al., 2009). The development, survival, reproduction and life table parameters of insects are influenced by host plant type (Tsai and Wang, 2001; Kim and Lee, 2002; Li et al., 2004). The physical and volatile signals originate from plants that attract the insect to its surface whereas chemical and nutritional factors of the food substrate determine consumption, development and survival in the larval stages and egg production of subsequent adults (Singh and Mullick, 1997). The shorter developmental time and greater total reproduction of insects on a host plant indicate greater suitability of that plant (van Lenteren and Noldus, 1990). Host plant specificity and oviposition motivation are affected by the 2 physiological state of insect pest including age, feeding status, mated status and egg load (Jallow and Zalucki, 1998). Food preference of mealybug toward host plants is variable. It may be due to the difference in the morphological traits, phenology, secondary metabolites, tissue solidity, quality and quantity of macro and micronutrients, volatile compounds, and defense mechanisms (Joachim-Bravo et al., 2001; Shahid et al., 2012). Each insect has varying level of dietary requirement. Nutrients not only affect the growth and development of plant species but also alter the quality of the food source of herbivorous insect pest (Heng-Moss et al., 2004; Goncalves-Alvim et al., 2004). It has also been shown that the quality and quantity of nourishment ingested by an insect can directly affect its survival and reproduction (van Steenis and El-khawass, 1995; Du et al., 2004). So, fitness of the plant-feeding insects depends upon the nutrients in their host plant. Biology of CMB is affected with respect to the plant material. Developmental period of first, second and third instar of P. solenopsis on Hibiscus rosa-sinensis was 6, 8 and 10 days (Akintola and Ande, 2008). Longevity of P. solenopsis adult female on Gossypium hirsutum was 22.2 days and life-cycle completion period was 47.7 days however developmental period of first, second and third instars of P. solenopsis on Solanum tuberosum, G. hirsutum and H. rosa-sinensis plants were 7.5, 3.6 and 7.2 days respectively Sahito et al. (2010). Developmental period of male mealybug was 20.3, 21.4 and 21.8 days but 38.5, 39.4 and 39.2 days on S. tuberosum, G. hirsutum and H. rosa- sinensis respectively (Hanchinal et al., 2010). Developmental duration of female mealy bug was rapid on G. hirsutum, but of males was rapid on H. rosasinensis (Mammoon-ul- Rasheed et al., 2012). Developmental period of first, second and third instars, longevity and life cycle of adult female on Abelmaschus esculentus was 4.9, 7.9, 5.7, 24.8 and 43.4 days whereas it was 9.8, 8.6, 5.8, 27.6 and 51.8 days on H. rosasinensis respectively. The developmental period for first, second instars, pupal stage, longevity and life cycle of male was 5.6, 4.5, 4.3, 2.9 and 17.4 days respectively on Abelmaschus esculentus and 7.5, 4.4, 5.3, 3.2 and 20.4 days on H. rosasinensis. The sex ratios recorded on A. esculentus and H. rosasinensis were 1:33.5 and 1:10.2, respectively (Sahito and Abro, 2012). Resistant plants induce antagonistic effects on the herbivorous insect pests. Plants including Rosa indica, Jatropha curcus, Mangifera indica, Saraca indica, Ocimum basilicum and Bougainvillea spp; R. indica induced maximum mortality in 1st instar nymphs (70-90%), reduced fecundity (100-200eggs/ovisac/female) and prolonged nymphal duration by 20-23 days; as compared with H. rosa-sinensis producing >400 3 eggs/ovisac/female and nymphal duration was shortened (16-17 days) when nymphs were fed on G. hirsutum and H. annuus (Sana-Ullah et al., 2011). Farmers mostly rely on use of pesticides for the control of insect pests but in case of mealybug, chemical control is difficult because insecticides can not penetrate and access to the target site due to the provision of wax body covering (Franco et al., 2004). Repeated usages of conventional insecticides exert harmful effects on the natural enemies, induce insecticide resistance in mealybug (Bushra et al., 2014) and other targeted and make food unacceptable for human use due to their residual toxicity (Walton et al., 2006). Safe way to manage mealybug on the economic crops and overcome the harmful effect of pesticides is by the use of host plant resistance. Resistant plants protect themselves from insect pest herbivory due to the provision of resistance mechanisms. Biophysical and biochemical traits provide basis for plant resistance mechanisms against insect pests (Bernays and Chapman, 1994). Plant surface is provided with some glandular and non-glandular trichomes. Non glandular trichomes deter the feeding and oviposition whereas glandular ones excrete some volatile exudates that repel the insect and force the insect to stay away from the plant surface, in this way they change the behavior of the phytophagous insect pests (Mierziak et al., 2014). Various researchers categorized host plants into resistant and susceptible ones on the basis of pest infestation (Arif et al., 2009; Abbas et al., 2010). Susceptible host plants serve as food source substrate for feeding and multiplication of CMB and ensure its dispersal to the next economic crop (Abbas et al., 2010). They also identified levels of resistance in plants to insect pests (Baker et al., 1981.; Reinert 1982; Ahmad et al., 1986; Smith 1989; Quisenberry 1990; Braman et al., 1994; Johnson-Cicalese et al., 1998; Reinert and Busey 2001; Heng-Moss et al., 2002; Rangasamy et al., 2006). Morphological structures like epicuticular wax structures and trichome densities do not contribute toward tolerance, antixenosis, and antibiosis mechanisms against mealybug species (Heng-Moss et al., 2003). Plant sap also contains some chemical and nutritional substances that affect the biological parameter of insect including insect development, its survival, insect stages and egg production in adults (Tsai and Wang, 2001; Kim and Lee, 2002; Arif et al., 2013). In addition to resistance ability plants have also potential to tolerate or withstand the attack of insect pest injury and expoloit morphological and biochemical changes. According to Khattab (2007), aphid feeding on cabbage caused significant reduction in 4 the percentage of epicuticular wax, dry weight, sugar and amino acid levels but it enhanced the uptake of some nutrient elements such as P, K, Ca, Mg and Fe similarly lipid peroxidation, polyphenol peroxidase and oxidase activities were markedly increased but oxidative enzyme activities (superoxide dismutase, ascorbate peroxidase, ascorbate oxidase) and total soluble proteins were significantly reduced. It also affected the levels of antioxidant compounds (glutathione, ascorbic acid, carotenoids and phenols). These features are critically very important in the decision making of an insect to feed, probe and oviposit any plant (Mierziak, et al., 2014). Keeping in view the importance of economic crops, the losses caused by the pest, it potential to climatic adaptability, its association with ants that protect it from biocontrol agents, development of resistance toward insecticides and its polyphagous feeding nature, pest has attained the status of major economic insect pest. Now under the context of sanitary and phytosanitory measures as well as food security only option to manage P. solenopsis is through the host plant resistance that is basic component of integrated pest management. Therefore, present study was carried out regarding mechanisms of resistance in different host plants against cotton mealybug P. solenopsis Tinsley (Hemiptera: Pseudococcidae) in Punjab, Pakistan under objectives given as below:

Objectives: 1. Determination of natural incidence of P. solenopsis on different host plants from cotton and central mixed zone of Punjab, Pakistan. 2. Assesment of antixenosis mechanisms of resistance in different plant species toward P. solenopsis 3. Assesment of antibiosis mechanisms of resistance in different plant species toward P. solenopsis 4. Assessment of tolerance mechanisms (morphological and chemical changes) among the healthy versus infested plants with P. solenopsis

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CHAPTER 2 REVIEW OF LITERATURE

2.1 Economic importance of Phenacoccus solenopsis The economy of Pakistan is highly associated with cotton production in the country. Cotton account for 8.2% of the value added in agri-business and 2% GDP of Pakistan. Economic estimated losses due to cotton mealybug, P. solenopsis were up to 14% in cotton during 2005 (Hodgson et al., 2008; Dhawan et al., 2009). Pest caused 44% decline in seed-cotton yield in Pakistan (Dhawan et al., 2009) and 1.3 million bales reduction in Pakistan (Kakakhel, 2007; Abdullah, 2009; Hameed et al., 2012). The cost of pesticides purchased and used to control mealybug was up to US $121.4 million in the Punjab, province of Pakistan (Nalwar et al., 2009; Dutt, 2007). 2.2 Geographical distribution of P. solenopsis With the passage of time, P.solenopsis has now been established all over the world including in Cuba, Ecuador and Mexico since 1992 (Williams and Willink, 1992), 2001 in Galapagos Islands (Causton et al., 2006), 2003 in Argentina (Granara Willink de, 2003), 2002 in Brazil (Muniappan, 2009) and Chile (Prishanthini and Vinobaba, 2009), 2007 in Ghana (Muniappan, 2009), 2008 in China (Muniappan, 2009) and Colombia (Granara et al., 2007), 2005 in Pakistan (Arif et al., 2007), 2006 in India (Prishanthini and Vinobaba, 2009), 2007 in Thailand (Muniappan, 2009), during 2007 in Sri Lanka and Nigeria (Muniappan, 2009). According to Wang et al. (2009), this invasive species could spread to 17 provinces and 11 cotton growing regions in China. 2.3 Population dynamics of P. solenopsis In Pakistan mealybug infestation was observed in all cotton growing districts of Sindh (Sahito et al., 2011) and cotton growing areas of southern Punjab to investigate the host plants of cotton mealybug (Arif et al., 2009). A list of 154 plant species in 53 families were recorded comprising of numerous crops, weeds, vegetables, ornamental plants and economic fruits. Economic damage occurred on cotton, brinjal, okra, tomato, sesame, chineserose and sunflower. Similarly there was high infestation of cotton mealybugs in cotton growing regions of the Bahia, Agreste and Semi-arid of the Paraiba State, during the cotton season in Brazil (da Silva, 2012). Population dynamics of Phenacoccus solenopsis (Tinsley) was higher during the month of October on cotton (Gossypium hirsutum L.) and okra (Abelmaschus esculentus L.) in India. They stated that maximum population of mealybug occurred on Tomato

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(Lycopersicon esculentum L.) and Potato (Solanum tuberosum L.) were seen during the month of February. The mealybug population exhibited positive correlation with higher temperature but negative correlation with lower temperature and humidity. The biology of the Phenacoccus solenopsis (Tinsley) on Hibiscus rosa-sinensis (L.) showed that the fecundity rate of female ranged from 300 to 750; incubation period ranged from 2.45-4.8 minutes, first nymphal stage 3-6 days; second nymphal stage 4-6 days; third nymphal stage 4-6; pre-oviposition period 6-9; oviposition period 12-15; post-oviposition 2-5 days; fecundity (no. of eggs laid/ female) 300-750; Ovisacs (no. of ovisacs/ female) 2-5; Adult longevity (days) 21-30; Total life cycle (days) 33-44 days, however longevity of female was higher (24.44±2.33 days) than male mealybug (1.960±0.84 days) (Singh and Kumar, 2012). 2.4 Polyphagous feeding and invasiveness nature Phenacoccus solenopsis (Hemiptera: Pseudococcidae) has potential to increase its population and disperse rapidly due to its polyphagous nature. Historically it was recorded for the first time on Boerhavia spicata Choisy and Kallstroemia brachystylis Vail weeds from USA (Tinsley, 1898; McKenzie, 1967). It also appeared in Texas on non-cultivated host plant species by 1975 (McDaniel, 1975), then on Ambrosia sp., (USDA, 1978) and cotton (Fuchs et al., 1991). It also appeared on tomato (Culik and Gullan, 2005) in Brazil, cotton (Abbas et al., 2005; Jhala et al., 2008; Bhosle et al., 2009; Charleston et al., 2010) in Pakistan, India and Australia, Hibiscus rosasinensis in Nigeria, Iran and Africa (Akintola and Ande, 2008; Muniappan, 2009; Moghaddam and Bagheri 2010), vegetables in Thailand (Tanwar et al., 2007; Bambawale, 2008; Hodgson et al., 2008), Jojoba and cotton in China (Wu and Zhang, 2009). Deshpande (2009) suspected about the invasion of P. solenopsis in Asia that was attributed to illegal bringing of Bt. cotton bolls by some progressive growers from USA (Deshpande, 2009). With the promotion of international trade all over the world, this exotic pest species has been found on plant material at international ports and greenhouses outside its native range (Jansen, 2004) and through trade products (Tanwar et al., 2007; Prishanthini and Vinobaba, 2009; Nagrare et al., 2009). Other reasons behind invasive nature of P. solenopsis include polyphagous nature, high reproductive potential, climatic adaptability/habitat generalist, mealy powder and wax provision on body avoids entry of pesticides into the body and easy way of dispersal (Hodgson et al., 2008; Lu et al., 2008; Franco et al., 2009).

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2.5 Nature of damage of P. solenopsis Mealybug damaged cotton plants stay stunted and produce less number of bolls with a small size, leaves appear yellow and finally drop off from the infested plant (Mark and Gullan, 2005). Dutt, (2007) reported that P. solenopsis attacked both Bt and non-Bt cultivars of cotton. Heavily infested plants look like sprayed with defoliator (Abbas et al., 2007; Arif et al., 2006; Arif et al., 2007). Mealybug-infested leaves induce high amounts of proteins and sugars as compared to the amounts produced in normal leaves. Jagadish et al. (2009) have also described a decline in the phenol concentration in infested plants of sunflower. 2.6 Life history parameters Females of CMB show ovoviviparous mode of reproduction and produce ovisac that is composed of fuzzy, loose- wax strands (Lu et al., 2008). The durations of the first, second and third instars were 3.9, 5.1 and 4.2 days respectively under laboratory conditions (23–30°C and 49–92% relative humidity). The male and female longevity of mealybug was 1.5 and 42.4 days respectively and females lay on an average 344 nymphs with reproductive period 30.2 days (Vennila et al., 2010). They further explained that nymphs of P. solenopsis originating into males had extended developmental duration than females i.e., 18.7±0.9 days and 13.2±1.8 days respectively that might be due to extra pupal stage in males. P. solenopsis can complete 15 generations per year (Tanwar et al., 2007) and are capable of producing 128 to 812 crawlers (Vinnila et al., 2010). The first instar crawlers of P. solenopsis scatter to settle mostly on the leaves, leaf petioles, the stems and bracts of buds in cotton (Ben-Dov, 2010). The nymphs undergo three instar moults for female and 4 instars in male including puparium to become adult (Miller, 2005). According to Chong et al. (2003), 2nd instar of P. solenopsis had longer developmental period than the other instars. The average life cycle of P. solenopsis is from 25 to 38 days (Joshi et al., 2010) and Hanchinal et al. (2010) reported that oviposition in P. solenopsis lasted usually for 9- 12 days. According to Nikam et al. (2010) longevity of female and male was 33.67 ± 1.19 and 8.70 ± 0.79 days respectively at temperature and relative humidity range from 25 to 30ºC and 75 to 80% respectively. Total life span of P. solenopsis on potato sprouts was 39.12±2.85 and 18.60±1.5 days for female and male respectively (Kedar et al., 2011). 2.7 Host plants of mealybug in Pakistan Being polyphagous feeding nature, P. solenopsis has broad range of variable host plants. Lot of studies indicated that plants were declared as host plants of P.solenopsis 8 and the studies were based on either field survey or laboratory experiments. The host plants fulfilled all the requirements of insect pest feed, its breed and completion of whole life cycle. ICAC Recorder (2008) included 22 plant species whereas Hodgson et al. (2008) reported 55 hostplants in 18 families, however from Pakistan Arif et al. (2009) reported 154 host plants of P. solenopsis. 2.8 Drawback of chemical control for the management of P. solenopsis Efficacy of chemical control for the management of mealybug faces difficulty in approach to the target site due to the provision of wax body covering. On the other hand repeated usages of conventional insecticides exert harmful effects on environment, the natural enemies and induce insecticide resistance in targeted arthropods thus make food unacceptable for human use due to their residual toxicity (Franco et al., 2004; Walton et al., 2006; Bushra et al., 2014). Due to excessive and misuse of pesticides, mealybug P. solenopsis has now developed resistance to most chemical group of insecticides and exhibited insecticidal resistance to some organophosphate and pyrethroid group of insecticides (Bushra et al., 2014). Resistance ratios (RRs) at LC50 ranged from 2.7-13.3 folds for chlorpyrifos, 11.6-30.2 for profenofos and 10.6-46.4 for bifenthrin, 5.8-25.2 for deltamethrin and 4.1-25.0 for lambda-cyhalothrin (Bushra et al., 2014). 2.9 Importance of host plant resistance Safe way to manage mealybug on the economic crops and overcome the harmful effect of pesticides is by the use of host plant resistance. Resistant plants protect themselves from insect pest herbivory due to the provision of resistance mechanisms. Biophysical and biochemical traits provide basis for plant resistance mechanisms against insect pests (Bernays and Chapman, 1994). Plant surface is provided with some glandular and non-glandular trichomes. Non glandular trichomes deter the feeding and oviposition whereas glandular ones excrete some volatile exudates that repel the insect and force the insect to remain away from the plant surface, in this way they change the behavior of the phytophagous insectpests (Mierziak, et al., 2014). Plant sap also contains some chemical and nutritional substances that not only affect the growth and development of plant species but also alter the quality of their food source for herbivorous insect pest (Goncalves-Alvim et al., 2004). It has also been documented that quality and quantity of food affect food selection behavior, survival and reproduction of phytophagous insect pest (Tsai and Wang, 2001; Kim and Lee, 2002; Du et al., 2004; Arif et al., 2013). It may be due to variation in volatile compounds, phenology, secondary metabolites, tissue solidity and defense mechanisms. Likewise 9 nitrogen being a structural element of chlorophyll and protein molecules helps in the formation of chloroplasts and accumulation of chlorophyll make plant succulent (Amaliotis et al., 2004; Daughtry, 2000). Sucking insect pests are commonly attracted toward succulent plants that are enriched with chlorophyll (Tucker, 2004). Inhibition of feeding and oviposition in mites and whiteflies has also been documented by (Neal et al., 1994; Liu and Stansly, 1995; Slocombe et al., 2008) due to imbalanced nutrition. Mechanisms of plant resistance play significant role against insect pests, these are actually the defense strategies evolved by plants to cope with damage caused by herbivores (Gard et al., 2013). Nutrient plant chemistry also play important role in the fitness of feeding insect pest because of quantitative and qualitative dietary requirement of insect pest for food (Liu et al., 2004). It also affects insect performance (Mattson, 1980; Rausher, 1981; Scriber and Slansky, 1981; Raupp and Denno, 1983; Osier and Lindroth, 2001; Holton et al., 2003). Food quality is partially determined by defenses, primarily toughness and secondary metabolites, but also by nutrients, primarily water and nitrogen. According to Coley and Barone (1996), most herbivory occurs on young leaves, which are more nutritious than mature leaves. This variation is positively correlated with leaf expansion rates (Coley and Kursar, 1996; Kursar and Coley, 2003). Although rapid expansion shortens the window of vulnerability when leaves are tender, rapid expansion requires high concentrations of nitrogen associated with growth processes (Kursar and Coley 1991, 1992). In addition, in order to expand quickly, resources are shifted from defense to growth (Kursar and Coley 2003; Brenes-Arguedas et al., 2006). Thus, the higher rates of occurrence of herbivores on fast expanders can be explained by their higher nitrogen content and less effective chemical defenses (Kursar and Coley 2003; Coley et al. 2005). These characteristics of plants are critically very important in decision making of insects for feeding, probing and oviposition (Joachim-Bravo et al., 2001; Shahid et al., 2012). Due to the reason practical use of host plant resistance against insect pest is increasing day by day (Mierziak et al., 2014). 2.10 Mechanisms of resistance

Understanding the mechanisms of resistance in host plants is very useful in the integrated pest management approach. There are three mechanisms of resistance i.e. antixenosis, antibiosis and tolerance such mechanisms of resistance in plants collectively enhance resistance in plants either by altering the feeding and oviposition behavior of

10 insect or by affecting the development, survival, reproduction and life history parameters of insects (Cook and Smith, 1988). Resistance mechanism possibly may not be similar for all tested genotypes toward a variety of insect pests. Some among them may exhibit tolerance, antibiosis or antixenosis mechanism against herbivorous insect pest or a combined action of such mechanisms. Host-plant selection is primarily regulated by the chemoreception behavior of herbivorous insect pest (Jeremy and Szentesi, 2003). It involves host habitat findings, host recognition, host acceptance and host fitness phases. These circumstances express selection pressures for the herbivorous insect pests and enable them to recognize dissimilarities among favorable and unfavorable host plants for food as well as oviposition preference due to the availability of sensory cells on their body (Anderson et al., 1989). Physical and chemical characteristic of plants are involved in host-plant selection process by insects (Harrewijn, 1990; Niemeyer, 1990), in this way herbivorous insect pest make decision to reject or accept food source and make food preference in choice situations (Bernays and Chapman, 1994; Renwick, 2002). Morphological traits are recognized as physical factors or epiphylaxis and chemical factor as internal protection agencies or endophylaxis/biochemical factors (Ernest, 1989; Stadler, 2000). Epiphylaxis factors include colour, shape, size, thickness of cell wall, solidness, trichomes, accumulation of mineral contents in cuticle (silicon or others), surface waxes (Hirota and Kato, 2001; Langan et al., 2001). According to Norris and Kogan (1980) pubescence was widely involved in plant resistance to insects that alter the behavioral and physiological response of arthropods to plants. Endophylaxis include the presence of certain phenols, tannin, flavinoids (Goncalves-Alvim et al., 2004) that are volatile in the form of glandular exudates from the plant parts and make them unattractive or repellent or unsuitable for the food requirements of insects. Epiphylaxis factors influence the feeding and ovipostion of the insectpest. Endophylaxis factors influence the biological or life history parameters of the herbivorous insect pest (Dhaliwal and Arora, 2003). Single trait or combination of plant traits in any crop may impart resistance against insect pests. In vigna crop, trichomes imparted resistance to Maruca testulalis M. vitrata, Clavigralla tomentosicollis and Callosobruchus maculatus (Oghiakhe, 1997). Similarly in wheat crop trichomes imparted resistant to Sipha flava (Webster et al., 1994). Similarly a single plant may impart resistance to only one herbivorous insect pest or resistance against a variety of insect pests likewise pubescent genotypes provide resistance to boll weevil, pink bollworm and 11 plant bugs (Lukefahr et al., 1971; Ahmad et al., 1987). According to Descamps and Chopa (2011) beer barley was the prefered food for Rhopalosiphum padi and intrinsic rate of natural increase (0.309 female-1d-1) of pest on barley was greater than all other cereal crops and lower was nymphal mortality (22.2%) and doubling time (2.24). So, plant insect interaction is a system of continuous evolution coped with biochemicals (Kliebenstein et al., 2001; Birkett et al.,2000), proteins (Haruta et al., 2001) and physical weapons (Schoonhoven et al. 2005). 2.11 Antixenosis mechanism Antixenosis mechanism also recognized as non-preference mechanisms of resistance, alter the host choice or selection behavior of herbivorous insect pest for feeding, shelter (Sharma and Nwanze, 1997), oviposition (Pancoro and Hughes, 1992), and their colonization (Dhaliwal and Arora, 2003). Due to provision of this mechanism insect show avoidance behavior from that specific plant and make the plants unuseful or poor quality for invasion of insects (Bazzaz et al., 1987; Schoonhoven et al., 1998). According to Smith, (2012) oviposition rate of weevil Ceratapion basicorne was high on its preferred plant species than on non-target species due to antixenosis mechanism of resistance. Centaurea solstitialis (yellow starthistle) had (66% of eggs, on a per replicate basis) followed by Centaurea cyanus (bachelor's button 22%), Centaurea melitensis (6%), Centaurea americana (1%), Saussurea americana (3%) and Carthamus tinctorius (safflower 2%). Morphological and biochemical traits of the plant play vital role in mechanisms of resistance likewise, epicuticular wax content in the leaves served as a mechanical barrier for Flea beetles (Phyllotreta spp.), cabbage stink bugs (Eurydema ventrale) and onion thrips (Thrips tabaci) (Znidarcic et al., 2008). Availability of certain allomones or deficiency of some kairomones or imbalance between allomones and kairomones also enhance mechanism of resistance in plant to insect pest (Feeny et al., 1983; Panda and Khush, 1995). Various plant species have been identified possessing mechanism of plant resistance property and exhibiting varying levels of resistance to insect pests throughout the world (Heng-Moss et al., 2002; Rangasamy et al., 2006). Turfgrasses exhibited tolerance mechanisms due to modifications in plant proteins and oxidative enzymes, resulting in greater rhizome numbers and turf densities, however pubescence was positively correlated with buffalograss susceptibility to mealybugs and glabrous leaf surface was suggested as a possible mechanism of resistance (Heng-Moss et al., 2003).

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It has also been documented that quality and quantity of food collectively affect food selection behavior, survival and reproduction of phytophagous insect pest (Du et al., 2004; Nasiri et al., 2009). Other than nutritional effect of plants, plant traits also affect the performance of insect pests (Schoonhoven et al., 2005). Indeed, sucking insect pest are very selective sap feeders and select their host plants (food source) through visual, mechanical, and chemical stimuli (Bernays 1998). The decision for acceptance or rejection of plant by insect pest involves type of the volatile chemicals emitted by plant, plant surface waxes, cell wall thickness, mesophyll and phloem content compositions (Niemeyer 1990; Caillaud and Via 2000). Chemical concentration and constituents varies with respect to plant species and plant organs within the same plant (Schoonhoven et al., 2005). 2.12 Antibiosis mechanism Antibiotic mechanism of resistance adversely affects the physiological functioning of herbivorous insect pests (Pedigo, 1996; Felkl et al., 2005). Ingestion of a plant by an insect may manifest antibiotic symptoms varying from acute or lethal to sub-chronic or mild effects that may be of permanent or temporary in nature (Dhaliwal and Arora, 2003). The most common symptoms in insect pests include larval death in the early instars, irregular growth rates, decline in size and weight of the larvae or nymphs, prolongation of the larval period, failure to pupate, failure of adults to emerge from the pupae, inability to concentrate on food reserves, followed by a failure to hibernate, abnormal adults, decreased fecundity, reduction in fertility, restlessness and abnormal behaviour, reduced honey dew secretions by sucking insect pests (Hartnett and Abrahamson, 1979; Pedigo, 1996). These symptoms appear due to the presence of toxic substances, nutrient- imbalances, presence of certain antimetabolities and of enzymes, which adversely affect digestion process and also the utilization of various nutrients (Kogan, 1982; Pedigo, 1996; Kumara et al., 2006). The development, survival, reproduction and life table parameters of insects are influenced by host plant type (Tsai and Wang, 2001; Kim and Lee, 2002; Li et al., 2004). The physical and volatile signals originate from plants that attract the insect to its surface whereas chemical and nutritional factors of the food substrate determine consumption, development and survival in the larval stages and egg production of subsequent adults (Singh and Mullick, 1997). The shorter developmental time and greater total reproduction of insects on a host plant indicate greater suitability of that plant (van Lenteren and Noldus, 1990). Host plant specificity and oviposition motivation are affected by the 13 physiological state of insect pest including age, feeding status, mated status and egg load (Jallow and Zalucki, 1998). Several physiological and biochemical traits are also important factors conferring mechanisms of nonprefference and antibiosis. A well known example is the presence of gossypol gland and phenolic compounds that exhibit resistance to several insect pests in cotton (Dhaliwal et al., 1993). These characters of plants provide protection against herbivorous insect pests or influence the development and growth of herbivorous insect pest, in this way activity of insect pest is affected. It may be due to physicomorphic traits of plant (Stadler, 2000; Harota and Kato, 2001; Goncalves-Alvim et al., 2004) or nutritional variations (Chau et al., 2005). Similarly chemical factors are known to impart resistance to a wide variety of insect pests (Stadler, 2000; Goncalves-Alvim et al., 2004) they include inorganic chemicals, primary and intermediary metabolites and secondary substances (Dhaliwal and Arora, 2003) which are categorized into nutrients and allelochemicals. The surfaces of plants parts have different volatile and non-volatile compounds (Baur et al., 1996), that produce certain stimuli, which are perceived by the insects through sensilla and mediate the behavior of insects from the host recognition to the host acceptance (Stadler, 2002; Goncalves-Alvim et al., 2004). These compounds include inorganic chemicals, primary and intermediary metabolites and secondary substances (Dhaliwal and Arora, 2003) which are categorized into nutrients and allelochemicals.

Allelochemicals are called as secondary metabolites that are not involved in the essential photosynthetic and metabolic activities, like growth, development or reproduction of organisms. These substances are organic compounds which are often produced as by-products during primary metabolic pathways. Due to the synergistic interactions between the volatile and non-volatile compounds herbivorous insect pests decides to utilize any plant (De Jong and Stadler, 1999). Tannins and phenolics regarded as secondary defence metabolites influence insect behaviour (Schoonhoven et al., 1998), effectiveness of these compounds against herbivorous insect pest may vary (Wang et al., 2012).

