Development of Management Strategies for Jassid, Amrasca Devastans (Dist.) on Cotton in Southern Punjab, Pakistan

Development of Management Strategies for Jassid, Amrasca devastans (Dist.) on Cotton in Southern Punjab, Pakistan

RABIA SAEED M.Sc. (Hons.) Agri. Entomology

Thesis submitted for fulfillment of the degree of Doctor of Philosophy in Agricultural Entomology

DEPARTMENT OF ENTOMOLOGY FACULTY OF AGRI. SCIENCES & TECHNOLOGY B. Z. UNIVERSITY, MULTAN, PAKISTAN 2015

ACKNOWLEDGEMENTS

Present research work of this thesis has been performed under the supervision of Assistant

Professor Dr. Muhammad Razaq. His guidance and supervision during the course of this research work and active contribution in discussion during entire work is much appreciated.

This lead to the final submission of this thesis after completing required objectives of research work. Associate Professor Dr. Hardy, I.C.W., Nottingham University London, UK helped me a lot in writing up and to learn some advance techniques to rear parasitoids under

International Research Initiative Program (IRSIP) financed by Higher Education Commission of Pakistan. My PhD research work in the form of thesis is now ready for evaluation. I am also thankful to Muhammad Rafiq, Head Entomology Section, Central Cotton Research

Institute (CCRI) Multan, Pakistan who gave contrasting opinions throughout this learning process. The guidance, encouragement and technical support of many researchers around the world for provision of relevant research materials, articles and ideas is also much respected.

I am also thankful for support, encouragement and patience of my parents (passed away during this period), brother and sisters during this study. Special thank goes to my husband for his patience and love.

Here I would also like to thank my family members, friends and the class fellows for their prayers and continuous encouragement that always helped me to face the challenges.

Rabia Saeed

TABLE OF CONTENTS

Chapter Description Page Acknowledgements I List of tables IV List of figures VI

Abstract 1 Chapter-1 General introduction and objectives 4 References 9 Chapter-2 The importance of alternative host plants as reservoirs of the 13 cotton leaf hopper, Amrasca devastans, and its natural enemies 2.1 Introduction 14 2.2 Materials and methods 17 2.3 Results 20 2.4 Discussion 37 References 43 Chapter-3 Cotton planting date affects the abundance of Amrasca 52 devastans (Dist.) (Homoptera: Cicadellidae) 3.1 Introduction 53 3.2 Materials and methods 55 3.3 Results 59 3.4 Discussion 65 References 68 Chapter-4 Evaluating action thresholds for cotton leafhopper 74 (Homoptera: Cicadellidae) management at different planting time of transgenic and non-transgenic cotton 4.1 Introduction 75 4.2 Materials and methods 78 4.3 Results 82 4.4 Discussion 92 References 95 Chapter-5 Impact of neonicotinoid seed treatment of transgenic cotton on 100 the cotton leaf hopper, Amrasca devastans (Homoptera: Cicadellidae), and its natural enemies 5.1 Introduction 101 5.2 Materials and methods 104 5.3 Results 107 5.4 Discussion 116 References 120

Chapter-6 Integrating plant resistance and pesticide application to 126 manage cotton leafhopper, Amrasca devastans (Dist.): its impact on natural enemies, yield and fiber parameters of transgenic and non-transgenic cotton 6.1 Introduction 127

6.2 Materials and methods 130 6.4 Results 134 6.4 Discussion 149 References 152 Chapter-7 Effect of prey resource on the fitness of the predator 157 Chrysoperla carnea (Neuroptera: Chrysopidae) 7.1 Introduction 158 7.2 Materials and methods 160 7.4 Results 163 7.4 Discussion 169 References 171 Chapter-8 Evaluating spray regimes against cotton leafhopper, Amrasca 175 devastans (Dist.): its impact on natural enemies, yield and fiber characteristics of transgenic Bt cotton 8.1 Introduction 176 8.2 Materials and methods 178 8.4 Results 183 8.4 Discussion 193 References 197 Chapter-9 Conclusions and recommendations for further research 202

III

LIST OF TABLES

Chapter Table Description Page Chapter-2 Table 1. Alternate host plants of the Amrasca devastans recorded 21 during 2009-2010 Table 2 Effects of true alternative host plant variables on 30 population density of Amrasca devastans and its natural enemies Table 3 Monthly variation in Amrasca devastans populations across 31 true alternative host plant species Table 4 Mean numbers of arthropod predators on true alternative 34 host plants Chapter-3 Table 1 Dates of spray, pest (ETL), chemical names, company 58 names and dose Table 2 Effect of planting time, varieties and sampling dates on 62 population density of Amrasca devastans Table 3 Seed cotton yield (kg ha-1) for crops planted on 15th of 64 March, April and May 2010 and 2011 Chapter-4 Table 1 Weather data of experimental site during two crop seasons 79 Table 2 Seasonal mean (± SE) densities of Amrasca devastans in 85 relation to different action thresholds at three planting times Table 3 Yield and fiber characteristics (± SE) of transgenic cotton in 89 relation to action thresholds at three planting times Table 4 Yield and fiber characteristics (± SE) of non-transgenic 90 cotton in relation to action thresholds at three planting times Table 5 Comparison of economic benefits of transgenic cotton in 91 relation to different action thresholds at three planting times Chapter-6 Table 1 Interaction effect of varieties and pesticide application on 137 seasonal mean number of Amrasca devastans per leaf Table 2 Comparison of plant traits in different transgenic and non- 139 transgenic cotton varieties Table 3 Correlation coefficient of Amrasca devastans per leaf and 140 plant traits of different transgenic and non-transgenic varieties of cotton Table 4 Combined analysis of influence of year, varieties and 141 pesticide regimes on Amrasca devastans (per leaf), predators (per 5plants) and seed cotton yield (kg ha-1) Table 5 Influence of pesticide regimes on seasonal mean abundance 142 of predators per 5 plants of cotton during study period Table 6 Interaction effect of varieties and pesticide application on 144 GOT (%) and micronaire (μg inch-1) Table 7 Interaction effect of varieties and pesticide application on 145 staple length (mm) and fiber strength (tppsi) Table 8 Interaction effect of varieties and pesticide application on 147 seed cotton yield (kg ha-1) Chapter-7 Table1 Predatory potential of Chrysoperla carnea immature stages 164 on various life stages of Amrasca devastans Table 2 Effect of Amrasca devastans life stages on different life 165

traits (± SE) of Chrysoperla carnea Table 3 Effect of Amrasca devastans life stages on reproductive 166 traits (± SE) of Chrysoperla carnea Table 4 Population growth traits of Chrysoperla carnea on various 168 life stages of Amrasca devastans Chapter-8 Table 1 Insecticides, their groups, common names, trade names, 181 manufacturer and dose rates applied in different regimes Table 2 Regime wise insecticidal treatment combinations applied in 182 1st 2nd and 3rd sprays Table 3 Seasonal mean (± SE) of predators in tested spray regimes 188 and untreated control plots of transgenic cotton Table 4 Correlation between Amrasca devastans densities and plant 189 traits Table 5 Transgenic cotton growth parameters (± SE) in tested spray 190 regimes and an untreated control Table 6 Comparison of economic benefits among different spray 191 regimes Table 7 Fiber characteristics (± SE) influenced by tested spray 192 regimes

LIST OF FIGURES

Chapter Figure Description Page Chapter-2 Fig. 1 Seasonal fluctuation (± SE) of Amrasca devastans on true 26 alternative host plants Fig. 2 Temporal availability of true alternative host plants of 27 Amrasca devastans Fig. 3 Seasonal prevalence of Amrasca devastans on true alternative 28 host plants Fig. 4 Mean number (± SE) of Amrasca devastans on different true 29 alternative host plant types Fig. 5 Contribution of true alternative host plant types for carrying 35 natural enemies of Amrasca devastans during the survey period Fig. 6 Mean (± SE) parasitism of Amrasca devastans eggs laid on 36 true alternative host plant species Chapter-3 Fig. 1 Meteorological data recorded at the experimental site in 57 CCRI, Multan Fig. 2 Comparative population fluctuation of Amrasca devastans on 60 Bt and non-transgenic cotton at three planting times A) mid- March, B) mid-April and mid-May during 2010 Fig. 3 Comparative population fluctuation of Amrasca devastans on 61 Bt and non-transgenic cotton at three planting times A) mid- March, B) mid-April and mid-May during 2011 Chapter-4 Fig 1. Seasonal trend in the density of Amrasca devastans per leaf 83 on transgenic (Bt.CIM-599) cotton in relation to different action thresholds at three planting times Fig 2. Seasonal trend in the density of Amrasca devastans per leaf 84 on non-transgenic (CIM-554) cotton in relation to different action thresholds at three planting times Chapter-5 Fig. 1 Effects of pesticide and dose on seasonal total numbers of 109 Amrasca devastans Fig. 2 Impact of seed treatment on mean abundance of Amrasca 110 devastans per leaf at different time intervals after sowing Fig. 3 Effects of pesticide and dose on predator populations 111 Fig. 4 Effect of treatments on cotton plant size under field 114 conditions Fig. 5 Effect of treatments on cotton plant size under greenhouse 115 conditions Chapter-6 Fig. 1 Seasonal prevalence of Amrasca devastans per leaf per 135 sample date on transgenic varieties A) AA-802, B) NIBGE- 3701, C) NIBGE-2, D) AA-703 in treated, ETL and untreated control treatment plots during 2011 Fig. 2 Seasonal prevalence of Amrasca devastans per leaf per 135 sample date on non-transgenic varieties A) CIM-496, B) CIM-499, C) CIM-446, D) CRIS-134 in treated, ETL and untreated control treatment plots during 2011 Fig. 3 Seasonal prevalence of Amrasca devastans per leaf per 136 sample date on transgenic varieties A) AA-802, B) NIBGE-

3701, C) NIBGE-2, D) AA-703 in treated, ETL and untreated control treatment plots during 2012 Fig. 4 Seasonal prevalence of Amrasca devastans per leaf per 136 sample date on non-transgenic varieties A) CIM-496, B) CIM-499, C) CIM-446, D) CRIS-134 in treated, ETL and untreated control treatment plots during 2012 Fig. 5 Percentage reduction GOT, micronaire, staple length and 146 fiber strength in untreated transgenic and non-transgenic cotton varieties Fig. 6 Percentage yield (kg ha-1) reduction in untreated transgenic 148 and non-transgenic cotton varieties Chapter-8 Fig. 1 Mean seasonal population of Amrasca devastans per leaf in 184 tested spray regimes and untreated plots during study period Fig. 2 Amrasca devastans population reduction percentages one 185 week after spray in tested spray regimes as compared to untreated control by Henderson and Tilton formula

VII

ABSTRACT

Cotton jassid (CJ)/leafhopper, Amrasca devastans (Dist.) is the main constraint to cotton,

Gossypium hirsutum L. production in Pakistan since the first quarter of the 20th century. It is a polyphagous herbivore that remains active throughout the year due to the continuous availability of alternative hosts. The capacity of non-cotton plant species (both naturally growing and cultivated) to function as alternative hosts for the A. devastans and its natural enemies was evaluated. In three years of survey (2009-11) forty eight species harboured A. devastans. Twenty four species were true breeding hosts, bearing both nymphs and adult A. devastans, the rest were incidental hosts. The crop Ricinus communis and the vegetables

Abelmoschus esculentus and Solanum melongena had the highest potential for harbouring A. devastans and carrying it over into the seedling cotton crop. Natural enemies found on true alternative host plants were spiders, predatory insects (Chrysoperla carnea, Coccinellid spp.,

Orius spp. and Geocoris spp.) and two species of egg parasitoids (Arescon enocki and

Anagrus sp.). Predators were found on 23 species of alternative host plants, especially R. communis. Parasitoids emerged from one crop species (R. communis) and three vegetable species; with 39% of A. devastans parasitised.

Farmers start planting of Bt cotton usually from the March. Therefor, three planting times were evaluated to determine abundance of A. devastans and its impact on yield. Minimum numbers of A. devastans and maximum seed cotton yield was recorded from mid-March planted cotton and lowest yield from mid-May plantings in 2010 and 2011. Transgenic cotton, Bt.CIM-5599 produced high seed cotton yield as compared to conventional cotton,

CIM-554. Numbers of A. devastans (0.1, 1, 2, 3) per leaf of cotton (Bt and conventional) planted on 15th of March, April and May were tested as ATs for their compatibility in 2011 and 2012. All the tested ATs increased yield as compared to untreated check. For mid-March planting 1 AT level required only one spray application with no significant loss of yield. For

1 mid-April planting use of 2 ATs led to spray applications (3 sprays) as compared to 0.1 AT

(10 sprays), without any significant yield loss. For mid-May planting use of 1 AT by employing 4 sprays hindered significant yield loss compared to 0.1 AT (8 sprays).

Effect of neonicotinoid seed treatments on the abundances of the A. devastans and its arthropod predators under field conditions, and on transgenic cotton plant growth under field and laboratory conditions was evaluated. Imidacloprid and thiamethoxam reduced pest abundance, with greater effects when dosages were higher. Treatments at recommended doses delayed pest in reaching the economic damage threshold 30 days (thiamethoxam) or

40-45 days (imidacloprid) after sowing and also enhanced plant growth. It was concluded that imidacloprid applied at the recommended dose of 5 g/kg seed is effective against A. devastans and appears to be safer than thiamethoxam for natural enemies, and also enhances plant growth directly.

Potential of integrating host plant resistance with chemical control to manage A. devastans and its impact on natural enemies and crop yield was also evaluated. Treatments were consisted of three pesticide regimes (biweekly spray, spray at economic threshold level and untreated control) and four transgenic; AA-802, NIBGE-3701, NIBGE-2 and AA-703 and four non-transgenic; CIM-496, CIM-499, CIM-446 and CRIS-134 cotton varieties. Maximum

A. devastans populations were recorded on AA-703. NIBGE-2 harboured minimum numbers of the pest. Plant traits like leaf hair density, length, leaf thickness and plant height affected

A. devastans numbers negatively. Varieties did not affect populations of Orius spp., Geocoris spp., C. carnea, Coccinellid spp. and spiders. Spray at ETL (1per leaf) reduced the A. devastans infestation in all varieties was found comparatively safer for predators compared to biweekly spray treatment without affecting crop yield.

Green lacewing, C. carnea (Stephens) development and reproductive responses on all life stages of A. devastans [1st through 5th instar nymphs (N1-N5) and adult] proved that C.

2 carnea larvae consumed more N2 life stage. The developmental time from egg hatch to adult eclosion was shortest on N3 and longest on the adult. Surviavla rate, fecundity and egg hatching were highest when females had been reared on N3 A. devastans. Pupal weight (mg), egg volume (mm3) and net replacement rate were lowest for the populations reared on N5 and adult A. devastans; these prey regimens also resulted in the lowest intrinsic (rm) and finite (λ) rates of population increase. The results illustrated the potential importance of prey resources

(life stages) on C. carnea population growth.

Adoption of transgenic cotton led to alteration in insecticidal regimes which effect the population of pest and natural enemies. To examine this point, nine spray regimes including various combinations of conventional (endosulfan, dimethoate, acephate, carbosulfan and bifenthrin), or new classes (chlorfenapyr, pyriproxyfen, diafenthiuron and imidacloprid) and one untreated control were evaluated. The lower mean population and higher reduction percentage of A. devastans was found in spray regime, where two organophosphate

(dimethoate and acephate) insecticides rotated with novel mode of action insecticide

(chlorfenapyr). All the regimes proved toxic to generalist predators but with varied degree.

Overall highest yield and improved fiber quality were gained in spray regime where minimum numbers of A. devastans were observed.

To manage A. devastans area wide recommendations should be followed. Weeds that harbour the pest should be removed, cotton cultivation with R. communis, A. esculentus and S. melongena should be avoided and pesticides should be applied sparingly to cultivated alternative host plants. Cotton crops should be sown earlier and use planting time based action thresholds to apply pesticides. Embrace C. carnea and imidacloprid seed dressing in management programs of A. devastans and avoid repetition of insecticides belonging to same group or having same mode of action.

CHAPTER-1

General introduction and objectives

Insect pests are the major factor for reducing crop productivity since the dawn of Agriculture

(Oerke, 2006). Among the crops, worldwide expansion of cotton production to its present level of some 34 million hectares in more than 70 countries has brought cotton into contact with a large and diverse arthropod fauna. Cotton cultivation take places in temperate, subtropical, and tropical environments that lie between 42ºN and 33ºS making it perhaps the most adaptable of the world’s major crops in terms of the diversity of environments used for production (Munro, 1994; Oerke and Denhe, 2004).

Cotton has been superimposed upon various insect complexes across different habitats. Many insect species have expanded beyond their native ranges to encounter cotton in various environments. The result of this mixing and matching of environments and pest species has made this crop notorious for its insect pests management problems worldwide (Castle et al.,

1999; Shahid et al., 2012). Insect pests have quantitative and qualitative losses to cotton yield varying from 39-50 percent (Chaudhry, 1976; Oerke, 2006). The world’s fauna of cotton inhabiting insect pests has been estimated to include well over 1326 species, including 150 species in Pakistan (Huque, 1994; Kranthi, 2007). Insect especially belonging to orders

Hemiptera, Lepidoptera, Thysanoptera and Coleoptera are threatened to cotton.

Globally China, USA, India, Pakistan and Uzbekistan are major producers of cotton. It is an indispensable cash crop for various developing countries (Oerke and Denhe, 2004; Oerke,

2006). Cotton cultivation plays a vital role in the economic growth of Pakistan. It is cultivated on 15% of country’s arable land. Cotton is the important non-food cash crop, and a significant source of about 54% foreign exchange earnings. It accounts for 6.7% of the value added in agriculture and about 1.4% to GDP and 17% of total employment. Cotton is mainly grown by small farmers that possess less than five hectares of land, and approximately 1.6 million farmers rely upon the cotton. Cotton production cornerstone Pakistan’s largest

5 industrial sector, comprising of more than 400 textile mills, 1,000 ginneries and 300 cotton seed oil crushers and refiners (Anonymous, 2014; Rehman, 2014).

Pakistan is the 4th largest producer and 3rd largest consumer of cotton but with respect to yield it is far behind and stands at 10th rank (Abdullah, 2010; Arshad and Suhail, 2011).

Cotton jassid (= cotton leafhopper), Amrasca devastans (Dist.) (Hemiptera: Cicadellidae) has been regarded as one of the most damaging major sucking pest of cotton. It has many synonyms such as Amrasca biguttula biguttula (Ishida), Amrasca biguttula Shiraki, Chlorita biguttula biguttula (Ishida), Chlorita biguttula (Ishida), Chlorita biguttula (Shiraki), Chlorita bimaculata (Matsumura), Empoasca biguttula (Shiraki), Empoasca devastans (Distant),

Sundapteryx biguttula biguttula (Ishida) and Sundapteryx biguttula (Ishida) (Ghauri, 1983).

Previously its order was reported to be Homoptera, which is no longer considered an insect order now. Members of this former order have been added into the Hemiptera (Whitfield and

Alexander, 2013). A. devastans is of great significance in tropics and subtropics, as environmental conditions favours growth and development of pest and hosts throughout the year. It is most severe pest in Pakistan, India, Bangladesh, Thailand and other Southeast

Asian countries (Iqbal, 2011; Ali, 2012). It is also recorded from North Africa, Myanmr,

Philipines, Sri Lanka, Taiwan, Afghanistan and China (Lal, 1951; Ahmed, 1982; Srinivasan,

2009; Iqbal, 2011). In Indo-Pakistan subcontinent, A. devastans became problem with the introduction of upland cotton, Gossypium hirsutum L. during the first quarter of 20th century

(Afzal and Ghani, 1953) and attained the status of primary pest of cotton throughout the cotton growing areas of Sindh and Punjab (Afzal and Ali, 1983). It is regarded to be polyphagous, besides cotton it also attacks several malvaceous and solanaceous crops and remains active throughout the year due to the continuous availability of alternative host plants.

Amrasca devastans females lay eggs on underside of the leaves inside midrib, large veins and lamina in a depression made by the ovipositor. Eggs hatching take place in 4-11 days.

Nymphs look like adults but smaller, paler and wingless, and moult 5 times to become adult in 6-28 days. Adults are small, elongate and wedge shaped, 3 mm long that live for 5-7 week

(Ahsan, 2007; Iqbal, 2011). Both nymphs and adults suck the plant sap and introduce salivary toxins that impair photosynthesis by blocking xylem and phloem and produce hopper burn disease. The affected leaves curl downwards, turn yellowish then brown before drying

(Rehman, 1940; Narayanan and Singh, 1994). Its infestation not only reduces the plant height and number of bolls but also deteriorates lint quality (Afzal and Ghani, 1953; Younus, 1976).

In severe cases its infestation may cause complete crop failure (Rao et al., 1968). Seed cotton losses due to A. devastans infestation are estimated to be over 37% (Ahmad et al., 1985).

Currently insecticides are being used as the only management tool against jassid (Razaq et al., 2013). In order to lessen the crop losses, farmers aggressively acquire contentious practices, such as increasing the dosages or rates of pesticide applications (Iqbal, 2011). This sole and self-defeating reliance on the insecticides led to the development of resistance in jassid particularly against pyrethroids since 1990’s (Ahmad et al., 1999). In addition to development of the resistance, frequent use of insecticides exerts hazardous effects on the natural enemies, environment and socioeconomic aspects of the community (Villegas et al.,

2006; Naveed et al., 2011) suggesting a clear need for alternatives.

Integrated Pest Management (IPM), is a highly acquired alternative of a plant protection model, its importance was generally recognized after the overuse of insecticides and occurrence of subsequent crisis (Zalucki et al., 2009). For more than five decades, it has become archetype for pest control (Naranjo, 2011). There is no easy way for combating jassid threat to cotton. Planting pest-resistant crops, adopting cultural management, using bio-agents and judicious use of pesticides are four constates of IPM (Iqbal, 2011). Integration of these

7 control methods could significantly enhance efficiency and sustainability of IPM system against jassid. Hence, studies were conducted to develop the management strategies for combating A. devastans infestation on cotton, along with finding out their economic feasibility.

The present research was designed with following objectives,

1) Role of alternate hosts in harbouring A. devastans and its natural enemies.

2) Effect of planting time on seasonal abundance of A. devastans and its impact on

cotton yield.

3) Evaluation of action thresholds (ATs) with respect to planting time.

4) Impact of different doses of imidacloprid and thiamethoxam as seed treatment.

5) Influence of integrating varieties and pesticide application for managing A. devastans.

6) Effect of A. devastans prey resource on fitness of predator.

7) Role of insecticide rotations to manage A. devastans and its impact on yield.

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CHAPTER-2

The importance of alternative host plants as reservoirs of the

cotton leaf hopper, Amrasca devastans, and its

natural enemies

This chapter has been published as;

Saeed, R., Razaq, M. and Hardy, I.C.W., 2015. The importance of alternative host plants as reservoirs of the cotton leaf hopper, Amrasca devastans, and its natural enemies. J. Pest Sci.,

88: 517-531. (ISE Impact Factor 2.644)

2.1 INTRODUCTION

Agricultural production is commonly, and negatively, affected by insect pests (Kogan and

Jepson, 2007; Gray et al., 2009) and the problem can be exacerbated by agro-intensification due to rapidly growing human populations (Goodell, 2009; Carrière et al., 2012). Some phytophagous pests attack only a single cultivated plant species (monophagy) (Forare and

Solbreck, 1997), while others have a wider range of host plants (polyphagy) including cultivated plants and species which are not under agricultural production (Li et al., 2011).

Ascertaining the importance and extent of alternative host plants, both naturally growing and cultivated, can be fundamental to prevent the development of polyphagous pest populations on a ‘main’ or ‘focal’ agricultural species (Tabashnik et al., 1991). For instance, alternative host plants can support reservoirs of pests during periods when main hosts are seasonally unavailable, with pests subsequently migrating back onto the main host plants (Clementine et al., 2005). Alternative host plants can also be agriculturally beneficial when they harbour populations of natural enemies (Naveed et al., 2007). Thus, the availability, density and type of alternative host plants (Power, 1987; Atakan and Uygur, 2005), and the prevalence of natural enemies (Koji et al., 2012) can be important factors influencing the damage caused by insect pests. Due to the great diversity of agricultural systems, and species involved, the relative advantages and disadvantages of the presence of alternative host plants in the vicinity of crops are likely to vary across agro-ecosystems.

The cotton leaf hopper, Amrasca devastans (Dist.) [= Amrasca biguttula biguttula (Ghauri,

1983)] (Hemiptera: Cicadellidae) sucks sap from plant leaves and also injects toxic saliva, which can cause stunted plant growth, with leaves curling downwards and becoming yellow and then brown and dry, and, in severe cases, the shedding of fruiting bodies (Rehman, 1940;

Narayanan and Singh, 1994). A. devastans has been regarded in the Indian subcontinent as the most common and most devastating major insect pest of cotton, Gossypium hirsutum L.

14 since the first quarter of the twentieth century: reported cotton yield losses range from 37 to

67% (Ahmed, 1982; Ahmad et al., 1985; Bhat et al., 1986) and crop failure can be complete in given localities (Rao et al., 1968). Farmers in this area rely only on chemical pesticides to manage A. devastans (Razaq et al., 2013; Yousafi et al., 2013), even though frequent spraying is likely to adversely affect the natural enemy fauna (Zidan, 2012).

Amrasca devastans is not limited to feeding and breeding on cotton plants: it is regarded to be a widely polyphagous herbivore that can remain active throughout the year due to the continuous availability of alternative host plants. In many cotton growing areas in Asia, such as Pakistan, agricultural practices have changed from mono-cropping to multi-cropping, due to fragmentation of farms into small holdings of <5 ha, and intercropping of fodder, vegetables and oil seed crops with cotton is now common practice (Khan and Khaliq, 2004;

Akram et al., 2011). These plants share many of the same pest and natural enemy species and thus can act as reservoirs or carry-over sources to the cotton crop (Goodell, 2009). Further, pest management practices applied to one plant species can cause direct or indirect effects on pest and natural enemy populations on others (Edwards et al., 1990). For instance, management of the whitefly, Bemsia tabaci (Genn.) on alternative hosts prior to the seasonal availability of cotton plants can significantly reduce its carry over to cotton (Attique et al.,

2003; Rafiq et al., 2008).

Despite the importance of A. devastans, there have been no quantitative reports on its abundance on alternative host plant species that are found within cotton growing areas; previous literature has only reported its occurrence (Huque, 1994, Table 1). There is similarly limited information on the occurrence and abundance of natural enemies on alternative host plants (Rao et al., 1968). Here we report, for the first time, temporal patterns of occurrence and abundance of A. devastans and its natural enemies on a wide range of potential alternative (non-cotton) host plants in cotton growing areas of Southern Punjab, Pakistan.

This allows evaluation of the role of non-cotton species in carrying over A. devastans populations between cotton growing seasons, their importance in harbouring this pest during the growing season and in maintaining populations of natural enemies.

2.2 MATERIALS AND METHODS

We assessed A. devastans and its natural enemies in the cotton agro-ecosystem near Multan in the Punjab province of Pakistan (between 30o11´52 ̋ N and 71o28´11 ̋ E). Multan is at an altitude of 122m with land area dominated by silt loam soils. It has semi-arid climatic conditions (average rainfall circa 186mm) marked by four distinct seasons: a very hot summer (April-June), a wet season in which most of the precipitation occurs with south- western monsoon (July-September) when temperature ranges from 19.5 to 43oC and a cooler or mild winter (October-March), during which temperature ranges from 4.5 to 34.6oC

(National Oceanic and Atmospheric Administration Data, 1961-1990) (see also Fig. 1).

