CHARACTERIZING PHENOTYPIC AND GENETIC VARIATIONS IN THE INVASIVE CHILLI , DORSALIS HOOD (THYSANOPTERA: )

By

VIVEK KUMAR

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2012

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© 2012 Vivek Kumar

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To my family I would have not succeeded if I had not failed

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ACKNOWLEDGMENTS

The list is countless, but I would like to begin by thanking my major advisor Dr.

Dakshina R. Seal who gave me the opportunity to work on this project. His constant support, encouragement and kindle faith in me always boosted me and kept me focused towards the goal. My sincere thanks to Vegetable IPM Lab members of TREC, Cathie

Sabines, Carlos, Charles Carter, and Jacinto who played important role in my projects while being behind the scene. Special thanks to graduate committee member Dr. Cindy

L. McKenzie for her unwavering support and allowing me to use USDA-ARS facility, without which completion of this project would have been difficult. I would like to extend my thanks to other committee members Dr. David Schuster, Dr. Lance Osborne, Dr.

James Maruniak and Dr. Shouan Zhang for their valuable suggestions, constructive criticism and guidance during the doctoral program. I am also grateful to Dr. Ale

Maruniak, John Prokop, and Michael Cartwright for helping me with molecular techniques and Dr. Robert Shatters, Dr. Aaron M. Dickey for scientific advice to understand the output. I owe sincere thanks to Dr. Wayne Hunter, Lyle Buss and

Thomas Skarlisnky who trained me in various photographic techniques and helped me identify different thrips . I thank Dr. Donald Hall, Dr. Heather McAuslane, Debbie

Hall and Maria Bernal for making me aware of the rules and departmental requirements and updating me with the deadlines.

I also thank to my colleague and friends at University of Florida Deepak

Golasangimath, Megha Kalsi, Amit Gupta, Phalgun Nelaturu, Sudhamshu Acharya,

Ameya and Mithila Gondhalekar, Tamrat Wuletaw, Nichole Dobbs, Xiaodan Mo, Germo

Tatto for making life happy and easier. Great deal of thanks to Dr. Jeet and Seemanti

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Sengupta for encouragements, advice and friendly nature. I will always cherish those moments.

I am indebted to my parents late Ram Lochan Jha and Kali Jha, and brothers-

Pramod Jha, Ashish Jha, Santosh Jha and other family members who showed confidence and continuously encouraged me to complete my doctoral program. The achievements and awards earned during this journey are dedicated to them. Special thanks to my father-in-law Kuldeep Singh Kakkar, whose never ending challenges motivated me to go for higher studies in this great nation. Words fail to express thanks to my wife Garima Kakkar Jha, for her endless, unconditional love and support without whom I could not have accomplished this task. Finally, I would like to thank almighty

God for giving me eternal life, his blessings and the path shown during my journey.

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TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 8

LIST OF FIGURES ...... 9

ABSTRACT ...... 11

CHAPTER

1 LITERATURE REVIEW ...... 13

Introduction ...... 13 Background Information ...... 14 Economic Host ...... 16 Geographical Distribution ...... 17 Worldwide distribution ...... 17 U. S. invasion ...... 17 Host Damage ...... 19 Summary of Damage Symptoms ...... 20 Identification ...... 20 Life Cycle ...... 21 Management of S. dorsalis ...... 22 Cultural Practices ...... 22 Chemical Control ...... 23 Biological Control ...... 25

2 SCIRTOTHRIPS DORSALIS (THYSANOPTERA: THRIPIDAE): SCANNING ELECTRON MICROGRAPHS OF KEY TAXONOMIC TRAITS AND A PRELIMINARY MORPHOMETRIC ANALYSIS OF THE GENERAL MORPHOLOGY OF POPULATIONS OF DIFFERENT CONTINENTS ...... 36

Introduction ...... 36 Materials and Methods...... 39 Identification of Specimens ...... 40 Scanning Electron Microscopy ...... 40 Morphometric Measurements of Major Body Traits ...... 41 Statistical Analysis ...... 41 Results ...... 42 Identification of Specimens ...... 42 Morphometric Measurements of Major Morphological Features ...... 43 Discussion ...... 45

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3 COUPLING SCANNING ELECTRON MICROSCOPY WITH DNA BAR CODING FOR MORPHOLOGICAL AND MOLECULAR IDENTIFICATION OF THRIPS ...... 68

Introduction ...... 68 Materials and Methods...... 71 Morphological Identification ...... 71 Molecular Identification ...... 72 PCR protocol and sequencing ...... 72 Results and Discussion...... 73

4 INTRAGENOMIC VARIATION IN mtCO1 AND rDNA ITS2 OF THREE MAJOR THRIPS SPECIES, SCIRTOTHRIPS DORSALIS, AND FRANKILINIELLA OCCIDENTALIS (THYSANOPTERA: THRIPIDAE) ...... 79

Introduction ...... 79 Materials and Methods...... 84 Taxon Sampling ...... 84 Morphological Identification of Thrips ...... 84 DNA Processing ...... 85 Sequence Alignment and Genetic Distance Matrix ...... 86 Results ...... 87 Inter- and Intragenomic Variation ...... 87 Parsimony Analysis of ITS2 ...... 90 Discussion ...... 90 Mitochondrial Cytochrome Oxidase I ...... 90 Internal Transcribed Spacer 2 Variation ...... 92

5 SUMMARY ...... 110

LIST OF REFERENCES ...... 113

BIOGRAPHICAL SKETCH ...... 129

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LIST OF TABLES

Table page

1-1 Plants infested with S. dorsalis as reported in global pest and disease database...... 27

1-2 Confirmed hosts of Scirtothrips dorsalis in Florida...... 33

1-3 Choices of insecticides for rotational use against S. dorsalis populations...... 35

2-1 Scirtothrips dorsalis populations by year collected, geographical location, host plant, preservative and specimen source...... 50

2-2 Measurements of fourteen morphological characters from five different populations of Scirtothrips dorsalis...... 51

2-3 Number of traits in which significant quantitative differences occurred between the various geographic populations of Scirtothrips dorsalis ...... 52

3-1 PCR amplification conditions for two genes...... 77

4-1 Collection date, localities and hosts for specimens used in cloning of rDNA and mtCO1 genes of thrips species of three genera...... 96

4-2 PCR amplification conditions for two genes...... 97

4-3 Number of clones sequenced and recovered haplotypes for the four individuals of each thrips species...... 98

4-4 The rDNA ITS2 sequences that differ among Scirtothrips dorsalis individuals. .. 99

4-5 The mtCO1 sequences that differ among Scirtothrips dorsalis individuals...... 101

4-6 The rDNA ITS2 sequences that differ among Thrips palmi individuals...... 102

4-7 The mtCO1 sequences that differ among Thrips palmi individuals...... 104

4-8 The rDNA ITS2 sequences that differ among Frankliniella occidentalis individuals...... 105

4-9 The mtCO1 sequences that differ among Frankliniella occidentalis individuals...... 106

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LIST OF FIGURES

Figure page

2-1 Slide mount of S. dorsalis female showing dark brown antecostal ridge (AR) on tergites...... 53

2-2 Eight segmented antennae with third and fourth segments each possessing forked sensorium...... 54

2-3 Dorsal view of S. dorsalis head with ocellar triangle, interocellar setae (IOS), hind ocelli (HO) and postocular setae (POS)...... 55

2-4 Pronotum of S. dorsalis exhibiting horizontal closely spaced sculpture lines...... 56

2-5 Posterior half of the metanotum presents longitudinal striations; medially located metanotal setae arise behind anterior margin...... 57

2-6 Shaded forewing of S. dorsalis is distally light in color with first and second vein possessing three and two widely spaced setae, respectively...... 58

2-7 Abdominal tergites III to VI of S. dorsalis possess small setae medially situated close to each other...... 59

2-8 The posteromarginal comb (row of microtrichia) on segment VIII is complete.... 60

2-9 Discal setae absent on sternites, sternites covered with rows of microtrichia with the exception of the antero-medial region...... 61

2-10 Simple D1 and funnel-shapped D2 setae on the head of a S. dorsalis ...... 62

2-11 Funnel shaped setae on abdominal terga IX and X of a S. dorsalis larva...... 63

2-12 Reticulated pronotum of a S. dorsalis larva illustrating the presence of 6-7 pairs of pronotal setae...... 64

2-13 Abdominal segments IV-VII of a S. dorsalis larva illustrating the presence of 8-12 setae each...... 65

2-14 Forefemora of a S. dorsalis larva illustrating the presence of four funnel shaped setae on the distal two-thirds portion...... 66

2-15 Body of a S. dorsalis larva indicating the presence of granular plaques...... 67

3-1 Agarose gel showing PCR results using the ITS2 primers and mtCO1 primer set for the detection of S. dorsalis...... 78

4-1 An unrooted semi strict MP generated from rDNA ITS2 sequence obtained from 2 female and 2 male individuals of S. dorsalis...... 107

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4-2 An unrooted semi strict MP tree generated from rDNA ITS2 sequence obtained from 2 female and 2 male individuals of T. palmi...... 108

4-3 An unrooted semi strict MP tree generated from rDNA ITS2 sequence obtained from 2 female and 2 male individuals of F. occidentalis...... 109

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

CHARACTERIZING PHENOTYPIC AND GENETIC VARIATIONS IN THE INVASIVE CHILLI THRIPS, SCIRTOTHRIPS DORSALIS HOOD (THYSANOPTERA: THRIPIDAE)

By

Vivek Kumar

May 2012

Chair: Dakshina R. Seal Major: Entomology and Nematology

Chilli thrips, Scirtothrips dorsalis Hood, has been a serious problem across the globe. Detection of S. dorsalis larvae and adults on host plants is difficult due to the thigmotactic behavior and tiny stature (< 2 mm in length) of the thrips. In this study, 14 different morphological characters of five different populations of S. dorsalis, collected from two different continents were compared. The objective of the study was to determine if certain morphological characters of S. dorsalis adults differ significantly in size among populations from different geographic regions of the world. These populations of S. dorsalis did not differ significantly for nine morphological characters, but statistical differences were observed among five populations for 2-5 characters.

In order to make the identification of thrips simple and more accurate, a non- destructive taxonomic characterization technique for thrips was developed for larvae and adults. The method involves the integration of high resolution and magnification capabilities of Scanning electron microscopy with the DNA bar coding technique. In this protocol, a single specimen can be identified using both morphological and molecular identification techniques. The thrips specimen is first identified using morphological

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characters is then further processed for DNA extraction and PCR based assays to confirm the identification.

The genetic characterization of three economically important thrips species, S. dorsalis, Frankliniella occidentalis (Pergande) and Thrips palmi Karny was conducted using one nuclear encoded ribosomal DNA sequence (rDNA ITS2) and one mitochondria encoded gene (mitochondrial cytochrome oxidase 1). High degree of intragenomic variations were reported in the ITS2 sequences of the three species suggesting that ITS2 copies in these thrips do not evolve in concert. Thus, this marker region is not phylogenetically informative for population studies, and species-specific

PCR identification of the thrips species understudy. However, less intragenomic and intraspecific variations were observed in conserved mtCO1 region of the three pest species, indicating that this gene might be more useful than ITS2, in phylogenetic characterization of the three thrips species. Results from different studies confirmed the existence of morphological and genetic variation in population of S. dorsalis that suggests the possibility of this species being a cryptic species complex.

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CHAPTER 1 LITERATURE REVIEW

Introduction

Of more than 5500 species of thrips described in the literature, 1% are considered serious pests (Morse and Hoddle, 2006). Thrips are polyphagous that inhabit tropical, subtropical and temperate regions of the world (Ananthakrishnan, 1993). The small size and cryptic nature of thrips pests enable them to occupy microhabitats in the field and within plants, often making monitoring and identification difficult. Thrips can reduce crop yield or value indirectly by vectoring plant diseases and directly by using agriculture products for food and reproduction. They can also act as irritants to the public or field workers and can negatively affect global trade due to the quarantine risks

(Morse and Hoddle, 2006).

The scientific literature available on the economics of thrips mainly deals with four thrips species: Thrips tabaci Lindeman, Frankliniella occidentalis (Pergande),

Scirtothrips dorsalis Hood and T. palmi Karny (Morse and Hoddle, 2006). Of these four thrips species, less information is available on S. dorsalis in the USA owing to its recent invasion. Since its establishment in Florida in 2005, S. dorsalis has emerged as an economically important pest of ornamental plants and is considered a potential threat to vegetable and crops (Seal et al. 2010). In a recent study, Kumar et al. (2012) reported this pest was economically damaging 12 different species of fruit plants at a nursery in Miami Dade county of Florida. Nine of these species had not been previously reported as hosts of this pest in the literature, suggesting that the host range of this pest is increasing in this region.

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Scirtothrips dorsalis, commonly known as the chilli thrips, is a serious pest of various vegetable, ornamental and fruit crops in southern and eastern Asia, Africa, and

Oceania (Ananthakrishnan 1993, EPPO 1997). The pest also vectors seven recorded viruses including Chilli Curl (CLC) Virus, Necrosis Virus (PBNV), Tobacco streak virus (TSV) silver mottle virus (WsMoV), Capsicum chlorosis virus

(CaCV) and Melon yellow spot virus (MYSV) (Amin et al. 1981, Mound and Palmer

1981, Ananthakrishnan 1993, Rao et al. 2003, Chiemsombat et al. 2008). According to the Florida Nurserymen and Growers Association, S. dorsalis is one of the thirteen most dangerous, exotic pests threatening the industry (FNGLA 2003).

In 2010, the Florida horticultural greenhouse/nursery industry was valued at ca.

$1.74 billion (ERS-USDA 2011). In addition, potential host crops in Florida including , peppers, , cucumbers, cotton, and blueberries were valued at an additional 1 billion. Even a 10% loss of these products can cause significant impact on

Florida’s economy and may open the market for foreign trade (Derksen 2009).

Background Information

The great reproductive potential, invasion ability and easy adaptation to new areas are a few of the qualities, which make Scirtothrips species major concerns of agriculture in many countries (Hoddle et al. 2008). From the beginning, S. dorsalis has been reported as an opportunistic generalist species that is able to feed on a variety of hosts, depending upon availability in the region of incidence. From the beginning, S. dorsalis has been reported as an opportunistic generalist species that is able to feed on a variety of hosts, depending upon availability in the region of incidence. The first reference to S. dorsalis was in 1890, when an unidentified thrips species was reported damaging the tea crop in the Ceylon area of Assam state in . Watt later supported this

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observation in 1898, but he was not sure that damage was being caused by one or two species of thrips (Dev 1964). Further investigation confirmed that S. dorsalis was responsible for damaging the tea crops in all of the major tea growing regions of eastern

India including Darjeeling, Cachar, the Assam Valley, Terai and the Dooars (Dev 1964).

In 1916, this pest was reported infesting castor in the Coimbatore district of the southern part of India and later was found infesting other hosts in the region including chilli, groundnuts, mango, beans, cotton, brinjal (Eggplant) and Casia fistula (Ramakrishna

Ayyar 1932, Ramakrishna Ayyar and Subbiah 1935). Young , buds, and tender stems of the host plants were severely damaged. Thrips repeated puncturing of tender leaf tissues with their stylet produces ‘sandy paper lines’ on the epidermis of the leaves and eventual crinkling of leaves. In India, the characteristic leaf curl damage caused by this pest is known as “Murda” (Hindi meaning- dead body) disease, because infestations resulted in the death of plants (Kulkarni 1922). Many different scientific names have been assigned to S. dorsalis since it was first described in 1919 mainly because of the lack of sufficient scientific literature regarding morphological differences and variations in host range from the different geographical regions. During the last 100 years, the host range and the bio-geographical range of S. dorsalis have broadened.

The thrips is established in all of the habitable continents except Europe, where repeated introductions have been intercepted and eliminated. Studying the history of S. dorsalis aids in the understanding of behavioral and morphological diversity exhibited by this species as a result of biological and ecological variations that have occurred duing its migratory period.

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Economic Host Plants

Prior to the introduction of S. dorsalis into the New World, the host range of the pest included more than 100 plant taxa among 40 families (Mound and Palmer 1981).

Subsequent to the introduction of S. dorsalis into the New World, the pest was found to attack additional taxa of plants (Venette and Davis 2004). The main wild host-plants belong to the family , which includes Acacia, Brownea, Mimosa and Saraca.

In its native range of the Indian subcontinent, chilli crops are reported to be attacked by

25 different pests, among which S. dorsalis is considered as one of the most serious threats (Butani 1976). The pest is responsible for yield losses ranging from 61 to 74%

(Patel et al. 2009). Scirtothrips dorsalis is also abundant on Arachis in India (Amin

1980), sacred lotus in (Mound and Palmer 1981), and tea and in Japan

(Kodomari 1978). Among the potential economic hosts of this pest listed by Venette and Davis (2004) are banana, bean, cashew, castor, corn, citrus, cotton, cocoa, cotton, eggplant, grapes, kiwi, litchi, longan, mango, melon, peanut, pepper, poplar, , , sweet potato, tea, tobacco, tomato, and wild yams (Dioscorea spp.).

Interestingly, S. dorsalis is not reported reproducing on all of the hosts mentioned in the literature. Most of the plant hosts were assigned to this pest based on the presence of adults and their damaging potential. Thus, it is worthwhile to describe the host plant infested with S. dorsalis as those used for feeding and/or reproduction. Based on information obtained from the Global Pest and Disease Database (GPDD-2011), S. dorsalis was reported to feed on (not necessarily reproduce on) more than 225 plant taxa worldwide in 72 different families and 32 orders of plants (Table 1-1). In Florida, S. dorsalis has been reported from 61 different plants to date (Table 1-2). Disparities in host selection in different geographical regions are documented in the literature. For

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example, S. dorsalis is reported on mango in Puerto Rico but not in adjacent Caribbean islands where it was reported earlier. Scirtothrips dorsalis is a significant pest of citrus in

Japan (Tatara and Furuhashi 1992) and Taiwan (Chang 1995), but not in India or the

United States. Many factors could be attributed to the differences in plant hosts of S. dorsalis reported from different geographical regions. These various factors could include variation in competition with other pests, availability of predators in the region of invasion, availability of hosts, environmental conditions, etc. (Derksen 2009), but could also be the result of differential biological activity of different S. dorsalis biotypes/cryptic species, none of which have yet been reported.

Geographical Distribution

Worldwide distribution

Scirtothrips dorsalis is widely distributed along its native range in Asia including

Bangladesh, Brunei Darussalam, China, Hong Kong, India, Indonesia, Japan, Republic of Korea, Malaysia, , Pakistan, Philippines, Sri Lanka, Taiwan, and Thailand.

Further south S. dorsalis occurs in northern and the Soloman Islands

(Macleod and Collins 2006). On the African continent, the pest is reported from South

Africa and the Ivory Coast, with plant health quarantine interceptions suggesting a wider distribution across West Africa and East Africa (Kenya). Scirtothrips dorsalis is in Israel as well as in the Caribbean including Jamaica, St. Vincent, St. Lucia, Barbados and

Trinidad. In western Venezuela, S. dorsalis has been found causing serious damage to grapevine (Macleod and Collins 2006).

U. S. invasion

Changing climatic conditions and globalization have resulted in the increasing importance of invasive species as recurrent problems around the globe. Pimentel et al.

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(2000, 2005), inferred that approximately more than 50,000 non indigenous species have already been introduced in the United States, causing an estimated annual damage of more than $120 billion in forestry, agriculture and other sectors of society.