Primary nutrients were thought to have little role in plant resistance, because most of these nutrients were understood to be used for the plant development and its growth (Frankel, 1969) but now nutrients are recognized to play an important role in insect host- plant selection process (Slansky, 1993; Jansson and Ekbom, 2002; Marazzi and Stadler,

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2005). Sometimes plant damage by insects correlates more with the nutrients (Chapman, 2003), than with the secondary plant metabolites (Louda and Mole, 1991). However, secondary plant substances/metabolites, collectively known as antiherbivoree compounds are important (Karban et al., 1997) to recognize suitable sites for the progeny (Renwick et al., 1992; Van Loon et al., 1992; Du et al., 1995; Stadler et al., 1995) and for the feeding behaviour of specialist insects because of the prime insect-sensitivity to nutrients (Thorsteinson, 1960; Berenbaum, 1995). Allelochemicals that are non-nutritional chemicals (Pedigo, 1996), either allomones or kairomones (Dhaliwal and Arora, 2003) produced by one species; they affect the growth behaviour or population biology of organism of another species (Whittakar, 1970; Pedigo, 1996). Allelochemicals are considered to be the major factors, which induce resistance in plants against insectpests (Renwick, 2001; Dhaliwal and Arora, 2003). The allomones consist of a wide variety of chemicals, like, terpenoids (sesquiterpene lactones and heliocides), phenolic compounds (protease-inhibitors, glycosidase-inhibitors and phytohema-glutinins), the lectins nitrogenous compounds (amino acids and amides); toxic seed lipids (fatty acids, acetylenic and allenic lipids, fluolipids and cyanolipids, saponins, lignins, tannins, silica contents) (Schoonhoven et al., 1998; Dhaliwal and Arora, 2003; Robards, 2003; Goncalves-Alvim et al., 2004; Dhillon et al., 2005), flavonoids, catechin, cyanidin, delphinidin and their glucosides, alkaloids, methyl ketones, gallic, venillic and salicylic acids, resorcinol, phloroglucinol and exudates of gosspol (Dhaliwal et al., 1993) however concentration and existence of these allelochemicals vary with respect to plant species and plants being attacked by insect pest species. Attack by insectpests usually cause induction of phenolics in plants (Dixon and Paiva, 1995, Somssich et al., 1996). According to Bi et al. (1997), activity of oxidative enzymes was incrased due to injury of cotton (Gossypium hirsutum L.) foliage. They further pointed out that there exist possitive association between oxidative enzymes and phenolic peroxidants (i.e., chlorogenic acid) and lipid peroxides. Phenolics are known to play important role in the host plant resistance (Dethier, 1970, Todd et al., 1971, Elliger et al., 1980, Stotz et al., 1999). They play important role in inhibition of oviposition, larval growth and survival of insect (Stotz et al., 1999). Tannins (complex polyphenols) are more prevalent in woody perennials than in herbaceous plants (Swain, 1979). They are considered as general feeding deterrents in plant insect interactions, therefore, play an

15 important role in chemical ecology and defense against insects (Hagerman and Butler, 1991). The behavior, development, and growth of insects are influenced by plant flavonoids (Hedin and Waage, 1986). The gossypol is an allelochemical (sesquiterpenoid phenol aldehyde) that cause reduction of the digestibility in herbivores through antibiosis mechanism of plant resistance in cotton (Syed et al., 2003; Du et al., 2004). Antibiosis or non preference behavior is shown toward a group of insect pest species (Stipanovic et al. 2006; Syed et al. 2003; Leghari et al., 2001). Weight and honeydew production of the invasive mealybug, P. solenopsis was influenced on tomato (Solanum lycopersicun), Hibiscus rosa-sinensis, and cotton (Gossypium sp.) that was greater on S. lycopersicum than H. rosa-sinensis and G. hirsutum. The amount of honeydew excreted by the first and second instar nymphs was not significantly different on the same host plant, however, there exist a significant variation between the third instar nymph and adult of P. solenopsis; amount of honeydew excreted by a single adult fed on H. rosa-sinensis was decreased from 3085.3μg to 572.0μg with in 2 weeks (Zhou et al., 2013). 2.13 Tolerance mechanism Tolerance refers to the ability of the host plant to withstand damage caused by herbivorous insect pest through some compensation regarding yield and quality of the produce (Ierusalimov, 1998; Tiffin, 2000). Physical injury of host plant tissue induces number of physical and biochemical changes in plants which are mostly defensive in nature. According to Korth (2003); Arimura et al. (2005); Frost et al. (2008), Arthropods attack cause mechanical injury and induce structural defenses in plants. Stotz et al. (2000) reported that phenolics accumulate in epidermis and phloem part of stem after physical injury, it means quantity of physical barriers and biochemical defenses increase to attack due to tolerance behavior in plants and production of physiological factors likewise, phenolics and terpenoids are arthropod attack based (Frankenstein et al., 2006). It is generally correlated to the plant vigor, regrowth of damaged tissues, resistance to lodging, ability to produce extra branches, consumption of non-vital parts by insects and compensation by growth of neighbouring plants (Pedigo, 1996). As tolerance is not likely to provide a high level of resistance, it could be useful in combination with other mechanisms of resistance (Strauss and Agrawal, 1999; Stowe et al., 2000).

16

In response to pest attack, plants undergo compensatory growth and reparation as well as restitution of their biochemical contents exhibiting tolerance against infesting insects due to provision of various kinds of compensatory processes/mechanisms (Gogi et al., 2010; Al-Shareef, 2011; El-Zalabani et al., 2012). According to Sarmah et al. (2011) weight of larva and cocoon was highly influenced by nitrogen and crude protein content of foliage. Attack of herbivorous arthropods modulate in infested plants various morphological and physiological changes (Hopkins and Huner, 2004) that include alteration in leaf area, number of leaves, dry weight, photosynthesis, chlorophyll, carbohydrates, water use efficiency, protein profile, wax deposition (barrier), accumulation of proline, activity of oxidative and lipid peroxidation enzymes (Ni et al., 2001; Heng-Moss et al., 2004; Znidarcic et al., 2008; Huang et al., 2013; Hussain et al., 2014), uptake of macro and micro-nutrients (Chapman et al., 2001; Wu et al., 2004; Al- Shareef, 2011) and production as well as volatilization of allelochemicals or secondary metabolites (Gogi et al., 2010; Al-Shareef, 2011). Mealybug infestation alters the physiological process in infested plants. Infestation on white and red wines decreased total polyphenols, anthocyanins and tannins under spectrophotometry and high performance liquid chromatography (Bordeu et al., 2011). Infestation on sugar cane altered the concentration of allelochemical, howevver total carbohydrates, reducing sugar, non reducing sugar, protein, ash and nitrogen contents were positively correlated, but crude fiber, fiber fraction, crude lipids, wax, silica, calcium, phenols, tannins and flavonoids were negatively correlated with mealybug infestation (Eid et al., 2011). In cotton infestation of mealybug caused an increase in lignin, cellulose and hemicellulose contents also an increase in defensive biochemicals of cotton i.e. phenolics and terpenoids were significantly increased up to 7 times (than control) within 0-3 hours after infestation in injured plants. Defensive enzymes i.e. phenyl ammonia lyase, polyphenol oxidase and peroxidase were also increased after mealybug feeding. Similarly, expression of thaumatin-like metallothionein and profilin genes was enhanced with the elicitation of plant defenses due to insect herbivory (Shafique et al., 2014). All these variations in infested plants result in tolerance mechanism of plants, initial infestation of P. solenopsis had no effect on chlorophyll content as well as on light utilization efficiency that might be due to compensatory photosynthesis (Huang et al., 2013). 2.14 Effect of plant resistance on P. solenopsis 17

Although Phenacoccus solenopsis has been established in about 24 countries of the world on several plants species (Fand and Suroshe, 2015) but level of incidence among all plant species is not similar due to mechanisms of plant resistance. Plant species including, Abelmoschus esculentus Linn., Capsicum annum Linn., Solanum melongena Linn., Solanum lycopersicum Linn., Punica granatum Linn., Psedium guajava Linn., Vites vinifera Linn., Hibiscus rosa-sinensis Linn., as well as various weeds (Tanwar et al., 2007; Nagrare et al., 2009; Vennila et al., 2010) serve as preferred host plants of P. solenopsis and carryover of pest to the economic crop during off season the cotton crop (Arif et al., 2009; Nagrare et al., 2009; Abbas et al., 2010; Vennila et al., 2010). Phenacoccus solenopsis originating from North America has co-evolved with several plants species and become a highly exotic polyphagous insect pest in about 24 countries of the world (Fand and Suroshe, 2015). Other than cotton crop, more than 200 plant species are directly utilized for feeding, oviposition and development of the pest (Abbas et al., 2005, 2010; Vennila et al., 2010; Arif et al., 2013). Its favorit host plants include, Abelmoschus esculentus Linn., Capsicum annum Linn., Solanum melongena Linn., Solanum lycopersicum Linn., Punica granatum Linn., Psedium guajava Linn., Vites vinifera Linn., ornamentals like Hibiscus rosa-sinensis Linn., as well as various weeds (Tanwar et al., 2007; Nagrare et al., 2009; Vennila et al., 2010) and serve as carryover of pest to the crop during off season of cotton (Arif et al., 2009; Nagrare et al., 2009; Abbas et al., 2010; Vennila et al., 2010). Infestation severity of P. solenopsis among plant species is not similar and plants indicate low to moderate levels of resistance due to the involvement of different mechanisms of plant resistance. Plant resistance mechanisms affect the food preference, infestation and population severity of pest attack; as well as biological parameters of phytophagous insect pest. According to Johnson-Cicalese et al. (1998) leaf surface play an important role in mealybug resistance, they further demonstrated that positive and significant correlation was found between leaf pubescence and mealybug infestation levels (Johnson-Cicalese et al., 1998). Type of plant may affect the biological parameters of P. solenospsis, developmental period of female mealy bug was rapid on G. hirsutum, whereas of males it was fast on H. rosasinensis (Mammoon-ul-Rasheed et al., 2012), adult female longevity and duration of life cycle on A. esculentus was 24.8 and 43.4 days respectively (Sahito and Abro, 2012). The duration of first, second, third instar, longevity of female and life cycle of P. solenospsis on H. rosa-sinensis was 9.8, 8.6, 5.8, 27.6 and 51.8 days 18 respectively. On A. esculentus developmental period of first and second instars was 5.6 and 4.5 days respectively, whereas pupal stage (4.3), male longevity (2.9d) and duration of life cycle (17.4 days) was 7.5, 4.4, 5.3, 3.2 and 20.4 days for first, second instar, longevity of female and life cycle respectively. The sex ratios were 1: 33.5 and 1: 10.2 days for male and female reared on A. esculentus and H. rosa-sinensis respectively Sahito and Abro (2012). According to Sana-Ullah et al. (2011), plants including Rosa indica, Jatropha curcus, Mangifera indica, Saraca indica, Ocimum basilicum and Bougainvillea spp (tested plant species) against CMB exhibited resistance and R. indica induced maximum mortality in 1st instar nymphs (70-90%), prolonged nymphal duration and decreased fecundity. Nymphal duration was prolonged by 20-23 days when nymphs were fed on rose, jatropha, mango and ashoke plant whereas the same was shortened (16-17 days) when nymphs were fed on cotton, shoeflower and silvery. Effects of rose and jatropha feeding resulted in declined fecundity of CMB to (100 to 200eggs/ovisac/female) as compared with shoeflower producing (>400 eggs/ovisac/female).

19

CHAPTER 3 OBJECTIVE 1

3.1 Determination of natural incidence of P. solenopsis on different host plants from cotton and central mixed zone of Punjab, Pakistan Abstract Cotton mealybug (CMB), P. solenopsis Tinsley (Hemiptera: Pseudococcidae) is an important sucking insect pest with polyphagous feeding nature. Incidence of P. solenopsis was documented among 25 different plant species in cotton and mixed cropping zone of Punjab, Pakistan. Significant variations in plant species were recorded for population and infestation of P. solenopsis. Infestation of mealybug among the tested plant species ranged from 5.0 to 51.5 percent. Least infestation was observed on D. arvensis and C. album that was at par with C. morale, C. didimus, A. aspera, Eclipta prostrate and C. bonariensis. High infestation (51.5%) was observed on T. partulacastrum that was at par with both P. oleraceae and Euphorbia prostrate (45%) followed by G. hirsutum. Population density ranged from 11.6 mealybugs/6cm twig on D. arvensis that was at par with A. aspera (16.0 CMB/6cm twig), whereas maximum population (141.0 CMB/6cm twig) were recorded on T. partulacastrum that was at par with H. rosa-sinensis (140.0 CMB/6cm twig), W. somnifera (137.7 CMB/6cm twig), S. melongena (137.0 mealybugs/6cm twig), E. prostrate (132.7 mealybugs/6cm twig) and P. oleraceae (131.0 mealybugs/6cm twig). Present studies were carried throughout the year in case of perrinial plants but during the growing season for dicidous plant. However, plants including L. camara, H. rosa-sinensis, C. inerme, G. hirsutum, C. morale, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, C. album, A. spinosus, T. portulacastrum, P. oleracea, T. terrestris, E. prostrate and P. hysterophorus supported mealybug population for >3 months thus were considered as attractive plant of P. solenopsis. Remaining plant species were considered as incidental plant species because they supported mealybug population for <3 months. Clusters were made on the basis of infestation and population level of P. solenopsis among the selected plant species. Cluster-1 comprised of 13 plant species including H. annuus, H. rosa-sinensis, A. spinosus, W. somnifera, S. melongena, A. esculentus, T .terrestris, C. frutescens, E. prostrate, G. hirsutum, L. camara, P. oleracea and T. partulacastrum showed similarity with each other for mealybug infestation and population. Cluster-2 consisted of a group of three plant species including C. arvense, C. inerme and P. hysterophorus while cluster-3 possessed plant species including D. arvensis, E. prostrate, C. arvensis, C. didimus, C. bonariensis, C. album, C. morale, L. nudicaulis and A. aspera respectively. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-2 demonstrated maximum diversity (96.0) against the members of cluster-1 for infestation and population of P. solenopsis. In this study, first Principal component (PC) was taken having Eigenvalues ≥1. Results depicted that first PC expressed 82% of the total variability amongst the selected plant species of P. solenospsis as compared with second PC (18%). Mealybug infestation and population demonstrated positive factor loadings on PC1. On PC2 infestation expressed positive but population established negative factor loadings. So special consideration and timely awareness to the farmers should be initiated to avoid the population build of P. solenopsis from attractive plants to the major economic crop whereas incidental plants should be investigated for plant traits imparting role to keep pest population under control.

20

Introduction

Mealybugs are geographically present throughout the world on numerous plant species. P. solenopsis is also one of the mealybug species, its existence in Pakistan was noticed for the first time during 2005 (Abbas et al., 2005). It is an invasive insect pest that was reported for the first time on Boerhavia spicata Choisy and Kallstroemia brachystylis Vail weeds (Tinsley, 1898), then on Ambrosia sp., (USDA, 1978) and cotton (Fuchs et al., 1991). Both nymphs and adults of cotton mealybug cause damage by sucking cell sap, staining cotton lint, reducing its quality (Charleston et al., 2010) and affecting photosynthetic activity of plants due to development of sooty mold fungus on honey dew secretions (Saeed et al., 2007). Infested plants with P. solenopsis show range of symptoms depending upon plant species and severity of attack but commonly damage is done by extracting sap from the plant, injection of toxic saliva and excretion of honey dews that serve as substrate for sooty mould development (Miller et al., 2002; Saeed et al., 2007) and defoliation of leaves and can serve indirectly as vectors of pathogens (Culik and Gulan, 2005). Phenacoccus solenopsis remain active throughout the year in Pakistan and peak population of mealybug was recorded during August and September when temperature and humidity ranged 28-33.5˚C and 59-78%, respectively (Shahid et al., 2012). Cotton mealybug has significant positive correlation with temperature and sunshine (Suresh and Kavitha 2008; Dhawan et al., 2009; Hanchinal et al., 2010; Shahid et al., 2012) and is capable to tolerate temperatures from 0-45°C (Sharma, 2007). According to Singh and Kumar (2012), population dynamics of Phenacoccus solenopsis (Tinsley) was higher during the month of October on cotton (Gossypium hirsutum L.) and okra (Abelmaschus esculentus L.) in India. They further stated that maximum population of mealybug was observed on tomato (Lycopersicon esculentum L.) and potato (Solanum tuberosum L.) during the month of February. Researchers surveyed the only cotton growing areas instead of comparing cotton growing areas and mixed cropping areas. Sahito et al. (2011) surveyed different districts of Sindh for incidence and severity of cotton mealybug. They explained that mealybug infestation was observed in all cotton growing districts of Sindh. In Brazil, da Silva (2012) explained that there was high infestations of cotton mealybugs in cotton growing regions of the Bahia, Agreste and Semi-arid of the Paraiba State. Arif et al. (2009) surveyed cotton growing areas of southern Punjab to investigate the host plants of cotton

21 mealybug. They described a list of 154 plant species were recorded comprising of numerous crops, weeds, vegetables, ornamental plants and economic fruits. They further explained that economic damage was observed on these plant species. Keeping in view the present research was carried out by comparing population of P. solenopsis in different districts, on different host plants to find out the infestation and population level of pest among tested plant species. Material and methods Districts of southern Punjab consisting of Vehari (29.36°N,71.44°E), Lodhran (29.54°N,71.63°E), Multan (30.2°N, 71.45° E), Bahawalpur (29.50°N, 72.50°E), Faisalabad (31.47°N, 73.40°E) and Sahiwal (30.40°N, 73.06°E) were surveyed to record incidence of mealybug on different plant species during 2007-08. In Multan, Vehari, Lodhran and Bahawalpur, there is typical cotton monocropping pattern, but in Sahiwal and Faisalabad agricultural regions, crop rotation is followed every year, normally cotton and maize are the main crops in these areas; while, other crops are planted as a mosaic pattern among cotton and maize farms in a non-regular arrangement. Numerous weeds, fruits, vegetables, economic crops and ornamentals are grown adjacent to water channels and cultivated fields. From each districts, twenty five villages and from each village 10 sites including farmers fields, parks and schools lawns were surveyed and data was pooled. Each site was considered as one replication. Incidence of P. solenopsis was recorded on 25 host plant species from each site, there details are given in (Table 1.1). Five plants from each plant species were randomly selected in each replication to investigate the infestation and population of P. solenopsis from 6 cm twig. Plants were bent and were shaken on a white paper with the help of camel hair brush and mealybug densities were estimated by counting individuals on each plant species. Special attention was given that none of the selected plants were treated with pesticides while recording the data. To study the seasonal population dynamics and carryover of cotton mealybug (P. solenopsis) on economic crops, vegetables and ornamental plants were examined throughout the year. Sample size varied depending on the size and nature of plant species. The data were presented as population for both adults and nymphs of mealybug per 6 cm twig. Based on the mealybug density and duration of infestation plant species were categorized into resistant and susceptible host plants. Plant species (both cultivated and uncultivated) supporting mealybug infestation for more than three months were considered as susceptible host plant while the others supporting P. solenopsis for less than three months during the year were considered as incidental host plants.. 22

Statistical analysis The data collected on infestation and population of cotton mealybug were subjected to uni-variate analyses by using Minitab software (Sneath and Sokal, 1973). The sites were pooled and completely randomized design was used for data analysis. The means of significant treatments were compared with Tukey’s honestly significant difference (HSD) (Danho et al., 2002). Dendrogram and genetic similarity among the plant species were also generated using the Jaccard’s Coefficient of similarity expressed as Euclidean genetic distances. Similarly, cluster analysis was used to sort the plant species into their appropriate groups with minimum error by using Statistical Package for Social Sciences (SPSS) and Minitab softwares (Sneath and Sokal, 1973). The data was also subjected to principle component analysis using Minitab software for determining the variation in infestation and population of cotton mealybug among selected plant species.

23

Figure 3.1.1 Geographic location of studied districts on the Map of Pakistan and Plate showing the studied area.

24

Table 1.1: List of plant species selected during study. Sr. No Common name Botanical name Family name Sr No Common name Botanical name Family name 1 Lantana Lantana camara Verbenaceae 14 Chilies Capsicum frutescens Solanaceae 2 Peelidhodak Launea nudicaulis Euphorbiaceae 15 Hazardani Euphorbia prostrate Euphorbiaceae 3 Krund Chinopodium morale Chenopodiaceae 16 Brinjal Solamum melongena Solanaceae 4 Lehli Convolvulus arvensis Convulvulaceae 17 Puthkanda Achyranthes aspera Amaranthaceae 5 Parthenium Parthenium hysterophorus Asteraceae 18 Bathu Chenopodium album Chenopodiaceae 6 Aksun Solanaceae 19 Sunflower Helianthus annuus Asteraceae 7 Cholai Amaranthus spinosus Amaranthaceae 20 Tandla Digera arvensis Amaranthaceae 8 Janglihaloon Coronopus didimus Brassicaceae 21 Qulfa Portulaca oleracea Portulacaceae 9 Itsit Trianthema portulacastrum Aizoaceae 22 Daryiboti Eclipta prostrate Asteraceae 10 Bakhra Tribulus terrestris Zygophyllaceae 23 Gardenia Clerodendron inerme Amaranthaceae 11 Chinese rose Hibiscus rosa-sinensis Malvaceae 24 Cotton Gossypium hirsutum Malvaceae 12 Okra Abelmoschus esculentus Malvaceae 25 Leh Cirsium arvense Asteraceae 13 Loosenbooti Conyza bonariensis Asteraceae - - -

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Results The results of present study regarding infestation and population of cotton mealybug on different host plants in the tested localities viz. Bahawalpur, Lodhran, Multan, Vehari (cotton zone), Sahiwal and Faisalabad (mixed cropping zone) have been described under following sub-sections. 3.2 Percentage infestation of cotton mealybug on the tested host plants Analysis of variance regarding the effect of plant species on the mealybug infestation is given in Table 3.2.1 which revealed that mealybug infestation among tested plant species differed significantly (F= 197.7; df= 24; P <0.05). Mean comparison regarding infestation of cotton mealybug among tested plant species by using Tukey Honesty Significant Difference test at P=0.05 revealed that infestation of mealybug among the tested plant species ranged from 5 to 51.5%. Least infestation was observed on D. arvensis and C. album that was at par with C. morale (6.0%), C. didimus (8.0%) followed by A. aspera, Eclipta prostrate and C. bonariensis (9.0% infestation). High infestation (51.5%) was observed on T. partulacastrum that was at par with both P. oleraceae and Euphorbia prostrate (45%) followed by G. hirsutum (39.0). Remaining plants had intermediate infestation between 11.0-29.0%. TABLE 3.2.1: ANOVA parameters regarding infestation level of P. solenopsis on twenty five selected plant species in different districts. SOV df SS MS F P Plant species 24 172.3 7.18 197.6 0.000** Error 50 1.74 0.03 Total 74 174.1 SOV= Source of variance, df= degree of freedom, SS= Sum of square, MS= mean sum of square, **= highly significant difference at P=0.05

25

Figure 3.2.1: Mealybug infestation (%±SE) among selected plant species. Standard error bars above indicate significant differences (Tukey HSD test; P<0.05) in mealybug infestation among plant species. 3.3 Population of cotton mealybug on the tested host plants

Analysis of variance regarding the effect of plant species on the cotton mealybug population is given in Table (3.2.2) which revealed that cotton mealybug population level among tested plant species differed significantly among each other similarly population (F =128.7; df=24; P= 0.000). Mean comparison regarding the effect of tested plant species on the population of cotton mealybug by using Tuckey Honesty Significant Difference test at P=0.05 revealed that population of cotton mealybug among the tested plant species varied from 11.67 to 141.0 numbers per 6 cm twig. Least population 11.67- 56.67 was recorded on C. morale, C. arvensis, L. nudicaulis, C. didimus, C. bonariensis, C. album, D. arvensis, E. prostrate and A. aspera but high population (91.6-141 CMB/6 cm twig) was recorded on L. camara, H. rosa-sinensis, W. somnifera, E. prostrate, S. melongena, A. esculentus, C. arvense, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, P. hysterophorus and H. annuus (Figure 3.2.2).

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Table 3.2.2: ANOVA parameters regarding population of P. solenopsis on twenty five selected plant species in different districts. SOV Df SS MS F P Treatment 24 31959.4 1331.6 128.7 0.000** Error 50 517.7 10.3 Total 74 32477.1 SOV= Source of variance, df= degree of freedom, SS= Sum of square, MS= mean sum of square, **= highly significant difference at P=0.05

Figure 3.2.2: Cotton mealybug population (n±SE=mealybug i.e., number±standard error) among selected plant species. Bars above indicate significant differences (Tukey HSD test; P<0.05) in mealybug popution among plant species. 3.4 Instar wise proportion of cotton mealybug among selected plant species From the whole population, instar wise population of mealybug on tested plant species revealed that population of first instar was maximum than second and third instars but ovisaced females had least population. Population of first instar of cotton mealybug ranged from 12.3 to 61.0. The population of first instar i.e. (>30 CMB) was on L. camara, H. rosa-sinensis, C. arvensis, L. nudicaulis, W. somnifera, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. frutescense, A. spinosus, C. inerme, T. terrestris, P. hysterophorus and H. annuus. The population of first instar i.e. (<30 CMB) was recorded on C. morale, C. didimus, E. prostrate, C. album, G. hirsutum, T. partulacastrum, P. oleraceae, D. arvensis, E. prostrate and A. aspera.

27

Population of second instar ranged from 10 to 43.4 nymphs per 6cm twig among the tested plant species. More than 20 nymphs of second instar per 6 cm twig was recorded on L. camara, C. arvensis, L. nudicaulis, W. somnifera, C. bonariensis, A. esculentus, C. arvense, C. frutescense, A. spinosus, C. inerme, T. terrestris and H. annuus. However, C. morale, H. rosa-sinensis, C. didimus, E. prostrate, S. melongena, C. album, G. hirsutum, T. partulacastrum, P. oleraceae, D. arvensis, E. prostrate, P. hysterophorus and A. aspera demonstrated a population density of ≤20 second instar nymphs per 6cm twig. Third instar of mealybug population among selected plant species ranged from 3 to 9.7 nymphs per 6cm twig being minimum on C. morale, C. didimus, E. prostrate, C. album, T. partulacastrum. Maximum was on L. camara, H. rosa-sinensis, L. nudicaulis, C. bonariensis, A. esculentus, C. frutescense, P. oleraceae and T. terrestris. All the remaining plants had intermediate level of mealybug population. Ovisaced female of mealybug recorded on selected plant species ranged from 1.5 to 5.3 being minimum 1.5 to <3.0 on D. arvensis, C. morale, C. didimus, A. spinosus but maximum on L. camara, H. rosa-sinensis, L. nudicaulis, C. bonariensis, A. esculentus, C. frutescense, C. inerme, P. oleraceae, T. terrestris, E. prostrate, P. hysterophorus and H. annuus ≥3.0 ovisac females per 6 cm twig (Figure 3.2.3).

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Figure 3.2.3: Instar wise cotton mealybug population (n±SE) among selected plant species. Standard error bars above indicate significant differences (Tukey HSD test; P<0.05) in mealybug population among plant species.

29

3.5 Categorizing cultivated host plants of cotton mealybug into incidental and susceptible hosts On the basis of cotton mealybug population and its duration of existence among cultivated plant species, tested host plants were categorized into the susceptible and incidental hosts (Figure 3.2.4). L. camara, H. rosa-sinensis, C. inerme and G. hirsutum supported population build up of mealybug for more than 9 months and were considered as susceptible host plant species. On the other hand A. esculentus, C. frutescence, S. melongena and H. annuus supported CMB population for a minimum period of only 3 months and were considered as incidental host plants. Incidental plants also had less mealybug population (≤5 CMB per 6cm twig) as compared with susceptible host plants (≥5 but ≤10 CMB per 6cm twig) (Figure 3.2.4).

Figure 3.2.4: Month wise average cotton mealybug population (n±SE) and mealybug supporting period by tested plant species (cultivated) (S and I indicate susceptible and incidental plants, respectively). 3.6 Categorizing un-cultivated/weed plants of cotton mealybug into incidental and susceptible hosts On the basis of cotton mealybug population among the uncultivated plant species and the duration of their existence, C. morale, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, C. album, A. spinosus, T. portulacastrum, P. oleracea, T. terrestris, E. prostrate and P. hysterophorus were categorized as susceptible host plants of mealybug except D. arvensis and A. aspera. All susceptible host plants supported mealybug for a period of more than 3 months as well as sustained reasonable mealybug population (4 CMB per 6cm twig) (Figure 3.2.5).

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Figure 3.2.5: Month wise average cotton mealybug population (n±SE) and mealybug supporting period on (un-cultivated/weeds) plant species(S and I indicate susceptible and incidental plants, respectively).

3.7 District wise infestation and population of cotton mealybug on different plant species Analysis of variance revealed that percent infested plants (df= 24; P= ≤0.05) and populations of mealybug (df= 24;P= ≤0.05) varied significantly for tested host plant species (Table 3.2.3). Table 3.2.3: Analysis of variance regarding mealybug infestation and population among the selected districts. Source Location Df F-value P-Value Infestation Faisalabad 24a/48b 7.01 0.001** Lodhran 24a/48b 6.1 0.000** Bahawalpur 24a/48b 5.54 0.005** Multan 24a/48b 9.64 0.003** Sahiwal 24a/48b 6.8 0.003** Vehari 24a/48b 7.43 0.002** Population Faisalabad 24a/48b 28.0 0.003** Lodhran 24a/48b 40.5 0.04* Bahawalpur 24a/48b 44.08 0.003** Multan 24a/48b 51.2 0.02* Sahiwal 24a/48b 48.2 0.000** Vehari 24a/48b 49.5 0.003** df= a/b: degree of freedom for tested plant species/Error degree of freedom; P value= probability value; *= significant at probability value of 5%; **= highly significant at probability value of 5%

3.8 Infestation of cotton mealybug on the tested host plants in selected districts Mean comparison regarding percentage infestation of mealybug among the tested plant species by using Tukey Honesty Significant Difference test at P value <0.05 is given in (Figure 3.2.6). Mealybug infestation among the tested plant species in different

31 districts varied from 32.7 to 49.3%. Least infestation of mealybug on plant species existing in Faisalabad was recorded (32.7%) that was at par with (37.6%) in Sahiwal district, while infestation in cotton zones comprised of Multan (49.3%), Vehari (48.8%) followed by Bahawalpur (43.2%) and Lodhran (42.5%) (Figure 3.2.6).

Figure 3.2.6: Mealybug infestation (%±SE) in selected districts. Standard error bars above indicate significant differences (Tukey HSD test; P<0.05) in mealybug infestation. 3.9 Population of cotton mealybug on the tested host plants Mean comparison regarding population of mealybug among the tested plant species by using Tukey Honesty Significant Difference test at P value <0.05 is given in (Figure 3.2.7). Mealybug population among the tested plant species in different districts varied from 37.7 to 110.8 CMB per 6 cm twig. Least population (37.7 CMB per 6cm twig) was recorded among tested plant species existing in Faisalabad that was at par with Sahiwal district. Higher population of mealybug (80.9-110.8 CMB per 6cm twig) was observed on plant species occurring in Multan, Bahawalpur, Lodhran and Vehari districts (Figure 3.2.7).