2.2.1 Alternative host plant surveys

Exploratory searches were conducted within 100 km of Multan. There were a total of 50 visits to each of 42 sites between 1 January and 31 December 2009, with four visits in each month except for January in which there were six visits to each site. On each survey day, all the available flora inside cotton farmland were examined visually, and we also surveyed flora up to 500 m outside each cotton field. A. devastans lay eggs inside leave veins or lamina, which are not visible through naked eye under field conditions therefore, we observed nymphal and adult life stages of A. devastans. Plants hosting nymphal and/or adult A. devastans were usually identified in the field according to Ali (1982), Ali and Nasir (1991) and Zafar (1996). Any unidentified specimens were taken to the Botany Department of

Bahauddin Zakariya University, Multan, for identification by Dr Z.U. Zafar. If A. devastans was found on a plant species on at least two survey dates at the same location, the species was considered to be an alternative host. Alternative host plants were further categorised as

‘true’ host plants if they harboured both nymphal and adult life stages of A. devastans, and as

‘incidental’ host plants if they carried only a few adults for periods of approximate 1 week at a given location and on which adults were found during at least two survey visits at each site

(Mound and Marullo, 1996; Froudi et al., 2001). We also noted the availability of identified host plants on each visit throughout the year. Host plants were further assorted for abundance

[‘abundant’ (a large number of the plant species present in all visited locations), ‘fair’ (found in small numbers in all locations or in large number at few locations) and ‘rare’ (small numbers at few locations)], plant growth habit or life form (herb, shrub, climber and tree), perenniality (annual, biennial and perennial) and horticultural utility or host type (vegetable, crop, fruit, ornamental and weed) according to a pre-existing system (Attique et al., 2003;

Arif et al., 2009; Li et al., 2011; Tiple et al., 2011).

2.2.2 Pest population density estimates

Eighteen of the field sites were selected, on the basis of high host plant availability, from those surveyed in 2009, and were visited at 15-day intervals between January 2010 and

December 2011. The prevalence of A. devastans on those alternative host plant species which had been found to harbour both nymphal and adult life-history stages in 2009 (i.e. true alternative host plants) was estimated by examining leaves according to the method of

Horowitz (1993, see also Leite et al., 2011). Specifically, three leaves were taken from each selected plant; one apical leaf, one leaf from the middle of the plant and one leaf from the lower portion, and the numbers of A. devastans nymphs and adults on them were counted.

The number of alternative host plants surveyed at each site depended on variation in their abundance (Attique et al., 2003): we sampled from 3 to 33 plants per species per site per visit.

2.2.3 Natural enemy populations

To record predators, whole plant counts (Naveed, 2006) were taken from the same true alternative host plant species and from the same sites as selected for population density estimates (see above). The number of plants per sample varied depending variation in abundance (as above); we sampled from three to five plants per species per site per visit.

To assess the prevalence of parasitoid attack, a total of 50 leaves were removed from each species of alternative host plant present at each site on each visit, taking leaves only from those individual plants that harboured both nymphal and adult A. devastans and that could also bear A. devastans eggs. These leaves were brought back to the laboratory and a 5-cm2 diameter leaf discs was cut from the centre of each leaf and placed on moist filter paper, in a

5-cm2 diameter petri dish and covered with a lid. Leaf discs were kept at 25 ± 2°C and 65 ±

3% RH until nymphs of A. devastans and adult parasitoids emerged. The proportion of parasitism of the A. devastans on each leaf disc was calculated as the number of parasitoids emerged divided by the total number of parasitoids plus A. devastans (following Naveed et al., 2011): we assumed that all parasitoids belonged to solitary species, as all identified wasps belonged to egg-parasitoid genera which are either exclusively or predominantly solitary

(Jepsen et al., 2007; Segoli and Rosenheim, 2013).

2.2.4 Statistical analysis

Data analysis was carried out using the GenStat statistical package. As population density data were non-normally distributed, non-parametric tests (Kruskal-Wallis, Spearman’s rank correlation) were employed to explore the influences of single recorded explanatory variables

(Siegel and Castellan, 1988). We were constrained to treat all explanatory variables as random effects. Within Kruskal-Wallis analyses, differences between group averages within treatment categories were evaluated by multiple comparisons tests (Siegel and Castellan,

1988). Across similar analyses, significance thresholds were adjusted to control type I error rates using the Bonferroni procedure (Quinn and Keough, 2002). Proportion parasitism was analysed using logistic ANOVA (Crawley, 1993).

2.3 RESULTS

2.3.1 Alternative host plant surveys

In 2009, A. devastans was recorded from 48 alternative host plant species belonging to 22 taxonomic families (Table 1). Thirty of these species have not previously been recorded as hosts of A. devastans. Seven of the alternative host plant species were crops, 5 species were fruit plants, 7 were ornamentals, 17 were vegetables and 12 were weeds. The alternative host plants varied considerably in their growth habit; most were herbs (24 species) with the remainder being climbers (eight species), shrubs (seven species) and trees (five species).

Most of the alternative host plant species were classed as ‘abundant’ (28 species), followed by 13 ‘fair’ and 7 ‘rare’ plant species in the surveyed area. The majority of the alternative plant species were annuals (32), with only a few perennials (15) and one biennial species

(Table 1). Of the recorded alternative host plant species, 24 were categorised as ‘true’ host plants as these plants harbour both nymphal and adult life stages of A. devastans. As the remaining 24 plant species carried only a few adults for short periods, these were categorised as ‘incidental’ hosts (Table 1): the remainder of this paper focuses on true alternative host plants.

The availability of true alternative host plants varied throughout the year. Weeds, fruit plants and ornamentals were typically available throughout the year, and crops were mainly available between March and September (Fig. 2). Some vegetable species were present throughout the year (Abelmoschus esculentus and Solanum melongena) while others were absent for 2-6 months: Pisum sativum and Solanum tuberosum were absent from April and

May, respectively, until October and members of the family Cucurbitaceae (Citrullus lanatus,

Cucumis melo and Cucumis sativus) were typically absent from around October until around

February (Fig. 2); these patterns reflect the annual cycle of cultivation and harvest of each vegetable.

Table 1. Alternate host plants of the Amrasca devastans recorded during 2009-2010

Plant characteristics Results Family Host plant Vernacular name Host typea Growth Perennialitya New host Statusa Abundancea habita recordb Amaranthaceae Achyranthes aspera L. Phuttkanda Weed Shrub Biennial Yes True Abundant Digera arvensis Forsk Diagra, Tandla Weed Herb Annual Yes Incidental Abundant Apiaceae Corianderum sativum L. Dhania, Coriander Vegetable Herb Annual Yes Incidental Fair Asteraceae Helianthus annuus Linn. Sunflower Crop Herb Annual No True Abundant Xanthium strumarium L. Cocklebur Weed Herb Annual Yes True Abundant Gerbera jamesonii Adlam Gerbera Ornamental Herb Perennial Yes Incidental Rare Bignoniaceae Tecoma stans Juss. Tecoma Ornamental Shrub Perennial Yes Incidental Rare Boraginaceae Cordia dichotoma G. Forst Lasora Fruit Tree Perennial Yes True Rare Brassicaceae Brassica rapa L. Turnip Vegetable Herb Annual Yes Incidental Abundant B. compestris var. sarson Sarson Vegetable Herb Annual Yes Incidental Abundant Raphanus sativus L. Radish Vegetable Herb Annual Yes Incidental Abundant Chenopodiaceae Chenopodium murale L. Karund Weed Herb Annual Yes True Abundant Chenopodium album L. White goosefoot, Bathoo Weed Herb Annual Yes Incidental Abundant Spinacea oleraceae L. Spinach Vegetable Herb Annual Yes Incidental Abundant Convolvulacae Convolvulus arvensis L. Lehli Weed Climber Perennial Yes Incidental Abundant Cucurbitaceae Cucumis melo L. var. Phut Phutt Vegetable Climber Annual Yes True Abundant C. melo L. sativus Muskmelon Vegetable Climber Annual Yes True Abundant C. sativus L. Cucumber Vegetable Climber Annual Yes True Abundant Citrullus lanatus (Thumb) Watermelon Vegetable Climber Annual No True Fair Mansf. Lagenaria vulgaris Ser. Gourd, Kaddu Vegetable Climber Annual No True Abundant Luffa aegyptiaca Mill. Sponge gourd, Tori Vegetable Climber Annual No True Abundant Cucurbita pepo L. var. Squash Vegetable Climber Annual Yes Incidental Fair Melopepo Cyperaceae Cyperus rotundus L. Deela Weed Herb Perennial Yes Incidental Abundant Euphorbiaceae Ricinus communis L. Castor oil plant Crop Shrub Perennial No True Abundant Labiatae Ocimum basilicum L. Niazboo Ornamental Herb Annual Yes Incidental Rare Leguminoseae Trifolium alexandrinum L. Barseem Crop Herb Annual Yes Incidental Fair Malvaceae Abelmoschus esculentus L. Okra, Bhindi, Ladies' fingers, Vegetable Herb Annual No True Abundant Gumbo Abutilon indicum Sweet Mallow, Kanghi Weed Shrub Annual No True Abundant Hibiscus rosa-sinensis L. China rose Ornamental Shrub Perennial No Incidental Rare To be continued………

Table 1. Continued

Plant characteristics Results Family Host plant Vernacular name Host typea Growth Perennialitya New host Statusa Abundancea habita recordb Malvaviscus arboreus Cav. Cocks comb Ornamental Shrub Perennial Yes Incidental Rare Diss Moraceae Morus laevigata L. Shahtoot Fruit Tree Perennial Yes Incidental Fair Myrtaceae Syzgium cumini L. Skeels. Jaman Fruit Tree Perennial Yes Incidental Fair Pedaliaceae Sesamum indicum L. Sesame, Til Crop Herb Annual No True Rare Papilionaceae Pisum sativum L. Peas Vegetable Shrub Annual No True Abundant Cyamopsis tetragonoloba L. Guar Crop Shrub Annual Yes True Fair Phaseolus mungo L. Hepper Rawan Crop Herb Annual No True Fair Rhamnaceae Zizyphus mauritiana Lamk Ber Fruit Tree Perennial Yes Incidental Abundant Rosaceae Rosa indica L. Rose Ornamental Shrub Perennial Yes Incidental Fair Solanaceae Solamum melongena L. Brinjal, Eggplant, Aubergine Vegetable Herb Annual No True Abundant S. inacum Dunal Ester white egg plant Ornamental Herb Annual No True Fair S. tuberosum L. Potato Vegetable Herb Annual No True Abundant S. nigrum L. Mako Weed Herb Annual Yes Incidental Abundant Nicotiana tabacum L. Common tobacco Crop Herb Annual No True Fair Datura metel L. Thornapple, Datoora Weed Shrub Annual No True Abundant Physalis alkakengi. L. Mamola Weed Herb Perennial Yes Incidental Abundant Capsicum frutescens L. Chillies Vegetable Herb Annual No Incidental Abundant Withania somnifera Dunal Winter cherry, Aksen Weed Shrub Perennial Yes Incidental Fair Tiliaceae Grewia asiatica L. Falsa Fruit Tree Perennial No True Fair a The categories of host plants scored according to Mound and Marullo (1996), Attique et al. (2003), Arif et al. (2009), Li et al. (2011), Tiple et al. (2011) b Yes= new alternative host plants in Pakistan with no previous world record, No= alternative host plants previously reported by Bhatia (1932), Cherian and Kylasam (1938), Hussain and Lal (1940), Rajani (1940), Ghani (1946), Anonymous (1988)

2.3.2 Pest population density estimates

Amrasca devastans population density varied both in time and between true host plant species (Fig. 3). The vegetable A. esculentus supported the highest densities of pests. On this species, both nymphs and adults were active from March to December, with densities of both peaking around April-May during both 2010 and 2011. In January and February, this host species was present but the upper parts had been cut by the farmers and A. devastans adults and nymphs were absent (Fig. 3). The vegetable S. melongena harboured A. devastans adults throughout the season from January to December with peak density in November. The presence of multiple nymphal instars throughout the year indicated that breeding took place during all months, but nymphal densities fluctuated greatly and peaked around April-May

(Fig. 3). Populations of adult A. devastans on S. tuberosum fluctuated in the same way as for S. melongena but the densities of nymphs were very different, with nymphs present only when adults were present and at very low density (Fig. 3). A. devastans was only found on P. sativum during March in 2010, and March and January in 2011, but densities were always very low

(Fig. 3). The remaining species in the vegetable host-type category all showed the same pattern of A. devastans abundance, with both adults and nymphs present around May-August and absent in the remaining months of the year (Fig. 3).

The crop species Ricinus communis harboured adult and nymphal A. devastans throughout the year with adult densities peaking in October and peak nymphal densities in May (Fig. 3). On

Helianthus annuus, adults and nymphal A. devastans were present from April-June with maximum densities in April. The remaining crop plant species harboured A. devastans from around May until around August (Fig. 3).

Among the weeds, Xanthium strumarium supported A. devastans adults and nymphal stages throughout the period it was present in the field, with maximum adult densities in November and nymphal densities in August. On Abutilon indicum, A. devastans adults were found for

23 most periods of the year except February, June and July 2010, and February 2011. Nymphs were present throughout observation period except in June of both years. Both nymphal and adult maximum densities were found in September during both the years. However, the weed

Chenopodium murale carried overwintering A. devastans in January and December. On the remaining weed species, A. devastans was present in low numbers from approximately April to December. Plant species belonging to the fruit or ornamental host-type categories carried low densities of A. devastans adults and nymphs, with peaks occurring in May or June (Fig.

3).

Estimates of population densities (mean A. devastans per leaf) from true alternative hosts did not differ significantly between 2010 and 2011 (Kruskal-Wallis test: H = 2.71, df =1, P =

0.07), so the data were pooled before further analysis of influence on the average number of

A. devastans per leaf. Densities of A. devastans (nymphs plus adults) were significantly affected by all six of the plant characteristics explored (Table 2). Similarly, when data on nymphal and adult A. devastans were analysed separately, there were significant differences in density between plant families (nymphs: H = 408.8, df = 10, P < 0.001; adults: H = 385.8, df = 10, P < 0.001), with the highest densities on host plants in the family Malvaceae followed by the Euphorbiaceae. Species effects were also found when nymphs and adults were analysed separately (nymphs: H = 558.6, df = 23, P < 0.001; adults: H = 548.9, df = 23,

P < 0.001). Multiple comparisons testing indicated that there were no significant differences in nymph or adult numbers between A. esculentus, R. communis and S. melongena, which harboured the highest densities of the pest.

In terms of host plant type, A. devastans was most prevalent on vegetables and least common on fruit plants, with densities per plant-type category ranging from approximately 0.1 to 1.0 individuals per leaf (Fig. 4). Multiple comparisons testing indicated that while numbers of A. devastans differed across crop types overall (Table 2), differences were not significant

24 between vegetables, crops and ornamentals, and also not between weeds and ornamentals.

Similar overall results were obtained when data on nymphal and adult A. devastans were analysed separately (nymphs: H = 44.31, df = 4, P < 0.001; adults: H = 51.84, df = 4, P <

0.001).

Amrasca devastans prevalence varied significantly across host growth habits (Table 2), and similar results were found for nymphs and adults when analysed separately (nymphs: H =

59.43, df = 3, P < 0.001; adults: H = 98.21, df = 3, P < 0.001). Prevalence was the greatest on herbs as compared to shrubs, climbers and trees. Annual plants were found to harbour more adult A. devastans than perennial or biennial plants (H = 11.38, df = 3, P < 0.001) while nymphs were more abundant on perennial plants (H = 5.97, df = 3, P = 0.024). For both nymphs and adults, population densities were greater on abundantly distributed plants than on plants with fair or rare abundances (nymphs: H = 95.90, df = 2, P < 0.001; adults: H = 98.88, df = 2, P < 0.001).

Populations of A. devastans varied significantly between sampling months (H = 210.4, df =

11, P < 0.001) with the highest densities observed in May and June (Fig. 1, see also Fig. 3).

A. devastans populations were positively correlated with mean monthly temperature

(Spearman's rank correlation test: rs = 0.664, n = 12, P = 0.005, Fig. 1) and inversely correlated with mean monthly relative humidity (rs = -0.510, n = 12, P = 0.022, Fig. 1).

Temperature and relative humidity were inversely correlated (rs = -0.462, n = 12, P = 0.032,

Fig. 1). There was also significant variation across host species during each month (Table 3).

A. devastans nymphs were most prevalent on R. communis from November to March but most prevalent on A. esculentus from April to October. A. devastans adults were most prevalent on

S. tuberosum from November to January and on R. communis in February and March. As found for nymphs, adults were more prevalent on A. esculentus from April to October (Table 3).

Amrasca devastans Temperature °C Relative Humidity (RH %) 2.5 80 70 2.0 60

1.5 50 C and RH RH and C % 40 ° 1.0 30

Numberperleaf 20 0.5

10 Temperature 0.0 0 J F M A M J J A S O N D Months

Fig. 1 Seasonal fluctuation (± SE) of Amrasca devastans on true alternative host plants. All data are pooled across 2010 and 2011. A. devastans bars represent nymphs plus adults. Meteorological data were obtained from the Central Cotton Research Institute, Multan

Alternative host plant Vegetable Abelmoschus esculentus

Citrullus lanatus - - -

Cucumis melo - -

Cucumis melo var. phutt - - - - -

Cucumis sativus - - -

Lagenaria vulgaris - - - -

Luffa aegyptiaca

Pisum sativum ------

Solamum melongena

Solamum tuberosum - - - - -

Crop Cyamopsis tetragonoloba - - - - -

Helianthus annuus ------

Nicotiana tabacum ------

Phaseolus mungo - - - - -

Ricinus communis

Sesamum indicum ------

Weed Abutilon indicum

Achyranthes aspera

Chenopodium murale

Datura metel

Xanthium strumarium - - -

Ornamental Solamum incanum

Fruit Cordial dichotoma

Grewia asiatica

Month (2009) J F M A M J J A S O N D

Fig. 2 Temporal availability of true alternative host plants of Amrasca devastans. Cotton is commonly sown from early May and remains in the field until harvest in October each year (indicated by line below months)

Fig. 3 Seasonal prevalence of Amrasca devastans on true alternative host plants. Dotted lines indicate data on nymphs, solid bold lines indicate adults. F, O, C, W and V respectively indicate fruit, ornamental, crop, weed and vegetable plants. Note that different panels have different y-axis scales

1.2

0.8

0.4 Numberperleaf

0.0 Vegetable Crop Weed Ornamental Fruit Host plant type

Fig. 4 Mean number (± SE) of Amrasca devastans on different true alternative host plant types (pooled data for 2010 and 2011, nymphs plus adults). The numbers of A. devastans differed significantly across host plant types overall but comparisons were not significantly different between vegetables, crops and ornamentals, and also not between weeds and ornamentals

Table 2. Effects of true alternative host plant variables on population density of Amrasca devastans and its natural enemies Explanatory variable Df H value Pa

Amrasca devastans Family 10 426.5 < 0.001 Species 23 586.6 < 0.001 Type 4 50.36 < 0.001 Growth habit 3 89.91 < 0.001 Perenniality 2 9.62 0.003 Abundance 2 97.18 < 0.001 Predators Family 10 116.0 < 0.001 Species 23 166.7 < 0.001 Type 4 42.36 < 0.001 Growth habit 3 24.50 < 0.001 Perenniality 2 14.12 < 0.001 Abundance 2 22.98 < 0.001

Parasitoids Family 10 23.57 < 0.001 Species 23 37.02 < 0.001 Type 4 3.19 < 0.001 Growth habit 1 1.72 0.018 NSa Perenniality 2 3.79 < 0.001 Abundance 2 3.19 < 0.001 Results are from Kruskal-Wallis one-way analyses of variance on pooled numbers of adult and nymphal A. devastans and on predators (5 species pooled) and parasitoids (2 species) for 2010 and 2011. Host plant variables are as in Table 1 a Because 6 tests were carried out for each category of organisms we adjusted the significance criterion, according to the Bonferroni procedure, to be 0.05/6, i.e. <0.0083

Table 3. Monthly variation in Amrasca devastans populations across true alternative host plant species Month Preferred host plant Difference across 24 host species df H Pa Nymphs January Ricinus communis 23 71.3 < 0.001 February " 23 59.9 < 0.001 March " 23 72.1 < 0.001 April Abelmoschus esculentus 23 114.0 < 0.001 May " 23 133.6 < 0.001 June " 23 113.3 < 0.001 July " 23 114.8 < 0.001 August " 23 114.3 < 0.001 September " 23 136.1 < 0.001 October " 23 90.8 < 0.001 November Ricinus communis 23 83.8 < 0.001 December " 23 83.6 < 0.001

Adults January Solanum tuberosum 23 85.9 < 0.001 February Ricinus communis 23 49.9 < 0.001 March " 23 71.3 < 0.001 April Abelmoschus esculentus 23 134.9 < 0.001 May " 23 124.0 < 0.001 June " 23 112.3 < 0.001 July " 23 123.5 < 0.001 August " 23 143.3 < 0.001 September " 23 141.1 < 0.001 October " 23 84.3 < 0.001 November Solanum tuberosum 23 93.4 < 0.001 December " 23 94.9 < 0.001 Data are pooled across 2010 and 2011 a Because 12 tests were carried out for each A. devastans life history stage we adjusted the significance criterion, according to the Bonferroni procedure, to be 0.05/12, i.e. <0.0042: all results were significant at this more stringent level

2.3.3 Natural enemy populations

The natural enemies of A. devastans found on true alternative host plants comprised both predators and parasitoids. Predatory arthropods were spiders (Order: Araneae) and insects: we recorded green lacewing, Chrysoperla carnea (Stephens) (Neuroptera: Chrysopidae),

Coccinellid beetles (Coleoptera: Coccinellidae) and two genera of hemipterans: Orius spp.

(Hem.: Anthocoridae), Geocoris spp. (Hem.: Lygaeidae). Possible species within these genera were minute pirate bug, O. insidiosius and big-eyed bug, G. punctipes, as both have been previously reported within Pakistani cotton agro-ecosystems (Mari et al., 2007). Among these natural enemies, spiders and coccinellids were the most abundant predators, followed by C. carnea (Table 4). Spiders were species in the families Lycosidae and Thomisidae and coccinellid species included Coccinella septempunctata (L.), C. undecimpunctata (L.),

Hyperaspis maindroni Sicard, Scymnus nubilus Muslant, Menochilus sexmaculatus (F.) and

Brumus suturalis (F.). The dominant (numerically) coccinellids were C. septempunctata, M. sexmaculatus and B. suturalis.

Densities of predators were significantly affected by all six of the plant characteristics explored (Table 2). Plants in the family Euphorbiaceae harboured the highest densities of three predators, due to large numbers of spiders, coccinellids and C. carnea present on the crop plant R. communis (Table 4). Overall, predators were around three times more common on crop plants than on vegetables, and least prevalent on weeds, fruiting plants and the one species of ornamental (Table 4). All five groups of predators were found on most types of alternative host plant, except for fruit plants where Orius spp. were the only predators found

(Table 4; Fig. 5a). Predators were the most common on abundant perennial shrub plants

(Tables 1, 4). The only predator found on rare plants was C. carnea (Tables 1, 4).

All parasitoids found were hymenopterans in the family Mymaridae: Arescon enocki (Subba

Rao and Kaur) and Anagrus sp. These species oviposit in A. devastans eggs (Rao et al., 1968;

Sahito et al., 2010) that have been laid inside leaf veins (Agarwal and Krishnananda, 1976).

Overall, Anagrus sp. was more common (58.8% of individual parasitoids) than A. enocki. The total numbers of parasitoids that emerged were significantly affected by five of the six of the plant characteristics explored but not by the plant’s growth habit (Table 2). Parasitoids were most common on perennial plants and emerged from leaves of abundant plant species only

(Tables 1, 2; Fig. 6). Parasitoids did not emerge from leaves of weed, ornamental or fruit plant species, but did emerge from three species of vegetables and one species of crop plant (Figs. 5b,

6).

Across these four plant species, the overall proportion of A. devastans eggs parasitised 0.386 (±

0.03 SE) and did not differ significantly between plant species (logistic ANOVA corrected for overdispersion: F3,42 = 2.47, P = 0.075, Fig. 6). However, when parasitism by A. enocki and

Anagrus sp. was treated separately, there were significant differences in parasitism across these plant species (A. enocki: F3,42 = 21.64, P < 0.001; Anagrus sp.: F3,42 = 9.82, P < 0.001, Fig.

6) due to specialism within vegetable species: Anagrus sp. was the only parasitoid to emerge from leaves of C. melo var. phutt and 83.3% of the parasitoids that emerged from L. aegyptica were Anagrus sp., while on A. esculentus only 13.8% of parasitoids that emerged were Anagrus sp.

Table 4. Mean numbers of arthropod predators on true alternative host plants Host plant type Predator and species Orius spp. Geocoris Chrysoperla Coccinellid Araneae Overall spp. carnea spp. spp. Mean Minute Big eyed Green Lady Spiders pirate bug bug lacewing beetles

Vegetable Mean 2.26 1.77 1.34 1.26 3.70 2.06 Abelmoschus esculentus 1.15 0.09 1.42 1.10 5.55 1.86 Citrullus lanatus 0.85 1.35 0.60 0.50 1.75 1.01 Cucumis melo 1.65 0.60 0.50 0.90 1.35 1.00 Cucumis melo var. phutt 5.35 4.25 0.60 1.10 7.50 3.76 Cucumis sativus 0.60 0.75 1.15 1.10 3.10 1.34 Lagenaria vulgaris 7.50 7.50 0 5.00 0 4.00 Luffa aegyptiaca 3.60 0 0.25 1.00 2.75 1.52 Pisum sativum 0 0 0 0.50 0.35 0.17 Solamum melongena 1.85 3.15 3.85 1.35 9.60 3.96 Solamum tuberosum 0 0 5.00 0 5.00 2.00

Crop Mean 2.13 0.23 4.86 7.93 15.31 6.09 Cyamopsis tetragonoloba 0 0 1.15 0 9.15 2.06 Helianthus annuus 0.25 1.35 2.85 2.60 5.10 2.43 Phaseolus mungo 5.00 0 3.75 0 2.50 2.25 Nicotiana tabaccum 0 0 0 0 1.35 0.27 Ricinus communis 7.50 0 11.40 45.00 73.75 27.53 Sesamum indicum 0 0 10 0 0 2.00

Weed Mean 0.50 0.67 0.75 2.48 1.00 1.08 Abutilon indicum 0 3.35 0 1.00 0 0.87 Achyranthes aspera 0 0 0 0.09 0 0.02 Chenopodium murale 0 0 0 10.00 0 2.00 Datura metel 0 0 0 0.08 0 0.02 Xanthium strumarium 2.50 0 3.75 1.25 5.00 2.50

Ornamental Solamum incanum 0.25 1.00 0.90 0.15 2.75 1.01

Fruit Mean 1.25 0 0 0 0 0.25 Cordial dichotoma 0 0 0 0 0 0 Grewia asiatica 2.50 0 0 0 0 0.50

Overall mean 1.69 0.97 1.97 3.03 5.69 2.67 Numbers shown are means from up to 5 plants per species per site per visit, pooled across all sites and across two sampling years

(A) Predators

1.0

Araneae spp. 0.5

Coccinellid spp. Proportion Chrysoperla carnea Geocoris punctipes

0.0 Orius insidiosus

(B) Parasitoids

1.0

0.5

Anagrus spp. Proportion Arescon enocki

0.0

Fig. 5 Contribution of true alternative host plant types for carrying natural enemies of Amrasca devastans during the survey period: (A) predators, (B) parasitoids

1.0 Arescon enocki

Anagrus sp.

0.5 Proportionparasitised

0.0

Host plant species

Vegetable Crop

Fig. 6 Mean (± SE) parasitism of Amrasca devastans eggs laid on true alternative host plant species

2.4 DISCUSSION

Of the 48 plant species that were found to harbour A. devastans, 30 were recorded as alternative hosts for the first time. The other 18 species have been previously recorded by

Bhatia (1932), Cherian and Kylasam (1938), Rajani (1940), Hussain and Lal (1940), Ghani

(1946) and Anonymous (1988). Twenty-four of these species can be categorised as true alternative hosts (Mound and Marullo, 1996) for A. devastans, since they carried both adult and nymphal life-history stages, and constitute the focus of this study (the other species are thus incidental hosts, Froudi et al., 2001).

There was a clear ranking in terms of the importance of different true alternative host plants for A. devastans. Species belonging to the families Malvaceae and Euphorbiaceae were the most exploited by both nymphs and adults, as also found by Rao et al. (1968); in particular, okra, A. esculentus, egg plant, S. melongena and castor oil plant, R. communis harboured the highest densities of A. devastans. A. esculentus is commonly grown near to cotton fields (Baig et al., 2009) and sometimes intercropped with cotton (R.S., pers. obs.). The highest densities of both nymphal and adult A. devastans that were observed on this plant in our study, and also in laboratory evaluations (Ghani, 1946), may be due to its chemical properties (crude protein, lignin and nitrogen) being particularly favourable for A. devastans (Iqbal et al., 2011).