The rich vegetation and neotropical climate of Florida make the state suitable for the invasion and establishment of exotic flora and fauna (Ferriter et al. 2006). Scirtothrips dorsalis is a newly introduced insect pest in Florida believed to have originated in

Southeast Asia. Since 1984, USDA-APHIS inspectors at various ports-of-entry have intercepted S. dorsalis 89 times on imported plant materials belonging to 48 taxa, most commonly on cut , and vegetables (USDA 2003). With the exception of

Hawaii, the presence of this tropical south Asian pest was not confirmed in the Western

Hemisphere until 2003. In Florida, S. dorsalis was reported from Okeechobee County in

1991 and from Highland County in 1994 but failed to establish a durable population

(Silagyi and Dixon 2006). In 2003, Tom Skarlinsky (USDA-APHIS-PPQ) reported live larvae and pupae under the calyx of treated peppers in a shipment of Capsicum spp. traced back to hot pepper production areas in St. Vincent and the Grenadines, West

Indies (Holtz 2006). Later, with the collaborative efforts of the USDA (APHIS) and IFAS

(University of Florida), S. dorsalis was found established in different agricultural districts of St. Lucia and St. Vincent (Ciomperlik and Seal 2004), Barbados, Suriname, Trinidad and Tobago, and Venezuela (Holtz 2006). In 2005, S. dorsalis was found on pepper and

‘Knockout’ Rose plants in retail garden centers in Florida and Texas. Subsequently, S. dorsalis has been reported many times on different ornamental plants in commercial nurseries throughout Florida (Hodges et al. 2005). In a collaborative survey over a two- month period (Oct-Nov 2005), the Florida Department of Agricultural and Consumer

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Services (FDACS) and the University of Florida found infestations 77 times in 16 counties (Holtz 2006). Of the 77 positive observations, 66 were found on , 10 on

Capsicum and one on Illicium.

Venette and Davis (2004) projected the potential geographic distribution of S. dorsalis in North America to extend from southern Florida to the Canadian border, as well as to Puerto Rico and the entire Caribbean region. This suggests that this pest could also become widely established in South America and Central America. The small size (< 2 mm in length) and thigmotactic behavior of S. dorsalis make it difficult to detect the pest in fresh vegetation, thus, increasing the likelihood of the transportation of the pest through international trade of botanicals.

Host Damage

Scirtothrips dorsalis feeding on the meristems, terminals and other tender plant parts of the host plant above the soil surface results in undesirable feeding scars, distortion of leaves, and discoloration of buds, flowers and young fruits. The pest is not reported to feed on mature host tissues. It possesses piercing and sucking mouthparts and causes damage by extracting the contents of individual epidermal cells, leading to the necrosis of tissue. The color of damaged tissue changes from silvery to brown or black. The appearance of discolored or disfigured plant parts suggests the presence of

S. dorsalis. Larvae feed on the lower surfaces of young leaves, causing the leaves to curl upward. According to Sanap et al. (1987), adults and larvae of S. dorsalis suck the cell sap of the leaves, causing the leaves to curl upward. Severe infestations of S. dorsalis cause the tender leaves and buds to become brittle, resulting in complete defoliation and yield loss. For example, heavy infestations of pepper plants by S. dorsalis cause changes in the appearance of plants termed “chilli leaf curl”. The

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appearance of discolored or disfigured plant parts suggests the presence of S. dorsalis.

Larvae feed on the lower surfaces of young leaves, causing the leaves to curl upward.

On many hosts, the thrips may feed on the upper surfaces of leaves when infestations are high. Infested fruits develop corky tissues (Seal et al. 2006a). Sometimes, plants infested by S. dorsalis appear similar to plant damaged by the feeding of broad mites

Summary of Damage Symptoms

 Silvering of the leaf surface

 Linear thickening of the leaf lamina

 Brown frass markings on the leaves and fruits

 Grey to black markings on fruits, often forming a distinct ring of scarred tissue

around the apex

 Fruit distortion and premature senescence and abscission of leaves

Identification

Larvae of S. dorsalis are creamish white to pale in color. The sizes of the first instars, the second instars, and the pupae range between 0.37-0.39, 0.68-0.71 and

0.78-0.80 mm, respectively (Seal et al. 2010). Adults are less than 1.2 mm in length with dark wings. Dark spots form incomplete stripes seen dorsally on the abdomen (Seal et al. 2010). There are numerous microtrichia and dark transverse antecostal ridges on the abdominal tergites and sternites. Three discal setae are located on the lateral microtrichial fields of the abdominal tergites.and the posteromarginal comb on VIII segment is complete. The shaded forewings are distally lighter in color with posteromarginal straight cilia on the distal half and the first and second veins bear three and two widely spaced setae, respectively (Skarlinsky 2004, Hoddle et al. 2009).

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Detailed information about the morphological identification of S. dorsalis adults and larvae are in Chapters 2 and 3.

Life Cycle

Thysanopterans have always been recorded as opportunistic species, as their life history strategies are preadapted from the detriophagous ancestral group developed in a habitat where optimal conditions of survival are brief (Funderburk 2001). Mating does not result in fertilization of all the eggs and unfertilized eggs produce males while fertilized eggs produce females. Sex ratio is in favor of female progeny (Dev 1964). The stages of the life cycle of S. dorsalis include the egg, first and second instar larva, prepupa, pupa and adult. Gravid females lay eggs inside the plant tissue (above the soil surface) and eggs hatch between 5-8 days depending upon environmental conditions

(Dev 1964, Seal et al. 2010). Larvae and adults tend to gather near the mid-vein or borders of the damaged portion of leaf tissues. Pupae are found in the leaf litter, on the axils of the leaves, and in curled leaves or under the calyx of and fruits. Larval stages complete in 8-10 days, and it takes 2.6-3.3 days to complete the pupal stage.

The life span of S. dorsalis is considerably influenced by the type of host they are feeding. For example, it takes 11.0 days to become an adult from first instar larva on pepper plants and 13.3 days on squash at 28°C. S. dorsalis adults can survive for 15.8 days on eggplant but 13.6 days on tomato plants (Seal et al. 2010). They can grow at minimal temperature as low as 9.7°C and maximum temperature 33.0°C. Their thermal requirement from egg to egg is 281-degree days and egg to adult is 265-degree days

(Holtz 2006). Population is multivoltine (having more than one generation per year) in temperate regions of up to eight generations per year and 18 in warm subtropical and tropical areas (Nietschke et al. 2008). They start egg laying in late March or early April

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when temperature is favorable for development (Shibao et al.1991) and first generation adults can be seen from early May (Masui 2007a). However, S. dorsalis cannot overwinter in regions where temperature remains below -4°C for five or more days

(Nietschke et al. 2008). Prolonged rainy seasons do not affect populations much, but the population remains more abundant during prolonged dry conditions than in moist rainy periods.

Management of S. dorsalis

Incursions of S. dorsalis are difficult to manage, and successful eradication is possible only with early detection and implementation of management practices. Host crops, which develop from, seeds such as bean, corn or cotton, must be carefully monitored during the seedling stage of growth because this stage is extremely susceptible to attack by S. dorsalis (Seal et al. 2010). Symptoms of infestations of S. dorsalis must be monitored on their susceptible host plants like roses, pepper, cotton, etc. twice per week and if symptom appears then samples should be sent to a reputable laboratory for confirmation.

Cultural Practices

Development of effective management practices for S. dorsalis is still in its infancy. The World Vegetable Center has several recommendations, which could serve as basic management practices for the control of this pest. It involves crop rotation, removal of weeds (which may serve as hosts), insecticide rotation and supporting the maximum use of natural enemies including predators and parasites. In some of the plant resistance to S. dorsalis feeding appears to exist. Presence of gallic acid plays a crucial role in resistance to S. dorsalis in some varieties of the chilli plant (Holtz

2006). In Japan, synthetic reflective (vinyl) film has been used to protect citrus crops

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from S. dorsalis infestations (Tsuchiya et al.1995a). In another study, Tsuchiya et al.

(1995b) reported the use of white aqueous solution, i.e. 4% CaCO3 on mandarin orange along with reflective-sheet mulching to provide better suppression in S. dorsalis.

Use of different colored sticky traps in monitoring and for thrips control has also been evaluated. Tsuchiya et al. (1995c) found that yellowish-green, green and yellow sticky board provided effective suppression in pest population on host plant. However, yellowish-green was most effective in attracting S. dorsalis adults. In a recent study,

Chu et al. (2006) evaluated three different sticky cards (blue, yellow and white) for sampling of S. dorsalis, and suggested yellow sticky cards could be used efficiently for population detection and monitoring purposes of this pest.

Chemical Control

Chemical control is a primary mode of management of S. dorsalis and a wide range of insecticides belonging to different chemical groups is currently used worldwide to control this pest. In south-central Asia, chemical control is conducted using quinalphos, dimethoate, phosphamidon and carbaryl. However, monocrotophos and permethrin gave better suppression of this pest in India and Japan (Sanap et al. 1987,

Shibao 1997). Asaf-Ali et al. (1973) reported that malathion was effective against S. dorsalis on grapevine. Since their introduction in the Greater Caribbean, there was a paucity of information for effective management of this insect using modern insecticides.

Seal et al. (2006a) and Seal and Kumar (2010) showed the effectiveness of various novel chemistries against S. dorsalis. Ten chemical insecticides belonging to seven different mode of action classes (Table 1-3) provided effective suppression of the pest.

Bethke et al. (2010) suggested the rotational use of three or more insecticides from different action classes could provide prolonged suppression of the pest population.

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Pyrethroids have not been reported to provide effective control against S. dorsalis in the

New World. Although it causes an instant reduction in pest population, it also kills natural controlling agents, ultimately leading to resurgence of pest populations. Various formulations of imidacloprid, used as either soil drenches or foliar applications provides control against S. dorsalis without harming any natural controlling agents. Its application results in suppression of S. dorsalis populations for several days (Table 1-3) after application of treatments.

Management practices from an ecological point-of-view must be environmental friendly but from a growers’ viewpoint must be economical, fast acting as well as long lasting. Different chemical insecticides that could satisfy all concerns, like spinetoram and various neonicotinoid insecticides do cause significant reduction in S. dorsalis on pepper crops (Seal et al. 2006b). However, due to the frequent use, insect pests are under intense selection pressure to developed resistance against these insecticides.

There are many reports where excessive reliance on insecticide has resulted in resistance development in this pest (Reddy et al. 1992). In India, Reddy et al. (1992) reported resistance in S. dorsalis populations to a range of organochlorine (DDT, BHC and endosulfan), organophosphate (acephate, dimethoate, phosalone, methyl-o- demeton and triazophos) and carbamate insecticides (carbaryl). Recently, S. dorsalis was reported to develop resistance against monocrotophos, acephate, dimethoate, phosalone, carbaryl and triazophos (Vanisree et al. 2011). Thus, in order to forestall or delay development of resistance or minimize the progressive assembly of genes for resistance through selection in the pest against a particular chemistry, it is necessary to rotate insecticides from diverse chemical groups, and explore alternative methods of

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pest control. Inclusion of effective biorational and biological products in a best management program for S. dorsalis can lead to reduced applications of synthetic insecticides. Use of biorational and biocontrol products early in the season will delay the buildup of damaging pest populations on host plants. Furthermore, reduction in the use of harmful insecticides will increase the population of natural biocontrol agents.

Biological Control

Various biological controlling agents like minute pirate bugs, Orius spp.

(Hemiptera: Anthocoridae) and the phytoseiid mites and

Amblyseius swirskii have been reported to provide effective control of S. dorsalis on pepper (Dogramaci et al. 2011, Arthurs et al 2009). Adults of Orius insidiosus feed on all the life stages of thrips, and since it also feeds on aphids, mites, moth eggs and pollen, its population does not decline when there are periodic drops in the thrips population.

Arthurs et al. (2009) evaluated two phytoseiid mites Neoseiulus cucumeris and

Amblyseius swirskii as potential biological control agents of S. dorsalis and reported A. swirskii can be a promising tool in managing its population on pepper. Shibao et al.

(2004) showed the effect of predatory phytoseiid mites sojaensis in regulating

S. dorsalis population, on grapes in Japan. Chow et al. (2008) suggested the use of two or more natural enemies as a strategy to improve biological control of greenhouse pests. Predators that warrant further study as potential natural enemies of S. dorsalis include lacewings (Chrysoperla spp.), several mird bugs, ladybird , and a number of predatory thrips including Franklinothrips vespiformis, the black hunter thrips, the six spotted thrips (Leptothrips mali), Scolothrips sexmaculatus, the banded wing thrips (Aeolothrips spp.), and predatory phytoseiid mites, Euseius hibisci and Euseius tularensis.

25

Role of entomopathogens like , Metarhizium anisopliae and

Isaria fumosorosea in managing field population of S. dorsalis are still under study.

Beauveria bassiana used with some adjuvants has been reported to control larval populations of S. dorsalis for the first few days after application but soon the population of S. dorsalis increases and becomes equivalent to the control plants (Seal and Kumar.

2010). Mikunthan and Manjunatha (2008) showed a significant reduction in S. dorsalis populations using entomopathogens Fusarium semitectum in pepper fields. However, commercialization and success of this biorational product in different biogeographical regions is still in need of evaluation. Therefore, there is an immense need for developing new strategies to employ best management practices for this serious pest utilizing cultural, chemical and biological control methods.

26

Table 1-1. Plants infested with S. dorsalis as reported in global pest and disease database.

Plant order Plant family Scientific name Common or trade Name Alismatales Araceae Colocasia esculenta (L.) Schott Taro Apiales Apiaceae Daucus carota L. Carrot Apiales Araliaceae Schefflera arboricola (Hayata) Merr. Dwarf schefflera, dwarf umbrella tree Apiales Araliaceae Schefflera spp. J.R. and G. Forst. Schefflera Apiales Araliaceae Hedera helix L. English Ivy Apiales Pittosporaceae Pittosporum spp. Banks ex Gaertn. Cheesewood Apiales Pittosporaceae Pittosporum tobira (Thunb.) W. T. Chinese pittosporum Aiton Aquifoliales Aquifoliaceae Ilex crenata Thunb. Japanese holly Aquifoliales Aquifoliaceae Ilex integra Thunb. Mochitree Aquifoliales Aquifoliaceae Ilex spp. L. Holly Asperagales Alliaceae Allium cepa L. Onion Asperagales Alliaceae Allium sativum L. Garlic Aspergales Asparagaceae Asparagus officinalis L. Asparagus Asterales Asteraceae Brachyscome spp. Cass. Chrysanthemum Asterales Asteraceae Chrysanthemum morifolium Ramat. Chrysanthemum Asterales Asteraceae Coreopsis spp. L. Tickseed Asterales Asteraceae Dahlia pinnata Cav. Pinnate dahlia Asterales Asteraceae Dahlia spp. Cav. Garden dahlia Asterales Asteraceae Dimorphotheca aurantiaca DC., non African daisy, Cape Horton marigold Asterales Asteraceae Echinops echinatus Roxb. Indian globe thistle Asterales Asteraceae Helianthus annuus L. Sunflower Asterales Asteraceae Sonchus asper (L.) Hill Spiny sowthistle Asterales Asteraceae Tagetes erecta L. African marigold Asterales Asteraceae Tagetes patula L. Indian marigold, French marigold Asterales Asteraceae Zinnia elegans L. Zinnia Brassicales Brassicaceae Brassica rapa L. var. silvestris Colza (Lam.) Briggs Brassicales Moringaceae Moringa oleifera Lam. Drumsticktree Caryophyllales Amaranthaceae Alternanthera sessilis (L.) R. Br. ex Sessile joyweed DC. Caryophyllales Amaranthaceae Amaranthus blitum L. Purple amaranth Caryophyllales Amaranthaceae Amaranthus lividus L. Amaranth Caryophyllales Amaranthaceae Amaranthus spp. L. Grain amaranth, Pigweed Caryophyllales Amaranthaceae Celosia argentea L. var. cristata (L.) Celosia Kuntze Caryophyllales Amaranthaceae Celosia spp. L. Cock’s comb Caryophyllales Chenopodiaceae Beta vulgaris L. Beetroot Caryophyllales Plumbaginaceae Limonium spp. Mill., nom. cons. Limonium Caryophyllales Plumbaginaceae Plumbago auriculata Lam. Cape leadwort Caryophyllales Polygonaceae Coccoloba uvifera (L.) L. Seaside grape Caryophyllales Polygonaceae Fagopyrum esculentum Moench Buckwheat Caryophyllales Polygonaceae Polygonum esculentum Knotweed Caryophyllaes Portulacaceae Portulaca oleracea L. Pigweed, Little hogweed, purslane

27

Table 1-1. Continued

Plant order Plant family Scientific name Common or trade Name Celastrales Celastraceae Euonymus japonica Thunb. Japanese spindletree Celastrales Celastraceae Euonymus spp. L. Euonymus Commelinales Commelinaceae Tradescantia zebrina hort. ex Bosse Wandering jew Cornales Hydrangeaceae Hydrangea spp. L. Hydrangea Cucurbitales Cucurbitaceae Citrullus lanatus (Thunb.) Matsum. & Watermelon Nakai Cucurbitales Cucurbitaceae Cucumis melo L. Cantaloupe Cucurbitales Cucurbitaceae Cucumis sativus L. Cucumber Cucurbitales Cucurbitaceae Cucurbita moschata (Duchesne ex Pumpkin Lam.) Duchesne ex Poir. Cucurbitales Cucurbitaceae Cucurbita pepo L. Pumpkin, Zucchini Cucurbitales Cucurbitaceae Cucurbita spp. L. Squash Cucurbitales Cucurbitaceae Momordica charantia L. Bitter gourd, bitter melon, balsam apple Dioscoreales Dioscoreaceae Dioscorea spp. L. Yam Caprifoliaceae awabuki K. Koch Viburnum Dipsacales Caprifoliaceae Viburnum odoratissimum Ker Gawl. China Laurestine Dipsacales Caprifoliaceae Viburnum plicatum Thunb. Japanese snowball Dipsacales Caprifoliaceae Viburnum suspensum Lindl. Viburnum Ericales Actinidiaceae Actinidia chinensis Planch. Chinese gooseberry Ericales Actinidiaceae Actinidia deliciosa [A. Chev.] C.F. Kiwifruit Liang et A.R. Ferguson Ericales Balsaminaceae Impatiens spp. L. Impatiens Ericales Balsaminaceae Impatiens walleriana Hook. f. Super Elfin White Ericales Ebenaceae Diospyros kaki Thunb. Persimmon Ericales Ericaceae Pieris japonica (Thunb.) D. Don ex Japanese-andromeda G. Don Ericales Ericaceae Rhododendron spp. L. Azalea Ericales Ericaceae Vaccinium corymbosum L. Highbush blueberry Ericales Ericaceae Vaccinium spp. L Blueberry Ericales Sapotaceae Mimusops hexandra Roxb. Palu, rayan Ericales Theaceae Camellia japonica L. Japanese camelia Ericales Theaceae Camellia sasanqua Thunb. Sasanqua camellia Ericales Theaceae Camellia sinensis (L.) Kuntze Tea Ericales Theaceae Eurya japonica Thunb. Eurya Fabaceae Acacia arabica (Lam.) Willd. Acacia, babul Fabales Fabaceae Acacia auriculiformis A. Cunn. ex Darwin black wattle Benth. Fabales Fabaceae Acacia brownii (Poir.) Steud. Heath wattle Fabales Fabaceae Acacia nilotica (L.) Delile Acacia Fabales Fabaceae Acacia spp. Mill. Acacia Fabales Fabaceae Albizia odoratissima (L. f.) Benth. Ceylon rosewood Fabales Fabaceae Arachis hypogaea L. Peanut, groundnut Fabales Fabaceae Brownea spp. Jacq., nom. cons. Brownea Fabales Fabaceae Caesalpinia pulcherrima (L.) Sw. Pride-of-Barbados Fabales Fabaceae Dolichos biflorus L. Horse gram Fabales Fabaceae Dolichos lablab L. Hyacinth bean, labalab bean Fabales Fabaceae Glycine max (L.) Merr. Soyabean