32

Figure 3.2.7: Cotton mealybug population (n±SE) in selected districts. Bars above indicate significant differences (Tukey HSD test; P <0.05) in mealybug population. 3.10 Seaonal population dynamics of mealybug on selected plant species Figure 3.2.8 show seasonal population dynamics of cotton mealybug on selected plants species during different months of the year. Mealybug population on L. camara was initiated during the month of February and it gradually increased till May (15.0 CMB per 6cm twig) but it declined during June, July (≤4.0 CMB per 6cm twig) and again increased during August and reached to its peak population during September (35.0 CMB per 6cm twig), however it was decreased from October to December. On L. nudicaulis mealybug population appeared in the month of February and increased abruptly till May, when it got its peak population (3.0 CMB per 6cm twig) later on it decreased during the months of June, July till August when population was single CMB per 6cm twig. Cotton mealybug population on C. arvensis initiated during the month of February and gradually increased till May but it declined during June, July and again increased during August and reached to its peak population (34.6 CMB per 6cm twig) during September, it was decreased during October and November till December, however C. arvensis sustained mealybug population throughout the year. Cotton mealybug population appeared on H. rosa-sinensis during the month of January, February and gradually increased till June to its peak (26 CMB per 6cm twig) but it declined during July and again increased during August and reached to its second highest peak population during September (29 CMB per 6cm twig), then it was decreased during October and Novemeber till December. Mealybug population on C. morale was initiated during the month of February and gradually increased till June but it declined during July and again

33 increased to its peak (10 CMB per 6cm twig) during September that was declined later on. However it supported mealybug population for eight months of the year (March- October) (Figure 3.2.8). On W. somnifera mealybug population was recorded throughout the year, because pest population appeared on W. somnifera initiated during the month of January and increased gradualy till it attained its initial peak in May (20 CMB per 6cm twig), then population declined till July and again increased during August and reached to its peak population during September (40 mealybug per 6cm twig), however it was decreased during October and November till December months of the year. Mealybug population on C. didimus initiated during the month of January and increased till April with peak population (9 CMB per 6cm twig), later on population was decreased and plant was unavailable to CMB in the field till November and December (Figure 3.2.8).

Euphorbia prostrate also supported mealybug population throughout the year. Mealybug population on E. prostrate initiated during the month of February and increased till May (25 CMB per 6cm twig), later on population was decreased till July and again increased during August and reached to its peak population during September, however it was decreased during October and Novemeber till December months of the year. On C. bonariensis mealybug appeared during the months of June (1.5 CMB per 6cm twig). Population increased sharpely during September (4 CMB per 6cm twig) and during October mealybug population reached to its peak (6 CMB per 6cm twig) that was declined later on. Cotton mealybug population on S. melongena initiated during the month of May and increased till it reached to its peak population during August, September (23 CMB per 6cm twig). Mealybug population on A. esculentus initiated during the month of April and increased gradually till it reached to its peak population during August (35 CMB per 6cm twig) (Figure 3.2.8).

On C. arvense plant P. solenopsis population initiated from February and remained till September. Increase in population on it was slow till the month of May. After May population abruptly increased and attained peak population during September (7 CMB per 6cm twig). Mealybug population on C. album initiated from February and remained till September. Increase in population on it was slow till the month of May- June. After this period population further increased and attained peak population during September (8 CMB per 6cm twig). Mealybug population on Capsicum sp., remained from May to September. Initial population was very low (4 CMB per 6cm twig) that was 34 increased to its peak population during August (16 CMB per 6cm twig). Decline inpopulation was recorded during September on this plantspecies upto 9 CMB per 6cm twig. Clerodendron inerme supported mealybug for a longer period from February to November. Initial population was very low from February to the month of July (4 CMB per 6cm twig) that was increased to its peak population during August and September (30 CMB per 6cm twig). Decline in population was recorded from September to onward. Trianthema portulacastrum supported mealybug for a longer period from February to November. Initial population was very low from February to the month of July (5 mealybug per 6cm twig) that was increased to its peak population during September (18.5 mealybug per 6cm twig). Decline in population was recorded from September to onward. Portulaca oleraceae supported mealybug for a longer period from March to November. Initial population was very low from February to the month of July (5 mealybug per 6cm twig) that was increased to its peak population during August and September (15 and 20 CMB per 6cm twig respectively). Onward from September to November, there was decline in population of cotton mealybug (Figure 3.2.8). Tribulus terrestris supported cotton mealybug for a longer period from February to November. Initial population was very low from February to the month of July (6 CMB per 6cm twig) that was increased to its peak population during August and September (26 CMB per 6cm twig). Decline in population was recorded from October to onward. Digeria arvense supported mealybug for a very short duration and its population also remained low even during the peak density period of mealybug during August and September i.e., 7.0 CMB per 6cm twig.

On E. prostrate mealybug spent very short duration i.e., from February to July and its population also remained very low. Peak density was during April (5 CMB per 6cm twig) and then its population was declined till the month of June (2.0 CMB per 6cm twig). On A. aspera plant mealybug spent very short duration i.e., from March to May and its population also remained ≤5 cotton mealybug/6cm twig. Peak density was during April (4.0 cotton mealybug per 6cm twig) and then its population was declined till the month of June (2 CMB per 6cm twig). Helianthus annuus supported mealybug population during the spring season of March, April, however its peak population was during the month of June (50 CMB per 6cm twig). After this population was decreased to 20 cotton mealybugs per plant, however there was slight increase during August. After this period plant was not available in the field and growing period of plant was completed (Figure 3.2.8).

35

Figure 3.2.8: Seasonal occurrence of mealybug population on selected plant species.

3.11 Cluster analysis among plant species on the basis of mealybug population and infestation Twenty five plant species were categorized into three different clusters in dendrogram with the help of cluster analysis (Figure 3.2.9). Clusters were made on the basis of infestation and population level of P. solenopsis among the selected plant species. Cluster-1 comprised of 13 plant species including H. annuus, H. rosa-sinensis, A. spinosus, W. somnifera, S. melongena, A. esculentus, T. terrestris, C. frutescens, E. prostrate, G. hirsutum, L. camara, P. oleracea and T. partulacastrum showed similarity with each other for mealybug infestation and population. Cluster-2 consisted of a group of three plant species including C. arvense, C. inerme and P. hysterophorus while cluster-3 possessed plant species including D. arvensis, E. prostrate, C. arvensis, C. didimus, C. bonariensis, C. album, C. morale, L. nudicaulis and A. aspera (Table 3.2.4). The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-2 demonstrated maximum diversity (96.0%) against the members of cluster-1 for infestation and population of P. solenopsis (Table 3.2.5).

36

3.12 Principal component analysis In this study, first Principal component (PC) was taken having Eigenvalues ≥1. Results depicted that first PC expressed 82% of the total variability amongst the selected plant species of P. solenospsis as compared with second PC (18%) (Table 3.2.6). Mealybug infestation and population demonstrated positive factor loadings on PC1. On PC2 infestation expressed postive but population established negative factor loadings (Table 3.2.6).

Dendrogram Complete Linkage, Euclidean Distance

0.00

y

t 33.33

i

r

a

l

i

m

i S Cluster-1 Cluster-3 66.67 Cluster-2

100.00 a s e s s s a a s e e e e s e s s a s s s e r ri s u u si r n u t m a m s u l li si r si si u t m a t n s n n fe e t ra tu e ru n rm r ra u n e n n ra u s e o n e i g n t c t e o a e p e e im t b m re c n a n n n le s su a s v e h o ic i s v v d s l ca r s i . i u o r r a r in p m r a r r i o a e e p s m lo c r i le c a . o . d a . a a d r . L. t t s H - o e s p h a . C r u n A . . . p C . ru . sa s e . . o l C e C n o C C . T f A . m . E G . tu t . b D E . ro . A P r s L . C . W S a y C p h H . . T P Observations Figure 3.2.9: Cluster diagram of the selected plant species on the basis of infestation and population of mealybug. Table 3.2.4: ANOVA parameter for cluster and cluster membership among infestation and population of P. solenopsis among selected host plants. Independent d.f F P Final Cluster Centers variables Cluster-1 Cluster-2 Cluster-3 H. annuus, H. C. arvense, C. D. arvensis rosa-sinensis, A. inerme, and P. E. prostrate, spinosus, W. hysterophorus, C. arvensis, C. somnifera, S. didimus, C. melongena, A. bonariensis, C. esculentus, T album, C. morale, .terrestris, C. L. nudicaulis, A. frutescens, E. aspera prostrate, G. hirsutum, L. camara, P. oleracea, and T. partulacastrum Infestation% 2/24 7.6 0.00 26.9 14.7 19.0 Population 2/24 9.0 0.00 127.7 96.7 90.0

37

Table 3.2.5: D2 distance among different clusters.

Cluster-1 Cluster-2 Cluster-3 Cluster-1 0.000 Cluster-2 96.0 0.000 Cluster-3 33.3 63.5 0.000 Table 3.2.6: Principal component analysis regarding population and infestation of P. solenopsis among selected host plants.

PC1 PC2 Eigenvalue 1.6 0.36 of total variance 0.82 0.18 Cumulative variance % 0.82 1.00 Factor loading by various biochemical traits Variable PC1 PC2 Infestation% 0.70 0.70 Population 0.70 -0.70 Discussion Understanding of population dynamics of insect pests is very useful to devise for their sustainable management program. Various factors including cropping pattern and intensity of the cropping system affect the insect pest population. Based on survey results of present study, it was found that mealybug population and infestation was higher in the fields of cotton growing districts including Multan, Bahawalpur, Vehari and Lodhran as compared with mixed cropping zones districts of Faisalabad and Sahiwal. Cotton mealybug infestation in Multan was 49.3% while in Faisalabad it was 32.7%. Reason for increase in pest infestation was attributed to mono-cropping pattern, prolonged growing season of cotton and repeated cultivation of cotton year after year in the cotton growing districts. Host plants in cotton fields provide food for cotton mealybug and they are shifted to the next season crop without any break in their chain and life cycle. In this way incidence and severity of pest gradually increased in that locality because monocropping cotton cultivation promot mealybug and other insect pest pressure as compared with polyculture (Andow, 1991; Coll and Bottrell, 1994). Population dynamics of mealybug differed with respect to plant species. Result revealed that population of cotton mealybug among the tested plant species varied from 11.67 to 141.0 numbers per 6 cm twig. Least population 11.67-56.67 was recorded on C. morale, C. arvensis, L. nudicaulis, C. didimus, C. bonariensis, C. album, D. arvensis, E. prostrate and A. aspera but high

38 population (91.6-141 CMB per 6 cm twig) was recorded on L. camara, H. rosa-sinensis, W. somnifera, E. prostrate, S. melongena, A. esculentus, C. arvense, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, P. hysterophorus and H. annuus. The reason was that most of the preferred host plants were evergreen and summer season plants instead of deciduous plants. The results are partially supported by Singh and Kumar (2012), according to them population dynamics of Phenacoccus solenopsis (Tinsley) was higher on cotton (Gossypium hirsutum L.) and okra (Abelmaschus esculentus L.) during the month of October, however it was higher on tomato (Lycopersicon esculentum L.) and potato (Solanum tuberosum L.) during the month of February. The variation in results may be due to difference in plant material and environmental conditions. Among total 25, the 14 plant species were uncultivated plant species (weeds) i.e., C. morale, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, C. album, A. spinosus, T. portulacastrum, P. oleracea, T. terrestris, E. prostrate and P. hysterophorus they provided food, shelter and sustained cotton mealybug for most of the studied period. Cultivated plants supported for less period because they were harvested for economic use. Based on the results of present study it was found that Withania somnifera and Euphorbia prostrate supported mealybug almost throughout the year. Peak population of mealybug on W. somnifera was recorded (40 mealybug per 6cm twig) during September, whereas on E. prostrate (25 CMB per 6cm twig) during May. Evergreen plants provide regular food supply and ground covering plants protect the mealybug from the climatic extremes. Such plants result in carryover of mealybug and other insectpests to the next season economic crop (Mohyuddin et al. 1989; Rafiq et al., 2008; Arif et al., 2009; Abbas et al., 2010). Plant species including Digeria arvensis was resistant to cotton mealybug, P. solenopsis and supported pest for a minimum duration. For proper management of cotton mealybug special attention should be given on eradication of susceptible host plants of cotton mealybug to reduce mealybug pest pressure on cotton because through better management of weed plants and mealybug, there will be reduction of pesticide use on cotton These studies are helpful to understand the status of host plant species and time- related population dynamics of mealybug. There is also dare need to identify the genetic make up of resistant plants to identify resistant traits against mealybug (especially in Digeria arvensis) and their manipulation into economic crops through biotechnological approaches in future. 39

CHAPTER 4 OBJECTIVE 2

4.1 Assesment of antixenosis mechanisms of resistance in different plant species for Phenacoccus solenopsis Under this objective, physico-morphic and biochemical basis of antixenosis mechanisms of resistance were investigated. The details of the study are as under. Objective 2a 4.1.1 Physico-morphic based antixenosis mechanism of resistance in selects host plants for P. solenopsis Abstract In order to investigate the antixenosis mechanism of resistance in plant species, morphological traits of the selected plant species and attractiveness index of P. solenopsis were investigated. Significant variations among tested plant species toward the attractiveness of P. solenopsis (p < 0.05) were determined. G. hirsutum, E. prostrate, H. annuus, P. oleraceae, W. somnifera, L. camara and P. hysterophrous were categorized as attractive (attractive index ≥1) while D. arvensis, C. bonariensis and L. nudicaulis proved resistant plant species toward P. solenopsis as compared with H. rosa-sinensis kept as standard control. Physico-morphic traits of the selected plant species revealed that trichome density, trichome length, leaf area and leaf thickness had a positive correlation with mealybug attractiveness. Cluster analysis revealed that cluster-1 comprised of three plant species including L. camara, H. annuus and G. hirsutum demonstrating final cluster center readings of 225.0 trichomes/cm2, 1.12 µm, 62.3 cm2, 2.6 µm and 0.95 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively. Cluster-2 consisted of eight plant species including C. inerme, C. arvensis, C. didimus, H. rosa-sinensis, S. melongena, W. somnifera, A. esculentus and T.terrestris describing final cluster center readings of 22.3 trichomes/cm2, 1.04 µm, 12.2 cm2, 1.7 µm and 0.53 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively; while cluster-3 possessed a group of fourteen plant species including E. prostrate, A. spinosus, P. hysterophorus, E. prostrate, P. oleracea, T. portulacastrum, C. frutescens, L. nudicaulis, C. arvense, C. morale, C. album, A. aspera, C. bonariensis and D. arvensis with cluster center readings of 2.8 trichomes/cm2, 0.6 µm, 0.45 cm2, 0.77 µm and 0.29 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-2 demonstrated maximum diversity (D2= 208.9) against the members of cluster-1 for the most of the studied morphological traits. Principal component analysis results depicted that first two PCs expressed 73% of the total variability amongst the selected plant species for P. solenospsis while other PCs contributed only about 27% of the total variability. PC1 contributed maximum variability (52%) following PC2 (20%), PC3 (12%), PC4 (12%) and PC5 (3.4%). The morphological traits like trichome density, leaf thickness, leaf area and trichome length explained positive factor loadings on PC1. These morphological demonstrated positive factor loadings on PC2 but trichome density and trichome length demonstrated negative factor loadings on PC2 and leaf thickness, leaf area and trichome length described negative factor loadings on PC3. These results indicated that physico- morphic traits of plant species play an important role in attractiveness index of mealybug.

40

Introduction

Plants possess different phenotypic and biochemical modifications which enable plants to avoid or recover the effects of insect pest attacks (Heng-Moss et al., 2002; Rangasamy et al., 2006) and may have either constitutive or induced effect on phytophagous insect pest (Karban and Agrawal, 2002; Traw and Dawson, 2002). Non- preference or antixenosis, antibiosis and tolerance are three mechanisms of plant resistance (Painter, 1951; Felkl et al., 2005). Antixenosis property exhibited by plant is due to availability of certain morphological structures, as well as allomones or deficiency of some kairomones or imbalance between allomones and kairomones (Feeny et al., 1983; Panda and Khush, 1995; Gogi et al., 2010). Population of pest varies from plant to plant that may be due to external or internal physiology of the plant because plants have ability to alter the behavior of feeding insect (Karban and Baldwin, 1997) through accumulation and excretion of toxic exudates or creates hindrance against insect pest due to physicomorphic traits (Stadler, 2000; Harota and Kato, 2001; Goncalves-Alvim et al., 2004), because thick waxy cuticular layer works as a defense against herbivory of insect pests (Taiz and zeiger, 1998). These features impair the normal feeding or oviposition of insect pests (Morris and Dwyer, 1997; Underwood, 1999). It has also been documented that quality and quantity of food collectively affect food selection behavior, survival and reproduction of phytophagous insect pests (Nasiri et al., 2010). Other than nutritional effect of plants, plant traits also affect the performance of insect pests (Schoonhoven et al., 2005). Znidarcic et al. (2008) reported that epicuticular wax content in the leaves served as a mechanical barrier for flea beetles (Phyllotreta spp.), cabbage stink bugs (Eurydema ventrale) and onion thrips (Thrips tabaci). Allelochemicals have direct defensive effects, such as lectins and protease inhibitors may have an antibiotic effect on sucking insect pest (Goggin, 2007). Antixenosis mechanism also recognized as non-preference mechanisms of resistance, alters the host choice or selection behavior of herbivorous insect pest for feeding, shelter (Sharma and Nwanze, 1997; ), oviposition (Pancoro and Hughes, 1992) and their colonization (Dhaliwal and Arora, 2003; Gogi et al., 2010). Due to the provision of this mechanism insect show avoidance behavior from that specific plant and make the plants unuseful or poor quality for invasion of insects (Bazzaz et al., 1987; Schoonhoven et al., 1998). According to Smith (2012), oviposition rate of weevil Ceratapion basicorne

41 was high on its preferred plant species than on non-target species due to antixenosis mechanism of resistance. Various plant species have been identified possessing resistance property and exhibiting varying levels of resistance to insect pests throughout the world. Turfgrasses exhibited tolerance mechanisms due to modifications in plant proteins, increased oxidative enzyme activity, altered resource reallocation, greater rhizome number and turf density and vigor (Heng-Moss et al., 2002; Rangasamy et al., 2006). Heng-Moss et al., (2003) discussed that pubescence was positively correlated with buffalograss susceptibility to mealybugs. A glabrous leaf surface was suggested as a possible mechanism of resistance.

Indeed, sucking insect pests are very selective sap feeders and select their host plants (food source) through visual, mechanical and chemical stimuli (Bernays, 1998). The decision for acceptance or rejection of plant by insect pests involves type of the volatile chemicals emitted by plant, plant surface waxes, cell wall thickness, mesophyll and phloem content compositions (Niemeyer, 1990; Caillaud and Via, 2000). Morphological and chemical constituents vary with respect to plant species and plant organs within the same plant (Schoonhoven et al., 2005). This information is essential for understanding the morphological mechanisms underlying the resistance in differetnt host plants against mealybug. The research on this aspect is still quite sketchy and needs more extensive research. Keeping in view the deficiency, present study was undertaken to investigate the physico-morphic based antixenosis mechanism of resistance in twenty five different host plants on the basis of associations between physico-morphic plant traits and P. solenopsis. Materials and Methods 4.1.2 Colony culture of cotton mealybug The adults of P. solenopsis were collected alongwith their host plant (Hibiscus rosa-sinensis) thus brought in Integrated Pest Management Laboratory, University of Agriculture, Faisalabad and again cultured on H. rosa-sinensis during 2008-09. The culture was maintained in glass jars with dimension (30 x 30 x 30 cm) at a temperature of 25±2ºC and relative humidity 65±5% for further experimentation. 4.1.3 Plant material Detail of selected plant species is given in Table 1.1:

42

4.1.4 Determination of attractiveness index of different instars of P. solenopsis In order to study the host-plant preference of mealybug toward the selected plant species, healthy twigs of these plants with at least five tender leaves which were neither exposed to any pesticide applications nor had mealybug infestation were cliped and brought into laboratory. The collected twigs were cleaned, washed and air-dried to remove moisture from the surface of leaves. A Host-Plant-Preference-Study-Wheel (HPPSW) was constructed from thermopore sheet of diameter 120 cm (Figure 4.1.1). In the center of sheet a hole of 7.5 cm diameter was made where a petridish of diameter 7.5 cm was adjusted that was used for release of insect individuals. On the outer boundary of HPPSW, the glass vials filled with nutrient solution were adjusted and selected plant twigs were inserted in the nutrient solution in the vials (to maintain the turgidity and freshness of plants). The vials having plant’s twigs were adjusted at equidistance from each other as well as from the petridish adjusted in the central hole of sheet. A counted numbers of newly emerged instars (1st, 2nd and 3rd) of mealybug (400) were collected from the culture with the help of camel hair brush into plugged test tube, starved for two hours and then released in the petridish adjusted in the center of HPPSW and data was recorded at 2, 4 and 8 hours after release. The numbers of mealybugs settled on the twigs of each plant species were counted and the attractiveness of P. solenopsis to the tested plant species was compared with Chinese rose (CMB susceptible plant kept as control) by using the equation described by Lin et al. (1990).

G: Number of mealybug on tested plant, S: Number of mealybug on control plant Selected plants were categorized into attractive and resistant plants on the basis of comparison between attractiveness index values of these plants and standard plant (Chinese rose, H. rosa-sinensis). Plant species bearing mealybugs more than standard having attractiveness index ≥ 1 were considered as attractive plants while plant species having attractiveness index <1 but ≥0.5 < 0.5 were considered as neutral plant and resistant plants, respectively. The experiment was repeated thrice for each instar of P. solenopsis and data was analysed statistically by using Completely Randomized Design.

43

Figure 4.1.1: Host Preference Wheel. 4.1.5 Determining physic-morphic traits of selected plant species Following physic-morphic traits were determined for selected plant species. 1) Thickness of leaf lamina 2) Leaf area 3) Trichome density 4) Trichome length 4.1.6 Thickness of leaf lamina (µm) The thickness of leaf lamina was measured according to the procedure by Raza et al. (2000) in order to correlate it with the attractiveness index of P. solenopsis. For this purpose fully mature leaves were picked from each plant species and taken for the morphological observations under laboratory. Leaves collected were cleaned to remove dust particles from the leaf surface with the help of muslin cloth and cross section of each leaf was cut with the help of surgical blade. The leaf portion was placed on the glass slide vertically with the help of glycerin. The prepared glass slides were observed under a CARL ZEISS binocular microscope and numbers of divisions were recorded with the help of ocular micrometer. The factor was calculated for ocular micrometer with the help of stage micrometer. Numbers of divisions of each sample was multiplied with the factor for calculating thickness of leaf lamina in micrometers.

44

4.1.7 Leaf area (cm2) Leaf area of the selected plant species was determined with the help of digital area meter to assess their role in regulating the antixenotic behavior of P. solenopsis. For this purpose mature leaves from the selected plants were picked up, taken to the laboratory and were placed on the glass sheet of digital area meter in horizontal position. Reading of the leaf area (cm2) was observed and recorded from the screen of digital leaf area meter. 4.1.8 Trichome density and trichome length (µm) Number of trichomes per centimeter square was determined under binocular microscope to investigate the response of P. solenopsis toward trichome density. For this purpose, a square ring of 1cm2 was made and placed at three different places on leaf and leaf portion from each place was cut and placed on the slide to observe under the CARL ZEISS binocular microscope. In this way density and length of trichomes were determined by visualizing numbers of divisions recorded with the help of ocular micrometer. The factor was calculated for ocular micrometer with the help of stage micrometer. Numbers of divisions of each sample were multiplied with the factor for calculating the leaf lamina thickness in micrometers. Statistical analysis The data collected on attractiveness index and physic-morphic plant traits were subjected to uni- and multivariate analyses by using Minitab software for determining the variation in attractiveness of mealybug for host plants (Sneath and Sokal, 1973). The means of significant treatments were compared with Tukey’s honestly significant difference (HSD) (Danho et al., 2002). Regression analysis between attractiveness index of mealybug and physic-morphic traits of the plants was established and their coefficient of determination values were computed to determine the strength and role of each independent variable in the variation of dependant variable (Attractiveness index). Correlation and scatter diagrams were also established, using linear regression and Pearson correlation analysis at 5% level of probability to determine the nature of association between dependent and independent variables. Results A significant variation in attractiveness index of first, second and third instar to selected plant species was determined for three time intervals (2, 4 and 8 hours after release) (p < 0.05) (Table 4.2.1).

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Table 4.2.1: ANOVA parameters regarding food preference of P. solenopsis at different intervals toward twenty five selected plant species under multi-choice laboratory experiment. Source Time interval (hours) Df F-value P-Value First instar 2 24a/48b 13.4 0.001** 4 24a/48b 9.5 0.000** 8 24a/48b 6.8 0.005** Second instar 2 24a/48b 21.0 0.003** 4 24a/48b 23.7 0.003** 8 24a/48b 21.0 0.002** Third instar 2 24a/48b 12.6 0.003** 4 24a/48b 15.0 0.04* 8 24a/48b 12.1 0.003** df= degree of freedom, * = highly significant at 5% probability level, a = degree of freedom of treatments (plant species), b = Error degree of freedom, CMB= cotton mealybug; SOV= Source of variance, df= degree of freedom, SS= Sum of square, MS= mean sum of square, **= highly significant difference at P=0.05 4.1.9 Attractive index of first instar of P. solenopsis for different plant species at 2, 4 and 8 hours post-release intervals At 2 hours of post-release interval, first instar of P. solenopsis showed attractiveness index (AI) ≥1.0 for L. camara, H. rosa-sinensis, E. prostrate and G. hirsutum which were categorized as attractive plant species. In contrast, first instar of P. solenopsis demonstrated attractive index of < 0.5 for C. morale, L. nadicaulis, C. arvense, C. bonariensis, C. album, P. oleraceae and D. arvensis which were categorized as resistance plant species. Attractiveness index of first instar of P. solenopsis was <1 but ≥0.5 for C. arvensis, W. somnifera, C. didimus, S. melongena, A. esculentus, C. frutescens, A. spinosus, C. inerme, T. portulacastrum, T. terrestris, Eclipta prostrate, P. hysterophorus, A. aspera and H. annuus which were considered as neutral plants (Figure 4.2.1). At 4 hours of post-release interval, first instar of P. solenopsis showed attractiveness index (AI) ≥1.0 for H. rosa-sinensis which were categorized as attractive plant species. In contrast, first instar of P. solenopsis demonstrated attractive index of < 0.5 for C. morale, L. nadicaulis, C. bonariensis, C. album, C. arvense, C. didimus and D. arvensis which were categorized as resistance plant species. Attractiveness index of first instar of P. solenopsis was <1 but ≥0.5 for L. camara, C. arvensis, W. somnifera, Euphorbia prostrate, S. melongena, A. esculentus, G. hirsutum, C. frutescens, A. spinosus, C. inerme, T. portulacastrum, P. oleraceae, T. terrestris, Eclipta prostrate, P. hysterophorus, A. aspera and H. annuus which were considered as neutral plants. At 8 hours post-release interval, the attractiveness index of first instar of P. solenopsis was highest (AI≥1) for G. hirsutum and H. rosa-sinensis which was considered as attractive plant species. Least attractiveness (AI<0.5) first instar of P. solenopsis was

46 recorded for C. morale, L. nudicaulis, C. didimus, C. bonariensis, C. arvense, C. album and D. arvensis which were categorized as resistant plant species. However, L. camara, C. arvensis, S. melongena, W. somnifera, Euphorbia prostrate, A. esculentus, C. frutescens, A. spinosus, C. inerme, T. portulacastrum, P. oleraceae, T. terrestris, E. prostrate, P. hysterophorus, A. aspera and H. annuus proved were categorized as neutral plant species as first instar of P. solenopsis exhibited attractiveness index <1 but ≥0.5 for these plant species at 4 hours post-release interval (Figure 4.2.2 and 4.2.3).

A = attractive; N = neutral; R = resistant; S = standard; standard error line bars in the bargraph indicate the standard error Figure 4.2.1: Attractive index (means±SE) of first instar of P. solenopsis for different plant species at 2 hours post-release interval.

A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.2: Attractive index (means±SE) of first instar of P. solenopsis for different plant species at 4 hours post-release interval.

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A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.3: Attractive index (means±SE) of first instar of P. solenopsis for different plant species at 8 hours post-release interval.