Although A. esculentus was present in fields throughout the year, it did not support A. devastans populations in the months of January or February (see also Eijaz et al., 2012) possibly due to adverse weather conditions (Chiykowski, 1981), lower abundance (Power, 1987) and plant maturity (Anitha, 2007). Despite regular spraying (farmers typically apply insecticides twice per week once pest infestations have become apparent, R.S., pers. obs.), A. devastans populations reached high density during April and May. Similar to A. esculentus, the vegetable S. melongena is typically cultivated in close spatial association with cotton, and A. devastans also breeds on

37 this alternative host throughout the year, with regular spraying (Yousafi et al., 2013) constituting a possible cause of the observed fluctuations in adult and nymphal densities.

In contrast, R. communis is a perennial plant that is cultivated for oilseed on a commercial scale in many countries (Parson and Cuthbertson, 1992); in Pakistan it is grown on a domestic scale on marginal land or near field borders (Hattam and Abbassi, 1994). These plants are exposed to relatively little insecticide spray and hence A. devastans populations are able to exist on them continuously, with observed fluctuation likely due to the growth stage of the plants and meteorological conditions, as above. These three alternative host plants are thus the main reservoir of A. devastans and the primary carry-over source to cotton (see also Huque, 1994;

Srinivasan, 2009).

Although weed species, particularly A. indicum and C. murale, harbour comparatively low populations of A. devastans, their availability throughout the year and potential to harbour refuge populations when cotton is not present (inter-harvest period) suggests that weeds may play a disproportionally important role in influencing pest dynamics.

Our population density studies showed that A. devastans persist in the cotton agro-ecosystem throughout the year due to the continuous availability of at least some species of true alternative host plants but the population density on each host plant varied according to its seasonal cycle. These results accord with observations of Setamou et al. (2000) and Barman et al. (2010) who found notable effects of season and growth stage of host plants on population density fluctuation of Mussidia nigrivenella (Lepidoptera: Pyralidae) in the maize agro-ecosystem in Benin and of Lygus hesperus (Hemiptera: Miridae) in the cotton agro- ecosystem in Texas (USA), respectively.

In the cotton agro-ecosystem we observed, the usage of true alternative host plants by A. devastans peaked in May and June, when temperatures were highest and humidity was the lowest: high pest densities on preferred alternative host plants are likely to promote local

38 dispersal of A. devastans individuals onto other available plant species. In a study of A. devastans populations within cotton crops, Naveed (2006) concluded that both warm and humid weather promoted pest population growth: the difference between this and our findings may be due to the differing foci on cotton and non-cotton alternative hosts. In most areas of the Southern Punjab, cotton sowing commonly starts in May (Ali et al., 2011), which coincides with the greatest build-up of A. devastans populations. Hence, shortly after cotton seedling emergence, A. devastans individuals are likely to migrate from nearby alternative vegetable, crop and weed hosts into the cotton crop, leading to severe infestation and possibly the complete failure of the crop (Ghani, 1946). Chemical control is the only tactic being widely used by farmers to protect the cotton crop from A. devastans infestation (Razaq et al.,

2013). Harmful effects of pesticide usage are well documented by many authors (Zhang et al., 2011; Zidan, 2012). Due to excessive and sole reliance on insecticides, A. devastans has now developed resistance against pyrethroid insecticides (Ahmad et al., 1999).

In developed countries, agriculturalists have reduced pesticide usage by employing biological pest control (e.g. Bari and Sardar, 1998; Tscharntke, 2000; Thacker, 2002; Gray et al., 2009).

Orius spp., Geocoris spp., C. carnea, Coccinellid spp. and spiders are all common predators of A. devastans (Mallah et al., 2001; Vennila at al., 2007). We found the highest numbers of predators on crop and vegetable alternative host plants, especially R. communis. R. communis may provide a favourable habitat for predatory arthropods due to relatively low exposure to pesticides (see above) or because its perennial bushy canopy provides both shelter during adverse environmental conditions and harbours prey throughout the year. Further, C. carnea adults feed on R. communis pollen (Sattar, 2010).

In addition to the predators, two species of egg parasitoids commonly attacked A. devastans on some vegetable and crop alternative host plants. Egg parasitoids may be particularly effective in reducing damage by phytophagous species because hosts are parasitised prior to their

39 feeding on the plant (Wajnberg and Hassan, 1994). However, our estimate of A. devastans parasitism (38.6%) is only slightly greater than an empirically estimated minimum threshold of 32-36% for biological control success (Tscharntke, 2000), and we found no evidence for parasitoid attack on other alternative plant species; this casts doubt on whether parasitoid action alone could be sufficient to control A. devastans across the agro-ecosystem. A. enocki was predominant on A. esculentus (see also Sahito et al., 2010) and R. communis and Anagrus sp. was predominant on C. melo var. phutt and exclusive on L. aegyptiaca. This variation is potentially due to differing availability of nectar or differences in plant volatile profiles or plant morphology (e.g. Micha et al., 2000; Kennedy, 2003; Jervis and Heimpel, 2005) or plant- mediated outcomes to competitive interactions between the parasitoid species (Hawkins, 2000;

Tscharntke, 2000).

Given that there are at least seven species of natural enemies of A. devastans present on alternative host plants, there is potential for these predators and parasitoids to suppress A. devastans population outside of, and within, the cotton crop. The degree of any suppression will, however, be dependent on many interrelated factors, which include the abundance of the natural enemy populations, the extent and consequences of any competitive interactions between species (intra-guild predation: Rosenheim et al., 1995; Hawkins, 2000), the susceptibility of natural enemies to pesticides (Tscharntke, 2000) and the potential for the natural enemies to migrate from alternative host plants into the cotton crop during the growing season, and out of the cotton crop at harvest (Tscharntke, 2000). Such factors will ultimately determine whether each species of alternative host plant acts more as a source of natural enemies or as a source of

A. devastans. It is also possible that further plant species (that do not harbour A. devastans and are thus not among the ‘alternative host plants’ we surveyed), could harbour different species of insect herbivores and serve as sources of generalist natural enemies of A. devastans, thus additionally influencing the population biology of this pest.

2.4.1 Conclusions and recommendations

In conclusion, our study has shown that alternative host plants can harbour A. devastans populations and thus have high potential to act as reservoirs of pest individuals which can then migrate into the cotton crop. These reservoirs will be particularly important during the inter-harvest period, when cotton plants are not present. In this respect, the presence of alternative host plants is disadvantageous to the cotton agro-ecosystem but the disadvantage is mitigated in two ways: first, alternative host plants harbour natural enemies of A. devastans and second, many alternative host plants are vegetables, crops and fruits and thus agriculturally beneficial in their own right. The relative pros and cons of their presence in cotton growing areas are thus not straightforward to evaluate, but our results indicate that the characteristics of given species of alternative host plant species, such as type, growth habit, perenniality and abundance, will influence this balance. This evaluation was based on a series of regular field surveys in which the composition and numbers of plant species at each site and survey date varied, and thus the plant characteristics examined, were not under experimental control. Further work may be required to tease apart the influences of phylogenetically non-independent characters, such as type, growth habit and perenniality.

Given current evidence, we recommend the following actions to reduce damage by A. devastans via integrated pest management: (1) Remove alternative host weeds from cotton fields and their vicinity. (2) Avoid intercropping and cultivation of the vegetables, A. esculentus and S. melongena in cotton fields, and also avoid growing the perennial R. communis near cotton fields or in field margins. Despite harbouring natural enemies, these three species harbour the highest densities of A. devastans throughout the year and thus appear to constitute important carry-over sources of the pest. (3) Avoid frequent use of pesticides on vegetables: when applications are necessary, use selective insecticides which have minimal effects on natural enemy species. (4) Modify the timing of sowing to desynchronize the period during

41 which cotton plants are in the early seedling stage, and especially vulnerable to A. devastans attack, from the peak period of pest density.

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(Solanum melongena L.) varieties sown in autumn for resistance to cotton jassid,

Amrasca biguttula biguttula (Ishida). Pakistan J. Zool., 45: 897-902.

Zafar, Z.U., 1996. Flora of Khanewal. MPhil thesis, Department of Botany, Institute of Pure

and Applied Biology, Bahauddin Zakariya University Multan, Pakistan.

Zhang, L., Greenberg, S.M., Zhang, Y. and Liu, T.X., 2011. Effectiveness of thiamethoxam

and imidacloprid seed treatments against Bemisia tabaci (Hemiptera: Aleyrodidae) on

cotton. Pest Manag. Sci., 67: 226-32.

Zidan, L.T.M., 2012. Bioefficacy of three new neonicotinoid insecticides as seed treatment

against four early sucking pests of cotton. Am. Eurasian J. Agric. and Environ. Sci.,

12: 535-540.

CHAPTER-3

Cotton planting date affects the abundance of Amrasca devastans

(Dist.) (Hemiptera: Cicadellidae)

3.1 INTRODUCTION

Cotton, Gossypium hirsutum L. accounts for 40% production of the world’s natural fiber and is cultivated in more than 70 countries lying in temperate, tropical and subtropical environments (Munro, 1994; Oerke and Denhe, 2004). Being cultivated in wide range of habitats it is vulnerable to a complex of sucking and chewing insect pests. Of the 1326 insect pest species attacking cotton globally, 150 species have been associated with cotton during its growth period in Pakistan (Huque, 1994; Shahid et al., 2012). Insects particularly belonging to orders Hemiptera, Lepidoptera, Thysanoptera and Coleoptera are damaging to cotton

(Oerke and Denhe, 2004). Genetically modified cotton encoding Bacillus thuringiensis

Berliner genes (known as Bt cotton) producing the Cry1Ac protein, provides effective and selective control of lepidopteran pests. A total of 11 countries grow Bt cotton including top five cotton producing nations throughout the world (Naranjo, 2011).

Pakistan is the fourth largest producer of cotton; since 2005 area under Bt cotton is increasing rapidly and now approached to more than 80% (Abdullah, 2010; Bilal et al., 2012;

Anonymous, 2013). Before introduction of Bt varieties, cotton was planted from mid-May to end June to escape bollworms attack (Naveed, 1990). Wider adoption of Bt cotton has shifted the cropping scenario to early planting followed by a marked reduction in the use of broad spectrum insecticides against bollworms (Sabir et al., 2011; Bilal et al., 2012; Razaq et al.,

2013).

Sucking pests that were managed previously by using broad spectrum insecticides against bollworms have now increased in their numbers and become a major threat to cotton

(Naranjo, 2011). One of these is cotton leafhopper or jassid, Amrasca devastans (Dist.) [=

Amrasca biguttula biguttula (Ishida)] (Hemiptera: Cicadellidae) (Sharma et al., 2005). It is regarded as a primary pest of cotton and needs regular control measures in every growing season (Razaq et al., 2013). Surveys conducted by Punjab Govt. Pakistan reported gradual

53 increase in cotton fields severely infested with A. devastans in Punjab since the last decade

(Anonymous, 2013). A. devastans adult and immature stages (nymphs) suck the sap from underside of the leaves and inject phytotoxic saliva in the plant tissues, its damage leads to uneven plant growth, crinkled leaves and shedding of squares and bolls. Quality of fiber is also deteriorated due to severe damage at the boll formation stage (Huque, 1994). Estimated seed cotton losses due to A. devastans are above 37% in Pakistan (Ahmad et al., 1985; Saeed et al., 2015). Pest management options for A. devastans are solely directed towards use of chemical insecticides in the form of seed dressing and foliar applications (Saeed et al., 2015).

Due to harmful effects of insecticides alternative tactics are needed to manage this pest.

Among the substitute approaches, altering planting dates is one of the most important and is a widely used component of integrated pest management (IPM) practices that reduce likelihood of pest problems (Kamara et al., 2010). By changing crop phenology, asynchronization can be developed among pests and crops. Hessian fly, Mayetiola destructor Say, cabbage looper,

Trichoplusia ni Hübner, clover seed midge, Dasineura leguminicola (Lintner) and sunflower beetle, Zygogramma exclatmationis Fabricius have been successfully managed by modifying planting dates (Luko et al., 2001; Speight et al., 2008; Pedigo and Rice, 2009; Kamara et al.,

2010).

However, there is lack of information about the impact of planting dates on the A. devastans infestation on transgenic and non-transgenic cotton. The objective of the present study was to identify the appropriate planting time that asynchronizes the development of A. devastans on cotton.

3.2 MATERIALS AND METHODS

3.2.1 Experimental site

The field experiments were conducted under semi-arid climatic conditions on silt loam soils of experimental area at Central Cotton Research Institute (CCRI), Multan (30.120N and

71.280E) in the Southern Punjab of Pakistan during 2010 and 2011. Meteorological data of study period is given in Figs. 1 A and B.

3.2.2 Cotton cultivars, planting dates and experimental design

Experiments were planted in split-plot design with three replicates. Seeds of two varieties:

Bt.CIM-599 and CIM-554 (non-Bt variety) were provided by the cotton Breeding Section of

CCRI, Multan. These varieties were planted in mid-March (15th of March), mid-April (15th of

April) and mid-May (15th of May) during 2010 and 2011. Main plots were planting dates whereas varieties were in subplots. Planting was done by bed and furrow method. Each treatment was 7.31 m × 12.19 m. Plant to plant and row to row distance was of 0.23 m and

0.76 m, respectively.

Furrows were irrigated and cotton seeds (delinted with Sulphuric Acid @ 10 ml/kg seed) were dibbled manually. Irrigation was applied again, 72 hours after dibbling. Subsequent irrigations were applied as recommended. Fertilizer was applied at the rate of 60 kg ha-1 of phosphorus fertilizer (Diamonium Phosphate containing 16% N and 48% P) at the time of seed bed preparation and nitrogen fertilizer (Urea 46% N) was applied at the rate of 100 kg ha-1 in three equal doses at seed bed preparation, flowering and boll formation stage of the crop. No insecticides were applied to manage A. devastans during either year of the study.

When population/damage of whitefly and bollworms approached the Economic Threshold then insecticides were applied as recommended by CCRI, Multan to manage these insect pests (Table 1).

3.2.3 Sampling of Amrasca devastans, yield assessment and statistical analysis

We recorded numbers of A. devastans from randomly selected plants (n= 10) from each plot.

On the appearance of A. devastans, the visual counting was done from one leaf of upper, middle and lower portion of 1st, 2nd and 3rd plant, respectively (Razaq et al., 2005). Both nymphs and adults of A. devastans were counted weekly in the morning hours up to 31st week after planting. Impact of treatments on A. devastans densities were compared using repeated measures ANOVA. Observation dates were considered as repeats over time whereas varieties and planting dates were considered as treatment effects. At crop maturity, raw cotton was picked from each plot for recording yield. Treatments influence on yield was compared using split plot layout with planting date as main factor and varieties as sub factor. Tukey’s (1953)

HSD tests (P < 0.05) were used to separate means showing significant treatment effect. All the statistical analysis was carried out using was carried out using software Statistix 8.1.

A) Temp °C 2010 Temp °C 2011 %RH 2010 %RH 2011

40 100

35 90 C)

º 80 30 70 25 60 20 50 15 40 30 10 20 % Relative humidity Mean TemperatureMean ( 5 10 0 0 April May June July August September October Months

B) Rainfall2010 Rainfall2011 180 160 140 120 100 80 60

Total rainfall Totalrainfall (mm) 40 20 0 April May June July August September October Months

Fig. 1 Meteorological data recorded at the experimental site in CCRI, Multan: A) mean monthly temperature (ºC) and weekly relative humidity (%RH), B) total monthly rainfall (mm)

Table 1. Dates of spray, pest (ETL), chemical names, company names and dose Application Pest /(ETL) Insecticide Dose a.i. dates (g or l) /ha.

2010

12-Jul-10 Bemisia tabaci Pyriproxyfen (Priority 10.8 EC), 54.0 (4-5/leaf) KANZO Ag Multan, Pakistan Earias insulana Deltamethrin (Decis 2.5EC), Bayer 12.4 (3 larvae/25 plants) Crop Science, Karachi, Pakistan 24-Aug-10 Earias insulana Deltamethrin (Decis 2.5EC), Bayer 12.4 (3 larvae/25 plants) crop Science, Karachi, Pakistan 3-Sep-10 Bemisia tabaci Pyriproxyfen (Priority 10.8 EC), 54.0 (4-5/leaf) KANZO Ag Multan, Pakistan Earias insulana Spinosad (Tracer 240 EC), Arysta 47.4 (3 larvae/25 plants) Life Science, Karachi, Pakistan

2011

11-Jul-11 Bemisia tabaci Pyriproxyfen (Priority 10.8 EC), 54.0 (4-5/leaf) KANZO Ag Multan, Pakistan Earias insulana Deltamethrin (Decis 2.5EC), Bayer 12.4 (3 larvae/25 plants) Crop Science, Karachi, Pakistan 20-July-11 Bemisia tabaci Acetamiprid (Mospilan 20SP), 61.8 (4-5/leaf) Arysta Life Science, Karachi, Pakistan Earias insulana Spinosad (Tracer 240 EC), Arysta 47.4 (3 larvae/25 plants) Life Science, Karachi, Pakistan 3-Aug-11 Earias insulana Spinosad (Tracer 240 EC), Arysta 47.4 (3 larvae/25 plants) Life Science, Karachi, Pakistan 10-Aug-11 Earias insulana Spinosad (Tracer 240 EC), Arysta 47.4 (3 larvae/25 plants) Life Science, Karachi, Pakistan 11-Aug-11 Phenacoccus Profenofos (Curacron 500EC), 988.0 solenopsis (on Syngenta, Karachi, Pakistan. appearence) 18-Aug-11 Earias insulana Deltamethrin (Decis 2.5EC), Bayer 12.4 (3 larvae/25 plants) Crop Science, Karachi, Pakistan

Earias insulana did not reach ETL in Bt plots therefore, did not receive any insecticides applications

3.3 RESULTS

3.3.1 Amrasca devastans density per leaf

Planting time significantly influenced A. devastans; higher densities (0.70 ± 0.09 and 2.01 ±

0.20 per leaf in 2010 and 2011, respectively) were perceived on mid-April planted cotton.

While A. devastans densities were lower (0.23 ± 0.03 and 0.45 ± 0.04 per leaf in 2010 and

2011, respectively) on the cotton planted in mid-March. Varietal impact was also found to be significant during both years; Bt.CIM-599 supported more numbers of A. devastans, 0.52 ±

0.06 and 1.42 ± 0.14 per leaf as compared to CIM-554, 0.46 ± 0.06 and 1.20 ± 0.10 per leaf in 2010 and 2011, respectively. In all planting times, A. devastans population fluctuated significantly over time i.e. sampling date and sowing date × sampling date was the only interaction that was significant during both cropping seasons (Table 2).

During 2010, A. devastans appeared on mid-March planted cotton on 6th April and remained below ETL (1 A. devastans/leaf) up till 1st week of June and reached at ETL on 8th June with decreasing trend afterwards on both Bt and non-transgenic varieties (Fig. 2A). On mid-April planted cotton, A. devastans appeared on 11th May with higher density than that on mid-

March planted cotton. Population remained at ETL until 22nd of the June on mid-April planted cotton and then decreased afterwards (Fig. 2B). On mid-May planted cotton, A. devastans appeared on 8th June. Population declined gradually and remained at ETL until 15th

June (Fig. 2C). However, on all planting dates, A. devastans reached at its peak on 8th June

(Fig. 2A-C). Impact of year (F1,4 = 284.62, P < 0.001) and year by treatment interaction (F2,8

= 112.02, P < 0.001) were found to be significant, therefore two years are reported separately.

per leaf per

Amrasca devastans Amrasca devastans

Sampling dates

Fig. 2 Comparative population fluctuation of Amrasca devastans on Bt and non- transgenic cotton at three planting times A) mid-March, B) mid-April and mid-May during 2010

A) Mid-March planting plantplanting

per leaf per B) Mid-April planting

Amrasca devastans Amrasca devastans

C) Mid-May planting

Sampling dates

Fig. 3 Comparative population fluctuation of Amrasca devastans on Bt and non- transgenic cotton at three planting times A) mid-March, B) mid-April and mid-May during 2011

Table 2. Effect of planting time, varieties and sampling dates on population density of Amrasca devastans Variables df 2010 2011 F P F P value value value Value

Planting time 2,12 305.89 < 0.001 219.25 < 0.001 Varieties 1,12 11.27 0.030 20.82 0.004 Planting time×Varieties 2,12 2.09 0.167 3.08 0.083 Sampling date 27,324 100.42 < 0.001 119.62 < 0.001 Planting time×Sampling date 54,324 20.12 < 0.001 26.05 < 0.001 Varieties×Sampling date 27,324 1.48 0.062 8.10 < 0.001 Planting time×Varieties×Sampling date 54,324 0.78 0.868 2.28 < 0.001

Results are from repeated measue analysis of variance on pooled numbers of adult and nymphal Amrasca devastans for 2010 and 2011

During 2011 on mid-March planted cotton, incidence of A. devastans was observed two weeks later than 2010. It appeared on both Bt and non-transgenic varieties in last week of

April, reached the ETL on 28th June (Fig. 3A). On mid-April planted cotton A. devastans appeared on 17th May and the population increased subsequently and reached at ETL on 7th

June, this density was higher than on both the other planting dates. Its peak was observed on

28th June, which was also comparatively higher than the other two planting dates (Fig. 3B).

On mid-May planted cotton A. devastans appeared on 7th June and reached at ETL on 14th

June. Consequently pest population continued to increase and peak density was recorded on

28th June which was higher than mid-March planted cotton but lower than mid-April planted cotton (Fig. 3C).

3.3.2 Seed cotton yield

Seed cotton yield (kg ha-1) was significantly influenced by planting time on both Bt and non- transgenic varieties (Table 3). Average cotton yield was higher during 2010 on both varieties as compared to that during 2011. Seed cotton yield was significantly higher (2010: F2,4 =

th 56.46, P = 0.001; 2011: F2,4 = 65.23, P < 0.001) when cotton crop was planted on 15 of

March. Lowest seed cotton yield was obtained from mid-May planted cotton crop. Bt.CIM-

599 produced significantly higher (2010: F1,6 = 28.40, P = 0.002 ; 2011: F1,6 = 12.35, P =

0.013) seed cotton yield as compared to CIM-554 on all planting dates. Planting dates and varietal interaction was non-significant (2010: F2,6 = 1.55, P = 0.29 ; 2011: F2,6 = 0.23, P =

0.800) as both the varieties showed similar yield trends i.e. high yield in mid-March and low yield in mid-May planted cotton (Table 3).

Table 3. Seed cotton yield (kg ha-1) for crops planted on 15th of March, April and May 2010 and 2011 2010 2011 Planting Mean Mean time Bt-CIM- Bt-CIM- CIM-554 CIM-554 599 599 Mid- March 4011±613 2807±257 3409±397a 3786±316 2546±280 3166±447a Mid-April 3869±571 2726±246 3298±375a 3033±246 2037±140 2535±267b Mid-May 2442±383 1721±281 2082±260b 1665±335 1153±205 1409±201c Mean 3441±352A 2418±217B 2828±354A 1912±235B

Tukey’s HSD value □D 742.87 597.30 ●V 513.50 420.63 ∆D × V 1446.50 1184.90

□D = date of planting, ●V = variety, ∆D × V = interaction between date of planting and variety Capital letters across the row represent varietal significance Small letters across the columns represent significance of planting time

3.4 DISCUSSION

In the current study, lowest pest infestation and maximum yield was obtained in early planted

(mid-March) cotton. There are several examples which support that early planting reduces various pest infestations and ultimately increase yield. Early planting reduced damage of pea pod borer, Etiella zinckenella Tr. (Srivastava et al., 1974), maize stalk borers, Chilo partellus

(Swinh.) and Chilo orichalcociliellus Strand (Wariu and Kuria, 1983), flower thrips,

Frankliniella occidentalis (Pergande) on cotton in Turkey (Atakan and Gencer, 2008), aphid,

Lipaphis erysimi Kalt. on Brassica napus L. (Saljoqi et al., 2009) and rice water weevil,

Lissorhoptrus oryzophilus Kuschel on rice (Stout et al., 2011). Lower populations of aphids,

Aphis gossypii Glover, jassid, Empoasca fabae (Harris) and red bollworm, Diparopsis castanea

Hamps have been observed on early-planted cotton than later-planted in Zimbabwe (Karavina et al., 2012). In Uganda, early planting reduced the infestation by aphids, Aphis craccivora

Koch, thrips, Megalurothrips sjostedti Trybom and four pod feeding bug species on cowpea

(Karungi et al., 2000b). Damage due to insect pests to crops depends upon the active period of feeding of pest and availability of vulnerable crop stage. Hence the reason for less damage to early planted crops might be that these crops established better and reached to maturity before insects appear and become less palatable (Pedigo and Rice, 2009).

During the peak active period of A. devastans, mid-April planted cotton attained maximum vegetative growth thus supporting highest A. devastans population, as middle aged cotton plants are more preferred by A. devastans than older or younger plants (Huque et al., 1994). Despite the fact that A. devastans density was higher in mid-April planted cotton; lowest yield was found in mid-May planted cotton. The reason may be that cotton planted during mid-May was attacked by A. devastans in more sensitive, early true leave stages that caused more damage to cotton leading to poor crop stand and reduction in yield.

Occurrence of A. devastans on cotton was three week later during 2011 as compared to that during 2010. Delay in A. devastans appearance may be due to high rainfall and low temperature

(16.7 mm and 26.19 ºC, respectively) during April 2011 that badly affected A. devastans build up until last week of April, later on rise in temperature favoured population build up. In the current study, significant interaction of sowing date with sampling date apprehended that meteorological conditions play substantial role in A. devastans population dynamics. Imperative role of meteorological factors in the sucking insect pest dynamics has been documented previously (Panickar and Patel, 2001; Ashfaq et al., 2010; Akram et al., 2013). For example, in

Eastern Uganda heavy early season rainfall diminished aphids, A. craccivora build up on cowpea during 1997 and 1998 (Karungi et al., 2000a). In Minas Gerais, Brazil a drastic decrease in Bemisia tabaci (Genn.) population was perceived due to rains in October, 1999

(Leite et al., 2005). Horowitz (1986) also observed a decline in B. tabaci population owing to heavy rains, in Sudan. Previous studies reported negative correlation of rainfall and positive correlation of temperature with A. biguttula biguttula (Ishida) density on brinjal, cotton and okra crops (Mahmood et al., 2002; Ashfaq et al., 2010; Iqbal et al., 2010).

More than half of the global cotton area is now under genetically modified cotton (Ali et al.,

2010). There have been conflicting results about Bt cotton cultivars impact on non-target pests, with both increases and decreases observed. In India, similar numbers of sucking insects (A. biguttula biguttula, B. tabaci, A. gossypi, Thrips tabaci Lind. and of the foliage feeder

Myllocerus undecimpustulatus Faust) were observed on Bt and non-transgenic cotton (Mann et al., 2010). But in some countries for example, in Australia, the green mirid, Creontiades dilutus

(Stal), green vegetable bug, Nezara viridula (L.), leafhoppers, Austroasca viridigrisea (Paoli) and Amrasca terraereginae (Paoli) and thrips, T. tabaci, Frankliniella schultzei Trybom and F. occidentalis have increased in their importance (Naranjo, 2011). In the current study, A. devastans density was comparatively higher on Bt cotton than non-transgenic cotton. There has

66 been no evidence that Bt toxin itself have any direct impact on population change (Head et al.,

2005; Naranjo, 2005; Whitehouse et al., 2005; Wolfenbarger, 2008; Lu et al., 2010). There may be two reasons for increase in A. devastans population 1) reduction in sprays and 2) variation in plant traits. These two reasons have been considered to increase populations of non-target pest species of Bt cotton in cotton production system of the world (Men et al., 2004; Naranjo, 2011;

Naveed et al., 2011). Populations of other insect pests like B. tabaci and T. tabaci were also recorded along with A. devastans and will be published elsewhere.

Both Bt and non-transgenic varieties showed similar trend towards yield with regard to planting time i.e. maximum yield was obtained from mid-March planted cotton and minimum from mid-

May planted cotton during both the years. Previous studies recorded higher seed cotton yield at early planting dates than that with delay in planting dates (Boquet and Clawson, 2009; Adams et al., 2013). However, average yield of Bt.CIM-599 was higher as compared to CIM-554 in all planting dates during both 2010 and 2011. These findings are in line with several with several meta-studies in the world those reported higher yield potential of Bt cotton than that of non- transgenic cotton (Carpenter, 2010; Brookes and Barfoot, 2011; Forster et al., 2013).