28

Table 1-1. Continued

Plant order Plant family Scientific name Common or trade Name Fabales Fabaceae Melilotus indica (L.) All. Hubam clover Fabales Fabaceae Mimosa pudica L. Action plant, sensitive plant Fabales Fabaceae Phaseolus vulgaris L. Common Bean, green bean, snap bean Fabales Fabaceae Prosopis cineraria (L.) Druce Jand Fabales Fabaceae Prosopis spicigera L. Khejri Fabales Fabaceae Saraca indica L. Asoka tree Fabales Fabaceae Saraca minor Miq Kembang dedes Fabales Fabaceae Saraca spp. L. Saraca Fabales Fabaceae Tamarindus indica L. Indian tamarind Fabales Fabaceae Tamarindus spp. L. Tamarind Fabales Fabaceae Vicia angustifolia L. Narrow leaf vetch Fabales Fabaceae Vigna radiata (L.) R. Wilczek Mung bean Fabales Fabaceae Melanoxylon spp. Schott Melanoxylon Fabales Fabaceae Melanoxylum spp. Schott Brauna Fagales Fagaceae Castanea crenata Sieb. and Zucc. Japanese chestnut Fagales Fagaceae Quercus glauca Thunb. Ring cup oak Fagales Fagaceae Quercus virginiana Mill. Live oak Geraniales Geraniaceae Pelargonium ×hortorum L. H. Bailey Florist’s geranium Gentianales Apocynaceae Calotropis gigantea (L.) W. T. Aiton Calotropis Gentianales Gentianaceae Eustoma grandiflorum (Raf.) Lisianthus Shinners Gentianales Rubiaceae Gardenia jasminoides J. Ellis Gentianales Rubiaceae Pentas lanceolata (Forsk.) Deflers Egyptian starcluster Gentianales Rubiaceae Pentas spp. Benth. Pentas Gentianales Rubiaceae Richardia brasiliensis Gomes Tropical Mexican clover Geraniales Geraniaceae Geranium spp. L. Geranium Ginkoales Ginkoaceae Ginkgo biloba L. Ginko Illiales Illiaceae Illicium floridanum J. Ellis Florida anisetree strictum (Nees) Kuntze Firespike Lamiales Acanthaceae Strobilanthes dyerianus Mast. Persian shield Lamiales Jasminum multiflorum (Burm. f.) Star jasmine Andrews Lamiales Oleaceae (L.) Ait. Pikake Lamiales Oleaceae Ligustrum japonicum Thunb. Japanese privet Lamiales Plantaginacae Antirrhinum majus L. Snapdragon Lamiales Lamiaceae Coleus spp. Lour. Coleus Lamiales Lamiaceae Lamium barbatum Sieb. & Zucc. Dead nettle Lamiales Lamiaceae Ocimum basilicum L. Sweet basil Lamiales Lamiaceae heterophyllus (G. Don) Holly-olive P. S. Green Lamiales Lamiaceae Plectranthus scutellarioides (L.) R. Painted nettle Br. Lamiales Lamiaceae Salvia farinacea Benth. Mealycup sage Lamiales Verbenaceae Duranta erecta L. Golden dewdrops Lamiales Verbenaceae Duranta spp. L. Duranta Lamiales Verbenaceae Verbena spp. L. verbana

29

Table 1-1. Continued

Plant order Plant family Scientific name Common or trade Name Lamiales Verbenaceae Glandularia ×hybrida (hort. ex Florist’s verbana Groenl. & Rümpler) G. L. Nesom & Pruski Laurales Lauraceae Laurus nobilis L. Sweet bay, laurel bay Magnoliales Annonaceae Annona squamosa L. Sugar apple Malphigiales Euphorbiaceae Breynia nivosa (W. Bull) Small Snowflower Malphigiales Euphorbiaceae Euphorbia pulcherrima Willd. ex Poinsettia Klotzsch Malphigiales Euphorbiaceae Hevea brasiliensis (Willd. ex A. Rubber Juss.) Müll. Arg. Malphigiales Euphorbiaceae Hevea spp. Aubl. Hevea Malphigiales Euphorbiaceae Manihot esculenta Crantz Cassava Malphigiales Euphorbiaceae Poinsettia pulcherrima (Willd. ex Christmas flower Klotzsch) Graham Malphigiales Euphorbiaceae communis L. Castor bean Malphigiales Euphorbiaceae Ricinus spp. L. Ricinus Malphigiales Euphorbiaceae Sauropus androgynus (L.) Merr. Star-gooseberry Malphigiales Passifloraceae Passiflora edulis Sims Purple granadilla, passion fruit Malphigiales Salicaceae Populus deltoides Bartr. ex Marsh. Eastern cottonwood Malvales Malvaceae Abelmoschus esculentus (L.) Okra Moench Malvales Malvaceae Gossypium herbaceum L. Arabian cotton, Levant cotton Malvales Malvaceae Gossypium hirsutum Bourbon cotton Malvales Malvaceae Gossypium spp. L. Cotton Malvales Malvaceae Theobroma cacao L. Cocoa Combritaceae Calycopteris floribunda Lam. Getonia Myrtales Combritaceae Laguncularia racemosa (L.) C. F. White buttonwood Gaertn. Myrtales Combritaceae Concocarpus erectus L. Myrtales Lythraceae Cuphea hyssopifolia Kunth Mexican heather Myrtales Lythraceae Cuphea spp. P. Browne Cuphea Myrtales Lythraceae Lagerstroemia indica L. Crapemyrtle Myrtales Lythraceae Punica granatum L. Pomegranate Myrtales malaccense (L.) Merr. and Malay-apple L. M. Perry Myrtales Myrtaceae Syzygium samarangense (Blume) Water apple, wax apple Merrill & Perry Myrtales Onagraceae Gaura lindheimeri Engelm. & A. Gray Lindheimer's beeblossom Nymphaeales Nymphaeaceae Nymphaea pubescens Willd. Red water lily Nymphaeales Nymphaeaceae Nymphaea spp. L. Waterlily Pinales Podocarpaceae Podocarpus macrophyllus (Thunb.) Yew plum pine Sweet Pinales Podocarpaceae Podocarpus spp. L'Hir. ex Pers. Plum pine Poales Poaceae Zea mays L. subsp. Mays Corn Proteales Nelumbonaceae Nelumbo lutea L.Willd. Lotus Proteales Nelumbonaceae Nelumbo nucifera Gaertn. Sacred lotus Proteales Nelumbonaceae Nelumbo spp. Adans Lotus

30

Table 1-1. Continued

Plant order Plant family Scientific name Common or trade Name Proteales Nelumbonaceae Nelumbo nucifera Gaertn. Sacred lotus Ranunculales Berberidaceae Mahonia bealei (Fortune) Carrière Leatherleaf mahonia, Kuo Ye Shi Da Gong Lao Moraceae Ficus carica L. Common fig Rosales Moraceae Ficus elastica Roxb. ex Hornem. Rubberplant Rosales Moraceae Ficus spp. L. Ficus Rosales Moraceae Morus spp. L. Mulberry Rosales Rhamnaceae Zizyphus mauritiana Lam. Badari Rosales Amygdalus persica L. Peach Rosales Rosaceae Fragaria ananassa Duchesne ex Strawberry Rozier Rosales Rosaceae Fragaria chiloensis (L.) Mill. Strawberry Rosales Rosaceae Fragaria chiloensis (L.) P. Mill. Beach strawberry Rosales Rosaceae Fragaria chiloensis (L.) Mill. var. Strawberry ananassa (Duchesne ex Rozier) Ser. Rosales Rosaceae Fragaria virginiana Duchesne Strawberry Rosales Rosaceae Fragaria ×ananassa Duch. Garden strawberry Rosales Rosaceae glabra (Thunb.) Maxim. Japanese photonia Rosales Rosaceae Prunus avium (L.) L. Sweet cherry Rosales Rosaceae Prunus mume Siebold & Zucc. Japanese apricot Rosales Rosaceae Prunus persica (L.) Batsch Peach Rosales Rosaceae Prunus salicina Lindl. Japanese plum Rosales Rosaceae Prunus spp. L. Cherry, Stone fruit Rosales Rosaceae Pyracantha angustifolia (Franch.) Firethorn Schneid. Rosales Rosaceae Pyracantha spp. M. Roemer Firethorn Rosales Rosaceae Pyrus spp. L. Pear Rosales Rosaceae Raphiolepis indica (L.) Lindl. Indian hawthorn Rosales Rosaceae Raphiolepis umbellata Thunb. Yeddo Hawthorne Rosales Rosaceae indica (L.) Lindl. ex Ker Shi Ban Mu Gawl. Rosales Rosaceae Rhaphiolepis umbellata (Thunb.) Japanese-hawthorn Makino Rosales Rosaceae Rosa chinensis Jacq. Chinese rose Rosales Rosaceae Rosa spp. L. Rose Rosales Rosaceae Rosa ×hybrida L. Knockout Radrazz rose Rosales Rosaceae Rubus spp. L. Blackberry, raspberry Sapindales Aceraceae Acer spp. L. Maple Sapindales Anacardiaceae Anacardium occidentale L. Cashew nut Sapindales Anacardiaceae Mangifera indica L. Mango Sapindales Anacardiaceae Mangifera spp. L. Mango Sapindales Rutaceae Citrus aurantiifolia (Christm.) Swingle Lime Sapindales Rutaceae Citrus limon (L.) Burm. f. Lemon Sapindales Rutaceae Citrus maxima (Burm.) Merr. Pummelo Sapindales Rutaceae Citrus paradisi Macfad. Grapefruit Sapindales Rutaceae Citrus reticulata Blanco var. unshiu Satsuma mandarin (Marco.) H. H. Hu Sapindales Rutaceae Citrus sinensis (L.) Osbeck Orange Sapindales Rutaceae Citrus unshiu Marc. Satsuma mandarin

31

Table 1-1. Continued

Plant order Plant family Scientific name Common or trade Name Sapindales Rutaceae ×Citrofortunella microcarpa (Bunge) Calomondin Wignands Sapindales Rutaceae ×Citrofortunella spp. J. W. Ingram & Orangequat, H. E. Moore citrangequat Sapindales Rutaceae Fortunella spp. Swingle Kumaquat Sapindales Rutaceae Murraya paniculata (L.) Jack Orange-jasmine Sapindales Rutaceae Poncirus trifoliata (L.) Raf. Trifoliate orange Sapindales Rutaceae Zanthoxylum piperitum (L.) DC. Japanese-pepper Sapindales Sapindaceae Dimocarpus longan Lour. Longan Sapindales Sapindaceae Litchi chinensis Sonn. Litchi, lychee Sapindales Sapindaceae Nephelium lappaceum L Rambutan Sapindales Sapindaceae Nephelium litchi Cambess. Litchi Sapindales Sapindaceae Nephelium longana (Lam.) Longan Cambess. Saxifragales Hamamelidaceae Distylium racemosum Siebold & Isu-no-ki Zucc. Solanales Convolvulaceae Ipomoea batatas (L.) Lam. Sweet potato Solanales Solanaceae Capsicum annuum L. Chilli, pepper, Jalapeno pepper, black pearl Solanales Solanaceae Capsicum annuum L. var. anuum Bell pepper Solanales Solanaceae Capsicum chinense Jacq. Bonnet pepper Solanales Solanaceae Capsicum frutescens L. Chilli Solanales Solanaceae Capsicum minimum Blanco Blanco pepper Solanales Solanaceae Datura fastuosa L. Devil's Trumpet Solanales Solanaceae Lycopersicon esculentum Mill. Tomato Solanales Solanaceae Lycopersicon spp. Mill. Tomato Solanales Solanaceae Nicotiana spp. L. Tobacco Solanales Solanaceae Nicotiana tabacum L. Tobacco Solanales Solanaceae Petunia spp. Juss., nom. cons. Petunia Solanales Solanaceae Petunia ×hybrida hort. ex E. Vilm. Petunia Solanales Solanaceae Solanum lycopersicum L. Tomato Solanales Solanaceae Solanum melongena L. Eggplant, aubergine Solanales Solanaceae Solanum nigrum L. Black nightshade Vioales Begoniacae Begonia spp.L. Begonia Vioales Violaceae Viola wittrockiana Gams Field pansy Vioales Violaceae Viola ×wittrockiana Gams Garden pancy Vitales Vitaceae Ampelopsis brevipedunculata Porcelain (Maxim.) Trautv. Vitales Vitaceae Ampelopsis spp. Michx. Peppervine Vitales Vitaceae Cayratia japonica (Thunb.) Gagnep. Yapu garashi Vitales Vitaceae Vitis pteroclada (Hayata) Hayata Vitis pteroclada Vitales Vitaceae Vitis vinifera L. Grape, grapevine Zingiberales Musaceae Musa spp. L. Banana

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Table 1-21. Confirmed plant hosts of Scirtothrips dorsalis in Florida.

Scientific name Common or trade name

Antirrhinum majus L. Liberty Classic White Snapdragon Arachis hypogaea L Peanut or groundnut Begonia sp. Begonia Breynia nivosa (W. Bull) Small Snow bush, snow-on-the-mountain Camellia sinensis (L.) Kuntze Tea Capsicum annuum L. Jalapeno pepper, Bonnet pepper Capsicum frutescens L. Chilli pepper Capsicum spp. Celosia argentea L. Celosia – red fox Citrus spp. Concocarpus erectus Coreopsis sp. Tickseed Cuphea sp. Waxweed, tarweed Duranta erecta L. golden dewdrop, pigeonberry, skyflower Euphorbia pulcherrima Willd. Poinsettia Eustoma grandiflorum (Raf.) Shinn. Florida Blue Lisianthus Ficus elástica Roxb. Ex Hornem. Burgundy Rubber Tree Gardenia jasminoides J. Ellis Jasmine Gaura lindheimeri Engelm. & Gray Lindheimer’s beeblossom Gerbera jamesonii H. Bolus ex Hook. F. Gerber daisy Glandularia x hybrida (Grönland & Rümpler) Verbena Neson & Pruski Gossypium hirsutum L. Cotton Hedera helix L. English Ivy Illicium floridanum Ellis Florida anisetree Impatiens walleriana Hook. F. Super Elfin White Jasminum sambac (L.) Ait. Pikake Lagerstroemia indica L. Crape myrtle Laguncularia recemosa (L.) Gaertn. f. White buttonwood Ligustrum japonicum Thunb. Japanese privet Litchi chinensis Sonn. Litchi Mahonia bealei (Fortune) Carrière Leatherleaf mahonia Manilkara zapota(L.) D. Royen Sapodilla Mangifera indica L. Mango Murraya paniculata (L.) Jack Orange-jasmine Ocimum basilicum L. Sweet Basil Pelargonium x hortorum Bailey Geranium Pentas lanceolata (Forssk.) Deflers Graffiti White Persea americana Mill. Avocado

1 Reprinted with permission of Seal and Kumar 2010.

33

Table 1-2. Continued

Scientific name Common or trade name

Petunia x hybrida Petunia Easy Wave Red Pittosporum tobira (Thunb.) Ait. f. Variegated Pittosporum Plectranthus scutellarioides (L.) R. Br. Coleus Pouteria campechiana (Kunth) Baehni Canistel Rhaphiolepsis indica(L.) Lindl. ex Ker Gawl. Shi Ban Mu Ricinus communis L. Castor Bean Rhaphiolepis umbellate (Thunb.) Mak. Yeddo Hawthorn Richardia brasiliensis Gomes Brazil Pusley Rhododendron spp. Azalea Rosa X ‘Radrazz’ ‘Knockout®’ rose Salvia farinacea Benth. Victoria blue Schefflera arbicola (Hayata) Merr. Dwarf umbrella tree Strobilanthes dyerianus Mast. Persian shield Synsepalum dulcificum (Schumach. & Thonn.) Daniell Miracle fruit Tagetes patula L. Marigold Tradescatia zebrina hort. ex Bosse Wandering jew Vaccinium corymbosum L. Highbush blueberry Viburnum odoratissimum var. awabuki (K. Koch) Zabel Sweet viburnum Viburnum suspensum Lindl. Viburnum Viola x wittrockiana Gams Wittrock's violet Vitis vinifera L. Grapevine Zinnia elegans Jacq. Zinnia Profusion White Sources: Silgayi and Dixon 2006, Klassen et al. 2008, Osborne 2009, Kumar et al. 2012

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Table 1-32. Choices of insecticides for rotational use against S. dorsalis populations.

Common Name Trade Name IRAC Class Residual Control (days) Foliar Soil Adult Larva Adult Larva

Abamectin Agrimek®, Avid® 6 2a 2a

Acephate Orthene® 1B 7b 7b 7b 7b

Chlorfenapyr Pylon® 13 7a,b 7a,b - -

Dinotefuran Venom®, Safari® SG 4A 10 15 0 0 imidacloprid Marathon®, Provado®, 4A 15 15 15 15 Admire® Novaluron Pedestal®, Ramon® 15 7-14a, b 7-14 a, b - -

Spinosad Conserve®, SpinTor® 5 15 15 _ _

Spinetoram Radiant® 5 15 15 15 15

Thiamethoxam Actara®, Platinum® 4A 10 15 10 15

Borax + orange TriCon® 8D 10 10 - - oil + detergents

Beauveria Botanigard® Not applicable 3-7 b, c 3-7 b, c - - bassiana

Metarhizium Met52® Not applicable 7 c 7 c - - anisopliae a Seal et al. 2006b. b Bethke et al. 2010. c Seal et al. 2007.

2 Reprinted with permission of Seal and Kumar 2010.

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CHAPTER 2 SCIRTOTHRIPS DORSALIS (THYSANOPTERA: THRIPIDAE): SCANNING ELECTRON MICROGRAPHS OF KEY TAXONOMIC TRAITS AND A PRELIMINARY MORPHOMETRIC ANALYSIS OF THE GENERAL MORPHOLOGY OF POPULATIONS OF DIFFERENT CONTINENTS

Introduction

Scirtothrips dorsalis Hood commonly known as the Assam thrips, castor thrips, chilli thrips, berry thrips or yellow tea thrips (Dev 1964, Asaf- Ali et al. 1973, Seal and

Klassen 2005, Masui 2007b) is a highly polyphagous adventive pest species that originated in south Asia. With liberalization of trade in agricultural products and the historic growth in tourism during the past three decades, this tropical and subtropical pest has spread to all habitable continents except Europe. Scirtothrips dorsalis has been intercepted numerous times on various flower, fruit and vegetable consignments imported into Europe, but failed to establish a durable population on that continent

(Vierbergen and Gagg 2009). Recently an incursion was also noted in a glasshouse of a botanical garden in the United Kingdom, but eradication measures were taken and the pest was controlled successfully (A. Roy 2011; V. Kumar, personal communication). In the Americas, S. dorsalis gained its first foothold in Venezuela, where it has been causing damage to grapevine, Vitis vinifera L. (Vitaceae) since 2000(MacLeod and

Collins 2006, Seal et al. 2010). A few years later Skarlinsy (2003) found S. dorsalis established in St. Vincent and subsequently this species became widely distributed in the Lesser Antilles and Puerto Rico (Ciomperlik and Seal 2004) and Surinam

(Ciomperlik et al. 2005). In 2005, S. dorsalis became established in Palm Beach County

Florida on ‘Knockout’® rose (Rosa X ‘Radrazz’) (Coolidge 2005), and in three counties in Texas. Currently, S. dorsalis has established in 30 counties in Florida and eight counties in Texas with confirmations in Alabama and Louisiana in 2009 and New York

36

in 2010. In Florida, the pest rapidly distributed throughout the state via the retail trade industry of nursery plants. Osborne (2009) found this pest reproducing on more than 50 plant species in Florida.