4.1.10 Attractive index of second instar of P. solenopsis for different plant species at 2, 4 and 8 hours post-release intervals At 2 hours of post-release interval, second instar of P. solenopsis exhibited attractiveness index (AI) ≥1.0 for E. prostrate, S. melongena, G. hirsutum, T. portulacastrum and P. oleraceae, which were categorized as attractive plant species. In contrast, second instar of P. solenopsis presented attractive index of < 0.5 for C. morale, L. nudicaulis, C. bonariensis, D. arvensis, C. arvense, C. album, T. terrestris and A. aspera which were categorized as resistance plant species. Whereas second instar of P. solenopsis demonstrated attractiveness index of <1 but ≥0.5 for L. camara, C. arvensis, W. somnifera, C. didimus, A. esculentus, C. frutescense, A. spinosus, C. inerme, E. prostrate, P. hysterophorus and H. annuus which were considered as neutral plants (Figure 4.2.4). At 4 hours post-release interval the attractiveness index of second instar of P. solenopsis was highest (AI≥1) for H. rosa-sinensis, G. hirsutum and T. partulacastrum which was considered as attractive plant species. Least attractiveness (AI<0.5) of second instar of P. solenopsis was recorded for C. morale, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, C. bonariensis, C. arvense, C. album, C. frutescense, A. spinosus, C. inerme, T, terrestris, E. prostrate, D. arvensis and A. aspera, so they were categorized as resistant plant species. However, L. camara, E. prostrate, S. melongena, A. esculentus, P. oleraceae, H. annuus and P. hysterophorus were categorized as neutral plant species

48 because second instar of P. solenopsis exhibited attractiveness index <1 but ≥0.5 for these plant species at 4 hours post-release interval (Figure 4.2.5). At 8 hours post-release interval, the attractiveness index of second instar of P. solenopsis was ≥1 for L. camara, H. rosa-sinensis, E. prostrate, G. hirsutum, C. inerme, T. portulacastrum and P. oleracea, which were grouped into attractive plant species. Least attractiveness (AI<0.5) of second instar of P. solenopsis was recorded for C. morale, L. nudicauls, C. bonariensis, C. arvense, C. album, T. terrestris, D. arvensis and A. aspera which were categorized as resistant plant species. However, C. arvensis, W. somnifera, C. didimus, S. melongena, A. esculentus, C. frutescense, A. spinosus, E. prostrate, P. hysterophorus and H. annuus were considered as neutral plant species as second instar of P. solenopsis exhibited attractiveness index <1 but ≥0.5 for these plant species at 8 hours post-release interval (Figure 4.2.6).

A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.4: Attractive index (means±SE) of second instar of P. solenopsis for different plant species at 2 hours post-release interval.

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A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.5: Attractive index (means±SE) of second instar of P. solenopsis for different plant species at 4 hours post-release interval.

A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.6: Attractive index (means±SE) of second instar of P. solenopsis at 8 hours after release for different plant species.

4.1.11 Attractive index of third instar of P. solenopsis for different plant species at 2, 4 and 8 hours post-release intervals At 2 hours of post-release interval, third instar of P. solenopsis showed attractiveness index (AI) ≥1.0 for E. prostrate, G. hirsutum, H. rosa-sinensis and T. portulacastrum which were categorized as attractive plant species. In contrast, third instar of P. solenopsis demonstrated attractive index of < 0.5 for C. morale, C. didimus, C. arvense,

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C. bonariensis, C. inerme, T. terrestris, A. aspera and D. arvensis which were categorized as resistance plant species. Attractiveness index of third instar of P. solenopsis was <1 but ≥0.5 for L. camara, C. arvensis, L. nudicaulis, W. somnifera, S. melongena, A. esculentus, C. album, A. spinosus, S. frutescense, P. oleraceae, Eclipta prostrate, P. hysterophorus and H. annuus which were considered as neutral plants (Figure 4.2.7). At 4 hours of post-release interval, third instar of P. solenopsis showed attractiveness index (AI) ≥1.0 for E. prostrate, H. annuus, T. portulacastrum, P. oleraceae and G. hirsutum which were categorized as attractive plant species. In contrast, third instar of P. solenopsis exhibited attractive index of < 0.5 for C. bonariensis, C. didimus, A. aspera and D. arvensis which were categorized as resistance plant species. Attractiveness index of third instar of P. solenopsis was <1 but ≥0.5 for L. camara, C. morale, C. arvensis, L. nudicaulis, W. somnifera, S. melongena, A. esculentus, C. arvense, C. album, C. frutescence, A. spinosus, C. inerme,, T. terrestris, E. prostrate, P. hyseterophorus and H. annuus which were considered as neutral plants (Figure 4.2.8). At 8 hours post-release interval, the attractiveness index of third instar of P. solenopsis was highest (AI≥1) for H. rosa-sinensis, E. prostrate, G. hirsutum, T. portulacastrum, P. oleraceae and H. annuus which were grouped into attractive plant species. Least attractiveness (AI<0.5) of third instar of P. solenopsis was recorded for C. bonariensis, C. didimus and D. arvensis which were categorized as resistant plant species. However, L. camara, C. morale, C. arvensis, L. nudicaulis, W. somnifera, S. melongena, A. esculentus, C. arvense, C. album, C. frutescence, A. spinosus, C. inerme,, T. terrestris, Eclipta prostrate, P. hyseterophorus and A. aspera were considered as neutral plant species as third instar of P. solenopsis exhibited attractiveness index <1 but ≥0.5 for these plant species at 8 hours post-release interval (Figure 4.2.9).

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A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.7: Attractive index (means±SE) of third instar of P. solenopsis at 2 hours after release for different plant species.

A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.8: Attractive index (means±SE) of third instar of P. solenopsis at 4 hours after release for different plant species.

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A = attractive; N = neutral; R = resistant; S = standard; Line bars in the bargraph indicate the standard error Figure 4.2.9: Attractive index (means±SE) of third instar of P. solenopsis at 8 hours after release for different plant species.

4.1.12 Morphological plant Characters Significant variations were observed in trichome density (F= 15.3; df=24; p <0.00), hair length (F= 7.6; df=24; p<0.00), leaf thickness (5.5) and leaf area (F= 17.3; df=24; p<0.00) for different plant species (Table 4.2.2). Table 4.2.2: Analysis of variance regarding morphological traits of tested plant species toward P. solenopsis.

SOV Df F value P value a Trichome density 24 /50b 15.3 0.000** Trichome length 24a/50b 7.6 0.000** a Leaf thickness 24 /50b 5.5 0.000** a Leaf area 24 /50b 17.3 0.000**

** = highly significant at 5% probability level, a = degree of freedom of treatments (plant species), b = Error degree of freedom, SOV= Source of variance, df= degree of freedom, 4.1.13 Trichome density and its association with attractiveness index of P. solenopsis Trichome density among the tested plant species ranged from 0.5 to 250 trichomes/cm2. Maximum trichomes (≥200 trichomes/cm2) were recorded in G. hirsutum (275.1 trichomes/cm2), followed by 200.0 trichomes/cm2 in both H. annuus and L. camara. Trichome density in the range of ≥100 but < 200 trichomes/cm2 was recorded in H. rosa- sinensis (150 trichomes/cm2), W. somnifera (130 trichomes/cm2), A. esculentus (121 trichomes/cm2), C. arvensis (100 trichomes/cm2) and S. melongena (100 trichomes/cm2). The plant species including C. didimus (95 trichomes/cm2), C. inerme

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(79 trichomes/cm2), T. terrestris (75 trichomes/cm2), A. spinosus (50 trichomes/cm2) and E. prostrate (50 trichomes/cm2), exhibited ≥50 but < 100 trichomes/cm2. The plant species including C. frutescence (47 trichomes/cm2), C. bonariensis (45 trichomes/cm2), A. aspera (27 trichomes/cm2), P. hysterophorus (23 trichomes/cm2), T. partulacastrum (23 trichomes/cm2), C. arvense (20 trichomes/cm2), P. oleraceae (12 trichomes/cm2), C. album (10 trichomes/cm2), L. nadicaulis (10 trichomes/cm2) and C. morale (5 trichomes/cm2) exhibited a density of <50trichomes/cm2. However, no trichome was observed in E. prostrate and D. arvensis (Figure 4.2.10). The probability values in all scatter diagrams indicated that association existed between trichome density and attractiveness index of first, secnd and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.11A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that trichome density had positive correlation with attractive index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value is closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.11 A, B and C). Regression parameters and scatter diagrams also demonstrated that trichome density had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.11 A, B and C). Trichome density explained 31.7%, 42.4% and 17.5% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.11 A, B and C).

Figure 4.2.10: Trichome density of tested plant species for P. solenopsis.

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Figure 4.2.11: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (trichome density/cm2).

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4.1.14 Trichome length in tested plant species and its association with attractiveness index of mealybug Trichome length among the tested plant species ranged from 0.0 to 2.75µm. Maximum trichome length (≥2.15µm) were recorded in T. terristris (2.75µm), followed by 2.65µm in both G. hirsutum and L. camara, 2.57µm in C. inerme, 2.56µm in C. arvense, 2.51µm in H. annuus, 2.49µm in E. prostrate, 2.25µm in P. hysterophorus, 2.19µm in S. melongena and W. somnifera, 2.15µm in C. didimus and L. nudicaulus. Trichome length in the range of ≥1.45 but < 2.00µm was recorded in A. esculentus (1.98µm) that was at par with C. arvensis (1.95µm), C. album and C. morale (1.92µm), followed by A. aspera (1.82µm), C. frutescence (1.75µm), H. rosa-sinensis, C. bonariensis (1.53µm), A. spinosus (1.5µm) and 1.45µm in P. oleraceae except D. arvensis and E. prostrate had no trichomes and trichome length (Figure 4.2.12). The probability values in all scatter diagrams indicated that association existed between trichome length and attractiveness index of first, secnd and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.13 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that trichome length had positive correlation with attractive index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.13 D, E and F). However regression parameters and scatter diagrams established that trichome length had non-significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.13 D, E and F). Trichome length explained 7.0%, 8.9% and 11.0% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.13 D, E and F).

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Figure 4.2.12: Trichome length of tested plant species for P. solenopsis.

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Figure 4.2.13: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (D), second (E) and third instar (F) nymphs of P. solenopsis) on X (trichome length µm ).

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4.1.15 Leaf area of tested plant species and its association with attractiveness of mealybug Leaf area among the tested plant species ranged from 70.5 to 100.2 cm2. Maximum leaf area were recorded in H. annuus (100.2 cm2), followed by 80.0 cm2 in S. melongena, 75 cm2 in W. somnifera and 70.5 cm2 in G. hirsutum. Leaf area in the range of ≥20 but < 45 cm2 was recorded in H. rosa- sinensis (42 cm2), P. hysterophorus (40 cm2), A. esculentus (26 cm2), A. spinosus (25 cm2) and plant species comprising C. album, L. camara and L. nadicaulis had leaf area (20 cm2). The plant species including C. morale, A. arvensis, C. frutescence, C. arvense (15 cm2), C. bonariensis (10), D. arvensis (5 cm2), T. terrestris (3.5 cm2) and C. didimus (3.0 cm2) i.e., ≥3 but < 17 cm2 was recorded (Figure 4.2.14). The probability values in all scatter diagrams indicated that association existed between leaf area and attractiveness index of first, second and third instar nymphs of P. solenopsis (Pvalue <0.05) (Figure 4.2.15 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that leaf area had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.15 G, H and I). Regression parameters and scatter diagrams also explained that leaf area had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P value <0.05) (Figure 4.2.15 G, H and I). Leaf area explained 15.7, 19.3 and 14.1% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.15 G, H and I).

Figure 4.2.14: Leaf area of tested plant species for P. solenopsis.

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Figure 4.2.15: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (G), second (H) and third instar (I) nymphs of P. solenopsis) on X (leaf area cm2).

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4.1.16 Leaf thickness of selected plant species and its association with attractiveness index of mealybug Leaf thickness among the tested plant species ranged from 1.25 to 1.9µm. Maximum leaf thickness were recorded in S. melongena (1.9µm), followed by 1.85µm in H. rosa-sinensis, 1.68µm in T. partulacastrum, 1.5µm in P. oleraceae, 1.4 in H. annuus, 1.28 in E. prostrate, 1.25 in W. somnifera, and 1.23 in P. hysterophorus. Leaf thickness in the range of ≥0.68 but < 1.00µm was recorded in C. album (1.12µm), A. aspera (1.00µm), E. prostrate (0.92µm), D. arvensis (0.87µm), C. inerme (0.8µm), A. spinosus (0.78µm), both L. camara, L. nudicaulus (0.71µm), C. bonariensis (0.7µm) and T. terrestris (0.68µm). Leaf thickness in range of ≥0.25 but < 0.4µm was recorded in plant species including C. didimus (0.4µm), C. morale (0.37µm) and C. arvensis (0.25µm) (Figure 4.2.16). The probability values in all scatter diagrams indicated that association existed between leaf thickness and attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.17 J, K and L). The scatter diagram and coefficient of correlarion value (r) demonstrated that leaf thickness had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion values were closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.17 G, H and I). Regression parameters and scatter diagrams also explained that leaf thickness had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (Pvalue <0.05) (Figure 4.2.17 J, K and L). Leaf thickness explained 25.0%, 32.4% and 25.7% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.17 J, K and L).

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Figure 4.2.16: Leaf thickness of tested plant species for P. solenopsis.

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Figure 4.2.17: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (J), second (K) and third instar (L) nymphs of P. solenopsis) on X (leaf thickness µm).

4.1.17 Cluster analysis among studied traits Twenty five plant species were categorized into three different clusters with the help of cluster analysis (Figure 4.3). Clusters were made on the basis of attractiveness index of mealybug and morphological traits of the selected plant species. Cluster ANOVA revealed that there were significant differences in the morphological leaf traits of the tested host plants (P < 0.05) and the attractiveness index of P. solenopsis (P < 0.05) (Table 4.2.3). Cluster-1 comprised of three plant species including L. camara, H.annuus and G. hirsutum demonstrating final cluster center readings of 225.0 trichomes/cm2, 1.12 µm, 62.3 cm2, 2.6 µm and 0.95 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively. Cluster-2 consisted of eight plant species including C. inerme, C. arvensis, C. didimus,H. rosa-sinensis, S. melongena, W. somnifera, A. esculentus and T.terrestris describing final cluster center readings of 22.3 trichomes/cm2, 1.04µm, 12.2cm2, 1.7µm and 0.53 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively; while cluster-3 possessed a group of fourteen plant species including E. prostrate, A. spinosus, P. hysterophorus, E. prostrate, P. oleracea, T. portulacastrum, C. frutescens, L. nudicaulis, C. arvense, C. morale, C. album, A. aspera, C. bonariensis and D. arvensis with cluster center readings of 2.8 trichomes/cm2, 0.6 µm, 0.45 cm2, 0.77 µm and 0.29 for trichome density, leaf thickness, leaf area, trichome length and attractiveness index, respectively (Table 4.2.3). Cluster-1 comprised of the most preferred host plant species compared with cluster-2 and

63 cluster-3. The plants included in cluster-2 demonstrated least preference and were considered as resistant plants for P. solenopsis. However, the plant species included in cluster-3 exhibited the intermediate preference for P. solenopsis and were categorized as neutral plant species (Table 4.2.3). The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-2 demonstrated maximum diversity (D2= 208.9) against the members of cluster-1 for the most of the studied morphological traits (Table 4.2.4).

Dendrogram Complete Linkage, Euclidean Distance

0.00

y

t 33.33

i

r

a

l

i

m

i

S Cluster-1 Cluster-2 66.67 Cluster-3

100.00 a s e s e a e s e s e s e s s s a a s s e s r m u l li m s m r a si t u t si s u si u r n si u ri a tu n ra u u n ru e e n ra r ra n n s n t fe e n rm t n a b e t p c e t o t e e o e n i g e im s m su a o ic l v s s a v s h s i c n n le n n v d e re ca r . m a r a a r r o p o r s i i u r i in r i . d . a c . le a r o r a e p s c m lo a d . e L. h H u C . a A . p r p n t s - s o e . . C t . C n C l o . e . o ru . sa e s C C . G . tu . D E t E b f A . . m T L r P s . . ro A . a y C C . W S p h . . H T P

Observations Figure 4.3: Cluster analysis regarding similarity between morphological traits versus attractiveness index of P. solenopsis.

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Table 4.2.3: ANOVA parameter for cluster and cluster membership among morphological traits of some host plants toward attractiveness index of P. solenopsis. Independent d.f F P Final Cluster Centers variables Cluster-1 Cluster-2 Cluster-3 L. camara, H.annuus, C. inerme, C. arvensis, E. prostrate, A. spinosus, P. hysterophorus, E. G. hirsutum C. didimus, H. rosa- prostrate, P. oleracea, T. portulacastrum, C. sinensis, W. somnifera, frutescens, L. nudicaulis, C. arvense, C. morale, C. A. esculentus album, A. aspera, C. bonariensis and D. arvensis S. melongena and T.terrestris Trichome density 2/22 4.6 0.00 225.0 22.3 2.8 Leaf thickness (µm) 2/22 1.56 0.00 1.12 1.04 0.6 Leaf area (cm2) 2/22 3.42 0.00 62.3 12.2 0.45 Trichome length (µm) 2/22 1.5 0.00 2.6 1.7 0.77 Attractiveness 2/22 0.2 0.00 0.95 0.53 0.29 Table 4.2.4.: D2 distance among different clusters among morphological traits of some host plants toward attractiveness index of P. solenopsis. Cluster-1 Cluster-2 Cluster-3 Cluster-1 0.000 Cluster-2 208.9 0.000 Cluster-3 122.8 85.9 0.000

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4.1.18 Principal component analysis In this study, two out of five Principal components (PCs) were taken having Eigenvalues ≥1. Results depicted that first two PCs expressed 73% of the total variability amongst the selected plant species for P. solenospsis while other PCs contributed only about 27% of the total variability (Table 4.2.5). PC1 contributed maximum variability (52%) following PC2 (20%), PC3 (12%), PC4 (12%) and PC5 (3.4%). The morphological traits like trichome density, leaf thickness, leaf area and trichome length explained positive factor loadings on PC1. These morphological explained positive factor loadings on PC2 but trichome density and trichome length demonstrated negative factor loadings on PC2 and leaf thickness, leaf area and trichome length explained negative factor loadings on PC3.

Table 4.2.5: Principal component analysis of morphological traits in different plant species of P. solenopsis.

PC1 PC2 PC3 PC4 PC5 Eigenvalue 2.6 1.03 0.6 0.6 0.17 % of total variance 0.52 0.20 0.12 0.12 0.034 Cumulative variance % 0.52 0.73 0.85 0.97 1.00 Factor loading by various biochemical traits Variable PC1 PC2 PC3 PC4 PC5 PC6 PC7 Trichome density 0.51 -0.343 0.339 -0.347 -0.624 -0.10 -0.46 Leaf thickness (µm) 0.37 0.69 -0.378 0.255 -0.427 0.38 0.31 Leaf area (cm2) 0.50 0.034 -0.40 -0.58 0.50 0.64 -0.27 Trichome length (µm) 0.36 -0.59 -0.40 0.60 0.063 -0.54 -0.20 Attractiveness 0.48 0.24 0.65 0.34 0.42 0.24 0.32

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Objective 2b 4.1.2 Biochemical based antixenosis mechanism of resistance in different host plants against cotton mealybug Abstract

The decision for acceptance or rejection of plant by insect pests involves phloem content compositions and type of the volatile chemicals emitted by plant. The nutritive as well as chemical stimulai are sensored by the insect pest. A significant variation was observed among biochemical traits in selected plant species. Biochemical contents comprising of nitrogen, phosphorus, potassium, crude protein, reducing sugar, total soluble sugar and chlorophyll contents were investigated in 25 selected plant species to determine their effect on attractiveness of P. solenopsis. Correlation coefficients demonstrated association between attractiveness of first, second and third instar nymphs of P. solenopsis with mineral contents including phosphorus contents (r= 0.05, 0.27 and 0.03), potassium (r= 0.03, 0.27, 0.03), nitrogen (r= 0.12, 0.07, 0.12), sodium (r= 0.21, 0.47, 0.27), total soluble sugar (r= 0.01, -0.12, 0.06), reducing sugar (r= 0.10, 0.1, 0.06),crude protein (r= 0.12, 0.07, 0.12) and chlorophyll contents (r= 0.29, 0.36,0.12), respectively. Cluster analysis for biochemical traits showed that Cluster-1 comprised of twelve plant species including L. camara, H. rosa-sinensis, H.annuus, P. hysterophorus, W. somnifera, E. prostrate, P. oleracea, S. melongena, T. portulacastrum, G. hirsutum, A. esculentus and C. frutescens having final cluster center readings of 1.72, 0.72, 0.5, 0.25, 0.06, 1.16, 0.1, 0.95 and 7.5% for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, chlorophyll, attractiveness index and crude protein respectively. Cluster-2 consisted of a group of five plant species including C. arvensis, E. prostrate, A. spinosus, C. inerme, and T. terrestris demonstrating final cluster center readings of 2.5, 0.64, 0.63, 0.7, 0.19. 1.42 0.3, 0.078 and 13.8% for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, attractiveness index, chlorophyll and crude protein respectively while cluster-3 possessed eight plant species including L. nudicaulis, C. didimus, C. arvense, C. morale, C. album, A. aspera, C. bonariensis, D. arvensis demonstrating final cluster center readings of 2.8, 0.6, 0.45, 0.77, 0.29, 2.1, 0.6, 0.057 and 16.3 for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, attractiveness, chlorophyll and crude protein respectively. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster 2 demonstrated maximum diversity (D2= 25.3%) against the members of cluster 3 for the most of the studied traits. Principal component analysis results depicted that first three PCs expressed 83% of the total variability amongst selected plant species. PC1 contributed maximum variability (40%) following PC2 (26%) and PC3 (17%). It can be concluded that chemical contents affected attractiveness index of P. solenopsis; however, there is need to explore allelochemicals that impart resistance against P. solenopsis.

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Introduction

The demand and practical implementation of plant resistance has been increasing consistently due to the ill effect of pesticides. Plants have ability to overcome the attack of insect pest in different ways. The physical and biochemical factors of the plants influence the life history of insect pest. The physical and volatile signals, originated from plants, attract the insect to its surface whereas chemical and nutritional factors of the food substrate determine consumption, development and survival in the larval stages and egg production of subsequent adults (Singh and Mullick, 1997). The shorter developmental time and greater total reproduction of insects on a host plant indicate greater suitability of that plant (van Lenteren and Noldus, 1990). Host plant specificity and oviposition motivation are affected by the physiological state of insect pest including age, feeding status, mated status and egg load (Jallow and Zalucki, 1998). Attractiveness, food selection and utilization by insect species are valuable steps which vary and demonstrate food and oviposition preference among different plants (Roitberg et al., 1999; Singer, 2000; West and Cunningham, 2002; Stamps and Linit, 2002; Nieminen et al., 2003; Arif et al., 2012). It may be due to the availability of qualitative and quantitative nutrients, volatile compounds, secondary metabolites, phenology, tissue hardness and other defensive mechanisms of the plants (Joachim-Bravo et al., 2001; McNeely and Singer, 2001; Awmack and Leather, 2002; De Bruyn et al., 2002; Morewood et al., 2003; Mannion et al., 2003; Meiners et al., 2005; Coley et al., 2006; Arif et al., 2012). The additive effects of these factors enable the plants to provide barrier to normal feeding or by repelling insect pests via volatile exudates (Van- Emden and Peakall, 1996). The application of nitrogen fertilizer in plants normally increased herbivore feeding preference, food consumption, survival, growth, reproduction and population density (Zhong-xian et al., 2007). According to Varela and Seif (2004), nitrogen application enhances leaf area of the plant due to improved radiation interception and higher rate of photosynthesis in plants also resulted in insect pest outbreaks (Dyck et al., 1979) because crops receiving high doses of nitrogen were more susceptible to insect pest attack and suffered heavier losses (Peng, 1993; Ajayi and Tabo, 1995). It has also been documented that quality and quantity of food affect food selection behavior, survival and reproduction of phytophagous insect pest (Du et al., 2004). Insect pest are forced to respond and decide either to be attracted or repelled from the food source for feeding and

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oviposition (Li et al., 2004; Arif et al., 2013). A well developed response has been observed in insect pests toward the chemical stimuli (Chelliah and Sambandam, 1974). Iqbal et al., (2011) reported that crude protein, nitrogen, lignin, reducing sugar, phosphorus and copper showed positive correlation with jassid infestation whereas neutral detergent fiber, acid detergent fiber, cellulose, silica, total ether, non reducing sugars, total sugars, calcium and magnesium had negative correlation with the population of jassid on okra. They further pointed out that crude protein showed the positive and significant impact (69%) on the jassid population fluctuation on okra which was followed by neutral detergent fibre with 21% contribution. When computed together, all the chemical components showed 99.7% role on jassid population fluctuation. Hu et al. (2010) reported that there was negative association between sugar concentrations and feeding as well as oviposition preference. Due to imbalanced nutrition, inhibition of feeding and oviposition in mites and whiteflies has also been documented by (Singh, 1988; Neal et al., 1994; Liu and Stansly, 1995 and Slocombe et al., 2008). Singh and Agarwal (1988) reported that highly susceptible genotypes contained significantly higher amount of proteins, as compared to the resistant genotypes. Singh and Taneja (1989) reported a positive correlation between the protein contents and oviposition of jassids. Balasubramanian and Gopalan (1981) reported lesser amounts of reducing sugar in the susceptible variety as compared to that in the resistant ones to jassid. Singh and Agarwal (1988) reported a negative correlation among the incidence of A. biguttula biguttula and the amount of total sugars and non-reducing sugars in the leaves of resistance genotypes. These characteristics of plants are critically very important in decision making of insect pests for feeding, probing and oviposition (Joachim-Bravo et al., 2001; Shahid et al., 2012). Various researchers have explored the host range of P. solenopsis in Pakistan and documented significant variation in preference of this pest on various host plants. The information regarding host-plants-resistance (HPR) regulating biochemical factors in various host plants for P. solenopsis is quite lacking. The present study was carried out to investigate the HPR regulating biochemical factors of different host plants against CMB. Materials and Methods Biochemical traits of the selected plant species were correlated with attractiveness index for the determination of antixenosis mechanism in plant species toward P. solenopsis.

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4.2.1 Determination of Biochemical factors/ Antibiotic factors in leaves of selected plant species The antibiotic factors which we have studied are as follows. 1) Sodium contents 2) Potassium contents 3) Nitrogen contents 4) Total soluble sugars/ Total carbohydrates 5) Reducing sugar 6) Percentage crude protein 7) Phosphorous contents 8) Chlorophyll contents For the determination of mineral content in the leaves of each plant species, fresh and un-infested leaves were collected, rinsed in water, oven dried and grinded with the help of electric grinder into fine powder. Digestion Process Before the determination of biochemical plant factors, finely ground plant leaf samples were digested through the digestion process. Apparatus and Reagents Electric oven, electric balance, conical flask, 98% pure conc. sulfuric acid, hydrogen per oxide, what man filter paper number-1, etc. Procedure For each powdered sample 0.5 gm was weighed with electric balance and taken in a conical flask. 5ml of conc. sulfuric acid was added to each flask. Each conical flask was than covered with paper and kept in a safe place for over night for digestion process. Next day all the conical flasks were kept on hot plate running at 100±5ºC. After 30 minutes,

5ml of hydrogen per oxide (H2O2) was added and heated continuously. After 30 minutes, again 5ml of hydrogen per oxide was added to each conical flask and this process was repeated until the sample became colorless. Conical flasks were gently removed and kept in a shade for 20 minutes for cooling. After that each sample was filtered through the whatman filter paper number 1 in plastic vials and volume was made up to 50 ml with distilled water (Loska and Wiechula, 1975). Precautions Because of the poisonous fumes and concentrated sulfuric acid gloves and mask should be used to avoid accidental injuries.

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Sodium contents (%) Sodium contents were analyzed on flame photometer (Model Jenway PFP7). 1 ml of the extract was taken each from 50 ml digested sample and volume was made upto 10 ml via distilled water. First of all, distilled water was run through the flame photometer and reading was adjusted to zero. Then 100 ppm standard solution of sodium was run and reading was adjusted to 100. After that each sample was run through flame photometer and reading was noted for each sample. From the reading of flame photometer, graph reading was taken from which sodium ions were calculated in mg/g. (Blake et al., 1969) Potassium contents (%) Potassium contents were analyzed on flame photometer (Jenway PFP7). A volume of 5 ml of the extract was taken each from 50 ml digested sample and volume was made upto 10 ml via distilled water. First of all, distilled water was run through the flame photometer and reading was adjusted to zero. Then 100 ppm standard solution of potassium was run and reading was adjusted to 100. After that each sample was run through flame photometer and reading was noted for each sample. From flame photometer reading graph reading was taken from which potassium ions were calculated in mg/g. Nitrogen Contents (%) Nitrogen is estimated by micro-kjeldhals according to the method of Bremmer and Keeney (1965) Reagents: Boric acid solution (20g in 1000 ml), Sulfuric acid standard (0.01 N) Procedure: Volume of 5ml from the above aliquot was taken in kjeldhal flask and placed it on the kjeldhal ammonia distillation unit. Volume 5ml of 40% NaOH was added to it. After that 5 ml of boric acid solution was taken in a conical flask with few drops of mixed indicator. When the distillate was approximately 40%, distillation was stopped. Distillate was cooled for few minutes and was titrated with 0.01 N standard H2SO4 till the solution turned pink. The blank sample was run for the complete procedure. The above process was repeated to the each treatment. Nitrogen percentage was estimated by following formula.

(V2 – V1) × N × 0.0014 N percentage: ------× 100 W V2 = Vol. of Std. H2SO4 required to titrate the sample solution.

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V1 = Vol. of Std. H2SO4 required to titrate the blank solution.

N = Normality of H2SO4

W = Weight of the sample in gram. Determination of Chlorophyll Chlorophyll contents (mg/gm) were estimated according to the method of Arnon (1949) and Davies (1976). Procedure Fresh leaves were cut into 0.5 cm and paced in glass vials. Measured 5ml of 80% acetone was added to each glass vial and placed over night at 0ºC. Absorbance of the supernatant was measured at 645 and 663 nm. Chlorophyll contents were calculated by using the fallowing formula. Chlorophyll= [12.7 (O.D 663) – 2.69 (O.D 645)] × v/1000 × W Where as V= Volume of acetone in which it was extracted. W= Weight of the sample. O.D= Optical density Sugars Glucose and total soluble sugars were determined according to the method described by Raizi et al. (1985). Reagents i. 5.4N KOH ii. O-tolidine: 60 ml/.05 M of O-tolidine and 2 g of thiourea was dissolved and make up the volume with glacial acetic acid.

iii. Anthrone: 150 mg of anthrone was dissolved in 100 ml H2SO4 (72% w/w) Extract Fresh leaves were chilled at 0ºC immediately after harvesting and than freezed at - 10ºC with in 10 minutes. 1gm of leaves was ground and added into the glass test tube. Then 10 ml of 80% ethanol was added to the glass test tube, covered it with aluminum foil to avoid evaporation of ethanol and placed it overnight for extracting. Reducing Sugar / Glucose 1 ml of the extract was taken in 25 ml glass test tube. 5ml of O-tolidine was added and heated at 97ºC. Then the test tubes were cooled in ice cold water. Absorbance of the supernatant was taken at 630 nm on spectrophotometer.