In conclusion, our studies provided evidence that the impact of A. devastans on cotton can be reduced by early planting. This is likely because of asynchronization between A. devastans populations and vulnerable stage of cotton crop. Early planting management strategy would reduce number of insecticide sprays, protect the environment from their hazardous effects and ultimately increase farmer’s income.

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CHAPTER-4

Evaluating action thresholds for cotton leafhopper (Hemiptera:

Cicadellidae) management at different planting time of

transgenic and non-transgenic cotton

4.1 INTRODUCTION

Cotton, Gossypium hirsutum L. is an important cash crop in the economies of many developing countries and thus occupies a unique position in the global economy. Its cultivation in a wide variety of environments subjects it to a diverse assemblage of pests.

At least 1326 pest species worldwide including 150 pest species in Pakistan (Huque, 1994) have been recorded as causing damage to cotton. Pakistan is the 4th largest producer of cotton but with respect to yield it is far behind and stands at 10th rank (Abdullah, 2010).

The cotton jassid (CJ)/leafhopper, Amrasca devastans (Dist.) [= Amrasca biguttula biguttula (Ishida)] is one of the most damaging sucking pests of cotton that has been a target of insecticidal applications in Pakistan (Ahmad, 1999). Both adults and nymphs of

A. devastans suck the cell sap from cotton leaves by mechanically blocking the phloem and xylem vessels, injecting toxic saliva that ultimately causes plant stunting, curling and browning of the leaves (Rehman, 1940; Narayanan and Singh, 1994). Besides cotton this pest has recorded from 48 plant species from cotton areas of Multan, Pakistan (Saeed et al., 2015). Rapid development of A. devastans populations that occurs most years in cotton fields of Pakistan have led to insecticides as the principal means of management for A. devastans (Razaq et al., 2013). An unfortunate outcome of over-dependency on insecticides has been the development of resistance in A. devastans against pyrethroids since 1990s (Ahmad et al., 1999).

Concern about over use of insecticides was realized in early 1960s. This concern led to the development of economic threshold (ET) and economic injury level (EIL) concepts (Stern et al., 1959; Pedigo et al., 1986). Economic threshold level can be defined as the pest density at which control measures should be taken. If control measure is not taken at this level the pest will reach EIL. Lowest pest population density that will cause economic damage is termed as EIL. The EIL most commonly referred as EIL= C/VIDK

Where C is cost of the management tactic, V is the market value per production unit, I is injury units per pest, D is damage per injury unit, and K is the proportional reduction in the pest population. The most important factor that can modify EIL is the market value of the commodity; moreover, EIL is the basis to calculate ET (Pedigo et al., 1986; Regsdale, et al., 2007). Economic threshold and action thtreshold (AT) are often used synonymously, even though ATs are not derived from EIL (Nault and Shelton, 2010). AT is the pest population density at which action must be taken to prevent population from reaching economic or aesthetic injury level (Ball and Marsan, 1991; Stejskal, 2002). ATs are developed from research based field trials to evaluate pest-crop relationship but they do not include the full complexities of EIL. They are commonly used in the situations where future pest damage to high value crop is greater than the cost of treatment, and in cases where it is too difficult to quantify future prices of commodity (Nault and Shelton, 2010).

Since the market values of different commodities changes in developing countries, ultimately affecting EIL and ETL, therefore it will be more appropriate to determine ATs for the pests, where optimum yield is obtained with minimum insecticide application.

Thresholds for various species of cotton jassid have been used in different countries on the basis of developmental stage and population density. In Queensland, Australia, 50 jassid/m or 80% infected young top leaves for pre-flowering cotton have been used for

Austroasca viridigrisean (Paoli). A threshold of 50 nymphs per 100 leaves was established for the cotton leafhopper, Amrasca terraereginae (Paoli) in Sudan (Kelly, 2002). In India,

5.2 nymphs per leaf or the appearance of crinkling, curling and yellowing on the lower leaves of cotton plants were suggested as threshold for spraying (Rote et al., 1985). In

Pakistan, 1 jassid per leaf was recommended as threshold since the 1980s, when planting time was restricted from May-15 to end-June to protect the crop from bollworm infestation

(Ahmad et al., 1985; Naveed, 1990). Introduction of Bt cotton [insect-resistant (IR)]

76 varieties since 2005 have specifically combated bollworms (Abdullah, 2010), which encourage inclusive adoption and early sowing of transgenic cotton by diminishing menace of bollworm attack that previously restricted early sowing of Bt cotton. Early sowing of cotton is one of the strategies to minimize Cotton Leaf Curl Virus (CLCuV) problem that became feasible after introduction of transgenic cotton. This wider adoption and early sowing practice of Bt cotton have altered commercial crop practices from May-

15 planting to early planting starting from last week of February in Southern Punjab

Pakistan (Anonymous, 2011; Sabir et al., 2011; Razaq et al., 2013). This change in cropping scenario that eliminated the host fallow period has effectively elevated A. devastans to the most damaging sucking pest in Pakistan cotton. Farmers still apply control measures at the previous 1 A. devastans per leaf threshold without taking into consideration changes in planting time. This has led to a crucial need for developing action thresholds by keeping in view the time of planting, as A. devastans population fluctuates with changing sowing dates, as seen for several other insect species (Jackson et al., 1973).

The objective of our study was to develop action threshold at different time of planting of conventional and transgenic cotton for designing insecticide application guidelines.

4.2 MATERIALS AND METHODS

4.2.1 Experimental site

Field experiments were conducted in semi-arid climatic conditions on silt loam soils at the

Central Cotton Research Institute (CCRI) fields, in Multan (30.120N and 71.280E) Region of Southern Punjab, Pakistan. Seeds of conventional (CIM-554) and Bt. variety (Bt.CIM-

599) were planted using bed and furrow method during 2011 and 2012. Weather conditions at the experimental site during two years are presented in table 1.

4.2.2 Planting time and ATs

To develop action threshold for A. devastans two separate experiments were conducted.

Transgenic cotton variety Bt.CIM-599 (experiment no.1) and conventional cotton variety,

CIM-554 (experiment no. 2) were sown (at three planting times i.e. 15th of the March,

April and May) in 2011 and 2012. Both of these varieties have been developed by the

Plant Breeding and Genetics Section of CCRI, Multan, Pakistan. Cotton plots were established for four ATs [0.1, 1.0, 2.0, 3.0 A. devastans (nymph + adult) per leaf].

Treatments included all combination of planting times and thresholds plus untreated check.

Each treatment plot consisted of 16 rows that were 7.31 m in length. There were 31 plants in each row. Numbers of plants were also equal in all the rows. Plant to plant and row to row distance were 0.23 m and 0.76 m, respectively. Replicates and plots were 2.0 m and

1.23 m apart. All treatments were arranged in randomized complete block design with three replicates. Identical agronomic practices were followed for both the experiments.

Dimethoate (Dnadim Progress 40% EC Swat Agro chemicals, Pakistan) was applied from a knapsack sprayer at the pressure of three bars whenever densities of A. devastans reached one of the AT levels in the respective plots.

Table 1. Weather data of experimental site during two crop seasons 2011 2012 Air Relative Wind daily Sun Precipitation Air Relative Wind daily Sun Precipitation Month Temp Humidity total shine (mm) Temp Humidity total shine (mm) (oC) (%RH) (km/hr) (hours) (oC) (%RH) (km/hr) (hours) February 16 76 5 6 23 14 64 4 4 0 March 21 64 4 9 5 21 55 6 4 0 April 26 47 6 9 17 27 64 7 8 0 May 34 52 7 10 6 33 55 6 9 1 June 34 66 7 8 2 34 58 8 8 0 July 33 73 6 7 16 33 61 173 8 17 August 31 85 6 7 45 32 72 6 7 11 September 29 69 5 7 100 29 80 5 7 167 October 26 76 3 9 4 25 62 3 8 3

Whitefly, Bemisia tabaci (Genn.) was the only other insect pest except A. devastans that reached recommended economic threshold Level (ETL 4-5/leaf) which was controlled by applying pyriproxyfen (Priority 10.8 EC Kanzo Ag Pakistan ) on all plots including control in both the experiments. Spotted bollworm, Earias spp. and American bollworm,

Helicoverpa armigera (Hübner) were controlled by spinosad (Tracer 240 EC Arysta Life

Science) in the conventional cotton plots. In both experiments weeds were controlled by using the pre-sowing herbicide Stomp 400 EC (Pendimethaline 33% Bayer Crop Science)

@ 1200 g ha-1 of a.i. at the time of preparation of beds in dry conditions with hand operated knapsack sprayer having flat fan nozzle.

4.2.3 Sampling of Amrasca devastans

Amrasca devastans was monitored twice a week and total numbers were recorded from 15 randomly selected plants from each plot (n= 45 plants per treatment per sample). Both nymphs and adults of A. devastans were counted from individual leaves in the upper, middle and lower portions of three consecutive plants by sampling only one portion of each of the three plants. Counts of A. devastans were made in morning hours from the selected plants beginning with the first appearance of A. devastans in the experimental plots (Razaq et al., 2005). Population densities were estimated by calculating mean numbers of A. devastans per leaf across all three plots. If the population mean densities reached or crossed the target AT, all plots in the treatment were sprayed within 24-48 hours. At crop maturity or harvest raw cotton from each plot (n= 3 plots per treatment) was picked manually for recording yield. Seed cotton samples (n= 100 g per replicate) for each treatment were packed separately in paper bags and sent to Fiber Technology Section,

CCRI, Multan for lint testing.

4.2.4 Statistical and economic analysis

The effect of planting time and tested thresholds along with their interaction on A. devastans density, cotton yield and fiber quality were analysed by employing General

Linear Model.

풀풊풋풌 = 푺푫풊 + 푬푻푳풋 + (푺푫 ∗ 푬푻푳)풊풋+Ɛ풊풋풌

Where Yijk= response variable, SDi= ith sowing date (i= 1,2,3)

ETLj= jth economic threshold level (j= 1…..5)

SD*ETL= interaction of ith sowing date and jth

ETL Ɛijk= random error associated with individual observations

Significant treatments means were separated by employing Tukey’s HSD test (P < 0.05) using SPSS Software Package version 16 (SPSS Inc., 2007).

A simple budgeting analysis was carried out to estimate the net return and marginal return for each threshold treatment on each planting time (Naranjo et al., 1998). The formula for net return was as follows: Net return= yield (kg/ha) × price ($/ha) – control cost ($/ha) per application × number of applications. We estimated net return for per application cost of

$25.41 ± $3/ ha and lint price of $ 0.80 ± 0.10/ kg to cover a range of realistic values.

Marginal return determines the value of yield gain due to spraying, relative to the cost of spray schedule (Nabirye et al., 2003).Value of marginal return less than 1 indicates that increase in cotton yield does not compensate for the cost of spraying.

4.3 RESULTS

4.3.1 Planting time and action threshold impact on Amrasca devastans population dynamics

Amrasca devastans population densities in both experiments mirrored each other during both study years. Therefore, spray applications were made at the same time on transgenic and conventional cotton (Fig. 1 A-F and Fig. 2 A-F).

4.3.1.1 March-15 Planting

In both experiments, A. devastans remained < 2 per leaf throughout the season in all plots of

March-15 planting during each year. Therefore, only the 0.1 and 1 action thresholds (ATs) levels could be studied for their impact on cotton yield. In 2011, A. devastans population densities on untreated cotton reached their highest levels during the first week of July as compared to all other sampling dates. Thresholds of 0.1 and 1 A. devastans leaf-1 were reached on 12th May and 7th July, respectively. To maintain the 0.1 AT level, spray applications were made at 57, 71, 98, 105 and 121 days after planting. In contrast, maintenance of A. devastans at the 1 AT level required only one spray application at 121 days after planting (Fig. 1A and 2A). During 2012, in untreated plots of both experiments A. devastans population reached its peak in the last week of June. Thresholds of 0.1 and 1 A. devastans leaf-1 were met on 7th May and 2nd July, respectively. To maintain 0.1 AT level, spray applications were made at 52, 73, 93, 100 and 107 days after planting. To maintain 1

AT level only one spray at 107 days after planting was required (Fig. 1B and 2B).

4.3.1.2 April-15 planting

In both experiments, A. devastans season long density was significantly higher in the April-

15 planting as compared to other planting times in transgenic and non-transgenic cotton

(Table 2). In each study year all four ATs (0.1, 1, 2 and 3) were triggered along with untreated control for each cotton variety.

March-15 planting 2011 2012

April-15 planting

per leaf per

A. devastans

Number of Number

May-15 planting

Fig 1. Seasonal trend in the density of Amrasca devastans per leaf on transgenic (Bt.CIM-599) cotton in relation to different action thresholds at three planting times. Symbols above each graph show timing of pesticide application for each threshold level

March-15 planting 2011 2012

April-15 planting

per leaf per

A. devastans

umber

May-15 Planting

Fig 2. Seasonal trend in the density of Amrasca devastans per leaf on non-transgenic (CIM- 554) cotton in relation to different action thresholds at three planting times. Symbols above each graph show timing of pesticide application for each threshold level

Table 2. Seasonal mean (± SE) densities of Amrasca devastans in relation to different action thresholds at three planting times Planting Threshold Transgenic cotton Non transgenic cotton time 2011 2012 2011 2012 March-15ф 0.1/ leaf 0.12±0.06g 0.13±0.05g 0.17±0.02j 0.10±0.04g 1/ leaf 0.42±0.09efg 0.32±0.08fg 0.37±0.09ghij 0.35±0.10fg Untreated 0.75±0.11de 0.57±0.05ef 0.59±0.06fghi 0.54±0.03f

April-15 0.1/ leaf 0.33±0.02fg 0.31±0.08fg 0.35±0.07hij 0.34±0.06fg 1/ leaf 0.78±0.13de 0.71±0.07de 0.63±0.11fgh 0.64±0.11ef 2/ leaf 0.98±0.09d 0.90±0.14de 0.93±0.16ef 0.86±0.04de 3/ leaf 1.71±0.08c 1.67±0.12c 1.54±0.14c 1.54±0.07c Untreated 3.14±0.17a 3.06±0.15a 3.05±0.17a 2.95±0.11a

May-15 0.1/ leaf 0.26±0.06g 0.17±0.02g 0.20±0.07ij 0.14±0.02g 1/ leaf 0.74±0.10def 0.69±0.07def 0.78±0.13efg 0.64±0.07ef 2/ leaf 1.10±0.07d 1.07±0.11d 1.06±0.04de 1.01±0.06d 3/ leaf 1.69±0.21c 1.57±0.07c 1.45±0.09cd 1.39±0.10c Untreated 2.50±0.07b 2.40±0.14b 2.31±0.07b 2.00±0.12b

Planting date F(2,24) 206.10 242.49 141.08 177.01 P <0.001 <0.001 <0.001 <0.001 Action threshold F(4,24) 437.09 438.58 257.26 306.15 P <0.001 <0.001 <0.001 <0.001 Planting date × Action threshold F(6,24) 74.49 91.77 56.60 72.19 P <0.001 <0.001 <0.001 <0.001

ф Due to lower Amrasca devastans population, only two ATs were tested and compared with untreated check in March-15 sown cotton Means sharing similar letter within a column are not different significantly (Tukey’s HSD test, P < 0.05)

In 2011, populations of A. devastans reached their highest levels in the last week of June in untreated plots in the transgenic and non-transgenic-cotton. In both experiments, thresholds 0.1, 1, 2 and 3 were first reached on 19th May, 2nd June, 16th June and 23rd June, respectively. Ten spray applications at weekly intervals were required to maintain A. devastans densities at the 0.1 AT level whereas only five applications were required at the

1 AT level (Fig. 1C and 2C). For the 2 AT level, the first spray application was made 91 days after planting (DAT) compared to only 64 DAT for the 1 AT level. A follow-up spray application in the 2 AT level plots was required one week after the initial application and then two more sprays were applied for a total of 4 applications at the 2 AT level.

Maintenance of A. devastans densities at the 3 AT level required two spray applications made at 98 and 105 days after planting (Fig. 1C and 2C).

In 2012, peak populations were reached in the first week of July in untreated plots of both transgenic cotton and non-transgenic cotton. In all plots population increased sharply so spray applications were made in all 0.1, 1, 2 and 3 ATs plots on 11th June. Similar to the previous year, maintenance of densities at the 0.1 and 1 AT levels required ten and five weekly spray applications, respectively (Fig. 1D, and 2D). To maintain the 2 AT level, three spray applications after a fifteen day interval were required, but only one spray application was required to maintain the 3 AT level during 2012 (Fig. 1D and 2D). In both experiments, all the tested thresholds had significantly lowered A. devastans population as compared to untreated control during both years (Table 2).

4.3.1.3 May-15 planting

During both study years the May-15 sown cotton, transgenic and non-transgenic, was damaged by A. devastans at the seedling stage. In 2011, to maintain 0.1 and 1 AT the first spray application was made twenty four days after planting as the population flared up and crossed ATs. An additional eight spray applications were required to maintain 0.1 AT level

86 while four additional sprays were applied to maintain 1 AT level. The thresholds 2 and 3

A. devastans per leaf were reached on 16th June. To maintain densities at the 2 and 3 AT levels, three and two spray applications were made, respectively (Fig. 1E and 2E). In 2012, the population flared up and crossed 0.1, 1 and 2 ATs twenty four days after planting.

Hence eight, four and three spray applications were made respectively to maintain these levels. To maintain 3 AT only one spray application was required in 2nd week of July (Fig.

1F and 2F). Overall, the tested action thresholds had significantly lowered mean A. devastans population as compared to untreated control during both years (Table 2).

4.3.2 Planting time and action threshold impact on cotton yield and lint quality

Planting date and action threshold exerted profound impact on yield and fiber characteristics of both transgenic and non-transgenic cotton, and planting date interactions with action threshold were also significant for the tested parameters. During both years, the

March-15 planting gave maximum yield as compared to other two planting dates and there was significant yield difference among untreated control and ATs treatments. Yield differences for the 0.1 and 1 ATs were non-significant. Similarly, fiber characteristics including staple length (mm), fiber strength (tppsi) and micronaire (μg inch-1) were affected by A. devastans infestation in untreated check, however, 0.1 or 1 ATs did not differ significantly in terms of improving fiber quality in both experiments during 2011 and 2012 (Table 3 and 4).

In April-15 planting, significantly increased yields and improved fiber quality compared to the untreated control were seen in both experiments in 2011 and 2012. Though a pattern of higher yield and better fiber quality at lower thresholds was apparent, yield difference among 0.1, 1 and 2 ATs were non-significant (Table 3 and 4).

In the May-15 planting, yield and fiber quality were severely affected in the untreated control and at the 3 AT level in both experiments in 2011 and 2012. Yields and fiber quality at the 1 AT and 0.1 AT were similar (Table 3 and 4).

4.3.3 Economic analysis

A simple budgeting analysis was performed to evaluate comparative benefits associated with tested action threshold. The thresholds that provided highest net return did not change per unit control cost and lint prices in each sowing date during two years, thus only the results for average values are reported. In the March-15 planting, net returns for the 0.1 and 1 AT levels were higher compared to the untreated control, but marginal returns were

<1 for both transgenic and non-transgenic cotton. In April-15 planting net return was highest for plots treated at 2 A. devastans per leaf action thresholds (ATs). Marginal return was profitable for 0.1-2 ATs with highest marginal return obtained at 2 AT level for both transgenic and non-transgenic cotton. In May-15 planting marginal return was profitable only for 0.1 and 1 ATs but highest net return and marginal return were obtained from the plots treated at 1 AT. Marginal return was consistently negative for transgenic and non- transgenic cotton for the 3 AT treatment (Table 5).

Table 3. Yield and fiber characteristics (± SE) of transgenic cotton in relation to action thresholds at three planting times Planting Threshold 2011 2012 date Yield Micronaire Staple length Fiber strength Yield Micronaire Staple length Fiber strength (Kg ha-1) (μg inch-1) (mm) (tppsi) (Kg ha-1) (μg inch-1) (mm) (tppsi) March-15ф 0.1/ leaf 4707±67.2 a 4.63±0.09a 29.15±0.37a 108.95±0.67a 4808±108.2a 4.70±0.14a 29.34±0.24a 109.31±0.93a 1/ leaf 4651± 106.8a 4.52±0.06ab 28.63±0.25ab 108.3±0.49a 4775±106.1a 4.61±0.09ab 28.75±0.18ab 108.95±0.46a Untreated 3642±86.3c 3.42±0.03d 27.56±0.24cde 89.35±0.46d 3816±89.1c 3.48±0.06d 27.73±0.14cd 90.00±0.64d

April-15 0.1/ leaf 4099±105.4b 4.37±0.18abc 28.72±0.44ab 102.99±0.95b 4227±79.9b 4.38±0.20abc 28.92±0.47ab 103.22±0.61b 1/ leaf 4010±63.0b 4.28±0.13abc 28.34±0.20abc 101.11±0.63b 4135±46.0bc 4.30±0.07bc 28.45±0.32bc 102.96±0.42b 2/ leaf 3985±88.39b 4.12±0.11c 28.15±0.40abc 100.99±0.71b 4099±71.4bc 4.27±0.09bc 28.25±0.18bc 102.2±0.43b 3/ leaf 2400±63.6e 3.34±0.10de 26.58±0.29e 84.73±0.59e 2216±81.3e 3.39±0.06de 26.86±0.21e 85.87±0.45e Untreated 1825±48.8f 2.99±0.06ef 24.11±0.16f 78.63±0.80f 1938±42.4e 3.02±0.01de 24.43±0.14f 79.53±0.78f

May-15 0.1/ leaf 3202±72.1d 4.19±0.10bc 28.01±0.16bcd 94.77±0.69c 3330±130.1d 4.25±0.08bc 28.14±0.10bcd 95.86±0.69c 1/ leaf 3140±116.0d 4.06±0.13c 28.00±0.14bcd 93.89±0.43c 3258±65.1d 4.13±0.16c 28.08±0.14bcd 94.93±0.43c 2/ leaf 1552±92.6f 3.37±0.05de 27.10±0.13de 88.13±0.45d 2196±71.4e 3.42±0.03d 27.31±0.16de 89.53± 0.45de 3/ leaf 957±65.8g 2.89±0.06f 22.95±0.14g 76.05±0.53g 999±62.2f 2.93±0.04f 23.13±0.09g 77.15±0.53g Untreated 1025±48.1g 2.85±0.04f 22.75±0.11g 75.42±0.30g 1063±44.6f 2.89±0.01ef 23.00±0.18g 76.53±0.30g

Planting date F(2,24) 909.44 73.96 145.08 789.96 685.65 64.87 180.29 1086.53 P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Action threshold F(4,24) 476.24 239.02 226.48 1047.97 715.71 187.55 264.41 1285.85 P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Planting date × Action threshold F(6,24) 55.84 5.92 37.39 16.59 20.84 6.47 44.92 21.72 P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

Table 4. Yield and fiber characteristics (± SE) of non-transgenic cotton in relation to action thresholds at three planting times Planting Threshold 2011 2012 date Yield Micronaire Staple length Fiber strength Yield Micronaire Staple length Fiber strength (Kg ha-1) (μg inch-1) (mm) (tppsi) (Kg ha-1) (μg inch-1) (mm) (tppsi) March-15ф 0.1/ leaf 2690±116.7a 4.72±0.19a 29.37±0.26a 111.12±0.86a 2779±70.7a 4.78±0.06a 29.42±0.30a 112.31±0.40a 1/ leaf 2640±81.3ab 4.56±0.08a 28.81±0.13ab 109.95±0.91a 2730±84.9a 4.62±0.09ab 28.99±0.22ab 111.23±0.37a Untreated 1793±72.8d 3.44±0.10b 27.72±0.16de 89.85±0.25d 1827±94.8bc 3.49±0.06d 27.90±0.28de 90.01 ±0.71d

April-15 0.1/ leaf 2400 ±65.1abc 4.62±0.16a 28.87±0.26abc 103.87±0.40b 2562±85.6a 4.67±0.13abc 28.98±0.45abc 104.35±0.95b 1/ leaf 2335±99.0bc 4.51±0.08a 28.26±0.38bcd 103.77±0.62b 2495±84.9a 4.56±0.06bc 28.50±0.34bcd 103.99±0.28b 2/ leaf 2299±25.5c 4.40±0.14a 28.15±0.25bcd 103.55±0.25b 2450±79.2a 4.48±0.06bc 28.35±0.11bcd 103.89±0.63b 3/ leaf 1473±66.5e 3.37±0.05b 26.74±0.8f 86.53±0.69e 1547±99.0bcd 3.41±0.04de 26.94±0.10f 87.93±0.16e Untreated 1025±77.8f 3.07±0.06bc 24.83±0.13g 78.92±0.65f 1123±87.0de 3.15±0.04ef 25.10±0.21g 80.01±0.78f

May-15 0.1/ leaf 1729±102.5de 4.42±0.08a 28.20±0.14bcd 95.95±0.53c 1935±70.7b 4.49±0.06bc 28.29±0.15bcd 96.86±0.61c 1/ leaf 1637±51.6de 4.31±0.13a 28.01±0.13cd 95.23±0.40c 1865±49.5b 4.37±0.08c 28.10±0.14cd 96.32±0.48c 2/ leaf 949±92.6fg 3.39±0.06b 27.14±0.17ef 89.33±0.47d 1395±56.6cd 3.43±0.04d 27.21±0.07ef 90.23±0.54de 3/ leaf 703±45.3g 2.94±0.03c 23.11±0.15h 76.50±0.71g 608±50.2f 3.00±0.02f 23.34±0.04h 77.52±0.37g Untreated 640±90.5g 2.89±0.08c 23.02±0.08h 75.87±0.26g 679±55.6ef 2.98±0.04f 23.25±0.01h 76.97±0.40g

Planting date F(2,24) 395.33 42.33 211.43 1023.76 189.03 82.15 172.58 1135.32 P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Action threshold F(4,24) 213.82 187.69 285.77 1361.37 215.02 373.73 215.27 1526.34 P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Planting date × Action threshold F(6,24) 14.90 7.33 46.30 25.59 12.17 15.96 34.93 26.40 P <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001

ф Due to lower A. devastans population,only two ATs were tested and compared with untreated check in March-15 sown cotton Means sharing similar letter within a column are not different significantly (Tukey’s HSD test, P < 0.05)

Table 5. Comparison of economic benefits of transgenic cotton in relation to different action thresholds at three planting times Planting time Threshold Transgenic cotton Non transgenic cotton No. of sprays Net return Marginal returna No. of sprays Net return Marginal returna (98.37 PRS = (98.37 PRS = 1US$) 1US$) March-15ф 0.1/ leaf 5 3641.11 0.23 5 2062.03 0.42 1/ leaf 1 3697.94 0.26 1 2124.06 0.47 Untreated 0 1458.30 - 0 1448.99 -

April-15 0.1/ leaf 10 1514.65 1.04 10 1732.02 1.02 1/ leaf 5 1542.57 1.08 5 1806.25 1.10 2/ leaf 3 1558.47 1.10 3 1824.66 1.12 3/ leaf 1 936.74 0.20 1 1170.71 0.36 Untreated 0 732.00 - 0 859.79 -

May-15 0.1/ leaf 8 1180.52 1.88 8 1263.29 1.39 1/ leaf 4 1206.53 1.94 4 1300.10 1.46 2/ leaf 3 583.60 0.70 3 862.00 0.62 3/ leaf 1.5 358.65 -0.11 1.5 486.64 -0.08 Untreated 0 411.28 - 0 527.96 - ф Due to lower Amrasca devastans population, only two ATs were tested and compared with untreated check in March-15 sown cotton a Marginal returns <1 are not profitable (pooled data for two seasons)

4.4 DISCUSSION

Among the three planting times under study, lowest A. devastans populations were found each year in the March-15 planting. Furthermore, the 1 AT level was not reached until approximately three months after sowing at a time when the crop reached maturity, thereby showing the pest avoidance benefit of early planting. Other crop pests including flower thrips, Frankliniella occidentalis (Pergande) on cotton (Atakan and Gençer, 2008) and the aphid, Lipaphis erysimi Kalt. on canola (Saljoqi et al., 2009; Saeed and Razaq, 2014) have also been successfully managed by early planting. Lower populations of a different jassid species, Empoasca fabae (Harris) have also been observed on early-planted vs. later-planted cotton in Zimbabwe (Karavina et al., 2012). Maximum density of A. devastans was observed on all its true hosts during warm and dry weather in a recent survey from the Multan region

(Saeed et al., 2015). Average maximum temperatures in February-March usually remain between 14-21 ºC (Table 1), too low for rapid A. devastans build up, therefore, lower populations of A. devastans were observed in early planting. In the current study, maximum yield and fiber quality was obtained from the March-15 planting but declined steadily with later planting dates and under higher insect populations. In addition, climatic conditions are more favourable for the cotton plants in early sowing and plants avail maximum time to attain vigorous growth without devastation of insect pests (Ali et al., 2010).