Detection of S. dorsalis larvae and adults in fresh vegetation is difficult due to their thigmotactic behavior and tiny stature (larvae < 1 mm; adults < 2 mm). Eggs are deposited within plant tissues and may take a week for the larvae to emerge.

Consequently, chances of transportation of S. dorsalis through state, regional, and international trade of plant materials for all life stages is high (Seal and Kumar 2010). S. dorsalis life stages occur on meristems and other tender tissues of all above ground parts of the host plant. The feeding by this pest causes darkened scarring of extensive areas on various plant parts, stunted growth of young leaves, reduced yield and unmarketable fruit. Kuriyama et al. (1991) reported S. dorsalis to be a weak flier and that the most important route of invasion into the greenhouse was by introduction of infested pots but not aerial immigration. According to Meissner et al. (2005), the major pathways of spread of this pest are air passengers, crewmembers and their baggage, mail including mail delivered by express carriers, smuggled plant parts and windborne dispersal.

The Scirtothrips comprises more than 100 species of thrips. S. dorsalis is one of the most studied pests in the genus due to its economic importance and global distribution. Because of the small size of this thrips and morphological similarities in the genus, the identification to species is a challenge to non-experts. The morphological traits of taxonomic importance for identification of S. dorsalis are well defined in the literature. With slide mount images, Hoddle and Mound (2003) illustrated a taxonomic

37

identification key of S. dorsalis along with 20 other Scirtothrips species in Australia.

They noted that, of the 21 species of Scirtothrips, only S. aurantii and S. dorsalis have microtrichial fields extending fully across the sternites. In S. aurantii, the microtrichia almost cover the entire surface of the sternites, whereas in S. dorsalis they are restricted to a complete band across the posterior half of each sternite. Thus, a clear and accurate taxonomic characterization is required to distinguish between such species of Scirtothrips. The taxonomic traits of S. dorsalis by Skarlinsky (2004) and

Hoddle et al. (2009) illustrated with thrips slide mount images are very helpful.

Nevertheless, photographs taken at higher magnifications and resolutions using advanced techniques like Scanning Electron Microscopy (SEM) would be especially helpful to research, regulatory and extension personnel and, also, for teaching. The accurate and rapid identification of this invasive and potentially devastating pest is essential to implement effective plant quarantine and integrated control strategies.

A significant pathway of invasive pests into the Caribbean from south Asia were travelers whose ancestors had arrived from India as indentured servants following the abolition of slavery (Klassen et al. 2002). Many of these families traveled back and forth to visit relatives in India. Thus, the south Florida strain may have originated from the populations in India. However, when measurements of morphological features of the

Florida 2009 strain were compared to measurements of a population in India reported by Raizada (1976), five characters (body length, antennal length, prothorax length, forewing length and hind wing length) out of nine characters studied by Raizada were larger in the Florida (2009) strain. Conversely, three morphological characters (head length, abdomen width and ovipositor length) of the Florida population of S. dorsalis

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were smaller compared with the 1976 Indian population. Thus, there was merit in making a preliminary comparison of the measurements of the morphological traits selected by Raizada with corresponding measurements of traits of populations from different continents and other widely separated locations.

The objectives of this study were a) to produce high-resolution images of identifying characters of S. dorsalis adults and larvae using SEM, and b) to determine if certain morphological characters of S. dorsalis adults differ significantly in size among populations from different geographic regions of the world.

Materials and Methods

The year of sample collection, geographical location (longitude and latitude), host plant, preservative, and sample source are reported in Table 2-1. Samples of S. dorsalis were obtained from five geographic regions: New Delhi, India (2008); Shizouka,

Japan (2009); St. Vincent Island, West Indies (2006); Negev, Israel (2009); and Florida,

USA (2009). Florida population of S. dorsalis was collected from an established colony in the greenhouse; New Delhi and St. Vincent populations were collected directly from the field. However, no site collection information was provided about Negev and

Shizouka populations. The specimens from New Delhi, India reported by Raizada in

1976 were sampled from cotton (Gossypium hirsutum L.), castor (Ricinus communis L.), pepper (Capsicum spp.) and other crops. Actual sample techniques depended on the individual sampler, but, once adults were collected, they were immediately placed in 70-

95% ethanol and eventually mailed to the Tropical Research and Education Center,

UF/IFAS, Homestead, Florida where they were maintained at -20°C until processed for slide mounting and morphometric analysis.

.

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Identification of Specimens

Adult female thrips specimens were transferred to vials containing 75% alcohol for

10 min and then for 5 min to a 10% KOH (potassium hydroxide) solution prepared in

50% ethanol. While placed in KOH solution, the insect was gently pounded in the abdominal region using a fine insect pin to aid the in the removal of its abdominal contents. For gradual dehydration, the specimens were passed through a series of alcohol concentrations starting from 65%, followed by 75%, 85%, 90% and 95% for 5-8 min in each concentration. Each specimen was placed ventrally on a slide with a small drop of Hoyer’s mounting media and covered with a glass cover slip. The specimens were identified and their morphological traits were compared using taxonomic characteristics described by Hoddle and Mound (2003), Skarlinsky (2004) and Hoddle et al. (2009) using a dissecting microscope at a minimum of 10X magnification.

Furthermore, S. dorsalis samples (adults and larvae) collected from Florida were morphologically characterized using scanning electron microscopy to produce high quality pictures, displaying the features used for identification. Larvae were identified using the taxonomic keys of Vierbergen et al. (2010).

Scanning Electron Microscopy

Adult S. dorsalis females and larvae from Florida were collected in 30% ethanol and dehydrated in a graded series of 50%, 70%, 95%, and twice in 100% ethanol for 30 min in each gradation. Samples were kept in 100% ethanol overnight. On the next d, samples were dried in 50% and 100% of hexamethyldisilizane (HMDS:ethanol) for 30 min each. Dehydrated samples were placed on stubs consisting of black sticker using fine forceps. Thereafter, samples were sputter coated with gold/palladium using the

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Hummer sputtering system (Anatech, USA) and subsequently examined under a Hitachi

S-4800 SEM operated at 10-12 kV.

Morphometric Measurements of Major Body Traits

Fourteen morphological characters were studied in the five populations of S. dorsalis and the results were compared with the measurements previously reported by

Raizada (1976). Raizada (1976) subjected nine characters of S. dorsalis adults to morphometric analysis and in the present study; measurements of the pro, meso, and meta thorax were added for comparisons.

Ten female specimens were selected from each of the five populations for morphometric analysis. Specimens of S. dorsalis were placed individually on microscope slides with a drop of water: ethanol (50:50) to protect the specimen from dehydrating. The specimen was spread before measurements were taken. Fourteen morphological traits were quantified by measuring the lengths of the body, antennae, head, prothorax, mesothorax, metathorax, ovipositor, forewing and hind wing; and the widths of the head, abdomen, prothorax, mesothorax, and metathorax (Table 2-2) using an automontage advanced photography software program (Auto-Montage Pro software, version 5.02, Syncroscopy, Frederick, MD) and a Leica MZ 12.5 stereomicroscope.

Statistical Analysis

Data on the measurement of various body parts of thrips pertaining to different geographical regions were subjected to the square root (x + 0.25) transformation to stabilize variance. Transformed data were analyzed using one-way analysis of variance

(ANOVA, SAS Institute Inc. 2003). The differences among means of length and width of body segments were separated using Tukey’s HSD procedure (P < 0.05).

Untransformed means and standard errors are reported in Table 2-2.

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Results

Identification of Specimens

The results of the scanning electron microscopy investigation are depicted in

Figures 2-2 to 2-9 (adult) and 2-10 to 2-15 (larva). Selected characters were used for positive identification and morphological comparison of S. dorsalis populations prior to morphometric analysis. The body of adult S. dorsalis is pale yellow in color and bear dark brown antecostal ridges (AR) on tergites and sternites (Figure 2-1). The head is wider than long, bearing closely spaced lineations and a pair of eight segmented antennae with a forked sensorium on each of the third and fourth segments (Figure 2-

2). Of the three pairs of ocellar setae, the third pair, also known as the interocellar setae

(IOS), arises between the two hind ocelli (HO) (Figure 2-3) and is nearly the same size as the two pairs of post ocellar setae (POS) on the head. The pronotum presents closely spaced horizontal lineation (Figure 2-4). The pronotal setae (anteroangular, anteromarginal and discal setae) are short and approximately equal in length. The posteromarginal seta-II is broader and 1.5 times longer than the posteromarginal setae-I and III. The posterior half of the metanotum presents longitudinal striations; medially located metanotal setae arise behind the anterior margin and campaniform sensilla are absent (Figure 2- 5). The forewings are distally light in color with posteromarginal straight cilia on the distal half and the first and second veins bear three and two widely spaced setae, respectively (Figure 2-6). Abdominal tergites III to VI, each present a pair of small medially located setae (Figure 2-7). The posteromarginal comb on segment VIII is complete and tergite IX exhibits medially located discal microtrichia (Figure 2-8).

Discal setae are absent on sternites and sternites are covered with rows of microtrichia, excluding the antero-medial region (Figure 2-9).

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Several morphological characters can be used for identification of S. dorsalis larvae. D1 and D2 setae present on the head and abdominal terga IX of larvae are simple and funnel-shaped, respectively (Figure 2-10 and 2-11), while the D1 setae on terga X are funnel shaped. The larval pronotum is reticulated and has 6-7 pairs of pronotal setae present (Figure 2-12). Abdominal segments IV-VII of larvae have a total of 8-12 setae each (Figure 2-13). The distal two thirds of the forefemora of larvae possess four funnel shaped setae (Figure 2-14) and the body of larvae possess granular plaques (Figure 2-15).

Morphometric Measurements of Major Morphological Features

No significant differences were detected among the five S. dorsalis populations for nine of the morphological characters measured in this study, i.e., body length, antennal length, length of head, width of head, length of prothorax, width of prothorax, length of ovipositor and lengths of the forewings and the hindwings (Table 2-2). However, statistically significant differences were detected among the five populations for mesothorax (length and width), metathorax (length and width) and width of abdomen characters.

New Delhi, India (2008) Population. The population from New Delhi did not differ significantly from the Florida, St. Vincent or Negev populations for any of the morphological characters under consideration. Significant differences were detected between this population and the population from Shizouka in that both the metathorax length and abdomen width were smaller in the New Delhi population (Table 2-3).

The mean lengths of the antennae of the New Delhi (1976) population were numerically very similar to those of the Negev (2009) population, but shorter than those of all the other populations in this study. However, the differences in the measurements

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of all the remaining traits between the New Delhi (1976) and the other populations in this study were numerically small.

Florida, USA (2009) Population. The Florida population was not significantly different from the populations of New Delhi or Negev for any of the 14 morphological characters that were measured (Table 2-3). The Florida population was characterized by a significantly smaller metathorax than the St. Vincent population, but there were no significant differences between these two populations for the other 13 characters that were measured. Five morphological characters of the Florida population were significantly smaller than the Shizouka population. These differences were most significant with respect to the lengths and widths of the mesothorax, metathorax and width of abdomen (Table 2-3).

St. Vincent Island, West Indies (2006) Population. The St. Vincent population had a significantly longer metathorax than the populations from Florida and Negev and a significantly narrower abdomen compared with Negev and Shizouka populations.

Shizouka, Japan (2009) Population. The S. dorsalis population from Shizouka differed significantly from the other four populations for 2 or 5 morphological characters, depending on the population, suggesting that the Japan population is more robust (i.e., mesothorax and metathorax are longer and wider, and abdomen is wider) (Table 2-3).

The metathorax was longer and the abdomen was wider than the New Delhi population.

Further, the Shizouka population had a wider mesothrorax, metathrorax and abdomen, and longer mesothrorax and metathorax than the Florida population. The metathorax and abdomen of Shizouka were also wider than the St. Vincent population.

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Furthermore, the Shizouka population mesothorax was wider and metathorax longer compared with the Negev population.

Negev, Israel (2009) Population. The population from Negev did not differ statistically from the New Delhi (2008) and Florida (2009) populations in any of the morphological traits under study, but differed significantly in two features with St.

Vincent (metathorax length and abdominal width) and Shizouka populations

(mesothorax width and metathorax length).

Discussion

Since its development in the early 1950’s, SEM is considered as an efficient morphological identification tool with numerous advantages over traditional microscopy; i) large depth of field, ii) much higher resolution than light microscopy and iii) because

SEM uses electromagnetism instead of lenses, specimens can be magnified to much higher levels. Thus, the observer has better control of the degree of magnification of the specimen understudy (Schweitzer 2010). Nevertheless, the use of SEM in taxonomic characterization of Thysanopteran insects is limited. High-resolution pictures of S. dorsalis using the SEM techniques will help research, regulatory and extension personnel to identify this pest with great ease without extensively using complex taxonomic keys. SEM produced figures provide information about all the major identification characters of this pest. Two species of the genus Scirtothrips, S. aurantii and S. dorsalis are unusual in having sternites covered with microtrichia (Hoddle and

Mound 2003, Hoddle et al. 2009). SEM figure 2-9 clearly shows the band of microtrichia continuous only across the posterior half of the S. dorsalis sternite, a feature that differentiates this pest not only from S. aurantii, but, insofar as is known, from all other species of Scirtothrips.

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No major differences were observed in the body lengths of S. dorsalis adults recently collected from the five regions. Mean body lengths ranged from 0.85 mm

(Negev population) to 0.98 mm (Florida population). The mean length of adults collected from New Delhi, India in 2008 was greater than the length previously reported by Raizada (1976) (0.91 and 0.76 mm, respectively). The mean body length of the

Florida (2009) population is 0.223 mm longer than that of the New Delhi (1976) population. Likewise, the mean antennal length of the Florida (2009) population of S. dorsalis is 0.016 mm longer than that of the New Delhi (1976) population. These differences may be attributed to a possible role of the feeding and reproductive hosts in regulating body size of the pest.

Insects regulate their body size in response to the temperature surrounding them, which is often associated with elevation and latitude (Blanckenhorn and Demont 2004,

Tantowijoyoa and Hoffmann 2011). Some studies suggest that there can be positive correlations between elevation and latitude and body size (Smith et al. 2000). Other studies suggest there is no correlation, or even a negative correlation between sizes of body traits and elevation and latitude (Kubota et al. 2007, Hawkins and DeVries 1996).

Variation in size can affect fitness traits like development and reproduction (Berger et al.

2008, Tammaru et al. 2002), somatic and sexual growth (Blanckenhorn 2006, Fischer et al. 2003), thermoregulation (Bishop and Armbruster 1999) and dispersal ability

(Gutierrez and Menendez 1997). At high temperatures, some populations of thrips species acquire a smaller and paler form, and at low temperatures, they tend to be large and dark in color (Murai and Toda 2001, Hoddle et al. 2009). However, results from the present study did not suggest any significant impact of temperature on body size of S.

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dorsalis collected from the five regions, but no detailed information on temperatures during the times of collection were provided.

According to Björkman et al. (2009) body size within certain taxonomic groups tends to increase with latitude (Bergmann clines), while in certain other groups insect body size decreases (converse Bergmann clines), and in yet others tends to stay relatively constant with latitude. In this study, the populations were from the following latitudes: St. Vincent, West Indies: 13.35 N; Homestead, Florida: 25.48 N; Delhi, India:

28.38 N; Negev, Israel: 34.67 N; and Shizouka, Japan: 36.00 N. On comparing the measurements of individuals from five regions, the body lengths of S. dorsalis in these samples did not vary either directly or inversely with latitude (Table 2-2).

All of the specimens recently obtained from New Delhi, Florida, St. Vincent and

Negev were collected from pepper, but the Shizouka thrips population were collected from tea. Since tea was not a host plant of the other four populations sampled in this study, it could not be determined if host plants directly affected morphology.

Nevertheless, the Shizouka population differs significantly from the other populations by having a longer and wider mesothorax and metathorax and an abdomen that is wider, which is an essential morphological character of females that allows them to produce more eggs and have higher fecundity and greater fitness (Benitez et al. 2010). In a concurrent experiment conducted to determine the effect of host plant on the growth of

S. dorsalis, the pest was reared under identical conditions at Homestead, Florida on six different hosts, i.e., ‘Jalapeño’ pepper (Capsicum annuum L.), ‘Pod Squad’ bean

(Phaseolus vulgaris L.), ‘Black Beauty’ eggplant (Solanum melongena L.), ‘Butternut’ squash (Cucurbita moschata [ex Duchesne Lam.] Duchesne ex Poir.), ‘Solar Set’

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tomato (Solanum lycopersicum L.) and ‘Knockout’ rose (Rosa chinensis Jacq.) (Seal et al. 2010). Body lengths and widths of different development stages (10 individuals each) were measured, and no significant differences in body size of this pest were observed when S. dorsalis was reared on these six different hosts, indicating that these host plant species did not differentially induce size alterations in S. dorsalis.

The results from the present study suggest that the Japan population may have diverged the most from the ancestral population in south Asia. The Japan population does not appear to be ancestral to the populations in the Americas or Israel based on morphometric differences. The population in India may be ancestral to the populations in the New World and Israel and could have been facilitated by the extensive movement of people between India and Israel, and India and the Caribbean. In addition, Israel has commercial horticultural ventures in the Greater Antilles. Thus, movement of S. dorsalis from India to Israel and subsequently to the Caribbean cannot be ruled out. It would be interesting to determine whether there are substantial genetic or behavioral differences, and even barriers to reproduction, between the Shizouka and New Delhi populations as well as between the Shizouka and Florida populations.

Using the automontage system did not appear to introduce inordinately large errors caused by failure to have each specimen mounted perfectly within the horizontal plane. Each measurement was repeated on 10 different individuals, and it is well known that small experimental errors tend to cancel each other. Morphometric analysis is an efficient tool that is being utilized for identification, determination of larval instar, and discrimination of cryptic species of several insect species including leaf miners, bees, beetles, and aphids, (Daly 1985, Ellis and Ellis 2008, Favret 2009, Shibao 2004,

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Tantowijoyoa and Hoffmann 2011), but has rarely been utilized for thrips. This is because thrips body size and color are known to be phenotypically plastic in response to changing environments, which can occur across both small and large spatial scales

(Sakimura 1969, Murai and Toda 2001, Mound 2005). It may be important to collect live populations from different regions and rear them under identical environmental conditions in order to ascertain if the apparent stability of morphological traits has a genetic basis. Future research will concentrate on direct correlation of morphometric analyses with molecular analyses of the same individual to validate the hypothesis that the Japan population is not ancestral to populations in the four other regions.