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Total Soluble Sugars / Total Carbohydrates A volume of 0.1 ml of extract was taken in 25 ml test tube and 3ml of freshly prepared anthrone was added to it. The mixture was heated at 97ºC on water bath for 10 minutes. Test tubes were then cooled in ice bath. Absorbance of the supernatant was taken at 630 nm on spectrophotometer. Standard Curve Standard curve was developed with different concentrations of glucose by following the above mentioned procedure and sugars values were calculated by comparing sample absorbance of the supernatant with standards. Phosphorous Contents Phosphorous contents were determined according to Wolf (1982) by spectrophotometer. Reagents i. Barton′s Reagent ii. Solution a: A 25 g of ammonium molybdate was dissolved in 400 ml of distilled water. iii. Solution b: Measured weight of 1.25g of ammonium metavandate was dissolved in 300 ml of boiling water and left the mixture to be

cooled for few minutes. Quantity of 250 ml of conc. HNO3 was added to it and cooled it again at room temperature. Procedure Quantity of 5 ml Barton′s reagent was dissolved in 5 ml of the aliquot and volume was made upto 50 ml. Before the absorbance of the supernatant was taken, solution was left for half an hour at room temperature. Values of Phosphorous were calculated by using the standard curve. Concentrations 0, 2, 4, 6, 8 and 10 ppm standards of phosphorous were prepared from sodium di-hydrogen phosphate and color was developed with Barton′s reagent and read at 470 nm. Standard curve was prepared and absorbance of the supernatant of the samples was read against concentration from the standard curve.

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Percentage Crude Protein Percentage crude protein was determined by multiplying the percentage nitrogen of each sample with a factor 6.25. Statistical analysis The data collected were subjected to uni- and multivariate analyses to select plant species bearing resistance against P. solenopsis. Pearson Correlation Coefficient values were used to estimate the association of biochemical plant traits with attractiveness of mealybug. Dendrogram and genetic similarity among the plant species were also generated using the Jaccard’s Coefficient of similarity expressed as Euclidean genetic distances. Similarly, cluster analysis was used to sort the plant species into their appropriate groups with minimum error by using Statistical Package for Social Sciences (SPSS) and Minitab softwares (Sneath and Sokal, 1973). The data was also subjected to principle component analysis using Minitab software for determining the contribution of plant’s chemical traits towards the variation in attractiveness of mealybug.

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Results

4.2.2 Biochemical leaf traits of host plants, attractiveness index of P. solenopsis and their nature of association There were significant differences in the biochemical leaf traits of the tested host plants (P < 0.05) (Table 4.2.6). Table 4.2.6: ANOVA regarding biochemical contents of leaf and attractiveness index of P. solenopsis. Df F-value P-value Potassium contents 24a/50b 2.5 0.00** Nitrogen contents 24a/50b 3.4 0.00** Phosphorus contents 24a/50b 2.7 0.00** Sodium contents 24a/50b 3.6 0.00** Reducing sugar contents 24a/50b 2.7 0.00** Total sugar contents 24a/50b 1.9 0.00** Chlorophyll contents 24a/50b 1.3 0.004** Crude protein contents 24a/50b 8.8 0.00** Attractiveness index 23a/50b 1.1 0.00** a:Degree of freedom for plant species, b:Error degree of freedom; SOV= Source of variance, df= degree of freedom, SS= Sum of square, MS= mean sum of square, **= highly significant difference at P=0.05 4.2.3 Phosphorus contents and its association with attractiveness index of P. solenopsis Phosphorus contents among the tested plant species ranged from 0.2 to 0.48%. Maximum concentration (≥0.4%) were recorded in Euphorbia prostrate (0.48), followed by 0.47% in G. hirsutum, 0.47 in C. didimus, 0.45 in both P. oleraceae and P. hysterophorus, 0.44% that was at par with D. arvensis and Eclipta prostrate (0.4%). Phosphorus contents in the range of ≥0.25 but < 0.40 % was recorded in H. rosa- sinensis (0.38%), S. melongena (0.36%), C. bonariensis (0.34%), H. annuus (0.3%) and in both T. partulacastrum and T. terrestris (0.3%). The plant species including C. album had phosphorus (0.28%) and (0.26%) in both A. spinosus and C. inerme respectively. Phosphorus ≤0.2% was recorded in plant species including A. spinosus, A. esculentus, C. arvensis, L. camara and W. somnifera (Figure 4.2.18.) The probability values in all scatter diagrams indicated that association existed between phosphorus contents and attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.19 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that phosphorus concentration had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.19 A, B and

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C). Regression parameters and scatter diagrams also explaine that phosphorus contents had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.19 A, B and C). Phosphorus contents explained 0.270%, 7.41% and 0.14% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.19 A, B and C).

Figure 4.2.18: Phosphorus (%) of tested plant species for P. solenopsis.

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Figure 4.2.19: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (phosphorus %).

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4.2.4 Potassium contents and its association with attractiveness index of P. solenopsis Potassium contents among the tested plant species ranged from 1.28 to 5.88%. Maximum concentration (≥4.75%) was recorded in H. rosa-sinensis (5.88%), followed by 4.75% in P. oleraceae. Minimum concentrations <2.5% were recorded in L. nudicaulis (2.28%), S. melongena (2.22%), D. arvensis (2.08%), A. spinosus (1.88%), A. esculentus (1.68%), C. arvense (1.44%), L. camara (1.38%) and C. frutescense (1.28%). Intermediate potassium concentration between the minimum and maximum (≥3.44 but <4.2%) was recorded in the plant species including C. album (3.4%), E. prostrate (3.5%), C. didimus (3.66%), C. morale (3.72%), W. somnifera (3.94%), C. arvensis (4.18%) and C. bonariensis (4.2%) (Figure 4.2.20). The probability values in all scatter diagrams indicated that association existed between potassium contents and attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.21 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that potassium concentration had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.21 A, B and C). Regression parameters and scatter diagrams also explaine that potassium contents had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.21 A, B and C). Potassium contents demonstrated 3.96, 16.1 and 7.46% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.21 A, B and C).

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Figure 4.2.20: Potassium (%) of tested plant species for P. solenopsis.

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Figure 4.2.21: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Potassium %).

4.2.5 Nitrogen contents and its association with attractiveness index of P. solenopsis Nitrogen contents among the tested plant species ranged from 1.05 to 3.95%. Maximum concentration (3.95%) was recorded in H. annuus but minimum in C. morale (1.05) followed by 1.1% in E. prostrate and H. rosa-sinensis 1.16%. Maximum concentrations of nitrogen after H. annuus ranged between 2.7-3-0% A. esculentus (3.0) and 2.9% in all P. oleraceae, W. somnifera and E. prostrate followed by 2.7% in L. nudicaulis. Minimum concentration of nitrogen after C. morale, E. prostrate and H. rosa- sinensis ranged from 1.78- 2.57% that include plant species that contain intermediate concentrations of nitrogen. The nitrogen concentration was 1.78% in C. inerme, 2.0% in both D. arvensis, C. bonariensis, (2.1%), however in C. didimus, T. terrestris and T. partulacastrum and S. melongena (2.22%), 2.3% in A. aspera, 2.5% in all P. hysterophorus, T. partulacastrum, C. arvensis and C. frutescence (Figure 4.2.22). The probability values in all scatter diagrams indicated that association existed between nitrogen contents and attractiveness index of first, second and third instar nymphs of P. solenopsis (P value <0.05) (Figure 4.2.23 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that nitrogen concentration had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.23 A, B and C). Regression parameters and scatter diagrams also explaine that nitrogen contents had

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significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.23 A, B and C). Nitrogen contents explained 1.5, 0.5 and 1.6% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.23 A, B and C).

Figure 4.2.22: Nitrogen (%) of tested plant species for P. solenopsis.

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Figure 4.2.23: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (nitrogen%).

4.2.6 Sodium contents and its association with attractiveness index of P. solenopsis Sodium contents among the tested plant species ranged from 0.1 to 1.8%. Maximum concentration (≥1.3%) were recorded in H. rosa-sinensis (1.8%), followed by 1.7% in all C. morale, E. prostrate, S. melongena and G. hirsutum whereas it was 1.6% in D. arvensis and 1.5% in C. arvensis, C. didimus, P. hysterophorus and T. partulacastrum. All remaining plant species had sodium contents in the range of ≥0.7 but < 1.2 % was recorded in T. terrestris (0.7%), in both C. frutescence and C. bonariensis (0.8%), C. album (0.9) and P. oleraceae (1.1%) (Figure 4.2.24).

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The probability values in all scatter diagrams indicated that association existed between sodium contents and attractiveness index of first, second and third instar nymphs of P. solenopsis (P value <0.05) (Figure 4.2.25 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that sodium concentration had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value is closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.25 A, B and C). Regression parameters and scatter diagrams also explained that phosphorus contents had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.25 A, B and C). Sodium contents explained 4.40%, 22.3% and 7.2% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.25 A, B and C).

Figure 4.2.24: Sodium (%) of tested plant species for P. solenopsis.

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Figure 4.2.25: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (sodium %).

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4.2.7 Total soluble sugar percentage and its association with attractiveness index of P. solenopsis Total soluble sugar percentage among the tested plant species ranged from 2.86 to 3.93%. Maximum total sugar contents in the range of ≥2.86 but < 3.43% were recorded in H. annuus (3.43%), followed by 3.37% in both C. arvense and C. arvensis that was statistically at par with A. aspera 3.26%, L. nudicaulis (3.1%), A. esculentus (3.06%), T.terrestris (2.98%), H. rosa-sinensis (2.97%) and D. arvensis (2.86%).1.68% in T. partulacastrum, 3.4% in H. annuus, 1.28% in E. prostrate, 1.25% in W. somnifera and 1.23% in P. hysterophorus. Total sugar in P. oleraceae (0.97%), C. bonariensis (1.13%), 1.46% in both E. prostrate and T. partulacastrum, 1.57% in C. inerme and 1.7% C. album was recorded (Figure 4.2.26). The probability values in all scatter diagrams indicated that association existed between total soluble sugars and attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.27 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that total soluble sugar had negative correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion value was closer to positive one (-1) and data points were found scattered closer to the negatively sloped line (Figure 4.2.27 A, B and C). Regression parameters and scatter diagrams also explained that total soluble sugar had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.27 A, B and C). Total solule sugar explained 0.02%, 1.63% and 0.41% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.27 A, B and C).

Figure 4.2.26: Total soluble sugar (%) of tested plant species for P. solenopsis.

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Figure 4.2.27: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Total soluble sugar %).

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4.2.8 Reducing sugar percentage and its association with attractiveness index of P. solenopsis Reducing sugar percentage among the tested plant species ranged from 0.14 to 1.33%. Maximum reducing sugar contents in the range of ≥1.17 but < 1.33% were recorded in C. arvensis (1.33%), followed by A. aspera (1.32%), W. somnifera (1.27%), D. arvensis (1.26%), T. terrestris (1.21%), L. camara (1.17%) and C. morale (1.14%) that was statistically at par with A. esculentus 0.98%, H. annuus 0.96%, G. hirsutum 0.92% and E. prostrate 0.91%. However, minimum reducing sugar concentration ≥0.14 but < 0.36% was recorded in E. prostrate (0.14%), S. melongena (0.15%), A. spinosus (0.21%), C. frutescens (0.26%), C. inerme (0.28%), C. arvensis (0.29%) and C. bonariensis (0.36%) (Figure 4.2.28). The probability values in all scatter diagrams indicated that association existed between reducing sugars and attractiveness index of first, second and third instar nymphs of P. solenopsis (Pvalue <0.05) (Figure 4.2.29 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that reducing sugar had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion values were closer to positive one (+1) and data points were found scattered closer to the poitively sloped line (Figure 4.2.29 A, B and C). Regression parameters and scatter diagrams also explained that reducing sugar had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.29 A, B and C). Reducing sugar explained 1.14, 1.16 and 0.4% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.29 A, B and C).

Figure 4.2.28: Reducing sugar (%) of tested plant species for P. solenopsis.

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Figure 4.2.29: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (reducing sugar %).

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4.2.9 Crude protein contents and its association with attractiveness index of P. solenopsis Crude protein contents among the tested plant species ranged from 6.50 to 24.6%. Maximum concentration (24.6%) was recorded in H. annuus but minimum in C. morale (6.75%) followed by 6.9% in E. prostrate. Comparatively high concentrations of crude protein after H. annuus ranged between 16.9-18.8% A. esculentus (18.8%), 18.2% in all P. oleraceae, W. somnifera and E. prostrate followed by 13.2% in L. nudicaulis. Minimum concentration of crude protein after C. morale, E. prostrate, C. didimus, P. hysterophorus and C. frutescence ranged from 7.78-13.0% that include plant species that contain intermediate concentrations of crude protein. The crude protein concentration was 6.78% in C. inerme, 12.0% in both D. arvensis, C. bonariensis, (13.1%) in all C. didimus, T. terrestris and T. partulacastrum, 14.2% in S. melongena, 15.3% in A. aspera, 17.5% in all P. hysterophorus, T. partulacastrum, C. arvensis and C. frutescence (Figure 4.2.30). The probability values in all scatter diagrams indicated that association existed between crude protein contents and attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.31 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that crude protein concentration had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient of correlarion values were closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 4.2.31 A, B and C). Regression parameters and scatter diagrams also explained that crude protein had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.31 A, B and C). Crude Protein contents explained 1.5%, 0.5% and 1.6% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.31 A, B and C).

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Figure 4.2.30: Crude protein (%) of tested plant species for P. solenopsis.

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Figure 4.2.31: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Crude protein %).

4.2.10 Chlorophyll concentration percentage and its association with attractiveness index of P. solenopsis Chlorophyll contents percentage among the tested plant species ranged from 0.09 to 0.22mg/gm. Maximum chlorophyll contents in the range of ≥0.15 but < 0.25mg/gm were recorded in H. annuus (0.23mg/gm), followed by A. esculentus (0.22mg/gm), C. arvense (0.20mg/gm), P. oleraceae (0.176mg/gm), C. frutescense (0.172mg/gm), whereas all plant species including P. hysterophorus (0.17mg/gm), L. camara (0.17mg/gm), H. rosa-sinenis (0.17mg/gm), C. arvensis, C. didimus (0.17mg/gm), E. prostrate (0.17mg/gm), C. bonariensis (0.16mg/gm), S. melongena (0.165mg/gm), G. hirsutum (0.163mg/gm), A. spinosus (0.167mg/gm), C. inerme (0.158mg/gm), T. partulacastrum (0.160mg/gm), C. morale (0.16mg/gm), T. terrestris (0.153mg/gm) and A. aspera (0.165mg/gm). Least concentration of chlorophyll was recorded in plant species including L. nudicaulis (0.095mg/gm) and C. album (0.098mg/gm). Chlorophyll contents >10 but <15 mg/gm was recorded on plant species including E. prostrate (0.139) and D. arvensis (0.14 mg/gm) (Figure 4.2.32). The probability values in all scatter diagrams indicated that association existed between chlorophyll and attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.33 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that chlorophyll had positive correlation with attractiveness index of first, second and third instar nymphs of P. solenopsis as coefficient

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of correlarion value was closer to positive one (+1) and data points were found scattered closer to the poitively sloped line (Figure 4.2.33 A, B and C). Regression parameters and scatter diagrams also explained that chlorophyll had significant linear association with and demonstrated significant variability in attractiveness index of first, second and third instar nymphs of P. solenopsis (P<0.05) (Figure 4.2.33 A, B and C). Chlorophyll contents explained 8.5%, 13.6% and 1.55% of the total variability in attractiveness of first, second and third instar nymphs of P. solenopsis (Figure 4.2.33 A, B and C).

Figure 4.2.32: Chlorophyll content (mg/gm) of tested plant species for P. solenopsis.

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Figure 4.2.33: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (attractiveness index of first (A), second (B) and third instar (C) nymphs of P. solenopsis) on X (Chlorophyll contents %).

4.2.11 Cluster analysis among studied traits Twenty five plant species were categorized into three different clusters with the help of cluster analysis (Figure 4.4). Clusters were made on the basis of attractiveness index of mealybug and biochemical traits of the selected plant species. Cluster ANOVA revealed that there were significant differences in the biochemical leaf traits of the tested host plants and the attractiveness index of P. solenopsis (Pvalue <0.05) (Table 4.2.7). Cluster-1 comprised of twelve plant species including L. camara, H. rosa-sinensis, H.annuus, P. hysterophorus, W. somnifera, E. prostrate, P. oleracea, S. melongena, T. portulacastrum, G. hirsutum, A. esculentus and C. frutescens having final cluster center readings of 1.72, 0.72, 0.5, 0.25, 0.06, 1.16, 0.1, 0.95 and 7.5% for nitrogen, phosphorus,

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potassium, sodium, reducing sugar, total soluble sugar, chlorophyll, attractiveness index and crude protein respectively. Cluster-2 consisted of a group of five plant species including C. arvensis, E. prostrate, A. spinosus, C. inerme, and T. terrestris demonstrating final cluster center readings of 2.5, 0.64, 0.63, 0.7, 0.19. 1.42 0.3, 0.078 and 13.8% for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, attractiveness index, chlorophyll and crude protein respectively while cluster-3 possessed eight plant species including L. nudicaulis, C. didimus, C. arvense, C. morale, C. album, A. aspera, C. bonariensis, D. arvensis demonstrating final cluster center readings of 2.8, 0.6, 0.45, 0.77, 0.29, 2.1, 0.6, 0.057 and 16.3% for nitrogen, phosphorus, potassium, sodium, reducing sugar, total soluble sugar, attractiveness, chlorophyll and crude protein respectively (Table 4.2.7). Cluster-1 comprised of the most preferred host plant species as compared with cluster-2 and cluster-3. The plants included in cluster-2 demonstrated intermediate preference and were considered as neutral plants for P. solenopsis. However, the plant species included in cluster-3 exhibited the least preference for P. solenopsis. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species (Table 4.2.8) revealed that plant species of cluster 2 demonstrated maximum diversity (D2= 25.3%) against the members of cluster 3 for the most of the studied traits. 4.2.12 Principal component analysis In this study, three out of seven Principal components (PCs) were taken having Eigenvalues ≥1. Results depicted that first three PCs expressed 83% of the total variability amongst the selected plant species for P. solenospsis while other PCs contributed only about 17% of the total variability (Table 4.2.9). PC1 contributed maximum variability (40%) following PC2 (26%) and PC3 (17%). The biochemical traits like sodium, potassium, phosphorus and reducing sugar explained positive but nitrogen, chlorophyll, crude protein and total sugars demonstrated negative factor loadings on PC1. Biochemical traits like nitrogen, potassium, sodium, reducing, and total soluble sugars revealed positive but crude protein, chlorophyll and nitrogen expressesed negative factor loading on PC2. Nitrogen, phosphorus, potassium, sodium, reducing sugar, chlorophyll and crude protein demonstrated positive but total sugar explained negative factor loadings on PC3 (Table 4.2.9).

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Dendrogram Complete Linkage, Euclidean Distance

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Figure 4.4: Cluster analysis regarding similarity between biochemical traits versus attractiveness index of P. solenopsis.

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Table 4.2.7: ANOVA parameter for cluster and cluster membership among biochemical traits of some host plants toward attractiveness index of P. solenopsis. Independent variables d.f F P Final Cluster Centers % Cluster-1 Cluster-2 Cluster-3 L. camara, H. rosa-sinensis, C. arvensis, L. nudicaulis, H.annuus, P. hysterophorus, E. prostrate, C. didimus, W. somnifera, E. prostrate, A. spinosus, C. arvense, P. oleracea, S. melongena, C. inerme, C. morale, T. portulacastrum, G. hirsutum, T. terrestris C. album, A. esculentus and C. frutescens A. aspera, C. bonariensis, D. arvensis Nitrogen (%) 2/22 1.2 0.00 1.72 2.5 2.8 Phosphorus (%) 2/22 0.56 0.00 0.72 0.64 0.6 Potassium (%) 2/22 0.42 0.00 0.5 0.63 0.45 Sodium (%) 2/22 0.5 0.00 0.25 0.7 0.77 Reducing sugar (%) 2/22 0.2 0.00 0.06 0.19 0.29 Total soluble sugar (%) 2/22 0.32 0.00 1.16 1.42 2.1 Attractive index 2/22 0.40 0.00 0.1 0.3 0.6 Chlorophyll (mg/gm) 2/22 0.15 0.00 0.95 0.078 0.057 Crude protein (%) 2/22 1.3 0.00 7.75 13.8 16.3

Table 4.2.8: D2 distance among different clusters among biochemical traits of some host plants toward attractiveness index of P. solenopsis. Cluster-1 Cluster-2 Cluster-3 Cluster-1 0.000 Cluster-2 25.3 0.000 Cluster-3 11.8 15.5 0.000

Table 4.2.9: Principal component analysis of biochemical traits in different plant species of P. solenopsis. Eigenvalue PC1 PC2 PC3 PC4 PC5 PC6 PC7 2.84 1.81 1.18 0.48 0.34 0.18 0.15 % of total 0.40 0.26 0.17 0.07 0.05 0.02 0.02 variance Cumulative 0.40 0.66 0.83 0.90 0.95 0.98 1.00 variance % Factor loading by various biochemical traits. Variable PC1 PC2 PC3 PC4 PC5 PC6 PC7 Attractive index -0.38 0.06 0.61 -0.19 0.45 -0.10 -0.46 Nitrogen (%) -0.45 0.03 0.46 0.05 -0.57 0.38 0.31 Phosphorus (%) 0.49 -0.23 0.15 -0.44 -0.06 0.64 -0.27 Potassium (%) 0.47 0.09 0.42 0.03 -0.49 -0.54 -0.20 Sodium (%) 0.40 0.27 0.39 0.54 0.39 0.24 0.32 Reducing sugar (%) 0.07 0.64 0.004 -0.63 0.08 -0.08 0.39 Total soluble sugar (%) -0.07 0.66 -0.24 0.26 -0.20 0.27 -0.55 Chlorophyll (mg/gm) -0.46 0.04 0.43 0.03 -0.7 0.35 0.2 Crude protein % -0.45 0.29 0.47 0.06 -0.6 0.41 0.33

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Discussion The experiment was conducted to determine physico-morphic and biocheminal based antixenosis mechanism of resistance in different plant species against cotton mealybug P. solenopsis. Attractiveness index of mealybug, physico-morphic and biocheminal traits of the tested plants and their association were determined to investigate the possible physico-morphic and biocheminal base inducing antixenosis. Attractiveness, food selection and utilization by insect species are valuable steps which vary and demonstrate food and oviposition preference among different plants (Roitberg et al., 1999; Singer, 2000; West and Cunningham, 2002; Stamps and Linit, 2002; Nieminen et al., 2003; Arif et al., 2012). It may be due to the availability of qualitative and quantitative nutrients, volatile compounds, secondary metabolites, phenology, tissue hardness and other defensive mechanisms of the plants (Joachim-Bravo et al., 2001; McNeely and Singer, 2001; Awmack and Leather, 2002; De Bruyn et al., 2002; Morewood et al., 2003; Mannion et al., 2003; Meiners et al., 2005; Coley et al., 2006; Arif et al., 2012). The present findings revealed that attractive index of first, second and thirs instars of P. solenopsis significantly varied and ranged between < 0.1 to >1 among the tested plant species which were ctaegories as resistant, neutrally attractive and highly attractive plant species. The variation in attractiveness index of instars of P. solenopsis for same types of plant species may be attributes to their differential requirement of nurients which may vary in these plants as well as to differences in tested physico- morphic plant traits of twenty five plant species that may hinder their performance, proboscis insertion and feeding, movements etc. Similar reasons for antixenosis in plants against insects were documented by various researchers (Price et al., 1980; Abrahamson and Weiss, 1997; Morris and Dwyer, 1997; Underwood, 1999; Cortesero et al., 2000; Dhaliwal and Arora, 2003) who concluded that morphological and biochemical traits of the plants impair the normal feeding and/or oviposition of insect pests by limiting the amount of feeding and/or oviposition. The stage specific population density variation in mealybug as observed in present study on different plant species may be accredited to deficiency of specific growth promoting nutritional components or access of growth inhibiting chemical in one and other plant species observed in present study. The conclusion of Bernays and Chapman (1994) also support the results of present finding. They concluded that despite of trichomes on leaf, some other morphological structures including leaf shape, its angle, trichome length, leaf area, leaf thickness or some other may affect attractiveness of mealybug acting as barrier for the attachment of mealybug.

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The results of present findings exhibited positive association between leaf thickness and attractiveness of mealybug that are contradictory to the findings of other researchers that may be due to change in test insect pest because trichome length deters the feeding and oviposition of jassid. Mealybug can attack even more on the thick stem as compared with the tender leaf, however insect selection and utilization depends upon both biophysical and biochemical factors (Bernays and Chapman, 1994). The additive effects of these factors enable the plants to provide barrier to normal feeding or by repelling insect pests via volatile exudates (Van- Emden and Peakall, 1996). The results of present studies described that all instars of P. solenopsis had attractive index ≥1 toward attractive plants while (attractive index <0.5) toward resistant plant species. The results of morphological traits of these plant revealed that attractive plants (G. hirsutum, L. camara and H. annuus) had higher number of trichomes (>150 trichomes/cm2), longer trichomes (> 2 µm), more leaf area (>70cm2) except L. camara and greater thickness (>1.25 µm); whereas, resistant plants species (D. arvensis, L. nudicaulis, A. aspera and C. arvense) had lower number of trichomes (<30 trichomes/cm2), shorter trichomes (≤1.00 µm), less leaf area (≤20cm2) and least thickness (<1.00 µm). These results proved the role of these plants traits in antixenosis mechanism of resistance in these plants against P. solenopsis. A positive association determined between mealybug attractiveness index and trichomes density, trichome length, leaf area and leaf thickness in present study also support the role of these physic-morphic traits in the antixenosis. Heng-Moss et al., (2003) also discussed that pubescence was positively correlated with buffalograss susceptibility to mealybugs; they further explained that glabrous leaf surface was suggested as a possible mechanism of resistance. Johnson- Cicalese et al. (1998) reported that trichome length and density on plant surface provided provide foothold support for early instars of mealybugs.

Coofficent of determination (R2) revealed that attractive index of first, second and third instars of mealybug with trichome density exhibited variation (31.7, 42.4, 17.5%), trichome length (7.0, 8.9, 11.0%), leaf area (15.7, 19.3 14.1 cm2) and leaf thickness explained (25.0, 32.4, 25.7%) of the total variation in attractiveness index of all instars of P. solenopsis. These results can not be comparaed and contradicted with the results of other research who worked on resistant mechanisms in plants against insects because no exact information on the association of physic-morphic traits of studies plants with attractiveness (antixenosic behavior) of P. solenopsis instars are available in reviewed

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literature. However these results can be compared or contradicted with the research results of those workers who described association of various plants traits included in present studies with sucking insect pests other than P. solenopsis. For example, Hassan et al. (1999) reported that trichome density and its length contributed significant role in the population fluctuation of jassid whitefly. The results are also in confirmatory to the findings of Chu et al. (2002) who reported that okra leaved strains of cotton having narrow leaf size had less number of whitefly as compared with normal leaf upland varieties.

Dietary requirement and fitness of insect pests depends upon the nutrient chemistry of host plant. Nutrients not only affect the growth and development of plant species but also alter the quality of their food source for herbivorous insect pest (Goncalves-Alvim et al., 2004; Mierziak, et al., 2014). The application of nitrogen fertilizer in plants normally increase herbivore feeding preference, food consumption, survival, growth, reproduction and population density (Zhong-xian et al., 2007). According to Varela and Seif, (2004) nitrogen application enhances leaf area of the plant due to improved radiation interception and higher rate of photosynthesis in plants also resulted in insect pest outbreaks (Dyck et al., 1979) because crops receiving high doses of nitrogen were more susceptible to insect pest attack and suffered heavier losses (Peng, 1993; Ajayi and Tabo, 1995). It has also been documented that quality and quantity of food affect food selection behavior, survival and reproduction of phytophagous insect pest (Du et al., 2004). Insect pest are forced to respond and decide either to be attracted or repelled from the food source for feeding and oviposition (Li et al., 2004; Arif et al., 2013). A well developed response has been observed in insect pests toward the chemical stimuli (Chelliah and Sambandam, 1974). Based on the results of present studies it was found that biochemical contents including phosphorus, potassium, nitrogen, crude protein, reducing sugar and sodium exerted positive but non significant effect while total soluble sugars demonstrated negative effect on the attractiveness of P. solenopsis. Comparatively high concentration of crude protein ranged between 16.9-18.8% among plant species. A. esculentus (18.8), P. oleraceae, W. somnifera and E. prostrate (18.2% in all) and L. nudicaulis (13.2%) consitituted the group of attractive plant species. The lower crude protein concentration was 6.78% in C. inerme and 12.0% in both D. arvensis and C. bonariensis that constituted the resistant plant species. These results can not be compared and contradicted as exact information on the biochemical based antixenosis of studies twent five plant species against P. solenopsis is not available in the reviewed literature. However, these results can be compared or contradicted with those reported by various researchers who investigated such mechanism of resistance in various other host plants against some other sucking insect pests but not against P. solenopsis. For example, Iqbal

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et al. (2011) reported that crude protein, nitrogen, lignin, reducing sugar, phosphorus and copper showed positive correlation with jassid infestation whereas neutral detergent fiber, acid detergent fiber, cellulose, silica, total ether, non reducing sugars, total sugars, calcium and magnesium had negative correlation with the population of jassid on okra. They further pointed out that crude protein showed the positive and significant impact (69%) on the jassid population fluctuation on okra which was followed by neutral detergent fibre with 21% contribution. When computed together, all the chemical components showed 99.7% role on jassid population fluctuation. Hu et al. (2010) reported that there was negative association between sugar concentrations and feeding as well as oviposition preference. Inhibition of feeding and oviposition in mites and whiteflies has also been documented by Singh (1988), Neal et al. (1994), Liu and Stansly (1995) and Slocombe et al. (2008) due to imbalanced nutrition. Singh and Agarwal (1988) reported that highly susceptible genotypes contained significantly higher amount of proteins, as compared to the resistant genotypes. Singh and Taneja (1989) reported a positive correlation between the protein contents and oviposition of jassids. Balasubramanian and Gopalan (1981) reported lesser amounts of reducing sugar in the susceptible variety as compared to that in the resistant ones to jassid. Singh and Agarwal (1988) reported a negative correlation among the incidence of A. biguttula biguttula and the amount of total sugars and non-reducing sugars in the leaves of resistance genotypes. These characteristics of plants are critically very important in decision making of insectpests for feeding, probing and oviposition (Joachim-Bravo et al., 2001; Shahid et al., 2012). These finding depict the role of plant nutrient in antoxenosis against sucking insect pest and support our finding against P. solenopsis which is also a sucking insect pest. In conclusion, the additive effects of physicomorphic/morphological and biochemical traits of plant species constitute the antixenosis mechanism of resistant which enable the plants to provide barrier to normal feeding and/or repel insect pests via nutrient based deficit clues and/or volatile allelochemicals/phytoallexins. The important physicomorphic plant trait investigated in present study was trichome density while major biochemical traits included phosphorous, potassium and total soluble sugar which demonstrated significant role in antoxenotic response of plant species against attractiveness by P. solenopsis. There is need to investigate the genomes of these plants which control the transcription of trichome density and modulate the phosphorous, potassium and total soluble sugar regulating pathways in plants and then insert those genomes into the conventional cultivars to develop P. solenopsis resistant cultivars by using biotechnological approaches.