Shifting of A. devastans from nearby mature okra host (Srinivasan, 2009) and favourable weather conditions (Ghafoor et al., 2011) are two main factors that flare up A. devastans population. Peak densities and overall population pressure was highest in the April-15 planting compared to the other two sowing dates. Population density reached the 1 A. devastans per leaf level approximately two months after the April-15 sowing and eventually increased to a point where all four AT levels were triggered. More sprays were required to maintain all ATs compared to the other two sowing dates. Despite the greater A. devastans

92 pressure and higher number of sprays required for its control in the April-15 planting, significantly higher yields were generated compared to the untreated control. The highest marginal return was obtained at 2 AT level for the April-15 planting.

The results also suggest that threshold of 1 A. devastans per leaf recommended in the past

(Ahmad et al., 1999) can be used to produce profitable cotton with judicial use of insecticides, particularly in locations with late sown cotton (May-15 to end June). In May-15 planting, A. devastans infestation occurs just at the seedling stage. The seedling stage is highly vulnerable to A. devastans damage (Sikka et al., 1966) which helps to explain why the highest marginal return was obtained at 1 AT instead of 2 AT as compared with April-15 planting.

Results from our study showed that all of the tested action thresholds (with the exception of 3

AT in May-15 planting) resulted in significantly higher seed cotton yield compared to the untreated control. However, 1 AT proved better for March and May planting and 2 AT for

15-April planting compared to the 1 jassid per leaf recommendation that was in place prior to the introduction of transgenic cotton. Guidelines based on ATs, rather than calendar based spray schedule, are core to IPM programs and generally help in reducing unnecessary pesticide use (Nault and Shelton, 2010). Action thresholds have been successfully used to manage Plutella xylostella (L.), Pieris rapae (L.) and Trichoplusia ni (Hub.) on cole crops and Thrips tabaci Lind. on onion (Edelson et al., 1989; Fournier et al., 1995; Hines and

Hutchison, 2001; Maxwell and Fadamiro, 2006; Altson and Drost, 2008).

In conclusion, A. devastans populations on cotton were differentially influenced by the time of planting and action thresholds, hence indicating complexity of developing reliable ATs.

Moreover, date of planting had a strong influence on the relative effectiveness of different

AT levels in terms of marginal returns on cotton yields, and thus has important repercussions for using the action threshold concept in IPM.

Based on the result of present study and in an effort to reduce insecticide applications by focusing on planting time, our results for the March-15 planting date indicated that a single spray in the month of July returned a profitable yield. The April-15 planting was capable of withstanding greater pest pressure so that delaying control measures until the 2 AT effectively limited damage to an acceptable level without significant reduction in yield.

However, the May-15 planting was more sensitive to pest attack and therefore spray should be started at 1 AT level early in the season to manage A. devastans populations to avoid significant reduction in yield.

Determining the relationship between crop yield loss and insect numbers or damage is complicated. Many factors can affect this relationship, climate, variety, susceptibility level in plants to insect damage, growth stage of the crop and the insect stage targeted (as reviewed in

Nault and Shelton, 2010). Therefore, further continuous research will be needed to verify

ATs developed in this research. In short, action thresholds are flexible and can be changed with time of planting. Our results suggest that planting time based action thresholds can provide cost-effective method for timing insecticide application crucial for suppression of A. devastans, further yield and economic benefits will be maximized by adopting early planting of cotton.

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CHAPTER-5

Impact of neonicotinoid seed treatment of transgenic cotton on

the cotton leaf hopper, Amrasca devastans (Hemiptera:

Cicadellidae), and its natural enemies

This chapter has been accepted as;

Saeed, R., Razaq, M. and Hardy, I.C.W., 2015. Impact of neonicotinoid seed treatment of transgenic cotton on the cotton leaf hopper, Amrasca devastans (Hemiptera: Cicadellidae), and its natural enemies. Pest Manag. Sci. DOI 10.1002/ps.4146 (ISE Impact Factor 2.694)

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5.1 INTRODUCTION

Modern seed treatment products, focused against insect pests or fungal pathogens, were introduced in the 1970s and 1980s (Heyland, 1990; Taylor, 2001). Insecticidal treatment of seeds directly protects crops from early season foliar pests and seed or root feeders. Seed treatment has become common in agriculture as, compared to traditional foliar application, it has lower financial costs (Zhang et al., 2011), requires less active ingredient and reduces exposure to non-target organisms (Taylor et al., 2001; Albajes et al., 2003). Further, seed treatment can provide efficient pest control in situations where crop phenology prohibits foliar applications (Nault et al., 2004) or in conditions where management timing is crucial but difficult (Bradshaw et al., 2008; Strausbaugh et al., 2010).

The development of the neonicotinoid group of insecticides led to increased use of seed treatment in row crops (Elbert et al., 2008; Gore et al., 2010). Active ingredients of neonicotinoids are taken up by roots during germination and move systemically within the plant, protecting the growing plant from insect pests (Schemeer et al., 1990; Nault et al.,

2004). Imidacloprid and thiamethoxam are chloronicotinyl insecticides that are agonistic at the nicotinic acetylcholine receptor and interfere with the transmission of stimuli or impulses in the insect nervous system (Elbert et al., 1991). Due to their mode of action, they can combat a number of sucking pests on various agricultural crop plants. They have been used successfully against the early pest complex in sugar beet, vegetables, maize and other crops

(Leicht, 1993; Taylor, 2001; Nault et al., 2004). For example, imidacloprid and thiamethoxam treatment provides protection against Amrasca devastans (Dist.) on okra,

Abelmoschus esculentus L. (Kumar et al., 2001), and against Cerotoma furcate (Forster)

(Coleoptera: Chrysomalidae) on snap bean, Phaseolus vulgaris L. (Koch et al., 2005). Field studies have shown that both of these compounds can provide adequate protection against early-season sucking pests of cotton (Gossypium hirsutum L.), including Bemisia tabaci

101

(Genn.), Thrips tabaci Lind., Aphis gosypii Glover and A. devastans (Dhawan et al., 2006;

Naveed et al., 2010; Zhang et al., 2011; Zidan, 2012). In addition to providing protection against sucking pests, these seed treatment insecticides are reported to enhance plant growth

(Murugesan and Kavitha, 2009).

Since the introduction of bollworm resistant Bt cotton in 2005, the cotton bollworm,

Helicoverpa armigera (Hübner) has been brought under control in many Asian countries

(Sharma and Pampathy, 2006; Sabir et al., 2011). The cotton bollworm is a chewing pest but sucking pests are not susceptible to Bt toxins and thus remain a threat (Sabir et al., 2011). The cotton leaf hopper or jassid, A. devastans (Dist.) [= Amrasca biguttula biguttula (Ishida)

(Ghauri, 1983)] (Hemiptera: Cicadellidae), is one of the most devastating early-season sucking pests of cotton and eggplant, Solanum melongena L. (Razaq et al., 2013; Yousafi et al., 2013), with estimated seed-cotton losses averaging 37% in Pakistan (Ahmad et al., 1985).

A. devastans sucks the cell sap from the underside of the leaves, inducing downward curling and injects phytotoxic saliva into the host plant. Severe damage causes uneven and stunted cotton plant growth, the shedding of squares and bolls expediting along with deterioration of fiber quality (Huque, 1994; Maketon et al., 2008).

Farmers rely heavily on chemical control to manage A. devastans (Akbar et al., 2012). Direct application of insecticide to A. devastans is hindered by the fact that females lay eggs inside host plant leaf veins (Agarwal and Krishnananda, 1976). Seed treatment is thus an effective method for systemically delivering insecticide to the locality of A. devastans eggs.

Nonetheless, the sole reliance on insecticides may cause undesired effects in the form of insecticidal resistance by A. devastans and/or the mortality of its arthropod natural enemies

(Soerjani, 1998; Naveed et al., 2011, Saeed et al., 2015). For instance, increased use of neonicotinoid seed treatments has resulted in substantial increases in spider mite, Tetranychus sp. populations across the southern Mississippi, USA by killing natural enemies (Smith et al.,

102

2013). Further, in Pakistan, due to over-use of insecticides, A. devastans developed resistance against foliar formulations of pyrethroids in the 1990s (Ahmad et al., 1999) and some resistance against foliar formulations of neonicotinoids has recently been recorded

(Anonymous, 2012). Thus, the frequent use of cotton seed treatment insecticides, such as imidacloprid and thiamethoxam, may ultimately affect their efficacy against A. devastans.

Insecticidal treatment may also incur side-effects on non-target arthropod predators

(beneficial natural enemies) that occur within the transgenic cotton agro-ecosystem. Here we evaluate the efficacy of imidacloprid and thiamethoxam seed treatments at different dosages, including the recommended dose rates, for managing A. devastans and also their impact on natural enemies. We also evaluate the effect of these insecticides on cotton plant growth in both the presence and absence of A. devastans.

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5.2 MATERIALS AND METHODS

Our experiments used seeds of transgenic cotton (Bt-CIM-599). The evaluated insecticides were imidacloprid (Confidor 70 WS, Bayer Crop Science) and thiamethoxam (Actara ST 70

WS, Syngenta). The manufacturer-recommended doses for their application are 5 g/kg cotton seed for imidacloprid and 3 g/kg seed for thiamethoxam.

5.2.1 Effect of insecticide dose on insect populations

5.2.1.1 Seed treatment

Each insecticide was tested separately and at four dosages; specifically 0.5×, 1×, 1.5× and 2× its recommended dose. Before insecticidal application, acid delinted (using concentrated

H2SO4 at 100 ml/kg seed) cotton seeds were soaked in tap water for 30 min, to remove the acid, and then dried on sieves. Imidacloprid or thiamethoxam was then mixed into 200 ml of water in separate containers. Cotton seeds were then placed in bowls and shaken vigorously with an insecticide solution (imidacloprid at 2.5, 5.0, 7.5 and 10 g/kg seed, thiamethoxam at

1.5, 3.0, 4.5 and 6 g/kg seed) for five minutes then spread on plastic sheets to dry. Seeds for a control treatment (without insecticide) were prepared as above but shaken with water rather than an insecticide solution. The 9 experimental treatments were thus the four doses of imidacloprid, the four of thiamethoxam and the control.

5.2.1.2 Experimental design

Field experiments were conducted in both 2010 and 2011, between mid-May (sowing) and late October (harvest) under semi-arid climatic conditions on silt loam soils at the Central

Cotton Research Institute, Multan, Pakistan.

Treated seeds were planted in the bed and furrow method, via manual dibbling. Experiments were laid out in a randomized block design comprising one replicate plot of each of the nine treatments within each of three blocks. However, as there was no marked difference in soil fertility or other environmental factors in the experimental area, this left open the possibility

104 of analysing the data as if from a completely randomized design. Each plot was an area of

9.15 m × 4.57 m, with 0.23 m between plants and 0.76 m between rows within plots. Plots were 1.2 m apart and blocks were 3.0 m apart, with spaces between plots and blocks left fallow.

5.2.1.3 Population sampling

Sampling for A. devastans and its predators began two weeks after sowing. Once A. devastans was seen to be present, data were recorded following Razaq et al. (2005): every five days and within each sampling site, 10 plants per replicate were randomly selected and one apical leaf, one mid-plant leaf and one leaf from the lower part of each plant were inspected. The random selection of plants was repeated at each visit. The numbers of A. devastans per leaf found within each replicate on each visit were used as the estimators of population abundance. Predator abundance was estimated by counting the numbers of predatory arthropods (insects and spiders) present on 5 whole plants from each replicate on each visit.

5.2.2 Effect of insecticide on cotton growth

5.2.2.1 Field

At 30 and 40 days after sowing in the field (with A. devastans present), two plants were removed gently from each plot in which seeds had been treated with the manufacturer- recommended doses of thiamethoxam (3 g/kg), imidacloprid (5 g/kg) and from the control plots. In the laboratory, plants were washed with water to remove the soil and then spread on paper. For each removed plant, the number of leaves per plant was counted, and the root length and stem length measured.

5.2.2.2 Greenhouse

We used a greenhouse to obtain plant growth estimates in the absence of A. devastans. Seeds were treated with the manufacturer-recommended doses of imidacloprid or thiamethoxam, or

105 were untreated (control) following methods described above. Seeds were then sown in soil

(silt loam) in plastic pots, with four seeds per pot and ten pots per treatment. Pots were placed in a greenhouse at CCRI, Multan, in May 2012. Plants were watered daily, as required.

Conventional NPK fertilizer was applied to each pot three times during the experiment. After

10, 20, 30 and 40 days, six plants from each treatment were removed gently, washed with water and spread on paper. Root and stem lengths were measured and the numbers of leaves counted. After each observation day, pots containing fewer than four plants were discarded to remove confounding influences of variation in interplant competition.

5.2.3 Statistical analysis

All statistical tests were carried out using GenStat statistical package (VSN International,

Hemel Hempstead, UK). We used general linear models (GLMs) to explore effects of dosage of imidacloprid or thiamethoxam on the numbers of A. devastans and of beneficial insects present and also to examine patterns of cotton plant growth. For analyses of A. devastans and predator seasonal totals we treated data on according to the randomized block design (i.e.

ANOVAs and ANCOVA’s with blocking). Repeated measures ANOVAs and ANCOVAs were further employed for analyses of within-season pest sample data and for analyses of cotton plant growth.

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5.3 RESULTS

5.3.1 Effect of insecticide dose on arthropod populations

5.3.1.1 Amrasca devastans

The overall numbers (seasonal totals) of A. devastans present were significantly greater in

2010 than in 2011 (F1,50 = 19.58, P < 0.001) so further analyses of pest abundance were carried out separately for each year. In both years, around half as many A. devastans were present when insecticide had been applied to seeds than when it had not (ANOVA: 2010:

F1,23 = 48.87, P < 0.001; 2011: F1,23 = 145.83, P < 0.001). When insecticide had been applied

(i.e. with control treatment data excluded), the dose applied to the seeds influenced A. devastans seasonal totals; fewer A. devastans were present when doses (g/kg) were higher

(ANCOVA: 2010: F1,19 = 47.77, P < 0.001; 2011: F1,19 = 49.32, P < 0.001). The type of insecticide applied (imidacloprid or thiamethoxam) had no significant influence on A. devastans numbers in 2010 (ANCOVA: F1,19 = 1.59, P = 0.223) but in 2011 seasonal totals were lower for a given dose (g/kg) of thiamethoxam than for imidacloprid (ANCOVA: F1,19 =

23.60, P < 0.001). These patterns in seasonal pest totals are illustrated in Figure 1.

The numbers of A. devastans present varied within each of the two growing seasons (repeated measures analysis: 2010: F7,154 = 47.52, P < 0.001; 2011: F7,154 = 167.69, P < 0.001). Small numbers appeared after 20-25 days after sowing, with first appearances being earlier when sees were untreated (control) or received the lowest does of imidacloprid (2.5 g/kg) or thiamethoxam (1.5 g/kg) (Fig. 2). Numbers of A. devastans then typically increased over time, peaking after 50 days (2010) and at 55 days (2011). The effect of insecticide dose on A. devastans numbers, which is illustrated for seasonal totals in Figure 1, can also be seen in

Figure 2: within each year, the numbers of A. devastans present were almost always lowest on plants growing from seeds with the highest doses (g/kg) of insecticide applied

(represented by thickest lines), as confirmed by repeated measures analyses of the effect of

107 insecticide dose applied (2010: F1,19 = 47.76, P < 0.001; 2011: F1,19 = 49.32, P < 0.001).

These analyses also confirmed that in 2010 the type of insecticide applied had no significant influence on A. devastans numbers (imidacloprid or thiamethoxam: F1,19 = 0.50, P = 0.489; insecticide type × days after sowing interaction: F7,154 = 3.17, P = 0.078, Greenhouse-Geisser epsilon = 0.182) but in 2011 pest numbers were lower when thiamethoxam rather than imidacloprid was applied at a given dose (F1,19 = 7.53, P = 0.013) although there was no significant interaction between insecticide type and the number of days after sowing (F7,154 =

2.68, P = 0.069, Greenhouse-Geisser epsilon = 0.3354).

5.3.1.2 Predators

There was no difference in the mean number of predators sampled per visit in 2010 and 2011

(exactly 1964 individuals were found in each year: ANOVA: F1,52 = 0.00, P = 1.0) and no significant interaction between year and the experimental treatment (Factorial ANOVA: F8,34

= 0.47, P = 0.872); so predator data from the two years were analysed collectively.

There were fewer predators present when insecticide had been applied to seeds than when it had not (ANOVA: F1,50 = 9.12, P < 0.004). When insecticide had been applied (i.e. with control treatment data excluded), the higher the dose (g/kg) of insecticide applied, the fewer predators were present overall (ANCOVA: F1,43 = 273.11, P < 0.001) and for a given dose, there were fewer predators present when thiamethoxam was used rather than imidacloprid

(ANCOVA: F1,43 = 150.80, P < 0.001). We separately explored the effects of dose of each chemical on the total numbers of each type of predator: in every case predator numbers declined significantly (P < 0.001) with insecticide dose (for imidacloprid: Total, F1,26 =

109.34; Chrysoperla, F1,26 = 99.37; Spiders, F1,26 = 105.88; Orius, F1,26 = 91.4; Coccinellids,

F1,26 = 40.11; Geocoris, F1,26 = 45.27; for thiamethoxam: Total, F1,26 = 326.64, Chrysoperla,

F1,26 = 217.85; Spiders, F1,26 = 262.34; Orius, F1,26 = 330.01; Coccinellids, F1,26 = 56.22,

Geocoris, F1,26 = 48.95). Patterns in seasonal pest totals are illustrated in Figure 3.

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Fig. 1 Effects of pesticide and dose on seasonal total numbers of Amrasca devastans. Data points are total A. devastans sampled per leaf per replicate in each year. Fitted regression lines are from separate log-linear analyses (Crawley, 1993; Faraway, 2006) for 2010 and 2011 and do not include data from the control treatment (no insecticide applied). Parsimonious statistical descriptions were obtained by removing sequentially from a maximal model (Crawley, 1993) but as information on blocking was excluded, regression lines are presented for informal illustration only. In 2010 the response to dose was curvilinear and there was no difference in effect between the two pesticides. In 2011 the dose response was not curvilinear (i.e. it was a straight line on the log scale) and imidacloprid had a greater suppressive effect than thiamethoxam

109

Fig. 2 Impact of seed treatment on mean abundance of Amrasca devastans per leaf at different time intervals after sowing. Doses are expressed in g/Kg and are 0×, 0.5×, 1×, 1.5× and 2× the manufacturer recommended dose for each insecticide

110

Fig. 3 Effects of pesticide and dose on predator populations. Data are pooled across the two study years. Fitted regression lines are from separate log-linear analyses (Crawley, 1993; Faraway, 2006) of the total numbers of predators and for each predator taxon separately. All regressions, except for Chrysoperla, Geocoris and the Coccinellids treated with thiamethoxam, include a polynomial term. As information on blocking was excluded, the regression lines are presented as informal illustration of analytical results presented in the text

111

5.3.2 Effect of insecticide on cotton growth

5.3.2.1 Field

The lengths of cotton plant roots and shoots and the numbers of leaves on the plants all increased between 30 and 40 days after sowing (repeated measures ANOVAs: root length:

F1,15 = 82.84, P < 0.001; shoot length: F1,15 = 181.44, P < 0.001; number of leaves F1,15 =

18.859, P < 0.001, Fig. 4). Roots, shoots and leaves were also affected by seed treatment

(respectively, F2,13 = 73.64, P < 0.001; F2,13 = 458.95, P < 0.001; F2,13 = 219.30, P < 0.001), plants treated with the recommended dose of imidacloprid had longer roots and shoots and more leaves than those treated by the recommended dose of thiamethoxam, and untreated plants had the shortest roots and stems and the fewest leaves (Fig. 4) (the numbers of A. devastans that were present are shown in Fig. 2). There were also positive interactions between seed treatment and time for shoot length (F2,15 = 13.41, P < 0.001) and between seed treatment and time for leaf number (F2,15 = 44.63, P < 0.001) but no significant interaction between seed treatment and time for root length (F2,15 = 0.14, P = 0.873): plants treated with imidacloprid had notably the longest shoots and most leaves 40 at days after sowing (Fig. 4).

5.3.2.2 Greenhouse

The lengths of cotton plant roots and shoots and the numbers of leaves on the plants all increased between 10 and 40 days after sowing (repeated measures ANOVAs: root length:

F3,45 = 1448.27, P < 0.001; shoot length: F3,45 = 1163.82, P < 0.001; number of leaves F3,45 =

1525.96, P < 0.001, Fig. 5). Roots, shoots and leaves were also affected by seed treatment

(respectively, F2,13 = 137.84, P < 0.001; F2,13 = 424.63, P < 0.001; F2,13 = 61.36, P<0.001); plants treated with the recommended dose of imidacloprid or thiamethoxam had longer roots and shoots and more leaves than untreated plants (Fig. 5). There was also a positive interaction between seed treatment and time for shoot length (F6,45 = 17.42, P < 0.001) but no significant interaction for root length (F6,45 = 0.48, P = 0.774) or for leaf number (F6,45 =

112

2.71, P = 0.056): plants treated with the recommended dose of imidacloprid or thiamethoxam had greater increases in shoot length than untreated plants (Fig. 5).

113

Fig. 4 Effect of treatments on cotton plant size under field conditions. Seeds were treated with imidacloprid or thiamethoxam at manufacturer-recommended doses or were untreated (control). The standard error of the difference is denoted by s.e.d.

114

Fig. 5 Effect of treatments on cotton plant size under greenhouse conditions. Seeds were treated with imidacloprid or thiamethoxam at manufacturer-recommended doses or were untreated control). The effective standard error is donated by e.s.e.

115

5.4 DISCUSSION

Our results re-affirm that insecticidal seed treatments can reduce the incidence of A. devastans during the early growth stages of cotton crops (Vadodaria et al., 2001; Saleem et al., 2003; Vijaykumar, 2007). Dhawan et al. (2006) found equivalent effects of thiamethoxam and imidacloprid against A. devastans: our 2010 data similarly indicate that the overall response of A. devastans to insecticide dose is the same for these insecticides. However, our

2011 data indicate that, at a given dose (g/kg) thiamethoxam has a greater suppressive effect than imidacloprid. In terms of the effects of applying these insecticides at their manufacturer- recommended doses, the 2010 data indicate that imidacloprid would achieve the greater suppression (because the recommended dose is 2 g/kg higher than that of thiamethoxam) and the 2011 data indicate that the two pesticides would result in similar numbers of A. devastans being present during the season overall.

Pest abundance increased throughout the growing season in both years and exceeded the economic threshold level (ETL) for damage (one A. devastans per leaf, Ahmad et al., 1985) before harvest in both years and under all experimental treatments. Treatment did, however, affect the time taken for the ETL to be reached, with duration of protection increasing with increasing insecticidal dose (as also reported by Nault et al., 2004). A. devastans numbers on untreated (control) plants, and on plants treated with the lowest doses of thiamethoxam (1.5 g/kg) or imidacloprid (2.5 g/kg), reached the ETL at around 25 days after sowing in both years. Treatment with the recommended dose of thiamethoxam (3 g/kg) resulted in the ETL being reached after around 30 days and the recommended dose of imidacloprid (5 g/kg) suppressed A. devastans below the ETL until around 40 to 45 days after sowing. Our results support the recent report from Egypt by Zidan (2012) that imidacloprid has a greater potential than thiamethoxam to control A. devastans during the early growth stages of cotton plants.

Differences in the effect of these insecticides are potentially due to the development of

116 greater resistance by A. devastans to thiamethoxam than to imidacloprid. For instance, tobacco thrips, Frankliniella fusca have developed resistance to thiamethoxam, but applications of imidacloprid still provide effective management in Arkansas and the mid- south of the USA (Lorenz, 2013). The differences in pest populations between the two years in which the field experiment was carried out further indicate that many environmental, especially meteorological, factors may influence the degree of pest control that insecticidal application can provide (Zhang et al., 2011).

We found that application to seeds affected the subsequent abundances of beneficial predatory arthropods in the cotton crop. In general, higher doses of insecticide led to lower populations of predators but the negative effects of imidacloprid were not apparent unless the manufacturer-recommended dose was exceeded. In contrast, the recommended dose of thiamethoxam reduced the abundance of beneficial arthropods to approximately two-thirds of the numbers observed in plots untreated with pesticide. This accords with the findings of

Seagraves and Lundgren (2011) that thiamethoxam, but not imidacloprid, application was associated with a reduction in a community of generalist predators in the soybean agro- ecosystem. Even when application of insecticide does not affect the abundance of natural enemies (e.g. doses of imidacloprid ≤ 5 g/kg) there may be indirect negative effects on predators via a reduction in the abundance of their prey and also via sub-lethal effects on the performance of individual predators (Goulson, 2013; Li et al., 2015).

Treating seeds with the manufacturer-recommended doses of imidacloprid and thiamethoxam did not affect seed germination rates (R.S. unpublished data) showing that these insecticides are not phytotoxins. Similar findings have been reported when these chemicals have been applied to oil palm, Elaeis guineensis Jacq. seeds (Chanprasert et al., 2012) and in rice thiamethoxam can enhance the proportions of seeds that germinate (Almeida et al., 2013).

Moreover, we found that application of thiamethoxam and imidacloprid seed treatment

117 enhanced the subsequent growth of cotton plants in the field, similar to prior reports for cotton growth after imidacloprid seed treatment (Gupta and Lal, 1998; Dandale et al., 2001;

Murugesan and Kavitha, 2009) and for rice with thiamethoxam applied (Almeida et al.,

2013). Such enhancement could result indirectly from the reduced presence of A. devastans and/or as a direct effect of the neonicotinoids on plant growth. The fact that cotton plant growth was also enhanced by thiamethoxam and imidacloprid application under greenhouse conditions, where no pests were present, shows that these chemicals affect plant growth directly. Thiamethoxam has previously been reported to enhance plant growth by enhancing ionic transport, which increases mineral nutrition, and by promoting enzymatic activity leading to increased amino acid production (Almeida et al., 2013). Under greenhouse conditions, the growth of plants following seed treatment with thiamethoxam or with imidacloprid was very similar, whereas in the field plants growing from seed that had had imidacloprid applied were larger at 30 and 40 days after sowing than those treated with thiamethoxam; likely due to the longer time taken for A. devastans populations to reach the

ETL when imidacloprid was applied.

5.4.1 Conclusions and caveats

This study confirms that treating cotton seeds with thiamethoxam and imidacloprid has a suppressive effect on the subsequent abundance of the cotton leaf hopper, A. devastans.

These insecticides not only protect cotton plants from this sucking pest but also enhance plant growth directly. However, both chemicals, and especially thiamethoxam, can have detrimental effects on the populations of beneficial arthropods that are the natural enemies of

A. devastans. At the manufacturer-recommended dose of 5 g/kg of seed, imidacloprid provided effective control of A. devastans for at least 40 days after sowing and had little effect on the seasonal abundances of natural enemies. Despite this, when growing seed- treated cotton, agriculturalists should still carry out routine checking for A. devastans

118 throughout the season because the growing season for cotton is relatively long and A. devastans populations may increase suddenly mid-season, as seen in 2010. Under such circumstances foliar application of insecticides can be considered as a remedial measure.

Finally, while our data suggest that moderate doses of some neonicotinoids, especially imidacloprid, applied to cotton seeds may not have detrimental effects on natural enemy abundance, it is important to consider that we have not evaluated any longer-term effects on individual natural enemies nor have we evaluated effects on further beneficial insect species in and around the cotton agro-ecosystem. Given that there has been recent and substantial concern about sub-lethal but detrimental effects of neonicotinoids, including imidacloprid and thiamethoxam, on agriculturally beneficial insects (e.g. Whitehorn et al., 2012; Derecka et al., 2013; Goulson, 2013; Li et al., 2015) we cannot advocate their usage without due caution.