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Table 2-1. Scirtothrips dorsalis populations by year collected, geographical location, host plant, preservative and specimen source.

Year Geographical location Host Preservative Source of specimens collected (latitude and longitude)

1976a India- New Delhi; 28.38 N, 77. 12 E Variousb 70% alcohol Dr. Usha Raizada, University of Delhi, India

Dr. D. R. Seal, University of Florida, 2008 India- New Delhi; 28.38 N, 77. 12 E Pepper 95% ethanol Homestead, Florida, USA

Mr. M. L. Richards, Ministry of Agriculture St. Vincent Island, West Indies; 13.15 N, 2006 Pepper 70% ethanol and Fisheries, St. Vincent and the 61.12 W Grenadines, West Indies

United States- Homestead, Florida; Mr. V. Kumar and Dr. D. R. Seal, University 2009 Pepper 70% ethanol 25.28 N, 80.28W of Florida, Homestead, Florida, USA

Dr. Phyllis Weintraub, Entomology Unit, 2009 Israel- Negev; 30.50 N, 34.91 E Pepper 95% ethanol Gilat Research Center, D. N. Negev 85280, Israel

Dr. Masui Shinichi, Shizuoka Prefectural 2009 Japan- Shizouka; 34.55 N, 138.19 E Tea 95% ethanol Research Institute of Agriculture and Forestry Tea Research Center, Japan aPopulation previously reported by Raizada (1976) bMexican marigold (Tajetes erecta L.), pepper (C. annum), cotton (Gossypium spp.), castor (Ricinus communis L.), and many others

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Table 2-2. Measurements of fourteen morphological characters from five different populations of Scirtothrips dorsalis.

Morphological Character Mean (mm) ± SEM by Population (year collected) Morphological India (1976) New Delhi India Florida (2009) St. Vincent Island Shizouka Negev Israel Character (2008) (2006) Japan (2009) (2009) Body L 0.757 ± 0.021 0.912 ± 0.025a 0.980 ± 0.30a 0.871 ± 0.015a 0.873 ± 0.015a 0.856 ± 0.029a Antennal L 0.189 ± 0.001 0.198 ± 0.002a 0.206 ± 0.005a 0.196 ± 0.004a 0.218 ± 0.005a 0.182 ± 0.004a Head L 0.066 ± 0.002 0.052 ± 0.004a 0.054 ± 0.002a 0.062 ± 0.002a 0.060 ± 0.002a 0.054 ± 0.002a Head W 0.119 ± 0.002 0.120 ± 0.003a 0.111 ± 0.001a 0.120 ± 0.002a 0.120 ± 0.002a 0.122 ± 0.006a Prothorax L 0.086 ± 0.002 0.086 ± 0.005a 0.098 ± 0.003a 0.088 ± 0.004a 0.099 ± 0.003a 0.098 ± 0.003a Prothorax W ----- 0.142 ± 0.003a 0.141 ± 0.003a 0.146 ± 0.003a 0.147 ± 0.004a 0.145 ± 0.003a Mesothorax L ----- 0.055 ± 0.004ab 0.043 ± 0.001b 0.048 ± 0.004ab 0.056 ± 0.003a 0.048 ± 0.002ab Mesothorax W ----- 0.164 ± 0.004ab 0.149 ± 0.004b 0.166 ± 0.008ab 0.179 ± 0.006a 0.153 ± 0.006b Metathorax L ----- 0.098 ± 0.003bc 0.097 ± 0.002c 0.108 ± 0.003ab 0.112 ± 0.006a 0.097 ± 0.004c Metathorax W ----- 0.166 ± 0.004ab 0.160 ± 0.002b 0.162 ± 0.004b 0.181 ± 0.005a 0.176 ± 0.006ab Abdomen W 0.200 ± 0.004 0.192 ± 0.003bc 0.193 ± 0.005bc 0.182 ± 0.005c 0.213 ± 0.005a 0.207 ± 0.005ab Ovipositor L 0.156 ± 0.003 0.146 ± 0.003a 0.140 ± 0.004a 0.146 ± 0.004a 0.139 ± 0.004a 0.134 ± 0.005a Forewing L 0.511 ± 0.016 0.514 ± 0.011a 0.523 ± 0.012a 0.512 ± 0.010a 0.509 ± 0.012a 0.513 ± 0.017a Hind wing L 0.441 ± 0.012 0.458 ± 0.011a 0.467 ± 0.011a 0.460 ± 0.012a 0.459 ± 0.013a 0.461 ± 0.017a All data were analyzed using analysis of variance (ANOVA) procedures with the exception of the India (1976) population previously reported by Raizada (1976). Means were separated using Tukey test at the 0.05 level of significance. Means followed by same letter within a row are not significantly different (P ≤ 0.05).

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Table 2-3. Number of traits in which significant quantitative differences occurred between the various geographic populations of Scirtothrips dorsalis when compared two at one time.

St. Vincent India 2008 Florida 2009 Israel 2009 Japan 2009 2006 India 2008 X 0 0 0 2 Metathorax L Abdomen W

Florida 2009 0 X 1 0 5 Metathorax L Mesothorax L Mesothorax W Metathorax L Metathorax W Abdomen W

St. Vincent 0 1 X 2 2 2006 Metathorax L Metathorax L Metathorax W Abdomen W Abdomen W

Israel 2009 0 0 2 X 2 Metathorax L Mesothorax W Abdomen W Metathorax L

Japan 2009 2 5 2 2 X MetathoraxL Mesothorax L Mesothorax W Mesothorax W Abdomen W Mesothorax W Abdomen W Metathorax L Metathorax L Metathorax W Abdomen W

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Figure 2-1. Slide mount of S. dorsalis female showing dark brown antecostal ridge (AR) on tergites.

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Figure 2-2. Eight segmented antennae with third and fourth segments each possessing forked sensorium.

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Figure 2-3. Dorsal view of S. dorsalis head with ocellar triangle, interocellar setae (IOS), hind ocelli (HO) and postocular setae (POS).

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Figure 2-4. Pronotum of S. dorsalis exhibiting horizontal closely spaced sculpture lines.

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Figure 2-5. Posterior half of the metanotum presents longitudinal striations; medially located metanotal setae arise behind anterior margin, campaniform sensilla are absent.

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Figure 2-6. Shaded forewing of S. dorsalis is distally light in color with first and second vein possessing three and two widely spaced setae, respectively.

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Figure 2-7. Abdominal tergites III to VI of S. dorsalis possess small setae medially situated close to each other.

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Figure 2-8. The posteromarginal comb (row of microtrichia) on segment VIII is complete.

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Figure 2-9. Discal setae absent on sternites, sternites covered with rows of microtrichia with the exception of the antero-medial region.

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Figure 2-10. Simple D1 and funnel-shapped D2 setae on the head of a S. dorsalis larva.

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Figure 2-11. Funnel shaped setae on abdominal terga IX and X of a S. dorsalis larva.

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Figure 2-12. Reticulated pronotum of a S. dorsalis larva illustrating the presence of 6-7 pairs of pronotal setae.

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Figure 2-13. Abdominal segments IV-VII of a S. dorsalis larva illustrating the presence of 8-12 setae each.

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Figure 2-14. Forefemora of a S. dorsalis larva illustrating the presence of four funnel shaped setae on the distal two-thirds portion.

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Figure 2-15. Body of a S. dorsalis larva indicating the presence of granular plaques.

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CHAPTER 3 COUPLING SCANNING ELECTRON MICROSCOPY WITH DNA BAR CODING FOR MORPHOLOGICAL AND MOLECULAR IDENTIFICATION OF THRIPS

Introduction

Changing climatic conditions and globalization has resulted in increasing invasive species as a recurrent problem around the globe (Masters and Lindsay 2010). During international trade of plants and , importers pay a price to the exporter for their costs of production and transport, but neither party pays costs associated with invasion risk (Perrings et al. 2005). A recent study by Pimentel et al. (2005) concludes that more than 50,000 non indigenous species have already been introduced in the United States accounting for annual damage of more than $120 billion. Several states in the USA, including Florida and Hawaii, have always been prone to invasion by non-indigenous species where more than 25% of groups are non-native (Simberloff 1996).

These invasive species, facing no challenge by their natural enemies, thrive in the new environment (Chenje and Mohamed-Katerere 2006). In addition to the disturbance they cause to the biodiversity of agro-ecosystems, they pose a significant detrimental impact on the economic value of crops (Pimentel et al. 2000, Reitz and Trumble 2002). Correct identification and determination of the possible pathway of introduction of such pests are a basic requirement in the development of any effective quarantine and pest management strategy.

In the United States, Scirtothrips dorsalis Hood (Thysanoptera: Thripidae) is a newly introduced pest species of various tropical and subtropical crops that poses a significant economic threat to U.S. agriculture and trade (Farris et al. 2010). Since the introduction of S. dorsalis into Florida in 2005, the pest dispersed rapidly across the state and is causing significant economic damage to horticultural and nursery

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production (Seal et al. 2010). In 2007, the top two counties in agricultural sales in

Florida were Palm Beach and Miami Dade, contributing around 931 and 661 million dollars, respectively (ERS-USDA 2008). These two counties were also among the 15 counties in which S. dorsalis was reported to have been established in 2005 (Silagyi and Dixon 2006). Successful establishment of S. dorsalis on its preferred hosts in these counties could have a significant impact on agriculture production in the state.

According to an economic analysis, even a loss of 5% due to this pest could result in a

$3 billion loss to the US economy (Garrett 2004). Thus, it is essential to take necessary measures in order to limit the economic impact of this pest.

The small size (< 2 mm in length) and thigmotactic behavior of S. dorsalis, makes monitoring and detection of this pest difficult in fresh vegetation. Various life stages of S. dorsalis can be found on the meristems and other tender tissues of all above ground parts of their host plants. Because eggs are deposited inside the plant tissues and may take 6-8 days to hatch (Seal et al. 2010), the probability of dissemination of S. dorsalis through state, regional and international trade of plant materials is high for all life stages. Within five years of the introduction of S. dorsalis into the U. S., establishment has been confirmed in 30 counties of Florida and eight counties of Texas, with additional positive reports of the interception of this pest in Georgia, New York,

Alabama, Louisiana and California (Kumar et al. 2011). Recently, the pest was reported to be damaging 12 different crops in a fruit nursery in south Florida, including crops not previously reported as hosts, demonstrating that this pest is increasing its host range

(Kumar et al. 2012).

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Development of effective management practices of S. dorsalis populations will depend upon clarifying the , biology and ecology of this species. The biology, host preference, distribution and chemical control of this pest have been reported previously (Seal et al. 2006a, Seal et al. 2010, Seal and Kumar 2010). Correct identification of thrips, including S. dorsalis, has always been difficult due to their small size and cryptic nature (Farris et al. 2010). Using traditional taxonomic keys, adult thrips are identified to genus, but due to the intraspecific morphological variations in many species, identifying them to species requires substantial expertise (Rugman-Jones et al.

2006). For many taxa of thrips it is impossible to assign an immature to a particular species in the absence of adults (Brunner et al. 2002). Therefore, an accurate standard method is desirable to validate the species designations of thrips larvae as well.

Taxonomists involved with identification of Thysanoptera, mount specimens on slides for morphological identification under a light microscope. Mounting specimens on slides is often time consuming and labor intensive, and requires expertise and knowledge of distinct characters visible through microscopy (Bisevac 1997). The method also involves the risk of specimen collapse and the disintegration of specimens can have a devastating impact on projects involving the global collection and identification of pest species. The use of genetic markers offers an additional tool to supplement the phenotypic identification of thrips specimens. The integration of morphological and genetic marker techniques for identification of thrips has certain limitations. First, a sufficiently large number of specimens are required in order to confirm identifications using both techniques. Second, when a mixed population of thrips specimens labeled as one species (which is very common) is received, then

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morphological identification data do not corroborate with molecular identification. Third, sometimes only larvae of any thrips population are available for identification.

Since the development of the scanning electron microscope (SEM) in the early

1950’s, the technique has been used for morphological identification. SEM provides many advantages over traditional microscopy including a larger depth of field, a higher resolution and a higher level of magnification (Schweitzer 2010). These characteristics of SEM can be coupled with genetic marker techniques to develop a simple, reliable, robust tool for accurate identification of larval and adult thrips by closely studying their morphological characters with confirmation of species diagnosis with DNA bar coding using the same speciman. Because individual specimens can be used for both morphological identification using SEM and for molecular identification using polymerase chain reaction (PCR), the aforementioned limitations associated with using traditional morphological identification integrated with molecular identification are reduced. Thus, the specific objective of this study was to develop methodology for S. dorsalis identification that allowed comparing the morphological characters using SEM and the molecular PCR based assay utilizing the same individual (larva or adult) so that results could be directly correlated.

Materials and Methods

Morphological Identification

Larvae and adults samples of S. dorsalis subjected to morphological characterization under scanning electron microscope in the previous study (chapter 2), were used in this study. High quality pictures, displaying features used for S. dorsalis identification were obtained for photo-documentation of the specimens. Larvae were identified using the keys of Vierbergen et al. (2010), and adult female thrips were

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identified using taxonomic characteristics described by Skarlinsky (2004) and Hoddle et al. (2009).

Molecular Identification

After morphological identification of S. dorsalis adults and larvae, gold/palladium sputter coated specimens were removed from each stub using a fine forceps and were placed in 95% ethanol for 15 min before proceeding to their DNA extraction. Sputter coated adult females and larvae were subjected to DNA extraction by placing specimens individually into 1.5-ml labeled Eppendorf tubes, adding 50 µl of DNA lysis buffer (De Barro and Driver 1997, McKenzie et al. 2009), and grinding the specimen with a plastic pestle. Tubes were placed in a metal boiling rack and boiled at 95°C for 5 min and were then placed directly on ice for 5 min. Tubes were centrifuged at 8,000 × g for 30 s, and the supernatant (crude DNA lysate) was transferred to another labeled tube and stored at -80°C until further analysis. Aliquots from the same individual thrips

DNA extract were used for molecular identification to confirm morphological identification data.

PCR protocol and sequencing

PCR amplifications for the mtCO1 gene and ITS2 rDNA were performed separately using universal mtCO1 (Folmer et al. 1994) and Thrips-ITS2 (Campbell et al.1993, Toda and Komazaki 2002, Rugman-Jones et al. 2006). The 25 µl PCR reactions for CO1 and ITS2 gene consisted of 12.5 µl of go Taq PCR mastermix

(Promega Corporation, Madison, USA) and 2 µl of DNA template and 10 pmol of each primer.The PCR reactions were run using the conditions described in Table 3-1, in a

PTC-200 Peltier thermal cycler (MJ Research, Watertown, MA). The amplified products were cleaned using ExoSAP-IT PCR Clean-up Kit (GE Healthcare Limited, Amersham,

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UK) following the recommended protocol. Samples were sequenced after dilution of the cleaned sample with 15 µl of water. The process was repeated twice to get a concordant reliable result.

Fifty nanograms of total thrips genomic DNA was used in BigDye sequencing reactions. All sequencing was performed bidirectionally with the amplification primers and BigDye Terminator cycle sequencing kits (Applied Biosystems, Foster City, CA) at the Genomics Core Instrumentation Facility of USHRL-USDA, Fort Pierce, FL.

Sequence reactions were analyzed on an Applied Biosystems 3730XL DNA sequence analyzer, and compared and edited using Sequencher™5.0- Build 7081 (Gene Codes

Corporation, Ann Arbor, MI). Thrips species determination was based on direct sequence comparisons using the web-based National Center for Biotechnology

Information BLAST sequence comparison application

(http://blast.ncbi.nlm.nih.gov/Blast.cgi).

Results and Discussion

The results of sequencing both mtCO1 and ITS2 rDNA of individual larvae and adult thrips concurred 100% with the positive controls (known S. dorsalis specimens)

(Figure 3-1) and with the morphological identification using SEM. PCR reactions repeated twice also confirmed the concordant results (Figure 3-1), suggesting that coupling SEM morphological and molecular identification techniques can be accurately and efficiently used for detecting larvae and adults of S. dorsalis. The methodology would likely be useful in identifying different thrips genera, even to the species level.

Sequences obtained were deposited in Genbank with successive accession numbers

JN578861 and JN578862.

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Misidentification of thrips specimens using molecular identification based on genetic information available in databases such as Genbank and EMBL is very common

(Porco et al. 2010) until a voucher specimen or photo-documentation is available to confirm the identity. The current study was undertaken to improve the identification of S. dorsalis larvae and adults by coupling both morphological and molecular identification techniques using the same specimen. The figures 2-1 to 2-15 along with figure captions explains the keys features important for taxonomic identification of S. dorsalis adult and immature stages. The high-resolution SEM pictures of S. dorsalis produced in the previous study can be effectively used by research, regulatory and extension personnel to identify this pest with greater ease.

Although SEM has numerous advantages over light microscopy, its use in taxonomic identification of thrips has not been widely explored (Chandra and Verma

2010). Lack of sufficient phenotypic variation among closely related thrips species or the limitation of light microscopy to characterize these variations (Brunner et al. 2002) can often lead to misidentification of thrips specimens. In such cases, the qualities of SEM may be useful to distinguish between two species. The correct identification of a pest species is essential to assure that appropriate management strategies are employed.

Because different thrips species might differ in susceptibility to different insecticides, failure to correctly identify the problematic thrips and to correctly select the most efficacious insecticide might result in decreased yields and exports of harvested crops

(Timm et al. 2008). Thus, utilization of SEM in taxonomic identification of these minute insects can supplant or enhance traditional taxonomic identification techniques.

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The use of genetic markers is becoming more fully integrated with classical taxonomic techniques for identification of species of interest. Integration of these techniques has enhanced the quality of diagnostic tools, which has resulted in the discovery of new species and in the understanding of inter- and intra-species variability among the species (Carew et al. 2011).

Accurate identification of a pest is necessary to access previously reported biological information concerning the organism and becomes extremely important when the study organism is a part of cryptic species complex (Rugman-Jones et al. 2010). In a recent study, Hoddle et al. (2008) reported that S. dorsalis collected from three different regions of the world were morphologically identical but were genetically distinct, and the genetic diversity in the species was extensive. Often taxonomic identification is conducted using a compound microscope at maximum magnification of

650 to 1,000 times, which may be a limitation in identifying additional information needed to differentiate two morphologically similar thrips species. SEM can magnify an entire specimen or a particular body area of a specimen up to 500,000 times, which can be crucial in searching for new morphological characters to differentiate among cryptic species or a species complex within a thrips population.

Compared to other available integrated methods of insect identification, such as sonication of specimens for DNA extraction (Hunter et al. 2008) or the automated high- throughput DNA protocol (Porco et al. 2010), the current novel technique is simple and quick, utilizes fewer specimens for identification, provides high yield of DNA and can be easily mastered by non-experts. Another integrated technique available for thrips identification involves piercing the abdominal region of the specimen using a minute pin

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and processing the extracted gut content for molecular identification prior to the slide mount (Rugman-Jones et al. 2006). This method requires great skill to keep the specimen intact and save the specimen for slide preparation. Because thrips are soft- bodied, minute insects, specimens can be damaged while puncturing the abdomens or during slide preparation. In the method reported here, an unknown thrips specimen

(larva/adult) can be identified at higher magnification using SEM and then the same gold/palladium sputter-coated specimen can be used directly for DNA extraction. In addition, the high magnification of SEM can be efficiently used for taxonomic identification of thrips larvae in the absence of adults, which can be further confirmed using the genetic marker tool. Thus, the method can conserve specimens and avoid problems concerning mixed sample populations. Future research will concentrate on making the method more economical and more efficient in order to increase wider adoption of the method.