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CHAPTER 5 OBJECTIVE 3

5.1 Determination of antibiosis mechanism of resistance in selected plant species for P. solenopsis Abstract Antibiosis mechanism of resistance studies revealed that biological parameters of P. solenopsis were highly influenced by the plant species. Results revealed that significant variation in nymphal duration and mortality, crawlers per ovisac, pre- oviposition and oviposition period of P. solenopsis was determined for host plant species (treatments) (P value <0.05). The higher number of crawlers per ovisac (>70 but <101 crawlers/ovisac) were produced when mealybug female was fed on H. rosa- sinensis, G. hirsutum, H. annuus, E. prostrate, W. somnifera and T. partulacastrum as compared with the other tested plant species. D. arvensis demonstrated more antibiosis effects in studied biological paramters of P. solenopsis. The female P. solenopsis fed on D. arvensis produced less number of crawlers (41.3 crawlers/ ovisac) and exhibited higher pre- oviposition period (5.6 days), higher mortality (75, 45 and 30%) and longer nymphal durations (6.67, 6.67 and 7.5 days) in 1st, 2nd and 3rd instar nymphs of P. solenopsis. Biochemical analysis of plant species revealed that phosphorus, potassium and sodium had positive association with nymphal mortality, nymphal durations, pre-oviposition and oviposition periods of the female but had negative association with crawlers density. Nitrogen, total soluble sugar, chlorophyll and crude protein had positive association with crawler density but negative with nymphal duration, nymphal mortality and reproductive periods. Sodium had negative association with crawler density but positive with nymphal mortality, nymphal and reproductive duration. Coefficient of determination values (R2) exhibited that phosphorus explained 27.5, 29.3, 49.3, 27.78, 31.6, 33.9, 45.2, 52.9 and 68.8%; potassium demonstrated 21.7, 30.8, 11.3, 21.3, 26.4, 24.1, 14.6, 7.5 and 18.07%; nitrogen attributed 8.2, 9.6, 9.1, 2.5, 4.9, 4.4, 6.5, 0.15 and 17.38%; crude protein contributed 8.2, 9.6, 9.1, 2.5, 4.9, 4.4, 6.5, 0.1 and 17.3%; total soluble sugar explained 27.8, 7.9, 8.6, 26.0, 12.8, 17.34, 8.8, 20.4 and 25.4%; reducing sugar described 0.01, 0.3, 3.18, 0.1, 1.2, 0.2, 1.68, 1.37 and 1.48%; sodium demonstrated 31.4, 22.2, 39.2, 25.2, 37.2, 38.0, 52.3, 30.4 and 33.6%; chlorophyll attribiuted 12.0, 12.0, 4.4, 7.9, 5.96, 10.0, 0.3, 2.3 and 1.8% of total variation in preoviposition-period, oviposition-period, crawlers/ovisac, mortality of 1st, 2nd and 3rd instars and nymphal (duration) of 1st, 2nd and 3rd instars, respectively. The results of cluster analysis and dendrogram reveal that plant species were categorized into three clusters and cluster-2 demonstrated maximum diversity against the members of cluster-3 for the most of the studied biochemical traits and biological parameters of P. solenopsis. PCA explained first four PCs which commutatively expressed 81% of the total variability among the slelected plant species for the biological parameters of P. solenopsis with maximum contribution of PC-1 (52%).

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Introduction

Antibiosis mechanism of resistance adversely affects the physiological functioning of herbivorous insect pests (Pedigo, 1996; Felkl et al., 2005). Ingestion of a plant by an insect may manifest antibiosis symptoms varying from acute or lethal to sub- chronic or mild effects that may be of permanent or temporary in nature (Dhaliwal and Arora, 2003). The most common symptoms in insect pests include larval death in the early instars, irregular growth rates, decline in size and weight of the larvae or nymphs, prolongation of the larval period, failure to pupate, failure of adults to emerge from the pupae, inability to concentrate on food reserves, followed by a failure to hibernate, abnormal adults, decreased fecundity, reduction in fertility, restlessness and abnormal behaviour, reduced honey dew secretions by sucking insect pests (Hartnett and Abrahamson, 1979; Pedigo, 1996). These symptoms appear due to the presence of toxic substances, nutrient-imbalances, presence of certain antimetabolities and enzymes, which adversely affect digestion process and also the utilization of various nutrients (Kogan, 1982; Pedigo, 1996). The development, survival, reproduction and life table parameters of insects are influenced by host plant type (Tsai and Wang, 2001; Kim and Lee, 2002; Li et al., 2004). The physical and volatile signals originate from plants that attract the insect to its surface whereas chemical and nutritional factors of the food substrate determine consumption, development and survival in the larval stages and egg production of subsequent adults (Singh and Mullick, 1997). The shorter developmental time and greater total reproduction of insects on a host plant indicate greater suitability of that plant (van Lenteren and Noldus, 1990). Host plant specificity and oviposition motivation are affected by the physiological state of insect pest including age, feeding status, mated status and egg load (Jallow and Zalucki, 1998). Several physiological and biochemical plant traits are important factors conferring mechanisms of nonprefference and antibiosis. A well known example is the presence of gossypol gland and phenolic compounds that exhibit resistance to several insect pests in cotton (Dhaliwal et al., 1993). These characters of plants provide protection against herbivorous insect pests or influence the development and growth of herbivorous insect pest, in this way activity of insect pest is affected. P. solenopsis is polyphagous insect pest which infests more than 154 plant species in 53 families but with variable level of infestation (Arif et al., 2009). A little work about the antibiosis effects of different host plants on the biology of P. solenopsis has been

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carried out as few examples of studies on this aspect are available in the reviewed literature indicating antixenotic effects of only one type of host plant. For example, Vennila et al. (2010) studied the biology of the mealybug, P. solenopsis on cotton in India and Akintola and Ande (2008) on H. rosa-sinensis in Nigeria. No work on the antibiosis mechnanism of resistance in such a massive number of indeginous host plants against P. solenopsis has been carried out in Pakistan. This pest exhibits not only varying degree of incidence but significant variation in its different biological parameters on different types of host plants (Akintola and Ande, 2008; Arif et al., 2009; Vennila et al., 2010). It was, therefore, imperative to study the biological parameters of P. solenopsis on indegicous host plants commonly available in Punjab, Pakistan; to determine the biochemical components of differet host plants and their association with the biological parameters P. solenopsis; and investigate the plant chemicals that play vital role in antibiosis mechanism of resistance. This study was carried out to investigate these aspects. Material and methods 5.1.1 Plant species The details of the plant species evaluated in present studies are given in Table 1.1. 5.1.2 Maintenance of mealybug colony Colony was maintained by following the procedure described in section 4.1.1.

5.1.3 Experimental layout for determining the antibiosis mechanism of resistance in different host plants Present study was carried out in the Integrated Pest Management laboratory (maintained at 25±2ºC and 65±5% relative humidity), Department of Entomology, University of Agriculture Faisalabad, Pakistan to determine the antibiosis effects of twenty five host plants on different biological parameters of cotton mealybug (CMB), P. solenopsis. For the study of biological parameters of CMB, glass vials having moistened filter paper at the bottom of vials and leaf piece over it were used. The ovisaced females were released on the leaf disc and confined there till the emergence of 1st instar nymphs which later on were used in the experiment. For the conduct of this study, seventy five experimental units were prepared and maintained for twenty five treatments (plant species) replicated thrice in completely randomized design. Each experimental unit consisted of two transparent cups of plastic glass inverted over each other. Nutrient solution was poured and one plant’s twigs were adjusted in the lower cup, while a hole was made in the bottom of 2nd inverted cup of each experimental unit to introduce the nymphs of mealybug. The purpose of using nutrient solution was to maintain the turgidity

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and nutrients in the leaves of the twigs for facilitating feeding. The twigs of selected plants were made free from any kind of contamination by rinsing in water and air-drying before adjusting in experiment unit. After the emergence of first instar crawlers from the ovisac of adult female, twenty five nymphs of each instar were isolated and brushed with the help of camel hair brush over the twig of each experiment unit through the hole made in the 2nd inverted cup. The hole was then plugged with cotton swab soaked in water. Each experimental unit was observed on daily basis till their molting into next instar and their exuvia was cleaned. The nymphs successfully molted to next instar stage were counted, the nymphal duration and percent survival of all instars and as well as number of crawlers per ovisac were also calculated. The pre-oviposition period was considered the time between the emergence of female and ovisac production, whereas oviposition period consisted of female’s egg laying period. Mortality of all nymphal instars was calculated by dividing the numbers of dead nymphs by total nymphs and then multiplying with 100. 5.1.4 Determining Biochemical traits of selected plants The protocols used for the determination of biochemical plants traits of twenty five host plants have already been explained in section 4.2.1. Statistical analysis The data on biological parameters of P. solenopsis and biochemical plant trainst of twenty five plant species were analysed by ANOVA techniques using computer operated statistica package 5.5 and means, in case of significant results, were compared by using Tukey test. These results were also subjected to uni- and multivariate analysis to determine biochemical plant traists and plant species inducing antibiosis mechanism of resistance against P. solenopsis. Pearson correlation coefficient values were used to estimate the association of biochemical plant traits with pre-oviposition and oviposition period, crawlers per ovisac, nymphal mortality and durations of first, second and third instars of mealybug. Similarly, cluster analysis was used to sort the plant species into their appropriate groups with minimum error by using Statistical Package for Social Sciences (SPSS) and Minitab softwares (Sneath and Sokal, 1973). The data were also subjected to principle component analysis using Minitab software for determining the contribution of plant’s chemical traits towards the variation in pre-oviposition and oviposition period, crawlers per ovisac, nymphal mortality and durations of first, second and third instars of mealybug of mealybug.

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Results Analysis of variance regarding pre-oviposition, oviposition duration, mortality and nymphal duration of mealybug on tested plants is given in Table 5.2.1. It is evident from the the results that pre-oviposition period, oviposition period, mortality and nymphal duration of mealybug varied significantly among the plant species (P<0.05). Table 5.2.1: ANOVA parameters regarding the effect of twenty five host plant species (treatments) on the biological parameters of P. solenopsis under laboratory. SOV Biological parameters Life stage of P. Df F-value P-Value solenopsis Treatments Pre-oviposition Adult females 24 5.5 0.0000** Plant Oviposition Adult females 24 9.8 0.0000** species 1st instar 24 24.9 0.0000** Mortality 2nd instar 24 15.6 0.005** 3rd instar 24 12.0 0.000** Duration 1st instar 24 2.7 0.000** 2nd instar 24 4.2 0.000** 3rd instar 24 2.88 0.000** Fecundity Adult females 24 22.4 0.000** (crawlers/ovisac) SOV= Source of variance, df= degree of freedom, SS= Sum of square, MS= mean sum of square, **= highly significant difference at P=0.05 5.2 Effect of plant species on life parameters of P. solenopsis 5.2.1 Effect of plant species on the longevity of 1st, 2nd and 3rd instar nymphs of P. solenopsis First instar duration among the tested plant species ranged between 3.0 to 6.67 days. Maximum duration was documented 6.67 days on both D. arvensis and G. hirsutum followed by E. prostrate (6 days) that was statistically at par (5-5.33 days) with C. morale, H. rosa-sinensis, C. didimus, C. bonariensis, S. melongena and T. partulacastrum. Minimum nymphal duration in the range of ≥3.0 but < 4.0 days was recorded on C. inerme (3.0 days), C. arvensis (3.3 days) and L.nudicaulis (3.3 days) that was at par with L. camara, W. somnifera, C.arvense, T. terrestris, E. prostrate, A. aspera and H.annuus with first instar duration (≥3.6 days). On the remaining plants including A. esculentus, C. album, C. frutescence, A. spinosus, P. oleraceae and P.hysterophorus first instar duration of mealybug was recorded (≥4.0 days) (Figure 5.2.1).

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Figure 5.2.1:Nymphal duration of first instar of P. solenopsis among tested plant species. Second instar duration among the tested plant species ranged from 3.33 to 6.67 days. Maximum duration (6.33-6.67 days) was recorded both on E. prostrate and D. arvensis (6.67 days) followed by C. album and G. hirsutum (6.33 days). On H. rosa- sinensis, C. didimus, C. bonariensis, S. melongena, T. partulacastrum, P. oleraceae, P. hysterophorus and H. annuus, the range of second instar duration was 5.0-5.7 days. Second instar duration in the range of >3.0 but ≤4.0 days was recorded on C. arvensis (3.3 days), L. nudicaulis (3.6 days), W. somnifera (4.0 days), A. esculentus (3.6 days) and T. terrestris (4.0 days). On the remaining plant species comprising of C. morale, C. arvense, C. frutescence, A. spinosus, C. inerme, E. prostrate and A. aspera, the second instar duration of mealybug was recorded 4.0 days (Figure 5.2.2).

Figure 5.2.2: Nymphal duration of second instar of P. solenopsis among tested plant species. Third instar duration among the tested plant species ranged from 4.00 to 8.33 days. Maximum duration (≥7.00-8.33 days) was recorded on C. morale, H. rosa-sinensis,

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C. didimus, E. prostrate, G. hirsutum, P. oleraceae, D. arvensis, E. prostrate, P. hysterophorus followed by C. bonariensis, S. melongena, C. frutescence and T. partulacastrum with third instar duration >6.33 days. Third instar duration was minimum on C. arvensis and A. esculentus (4.0 days), L. nudicaulis, A. aspera and H. annuus (4.33 days) being statistically similar with L. camara and W. somnifera (4.67 days). Third instar duration in the range of 5-5.67 days was recorded on C. arvense, C. album, A. spinosus, C. inerme and T. terrestris (Figure 5.2.3).

Figure 5.2.3: Nymphal duration of third instar of P. solenopsis among tested plant species. 5.2.2. Effect of different plant spcies on the mortality of 1st, 2nd and 3rd instar of P. solenopsis First instar mortality among the tested plant species ranged from 8.33 to 75.0 percent. Maximum mortality of first instar was observed on D. arvensis (75.0%) followed by C. bonariensis (69.7%). First instar mortality in range of ≥46.6 but <70% was observed on C. morale, H. rosa-sinensis, E. prostrate, S. melongena, C. album, T. partulacastrum and P. oleraceae. Minimum mortality of first instar mealybug in range between 8.3 to 11.6% was recorded on both L. nudicaulis and A. esculentus had (8.33%), T. terrestris (10%), L. camara (11.6%) and H. annuus (11.67%). Plant species including C. arvensis W. somnifera, C. didimus, A. arvense, G. hirsutum, A. spinosus, C. inerme, E. prostrate and P. hysterophorus caused first instar mortality range (18.33- 23.33%). However, 25-35% first instar mortality was recorded on A. aspera and C. frutescense (Figure 5.2.4).

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Figure 5.2.4: Mortality percentage of first instar of P. solenopsis among tested plant species. Second instar mortality among the tested plant species ranged from 6.6 to 46.6%. Maximum mortality of second instar of mealybug was exhibited in the range between ≥30.0-45.0%, on D. arvensis (45%), C. album (35.0%) and P. oleraceae (35.0%). Minimum mortality of mealybug second instar ranging between 1-15% was recorded on L. nudicaulis (10.0), A. esculentus (8.3%) T. terrestris (11.0%) and H. annuus (11.6%) which demonstrated statistically similar effects on mortality of second instar. Mortality of second instar ranged between 15-30% on C. morale, H. rosa-sinensis, C. arvensis, W. somnifera, E. prostrate, C. didimus, S. melongena, G. hirsutum, C. frutescense, A. spinosus, T. partulacastrum, C. bonariensis, C. arvense, C. inerme, E. prostrate, P. hysterophorus and A. aspera (Figure 5.2.5).

Figure 5.2.5: Mortality percentage of second instar of P. solenopsis among tested plant species.

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Mortality percentage of third instar among the tested plant species ranged from 5.00 to 31.6 percent. Maximum mortality (25.0-31.6%) was recorded on E. prostrate, C. album, G. hirsutum, T. partulacastrum, P. oleraceae and D. arvensis. Mortality percentage of third instar of mealybug ranged from 16.6-23.3% on H. rosa-sinensis, C. didimus, S. melongena and C. frutescense. Minimum mortality of third instar mealybug crawlers was recorded in the range of 5.0-8.3% being 8.3% on both L. camara and T. terrestris, 6.6% on L. nudicaulis and 5.0% on both A. esculentus and H. annuus (5.0%). Mortality percentage of third instar of female mealybug on C. morale, C. arvensis, W. somnifera, C. bonariensis, C. arvense, A. spinosus, C. inerme, E. prostrate, P. hysterophorus and A. aspera was ≥11 but <15% (Figure 5.2.6).

Figure 5.2.6: Mortality percentage of third instar of P. solenopsis female among tested plant species. 5.2.3. Effect of different plant species on some biological parameters of female P. solenopsis Pre-oviposition period among the tested plant species ranged from 2.60 to 5.67 days. Maximum duration (5-5.33 days) was recorded on P. oleraceae (5.3 days), G. hirsutum (5.0 days), D. arvense (5.6 days), P. hysterophorus (5.33 days) that was statistically at par with C. morale, H. rosa-sinensis, S. melongena, C. album, T. partulacastrum and E. prostrate (4.33-4.6 days). Pre-oviposition duration in the range of ≥2.5.0 but < 3.6 days was recorded on L. camara, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, C. bonariensis, C. arvense, C. frutescense, A. spinosus, C. inerme, T. terrestris, H. annuus and A. aspera (Figure 5.2.7).

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Figure 5.2.7: Pre-oviposition period of P. solenopsis female among tested plant species. Oviposition period of mealybug female among the tested plant species ranged from 2.67-6.5days. Maximum oviposition period (5-5.6 days) was observed on plant species including E. prostrate (5.6 days), H. rosa-sinensis (5.3 days), C. album (5.3 days) and P. hysterophorus (5.3 days), G. hirsutum (5.0 days) and P. hysterophorus (5.0 days), while on L. camara (4.3 days) and H. annuus (4.6 days) respectively. Oviposition period of adult mealybug female on L. nudicaulis, W. somnifera, C. arvense, C. inerme and D. arvensis was very short (2.6-3.1 days). Oviposition period of mealybug female on C. arvensis, C. bonariensis, A. esculentus, C. frutescense, A. spinosus, T. terrestris and E. prostrate was recorded >3.1 but <3.7 days respectively (Figure 5.2.8).

Figure 5.2.8: Oviposition period of P. solenopsis female among tested plant species. Crawlers per ovisac of mealybug female among the tested plant species ranged from 41.3 to 99.6. Maximum crawlers per ovisac (91.0 to 99.67) were recorded on both

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A. esculentus (99.3) and G. hirsutum (99.3); C. inerme (98.6), L. nudicaulis (98.3), W. somnifera (96.6), T. terrestris (96.0), H. annuus (95.3), C. frutescens (95.6), C. arvensis (94.0), A. sinosus (93.3), A. aspera (93.6) and C. bonariensis (91.0). Minimum crawlers were produced when females were fed on D. arvensis (41.3), however females fed on remaining tested plant species including L. camara, C. morale, H. rosa-sinensis, C. didimus, E. prostrate, S. melongena, C. arvense, C. album, T. partulacastrum, P. olereaceae, E. prostrate and P. hysterophorus produced ≥70 but < 90 crawlers per ovisac (Figure 5.2.9).

Figure 5.2.9: Crawler density of P. solenopsis among tested plant species.

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5.3 Biochemical contents and its association with biological parameters of P. solenopsis

5.3.1 Association of phosphorus contents of plant species with various biological parameters of P. solenopsis

The probability values in all scatter diagrams indicated that association existed between phosphorus percentage and pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.10 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrate that phosphorus percentage had high positive correlation with pre-oviposition, oviposition period of female P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were observed scattered closer to the positively sloped line but negative with crawlers per ovisac (Figure 5.2.10 A, B and C). Regression parameters and scatter diagrams also explaine that phosphorus percentage had significant linear association with and demonstrated significant variability in pre-oviposition and oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.10 A, B and C). Phosphorus percentage explained 27.5%, 29.0% and 49.3% of the total variability in pre- oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.10 A, B and C).

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Figure 5.2.10 A,B,C: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (pre-oviposition period of female (A), oviposition (B) and crawlers per ovisac (C) of P. solenopsis) on X (phosphorus%). The probability values in all scatter diagrams indicated that association existed between phosphorus percentage and nymphal mortality of first, second and third instar of

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P. solenopsis (P<0.05) (Figure 5.2.11 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrate that phosphorus percentage had positive correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were scattered closer to the positively sloped line (Figure 5.2.11 D, E and F). Regression parameters and scatter diagrams also explained that phosphorus percentage had significant linear association with and demonstrated significant variability for mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.11 D, E and F). Phosphorus percentage explained 27.7%, 31.6% and 33.9% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.11 D, E and F).

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Figure 5.2.11: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instars (F) of P. solenopsis) on X (phosphorus%).

The probability values in all scatter diagrams indicated that association existed between phosphorus percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.12 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that phosphorus percentage had high positive correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were scattered closer to the positively sloped line (Figure 5.2.11 G, H and I). Regression parameters and scatter diagrams also explained that phosphorus percentage had significant linear association with and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.11 G, H and I). Phosphorus percentage explained 45.2%, 52.9% and 68.8% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.11 G, H and I).

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Figure 5.2.12: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Phosphorus%).

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5.3.2 Association of potassium contents of plant species with various biological parameters of P. solenopsis The probability values in all scatter diagrams indicated that association existed between potassium percentage and pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.13 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that phosphorus percentage had positive correlation with pre-oviposition, oviposition period of female P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were appeared scattered closer to the positively sloped line however negative association existed with crawlers per ovisac (Figure 5.2.13 A, B and C). Regression parameters and scatter diagrams also explaine that potassium percentage had significant linear association with and demonstrated significant variability pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.13 A, B and C). Potassium percentage explained 21.7%, 30.8% and 11.3% of the total variability pre- oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.13 A, B and C).

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Figure 5.2.13: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (pre-oviposition period of female (A), oviposition (B) and crawlers per ovisac (C) of P. solenopsis) on X (Potassium%).

The probability values in all scatter diagrams indicated that association existed between potassium percentage and nymphal mortality of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.14 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that potassium percentage had positive correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were scattered closer to the positively sloped line (Figure 5.2.14 D, E and F). Regression parameters and scatter diagrams also explaine that potassium percentage had significant linear association with and demonstrated significant variability for mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.14 D, E and F). Potassium percentage explained 21.3%, 26.4% and 24.1% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.14 D, E and F).

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Figure 5.2.14: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instars (F) of P. solenopsis) on X (Potassium%). The probability values in all scatter diagrams indicated that positive association existed between potassium percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.15 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that potassium percentage had positive

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correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to positive one (+1) and data points were scattered closer to the positively sloped line (Figure 5.2.15 G, H and I). Regression parameters and scatter diagrams also explaine that potassium percentage had significant linear association with and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.15 G, H and I). Potassium percentage explained 14.6%, 7.5% and 18.0% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.15 G, H and I).

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Figure 5.2.15: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Potassium%). 5.3.3 Association of nitrogen contents of plant species with various biological parameters of P. solenopsis The probability values in all scatter diagrams indicated that negative association existed between nitrogen percentage and pre-oviposition, oviposition period of female P. solenopsis (P<0.05) but positive association existed with crawlers per ovisac (Figure 5.2.16 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that nitrogen percentage had negative correlation with pre-oviposition, oviposition period of female P. solenopsis as coefficient of correlarion value is closer to positive one (-1) but positive association with crawlers per ovisac as coefficient of correlarion value was closer to positive one (+1) and data points were demonstrated scattered closer to the positively sloped line (Figure 5.2.16 A, B and C). Regression parameters and scatter diagrams also explaine that nitrogen percentage had significant linear association with and demonstrated significant variability pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.16 A, B and C). Nitrogen percentage explained 8.2%, 9.6% and 9.1% of the total variability for pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.16 A, B and C).

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Figure 5.2.16: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Nitrogen%).

The probability values in all scatter diagrams indicated that association existed between nitrogen percentage and nymphal mortality of first, second and third instar of P.

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solenopsis (P<0.05) (Figure 5.2.17 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that nitrogen percentage had weak negative correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion values were not closer to negative one (-1) although data points were observed scattered closer to the negatively sloped line (Figure 5.2.17 D, E and F). Regression parameters and scatter diagrams also explained that nitrogen percentage had significant linear association with and demonstrated significant variability for mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.16 D, E and F). Nitrogen percentage explained 2.5%, 4.9% and 4.4% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.17 D, E and F).

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Figure 5.2.17: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Nitrogen%).

The probability values in all scatter diagrams indicated that association existed between nitrogen percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.18 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that nitrogen percentage had weak negative correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion values were not closer to negative one (-1) although data points were found scattered closer to the negatively sloped line (Figure 5.2.18 G, H and I). Regression parameters and scatter diagrams also explained that nitrogen percentage had significant linear association with and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.18 G, H and I). Nitrogen percentage explained 6.55, 0.15 and 17.3% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.18 G, H and I).

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Figure 5.2.18: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Nitrogen%).

5.3.4 Association of crude protein contents of plant species with various biological parameters of P. solenopsis

The probability values in all scatter diagrams indicated that negative association existed between crude protein percentage and pre-oviposition, oviposition period of female P. solenopsis (P<0.05) but positive association existed with crawlers per ovisac (Figure 5.2.19 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that crude protein percentage had weak negative correlation with pre- oviposition, oviposition period of female P. solenopsis as coefficient of correlarion values were not closer to positive one (-1) but positive association with crawlers per ovisac as coefficient of correlarion value was closer to positive one (+1) although data points were found scattered closer to the positively sloped line (Figure 5.2.19 A, B and C). Regression parameters and scatter diagrams also explained that crude protein percentage had

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significant linear association with and demonstrated significant variability pre- oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.19 A, B and C). Crude protein percentage explained 8.2%, 9.6% and 9.1% of the total variability for pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.19 A, B and C).

Figure 5.2.19: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Crude protein%).

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The probability values in all scatter diagrams indicated that association existed between crude protein percentage and nymphal mortality of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.20 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that nitrogen percentage had weak negative correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to negative one (-1) although data points were found scattered closer to the negatively sloped line (Figure 5.2.20 D, E and F). Regression parameters and scatter diagrams also explaine that crude protein percentage had significant linear association with and demonstrated significant variability for mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.20 D, E and F). Crude protein percentage explained 2.5, 4.9 and 4.4% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.20 D, E and F).

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Figure 5.2.20: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Crude protein%).

The probability values in all scatter diagrams indicated that association existed between crude protein percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.21 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrate that crude percentage had weak negative correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion values were closer to negative one (-1) and data points were found scattered closer to the negatively sloped line (Figure 5.2.21 G, H and I). Regression parameters and scatter diagrams also explained that crude protein percentage had significant linear association with and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.21 G, H and I). Crude protein percentage explained 6.5, 0.1 and 17.3% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.21 G, H and I).

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Figure 5.2.21: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Crude protein%).

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5.3.5 Association of total soluble sugar contents of plant species with various biological parameters of P. solenopsis The probability values in all scatter diagrams indicated that negative association existed between total soluble sugars percentage and pre-oviposition, oviposition period of female P. solenopsis (P<0.05) but positive association existed with crawlers per ovisac (Figure 5.2.22 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that total soluble sugar percentage had weak negative correlation with pre- oviposition, oviposition period of female P. solenopsis as coefficient of correlarion values were closer to negative one (-1) but positive association with crawlers per ovisac as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 5.2.22 A, B and C). Regression parameters and scatter diagrams also explaine that total soluble sugar percentage had significant linear association with and demonstrated significant variability pre- oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.22 A, B and C). Total soluble sugar percentage explained 27.8%, 7.9% and 8.6% of the total variability for pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.22 A, B and C).

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Figure 5.2.22: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Total soluble sugar %).