119

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125

CHAPTER-6

Integrating plant resistance and pesticide application to manage

cotton leafhopper, Amrasca devastans (Dist.): its impact on

natural enemies, yield and fiber parameters of transgenic

and non-transgenic cotton

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6.1 INTRODUCTION

Like other cotton production systems of the world synthetic insecticides have been applied to manage insect pests of cotton in Pakistan since the 1950,s. In late 1980’s 100% area of cotton received application of insecticides (Ahmad, 1999). According to an estimation farmers spend US $300 million to buy pesticides annually, of which more than 80% are applied to manage cotton insect pests in the country (Khooharo et al., 2008; Arshad and Suhail, 2011;

Khan, 2011). Genetically modified cotton encoding Bacillus thuringiensis Berliner genes

(known as Bt cotton) that produce the Cry 1Ac protein, toxic to the lepidopteran insect species, was introduced 10 years ago in the country. However, sucking pests [cotton leafhopper, Amrasca devastans (Dist.), whitefly, Bemisia tabaci (Genn.) and thrips, Thrips tabaci Lind.] are still primary insect pests of cotton and induce huge losses (Sabir et al.,

2011).

Among these insect pests cotton leafhopper (= jassid), A. devastans (Dist.) (Hemiptera:

Cicadellidae) can cause 37.03 % yield decrements in Pakistan (Ahmad et al., 1985). Both adult and nymph of A. devastans feed on cell sap from cotton leaves by mechanically blocking the phloem and xylem vessels, injecting toxic saliva that ultimately cause stunting, curling and browning of the leaves (Rehman, 1940; Borror et al., 1981; Narayanan and Singh,

1994). In India this has been reported to result in complete crop failure in cotton (Rao et al.,

1968).

Host plant resistance (HPR) to manage arthropod pests was recognized 100 years as sound approach. Plant resistance is considered as key component of the IPM (Alabi et al., 2003).

Although this component provided complete control of several insect pests in the past [e.g. wheat hessian fly, Mayetiola destructor (Say)], however, in cotton production system host plant resistance has been integrated with insecticides (Dhawan et al., 2013). There are three mechanism of resistance i.e., preference/non-preference, antibiosis and tolerance. Resistant

127 cultivars released for cultivation usually possess one of above these mechanisms. Non- preference (antixinosis) mechanism of resistance has exploited in the past to manage populations of A. devastans. Hairy varieties of the cotton are not preferred by A. devastans.

The hair length on the mid vein interferes with the oviposition of the pest (Simwat, 1994). On the other hand hairy varieties are susceptible to B. tabaci (Rao et al., 1990) due to their preference for oviposition. Cultivation of the variety (LPS 141) resistant to whitefly in an

Indian region increased the populations of A. devastans (Basu, 1992). Therefore, breeding for resistance to A. devastans leads to the susceptibility of B. tabaci. Due to this limitation development of varieties only resistant to A. devastans or B. tabaci did not get attention of the breeders in India and Pakistan (Singh, 2004).

Cotton growers rely solely on the use of insecticides to manage A. devastans (Saeed et al.,

2015). Most of the Pakistani farmers are resource poor and need pest management strategies that are cost effective and sustainable. Hence, there is need to reduce use of pesticides due to their high costs and other associated risks including human health, natural enemies mortality and resistance development.

Integrated Pest Management (IPM) is the strategy being successfully applied throughout the world (Fitt, 2000) in order to minimize insecticides. Exploiting insect resistant traits alone may not manage the entire population of insect pest below the economic injury level but their combination with other control tactics could effectively manage the insect pest population

(Karungi et al., 2000b; Nargis et al., 2013). Integrating resistant/tolerant varieties with spray regimes successfully improved cowpea yield by suppressing insect pests in Nigeria (Kamara et al., 2007).

Researchers in the past evaluated newly developed cultivars of cotton for their comparative resistance to A. devastans or determining the correlation of different characters (hair density, length of hair etc.) of varieties with populations of the pest (Ahmad and Haq, 1981; Ali and

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Ahmad, 1982 also see references in discussion). But no literature reports integration of chemical control with HPR to manage A. devastans and their effect on cotton yield and its fibre quality. We concentrated on a comparison of transgenic cotton producing Bt toxin

Cry1Ac and non- transgenic cotton varieties, which have different agronomic traits (non- isogenic or non-parental lines) and are recommended for farmers in the Pakistani Cotton Belt

(Southern Punjab). Most of the varities are not sufficiently resistant to insect pest complex due to antagonistic nature of resistance mechanism. The hypothesis of present study was whether there is partial resistance to A. devastans and if integrated with chemical control can reduce the numbers of insecticide application ultimately without affecting yield. Since there is no susceptible or wild type variety available to compare resistance, therefore varities will be compared amongselves for harboring populations of A. devastans.

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6.2 MATERIALS AND METHODS

6.2.1 Experimental area

The field trials were conducted under semi-arid climatic conditions on silt loam soils at

Central Cotton Research Institute (CCRI), Multan (30.120N and 71.280E) situated in the

Southern Punjab, Pakistan during 2011 and 2012.

6.2.2 Cotton varieties and insecticides

Seeds of randomly selected transgenic cotton producing Bt toxin Cry1Ac (AA-802, NIBGE-

3701, NIBGE-2 and AA-703) and non- transgenic (CIM-496, CIM-499, CIM-446 and CRIS-

134) cotton varieties were provided by Cotton Breeding Section of CCRI, Multan.Three pesticide regimes were maintained i.e. 1) untreated control, 2) spray at economic threshold level ‘ETL’ (1jassid leaf-1; Ahmad et al., 1985) and 3) biweekly spray or ‘treated control.

Recommended insecticides dimethoate (Danadim Progress 40% EC, Swat Agro Chemicals,

Peshawar, Pakistan), acephate (Acefax 75% SP, Jaffer Group, Karachi, Pakistan) and diafenthiuron (Polo 500 SC, Syngenta, Karachi, Pakistan) were used in regime 2 and regime

3 with rotation. In treated control, a perfect protection of the crop was simulated with no damage by A. devasatns.

6.2.3 Experimental design

Randomized complete block design (RCBD) was followed with split plot layout having two factors i.e. spray regimes (main-plots) and varieties (sub-plots). Sub-plots size consisted of

12.20 × 6.10 m, separated by 1.52 m buffer zone. There were three replications in the experiment.

Seeds of each variety were dibbled manually by using bed and furrow method on 20th May and 22nd May during 2011 and 2012, respectively. Plant to plant and row to row distance was

0.23 m and 0.76 m, respectively. All the standard cultural practices recommended by Punjab

Agriculture Department, Government of Pakistan, were followed. Cotton plants were

130 protected from damage of whitefly and bollworms by applying insecticides pyriproxyfen

(Priority 10.8EC, KANZO Ag, Multan, Pakistan) and spinosad (Tracer 240 EC, Arysta Life

Science, Karachi, Pakistan) at their field recommended doses.

6.2.4 Sampling of Amrasca devastans and natural enemies

Sampling for A. devastans and its predators was started after two week of sowing from four inner rows in each subplot (Razaq et al., 2005). Expended leaves (n= 30), one leaf from apical, 2nd from middle and 3rd from the bottom portion of randomly selected plants (n= 10) from each sampling site were observed visually twice a week. Population densities were estimated by calculating mean number of A. devastans per leaf across all three replicates.

Whole plant counts of predators were made from randomly selected plants (n= 5) within four inner rows of each plot in each sampling date. Parasitoids were not recorded due to availability of limited resources and intensive labour.

6.2.5 Plant traits

6.2.5.1 Moisture contents (%)

To assess the leave moisture contents percentage, sixty days after sowing three samples of leaves i.e. from the top, middle and bottom portion of different plants from each plot of treated control (biweekly spray) were collected, packed separately in paper bags and brought back to the laboratory. Thereafter, moisture contents (%) were determined by using oven dry method (Saleem et al., 2013) by using the following formula:

푤eight of fresh leaves − weight of dry leaves Moisture contents (%) = × 100 Weight of fresh leaves

6.2.5.2 Chlorophyll level (SPAD)

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Chlorophyll level of leaves (n= 10 per replicate) from upper, middle and lower portion of different plants within four middle rows of each plot of treated control was taken sixty days after sowing with the help of SPAD 502 Plus Chlorophyll Meter (Ahmad et al., 2013).

6.2.5.3 Number of leaves and Plant height (cm)

Three plants from each plot of treated control were randomly selected. Leaves were counted visually and then ordinary meter road was used to measure plant height from ground level to canopy (Iqbal et al., 2011).

6.2.5.4 Leaf area (cm2)

To access area of leaf lamina, three plants were randomly selected from each plot of treated control. Then one leave each from upper, middle and lower portion of each selected plant were taken to measure leaf area with the help of Laser Leaf Area Measuring Meter Model CI

203 (USA made) (Ali et al., 2012).

6.2.5.5 Thickness (μm) and length (cm) of leaf parts

From each plot of treated control, three plants were randomly selected and then three leaves one each from upper, middle and lower portion of selected plants were taken. Fine razor was used to cut five cross sections of each leaf portion i. e. leaf lamina, midrib and vein.

Thickness of these cut sections was determined under a CARL ZEISS binocular microscope by using an ocular micrometer (Ahmad et al., 2005; Khan et al., 2010; Saleem et al., 2013).

Measuring scale was used to record the length of leaf midrib and length of side veins

(Eittipibool et al., 2001).

6.2.5.6 Hair length on the leaf lamina, midrib and vein (μm)

To determine hair length, leaves as described above (see 6.2.5.5) were taken and hair length on leaf lamina, midrib and vein was measured under a CARL ZEISS binocular microscope by using an ocular micrometer (Ahmad et al., 2005; Khan et al., 2010; Saleem et al., 2013).

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6.2.5.7 Hair density on leaf lamina, midrib and vein

Leaves were taken as described above (see 6.2.5.5) and then 1cm length of midrib and vein was selected, while the area for leaf lamina (1 cm2) was chosen with the help of iron dye of 1 cm2 to count hair density under stereoscopic microscope (Ahmad et al., 2005; Khan et al.,

2010; Saleem et al., 2013).

6.2.6 Seed cotton yield

At crop maturity, raw cotton from each plot (n= 3 plots per sub-treatment) was picked for recording yield. Seed cotton samples (n= 100 g) from each plot were packed separately in paper bags and sent to Fiber Technology Department, CCRI, Multan for lint testing during

2012. Reduction percentages of fiber parameters and seed cotton yield were estimated by dividing mean values of each variable taken from untreated control treatment with mean values of biweekly or treated control treatments.

6.2.7 Statistical analysis

Data on all variables means was subjected to analysis of variance (ANOVA) by using

Statistix software version 8.1. Treatments means showing significant F-statistics were compared using Tukey’s HSD test with 5% level of probability. Spearman’s rank correlation

(Siegel and Castellan, 1988) was employed to determine correlation between plant traits and

A. devastans and to explore impact of A. devastans infestation on seed cotton yield and fiber variables.

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6.3 RESULTS

6.3.1 Varieties and pesticide integration impact on Amrasca devastans

Varieties exerted profound impact on A. devastans in terms of its population variation.

Significantly lesser population was found on NIBGE-2 and higher on AA-703 followed by

CIM-496 during both 2011 and 2012. Furthermore, pesticide applications significantly reduced A. devastans numbers as compared to untreated control on all Bt and non-transgenic varieties, and interaction of varieties and pesticide regime was also found to be significant during both the years (Table 1; Fig. 1-4). During 2011, A. devastans reached at ETL (1 jassid leaf-1) on 16th June in untreated and treated plots of all the tested varieties with subsequent fluctuation through time. In untreated plots, A. devastans buildup was highest on AA-703 as compared to other varieties, on this variety first peak of A. devastans was observed on 16th

June and second on 21st July (Fig. 1 and 2). During 2012, A. devastans density was lower as compared to 2011 and fluctuated among the treatments over time. Amrasca devastans population as a whole reached at its peak on 2nd July in untreated plots of all tested varieties with comparatively higher density on AA-703 (Fig. 3 and 4). In ETL treated plots, all the varieties received first spray application untill 25th June except NIBGE-2, on which A. devastans reached or crossed ETL level on 28th July due to slower population buildup.

Population of A. devastans crossed ETL four and three times on NIBGE-2 variety during

2011 and 2012, respectively. In other transgenic varieties due to greater development of A. devastans, ETL of the pest was crossed 4-7 times (Fig. 1 and 3). However, non-transgenic varieties did follow identical pattern for ETL during both the years (Fig. 2 and 4).

Varieties, pesticides and seasons in alone or their interaction significantly affected abundance of A. devastans (Table 4).

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Amrasca devastans

Number of Number

Sampling dates Fig. 1 Seasonal prevalence of Amrasca devastans per leaf per sample date on transgenic varieties A) AA-802, B) NIBGE-3701, C) NIBGE-2, D) AA-703 in treated, ETL and untreated control treatment plots during 2011. Arrows above each graph show timing of pesticide application in economic threshold level (ETL= 1 jassid/leaf) treatment

Amrasca devastans

Number of Number

Sampling dates

Fig. 2 Seasonal prevalence of Amrasca devastans per leaf per sample date on non- transgenic varieties A) CIM-496, B) CIM-499, C) CIM-446, D) CRIS-134 in treated, ETL and untreated control treatment plots during 2011. Arrows above each graph show timing of pesticide application in economic threshold level (ETL= 1 jassid/leaf) treatment

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Amrasca devastans

Number of Number

Sampling dates

Fig. 3 Seasonal prevalence of Amrasca devastans per leaf per sample date on transgenic varieties A) AA-802, B) NIBGE-3701, C) NIBGE-2, D) AA-703 in treated, ETL and untreated control treatment plots during 2012. Arrows above each graph show timing of pesticide application in economic threshold level (ETL= 1 jassid/leaf) treatment

Amrasca devastans

Number of Number

Sampling dates

Fig. 4 Seasonal prevalence of Amrasca devastans per leaf per sample date on non- transgenic varieties A) CIM-496, B) CIM-499, C) CIM-446, D) CRIS-134 in treated, ETL and untreated control treatment plots during 2012. Arrows above each graph show timing of pesticide application in economic threshold level (ETL= 1 jassid/leaf) treatment

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Table 1. Interaction effect of varieties and pesticide application on seasonal mean number of Amrasca devastans per leaf Varieties 2011 2012 UP¥ EPф BP§ Mean UP¥ EPф BP§ Mean AA-802 2.70±0.07 0.89±0.01 0.18±0.02 1.26±0.40 0.92±0.02 0.56±0.01 0.07±0.01 0.52±0.13 NIBGE-3701 2.79±0.07 0.92±0.01 0.19±0.01 1.30±0.41 1.01±0.06 0.57±0.01 0.08±0.01 0.55±0.14 NIBGE-2 1.99±0.07 0.80±0.01 0.15±0.01 0.98±0.42 0.53±0.02 0.23±0.02 0.05±0.01 0.27±0.05 AA-703 3.52±0.05 1.28±0.01 0.26±0.01 1.69±0.51 1.76±0.06 0.86±0.01 0.23±0.01 0.95±0.24 CRIS134 2.84±0.07 0.94±0.01 0.20±0.01 1.33±0.44 1.11±0.09 0.58±0.01 0.09±0.01 0.59±0.16 CIM-446 3.00±0.07 1.00±0.01 0.21±0.01 1.40±0.27 1.27±0.04 0.69±0.01 0.13±0.01 0.70±0.17 CIM-496 3.10±0.07 1.02±0.02 0.22±0.01 1.45±0.45 1.39±0.07 0.72±0.02 0.15±0.01 0.75±0.19 CIM-499 3.46±0.07 1.20±0.01 0.24±0.02 1.63±0.51 1.55±0.07 0.80±0.03 0.20±0.02 0.85±0.20 Mean 2.93±0.10 1.01±0.03 0.21±0.01 1.19±0.08 0.63±0.04 0.13±0.01

F prob (P) Pesticides < 0.001 < 0.001 Varieties < 0.001 < 0.001 Pesticides × Varieties < 0.001 < 0.001 Tukey’s HSD value Pesticides (df 2,4) 0.08 0.05 Varieties (df 7,42) 0.08 0.07 Pesticides × Varieties (df 14,42) 0.21 0.17 ¥ UP = untreated no spray applied ф EP = spray at economic threshold level § BP = biweekly spray after A. devastans appearance

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6.3.2 Plant traits and their correlation with Amrasca devastans abundance

Amrasca devastans population had negative and significant correlation with hair density, hair length and thickness of leaf lamina, midrib and vein. Its correlation with plant height was also found to be negative and significant. A. devastans population positively and significantly correlated with length of leaf midrib and vein, leaf moisture contents, chlorophyll contents and leaf area. In the present study, number of leaves did not display any significant correlation with A. devastans population (Table 3). However, all the tested traits varied significantly among the transgenic and non-transgenic varieties (Table 2).

6.3.3 Varieties and pesticide integration impact on predator’s population

Varieties did not influence the population of predators i.e. Orius spp., Geocoris spp.,

Chrysoperla carnea, Coccinellid spp. and spiders, and interactions of varieties and pesticides were also non-significant in both the seasons. However, pesticide impact on all the predators was highly significant (Table 4).

More numbers of Orius spp., C. carnea, Coccinellid spp. and spiders were observed in untreated control followed by spray at ETL treatments as compared to biweekly sprayed plots during 2011 and 2012. However, Geocoris spp. was not affected significantly by pesticide treatments i.e. either at ETL or at biweekly spray. Overall Geocoris spp. and Coccinellid spp. population were very low during both the seasons as compared to other predators (Table 5).

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Table 2. Comparison of plant traits in different transgenic and non-transgenic cotton varieties Plant Varieties P F 7,23 traits AA- NIBGE- NIBGE- AA- CRIS- CIM- CIM- CIM- value 802 3701 2 703 134 446 496 499 Leaf hair density Lamina 677.0b 660.0b 718.0a 304.3f 573.3c 558.2c 507.8d 413.3e <0.001 826.9 (cm-2) Midrib 250.2b 235.3bc 285.1a 120.3f 215.1cd 190.2d 189.4de 160.3e <0.001 79.7 (cm-1) Vein 225.0b 214.0b 246.0a 110.0e 193.8c 154.5d 144.7d 120.2e <0.001 301.7 (cm-1)

Leaf hair length Lamina 764.9b 710.5 c 853.2a 338.3f 706.1c 578.1d 573.7d 544.3 e <0.001 846.8 (mμ) Midrib 764.9b 720.8 c 809.1a 323.6f 706.1c 603.1d 559.0 e 529.6 e <0.001 394.9 (mμ) Vein 357.5a 331.0b 367.8a 279.5e 308.9c 301.6cd 294.2cde 286.9de <0.001 79.7 (mμ)

Leaf thickness Lamina 0.40ab 0.36bc 0.45a 0.29c 0.35bc 0.34bc 0.33bc 0.31c <0.001 9.9 (mμ) Midrib 1.97ab 1.97ab 2.05a 1.42b 1.93ab 1.75ab 1.63ab 1.58ab 0.016 3.8 (mμ) Vein 1.33ab 1.31ab 1.42a 0.96c 1.30b 1.29b 1.26b 1.27b <0.001 35.4 (mμ)

Length 10.4e 10.5e 8.1f 14.3a 11.2d 11.5d 12.6c 13.5b <0.001 427.3 of leaf midrib (cm)

Length 6.11e 6.61d 5.97e 8.37a 6.67d 7.6c 8.02b 8.32a <0.001 277.1 of leaf vein (cm)

Moisture 81.4cd 82.1c 81.1d 84.4a 82.0cd 83.3ab 83.5ab 84.1ab <0.001 35.7 contents (%)

Chlorophyll 50.9cd 51.2cd 49.5d 55.8a 52.1c 52.7bc 53.1bc 54.8ab <0.001 22.8 contents (SPAD)

Leaf 70.7f 85.3e 88.0e 175.7a 99.3d 109.0c 153.7b 157.3b <0.001 898.2 area (cm2)

Number 97.5e 160.5b 130.5c 259.5a 122.0cd 165.0b 107.0de 133.0c <0.001 285.5 of leaves

Plant 110.0a 92.0b 111.0a 78.7c 82.0bc 91.3bc 116.0a 83.0bc <0.001 33.5 height (cm) Means with in a row sharing same letter are not significantly different in each year (Tukey’s HSD test, P < 0.05)

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Table 3. Correlation coefficient of Amrasca devastans per leaf and plant traits of different transgenic and non-transgenic varieties of cotton Plant traits Correlation P value Covariance Standard coefficient error Leaf hair density Lamina (cm-2) -0.98 <0.001 -44.93 27.49 Midrib (cm-1) -0.98 <0.001 -16.99 9.99 Vein (cm-1) -0.96 <0.001 -16.15 10.32 Leaf hair length Lamina (mμ) -0.91 <0.001 -45.81 31.20 Midrib (mμ) -0.89 <0.001 -47.80 30.38 Vein (mμ) -0.64 <0.001 -9.68 6.63 Leaf thickness Lamina (mμ) -0.91 <0.001 -0.02 0.01 Midrib (mμ) -0.65 <0.001 -0.07 0.03 Vein (mμ) -0.64 <0.001 -0.04 0.06

Length of leaf midrib (cm) 0.98 <0.001 0.63 0.39

Length of leaf vein (cm) 0.96 <0.001 0.31 0.19

Moisture contents (%) 0.91 <0.001 0.40 0.44

Chlorophyll contents (SPAD) 0.65 <0.001 0.69 0.44

Leaf area (cm2) 0.64 <0.001 11.84 7.67

Number of leaves 0.37 0.06 9.67 10.06

Plant height -0.49 0.02 -2.85 3.11

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Table 4. Combined analysis of influence of year, varieties and pesticide regimes on Amrasca devastans (per leaf), predators (per 5plants) and seed cotton yield (kg ha-1) Explanatory Df Amrasca Predators Seed cotton variables devastans Orius Geocoris Coccinellid Chrysoperla Spiders yield spp. spp. spp. carnea F P F P F P F P F P F P F P Value Value Value value value value value value value value value value value value Season 1,2 2280.38 <0.001 4.54 0.036 1.48 0.226 3.23 0.076 242.76 <0.001 716.48 <0.001 37.04 0.026 Pesticides 2,8 10220.30 <0.001 278.9 <0.001 121.4 <0.001 161.3 <0.001 2566.5 <0.001 2123.2 <0.001 3286.9 <0.001 Season × Pesticides 2,8 2172.32 <0.001 2.74 0.070 0.07 0.929 1.26 0.289 6.44 0.002 9.97 <0.001 35.08 <0.001 Varieties 7,84 308.52 <0.001 1.89 0.080 1.34 0.239 0.65 0.714 0.91 0.504 1.30 0.261 102.22 <0.001 Season ×Varieties 7,84 1.96 0.070 0.13 0.996 0.01 1.000 0.01 1.000 0.34 0.935 0.91 0.502 1.06 0.399 Pesticides ×Varieties 14,84 84.24 <0.001 2.74 0.211 0.52 0.916 0.45 0.953 0.51 0.920 0.36 0.981 59.08 <0.001 Season × Pesticides × 14,84 6.68 <0.001 0.09 1.000 1.61 0.089 0.01 1.000 0.22 0.999 0.65 0.815 1.50 0.128 Varieties

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Table 5. Influence of pesticide regimes on seasonal mean abundance of predators per 5 plants of cotton during study period (Pooled across varieties) Predatory arthropods 2011 2012 UP¥ EPф BP§ F P UP¥ EPф BP§ F P Value Value Value value Orius spp. 3.17 a 0.80 b 0.19 c 143.10 < 0.001 2.64a 0.70 b 0.19 c 179.61 < 0.001 Geocoris spp. 1.39 a 0.32 b 0.23 b 43.30 < 0.001 1.33a 0.23 b 0.13 b 105.68 < 0.001 Coccinellid spp. 1.14 a 0.28 b 0.07 c 114.89 < 0.001 0.95a 0.23 b 0.05 c 110.52 < 0.001 Chrysoperla carnea 8.92 a 6.09 b 2.08 c 1685.23 < 0.001 7.48a 5.26 b 0.67c 1444.03 < 0.001 Spiders 6.93 a 5.07 b 1.70 c 1435.42 < 0.001 5.02a 3.26 b 0.41c 1021.80 < 0.001 ¥ UP = untreated no spray applied ф EP = spray at economic threshold level § BP = biweekly spray after A. devastans appearance Means with in a row sharing same letter are not significantly different in each year (Tukey’s HSD test, P < 0.05)

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6.3.4 Varieties and pesticide integration impact on crop performance

6.3.4.1 Fiber characteristics of cotton

Cotton fiber characteristics comprising of GOT (%), micronaire (μg inch-1), staple length

(mm) and fiber strength (tppsi) differed significantly among varieties and were improved significantly by biweekly spray and ETL spray treatments as compared to untreated control and all the interaction of varieties and spray regimes were significant (Table 6 and 7).

Moreover, all the fiber characteristics were negatively correlated with A. devastans infestation (GOT: rs = -0.966; micronaire: rs = -0.937; staple length: rs = -0.922; fiber strength: rs = -0.970). When fiber characteristics values from untreated control compared with that of treated control, then maximum percent reduction in GOT (F7,14 = 100.27, P <

0.001), micronaire (F7,14 = 91.75, P < 0.001), staple length (F7,14 = 300.95, P < 0.001) and fiber strength (F7,14 = 98.46, P < 0.001) were found in AA-703 followed by CIM-499, while less percent reduction was observed in NIBGE-2 followed by AA-802 (Fig. 5).

6.3.4.2 Seed cotton yield

Seed cotton yield kg ha-1 differed significantly among varieties; the highest yield was obtained from NIBGE-2 variety during 2011 and 2012. Both biweekly spray and economic threshold spray did not differ significantly from each other in terms of increasing seed cotton yield but differed significantly from untreated control during 2011 and 2012 (Table 8). F- statistics on the combined effect of seasons, pesticide regimes and cotton varieties indicated significant effect of season, varieties and pesticides on seed cotton yield moreover, season × pesticides and varieties × pesticides interactions were found to be significant (Table 4).

Correlation of yield with A. devastans infestation found to be strongly negative (2011: rs = -

0.929; 2012: rs = -0.913). Therefore, when varietal yield from untreated control was compared with that of treated control, maximum yield reduction was found in AA-703 during both 2011 (F7,14 = 291.32, P < 0.001) and 2012 (F7,14 = 211.88, P < 0.001) (Fig. 6).