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Table 3-1. PCR amplification conditions for two genes of Scirtothrips dorsalis.

PCR Primer Set PCR amplification conditions (25-µl reactions) mtCO1 primers 94°C 2 min LCO1490:5'-GGTCAACAAATCATAAAGATATTGG-3' 35 cycles of HCO2198: 5'-TAAACTTCAGGGTGACCAAAA AATCA-3' 94°C 30 s 54°C 1 min 72°C 1 min 72°C 10 min ITS2 primers 94°C 2 min ITSF: 5'-TGTGAACTGCAGGACACATG-3' 35 cycles of ITSR- 5'AATGCTTAAATTTAGGGGGTA-3' 94°C 30 s 48°C 1 min 72°C 1 min 72°C 10 min

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Figure 3-1. Agarose gel showing PCR results using the ITS2 primers and mtCO1 primer set for the detection of S. dorsalis. The marker fragment was successfully amplified from S. dorsalis DNA (lanes 2- 5 and 9-12). Lanes 1 and 8 are the 1Kb DNA ladders. Lanes 2, 3, 9, and 10 are S. dorsalis adults. Lanes 4, 5, 11, and 12 are S. dorsalis larvae. Lanes 6 and 13 are negative controls and lanes 7 and 14 are positive controls (known specimens of S. dorsalis).

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CHAPTER 4 INTRAGENOMIC VARIATION IN mtCO1 AND rDNA ITS2 OF THREE MAJOR THRIPS SPECIES, SCIRTOTHRIPS DORSALIS, THRIPS PALMI AND FRANKILINIELLA OCCIDENTALIS (THYSANOPTERA: THRIPIDAE)

Introduction

Correct identification is a fundamental step in the development of sound management practices against a pest. Identification helps in attaining previously reported information against the subject species (Rugman-Jones et al. 2010) that supports in planning and implementation of an appropriate biological research strategy.

The morphological identification of various species in the order Thysanoptera can be difficult because of the high degree of polymorphism within and among species (Murai and Toda 2001, Hoddle et al. 2009, Kakkar et al. 2011), the similarity in developmental stages of different species (Brunner et al. 2002), and the lack of taxonomic experts to differentiate thrips specimens to the species level (Asokan et al. 2007). The presence of cryptic species makes identification more difficult because the delimiting boundary between two species is unknown (Hoddle et al. 2008, Rugman-Jones et al. 2010).

However, molecular identification is not limited by these factors (Asokan et al. 2007); it is cost effective, rapid, and can be accomplished by non-taxonomic experts (Rubinoff et al. 2006). Various molecular markers have been developed for use in species determination. These include several nuclear genes (i.e, 16S rRNA, 18S rRNA, 28S

RNA ) (Barr et al. 2005) and internal transcribed spacers (rDNA ITS) (Rugman-Jones et al. 2006), as well as the mitochondrial cytochrome c oxidase 1 (mtCO1) gene (Rugman-

Jones et al. 2010).

A portion of the mtCO1 gene is widely used as a DNA barcode for taxon characterization of animals i.e., taxon identification, species delimitation and

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phylogenetic placement (Rubinoff et al. 2006). This gene is putatively conserved among members of a species and diverged by 3% or more among different species

(Hebert et al. 2003, Song et al. 2008), making it well suited for this purpose (Brunner et al. 2002). However, this has proven not to be the case for several groups

(Gellissen and Michaelis 1987, Zhang and Hewitt 1996, Parfait et al. 1998, Bensasson et al 2001, Campbell and Barker 1999). In some of these cases, the presence of substantial intra- and intergenomic variation has confounded the traditional 3% divergence cut-off between species. These two variations have been attributed to i) duplication of the CO1 fragment (Campbell and Barker 1999), (ii) nuclear heteroplasmy, where multiple copies of mtDNA undergo coamplification (Petri et al. 1996, Thomas et al, 1998), (iii) amplification of mtDNA haplotypes of maternally inherited symbionts

(Parfait et al. 1998), and (iv) nuclear integration of mitochondrial sequences producing pseudogenes (numts) (Song et al. 2008). The first three events are rare phenomena and have been reported in few organisms. However, numts (nonfunctional copies of mtDNA) have been reported in more than 82% of eukaryotes (Bensasson et al. 2001).

These can be co-amplified with target mtDNA and can interfere in PCR-based identification and phylogenetic study by producing within individual sequence divergence. Numts coamplified with conserved orthologous mtDNA can be identified by the presence of indels, point mutations and in-frame stop codon (Song et al. 2008).

Due to some of these problems faced when delimiting species based on a single gene, some researchers use mtCO1 along with the second internal transcribed spacer in the nuclear ribosomal DNA (ITS2) for taxon characterization (Navajas et al. 1994,

1998, Ruiz et al. 2010). The internal transcribed spacer of the nuclear ribosomal 5.8S-

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28S gene exists in multiple copies within the nuclear genome. This region, like that of mtCO1, is believed to have low intraspecific and high interspecific variability (Fairley et al. 2005) making it useful for delimiting cryptic species (Li and Wilkerson 2007). The fixed intra- and interspecific differences in the non-coding ITS2 region are ensured by concerted evolution (Li and Wilkerson 2007). Concerted evolution is a universal biological phenomenon in which members of a multicopy gene family do not evolve independently and rapid spread of mutation is observed in all the members of the gene family (Liao 1999, Wörheide et al. 2004). In nuclear rDNA, homogenization of mutations acts as quality control to maintain intra- and intergenomic uniformity (Fairley et al.

2005). Molecular processes governing concerted evolution involves a variety of DNA recombination and repair and replication mechanisms in the form of unequal crossing over, gene conversion and gene amplification (Zimmer et al. 1980, Liao 1999).

Nevertheless, several authors have reported considerable intragenomic and/or intergenomic variation in the ITS region of (Vogler and Desalle 1994, Tang et al. 1996, Benevolenskaya et al. 1997, Rich et al. 1997, Navajas et al. 1998, Leo and

Barker 2002, Fairley et al. 2005, Li and Wilkerson 2007, Vesgueiro et al. 2011) raising questions regarding the suitability of this marker region for taxonomic characterization.

These variations can be attributed to i) faster rate of mutation among copies than the speed of homogenization (Fritz et al. 1994, Fairley et al. 2005), ii) duplication of DNA sequence produces new genes, which can either evolve independently to acquire new biochemical function or can remain non-functional as pseudogenes in the genome

(Murti et al. 1992); coamplification of such pseudogenes with the target ITS gene can bring ambiguity in taxon characterization (Mayol and Rossello 2001), iii) slow

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homogenization of duplicated genes has been reported to produce divergent sequences that evolve independently (Brunner et al. 1986), and iv) physical location of duplicated genes on the chromosome influencing its participation in recombination which decides its fate for concerted or divergent evolution (Murti et al. 1992, Liao 1999). Given that variations may exist in the mtCO1 and ITS2 genes of an individual, the ability of PCR to amplify sequences of these genes may lead to inaccurate identification and phylogenetic placement of the individual. Thus, determining the magnitude of intra- and intergenomic variations in the two genes is of paramount importance for any given species.

Worldwide, a large part of the literature dealing with economic thrips is focused on four major species i.e., Frankliniella occidentalis Pergande (western flower thrips),

Scirtothrips dorsalis Hood (chilli thrips), Thrips tabaci Lindeman (onion thrips), and

Thrips palmi Karny (melon thrips) (Morse and Hoddle 2006). Of these four species, F. occidentalis, S. dorsalis, and T. palmi are well known for their significant economic impact on agriculture and horticulture industries in Florida. These species are highly polyphagous and cause direct feeding damage to fruits, leaves or flowers of their hosts.

Apart from causing direct or cosmetic damage to the host, the species are well known for their ability to transmit important and damaging plant viruses. Twelve out of 14 species of virus within the genus Tospovirus are vectored by these three species of thrips (Whitfield et al. 2005). Frankliniella occidentalis transmits the Tomato spotted wilt tospovirus (TSWV), one of the most important members of the genus which has 1,090 host species in 85 different families of plants. Financial losses attributed to TSWV were estimated at more than $1 billion/year in the early 1990’s (Goldbach and Peters 1994).

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Other economically important tospoviruses vectored by S. dorsalis and T. palmi includes Capsicum chlorosis virus, Watermelon silver mottle virus, and Melon yellow spot virus (Chiemsombat et al. 2008). With the continued global expansion of these thrips vectors, the agriculture sectors in developing countries with limited resource input can suffer maximum damage. In addition, greater economic losses from plant diseases are expected with the emergence of new varieties and species of tospoviruses, which could be acquired and transmitted by the thrips (Pappu et al. 2009).

High level of variation in the basic biology, life history, host selection, pest status, vector efficiency and resistance to insecticides exist in different thrips species.

Misidentification of thrips species can lead to the misapplication of management practices, resulting in wasted money, resources and time (Rosen 1986). Considering the importance of correct identification, the objective of this study was to determine the suitability of two widely used marker genes i.e. mtCO1 and ITS2, for the identification of

F. occidentalis, S. dorsalis and T. palmi. Frey and Frey (2004) reported intragenomic variation in the mtCO1 gene of T. tabaci; however, no published information is available regarding such variation in the ITS2 gene of thrips species. Thus, in the current study the intragenomic and intraspecific variation in the mtCO1 and ITS2 gene of three thrips species was studied using the clone approach. Since thrips are known to exhibit haplodiploidy (Ananthakrishnan 1993), male and female thrips specimens were selected within each species to investigate any gender-based differences in ITS2 genes.

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Materials and Methods

Taxon Sampling

The adult male and female thrips specimens that were used for mtCO1 and ITS sequence determination during the study were obtained from either wild populations (T. palmi) or laboratory colonies (S. dorsalis and F. occidentalis). The date of sample collection, geographical location (longitude and latitude), host plant, and collector are reported in Table 4-1. The actual sample technique depended upon the individual collector, but once adults were collected, they were immediately placed in 70-95% ethanol. The specimens were shipped at room temperature to the US Horticultural

Research Lab in Fort Pierce, FL, where all samples subsequently were stored in 90% ethanol at -80°C.

Morphological Identification of Thrips

Thrips specimens were placed individually into vials containing 75% alcohol for 10 min and then into vials containing a 10% KOH (Potassium hydroxide) solution prepared in 50% ethanol for 5 min. While in the KOH solution, each specimen was macerated gently in the abdominal region using a fine insect pin to aid in the removal of abdominal contents. For gradual dehydration, each specimen was passed through a series of ethanol concentrations starting from 65%, followed by 75%, 85%, 90% and 95% for 5-8 min at each concentration. Each specimen was placed ventrally on a slide with a small drop of Hoyer’s mounting media and covered with a glass cover slip. The adult thrips specimens were identified using morphological characteristics described by Hoddle et al. (2009) using a dissecting microscope at a minimum of 10X magnification. The identity of thrips specimens were reconfirmed by USDA-APHIS entomologist, Thomas

Skarlinsky (Thysanoptera specialist- eastern region- Miami, FL).

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DNA Processing

Using cohorts from the sample that were morphologically identified, DNA was isolated from individual thrips by placing a single thrips specimen in a labeled 1.5-ml

Eppendorf tube, adding 25 µl of DNA lysis buffer (De Barro and Driver 1997, McKenzie et al. 2009), and grinding the specimen with a plastic pestle. The pestle was rinsed with an additional 25 µl of DNA lysis buffer and collected in the same tube. Tubes were placed in a metal boiling rack and boiled at 95°C for 5 min and then placed directly in ice for 5 min. The tubes were then centrifuged at 8,000 × g for 30 s, and the supernatant

(crude DNA lysate) was transferred to another tube and stored at -80°C for future processing. Aliquots from the same individual thrips DNA extract were used for both mtCO1 and ITS2 marker analysis so that thrips identity using both genes could be directly compared.

Polymerase chain reaction (PCR) amplifications of the mtCO1 gene for S. dorsalis and T. palmi were performed using universal CO1 primers LCO1490 and HCO2198 designed by Folmer et al. (1994). Mitochondrial CO1 gene amplification for F. occidentalis was conducted using mt D-7.2 and mt D-9.2 primers designed by Brunner et al. (2002). Amplification of rDNA ITS2 gene for all the three species was conducted using Thrips-ITS2 primer (Campbell et al.1993, Toda and Komazaki 2002, Rugman-

Jones et al. 2006). The complete primer sequence along with the PCR conditions are described in Table 4-2. The 25 µl PCR reactions for mtCO1 and ITS2 consisted of 2 uL of the DNA sample, 12.5 µl of go Taq PCR mastermix (Promega Corporation, Madison,

USA) and 10 pmol of each primer. PCR reactions were performed in a PTC-200 Peltier thermal cycler (MJ Research, Watertown, MA). Amplification of the correct PCR products was verified by electrophoresis in a 1.5% agarose gel, stained with ethidium

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bromide. Before sequencing, the amplified products excised from the gel were cleaned using nucleospin®Extract II, PCR clean up, Gel extraction kit (Macherey-Nagel, Inc.

Bethlehem, PA). Ligation and transformation of amplified DNA was done using the TOPO® TA Cloning® Kit (Invitrogen, Carlsbad, CA) following the manufacturer’s instructions. Transformed cultures were cultivated in 1.5 ml of Luria-Bertani medium overnight containing 50 ug/ml kanamycin. Plasmids were extracted using

Wizard® Plus SV Minipreps DNA Purification System (Promega Corporation, Madison,

WI), dissolved in 0.1X TE and sent for sequencing. All sequencing was performed bi- directionally with the amplification primers and ABI Prism® BigDye® Terminator v3.1

Cycle Sequencing Kits (Applied Biosystems, Foster City, CA) at the Genomics Core

Instrumentation Facility of USHRL-USDA. Sequence reactions were analyzed on an Applied Biosystems 3730XL DNA Analyzer (Applied Biosystems).

Sequence Alignment and Genetic Distance Matrix

Sequence base-calling was verified using Sequencher™5.0- Build 7081 (Gene

Codes Corporation, Ann Arbor, MI) and then aligned suing ClustalW 2.1 (Larkin et al.

2007) in mesquite (Maddison and Maddison 2011). Thrips species determination was based on direct sequence comparisons using the web-based National Center for

Biotechnology Information (NCBI) BLAST sequence comparison application

(http://blast.ncbi.nlm.nih.gov/Blast.cgi). Mean uncorrected “p” pairwise distances were calculated by PAUP version 4.0 (Swofford 1998) and it was used to assess sequence differentiation within and between individuals of same species. The aligned mtCO1 and

ITS2 sequences were analyzed by maximum parsimony (MP) as implemented in PAUP

(Li and Wilkerson 2007). Each indel was considered as a single character, and regardless of size, indels were coded as 0 or 1 (Simmons and Ochoterena 2000). In

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order to minimize possibility of Taq random error, single unique mutations were disregarded. Rate of Taq polymerase error was determined by recloning a cloned and sequenced fragment of a fifth S. dorsalis individual. Following the protocol of Li and

Wilkerson (2007), parsimony analysis was conducted using the heuristic search option with tree-bisection-reconnection branch swapping algorithm. Parsimony bootstrapping was conducted using 1,000 pseudoreplicates with 10 random taxon addition replicates for each pseudoreplicate.

Results

Inter- and Intragenomic Variation

Scirtothrips dorsalis. Evidence for intragenomic variation in the ITS2 of S. dorsalis was observed when individual clones of PCR products were analyzed. To assess the frequency of mutation in rDNA ITS2, 137 clones were sequenced from two females (SD-1, SD-2) and two males (SD-3, SD-4) as individual specimens, ranging from 23-46 clones/individual thrips (Table 4-3). Pairwise alignment of sequences from all the clones produced a consensus sequence of about 507 bp with GC content of

57%. When compared together, 137 clones of S. dorsalis produced 71 paralogous haplotypes (Table 4-4) of variable divergences. These haplotypes differed in 87 mutation points (nucleotides) out of 507 bp, amounting to 17% variable sites in haplotypes of S. dorsalis. Out of 71 variant haplotypes, 61 haplotypes consisted of a single clone from an individual specimen, and only four shared haplotypes (clones from two or more specimens) were observed. The frequency of the most common haplotype was 10.9% (Table 4-3). Maximum sequence divergence of 1.9% was observed between haplotypes. At the majority of nucleotide sites, haplotypes differed due to single base indels or substitutions, but two base substitutions/indels were observed at nucleotide

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positions 100, 107, 144, 338 and 462. Indels were observed at position 99, 100, 101,

107, 112, 113, 142, 144, 416 and 417.

Alignment of 132 mtCO1 clones from four S. dorsalis individuals produced 23 paralogous haplotypes. Haplotypes differed in 42-nucleotide positions in a total of 655 bp (AT- 72%), suggesting a site variation of about 6.4%. The most common haplotype

*SD (Table 4-5) consisted of 110 clones (83.3%) from four individuals (Table 4-3). At all nucleotide positions haplotypes differed in single base indels or substitutions, except at position 475 where haplotype SD-2.5 exhibited C and SD-2.11 had an A while all others had a T (Table 4-5). Maximum sequence divergence of 0.4% was observed between haplotypes. The uncorrected “p” distance matrix showed variation among clones of S. dorsalis, where the intragenomic base differences ranged from 0.1% to 3.4% for the

ITS2 gene and from 0.0% to 0.9% for the mtCO1 gene (Table 4-3). The intergenomic variation in this specis was similar to the intragenomic deviation, ranging from 0.1% to

3.8% and 0.0 to 0.9% for the ITS2 and mtCO1 genes, respectively.

Thrips palmi. Variations were observed within and between clones of the ITS2 gene of the four specimens of T. palmi (Table 4-6). Alignment of 149 clones from the four individuals produced 76 paralogous haplotypes. Haplotypes differed from each other in 79 mutation points (Table 4-6) in the 564 bp sequence (GC- 56%), amounting for 14% site variation. Sixty-five haplotypes consisted of a single clone from the same specimen and six shared haplotypes from two or four different specimens were observed. The frequency of the most common haplotype was 14.7% (Table 4-3). At nucleotide position 139, haplotypes differed in two base substitutions, where haplotype

T.P-1.11 and TP-2.6 exhibited A and C, respectively instead of T. Indels were observed

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at position 56, 249 and 250. Sequence divergence of 1.5% was observed between haplotypes.

Compared to ITS2, not much sequence variation observed among mitochondrial

CO1 clones of T. palmi. Fifteen paralogous haplotypes were obtained from 120 clones of four individuals. Haplotypes differed from each other in 25 nucleotides positions in

655 bp (AT- 70%), amounting to site variation of 3.8%. Haplotype TP-1.1 comprised of

34 clones from individual TP-1 and shared haplotype TP* consisted of 73 clones from the other three individuals (Table 4-7). Maximum sequence divergence among haplotypes was about 0.6%. Based on distance matrix, intragenomic variation of 0.0 to

2.6% and 0.0% to 0.7% and intergenomic variation of 0.0% to 2.8% and 0.0% to 1.0% was observed for ITS2 and mtCO1 clones of T. palmi, respectively (Table 4-3).