The probability values in all scatter diagrams indicated that association existed between total soluble sugar percentage and nymphal mortality of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.23 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that total soluble sugar percentage had negative correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to negative one (-1) and data points were found scattered closer to the negatively sloped line (Figure 5.2.23 D, E and F). Regression parameters and scatter diagrams also explaine that total soluble sugar

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percentage had significant linear association with and demonstrated significant variability for mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.23 D, E and F). Soluble sugar percentage explained 26.0%, 12.8% and 17.3% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.23 D, E and F).

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Figure 5.2.23: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Crude protein%).

The probability values in all scatter diagrams indicated that association existed between total soluble sugar percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.24 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that crude percentage had high negative correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion value was closer to negative one (-1) and data points were found scattered but closer to the negatively sloped line (Figure 5.2.24 G, H and I). Regression parameters and scatter diagrams also explaine that total soluble sugar percentage had significant linear association with and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.24 G, H and I). Total soluble sugar percentage explained 8.8%, 20.4% and 25.4% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.24 G, H and I).

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Figure 5.2.24: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Total soluble sugar %).

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5.3.6 Association of reducing sugar contents of plant species with various biological parameters of P. solenopsis The probability values in all scatter diagrams indicated that negative association existed between reducing sugars percentage with pre-oviposition and crawlers per ovisac; however there existed positive association with oviposition period of female P. solenopsis (P<0.05) (Figure 5.2.25 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that reducing sugar percentage had weak negative correlation with pre-oviposition and crawlers per ovisac of female P. solenopsis as coefficient of correlarion value was closer to positive one (-1) but positive association with oviposition period as coefficient of correlarion value was closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 5.2.25 A, B and C). Regression parameters and scatter diagrams also explaine that reducing sugar percentage had significant linear association with and demonstrated significant variability pre- oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.25 A, B and C). Reducing sugar percentage explained 0.01%, 0.31% and 3.18% of the total variability for pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.25 A, B and C).

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Figure 5.2.25: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Reducing sugar%).

The probability values in all scatter diagrams indicated that association existed between reducing sugar percentage and nymphal mortality of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.26 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that reducing sugar percentage had negative correlation with nymphal mortality of first instar as coefficient of correlarion value was closer to negative one (-1) and data points were found scattered closer to the negatively sloped line but positive correlation with second and third instar of P. solenopsis (Figure 5.2.26 D, E and F). Regression parameters and scatter diagrams also explaine that

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reducing sugar percentage had significant linear association with and demonstrated significant variability for mortality of first, second and third instars of P. solenopsis (P<0.05) (Figure 5.2.26 D, E and F). Reducing sugar percentage explained 0.01%, 1.2% and 0.2% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.26 D, E and F).

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Figure 5.2.26: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis on X (Reducing sugar %).

The probability values in all scatter diagrams indicated that association existed between reducing sugar percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.27 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that reducing sugar percentage had positive correlation with nymphal duration of first, instar but negative association with second and third instar of P. solenopsis (Figure 5.2.27 G, H and I). Regression parameters and scatter diagrams also explained that reducing sugar percentage had significant linear association and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.27 G, H and I). Reducing sugar percentage explained 1.68%, 1.3% and 1.40% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.27 G, H and I).

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Figure 5.2.27: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis on X (Reducing sugar %).

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5.3.7 Association of sodium percentage of plant species with various biological parameters of P. solenopsis The probability values in all scatter diagrams indicated that positive association existed between sodium percentage with pre-oviposition and oviposition period; however there exist negative association with crawlers per ovisac of female P. solenopsis (P<0.05) (Figure 5.2.28 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that sodium percentage had high positive correlation with pre-oviposition and oviposition period of female P. solenopsis as coefficient of correlarion values were closer to positive one (+1) but negative association with crawlers per ovisac as coefficient of correlarion value was closer to negative one (-1) and data points were found scattered closer to the negatively sloped line (Figure 5.2.28 A, B and C). Regression parameters and scatter diagrams also explained that sodium percentage had significant linear association with and demonstrated significant variability pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (P<0.05) (Figure 5.2.28 A, B and C). Sodium percentage explained 31.4%, 22.2% and 39.2% of the total variability for pre-oviposition, oviposition period of female P. solenopsis as well as crawlers per ovisac (Figure 5.2.28 A, B and C).

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Figure 5.2.28: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Pre-oviposition period (A), oviposition period (B) and crawler per ovisac of female (C) of P. solenopsis) on X (Sodium %). The probability values in all scatter diagrams indicated that association existed between sodium percentage and nymphal mortality of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.29 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that sodium percentage had high positive correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion values were closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 5.2.29 D, E and F). Regression parameters and scatter diagrams also explained that sodium percentage had significant linear association with and demonstrated significant variability for nymphal mortality of first, second and

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third instars of female P. solenopsis (P <0.05) (Figure 5.2.9 D, E and F). Sodium percentage explained 25.2, 37.2 and 38.0% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.29 D, E and F).

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Figure 5.2.29: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (mortality % of first (A), second (B) and third instar (C) of P. solenopsis) on X (Sodium %).

The probability values in all scatter diagrams indicated that association existed between sodium percentage and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.30 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that sodium percentage had positive correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion values were closer to positive one (+1) and data points were found scattered closer to the positively sloped line (Figure 5.2.30 G, H and I). Regression parameters and scatter diagrams also explained that sodium percentage had linear association with and demonstrated significant variability for nymphal duration of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.30 G, H and I). Sodium percentage explained 52.3, 30.4 and 33.6% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.30 G, H and I).

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Figure 5.2.30: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Nymphal duration of first (A), second (B) and third instar (C) of P. solenopsis) on X (Sodium %).

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5.3.8 Association of chlorophyll contents of plant species with various biological parameters of P. solenopsis The probability values in all scatter diagrams indicated that association existed between Chlorophyll (mg/gm) and pre-oviposition, oviposition and crawlers per ovisac of P. solenopsis female (P<0.05) (Figure 5.2.31 A, B and C). The scatter diagram and coefficient of correlarion value (r) demonstrated that chlorophyll concentration had negative correlation with pre-oviposition, oviposition and crawlers per ovisac of P. solenopsis female as coefficient of correlarion values were closer to negative one (-1) and data points were found scattered closer to the negatively sloped line (Figure 5.2.31 A, B and C). Regression parameters and scatter diagrams also explained that chlorophyll percentage had significant linear association with and demonstrated significant variability for pre-oviposition, oviposition and crawlers per ovisac female P. solenopsis (P<0.05) (Figure 5.2.31 A, B and C). Chlorophyll contents explained 12.0, 12.0 and 4.40% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.31 A, B and C).

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Figure 5.2.31: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (pre-oviposition (A), oviposition duration (B) and crawlers per ovisac (C) of P. solenopsis) on X (chlorophyll mg/gm). The probability values in all scatter diagrams indicated that association existed between Chlorophyll (mg/gm) and nymphal mortality of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.32 D, E and F). The scatter diagram and coefficient of correlarion value (r) demonstrated that chlorophyll concentration had high negative correlation with nymphal mortality of first, second and third instar of P. solenopsis as coefficient of correlarion values were closer to negative one (-1) and data points were found scattered closer to the negatively sloped line (Figure 5.2.32 D, E and F). Regression parameters and scatter diagrams also explained that chlorophyll percentage had significant linear association with and demonstrated significant variability for nymphal

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mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.32 D, E and F). Chlorophyll contents explained 7.9, 5.9 and 10.0% of the total variability for nymphal mortality of first, second and third instars of P. solenopsis (Figure 5.2.32 D, E and F).

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Figure 5.2.32: Coefficient of determination (R²), linear regression equation, various regression papameters (df, Fvalues and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Nymphal mortality of first (D), second (E) and third instar (F) of P. solenopsis) on X (chlorophyll mg/gm).

The probability values in all scatter diagrams indicated that association existed between Chlorophyll (mg/gm) and nymphal duration of first, second and third instar of P. solenopsis (P<0.05) (Figure 5.2.33 G, H and I). The scatter diagram and coefficient of correlarion value (r) demonstrated that chlorophyll concentration had high negative correlation with nymphal duration of first, second and third instar of P. solenopsis as coefficient of correlarion values were closer to negative one (-1) and data points were found scattered closer to the negatively sloped line (Figure 5.2.33 G, H and I). Regression parameters and scatter diagrams also explained that chlorophyll contents had significant linear association with and demonstrated significant variability for nymphal mortality of first, second and third instars of female P. solenopsis (P<0.05) (Figure 5.2.33 G, H and I). Chlorophyll contents explained 0.3, 2.0 and 1.80% of the total variability for nymphal duration of first, second and third instars of P. solenopsis (Figure 5.2.33 G, H and I).

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Figure 5.2.33: Coefficient of determination (R²), linear regression equation, various regression papameters (df, F values and P values), coefficient of correlation (r) and scatter diagram showing the fitted simple regression line of Ŷ (Nymphal duration of first (G), second (H) and third instar (I) of P. solenopsis) on X (chlorophyll mg/gm).

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5.3.9 Cluster analysis among studied traits Twenty five plant species were categorized into three different clusters with the help of cluster analysis (Figure 5.2.34). Clusters were made on the basis of biological parameters of mealybug and biochemical traits of the selected plant species. Cluster ANOVA revealed that there were significant differences in the biochemical leaf traits of the tested host plants (P < 0.05) and the biological parameters of P. solenopsis (P < 0.05) (Table 5.2.3). Cluster-1 comprised of fifteen plant species including L. camara, H.annuus, C. inerme, C. arvensis, C. didimus, W. somnifera, A. esculentus, T.terrestris, A. spinosus, P. hysterophorus, E. prostrate, C. frutescens, L. nudicaulis, C. arvense and A. aspera having final cluster center readings of 0.78, 4.47, 5.37, 19.44, 15.3, 11.7, 3.33, 3.51, 91.5, 0.0750, 0.29, 2.51, 2.37, 14.81, 2.62 and 0.78 for sodium, second instar duration, third instar duration, first instar mortality, second instar mortality, third instar mortality, pre-oviposition period, oviposition period, crawlers per ovisac, chlorophyll, phosphorus, potassium, nitrogen, crude protein, total soluble sugar and reducing sugar respectively. Cluster-2 consisted of a group of eight plant species including E. prostrate, C. bonariensis, P. oleracea, C. album, T. portulacastrum, H. rosa-sinensis,S. melongena, C. morale D. arvensis demonstrating final cluster center readings of 1.42, 5.75, 6.97, 59.4, 32.5, 22.7, 4.81, 4.83, 78.2, 0.073, 0.37, 3.78, 2.19, 13.7, 1.82 and 0.78 for sodium, second instar duration, third instar duration, first instar mortality, second instar mortality, third instar mortality, pre-oviposition period, oviposition period, crawlers per ovisac, chlorophyll, phosphorus%, potassium, nitrogen, crude protein, total soluble sugar and reducing sugar respectively while cluster-3 possessed G. hirsutum demonstrating final cluster center readings of 1.70, 6.33, 7.33, 23.3, 46.6, 26.6, 5.00, 5.00, 49.3, 0.076, 0.47, 4.68, 1.53, 9.60, 2.26 and 0.923 for sodium, second instar duration, third instar duration, first instar mortality, second instar mortality, third instar mortality, pre-oviposition period, oviposition period, crawlers per ovisac, chlorophyll, phosphorus, potassium, nitrogen, crude protein, total soluble sugar and reducing sugar respectively (Table 5.2.3). The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species (Table 5.2.4) revealed that plant species of cluster 1 demonstrated maximum diversity (D2= 55.2%) against the members of cluster 3 for the most of the studied biochemical traits. 5.3.10 Principal component analysis In this study, four Principal components (PCs) were taken having Eigenvalues ≥1. Results depicted that first four PCs expressed 81% of the total variability amongst the

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selected plant species for P. solenospsis while other PCs contributed only about 19% of the total variability (Table 5.2.5). PC1 contributed maximum variability (52%) following PC2 (14%), PC3 (9%) and PC4 (6%). The biochemical traits like potassium, phosphorus, sodium and reducing sugar revealed positive while nitrogen, chlorophyll, crude protein and total soluble sugar expressed negative factor loadings on PC1. Similarly all biological parameters expressed positive factor loadings on PC1 except crawlers per ovisac. PC1 demonstrated significant contribution as compared with all other PCs (Table 5.2.5). Dendrogram Complete Linkage, Euclidean Distance

0.00

y

t 33.33

i

r

a Cluster-2

l i Cluster-1 Cluster-3

m

i

S 66.67

100.00 a s s s s s e a e e s a s e s e a s e s e s r li u ri u si r s s u r u t u m l n si m m a si t si a u t t n n rm fe n n s e ra r tu ra e n ru u e n ra n a n s n e i e e o p im t o g e t b c e t e m ic le re a v e n v c n s d s h su o n n s l a i s v ca u r . r in r s i a i o p r m i a a r r o r d c e a . m a e p . d r o i . lo s c . le a r a L. u s t H . C o . t s A . p r h e - a C n p . n e . C s C ru . C . e . C sa l o o . . . T . f A E t G m tu . b E D L A . s . ro r P . W C y S . a C h p . H . P T

Figure 5.2.34: Cluster analysis regardingObs e similarityrvations between biochemical traits versus biological parameters of P. solenopsis.

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Table 5.2.2: ANOVA parameter for cluster and cluster membership among biochemical traits of some host plants toward biological parameters of P. solenopsis. Independent d.f F P Final Cluster Centers variables Cluster-1 Cluster-2 Cluster-3 L. camara, H.annuus, C. E. prostrate, C. G. hirsutum inerme, C. arvensis, C. bonariensis, P. didimus, W. somnifera, oleracea, C. album, T. A. esculentus, portulacastrum, H. T.terrestris,A. spinosus, rosa-sinensis,S. P. hysterophorus,E. melongena, C. prostrate, C. frutescens, morale, L. nudicaulis,C. arvense D. arvensis and A. aspera Sodium (%) 2/22 3.4 0.00 0.78 1.42 1.70 Second Instar duration (days) 2/22 1.6 0.00 4.47 5.75 6.33 Third instar duration (days) 2/22 3.2 0.00 5.37 6.97 7.33 First instar mortality (%) 2/22 4.3 0.00 19.44 59.4 23.3 Second instar mortality (%) 2/22 1.2 0.00 15.3 32.5 46.6 Third mortality (%) 2/22 4.3 0.00 11.7 22.7 26.6 Pre-oviposition period (days) 2/22 3.5 0.00 3.33 4.81 5.00 Oviposition period (days) 2/22 3.0 0.00 3.51 4.83 5.00 Crawlers per ovisac 2/22 2.5 0.00 91.5 78.2 49.3 Chlorophyll (mg/gm) 2/22 1.2 0.00 0.0750 0.0733 0.0764 Phosphorus (%) 2/22 1.13 0.00 0.29 0.37 0.47 Potassium (%) 2/22 1.0 0.00 2.51 3.78 4.68 Nitrogen (%) 2/22 2.1 0.00 2.37 2.19 1.53 Crude protein (%) 2/22 3.6 0.00 14.81 13.7 9.60 Total soluble sugar (%) 2/22 3.1 0.00 2.62 1.82 2.26 Reducing sugar (%) 2/22 1.1 0.00 0.78 0.78 0.923

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Table 5.2.3. D2 distance among different clusters among different clusters among biochemical traits of some host plants toward biological parameters of P. solenopsis.

Cluster-1 Cluster-2 Cluster-3 Cluster-1 0.000 Cluster-2 46.9 0.000 Cluster-3 55.2 48.6 0.000 Table 5.2.4: Principal component analysis of biochemical traits in different plant species of P. solenopsis. PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 Eigenvalue 8.8 2.4 1.6 1.1 0.72 0.6 0.56 0.33 % of total variance 0.52 0.14 0.09 0.06 0.04 0.035 0.03 0.02 Cumulative variance % 0.52 0.66 0.75 0.81 0.86 0.9 0.93 0.95 Factor loading by various biochemical traits. Variable PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 1st instar duration (days) 0.29 -0.03 -0.13 -0.15 0.01 -0.06 0.416 0.08 2nd instar duration (days) 0.27 -0.29 -0.02 -0.11 -0.09 -0.04 0.09 -0.01 3rd instar duration (days) 0.30 0.01 0.187 -0.15 0.27 0.18 0.051 -0.03 1st instar mortality (%) 0.26 -0.08 0.01 0.353 -0.40 0.16 0.23 -0.00 2nd instar mortality (%) 0.3 -0.07 -0.1 0.069 -0.28 -0.304 -0.10 -0.08 3rd instar mortality (%) 0.30 -0.086 -0.06 0.11 -0.31 -0.199 -0.08 -0.14 Pre-oviposition period (days) 0.31 -0.045 0.06 0.040 -0.03 0.115 -0.25 0.16 Oviposition period (days) 0.29 -0.013 -0.003 -0.13 -0.21 0.15 -0.48 -0.01 Crawlers per ovisac -0.28 0.008 0.098 0.33 -0.19 0.13 0.06 -0.50 Chlorophyll (mg/gm) -0.15 -0.40 0.12 -0.18 0.05 -0.73 -0.01 -0.04 Phosphorus% 0.26 -0.16 0.091 -0.29 0.41 0.178 -0.17 -0.42 Potassium% 0.2 -0.2 -0.03 0.529 0.39 -0.28 -0.21 -0.36 Nitrogen% -0.13 -0.52 -0.30 0.13 0.08 0.21 -0.06 -0.02 Crude protein% -0.12 -0.52 -0.30 0.13 0.08 0.21 -0.06 -0.02 Total sugar (%) -0.16 0.21 -0.38 -0.47 -0.32 0.01 -0.08 -0.48 Reducing sugar (%) 0.02 0.24 -0.67 0.08 0.16 -0.11 -0.22 0.29 Sodium% 0.24 0.08 -0.32 -0.01 0.19 -0.01 0.54 -0.20

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Discussion The experiment was conducted to determine antibiosis based mechanism of resistance in different plant species against cotton mealybug P. solenopsis. Biological parameters of mealybug, and biochemical traits of the tested plants and their association were determined to investigate the possible biochemical based antibiosis mechanism of resistance. Due to the polyphagous nature of P. solenopsis, it was imperative to study the effect of different food plants on its biology because food quality is known to be an important factor affecting demography, survival, fecundity and life expectancy of insect pest (Dixon, 1987). Present studies revealed that significant variation in the life cycle of P. solenopsis was observed among tested plant species. Maximum number of crawlers per ovisac of mealybug female was produced when it was fed on H. rosa- sinensis, G. hirsutum, H. annuus, E. prostrate, W. somnifera, T. partulacastrum as compared with the other tested plant species. However crawler density was much reduced when fed on D. arvensis (<50 crawlers/ovisac), increased mortality of 1st instar upto 75%, nymphal duration of 1st instar (>6days), pre- oviposition (5.6 days), oviposition period (<3.75 days) however, H. annuus and L. camara with crawler density >90.0 but <100.0, mortality of 1st instar <15%, nymphal duration of 1st instar <4.0 days, pre-oviposition period <4 days and oviposition (>5.0 days). The shorter developmental time and greater total reproduction of insects on a host plant indicate greater suitability of that plant (van Lenteren and Noldus, 1990).

Cluster analysis results revealed that cluster-1 comprised of fifteen plant species including L. camara, H.annuus, C. inerme, C. arvensis, C. didimus, W. somnifera, A. esculentus, T.terrestris, A. spinosus, P. hysterophorus, E. prostrate, C. frutescens, L. nudicaulis, C. arvense and A. aspera having final cluster center readings of 0.78, 4.47, 5.37, 19.44, 15.3, 11.7, 3.33, 3.51, 91.5, 0.0750, 0.29, 2.51, 2.37, 14.81, 2.62 and 0.78 for sodium, second instar duration, third instar duration, first instar mortality, second instar mortality, third instar mortality, pre-oviposition period, oviposition period, crawlers per ovisac, chlorophyll, phosphorus, potassium, nitrogen, crude protein, total soluble sugar and reducing sugar respectively. Cluster-2 consisted of a group of eight plant species including E. prostrate, C. bonariensis, P. oleracea, C. album, T. portulacastrum, H. rosa- sinensis, S. melongena, C. morale D. arvensis demonstrating final cluster center readings of 1.42, 5.75, 6.97, 59.4, 32.5, 22.7, 4.81, 4.83, 78.2, 0.073, 0.37, 3.78, 2.19, 13.7, 1.82 and 0.78 for sodium, second instar duration, third instar duration, first instar mortality,

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second instar mortality, third instar mortality, pre-oviposition period, oviposition period, crawlers per ovisac, chlorophyll, phosphorus%, potassium, nitrogen, crude protein, total soluble sugar and reducing sugar respectively. Based on results of present studies short oviposition period of P. solenopsis was due to the imbalanced nutrition in D. arvensis on which P. solenopsis failed to complete its development properly and under stress it was forced to shift itself to reproductive stage and produced youngones for its survival. The results are partially in support to the finding of previous researchers who demonstrated that antibiosis symptoms vary from acute or lethal to sub-chronic or mild effects that may be of permanent or temporary in nature (Dhaliwal and Arora, 2003). The most common symptoms in insect pests include larval death in the early instars, irregular growth rates, decline in size and weight of the larvae or nymphs, prolongation of the larval period, failure to pupate, failure of adults to emerge from the pupae, inability to concentrate on food reserves, followed by a failure to hibernate, abnormal adults, decreased fecundity, reduction in fertility, restlessness and abnormal behaviour, reduced honey dew secretions by sucking insect pests (Hartnett and Abrahamson, 1979; Pedigo, 1996). These symptoms appear due to the presence of toxic substances, nutrient-imbalances, presence of certain antimetabolities and enzymes, which adversely affect digestion process and also the utilization of various nutrients (Kogan, 1982; Pedigo, 1996). Similar reasons for antibiosis in plants against insects were documented by various researchers (Tsai and Wang, 2001; Kim and Lee, 2002; Li et al., 2004; Arif et al., 2013) who concluded that biochemical traits of the plants impair the normal feeding and/or oviposition of insect pests by limiting the amount of feeding and/or oviposition.

Nutrients not only affect the growth and development of plant species but also alter the quality of their food source for herbivorous insect pest (Goncalves-Alvim et al., 2004; Mierziak, et al., 2014). The results of present studies described that biochemical contents including nitrogen, crude protein, total soluble sugar and chlorophyll contents exhibited positive association with nymphal duration, pre-oviposition and oviposition periods except nymphal mortality and crawlers per ovisac. However potassium, phosphorus, sodium demonstrated negative association with nymphal duration and pre- oviposition and oviposition periods except nymphal mortality and crawlers per ovisac. Phosphorus contents with coefficient of correlation (r=0.70) played significant role in pre- oviposition and oviposition period of female. In general plant species exhibiting resistance against P. solenopsis had less quantity of total soluble sugar, crude protein,

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chlorophyll and nitrogen contents but had more quantity of phosphorus, potassium, reducing sugar and sodium as compared with susceptible ones. These results can not be compared and contradicted as exact information on the biochemical based antibiosis mechanism among studies twenty five plant species against P. solenopsis is not available in the reviewed literature. However, these results can be compared or contradicted with those reported by various researchers who investigated such mechanism of resistance in various other host plants against some other sucking insect pests but not against P. solenopsis. Singh and Agarwal (1988) reported that highly susceptible genotypes contained significantly higher amount of proteins, as compared to the resistant genotypes. Singh and Taneja (1989) reported a positive correlation between the protein contents and oviposition of jassids. Similarly, Sarmah et al. (2011) demonstrated that weight of larva and cocoon was highly influenced by nitrogen and crude protein content of foliage. Among the other nutrients required for normal development of insectpest, the nitrogen content is most important component of the diet that influence insect pest performance (Prosser et al., 1992; Abisgold et al., 1994; Girousse and Bournoville, 1994; Febvay et al., 1988). The application of nitrogen fertilizer in plants normally increase herbivore feeding preference, food consumption, survival, growth, reproduction and population density (Zhong-xian et al., 2007). Dietary requirement and fitness of insect pests depends upon the nutrient chemistry of host plant. The additive effects of biochemical factors especially dietary requirements influence the life parameters of herbivorous insect pest (Van- Emden and Peakall, 1996; (Goncalves-Alvim et al., 2004; Mierziak, et al., 2014). These finding depict the role of biochemical factors in antibiosis mechanism against sucking insect pest and support our finding against P. solenopsis which is also a sucking insect pest. Antibiosis mechanism of resistance adversely affects the physiological functioning of herbivorous insect pests (Pedigo, 1996; Felkl et al., 2005). Maximum number of crawlers per ovisac of mealybug female was produced when it was fed on H. rosa- sinensis, G. hirsutum, H. annuus, E. prostrate, W. somnifera, T. partulacastrum. Results are contradictory to the finding of previous researchers because they studied the effect of one or two host plants against mealybug. Sahito et al. (2010) studied the biology of P. solenopsis on cotton Gossypium hirsutum and reported that longevity of P. solenopsis adult female was 22.2 days and life-cycle completion period was 47.7 days. However developmental period of first, second and third instar of P. solenopsis on Solanum tuberosum, G. hirsutum and H. rosa-sinensis plants were 7.5, 3.6 and 7.2 days, respectively. Developmental period of male mealybug was 20.3, 21.4 and

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21.8 days but 38.5, 39.4 and 39.2 days on S. tuberosum, G. hirsutum and H. rosa-sinensis, respectively (Hanchinal et al. 2010). Developmental duration of female mealy bug was shorter on G. hirsutum than H. rosa-sinensis, but was reverse for male development (Mammoon-ul-Rasheed et al., 2012). Developmental period of first, second and third instars, longevity and life cycle of adult female on Abelmaschus esculentus was 4.9, 7.9, 5.7, 24.8 and 43.4 days; whereas the same were 9.8, 8.6, 5.8, 27.6 and 51.8 days on H. rosasinensis, respectively. The developmental period for first as well as of second instars, pupal stage, adult longevity and life cycle of male was 5.6, 4.5, 4.3, 2.9 and 17.4 days, respectively, on Abelmaschus esculentus and the same were 7.5, 4.4, 5.3, 3.2 and 20.4 days on H. rosasinensis. The sex ratios recorded on A. esculentus and H. rosasinensis were 1:33.5 and 1:10.2, respectively (Sahito and Abro, 2012). Resistant plants induce antagonistic effects on the herbivorous insect pests. Plants including Rosa indica, Jatropha curcus, Mangifera indica, Saraca indica, Ocimum basilicum and Bougainvillea spp., however R. indica induced maximum mortality in 1st instar nymphs (70-90%), reduced fecundity (100-200 eggs/ovisac/female) and prolonged nymphal duration by 20- 23 days; as compared with H. rosa-sinensis and demonstrating >400 eggs/ovisac/female and nymphal duration ranging between 16-17 days was observed on G. hirsutum and H. annuus (Sana-Ullah et al., 2011). These variations in life cycle of P. solenopsis may be attributed with the biochemical contents of the tested plant species. Plant sap also contain some chemical and nutritional substances that develop the biological parameter of insect including insect development, its survival, insect stages and egg production in adults (Tsai and Wang, 2001; Kim and Lee, 2002; Li et al., 2004; Arif et al., 2013).