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Table 6. Interaction effect of varieties and pesticide application on GOT (%) and micronaire (μg inch-1) Varieties GOT Micronaire UP¥ EPф BP§ Mean UP¥ EPф BP§ Mean AA-802 30.00±0.71 41.35±0.95 41.50±1.06 37.62±2.06 3.80±0.04 4.25±0.04 4.30±0.04 4.12±0.62 NIBGE-3701 27.50±1.06 40.70±1.20 41.50±0.71 36.57±2.45 3.90±0.04 4.45±0.09 4.50±0.14 4.28±0.84 NIBGE-2 31.50±0.35 41.50±1.06 41.50±0.71 38.17±1.80 3.90±0.02 4.25±0.04 4.25±0.04 4.13±1.37 AA-703 17.50±1.06 40.90±1.34 41.00±0.71 33.13±4.17 3.05±0.08 3.99±0.06 4.00±0.07 3.68±1.24 CRIS134 24.50±1.06 38.00±0.71 38.50±0.71 33.67±2.46 3.55±0.07 4.15±0.04 4.20±0.07 3.97±0.91 CIM-446 22.00±0.71 37.75±0.53 38.00±0.71 32.58±2.82 3.42±0.07 4.07±0.07 4.15±0.04 3.88±0.91 CIM-496 21.50±0.06 38.40±0.99 38.50±0.35 32.80±2.93 3.40±0.02 4.10±0.07 4.20±0.14 3.90±0.96 CIM-499 17.00±0.71 37.25±0.88 37.50±0.35 30.58±3.61 3.40±0.03 4.30±0.07 4.40±0.07 4.03±1.04 Mean 23.94±1.10 39.48±0.43 39.75±0.39 3.55±0.06 4.20±0.03 4.25±0.04

F prob (P) Pesticides < 0.001 < 0.001 Varieties < 0.001 < 0.001 Pesticides × Varieties < 0.001 < 0.001 Tukey’s HSD value Pesticides (df 2,4) 0.61 0.17 Varieties (df 7,42) 0.53 0.12 Pesticides × Varieties (df 14,42) 1.51 0.39 ¥ UP = untreated no spray applied ф EP = spray at economic threshold level § BP = biweekly spray after A. devastans appearance

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Table 7. Interaction effect of varieties and pesticide application on staple length (mm) and fiber strength (tppsi) Varieties Staple length Fiber strength UP¥ EPф BP§ Mean UP¥ EPф BP§ Mean AA-802 26.20±0.14 29.60±0.42 29.60±0.42 28.47±0.09 66.25±0.53 103.10±0.39 103.60±0.78 90.98±6.56 NIBGE-3701 24.60±0.28 29.10±0.07 29.50±0.35 27.73±0.11 62.50±0.71 102.60±0.24 102.98±0.37 89.36±7.13 NIBGE-2 27.50±0.35 30.25±0.18 30.25±0.18 29.33±0.21 68.65±0.46 106.30±0.44 106.60±0.49 93.85±9.81 AA-703 22.50±0.35 29.30±0.28 29.65±0.46 27.15±0.17 51.00±0.71 100.60±0.37 101.00±0.71 84.20±8.81 CRIS134 24.25±0.57 29.20±0.35 29.40±0.28 27.62±0.11 59.05±0.74 97.95±0.76 98.00±0.71 85.00±6.89 CIM-446 23.45±0.39 28.25±0.18 28.80±0.21 26.83±0.13 57.70±0.85 98.40±0.25 98.80±0.49 84.97±7.23 CIM-496 23.00±0.21 28.35±0.25 28.45±0.18 26.60±0.14 56.80±0.98 99.10±0.60 99.60±0.56 85.17±7.53 CIM-499 22.80±0.21 28.35±0.25 28.90±0.28 26.68±0.17 54.00±0.71 97.55±0.80 98.00±0.37 83.18±7.74 Mean 24.29±0.36 29.05±0.15 29.32±0.14 59.49±1.21 100.76±0.63 101.07±0.63

F prob (P) Pesticides < 0.001 < 0.001 Varieties < 0.001 < 0.001 Pesticides × Varieties < 0.001 < 0.001 Tukey’s HSD value Pesticides (df 2,4) 0.97 0.74 Varieties (df 7,42) 0.53 1.25 Pesticides × Varieties (df 14,42) 2.05 2.78 ¥ UP = untreated no spray applied ф EP = spray at economic threshold level § BP = biweekly spray after A. devastans appearance

145

Fig. 5 Percentage reduction GOT, micronaire, staple length and fiber strength in untreated transgenic and non-transgenic cotton varieties. Bars following similar letters not differ significantly at P<0.05 by Tukey’s HSD test

146

Table 8. Interaction effect of varieties and pesticide application on seed cotton yield (kg ha-1) Varieties 2011 2012 UP¥ EPф BP§ Mean UP¥ EPф BP§ Mean AA-802 1734±17 2998±85 3037±42 2590±228 2191±29 3049±37 3094±14 2778±156 NIBGE-3701 1649±21 2985±110 3030±56 2555±242 2040±39 3030±17 3077±16 2716±180 NIBGE-2 1976±269 3039±106 3085±51 2700±392 2550±20 3101±19 3145±16 2932±180 AA-703 850±14 3000±93 3054±29 2301±386 1105±14 3090±9 3128±7 2441±354 CRIS134 1479±269 2866±79 2911±34 2419±251 1870±14 2953±6 2992±16 2605±357 CIM-446 1326±21 2822±42 2870±19 2339±269 1564±21 2888±20 2924±18 2459±238 CIM-496 1241±14 2831±78 2880±31 2317±287 1460±22 2930±111 2960±77 2450±265 CIM-499 935±14 2840±40 2914±43 2230±346 1275±93 2937±103 2975±60 2396±299 Mean 1399±81 2923±27 2973±20 1757±99 2997±21 3037±19

F pob (P) Pesticides < 0.001 < 0.001 Varieties < 0.001 < 0.001 Pesticides × Varieties < 0.001 < 0.001 Tukey’s HSD value Pesticides (df 2,4) 122.73 72.97 Varieties (df 7,42) 131.36 90.78 Pesticides × Varieties (df 14,42) 337.34 220.00 ¥ UP = untreated no spray applied ф EP = spray at economic threshold level § BP = biweekly spray after A. devastans appearance

147

80 A 2011 2012 B a 60 C b C c DE D c E d 40 de

F e reduction(%) f

eld eld 20 Yi

Varieties

Fig. 6 Percentage yield (kg ha-1) reduction in untreated transgenic and non-transgenic cotton varieties. Bars with similar capital letters and small letters not differ significantly during 2011 and 2012, respectively at P<0.05 by Tukey’s HSD test

148

6.4 DISCUSSION

We found that number of A. devastans varied by variety and both the most preferred ones, i.e., AA-703 and comparatively resistant i.e., NIBGE-2 were transgenic varieties. With respect to plant traits, NIBGE-2 was found to be densely hairy with greater hair length, more leaf thickness and maximal plant height. These traits were found to be negatively correlated with A. devastans population, and hence considered as most important factors imparting resistance to the A. devastans (Bashir et al., 2001; Aheer et al., 2006; Ashfaq et al., 2010;

Iqbal et al., 2011). Thus, no single plant trait is responsible for resistance, combination of various plant traits determine resistance (Eittipibool et al., 2001). Our results also confirmed that varieties having greater leaf area, higher moisture contents (Iqbal et al., 2011), maximal length of leaf vein (Eittipibool et al., 2001) and increased chlorophyll contents (Shyoram et al., 2013) were susceptible to A. devastans. Pesticides application depressed A. devastans on all transgenic and non-transgenic varieties during both the cropping seasons and number of pesticide applications varied by variety. Maximum population reduction was found in biweekly sprays treatment followed by spray at economic threshold level treatment as compared to untreated control.

With respect to predatory arthropods, populations of Orius spp., C. carnea and spiders were higher during 2011 as compared to that in 2012 that might be in response to increase A. devastans during that year. Various studies reported that population of natural enemies fluctuated in response to insect pest population densities (Fuentes-Contreras et al., 1998;

Rutledge et al., 2003; Nargis et al., 2013). An increase in spiders during 1999 in response to increased leafhopper density was recorded by Men et al., (2004). Our results revealed that populations of predatory arthropods did not differ among varieties but significantly affected by pesticide applications on all transgenic and non-transgenic varieties during both cropping seasons. Predatory Geocoris spp. tended to be very sensitive to most pesticides (Boyd and

149

Boethel 1998). In the present study, both of the pesticide treatments; either biweekly spray treatment or spray at economic threshold treatment reduced the Geocoris spp. population as compared to untreated control. However, biweekly sprays more adversely affected the populations of Orius spp., Coccinellid spp., C. carnea and spiders as compared to other pesticide regimes. A number of studies showed the benefits of spraying at economic threshold level as compared to biweekly sprays in terms of reducing spray cost to manage pest with less hazard to natural enemies (Maltais et al., 1998; Ahmad 1999; Naranjo and

Ellsworth 2009). We found that at ETL treatment, NIBGE-2 required 4 sprays during 2011 and 3 sprays during 2012, while AA-703 required 7 and 5 spray applications during 2011 and

2012, respectively. It affirms that by using resistant varieties to manage A. devastans number of pesticide applications can be reduced that will ultimately reduce danger to natural enemies.

In the present study, reduction of seed cotton yield and fiber characteristics also varied among the varieties in response to A. devastans infestation. Lower reduction percentages were observed in NIBGE-2 that was found to be relatively resistant to A. devastans attack and higher in susceptible AA-703 variety as compared to other varieties. Pesticide applications increased the seed cotton yield and improved fiber characteristics by lowering A. devastans infestation. The influence of insecticidal applications on yield and fiber traits of cotton was also reported by Weaver et al. (1979). We found non-significant difference between two pesticide regimes (biweekly spray and spray at economic threshold levels) in terms of increasing seed cotton yield and improving fiber characteristics i.e. ginning out turn (GOT), micronaire, staple length and fiber strength, while both pesticide treatments were significantly different from untreated control.

In conclusion, our results revealed that growing the transgenic Bt varieties having morpho- physiacal traits that also confer resistance to non-target insect pests will exploit full potential of transgenic plants for sustainable crop production. We also found that the use of host plant

150 resistance alone may not reduce the yield loss substantially; it should be complemented with pesticide application at economic threshold level. This study suggests that integration of resistant transgenic cotton varieties with pesticide applications at economic threshold level to manage A. devastans, will reduce the number and cost of sprays, and consequently increase seed cotton yield with improving fiber characteristics.

151

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CHAPTER-7

Effect of prey resource on the fitness of the predator Chrysoperla

carnea (Neuroptera: Chrysopidae)

This chapter has been published as;

Saeed, R. and Razaq, M., 2015. Effect of prey resource on the fitness of the predator

Chrysoperla carnea (Neuroptera: Chrysopidae). Pakistan J. Zool., 47: 103-109. (ISE Impact

Factor 0.404)

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7.1 INTRODUCTION

Introduction and release of predatory insects accounts for up to one third of the successful biocontrol programs in the world. Among the predacious insects, the aphid lion, Chrysoperla carnea (Stephens) (Chrysopidae: Neuroptera) is one of the widely distributed, and most frequently used species (Athhan et al., 2004). It is a polyphagous carnivore present in agricultural crops, such as cotton (Mallah et al., 2001), brassicaceous oilseeds (Aslam and

Razaq, 2007), and okra (Saeed et al., 2015). C. carnea adults feed on pollen, nectar and honeydew, while larvae are voracious predators of a wide variety of plant pests such as aphids, whiteflies, leaf miners, psyllids, thrips and caterpillars (Youksel and Gocmen, 1992;

Syed et al., 2005; Mansoor et al., 2013). This predator’s adaptation to diverse environments, broad range of prey, high ability to find prey, and high resistance to commonly applied insecticides make it a valuable biological control agent (Sablon et al., 2013). C. carnea has high reproductive rates, short developmental times, is easy to mass rear, and can be successfully used in biocontrol programs in areas where insecticides are still a key pest management tool like in Pakistan (Mansoor et al., 2013).

The cotton leaf hopper, Amrasca devastans (Dist.) (Hemiptera: Cicadellidae) is a key pest of cotton in the Indo-Pak subcontinent (Ahmad, 1999). Besides cotton it also damages malvaceous and solanaceous crops. Both nymphs and adults of A. devastans suck the sap and inject phytotoxic saliva into the plant tissues resulting in crinkled leaves and shedding of squares and bolls; severe infestation may cause complete crop failure (Huque et al., 1994). Its ability to survive on a wide range of alternative hosts, short life cycle, destruction of biological control agents due to insecticides in its host crops, and development of resistance to chemicals made the management of this pest a formidable problem (Ahmad et al., 1999;

Akbar et al., 2012; Saeed et al., 2015). Due to harmful effects of pesticides, biological control should be considered as recourse in integrated pest management (IPM) for managing A.

158 devastans. Previous studies gave evidence that C. carnea use A. devastans as prey (Syed et al., 2005). Because prey quality including developmental stages can affect the survival, longevity and fecundity, and thus fitness of predators (Godin and McDonough, 2002; Saeed et al., 2010; Jokar and Zarabi, 2012), the impact of A. devastans as prey on the biology of C. carnea should be evaluated before making inundative releases in the field. In this study we report for the first time the effect of A. devastans as prey on the development and reproduction of C. carnea, and we also evaluated the intrinsic (rm) and finite (λ) rates of population increase.

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7.2 MATERIALS AND METHODS

7.2.1 Insect rearing

A culture of C. carnea was obtained from the biological control laboratory of the Central

Cotton Research Institute (CCRI) (Multan, Pakistan). The predator was reared using the methods of Sattar (2010). A. devastans was reared on cotton plants, G. hirsutum L., in cages with dimensions of 45 × 30 × 12 cm. Stock cultures of both prey and predator were maintained at 25 ± 2oC and 65 ± 5% R.H. and photoperiod of 16:8 L:D. Voucher specimens for the both the predator and prey have been deposited in the laboratory of Entomology

Section CCRI, Multan (Pakistan).

7.2.2 Predation rate

Fixed numbers of various developmental stages of prey A. devastans were offered to C. carnea instars in petri dishes (5cm diameter). Treatment diets consisted of all nymphal stages i.e. 1st instar (N1) to 5th instar (N5) and the adult stages of A. devastans; each treatment had six replicates. Each C. carnea first instar (L1) received 20 N1, 20 N2, 20 N3, 15 N4, 10 N5 and 10 adult nymphs; each second instar (L2) received 50 N1, 50 N2, 50 N3, 30 N4, 20 N5, and 15 adult nymphs; and each third instar (L3) received, 150 N1, 150 N2, 150 N3, 50 N4, 30

N5 and 20 adult nymphs. Each petridish had a cotton leaf disc (5cm) with moistened filter paper. At the end of each 24 hour period, the numbers of prey remaining were recorded.

7.2.3 Survival and development of immature Chrysoperla carnea

To determine effect of A. devastans on developmental time, C. carnea was first reared for a generation on A. devastans. The purpose was to eliminate the effect of previous host because our culture originated from a culture that had been reared on Sitotroga cerealella (Olivier).

Subsequent treatment diets were N1, N2, N3, N4, N5 and adult life stages of A. devastans. A fixed quantity (n= 30 per replicate per stage) of each diet was provided to individual larvae in petri dishes (see section 2.2); there were n= 25 replicate larvae per treatment. A neonate C.

160 carnea larva of F2 generation was released into each petridish and the larval diet was replaced daily. We recorded survival and the developmental period for each instar and also the pupae.

7.2.4 Chrysoperla carnea reproduction

Five pairs of adults that had been reared on each of the above treatment diets were placed in individual glass jars (16 X 23 cm) with napiliner strips for egg laying; they were fed honey solution. Numbers of eggs laid in each jar were noted daily and transferred to separate petri dishes to determine the rate of hatching. Hatching of eggs took place usually in 3-4 days. Egg volume was calculated using the formula previously employed by Ito (1997).

4 푙 ℎ 2 Volume = π ( ) × ( ) 3 2 2

Where l and h are egg length and width, respectively.

7.2.5 Growth Rate

Twenty larvae of first instar were randomly taken from colonies fed on each treatment diet

(see 2.3) and weighed, using an electric balance. These larvae were fed with their respective prey life stages until pupation, and then they were weighed again.

We used the following formula (Radford, 1967) to calculate mean relative growth rate

(MRGR):

MRGR= [In W2 (mg) − In W1(mg)]/푇, where W1 is initial larva weight, W2 is pupal weight and T is Time in days, from first instar to the pupae

7.2.6 Intrinsic and finite rates of population increase and doubling time

The net replacement rate (R0) was calculated by following formula previously employed by

Sayyed and Wright (2001) and Saeed et al. (2010):

R0= (n × le × la)/2 where n is mean number of eggs per female, Ie is fraction of fertile eggs, Ia is fraction of eclosing adults and 2 is sex ratio coefficient.

161

The intrinsic rate of population increase (rm) was then calculated by using net replacement rate (Birch, 1948): rm= (In Ro)/T where In is natural logarithm of a number, Ro is net replacement rate and T is total developmental time (egg to adult eclosion).

Further, finite rate of population increase (λ) and doubling time (DT) were calculated by using intrinsic rate of increase (Jokar and Zarabi, 2012).

λ= erm where e is exponent of a given number and rm is intrinsic rate of population increase.

DT= (In 2)/rm where In is natural logarithm of a number and rm is intrinsic rate of population increase.

7.2.7 Statistical analysis

The data were analysed using GenStat statistical package, version 15 (VSN International,

Hemel Hempstead, UK). We compared means of variables with Least Significant Difference

(LSD) test (P < 0.05).

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7.3 RESULTS

7.3.1 Predatory potential

Chrysoperla carnea showed a significant response to the different developmental stages of prey (A. devastans) (F = 6.18; df = 5; P = < 0.001). Predation on adult A. devastans was lowest compared to other stages of prey. However, predation of N2 was the highest, followed by N3 and N1. There were significant differences among the predatory potential or consumption rate of C. carnea larval instars. Third instar larvae (L3) of C. carnea consumed the largest number of prey in all life stages when compared to L1 and L2 larvae of C. carnea

(Table 1).

7.3.2 Development and survival of immature stages

The developmental period of C. carnea from egg to pupation was significantly affected by feeding on different stages of A. devastans (F = 96.20; df = 5; P = < 0.001). The larvae of C. carnea fed on N3 prey developed faster (first instar to adult with total duration of 16.72 days), had greater pupal body weight (11.62 mg) and a higher survival rate (96%) than those on other life stages. All of these variables were negatively affected when larvae were reared on adult prey (Table 2).

7.3.3 Chrysoperla carnea reproduction

Females of C. carnea whose larvae were fed on N3 prey had longer periods of oviposition and shorter pre-oviposition and post oviposition periods (Table 3). However, shorter oviposition (5.0 days) with longer pre-oviposition (8.8 days) and post oviposition (7.8 days) periods were observed from those fed on adult prey. Incubation period of eggs was less whereas mean numbers of eggs (322), their viability and volume laid by females emerged from larvae fed on N3 prey were greater than those reared on other life stages (Table 3).

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Table1. Predatory potential of Chrysoperla carnea immature stages on various life stages of Amrasca devastans C. carnea Prey stages (mean number consumed)+ larvae§ N1 N2 N3 N4 N5 Adult L1 11.00 c 16.17 c 13.67 c 6.67 c 3.00 c 2.17 c L2 93.00 b 99.33 b 95.00 b 41.67 b 21.33 b 14.33 b L3 515.00 a 581.67 a 551.00 a 132.00 a 64.00 a 36.00 a

LSD 5% 10.03 32.49 25.25 8.91 7.93 6.06 P value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 Means in columns followed by the same letter are not significantly different by LSD <0.05 § L1, L2 and L3 represents 1st instar, 2nd instar and third instar larvae of predator C. carnea + NI, N2, N3, N4 and N5 represent 1st instar, 2nd instar, 3rd instar, 4th instar and 5th instar nymph of prey A. devastans

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Table 2. Effect of Amrasca devastans life stages on different life traits (± SE) of Chrysoperla carnea Prey stages+ Developmental period (Days) of Chrysoperla carnea Pupal weight First larval Second larval Third larval Total larval Pupal period Total % Survival instar instar Instar period developmental (mg) period N1 3.32 ± 0.10 a 5.08 ± 0.12 c 7.32 ± 0.13 ab 15.72 ± 0.20 b 7.28 ± 0.21 c 23.00 ± 0.26 c 7.60 ± 0.51 d 78 ± 0.50 c N2 2.32 ± 0.10 b 4.08 ± 0.11 d 5.60 ± 0.14 d 12.00 ± 0.25 d 6.16 ± 0.25 d 18.16 ± 0.25 e 10.00 ± 0.23 b 90 ± 0.76 b N3 1.84 ± 0.08 c 3.88 ± 0.07 d 5.40 ± 0.03 d 11.12 ± 0.12 e 5.60 ± 0.12 e 16.72 ± 0.24 f 11.62 ± 0.20 a 96 ± 0.57 a N4 3.32 ± 0.14 a 5.20 ± 0.12 c 6.48 ± 0.16 c 15.00 ± 0.31 c 6.96 ± 0.31 c 21.96 ± 0.36 d 8.50 ± 0.29 c 82 ± 0.50 c N5 3.44 ± 0.15 a 5.80 ± 0.20 b 7.00 ± 0.19 b 16.24 ± 0.35 b 8.72 ± 0.35 b 24.96 ± 0.36 b 6.00 ± 0.25 e 70 ± 0.58 d Adult 3.60 ± 0.14 a 6.28 ± 0.18 a 7.48 ± 0.20 a 17.36 ± 0.23 a 9.32 ± 0.23 a 26.68 ± 0.32 a 4.10 ± 0.03 f 62+ 0.29 e

LSD 5% 0.33 0.39 0.43 0.70 0.43 0.83 0.78 3.90 P value < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 + NI, N2, N3, N4 and N5 represent 1st instar, 2nd instar, 3rd instar, 4th instar and 5th instar nymph of prey A. devastans Means in columns followed by the same letter are not significantly different by LSD <0.05

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Table 3. Effect of Amrasca devastans life stages on reproductive traits (± SE) of Chrysoperla carnea Prey stages+ Reproductive traits of Chrysoperla carnea Pre Oviposition Oviposition period Post oviposition Incubation period Egg volume Fecundity % Viability period (Days) (Days) period (Days) (Days) (mm3) N1 5.00 ± 0.29 c 11.0 ± 0.50 c 5.67 ± 0.25 b 3.20 ± 0.08 c 0.16×10-4c 156 ± 0.29 d 70.0 ± 0.58 d N2 3.67 ± 0.25 d 17.3 ± 0.25 b 3.33 ± 0.10 c 2.48 ± 0.10 d 0.18×10-4b 280 ± 0.50 b 86.0 ± 0.50 b N3 2.20 ± 0.00 e 19.2 ± 0.67 a 1.60 ± 0.25 d 2.00 ± 0.02 e 0.20×10-4 a 322 ± 0.29 a 92.3 ± 0.25 a N4 4.20 ± 0.29 cd 16.8 ± 0.09 b 3.80 ± 0.10 c 3.04 ± 0.04 c 0.17×10-4c 207 ± 0.19 c 75.7 ± 0.51 c N5 6.67 ± 0.51 b 9.0 ± 0.29 d 5.67 ± 0.09 b 3.52 ± 0.13 b 0.15×10-4 d 117 ± 0.51 e 66.0 ± 1.00 e Adult 8.80 ± 0.09 a 5.0 ± 0.29 e 7.80 ± 0.25 a 3.96 ± 0.14 a 0.15×10-4 d 79 ± 0.25 f 53.0 ± 0.29 f

LSD 5% 1.08 0.88 1.05 0.27 0.008×10-4 1.89 1.92 P value < 0.001 < 0.001 < 0.001 < 0.001 <0.001 < 0.001 < 0.001 + NI, N2, N3, N4 and N5 represent 1st instar, 2nd instar, 3rd instar, 4th instar and 5th instar nymph of prey A. devastans Means in columns followed by the same letter are not significantly different by LSD <0.05

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7.3.4 Population growth traits

Net replacement rate or net reproductive and intrinsic rates of increase of C. carnea were lower when larvae were reared on adult A. devastans. The mean relative growth rate was higher for the larvae fed on N3 prey than those reared on other developmental stages. It was also observed that generation doubling time was highest for the population reared on adult prey (Table 4). We noted significant relationship between intrinsic rate of increase and mean relative growth rate (t = 573, df = 5, P < 0.01). Mean relative growth rate was positiviely

correlated with intrinsic rate of increase (rs = 0.99, df = 5, P < 0.01) and finite rate of increase

(rs = 0.98, df = 5, P < 0.01). While mean relative growth rate showed negative correlation

with generation doubling time (rs = -0.93, df = 5, P < 0.01).

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Table 4. Population growth traits of Chrysoperla carnea on various life stages of Amrasca devastans Prey stages+ Growth traits of Chrysoperla carnea Net replacement Mean relative Intrinsic rate Finite rate of Doubling time rate (R0 per growth rate of increase increase (λ) (DT) generation) (MRGR) (rm) N1 85.18 0.26 0.20 1.22 3.41 N2 216.73 0.34 0.29 1.34 2.34 N3 285.79 0.44 0.34 1.40 2.04 N4 129.04 0.28 0.22 1.25 3.12 N5 54.17 0.19 0.16 1.17 4.32 Adult 26.16 0.16 0.12 1.13 5.64 + NI, N2, N3, N4 and N5 represent 1st instar, 2nd instar, 3rd instar, 4th instar and 5th instar nymph of prey A. devastans

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7.4 DISCUSSION

Life history traits and feeding efficiencies of insects are considerably affected by host resource value or quality (Hagley and Barber, 1992; Uckan and Gulel, 2000; Sattar and Abro,

2009). In the present study, C. carnea response to prey quality varied significantly with maximum predation on N2 followed by N3 A. devastans. Low consumption of N4, N5 and adult prey stages might be due to the fact that they are very active and require more handling time as compared to other prey stages. Third instar larvae C. carnea have been reported to be more voracious against Bemisia tabaci, Aphis gossypii, A. devastans and Phenacoccus solenopsis than other larval instars of the predator (Solangi et al., 2013). In another study on predatory potential of C. carnea against mealy bug, P. solenopsis a lower number of adults were consumed compared to younger prey stages (Huang and Enkegaard, 2010).

In the present study, the consumption rate of L3 C. carnea was higher than that of L1 and L2; this may be due to their larger size and higher dietary requirements (Atthan et al., 2004;

Ulhaq et al., 2006; Sattar et al., 2007). Youksel and Gocmen (1992) also showed higher aphid consumption by L3 C. carnea than other stages.

Developmental times and reproductive rates in insects are indicators of the quality of larval diets (Saeed et al., 2010). Therefore, these parameters can be employed to determine suitability of prey stages in supporting predator life cycles. In the present study, the developmental stages of prey had a profound impact on developmental period of C. carnea.

Shortest larval and pupal period was found on N3 prey while longest on adult A. devastans indicating that larval food significantly affected the length of developmental period. This has been also recorded previously for C. carnea when reared on natural and artificial diets (Sattar et al., 2011). In addition to variations in development there were marked differences in survival of larvae fed on different stages of prey A. devastans. Survival rate was higher when the predator larvae fed on N3 prey than other life stages of prey.

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In the current study, third instar (N3) A. devastans was found to be better prey for C. carnea for several reasons. First, the developmental period was shorter compared with other developmental stages of A. devastans. Second, because the relationship between pupal weight and fecundity is well documented for insects (e.g., Barah and Sengupta, 1991; Blackmore and

Lord, 2000), it was not unexpected that the higher pupal weights in C. carnea reared on third instar (N3) A. devastans will result in higher rates of oviposition. Indeed, in the present study, greater adult longevity occurred when C. carnea larvae were reared on N3 A. devastans, and this response was associated with longer oviposition period and significantly higher number of eggs laid per female.

Given our results, host quality should be expected to influence population growth traits of C. carnea. Intrinsic or finite rates of population increase are key measures of population growth

(Varley and Gradwell, 1970). We recorded a positive correlation between intrinsic rate of increase and mean relative growth rate that reflects the potential of N3 nymphs of A. devastans to favour C. carnea populations. Net reproductive rate was the highest in C. carnea larvae that fed on N3, which is the measure of population growth potential. A faster developmental time may also reduce the generation time (Saeed et al., 2010). We found a negative correlation between mean relative growth rate and generation doubling time.

Therefore, based upon the developmental time and other life-history responses, we can arrange the six stages of A. devastans in ascending order of host suitability:

N3>N2>N4>N1>N5> Adult.

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174

CHAPTER-8

Evaluating spray regimes against cotton leafhopper, Amrasca

devastans (Dist.): its impact on natural enemies, yield and fiber

characteristics of transgenic Bt cotton

This chapter has been accepted as;

Saeed, R., Razaq, M., Rafiq, M. and Naveed, M., 2016. Evaluating spray regimes against cotton leafhopper, Amrasca devastans (Dist.): its impact on natural enemies, yield and fiber characteristics of transgenic Bt cotton. Pakistan J. Zool., In press. (ISE Impact Factor 0.404)

175

8.1 INTRODUCTION

Adoption and cultivation of genetically modified crops has become foremost that continues to grow rapidly worldwide. More than half of the worldwide cotton grown area is occupied by cotton containing Bacillus thuringiensis genes (known as Bt cotton) (Ali et al., 2010;

Naranjo, 2011). Since 2005, Bt cotton was introduced in the Pakistan to control insecticide resistant strains of lepidopteron pests, with expected consequences of insecticide use reduction (Sabir et al., 2011). The reduction of insecticides usage, increased other non-target pest populations that might had been suppressed by the insecticidal applications against targeted bollworms (Williams, 2006; Naranjo, 2011; Karar et al., 2013). In addition, transgenic Bt cotton may attract or enhance growth of some sucking pest populations in response to difference in variety as compared to non-transgenic conventional cotton resulting in increase of insecticidal applications. Hence, introducing transgenic varieties led to alteration in insecticidal regimes to manage non-target pests. These alterations in pesticide application regimes might affect the pest and predatory arthropod populations (Men et al.,

2004; Arshad et al., 2009).