Frankliniella occidentalis. Compared to the other two thrips species, less site variation (5.7%) was observed among haplotypes of ITS2 in F. occidentalis. Out of 105

ITS2 clones, 14 different haplotypes were obtained (Table 4-8). These haplotypes differed in 23 nucleotide positions in 456 bp (GC- 54%). The frequency of the most common haplotype was 76%. Maximum sequence divergence of 1.5% was observed between haplotypes.

In the case of mtCO1 clones, a site variation of 5.2% was observed among 150 clones in 434 bp (AT- 68%) (Table 4-8). Frequency of the most common haplotype was

88%. Maximum sequence divergence among haplotypes was about 0.6%. Distance matrix analysis showed 0.4% to 1.1% and 0.2% to 1.1% intragenomic variation among clones of ITS2 and mtCO1 and the value of intergenomic variation between 0.4% to

1.5% and 0.2% to 1.5%, respectively.

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In all the three thrips species no sex based haplotype diversity was observed in male and female clones of the rDNA ITS2 gene (data not shown), which indicates existence of similar rDNA arrays in both sexes.

Parsimony Analysis of ITS2

Based on the variations observed in the ITS2 regions of the three thrips species,

MP analysis was conducted only for this region. For clear representation of tree topology of S. dorsalis and T. palmi, polytomys were removed and selective haplotypes were included to produce the unrooted consensus MP tree (Figure 4-1, 2). Bootstrap values were provided as branch support. The unrooted MP tree (Figure 4-1) showed a high degree of intragenomic variations among the clones of same individual specimen of S. dorsalis. These variations were equivalent to intergenomic variations i.e., variation between clones of different individuals of a species. Similar variations were seen in the

MP tree generated from rDNA ITS2 sequences obtained from four individuals of T. palmi (Figure 4-2). In the case of F. occidentalis, less intra- and intergenomic variations were observed; thus, the single most parsimonious tree was presented without removing polytomys (Figure 4-3).

Discussion

Mitochondrial Cytochrome Oxidase I

On comparing intra- and intergenomic variability observed in the sequence of the mtCO1 and ITS2 genes, the relatively low variation in mtCO1 and variant paralogous haplotype suggests that this gene could be used for the taxonomic characterization of the three thrips species. Corresponding to our results, Frey and Frey (2004) observed

2.5% nucleotide divergence in mtCO1 clones of T. tabaci and suggested that this was low enough to allow molecular diagnosis of the species. Nucleotide divergence of the

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mtCO1 sequence for the thrips observed in this study was much lower (0.4% seen in S. dorsalis and 0.6% seen in both T. palmi and F. occidentalis).

In the current study, there is the possibility that Taq polymerase induced error could contribute to variation among mtCO1 clones. Since, Taq polymerase lacks the ability of 3’-5’ proof reading (Barnes 1994), it may interfere in identifying and quantifying the actual level of intra- and intergenomic variation in the gene. However, Taq error rate

(mutations per nucleotide per cycle) can vary between 1 x 10-4 to 1x 10-5 (Eckert and

Kunkel 1991, Pray 2008, Vesgueiro et al. 2011) and are proportionally related to the length of the product. In this study, single unique mutations were disregarded to minimize the possibility of Taq random error. Based on the results obtained from cloning a clone product, the Taq error rate was observed about 1 out of 10,000 bases. In the three thrips species, 65,000 to 86,500 bases were sequenced for CO1 clones, thus, artifacts due to Taq polymerase account for an insignificant percentage of the clones and sequence variation can be attributed to nuclear integrated gene fragment copies or mitochondrial heteroplasmy. The results suggest the presence of a large number of numts which were co-amplified with target mtDNA using conserved universal primers in the three thrips species. The presence of numts can be identified by indels, point mutation and in-frame stop codons (Song et al. 2008). Due to the presence of an altered genetic code, numts are not expressed correctly and they randomly accumulate high degrees of mutations resulting in divergence of numts from the orthologous sequence (Zhang and Hewitt 1996). They induce nonsense mutations that result in presence of stop codon in the coding DNA, which makes it possible to identify them

(Frey and Frey 2004). However, in the current study, stop codon were not seen in the

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mtCO1 sequence of all three thrips species, but presence of indels and point mutations confirmed the presence of nonfunctional numt haplotypes. Presence of numts has previously been reported in a number of arthropods including aphids, crickets, locusts and grasshoppers (Zhang and Hewitt 1996, Parfait et al. 1998, Bensasson et al. 2001,

Gellissen and Michaelis 1987). In the case of variant T. palmi haplotype, TP-1.1 that comprises 34 functional clones (Table 4-7); heteroplasmy may be a possible cause behind this variation. Heteroplasmy has been reported in bark weevils and grasshoppers (Boyce et al. 1989, Song et al. 2008) which can be identified by absence of stop codon in paralogous haplotypes exhibiting multiple clones from the same individual. However, the results do not provide clear evidence of the possible reason behind variant haplotypes and it is worth mentioning that the low frequency of variant mtCO1 haplotypes in the three species do not interfere in their PCR-based identification. The possible origin of such variations can be traced by using allele- specific single cell-PCR and cytological methods of using high sensitive gold and silver staining with which any event of heteroplasmy and nuclear integration can be observed

(Frey and Frey 2004).

Internal Transcribed Spacer 2 Variation

Extensive inter- and intragenomic variations were observed in the ITS2 gene of S. dorsalis and T. palmi. There were a number of base substitutions and indels accounting for sequence variabilities. The unrooted MP tree for both species (Figure 4-1 and 4-2) showed cluster of clones from the same individuals that were as different from each other as from other individuals. Out of 71 paralogous haplotypes, only four shared haplotypes were observed where clones from SD-1 align together with clones from SD-

3 and SD-4 (Figure 4-1), but clones from SD-2 did not align with clones from other

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individuals and formed separate haplotypes. In the case of T. palmi six shared haplotypes were observed where TP* (Figure 4-2) comprised ITS2 clones from all four individuals indicating low variability among clones compared to S. dorsalis. ITS2 clones from F. occidentalis, FO-1 did not align with clones from other individuals and formed a separate cluster together (Figure 4-3). Alignment of clones is of primary importance to ensure the concerted evolution among members of the gene family (Vesgueiro et al.

2011). However, intra- and intergenomic variability in ITS2 clones in this study failed to support this hypothesis and questions the reliability of this gene for taxon characterization. Due to high within and between individual variability, it may be possible that during phylogenetic analysis, members from one individual species can form clades with another and provide ambiguous results.

Ignoring the insignificant percentage of Taq contamination in the ITS2 clones, high variability within this gene can be attributed to the evolutionary process causing failure of concerted evolution. Genetic exchange between homologous or non-homologous chromosomes by unequal crossing over or gene conversion (Zimmer et al. 1980, Liao

1999) is important in maintaining sequence homogeneity in a multigene family such as rDNA. In this process, mutation generated in one region is rapidly transferred to all the members of multigene families, even if repeats are located on different chromosomes

(Tautz et al. 1988). Due to this homogenization of mutation in noncoding regions like

ITS2, no intragenomic and fixed rate of intergenomic variation can be expected (Li and

Wilkerson 2007). However in the current study, within individual variations in ITS2 was similar among individual differences, which clearly suggests the rate of mutation within this gene is higher than homogenization of mutation. This may serve as a possible

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reason behind high intragenomic variation in ITS2 within the thrips species. In a similar study, distant populations of black had been reported to exhibit multiple copies of

ITS1 region (Tang et al. 1996). Although concerted evolution occurred in the ITS region in each of the black fly isolated populations, interbreeding between these populations was interpreted as a source of multiple copies of the ITS1 in this pest. Gasser et al.

(1998) reported that interbreeding populations of a parasitic nematode (red stomach worm, Haemonchus contortus) was the source of intragenomic variation in the ITS2 region of the pest (Leo and Barker 2002). Considering the global distribution of S. dorsalis, T. palmi and F. occidentalis, the intragenomic variations in the ITS2 gene of these pests due to interbreeding between geographically isolated populations cannot be ruled out. Because the thrips populations used in the present study were only from

Florida, the possible role of interbreeding in genetic divergence could not been determined. Future studies focused on assessing such variations in the global populations of individual thrips species could explain interbreeding in divergent evolution of the ITS2 gene.

Pseudogenes can also produce variant haplotypes in the ITS2 gene, resulting in the high degree of intra- and intergenomic variation observed in this study. Due to the heterogeneous nature of rDNA, infrequent existence of nonfunctional operons or pseudogenes can be noted within a genome (Harpke and Peterson 2006). Presence of pseudogenes can be identified by a high degree of indels in a nucleotide sequence

(Scholin et al. 1993, Santos et al. 2003). In this study, a considerable amount of indels were found in haplotypes of S. dorsalis suggesting involvement of nonfunctional pseudogenes in generating intragenomic variation. A better understanding of the

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presence of pseudogenes could have been provided by analyzing the secondary structure of the ITS2 gene (Bailey et al. 2003). Secondary structural stability is important for the proper functioning of rRNA and even a minute modification in the structure of the

ITS region can cease the production of mature rRNA’s (Musters et al. 1990, Henry et al.

1994, Thornhill et al. 2007). Structural variation can affect cleavage efficiency of the precursor RNA and may lead to formation of multiple pseudogenes of variable divergence (Li and Wilkerson 2007). Intragenomic variation due to pseudogenes has been reported in Drosophila melanogaster, Anopheles marajoara (Benevolenskaya et al. 1997, Li and Wilkerson 2007) and other organisms (Brownell et al. 1983,

Razafimandimbison et al. 2004).

Although the possible reason for ITS2 variation of these thrips species could not be traced, it can be concluded that the ITS2 copies in these thrips do not evolve in concert based on the degree of intra- and intergenomic variability. Thus, this marker region is not phylogenetically informative for population studies, and should not be used for species-specific PCR identification of the three major economic thips species studied. Ambiguity in correct identification, due to intra- and intergenomic variability within a gene can be avoided by incorporating other marker regions and alternate molecular tools as well as searching for additional biological and ecological information segregating thrips populations.

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Table 4-1. Collection date, localities and hosts for specimens used in cloning of rDNA and mtCO1 genes of thrips species of three genera. Scientific name Individual (M=male, Specimen no. Date collected Host Locality Coordinates Collector code F= female) Scirtothrips Indian USA, Florida- Dr. Lance CLM9.13 SD-1 Aug. 7- 2007 28.63 N, 81.55W dorsalis (F) Hawthorne Apopka Osborne

Scirtothrips Indian USA, Florida- Dr. Lance CLM9.14 SD-2 Aug. 7- 2007 28.63 N, 81.55W dorsalis (F) Hawthorne Apopka Osborne

Scirtothrips Indian USA, Florida- Dr. Lance CLM9.15 SD-3 Aug. 7- 2007 28.63 N, 81.55W dorsalis (M) Hawthorne Apopka Osborne

Scirtothrips Indian USA, Florida- Dr. Lance CLM9.16 SD-4 Aug. 7- 2007 28.63 N, 81.55W dorsalis (M) Hawthorne Apopka Osborne Thrips palmi (F) Vlaspek USA, Florida- CLM85.5 TP-1 Mar. 11- 2010 25.50 N, 80.49W Vivek Kumar cucumber Homestead Thrips palmi (F) Vlaspek USA, Florida- CLM85.6 TP-2 Mar. 11- 2010 25.50 N, 80.49W Vivek Kumar cucumber Homestead Thrips palmi (M) Vlaspek USA, Florida- CLM85.9 TP-3 Mar. 11- 2010 25.50 N, 80.49W Vivek Kumar cucumber Homestead Thrips palmi (M) Vlaspek USA, Florida- CLM85.10 TP-4 Mar. 11- 2010 25.50 N, 80.49W Vivek Kumar cucumber Homestead Frankliniella USA, Florida- Dr. Stuart CLM87.20 FO-1 Apr. 16- 2011 Green beans 30.48N, 84. 17W occidentalis (F) Tallahassee Reitz Frankliniella USA, Florida- Dr. Stuart CLM87.22 FO-2 Apr. 16- 2011 Green beans 30.48N, 84. 17W occidentalis (F) Tallahassee Reitz Frankliniella USA, Florida- Dr. Stuart CLM87.25 FO-3 Apr. 16- 2011 Green beans 30.48N, 84. 17W occidentalis (M) Tallahassee Reitz Frankliniella USA, Florida- Dr. Stuart CLM87.30 FO-4 Apr. 16- 2011 Green beans 30.48N, 84. 17W occidentalis (M) Tallahassee Reitz

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Table 4-2. PCR amplification conditions for two genes of Scirtothrips dorsalis, Thrips palmi and Frankliniella occidentalis.

PCR amplification conditions PCR Primer Set (25 µl reactions) mtCO1 primers 94°C 2 min LCO1490:5'-GGTCAACAAATCATAAAGATATTGG-3’ 35 cycles of HCO2198: 5'-TAAACTTCAGGGTGACCAAAAAATCA-3' 94°C 30 s *mt D-7.2F: 5'-ATTAGGAGCHCCHGAYATAGCATT-3' 54°C 30 s *mt D9.2R: 5'-CAGGCAAGATTAAAATATAAACTTCTG-3' 72°C 1 min 72°C 10 min ITS2 primers 94°C 2 min ITSF: 5'-TGTGAACTGCAGGACACATG-3' 35 cycles of ITSR: 5'-AATGCTTAAATTTAGGGGGTA-3' 94°C 30 s 52°C 1 min 72°C 1 min 72°C 10 min *Primers used for mtCO1 amplification of Frankliniella occidentalis with annealing temperature of 52°C

Annealing temperature for CO1 and ITS2 amplification of Thrips palmi was 40°C and 48°C, respectively.

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Table 4-3. Number of clones sequenced and recovered haplotypes for the four individuals of each thrips species.

Internal transcribed spacer 2 Cytochrome oxidase 1 Frequency Frequency Uncorrected No. of No. of of most No. of No. of of most Uncorrected “p” “p” distance Individual clones different common clones different common distance matrix matrix of sequenced haplotypes haplotypes sequenced haplotypes haplotypes of clones clones (%) (%) SD-1 23 17 21.7 0.001-0.022 33 4 90.9 0.003-0.006 SD-2 26 19 23.0 0.003-0.038 44 13 72.7 0.001-0.009 SD-3 42 21 33.3 0.001-0.023 24 4 87.5 0.001-0.006 SD-4 46 19 26.0 0.001-0.034 31 5 87.0 0.0-0.007 All Scirtothrips dorsalis 137 71 10.9 0.001-0.038 132 23 83.3 0.0-0.009 clones TP-1 41 23 24.3 0.0-0.023 42 9 80.9 0.0-0.007 TP-2 38 18 18.4 0.001-0.023 24 3 91.6 0.001-0.004 TP-3 31 16 22.5 0.001-0.026 24 1 100 * TP-4 39 28 15.3 0.001-0.026 30 4 90 0.003-0.006 All Thrips palmi clones 149 76 14.7 0.0-0.028 120 15 60.8 0.0-0.010 FO-1 20 4 17 0.004-0.008 42 6 90 0.002-0.009 FO-2 17 2 16 0.004 31 4 87.0 0.002-0.011 FO-3 36 7 30 0.004-0.011 46 5 86.9 0.002-0.011 FO-4 32 3 30 0.004-0.008 31 2 96.7 0.004 All Frankliniella 105 14 76 0.0-0.015 150 14 88.6 0.002-0.013 occidentalis clones *Because of only one haplotype, the distance matrix could not be calculated

Uncorrected “p” distance matrices between clones from same individual represents intragenomic variation, and uncorrected “p” distance matrices between clones of all individuals of the same species represents intergenomic variation.

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Table 4-4. The rDNA ITS2 sequences that differ among Scirtothrips dorsalis individuals.

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 Nucleotide position 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 3 4 7 8 9 0 0 0 0 1 1 1 2 3 4 4 4 4 4 8 8 9 0 0 1 2 2 3 3 3 3 4 4 5 5 5 6 6 7 8 9 9 0 0 1 2 3 3 4 4 5 6 7 7 8 8 8 9 9 9 0 0 0 1 1 1 1 2 3 3 3 3 3 4 5 5 5 6 6 6 7 7 8 9 S. no. Haplotype Ratio 1 6 2 2 3 9 4 9 0 1 7 9 1 2 3 6 3 1 2 3 4 7 1 4 0 5 6 9 2 4 3 4 6 7 1 2 0 3 8 2 8 5 2 3 6 2 3 8 4 5 8 4 8 5 5 1 7 0 4 6 3 4 8 1 3 8 2 4 6 7 3 0 1 6 7 9 7 1 2 9 0 1 2 3 7 5 5 1 SD-1.1 1/137 A C T C T A A G C G C A A − C T T T T T G C G T T C G C T G T T A C G T C A T G T G A G C C G C A C A C T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 2 SD-1.2 1/137 A T T C T A A G C G T A A A C T T T − C − C G C T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 3 SD-1.3 1/137 A T T C T A A G C G C A A − C T T T T T G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 4 SD-1.4 1/137 A C T C T A A G C G T A A A C T T T − C − C G C T C G C T G T T A C G T C G G G T G A G C C G C A C A T T C C A A C C A C G A A T A T T − − A T T T G G C G C T C C C G T T T 5 SD-1.5 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C G T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 6 SD-1.6 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C G T T C C A A C C G C G A A T A T T − − A T A T G G C G C T C C C G T T T 7 SD-1.7 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C G T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 8 SD-1.8 2/137 A C T C T A A G C G C A A − C T T T T T G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 9 SD-1.9 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C G T T C C G A C C G C G A A T A T T − − A T A T G G C G C T C C C G T T T 10 SD-1.10 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G C T T 11 SD-1.11 1/137 A C T C T A A G C G T A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 12 SD-1.12 1/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T G T T A C G T C A T G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 13 SD-1.13 1/137 A C T C T A A G C G − A A A C T T T − C C G T T C A C T G T T A C G T C A G G T A A G C C G C A C A T T C C A G C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 14 SD-2.1 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A T C G C G A A T A A C C T A T T T G G C G C T C C C G T T T 15 SD-2.2 6/137 A C T C T A A G C G T A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A T A T C C C A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 16 SD-2.3 1/137 A C T C T A A − − − T C A − − T C T T C G C G T T C G C T G T T A T G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T C G G A G C T C C C G T T T 17 SD-2.4 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G G G C C G C A C A T T C C A A T C G C G A A T A A C C T A T T T G G C G C T C C C G T T T 18 SD-2.5 2/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T T C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − − T T T G G C G C T C C C G T T T 19 SD-2.6 1/137 A C T C T A A G C G T A A A C T T T − C − C G T T C G C T G T T A C A T C A G G T G A G C C G C A T A T C C C A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 20 SD-2.7 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T A C A A C C G C G A A T A T T − − A T T T G G C G C T C C G G T T C 21 SD-2.8 2/137 G C T C T A A G C G T A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A T A T C C C A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 22 SD-2.9 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A T C G C A A A T A A C C T A T T T G G C G C T C C C G T T T 23 SD-2.10 1/137 A C T C T A A G C G T A A A C T T T − C − C G T T T G C T G T T A C G T C A G G T G A G C C G C A T A T C C C A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 24 SD-2.11 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C T G C A C A T T C C A A T C G C G A A T A A C C T A T T T G G C G C T C C C G T T T 25 SD-2.12 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T T T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 26 SD-2.13 1/137 A C T C T A A G C G T A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A T A T C C C A A C C G C G G G T A A C C T A T T T G G C G C T C C A G T C C 27 SD-2.14 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T T A G G T G A G T C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 28 SD-2.15 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T A C C G T T T 29 SD-2.16 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C T G T T A C G T C A G G T G A G T C G C A C A T T C C A A C C G C G A A T A A C C − A T T T G G C G C T C C A A T T C 30 SD-2.17 1/137 A C T C T A A G C G T A A − C T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A A T T G G C G C T C C C G T T T 31 SD-2.18 1/137 A C T T T A A − − − T C A − − T C C − C − C G T T C G C T G T T A C G T C A G G T G A G T C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 32 SD-2.19 1/137 A C T C T A A G C G T A A A C T T T − C − C G T T C G C T G C T A C G T C A G G T G A G C C G C A T A T C C C A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 33 SD-3.2 14/137 A C T C T A A G T G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 34 SD-3.3 1/137 A C T C T A A G C G C A A − C T T T T C A C G T T C G C T G T T A C G T C A G G T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T C 35 SD-3.5 1/137 A C T C T A A G C G − A A A C T T T T C G C G T T C G C T G T T A C G T C A T G T G A G C C G C C A T T C C A A C C G C G A A C A T T − − A T T T G G C G C T C C C G T T T 36 SD-3.6 1/137 G C T C T A A G C G − A A A C T T T T C G C G T T C G C T G T T A C G T C A T G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 37 SD-3.7 1/137 A C T C T A A G T G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C A C T C C C G T T T 38 SD-3.8 1/137 A C T C T A A G T G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G A T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T