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CHAPTER 6 OBJECTIVE 4

6.1 Determination of tolerance mechanism of resistance in host plant of P. solenopsis Abstract Cotton mealybug (CMB) densities had significant effect on the biochemical contents of the tested plants. At low density (50 CMB/plant), studied plant species including L. camara, C. arvensis, P. hysterophorus, C. didimus, T. portulacastrum, T. terrestris, A. esculentus, C. frutescens, E. prostrate, S. melongena, C. album, H. annuus and G. hirsutum exhibited tolerance (0.08-0.1%) while rest of the plant species exhibited no tolerance. However at a density level of 100 CMB/plant, none of the selected plant species exhibited tolerance against P. solenopsis. Nitrogen contents were 2.5, 1.3, 1.2, 1.5, 2.8, 3.1, 2.2, 3.1, 2.5, 2.5, 3.1, 2.5, 3.1, 1.6, 2.7, 2.1, 1.8, 2.6, 3.1, 2.5, 2.1, 1.1, 2.1, 2.3 and 4.7% at 0 CMB/plant, but 3.2, 2.9, 2.8, 3.2, 2.5, 3.8, 2, 2.8, 3, 2.1, 4.5, 4.3, 2.8, 4.4, 2.4, 3.6, 3.5, 2.3, 2.6, 2, 4, 3.5, 2.3, 2 and 3.7% at density of 50 CMB/ plant whereas contents were decreased to 2.1, 0.5, 1.0, 1.2, 2.2, 2.0, 1.8, 2.3, 1.5, 1.6, 2.5, 2.0, 2.6, 1.0, 2.7, 1.6, 1.6, 2.3, 2.7, 1.8, 1.5, 1.8, 2.1, 1.9 and 3.7% at density of 100 CMB/ plant in L. camara, C. morale, H. rosasinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus respectively. Cluster analysis revealed that cluster-1 comprised of fourteen plant species including L. camara, C. arvensis, H. annuus, T. terrestris, L. nudicallis, S. melongena, C. bonariensis, C. inerme, C. arvense, A. spinosus, P. oleracea, E. prostrate, E. prostrate and C. frutescens. Cluster-2 consisted of a group of three plant species including C. morale, H. rosa-sinensis and D. arvense, while cluster-3 possessed eight plant species including W. somnifera, A. aspera, A. esculentus, T. partulacastrum, P. hysterophorus, C. didimus, G. hirsutum, and C. album. The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species revealed that plant species of cluster-1 demonstrated 18% and 0.08% diversity against the members of cluster-2 and cluster-3 for the most of the studied biochemical traits, respectively. The members of cluster-3 exhibited 10.3% diversity against the members of cluster-2 for the most of the plant biochemical traits and tolerance. A principal component analysis (PCA) established to examine the relationship between leaf nutrients and different density of P. solenopsis depicted that, first two out of eight Principal components (PCs) having Eigenvalues ≥1 expressed 99% of the total variability amongst the selected plant species for P. solenospsis. Nitrogen, crude protein, sodium, total soluble sugar and chlorophyll were negatively correlated with mealybug density, but phosphorus, reducing sugar and potassium were positively correlated. Although all tested biochemical contents were decreased at higher mealybug density (100 mealybug/plant) but tolerance/compensatory growth, phosphorus, potassium were increased at low density (50 mealybug/plant) than control (without mealybug) confirming that plants exhibited tolerance mechanism against P. solenopsis. Introduction Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) mealybug originating from North America has co-evolved with several plants species and become a highly exotic polyphagous insect pest in about 24 countries of the world (Fand and

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Suroshe, 2015). Despite of cotton, more than 200 plant species are directly utilized for feeding, oviposition and development of the pest (Abbas et al., 2005, 2010; Vennila et al., 2010; Arif et al., 2013). Abelmoschus esculentus Linn., Capsicum annum Linn., Solanum melongena Linn., Solanum lycopersicum Linn., Punica granatum Linn., Psedium guajava Linn., Vites vinifera Linn., ornamentals plants like Hibiscus rosa-sinensis Linn., as well as various weeds (Tanwar et al., 2007; Nagrare et al., 2009; Vennila et al., 2010) serve as preferred host plants and carryover pest to the economic crop during cotton off season (Arif et al., 2009; Nagrare et al., 2009; Abbas et al., 2010; Vennila et al., 2010). Moreover mealybug P. solenopsis is risky to be managed through chemical control and has potential to develop resistance to most groups of insecticides. According to Saddiq et al. (2014), P. solenopsis has developed resistance to pyrethroid and organophosphate group of insecticides; especially chlorpyrifos, profenofos, bifenthrin, deltamethrin and lambda-cyhalothrin. Due to heavy potential of pest to utilize a wide diversity of host plant species and development of resistance against insecticides, P. solenopsis has poztential to disperse and invade in new regions in varying ecological conditions indicating that P. solenopsis can pose a serious risk to agricultural economy in future. Popularity of host plant resistance is increasing day by day due to its important role in integrated pest management. Plants deter insect pest attack due to the provision of mechanisms of resistance as well as have ability to withstand the effects of herbivory of arthropod. Attack of herbivorous arthropods modulate in infested plants various morphological and physiological changes (Hopkins and Huner, 2004) that include alteration in leaf area, number of leaves, dry weight, photosynthesis, chlorophyll, carbohydrates, water use efficiency, protein profile, wax deposition (barrier), accumulation of proline, activity of oxidative and lipid peroxidation enzymes (Ni et al., 2001; Heng-Moss et al., 2004; Znidarcic et al., 2008; Huang et al., 2013; Hussain et al., 2014), uptake of macro and micro-nutrients (Chapman et al., 2001; Wu et al., 2004; Al- Shareef, 2011) and production as well as volatilization of allelochemicals or secondary metabolites (Gogi et al., 2010; Al-Shareef, 2011). In response to pest attack, plants undergo compensatory growth and reparation as well as restitution of their biochemical contents exhibiting tolerance against infesting insects due to provision of various kinds of compensatory processes/mechanisms (Gogi et al., 2010; Al-Shareef, 2011; El-Zalabani et al., 2012). Huang et al. (2013) reported that initial infestation of P. solenopsis had no effect on chlorophyll content as well as on light utilization efficiency that might be due to compensatory photosynthesis. Biochemical

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modifications of the host plants also affect the physiological functioning of insect pest. According to Sarmah et al. (2011) weight of larva and cocoon was highly influenced by nitrogen and crude protein content of foliage. No information about the impact of pest densities on plant compensatory mechanisms is available in literature. Similarly, a little information is available on the extent of variation in such mechanisms in various host plant species. Although few host plants of P. solenopsis with varying degree of compensatory or tolerance mechanisms have been documented by different researchers (Huang et al., 2013); but the impact of population density of P. solenopsis on tolerance level and associated biochemical contents of its various host plants have not been explored yet. The present study was conducted to investigate compensatory growth and tolerance-associated biochemical variations in selected host plant species under biotic stress of different densities of P. solenopsis. Materials and methods: 6.1.1 Establishment of mealybug culture and experimental detail List of plant species used in this experiemnt is given in Table 1.1 of chapter 3, under section objective-1 while materials and method used for the establishment of mealybug culture is given in detail in section 4.1.1. The identical plants of weeds and economic plant species were collected from the field but ornamental plants were purchased from flower nursery and transplanted into the earthen pots containing homogenous mixture of soil (2:1:1 i.e., loamy, sand and farmyard manure respectively). Plants when needed were irrigated with equal quantity of water and fertilizer (1.5:1.0:0.5% N: P: K respectively) for uniformity among earthen plants. A set of three plants indicating three replications was prepared for each plant species. When the plants get established in earthen pots they were shifted into the field arranged in Completely Randomized Design for further experimentation. 6.1.2 Determination of tolerance level Three densities of adult female mealybug population i.e., 0, 50 and 100 CMB/plant were released on each selected plants which were caged by using muslin cloth of mesh size to retain mealybug population on plants as well as to avoid predators interference. These densities were maintained inside the cage for 30 days by adding fresh adult females from laboratory culture and/or removing dead and ovisaced female population when required.

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Because economic yield of weeds cannot be determined thus compensatory growth was assessed on vegetative growth basis following the equation as described by Qiu et al. (2011).

HT1 is height of plant after infestation, HT0 is height of plant before infestation, HC1 is the height of control measured at the time of HT1 and HC0 is height of control plant at HT0. 6.1.3 Biochemical analysis of plant species

In order to assess the biochemical alteration among control and mealybug infested plants; caged plants bearing different densities of mealybugs were collected from the field and brought into laboratory for biochemical analysis. Biochemical analysis was conducted in the Soil Chemistry Laboratory, Ayyub Agricultural Research Institute, Faisalabad. The detailed procedure of plant analysis is given in section 4.2.1. Statistical analysis The data collected were subjected to uni- and multivariate analyses to select plant species bearing resistance against P. solenopsis. Scatter diagram and Pearson Correlation Coefficient values were used to estimate the association of biochemical plant traits with density of mealybug. Dendrogram and genetic similarity among the plant species were also generated using the Jaccard’s Coefficient of similarity expressed as Euclidean genetic distances. Similarly, cluster analysis was used to sort the plant species into their appropriate groups with minimum error. The data was also subjected to principle component analysis by using Statistical Package for Social Sciences (SPSS) and Minitab softwares (Sneath and Sokal, 1973) for determining the variations in tolerance percentage of selected plant species toward different densities of mealybug. Results 6.1.4 Tolerance percentage in different plant species toward P. solenopsis At low density i.e., 50 CMB/plant, studied plant species including L. camara, C. arvensis, P. hysterophorus, C. didimus, T. portulacastrum, T. terrestris, A. esculentus, C. frutescens, E. prostrate, S. melongena, C. album, H. annuus and G. hirsutum exhibited tolerance in the range of 0.02-0.09% while rest of the plant species exhibited no tolerance. Tolerance was maximum (0.09%) both in C. didimus and C. frutescence but minimum in T. terrestris, E. prostrate and C. album (0.02%). However, at a density level of 100 CMB/plant, none of the selected plant species exhibited tolerance against P. solenopsis (Figure 6.2.1).

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Figure 6.2.1. Effect of different densities of P. solenopsis on tolerance percentage of different plant species. 6.2 Biochemical changes in plants in response to different densities of P. solenopsis Significant variation in biochemical contents was recorded at different densities of P. solenopsis (p<0.05) (Table 6.2.1). Table 6.2.1. ANOVA parameters regarding effect of different densities of P. solenopsis on chemical contents of twenty five selected plant species. Source CMB/plant Df F-value P-Value Potassium 0 2a/48b 7.8 0.003* 50 2a/48b 8.2 0.000* 100 2a/48b 7.98 0.001* Phosphorus 0 2a/48b 7.0 0.001* 50 2a/48b 8.2 0.000* 100 2a/48b 7.7 0.002* Nitrogen 0 2a/48b 6.3 0.003* 50 2a/48b 6.9 0.002* 100 2a/48b 7.0 0.003* Reducing sugar 0 2a/48b 5.6 0.000* 50 2a/48b 7.4 0.005* 100 2a/48b 6.6 0.008* Total soluble sugar 0 2a/48b 7.3 0.001* 50 2a/48b 8.6 0.007* 100 2a/48b 8.5 0.009* Crude protein 0 2a/48b 6.4 0.000* 50 2a/48b 8.5 0.006* 100 2a/48b 7.0 0.004* Sodium 0 2a/48b 5.03 0.002* 50 2a/48b 7.46 0.00* 100 2a/48b 6.35 0.006* Chlorophyll 0 2a/48b 4.7 0.001 50 2a/48b 6.1 0.005 100 2a/48b 5.6 0.004 df= Degree of freedom;CMB= cotton mealybug;a=df of treatment; b=df of error;*= highly significant at 5% probability value

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6.2.1 Effect of different densities of P. solenopsis on nitrogen contents of plant species Nitrogen contents of plants infested with 0 CMB/plant were 2.5, 1.3, 1.2, 1.5, 2.8, 3.1, 2.2, 3.1, 2.5, 2.5, 3.1, 2.5, 3.1, 1.6, 2.7, 2.1, 1.8, 2.6, 3.1, 2.5, 2.1, 1.1, 2.1, 2.3 and 4.7% in L. camara, C. morale, H. rosasinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus (Figure 6.2.2). At density of 50 CMB/ plant concentration of nitrogen percentage was 3.2, 2.9, 2.8, 3.2, 2.5, 3.8, 2, 2.8, 3, 2.1, 4.5, 4.3, 2.8, 4.4, 2.4, 3.6, 3.5, 2.3, 2.6, 2, 4, 3.5, 2.3, 2 and 3.7% in L. camara, C. morale, H. rosasinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus respectively (Figure 6.2.2). However at density of 100 CMB/plant nitrogen contents were 2.1, 0.5, 1.0, 1.2, 2.2, 2.0, 1.8, 2.3, 1.5, 1.6, 2.5, 2.0, 2.6, 1.0, 2.7, 1.6, 1.6, 2.3, 2.7, 1.8, 1.5, 1.8, 2.1, 1.9 and 3.7% in L. camara, C. morale, H. rosasinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus respectively (Figure 6.2.2).

Figure 6.2.2. Effect of different densities of P. solenopsis on variation in nitrogen contents in selected plant species.

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6.2.2 Effect of different densities of P. solenopsis on phosphorus contents of plant species Phosphorus contents of plants infested with 0 CMB/plant were 0.20, 0.29, 0.35, 0.30, 0.30, 0.20, 0.40, 0.28, 0.34, 0.35, 0.20, 0.31, 0.28, 0.17, 0.28, 0.26, 0.25, 0.3, 0.35, 0.3, 0.44, 0.40, 0.36, 0.27 and 0.33% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.3). At density of 50 CMB/plant phosphorus contents were 0.3, 0.29, 0.36, 0.32, 0.35, 0.25, 0.43, 0.29, 0.33, 0.34, 0.26, 0.33, 0.25, 0.15, 0.29, ,0.3, 0.32, 0.31, 0.33, 0.32, 0.4, 0.43, 0.35, 0.3 and 0.3% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.3). At density of 100 CMB/plant phosphorus contents were 0.25, 0.28, 0.3, 0.3, 0.31, 0.23, 0.41, 0.25, 0.3, 0.33, 0.23, 0.3, 0.3, 0.16, 0.27, 0.28, 0.29, 0.29, 0.3, 0.29, 0.42, 0.41, 0.33, 0.28 and 0.32% in in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.3).

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Figure 6.2.3 Effect of different densities of P. solenopsis on variation in phosphorus concentration in selected plant species.

6.2.3 Effect of different densities of P. solenopsis on potassium contents of plant species Potassium contents of plants infested with 0 CMB/plant were 1.38, 3.1, 3.9, 3.84, 2.78, 3.94, 2.66, 3.66, 2.68, 1.7, 1.84, 1.9, 1.95, 2.18, 1.28, 1.88, 2.92, 1.65, 2.37, 1.8, 2.58, 3.28, 2.05, 2.3 and 1.61% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.4). At density of 50 CMB/ plant potassium contents increased to 2.22, 3.28, 3.8, 2.04, 3.94, 2.92, 1.44, 2.68, 1.68, 2.72, 1.88, 1.76, 2.2, 2.08, 1.88, 1.78, 2.28, 1.66, 2, 2.02, 2.3, 2.9, 2.1, 1.98 and 1.84% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.4). At density of 100 CMB/ plant potassium contents in most of the plants were decreased as compared with 50CMB/ plant because they were 1.98, 3.1, 3.5, 2, 3, 2.5, 3, 2, 1.5, 2, 1.5, 1.35, 2.5, 1.9, 2, 1.5, 2.5, 2, 1.5, 2.6, 2.1, 2.2, 2.2, 1.87 and 1.38% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album,

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H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.4).

Figure 6.2.4 Effect of different densities of P. solenopsis on variation in potassium contents in selected plant species.

6.2.4 Effect of different densities of P. solenopsis on crude protein contents of plant species Crude protein percentage at 0 CMB/plant was 15.3, 6.5, 7.2, 9.0, 16.9, 18.1, 13.1, 18.1, 12.5, 13.9, 18.7, 15.9, 18.7, 9.6, 16.1, 13.1, 11.1, 15.6, 18.1, 13.5, 12.5, 6.8, 15.65, 14.3 and 24.7% among plant species including L. camara, C. morale, H. rosa-sinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus (Figure 6.2.5). At 50 CMB/ plant, decline in concentration of crude protein was observed 20, 18.1, 25, 17.5, 20, 15.6, 25, 23.7, 5, 12.5, 17.5, 18.7, 13.1, 28.1, 26.8, 17.5, 27.5, 22.5, 21.8, 14.3, 16.2, and 12.5% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.5).. At 100 CMB/plant, crude protein was decreased to 13, 4.5, 6, 7, 14.3, 12, 11.2, 15.6, 8, 9, 15, 12, 15.6, 6, 13.7, 9, 9, 12.5, 13.7, 10.6, 9, 5, 12.5, 10.6 and 21.2% in L. camara, C. morale, H. rosa-sinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T.

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terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus respectively (Figure 6.2.5).

Figure 6.2.5 Effect of different densities of P. solenopsis on variation in crude protein concentration in selected plant species.

6.2.5 Effect of different densities of P. solenopsis on sodium contents of plant species Sodium contents of plant species infested with 0 CMB/ plant were 1.38, 3.2, 2.56, 2.84, 2.78, 3.94, 2.33, 3.72, 2.34, 1.7, 1.84, 1.9, 2.78, 2.18, 1.28, 1.88, 2.92, 1.65, 2.3, 1.8, 2.58, 3.28, 2.05, 2.3 and 1.54% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.6). At density of 50 CMB/plant, sodium contents were decreased to 1.3, 3, 1.8, 2, 2.5, 3, 1.5, 3, 1.5, 1.7, 1.5, 1.6, 1.9, 1.7, 1.5, 1.8, 3, 1.5, 1.1, 1.6, 1.6, 1.5, 2.2 and 1.75% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, , E. prostrate, C. inerme and G. hirsutum, however P. oleracea exhibited an increase in sodium contents (3.5%) (Figure 6.2.6). In some plants including L. camara, C. morale, C. arvensis, P. hysterophorus, A. spinosus, C. didimus, T. portulacastrum, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, , S. melongena, A. aspera, C. album, H. annuus, D. arvensis, E. prostrate, C. inerme and G. hirsutum there was an increase in sodium contents at

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density of 100 CMB/plant as compared with 50CMB/plant (1.88, 3.22, 2.08, 2.96, 2.4, 2.28, 2.2, 2.98, 1.48, 1.86, 2.2, 2.42, 2.58, 2.5, 2, 2, 2.5, 1.3, 2, 1.5, 2, 3, 1.6 and 2%, respectively). However, sodium contents decreased in C. inerme, W. somnifera, L. nudicaulis, Euphorbia prostrate, T. partulacastrum and T. terrestris (Figure 6.2.6).

Figure 6.2.6 Effect of different densities of P. solenopsis on variation in sodium contents in selected plant species.

6.2.6 Effect of different densities of P. solenopsis on chlorophyll contents of plant species Chlorophyll contents of plant species infested with 0 CMB/ plant were 0.0138, 0.0372, 0.0388, 0.0318, 0.0328, 0.0334, 0.0366, 0.035, 0.042, 0.0222, 0.0168, 0.0144, 0.034, 0.0268, 0.0128, 0.0188, 0.0292, 0.043, 0.0475, 0.026, 0.0208, 0.0478, 0.031, 0.026 and 0.0204mg/gm in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.7). At density of 50 CMB/plant, chlorophyll contents were 0.0142, 0.033, 0.035, 0.033, 0.033, 0.038, 0.035, 0.033, 0.04, 0.025, 0.023, 0.018, 0.03, 0.025, 0.015, 0.023, 0.026, 0.035, 0.038, 0.024, 0.025, 0.045, 0.032, 0.025 and 0.022mg/gm in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.7).

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At density of 100 CMB/plant, chlorophyll contents were 0.014, 0.035, 0.036, 0.03, 0.03, 0.035, 0.032, 0.036, 0.035, 0.03, 0.025, 0.023, 0.029, 0.027, 0.02, 0.025, 0.028, 0.033, 0.035, 0.027, 0.028, 0.04, 0.035, 0.027 and 0.024mg/gm in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.7).

Figure 6.2.7 Effect of different densities of P. solenopsis on variation in total soluble sugar contents in selected plant species.

6.2.7 Effect of different densities of P. solenopsis on crude protein contents of plant species Total soluble sugar contents of plants infested with 0 CMB/ plant were 3.02, 2.1, 2.96, 3.36, 3.1, 1.6, 1.9, 1.46, 1.13, 1.76, 3.06, 3.36, 1.7, 2.2, 2.5, 2.1, 1.5, 1.46, 0.97, 2.98, 2.86, 2.08, 1.87, 3.26 and 3.43% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.8). At density of 50 CMB/plant, total soluble sugar contents were 3.74, 2.72, 1.24, 2.48, 1.48, 3.53, 1.68, 1.56, 3.9, 1.88, 2.68, 2.58, 1.08, 3.46, 1.8, 1.82, 3.98, 2.42, 3.48, 1.58, 2.24, 3.14, 3.12, 1.66 and 2.5% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S.

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melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum (Figure 6.2.8). At density of 100 CMB/plant, total soluble sugar contents were 3.42, 3.31, 2.54, 2.63, 2.71, 3.09, 2.67, 2.12, 2.8, 1.86, 2.31, 2.26, 1.63, 2.37, 1.84, 2.37, 2.81, 2.39, 2.64, 2.08. 2.76, 2.59, 2.71, 1.3 and 2.3% in L. camara, L. nudicaulis, C. morale, C. arvensis, P. hysterophorus, W. somnifera, A. spinosus, C. didimus, T. portulacastrum, T. terrestris, H. rosa-sinensis, A. esculentus, C. arvense, C. bonariensis, C. frutescens, E. prostrate, S. melongena, A. aspera, C. album, H. annuus, D. arvensis, P. oleracea, E. prostrate, C. inerme and G. hirsutum as compared with 0 CMB/ plant (Figure 6.2.8).

Figure 6.2.8 Effect of different densities of P. solenopsis on variation in total soluble contents in selected plant species.

6.2.8 Association between mealybug density and biochemical contents of the selected plant species Simple correlation coefficients between mealybug levels and biochemical contents of the plants are given in Figure 6.2.9-6.2.16. Nitrogen, crude protein, sodium, total soluble sugar and chlorophyll were negatively correlated with mealybug density, but phosphorus, reducing sugar and potassium were positively correlated. The probability value (P value ≤0.05) shows that significant relationship existed between mealybug levels and mineral contents of the plants kept as dependent variable. The correlation coefficient and scatter diagram reveal that levels of mealybug had negative association with nitrogen, crude protein, total soluble sugar, chlorophyll and sodium. The strength of association was very strong as coefficients of correlation values were very close to (-1) value and data points were found scattered around the sloped line. Probability values (P value

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≤0.05) depicted that positive correlation existed between phosphorus, potassium, reducing sugar and density of mealybug possessing strength of association very strong as coefficient of correlation were very close to (+1) value and data points were scattered around the slope line. Regression parameter and scatter diagram reveal that mealybug levels had a significant linear relationship with biochemical contents of the plants (P value ≤ 0.05) (Figure 6.2.9-6.2.15).

Figure 6.2.9: Nature of association between phosphorus contents in plant species and different densities of P. solenopsis.

Figure 6.2.10: Nature of association between nitrogen contents in plant species and different densities of P. solenopsis.

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Figure 6.2.11: Nature of association between potassium contents in plant species and different densities of P. solenopsis.

Figure 6.2.12: Nature of association between crude protein contents in plant species and different densities of P. solenopsis.

Figure 6.2.13: Nature of association between sodium contents in plant species and different densities of P. solenopsis.

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Figure 6.2.14: Nature of association between total soluble sugar contents in plant species and different densities of P. solenopsis.

Figure 6.2.15: Nature of association between reducing sugar contents in plant species and different densities of P. solenopsis.

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Figure 6.2.16: Nature of association between chlorophyll contents in plant species and different densities of P. solenopsis.

6.2.9 Cluster analysis among studied traits Twenty five plant species were categorized into three different clusters with the help of cluster analysis (Figure 6.2.17). Clusters were made on the basis of levels of P. solenopsis and biochemical traits of the selected plant species. Cluster-1 comprised of fourteen plant species including L. camara, C. arvensis, H. annuus, T. terrestris, L. nudicallis, S. melongena, C. bonariensis, C. inerme, C. arvense, A. spinosus, P. oleracea, E. prostrate, E. prostrate and C. frutescens. Cluster-2 consisted of a group of three plant species including C. morale, H. rosa-sinensis and D. arvense, while cluster-3 possessed eight plant species including W. somnifera, A. aspera, A. esculentus, T. partulacastrum, P. hysterophorus, C. didimus, G. hirsutum, and C. album (Figure 6.2.14). The pair wise Mahalanobis distances (D2 statistics) among three clusters of 25 plant species (Table 6.2.3) revealed that plant species of cluster-1 demonstrated 18% and 0.08% diversity against the members of cluster-2 and cluster-3 for the most of the studied biochemical traits, respectively. The members of cluster-3 exhibited 10.3% diversity against the members of cluster-2 for the most of the plant biochemical traits and tolerance.

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Dendrogram Complete Linkage, Euclidean Distance

0.00

y

t 33.33

i

r

a

l

i

m i Cluster-1 Cluster-2

S 66.67 Cluster-3

100.00 a s s s s a s e e s e e e e e s s a a s s s r si u ri li n si s u a t t s l si si r r u m u u m m a n n t u e n rm n s e ra ra n ra n n fe e t ru r tu u e n s a g e e o c t t e e e i p n t o im b m v a re ic n i e v n a s s c o n v n s le s h d su l ca r . r r in r i r o o s m i r a u a p i r a a e d lo a . a p le r r e . s a m . c c o d i . L. . H t u e n C . s p p t - . o A s a r . h C C . n o C . o . . ru C sa s e l e C . T . m b A . E E f D . . tu t G L . . P . ro A r s S C C . W a y p h H . . T P Observations

Figure 6.2.17. Cluster analysis regarding similarity between biochemical traits of twenty five plant species at different densities of P. solenopsis. Table 6.2.2. D2 distance among different clusters. Cluster-1 Cluster-2 Cluster-3 Cluster-1 0.000 Cluster-2 18.1 0.000 Cluster-3 0.08 10.3 0.000

6.2.10 Principal component analysis In this study, two out of eight Principal components (PCs) were taken having Eigenvalues ≥1. Results depicted that first two PCs commulatively expressed 99% of the total variability amongst the selected plant species of P. solenospsis (Table 6.2.4). Mealybug density, phosphorus and potassium demonstrated negative while nitrogen, sodium, chlorophyll, crude protein, total soluble sugar and reducing sugar established positive factor loadings on PC1. Phosphorus, reducing sugar and total soluble sugar expressed negative but nitrogen, potassium, sodium, and crude protein demonstrated positive factor loadings on PC2.

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Table 6.2.3. Principal component analysis regarding biochemical changes in plant species at different densities of P. solenopsis. PC1 PC2 PC3 PC4 PC5 PC6 PC7 Eigenvalue 6.4 1.59 0.05 0.00 0.00 -0.00 -0.00 % of total variance 0.80 0.19 0.09 0.00 0.00 -0.00 -0.00 Cumulative variance % 0.80 0.99 1.00 1.00 1.00 1.00 1.00 Factor loading by various biochemical traits. Variable PC1 PC2 PC3 PC4 PC5 PC6 PC7 CMB density -0.36 0.31 0.26 -0.15 -0.26 0.08 -0.6 Phosphorus (%) -0.35 -0.37 -0.46 0.22 0.37 -0.5 -0.4 Potassium (%) -0.39 0.27 0.08 0.76 -0.03 0.24 0.36 Nitrogen (%) 0.38 0.14 0.14 0.50 -0.5 -0.45 -0.26 Sodium (%) 0.24 0.26 -0.42 0.2 0.3 -0.36 -0.31 Chlorophyll (mg/g) 0.17 0.11 0.8 0.5 -0.3 -0.15 -0.1 Crude protein (%) 0.38 0.14 0.25 -0.08 -0.4 -0.42 0.22 Totalsoluble sugar (%) 0.39 -0.06 0.15 0.31 0.5 0.52 -0.48 Reducing sugar (%) 0.36 -0.3 -0.57 0.01 -0.4 0.3 -0.02

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Discussion

Tolerance mechanism of plant resistance plays an important part to withstand the herbivorus arthropod attack (Tiffin, 2000). Morphological and physiological changes in infested plants may develop tolerance mechanism of resistance against insect herbivory (Hopkins and Huner, 2004). Plant modifications in response to insect pest attack may include either external variation in leaf area, number of leaves, dry weight, or internal plant physiology regarding photosynthesis, chlorophyll, carbohydrates, water use efficiency, protein profile, wax deposition (barrier), accumulation of proline, activity of oxidative and lipid peroxation enzymes (Ni et al., 2001; Heng-Moss et al., 2004; Znidarcic et al., 2008; Huang et al., 2013; Hussain et al., 2014), uptake of macro and micro-nutrients (Chapman et al., 2001; Wu et al., 2004; Al-Shareef, 2011), allelochemicals or secondary metabolites. Due to these modification, plants exhibit tolerance mechanism (El- Zalabani et al., 2012). The results of present studies it was found that infested plants exhibited tolerance mechanism in response to mealybug attack and promoted increase in levels of phosphorus and potassium. Present findings are in confirmatory to Al-Shareef (2011) who reported that whitefly, B. tabaci (Gennadius) feedings reduced level of Zinc and Molybdenum micronutrients in infested plants; however, whiteflt feeding had no significant effects on manganese and copper contents. The variation in results change may be due to difference in pest incidence and change in nutrient profile of infested plant. According to Lokeshwari et al. (2014), the amount of total soluble sugars (TSS) in infested and uninfested shoots with varying levels of aphid infestation, (low, medium and high) were quantified. Results indicated a significant reduction in the amount of TSS in infested shoots due to aphid feeding (P< 0.05). At maximal aphid abundance (251-300 aphids/shoot), total soluble sugar declined by 32%. Further, regression analysis between aphid numbers and the quantity of total soluble sugar yielded simple linear equations with R2= 0.99, which can be used as an alternative way to estimate aphids numbers. Results presented that plants exposed to the low density of mealybug i.e., 50CMB/plant exhibited tolerance as compared with high population. Results of the present findings are supported by Huang et al. (2013) who reported that initial infestation of P. solenopsis had no effect on chlorophyll content as well as on light utilization efficiency that may be due to compensatory photosynthesis. Nitrogen helps in the formation of chloroplasts and accumulation of chlorophyll in them through

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photosynthesis that make plant succulent (Amaliotis et al., 2004; Daughtry, 2000). Sucking insect pests are commonly attracted toward succulent plants that are enriched with chlorophyll. There was decline in nitrogen contents of the susceptible host plants of CMB. The results of this study demonstrated that nitrogen and crude protein were declined in the mealybug infested plants as compared to uninfested plants. Nitrogen contents were 2.5, 1.3, 1.2, 1.5, 2.8, 3.1, 2.2, 3.1, 2.5, 2.5, 3.1, 2.5, 3.1, 1.6, 2.7, 2.1, 1.8, 2.6, 3.1, 2.5, 2.1, 1.1, 2.1, 2.3 and 4.7% at 0 CMB/plant, but 3.2, 2.9, 2.8, 3.2, 2.5, 3.8, 2, 2.8, 3, 2.1, 4.5, 4.3, 2.8, 4.4, 2.4, 3.6, 3.5, 2.3, 2.6, 2, 4, 3.5, 2.3, 2 and 3.7% at density of 50 CMB/ plant whereas contents were decreased to 2.1, 0.5, 1.0, 1.2, 2.2, 2.0, 1.8, 2.3, 1.5, 1.6, 2.5, 2.0, 2.6, 1.0, 2.7, 1.6, 1.6, 2.3, 2.7, 1.8, 1.5, 1.8, 2.1, 1.9 and 3.7% at density of 100 CMB/ plant in L. camara, C. morale, H. rosasinensis, C. arvensis, L. nudicaulis, W. somnifera, C. didimus, E. prostrate, C. bonariensis, S. melongena, A. esculentus, C. arvense, C. album, G. hirsutum, C. frutescense, A. spinosus, C. inerme, T. partulacastrum, P. oleraceae, T. terrestris, D. arvensis, E. prostrate, P. hysterophorus, A. aspera and H. annuus respectively.The result findings of present study are confirmatory to the research findings of Huang et al. (2013) who reported that mealybug density, infestation time, and their interaction significantly affected the chlorophyll content of tomato leaves up to 57.3 and 9.7% for the high and low densities of P. solenopsis, respectively. These biochemical variations in plant enable them to tolerate and compensate growth after the attack of P. solenopsis.

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