The cotton leafhopper, Amrasca devastans (Dist.) [= Amrasca biguttula biguttula (Ishida)] is a principal insect pest of cotton inducing over 37% seed cotton losses. Farmers rely solely on chemical insecticides to manage this pest (Saeed et al., 2015). Insecticides have been applied on cotton without any gap since long. Monitoring of insecticide resistance occurrence is critical for designing insecticide resistance management strategy (Forrester et al., 1993).

Resistance in A. devastans to some pyrethroids has been reported in late 1990’s from cotton growing areas of Pakistan (Ahmad et al., 1999). However, resistance in Bemisia tabaci

(Genn.) to five neonicotinoids and two insect growth regulators (IGRs) have been reported in recent research (Basit et al., 2011).There is no published literature pertaining to insecticide resistance monitoring in A. devastans after 1999.

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In past, researchers documented efficacy and scheduling of various insecticides alone or in mixture to A. devastans on various crops (Razaq et al., 2005; Khattak et al., 2006; Shah et al., 2007; Asi et al., 2008; Awan and Saleem, 2012; Haq et al., 2012). But there is lack of research on efficacy of conventional insecticides in rotation with new chemistry insecticides against A. devastans and its impact on natural enemies on transgenic cotton. The objectives of the current two year field study were 1) to evaluate comparative efficacy of conventional and new classes of insecticides in different spray regimes against A. devastans and their impact on natural enemies and 2) specifically, to examine which regime improve yield and fiber characteristics of transgenic Bt cotton.

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8.2 MATERIALS AND METHODS

To evaluate efficacy of different insecticidal spray regimes against A. devastans transgenic Bt cotton (Bt-CIM.599) was planted on 20th May 2012 and 22nd May 2013. Plots were 10.67 m

× 5.34 m and separated by 1.52 m buffer zone. Plant to plant and row to row distance was

0.23 m and 0.76 m, respectively. In each year ten treatments (n= 3 replicates each) were arranged in randomized complete block design. These treatments were nine spray regimes

(including different combinations conventional and new classes of insecticides) and one untreated control (details of insecticides their combinations spray regimes given in table 1and table 2). In spray regimes insecticides were combined on the basis of mode of action. The study was conducted under semi-arid climatic conditions at the Central Cotton Research

Institute, Multan (30.120N and 71.280E) Pakistan; in a silt loam soil. All the standard cultural practices recommended for cotton growers were followed.

The experimental field was kept unsprayed initially, and A. devastans and their natural enemies were allowed to develop. A. devastans nymphs and adults were monitored twice a week, and spray was initiated as A. devastans population reached or crossed economic threshold level (ETL) of 1 jassid per leaf (Ahmad et al., 1985). Three consecutive sprays for each regime were applied at two week intervals starting from last week of June to cover the developmental period of A. devastans (Aheer et al., 2006). Insecticides were applied with a knapsack sprayer having a spray volume of 250 l ha-1 at the pressure of 3 bars fitted with a hollow cone nozzle. In each year, untreated control plot was kept unsprayed throughout the season for comparison.

Number of A. devastans on expended leaves (n= 30), one leaf from apical, 2nd from middle and 3rd from the bottom portion of randomly selected plants (10 plants/replicate) from each treatment were observed visually (Razaq et al., 2005) after each spray at a frequency of one week interval. In addition to A. devastans, other herbivores of interest were monitored by

178 using the above described method, in each treatment per sample date. However, to record natural enemies, whole plant counts of predators were made from randomly selected plants

(n= 10 plants/replicate) from each treatment on each sampling date.

One week after third spray plants (n= 3 per treatment) were removed gently from all the tested spray regimes and untreated plots and brought back to laboratory, washed with water and then spread on paper to measure root length and stem length, and to count number of leaves, squares, and flowers. At crop maturity, raw cotton from each plot (n= 3 plots per treatment) was picked for recording yield. Seed cotton samples (n= 100 g per replicate) were packed separately in paper bags and sent to Fiber Technology Department, CCRI, Multan,

Pakistan for lint testing during 2013.

8.2.1 Statistical analysis

For measuring efficacy of tested insecticides against A. devastans percent population reduction in different modules was calculated by using Henderson–Tilton formula

(Henderson and Tilton, 1955; Kolarik and Rotrek, 2013) given as under;

퐶푎 × 푇 푏 Population reduction (%) = (1 − ) × 100 퐶푏 × 푇푎

Ca= Pre-treatment population in control plot

Cb= Post-treatment population in control plot

Ta= Pre-treatment population in treated plot

Tb= Post-treatment population in treated plot

Data on all variables means were analysed for variance (ANOVA) by a General Linear

Model, using GenStat statistical package, version 15 (VSN International, Hemel Hempstead,

UK) which allows parameteric analysis of data with normally distributed error variance without prior transformation (Batchelor et al., 2006). Differences between treatments means were compared with Tukey’s HSD test with 5% level of probability following significant F-

179 test. Marginal return calculated as the value of yield gain due to spraying, relative to the cost of spray schedule (Nabirye et al., 2003).

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Table 1. Insecticides, their groups, common names, trade names, manufacturer and dose rates applied in different regimes Sr. no. Group/ Common name Trade name company name aDose bCost classification (a.i.) (100 Rs = 1 U$) 1 Carbamate Carbosulfan Advantage 20%EC FMC 200 925 2 Organochlorine Endosulfan Endosulfan 35% EC FMC 280 825 3 Organophosphate Dimethoate Danadem Progress 40% EC Swat Agro Chemicals 160 1,250 4 Organophosphate Acephate Acephate 75% SP Jaffer Group 247 653 5 Pyrethroid Bifenthrin Jatara 10% EC Jaffer Group 25 1,540 6 IGR Pyriproxyfen Priority 10.8 EC KANZO Ag 54 500 7 Neonicotinoid Imidacloprid Confidor 20% SL Bayer Crop Science 40 344 8 Pyrole Chlorfenapyr Pirate 320 SC BASF 81 4,000 9 Thiourea Diafenthiuron Polo 500 SC Syngenta 309 188 a Dose of active ingredient g or ml/ha b Cost calculated/ha

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Table 2. Regime wise insecticidal treatment combinations applied in 1st 2nd and 3rd sprays Spray regime 1st spray 2nd spray 3rd spray no.

Regime 1 Dimethoate Chlorfenapyr Acephate

Regime 2 Acephate Pyriproxyfen Bifenthrin

Regime 3 Pyriproxyfen Diafenthiuron Endosulfan

Regime 4 Chlorfenapyr Imidacloprid Pyriproxyfen

Regime 5 Diafenthiuron Dimethoate Carbosulfan

Regime 6 Endosulfan Bifenthrin Dimethoate

Regime 7 Imidacloprid Carbosulfan Chlorfenapyr

Regime 8 Carbosulfan Endosulfan Diafenthiuron

Regime 9 Bifenthrin Acephate Imidacloprid

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8.3 RESULTS

8.3.1 Amrasca devastans

During 2012, spray started from 24th of June as population crossed ETL (1 jassid leaf-1) in all plots, and second and third sprays were applied on 8th of July and 22nd of July, respectively.

During 2013, first spray was applied on 25th of June, second and third on 9th of July and 23rd of July in all spray regimes (Fig. 1A and B). Treatments significantly influenced A. devastans populations (F9,36 = 17.95, P < 0.001) but the effect of year (F1,36 = 1.00, P = 0.42) and treatment × year interaction (F9,36 = 0.98, P = 0.47) was non-significant. Therefore, subsequent discussion is based on pooled data for two years.

On the basis of two years average, results revealed that population reduction percentage was different among all the tested regimes. After first spray the highest average reduction percentage (93.88%) was found in regime 1 where, dimethoate, chlorfenapyr and acephate were rotated followed by regime 2 where Acephate, Pyriproxyfen and Bifenthrin (92.52%) were applied. While A. devastans population exceeded in regime 3 where (Pyriproxyfen,

Diafenthiuron and Endosulfan) and regime 9 (Bifenthrin, Acephate and Imidacloprid) than that of untreated plots during both the years (Fig. 1), hence negative average reduction percentages (-0.95 and 11.67%) were found. Highest reduction percentage (90.35%) after second spray was recorded in regime 1(dimethoate, chlorfenapyr and acephate) and negative percentages in regime 2 (Acephate, Pyriproxyfen and Bifenthrin) (-9.45%) and regime 6

(Endosulfan, Bifenthrin and Dimethoate) (-67.79%) were observed. After third spray negative reduction percentages (-11.66 and -26.03%) were found in regime 2 (Acephate,

Pyriproxyfen and Bifenthrin) and regime 4 (Chlorfenapyr, Imidacloprid and Pyriproxyfen) while highest population reduction (92.62%) recorded in regime 1. On the basis of average of all three sprays maximum reduction was recorded in regime 1 dimethoate, chlorfenapyr and acephate (92.62%) and lowest in regime 3 (16.70%) followed by regime 9 (23.86%) (Fig. 2).

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(A) 2012 Regime 1 12 Regime 2

10 Regime 3 / leaf / Regime 4 8 Regime 5 6 Regime 6

4 Regime 7 Regime 8

2 Regime 9 Amrascadevastans 0 Regime 10 6/24 7/1 7/8 7/15 7/22 7/29 Dates

(B) 2013 Regime 1 12 Regime 2 10

/ leaf / Regime 3 8 Regime 4

6 Regime 5 Regime 6 4 Regime 7 2

Regime 8 Amrascadevastans 0 Regime 9 6/25 7/2 7/9 7/16 7/23 7/30 Regime 10 Dates

Fig. 1 Mean seasonal population of Amrasca devastans per leaf in tested spray regimes and untreated plots during study period: (A) 2012, (B) 2013 Arrows represent timing of insecticide application for each tested spray regime

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Reduction percentage Reduction

Fig. 2 Amrasca devastans population reduction percentages one week after spray in tested spray regimes as compared to untreated control by Henderson and Tilton formula: A) 1st spray, B) 2nd spray, C) 3rd spray D) average of three sprays (average across two years)

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8.3.2 Natural enemies

All the spray regimes significantly affected abundance of Orius spp. (Hemiptera:

Anthocoridae) (F9,36 = 3612.70, P < 0.001), Geocoris spp. (Hemiptera: Lygaeidae) (F9,36 =

244.93, P < 0.001), Chrysoperla carnea (Neuroptera: Chrysopidae) (F9,36 = 756.89, P <

0.001), Coccinellid spp. (Coleoptera: Coccinellidae) (F9,36 = 739.96, P < 0.001) and spiders

(Araneae) (F9,36 = 1860.91, P < 0.001). More numbers of all the predators were recorded in untreated plots as compared to tested regime plots. Toxicity of spray regimes was also consistent for almost all the taxa. Spray regime consisting of Chlorfenapyr, Imidacloprid and

Pyriproxyfen proved to be less toxic to all predators (Table 3).

8.3.3 Impact on crop performance

Amrasca devastans exerted profound impact on crop performance, as all the plant traits [root length (cm), shoot length (cm), number of leaves, squares, flowers, yield (kg ha-1), GOT (%), fiber strength (tppsi), micronaire (μg inch-1) and staple length (mm)] was found to be negatively and significantly correlated with A. devastans densities (Table 4).

8.3.3.1 Plant growth, seed cotton yield and fiber characteristics

Plant growth parameters and seed cotton yield of transgenic cotton significantly differed in all the treatments. Maximum root length (cm) (F9,36 = 1445.13, P < 0.001), greater shoot length (cm) (F9,36 = 392.24, P < 0.001), more number of leaves (F9,36 = 606.49, P < 0.001)

-1 and higher seed cotton yield (kg ha ) (F9,36 = 252.49, P < 0.001) were found in regime 1 treated plants and lower in untreated control followed by regime 3 and regime 9 (Table 5).

The highest yield gain percentage with maximum marginal return and profit was obtained from plots that received the spray regime 1 (Table 6). During 2013, impact of treatments on fiber characteristics was also recorded. Treatments significantly influenced fiber characteristics including GOT (F9,18 = 123.64, P < 0.001), micronaire (F9,18 = 72.06, P <

0.001), staple length (F9,18 = 117.73, P < 0.001) and fiber strength (F9,18 = 118.59, P < 0.001),

186 that were higher in regime 1 treated cotton samples as compared to all other tested regimes and untreated cotton samples (Table 7).

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Table 3. Seasonal mean (± SE) of predators in tested spray regimes and untreated control plots of transgenic cotton Spray regimes Predators ( ± SE) Orius spp. Geocoris spp. Chrysoperla carnea Coccinellid spp. Spiders Total predators Regime 1 10.95 ± 0.67 d 1.93 ± 0.11 d 20.05 ± 0.54 d 3.35 ± 0.01 d 16.95 ± 0.36d 53.25 ± 1.42 d Regime 2 5.80 ± 0.59 g 1.19 ± 0.01 f 11.30 ± 0.37 g 1.86 ± 0.07 g 10.45 ± 0.52 g 30.60 ± 1.39 g Regime 3 12.80 ± 0.30 c 2.50 ± 0.15 c 25.55 ± 0.78 c 3.90 ± 0.15 c 19.65 ± 0.22 c 64.40 ± 1.07 c Regime 4 14.35 ± 0.37 b 2.80 ± 0.15 b 29.49 ± 0.99 b 4.18 ± 0.04 b 22.55 ± 0.52 b 73.37 ± 1.60 b Regime 5 4.35 ± 0.52 h 0.91 ± 0.13 g 9.34 ± 0.61 h 1.50 ± 0.15 h 8.05 ± 0.45 h 24.15 ± 1.50 h Regime 6 3.50 ± 0.44 i 0.70 ± 0.15 g 7.45 ± 0.32 i 1.01 ± 0.13 i 5.95 ± 0.22 i 18.61 ± 1.06 i Regime 7 11.10 ± 0.58 d 2.00 ± 0.15 d 21.05 ± 0.44 d 3.60 ± 0.04 d 17.50 ± 0.53 d 55.25 ± 1.20 d Regime 8 7.80 ± 0.30 e 1.46 ± 0.16 e 15.70 ± 0.69 e 2.44 ± 0.14 e 14.55 ± 0.67 e 41.94 ± 1.12 e Regime 9 6.85 ± 0.22 f 1.35 ± 0.16 ef 13.60 ± 0.40 f 2.12 ± 0.16 f 12.60 ± 0.59 f 36.52 ± 1.46 f Untreated 19.35 ± 0.52 a 3.30 ± 0.15 a 36.06 ± 0.98 a 5.79 ± 0.16 a 31.25 ± 0.82 a 95.74 ± 2.31 a Numbers shown are from 10 plants per treatment and across 2012 and 2013. Means with in a column followed by same letter are not significant (Tukey’s HSD test, P < 0.05)

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Table 4. Correlation between Amrasca devastans densities and plant traits Plant traits Correlation P value Covariance Standard error coefficient Root length (cm) -0.83 <0.001 -4.09 0.74 Shoot length (cm) -0.81 <0.001 -12.93 2.40 Leaves -0.80 <0.001 -16.82 3.18 Yield (kg ha-1) -0.79 <0.001 -931.17 178 GOT (%) -0.91 <0.001 -17.12 2.85 Fiber strength (tppsi) -0.77 <0.001 -10.03 2.01 Micronaire (μg inch-1) -0.71 <0.001 -0.18 0.04 Staple length (mm) -0.86 <0.001 -3.04 0.54

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Table 5. Transgenic cotton growth parameters (± SE) in tested spray regimes and an untreated control Spray regimes Root length Shoot length Number of leaves (cm) (cm) Regime 1 42.2 ± 0.44 a 71.9 ± 0.99 a 81.8 ± 0.80 a Regime 2 24.0 ± 0.51 e 43.9 ± 0.80 f 50.8 ± 0.80 f Regime 3 16.2 ± 1.20 hi 31.3 ± 1.00 gh 33.3 ± 1.83 hi Regime 4 26.6 ± 0.52 e 48.0 ± 0.45 e 56.5 ± 0.68 e Regime 5 33.2 ± 0.52 c 55.4 ± 1.06 c 67.8 ± 1.39 c Regime 6 20.5 ± 0.43 g 41.3 ± 1.07 f 42.3 ± 0.59 g Regime 7 34.9 ± 0.37 b 60.9 ± 2.04 b 72.8 ± 1.65 b Regime 8 31.3 ± 0.44 d 51.9 ± 0.80 d 64.3 ± 0.66 d Regime 9 16.8 ± 0.64 h 33.9 ± 2.00 g 35.3 ± 1.83 h Untreated 15.0 ± 0.59 i 29.8 ± 0.44h 31.0 ± 0.85 i Means with in a column followed by same letter are not significant (Tukey’s HSD test, P < 0.05) Data pooled across two sampling years

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Table 6. Comparison of economic benefits among different spray regimes Spray Regimes Yield ± SE Yield gain Marginal return (kg ha-1) (%) Regime 1 3415 ± 118 a 398.5 3.9 Regime 2 1300 ± 22 e 89.8 0.9 Regime 3 900 ± 80 fg 31.3 0.3 Regime 4 1565 ± 74 d 128.5 1.2 Regime 5 2372 ± 114 bc 246.3 2.4 Regime 6 1150 ± 52 ef 67.9 0.6 Regime 7 2512 ± 111 b 266.7 2.6 Regime 8 2112 ± 155 c 208.3 2.0 Regime 9 975 ± 77 f 42.3 0.4 Untreated 685 ± 73 g - - Means with in a column followed by same letter are not significant (Tukey’s HSD test, P < 0.05) Data pooled across two sampling years; marginal returns less than 1 indicated non-profitability

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Table 7. Fiber characteristics (± SE) influenced by tested spray regimes Spray Regimes GOT Micronaire Staple length Fiber (%) (μg inch-1) (mm) strength (tppsi) Regime 1 42.8 ± 0.88 a 4.10 ± 0.07 a 29.7 ± 0.35 a 103.2 ± 0.85 a Regime 2 30.0 ± 0.53 c 3.59 ± 0.06 cde 25.0 ± 0.71 d 85.0 ± 0.71 d Regime 3 22.5 ± 1.54 e 3.50 ± 0.07 ef 21.9 ± 0.28 e 80.0 ± 0.71 f Regime 4 31.0 ± 0.71 c 3.61 ± 0.01 cde 26.5 ± 0.35 c 87.3 ± 0.92 cd Regime 5 38.0 ± 0.18 b 3.70 ± 0.07 c 28.1 ± 0.19 b 91.4 ± 0.78 b Regime 6 28.1 ± 0.60 cd 3.55 ± 0.04 def 24.3 ± 0.21 e 83.9 ± 0.71 de Regime 7 39.0 ± 0.53 b 3.90 ± 0.04 b 28.2 ± 0.19 b 92.3 ± 0.49 b Regime 8 37.5 ± 0.53 b 3.65 ± 0.04 cd 28.0 ± 0.14 b 90.5 ± 0.71 bc Regime 9 25.2± 1.22 de 3.51 ± 0.08 ef 22.5 ± 0.14 e 81.0 ± 1.41 ef Untreated 18.0 ± 1.32 f 3.43 ± 0.02 f 21.1 ± 0.25 e 79.0 ± 0.35 f Means with in a column followed by same letter are not significant (Tukey’s HSD test, P < 0.05)

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8.4 DISCUSSION

In the present study, lowest mean population of A. devastans and its maximum reduction percentage was observed in regime 1, where insecticides with different mode of action were rotated i.e. organophosphates (dimethoate and acephate) rotated with novel mode of action insecticide (chlorfenapyr). Our results affirm the potential of dimethoate and acephate, belonging to organophosphate group of insecticides, to combat A. devastans (Anonymous,

2012; Eijaz et al., 2012; Karar et al., 2013). After the introduction of new chemistry insecticides, their application has been increseaed tremendously (26.07 to 33.44%) in cotton crop (Razaq et al., 2013). Therefore, A. devsastan populations might have become susceptible to conventional insecticides due their lower selection pressure. Repeated use of same mode of action insecticides is one of the reasons for resistance development in insect pests. To minimise onset of resistance in Helicoverpa armigera (Hübner), use of same mode of action insecticides has been prohibited and a rotational scheme for insecticide having different modes of action has been suggested (Razaq et al., 2007). However, exposing single generation of the pest with different mode of action insecticides may develop cross resistance. Australian IRM (Insecticides Resistance Management) strategy for pyrethroids and endosulfan program by exposing one generation of pest with similar mode of action of insecticides has been proved effective in delaying resistance in pyrethroids for twelve years

(Razaq et al., 2013).

Our results suggest that A. devastans population on cotton was distinctively impacted by the type of insecticides used within each spray regime. Among the tested spray regimes, whenever pyriproxyfen or bifenthrin added in the regime, population flared up and results showed negative reduction percentage, reflecting their poor potential against A. devastans.

Reduced potency of these two insecticides against A. devastans is also reported by

Anonymous (2011). Insect pests belonging to Hemiptera like A. devastans reproduced rapidly

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(12 generations/year) therefore the treatment effects can not be clearly depicted when compared graphically. In other hemipteran pests like aphids cumulative aphid days (CAD) are used to determine treatment/seasonal effects on plants (Hanafi et al., 1989). However, literature does not report application of cumulative days method to determine treatment effects on insect pests like, whiteflies and leafhoppers. Negative reduction percentages point out the occurrence of resurgence in insect pests (Sethi and Dilawari, 2008). Naveed et al.

(2008) found resurgence of B. tabaci in bifenthrin and pyriproxfen treated cotton plots as compared to untreated check.

The tested spray regimes against one pest may also have positive or negative impact on population of closely related pests and natural enemies (Al-Shannaf, 2010). We found that the generalist predator’s community in the transgenic cotton was reduced by all the tested regimes, but with varying levels. Population of Orius spp., Geocoris spp., C. carnea,

Coccinellids spp. and spiders were higher in untreated control followed by regime 4

(Chlorfenapyr, Imidacloprid and Pyriproxyfen), in which novel mode of action insecticides were rotated in all three sprays. Safety of new classes insecticides having novel mode of action for predators as compared to conventional insecticides is documented by various workers under laboratory and field conditions (Nagai, 1990; Delbeke et al., 1997; Elzen et al.,

1998; Naranjo et al., 2004; Naveed et al., 2008).

Tested regimes showed profound effect on plant growth and reproductive parameters. These parameters were negatively related to A. devastans infestation in all the regimes. Maximum root length, shoot length, number of leaves, flowers and squares were recorded in regime 1 as compared to all other regimes. Thapa et al. (1994) found higher efficacy of dimethoate to combat A. biguttula biguttula on okra with improved plant growth parameters, including taller plant, healthy pods and better quality seeds along with maximum net return as compared to other treatments. Plant growth was badly affected in untreated control plots

194 followed by plots treated with regime 3 (pyriproxyfen→diafenthiuron→endosulfan) and regime 9 (bifenthrin→acephate→imidacloprid) treated cotton plots. Though negative population reduction percentages were found in regime 2 after 2nd and 3rd spray but growth and reproductive parameters were less affected as compared to regime 9 and regime 3. This may be due to the reason that A. devastans is early season sucking pest and regime 2 treated plots received first application of acephate, which suppressed population up till 2nd week and escape most vulnerable period. While regime 3 and regime 9 treated plots received first application of pyriproxyfen and bifenthrin, due to weaker efficacy of these pesticides plants undergo stress and could not be recovered by proceeding foliar applications.

Severe infestation of A. devastans may cause deterioration of fiber quality (Afzal and Ghani,

1953). In present study, maximum yield kg ha-1 was recorded in regime 1 as compared to all other treatments. Moreover, regime 1 also improved fiber characteristics generating higher

GOT, micronaire, staple length and fiber strength as compared to other regimes and untreated control. Overall, regime 1 proved effective against A. devastans, ultimately increasing yield and improving fiber characteristics of transgenic Bt cotton. Hence, results indicated that use of poor potential or less effective insecticide when A. devastans reached to economic threshold level of 1 jassid per leaf may cause considerable yield loss, leading to reduced quantity and deteriorated quality of transgenic Bt cotton. However, under field conditions several factors like insect density, frequency of resistant insects, age of insects and plant size may contribute to the control failure (Razaq et al., 2007). Moreover, many of the biological characteristics like migratory ability of A. devastans cannot be controlled directly under field conditions; hence supplementary laboratory studies are desired.

Apart from this fact our results not only confirm that spray regime efficacy depends upon insecticides potential against A. devastans, but also suggest that use of some of these insecticides may harm IPM of cotton by reducing abundance of their key natural enemies.

195

Results suggested that seed cotton yield and fiber losses can be avoided by use of potential insecticides particularly in first spray and preceding insecticides rotation in different sequences to supress A. devastans. Use of repeated sprays belonging to same group or having same mode of action should be discouraged to avoid resurgence of A. devastans and to protect natural enemies on transgenic Bt cotton.

196

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CHAPTER-9

Conclusions and recommendations for further research

202

To manage A. devastans following recommendations should be followed area wide.

1) Remove alternative host weeds from cotton fields and their vicinity.

2) Avoid cultivation of the vegetables, Abelmoschus esculentus and Solanum melongena near

cotton fields or their intercropping with cotton, and also avoid growing the perennial Ricinus

communis near cotton fields or in field margins. These three species harbour the highest

densities of A. devastans throughout the year and thus appear to constitute important carry-

over sources of the pest.

3) Avoid frequent use of pesticides on those vegetables planted before cotton like A. esculentus

and S. melongena: when applications are necessary, apply insecticides in rotation having

different modes of action.

4) Early planting of cotton should be completed in the month of the March as mid-April

planting is more vulnerable to A. devastans.

5) Follow planting time based action thresholds to manage A. devastans. As proved in

present research March-15 planting 1AT level (Action Threshold Level) resulted in one

spray application with no significant loss of yield. For April-15 planting use of 2ATs led to

three spray applications as compared to 0.1AT (10 sprays), without any significant yield

loss. May-15 planting was more vulnerable to A. devastans damage. Hence 1AT by

employing 5 sprays hinder significant yield loss.

6) Seed treatment with imidacloprid and thiamethoxam at recommended doses reduced pest

abundance and delayed pest in reaching the economic damage threshold by around 30

days (thiamethoxam) or 40-45 days (imidacloprid) after sowing. These doses also

enhanced plant growth. Neonicotinoid applications reduced abundance of beneficial

arthropods, with lower populations after higher doses, but negative effects of

imidacloprid were not apparent unless the manufacturer-recommended dose was

203

exceeded. Therefore, both neonicotinoids can be applied as seed treatment to delay foliar

applications of insecticides.

7) NIBGE-2 variety can be planted to reduce applications of insecticides as proved resistant

to A. devastans with due caution as characters responsible for resistance (like dense hairs,

greater hair length, more leaf thickness etc.) favour Bemisia tabaci.

8) Chrysoperla carnea is potential predator of A. devastans. Embrace C. carnea in

management programs of A. devastans.

9) A spray regime in which two organophosphates (dimethoate and acephate) were applied

proved to be the best in reducing A. devastans populations. These insecticides might

have reverted susceptibilities due to their less frequency of application after introduction

of new chemistry insecticides. However, these insecticides should be applied with

caution and should be rotated with different mode of actions to avoid resistance

development.

FURTHER RESEARCH

This study revealed that the presence of alternative host plants of A. devastans is disadvantageous to the cotton agro-ecosystem. But many alternative host plants are vegetables, crops and fruits and also harbour natural enemies of A. devastans and thus economically beneficial in their own right. Characteristics of alternative host plant species, such as type, growth habit, perenniality and abundance, will influence this balance before sowing of cotton. Considerable work may be required to study the phylogenetically non- independent plant characters, such as type, growth habit and perenniality. Augmentation of natural enemies needs to be evaluated on alternate hosts before A. deastans migrates to cotton because during this period frequency of application of insecticides is also low.

Plant traits responsible for resistance to sucking insect pests in cotton varieties are antagonistic. Most work on host plant resistance in cotton has concentrated morphological

204 defences. Tolerance characters have not been considered in cotton resistance to sucking insect pests. Therefore, quantification of recovery capacity after damage for cotton cultivars/varieties should be carried out for A. devastans and other sucking insect pests.

Resistance monitoring is used to confirm whether or not resistance to insecticides causes control failure. Moreover, this provides an early warning of an impending resistance problem and to make the recommendations for the pesticides least affected by resistance. Insecticides are currently essential to manage A. devastans and are likely to remain an important component of control strategies in foreseeable future. No research reports occurrence of resistance in A. devastans since late 1990s (see also chapter). Therefore, it is dire need to monitor resistance in A. devastans to currently used insecticides to avoid crisis of its management.

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