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Table 4-4. Continued

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 Nucleotide position 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 3 4 7 8 9 0 0 0 0 1 1 1 2 3 4 4 4 4 4 8 8 9 0 0 1 2 2 3 3 3 3 4 4 5 5 5 6 6 7 8 9 9 0 0 1 2 3 3 4 4 5 6 7 7 8 8 8 9 9 9 0 0 0 1 1 1 1 2 3 3 3 3 3 4 5 5 5 6 6 6 7 7 8 9 S. no. Haplotype Ratio 1 6 2 2 3 9 4 9 0 1 7 9 1 2 3 6 3 1 2 3 4 7 1 4 0 5 6 9 2 4 3 4 6 7 1 2 0 3 8 2 8 5 2 3 6 2 3 8 4 5 8 4 8 5 5 1 7 0 4 6 3 4 8 1 3 8 2 4 6 7 3 0 1 6 7 9 7 1 2 9 0 1 2 3 7 5 5 39 SD-3.9 1/137 A C T C T A A G T G − A A A C T T T − C − C G T C C G C T G T T A C G T C A G G T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 40 SD-3.10 1/137 A C T C T A A G C G − A A A C T T T T C G T G T T C G C T G T T A C G T C A T G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 41 SD-3.11 1/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G A G A A T A T T − − A T T T G G C G C T C C C G T T T 42 SD-3.12 1/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G T A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 43 SD-3.13 1/137 A C T C T A A G T G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 44 SD-3.14 1/137 A C T C T A A G T G − A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C C C C C G T T T 45 SD-3.15 1/137 A C T C T A A G C G − A A A C T T T T C G C G T T C G C T G T T A C G T C A T G T G A G C C G C G C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 46 SD-3.16 1/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T A T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 47 SD-3.17 1/137 A C T C T A A G T G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A T C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 48 SD-3.18 1/137 A C T C T A A G C G − A A G C T T T T C G C G T T C G C T G T T A C G T C A T G C G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 49 SD-3.19 1/137 A C T C T A A G C G − A A A C T T T T C G C G T T C G C T G T T A C G T C A T G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C C C C C G T T T 50 SD-3.20 1/137 A C T C T A G G T G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C T T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 51 SD-4.1 1/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A T A T C C T A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T T 52 SD-4.2 12/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A T A T C C T A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 53 SD-4.3 1/137 A C T C C A A − − − T C G − − T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T A G C G C T C C A G T T C 54 SD-4.4 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C T G C G A A T A T T − − A T T T G G C G C T C T C G T T T 55 SD-4.5 1/137 A C T C T A A G C G T A A A C T T T − C − C G T T C G T T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 56 SD-4.6 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G A C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T C 57 SD-4.7 1/137 A C T C T A A − − − T C A − − C T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G A C G C T C C C G T T T 58 SD-4.8 1/137 A C T C T A A − − − T C A − − T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A T A T C C T A A C C G C G A A T A A C C T A T T T G G C G C T C C A G T T C 59 SD-4.9 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T C T G G C G C T C T C G T T T 60 SD-4.10 1/137 A C T C T G A − − − T C A − − T T T T C G C G T T C G C T G T C A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 61 SD-4.11 1/137 A C T C T A A − − − T C A − − T T T − C − C G T T C G C C G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G T T C T C G T T T 62 SD-4.12 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C A C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 63 SD-4.13 1/137 A C C C T A A G C G C A A − C T T T T T G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 64 SD-4.14 1/137 A C T C T A A − − − T C A − − T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T C G G C G C T C C C G T T T 65 SD-4.15 1/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T G T T − − A T T T G G C G C T C C C G T T T 66 SD-4.16 1/137 A C T C T A A G C G − A A A C T T T − C − C A T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 67 SD-4.17 1/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 68 SD* 6/137 A C T C T A A G C G − A A A C T T T T C G C G T T C G C T G T T A C G T C A T G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 69 SD** 3/137 A C T C T A A G C G T A A A C T T T − C − C G C T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T 70 SD*** 15/137 A C T C T A A G C G − A A A C T T T − C − C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C T C G T T T 71 SD**** 14/137 A C T C T A A G C G C A A − C T T T T C G C G T T C G C T G T T A C G T C A G G T G A G C C G C A C A T T C C A A C C G C G A A T A T T − − A T T T G G C G C T C C C G T T T SD* -1.20,26 -3.1,7,10,37 SD** -1.27 -3.8,13 SD*** -1.5,18,19,28,39 -4.1,4,8,16,20,23,25,29,38 SD**** -1.15 -3.5,6,25,32,48 -4.4,12,18,24,26,28,34,39

Columns 1, 2 and 3 are unique sequence number (S. no.), haplotype code, and number of clones of haplotype per total no. of clones from each of four individual specimens. For example, SD- 3.2 is S. dorsalis specimen number 3, set of like clones number 2, which was found in 14 of a total of 137 clones. Haplotypes consisting of clones of more than one individual specimen have been marked with asterisks. The coding for these haplotypes consists of bold digits denoting the specimen number, which is followed by the clones it exhibited. For example, SD** -1.27 -3.8,13, indicates that haplotype SD** consisted of one clone (clone no. 27) from specimen number 1 and two clones (8 and 13) from specimen number 3.

100

Table 4-5. The mtCO1 sequences that differ among Scirtothrips dorsalis individuals.

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 Nucleotide position 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3 3 3 4 4 4 4 4 4 4 5 5 5 5 5 6 6 6 6 2 2 3 3 4 6 8 8 2 4 6 9 9 1 3 4 4 7 9 0 2 3 3 3 4 7 0 3 3 6 7 9 9 1 4 5 7 7 0 1 1 2 S. no. Haplotype Ratio 2 4 1 4 0 2 1 8 0 2 0 3 5 4 6 1 9 9 3 9 6 1 2 6 3 5 6 2 5 7 5 1 7 9 5 6 6 8 1 3 6 8 1 SD-1.1 1/132 G T T T T A T A G C T A A A T T A C A A A A A T A C T C T A T A T T T A T T T T A T 2 SD-1.2 1/132 G T T T T A T A A T T A A A T T A C A A A A A T A C T C T A T G T T T A T T C T A T 3 SD-1.3 1/132 G T T T T A T G A T T A A A T T A C A A A A A T A C T C T A T A T T T A T T T C A T 4 SD-2.1 1/132 G T T C T G T A A T T A A A T T A C A A A A A T A C T C T A T A T T T A T T T T A T 5 SD-2.12 1/132 G T T T T A T A A T T A G A T T A C A G A A A T A C T C T A T A T T T A T T T T A T 6 SD-2.2 1/132 G T T T C A T A A T T A A A T T A C A A A G A T A C T C T A T A T T T A T T T T A T 7 SD-2.3 1/132 G T T T T A T A A T T A A A C T A C A A A A A T A C T C T A T A T T T A T C T T A T 8 SD-2.4 1/132 G T T T T A T A A T T A A A T T A C A A A A A T G C T C T A T A T T T A T T T T A T 9 SD-2.5 1/132 G T T T T A T A A T T A A A T T A C A A A A A T A C T C T A C A T T T A T T T T A T 10 SD-2.6 1/132 G T T T T A T A A T T A A A T T A C A A A A A T A C T C T A T A T T T A C T T T A T 11 SD-2.7 1/132 G C T T T A T A A T T A A A T T A C A A A A A T A C T C C A T A T T T A T T T T G T 12 SD-2.8 1/132 G T T T T A T A A T T A A A T T A C A A A A A G A T T C T G T A T T T A T T T T A T 13 SD-2.9 1/132 A T T T T A T A A T T A A A T T A C A A A A A T A C T C T A T A C T T A T T T T A T 14 SD-2.10 1/132 G T T T T A T A A T T G A A T C A C A A A A A T A C T T T A T A T T T A T T T T A T 15 SD-2.11 1/132 G T T T T A T A A T T A A A T T A C G A A A A T A C T C T A A A T C T A T T T T A T 16 SD-3.1 1/132 G T C T T A T A A T T A A A T T A C A A A A G T A C T C T A T A T T T A T T T T A T 17 SD-3.2 1/132 G T T T T A T A A T T A A A T T G A A A A A A T A C T C T A T A T T T A T T T T A T 18 SD-3.3 1/132 G T T T T A T A A T T A A G T T A C A A A A A T A C − C T A T A T T T A T T T T A T 19 SD-4.1 1/132 G T T T T A T A A T T A A A T T A C A A A A A T A C T C T A T A T T T G T T T T A T 20 SD-4.2 1/132 G T T T T A C A A T T A A A T T A C A A A A A T A C T C T A T A T T T A T T T T A C 21 SD-4.3 1/132 G T T T T A T A A T − A A A T T A C A A A A A T A C T C T A T A T T T G T T T T A T 22 SD-4.4 1/132 G T T T T A T A A T T A A A C T A C A A G A A T A C T C T A T A T T C A T T T T A T 23 SD* 110/132 G T T T T A T A A T T A A A T T A C A A A A A T A C T C T A T A T T T A T T T T A T

SD*-1.3,4,6,7,9,10,11,12,13,17,18,20,21,22,23,24,26,28,29,31,32,33,35,36,37,40,45,46,47,48-2.5,6,7,8,10,15,16,19,20,21,22,23,24,26,27,28,29, 30,31,32,33,34,36,38,40,41,42,43,44,45,46,48 -3.2,6,7,10,11,12,15,16,17,18,20,21,22,24,25,27,28,29,30,31,34 -4.9,10,17,19,20,22,24,25,26,27, 28,29,30,32,33,34,35,36,38,40,41,42,43,45,46,47,48

101

Table 4-6. The rDNA ITS2 sequences that differ among Thrips palmi individuals.

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Nucleotide position 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 1 5 5 6 7 8 9 0 0 1 2 2 3 3 4 5 7 7 9 0 0 1 2 3 4 5 5 6 6 6 6 7 8 8 0 0 0 1 1 2 2 3 3 5 5 5 5 7 8 9 9 9 9 0 0 1 2 2 3 3 3 3 5 6 8 8 9 9 9 9 0 0 1 1 2 3 5 6 S. no.Haplotype Ratio 1 7 1 6 8 9 0 7 5 8 8 1 8 0 9 4 3 1 4 2 4 8 2 2 1 9 0 5 0 1 2 7 8 0 9 2 4 5 0 1 0 7 1 4 1 2 5 9 6 7 1 4 8 9 0 8 7 1 3 0 1 2 6 7 8 1 8 0 5 6 8 0 3 3 5 6 7 4 2 1 TP-1.1 1/149 A A A T G A T T C T T A A T T A A A T G G T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A C G T T A G T T T T T T T A C C A C T G 2 TP-1.2 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 3 TP-1.3 1/149 A A A − G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A T T G T T G 4 TP-1.4 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C T A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A T T G C T G 5 TP-1.5 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T C A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C C C T G 6 TP-1.6 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C C C T G 7 TP-1.7 2/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T C A C C C A A C C A T T T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A T T G C T G 8 TP-1.8 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G A T T T A G A T C T G C A T G C C A G T T T T T T T A C C C C T G 9 TP-1.9 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T C A T C C A A C C A T T T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C C C T G 10 TP-1.10 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T C T G G A T C T G C A T G C C A G T T T T T T T A C C C C C G 11 TP-1.11 1/149 A A A T G A T T C T T A A T A A A A T G A T T G A T T G A C C C A A T C A T C T G G C T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A T T G T T G 12 TP-1.12 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C C C T A 13 TP-1.13 1/149 A A A T G T C T C T T A A T T A A A C G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C C C T G 14 TP-1.14 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T C A C C C A A C C A T T T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C C C T G 15 TP-1.15 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T T G G T T T G G A T C T G C A C G T T A G T T T T T T T A C C C C T G 16 TP-1.16 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C C C T G 17 TP-1.17 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A T C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A T T G T T G 18 TP-2.1 1/149 A A G T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A C C A T T T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 19 TP-2.2 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A C C A C T G 20 TP-2.3 1/149 A A A T G T C T C T T A A T T G A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A T G C C G G T T T T T T T A C C A C T G 21 TP-2.4 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T T A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 22 TP-2.5 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C G T G C C A G T T T T T T T A C C A C T G 23 TP-2.6 1/149 A A A T G A T T C T T A A T C A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T A C A T G C C A G T T T T T T T A C C A C T G 24 TP-2.7 1/149 A A A T A A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 25 TP-2.8 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G T T A G T T T T T T T A C C A C T G 26 TP-2.9 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C A T A C C A G T T T T T T T A C C A C T G 27 TP-2.10 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T C G G A T C T G C A C G T T A G T T T T T T T A C C A C T G 28 TP-2.11 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G A A T C T G C A C G T T A G T T T T T T T A C C A C T G 29 TP-2.12 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A C G T T A G T T T T T T T A C C A C T G 30 TP-2.13 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T C A T T G T T G 31 TP-2.14 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C A C G T T A G T T T T T T T A C C A C T G 32 TP-3.1 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C C G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A C C A C T G 33 TP-3.2 7/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C A G C A T G C T A G T T T T T T T A C C A C T G 34 TP-3.3 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G A G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 35 TP-3.4 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C G T C T G G C T T G G T T T G G A T C T G C A T G T C A G T T T C T T T A T T G T T G 36 TP-3.5 1/149 G A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A G C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A T T G T T G 37 TP-3.6 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G T T A G T T T T T T T A C C A C T G 38 TP-3.7 1/149 A A A T G T C T C T T G A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C A G C A T G C T A G T T T T T T T A C C A C T G 39 TP-3.8 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C A G C A T G C T A G T T T T T C T A C C A C T G 40 TP-3.9 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T C T T T A T T G C T G

102

Table 4-6. Continued

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Nucleotide position 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 1 5 5 6 7 8 9 0 0 1 2 2 3 3 4 5 7 7 9 0 0 1 2 3 4 5 5 6 6 6 6 7 8 8 0 0 0 1 1 2 2 3 3 5 5 5 5 7 8 9 9 9 9 0 0 1 2 2 3 3 3 3 5 6 8 8 9 9 9 9 0 0 1 1 2 3 5 6 S. no. Haplotype Ratio 1 7 1 6 8 9 0 7 5 8 8 1 8 0 9 4 3 1 4 2 4 8 2 2 1 9 0 5 0 1 2 7 8 0 9 2 4 5 0 1 0 7 1 4 1 2 5 9 6 7 1 4 8 9 0 8 7 1 3 0 1 2 6 7 8 1 8 0 5 6 8 0 3 3 5 6 7 4 2 41 TP-3.10 1/149 G A A T G T C T C T T A A T T A A G T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A C C A C T G 42 TP-3.11 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C G A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 43 TP-3.12 1/149 A A A T G T C T C T T A A T T A A A T A A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G G T C T G C A T G C C A G T T T T T T T A C C A C T G 44 TP-3.13 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A T T A C T G 45 TP-4.1 3/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T T G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 46 TP-4.2 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 47 TP-4.3 2/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A C G T T A G T T T T T T T A C C A T T G 48 TP-4.4 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C T T A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A T T G 49 TP-4.5 4/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C T C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 50 TP-4.6 1/149 A A A T G A T T C T T A A T T A G A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A T T G T T G 51 TP-4.7 1/149 A A A T G A T T T T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A C T T G C A T G C T A G T T T T T T T A T T G T T G 52 TP-4.8 1/149 A A A T G T C T C T T A A T T A A A T G A T C G A T T G A C C C A A T C A T C T T G T T G G G T T T G G A C C T G C A T G C C A G C T C T T T T A C C A C T G 53 TP-4.9 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C T C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A T T G T T G 54 TP-4.10 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C T C A A T C A T C T G G T T G G G C T T A G A T C T G C A T G C C A G T A T T T T T A C C A C T G 55 TP-4.11 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C T C A A T C A T C T G G T T G G G T T T A G A T C T G G A T G C C A G T T T T T T T A C C A C T G 56 TP-4.12 1/149 A G A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 57 TP-4.13 1/149 A A A T G A T T C T T A A T T A A A T G A T T A A T T G A C T C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 58 TP-4.14 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C T C A A T C A T C T G A T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A T T G 59 TP-4.15 1/149 A A A T G T C T C T C A A T T A A A T G A T T G A T T G A C C C A A T C A T C T T G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 60 TP-4.16 1/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T T G T T G G G T T T G G A T C T G C A T G C C A G T T T T C T T A C C A C T G 61 TP-4.17 1/149 A A A T G T C T C T T A G T T A A A T G A T T G A T T G A C T C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 62 TP-4.18 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T G T T G T T G 63 TP-4.19 1/149 A A A T G A T T C T T A A T T A A A T G A C T G G T T G A C T C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 64 TP-4.20 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G G C C C A A T C A T C T G G T T G G G T T T G G G T C T G C A T G C C A G T T T T T T T A C C A C T G 65 TP-4.21 1/149 A A A T G T C T T T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 66 TP-4.22 1/149 A A A T G T C T C T T A A T T A A A T G A T T A A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A C G T T A A T T T T T T T A C C A T T G 67 TP-4.23 1/149 A A A T G T C T C C T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A C G T T A G T T T T T T T A C C A T T G 68 TP-4.24 1/149 A A A T G A T C C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A C T T G C A T G C T A G T T T T T T T A T T G T T G 69 TP-4.25 1/149 A A A T G A T T C T T A A C T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A C C A C T G 70 TP-4.26 1/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A C C T G G T C G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 71 TP* 22/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 72 TP** 17/149 A A A T G A T T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T A G A T C T G C A T G C C A G T T T T T T T A C C A C T G 73 TP*** 2/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A C C C C T G 74 TP**** 6/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G C T T G G T T T G G A T C T G C A C G T T A G T T T T T T T A C C A C T G 75 TP***** 10/149 A A A T G T C T C T T A A T T A A A T G A T T G A T T G A C C C A A T C A T C T G G T T G G G T T T G G A T C T G C A T G C C A G T T T T T T T A C C A C T G 76 TP****** 9/149 A A A T G A T T C T T A A T T A A A T G A T T G A − − G A C C C A A C C A T C T G G C T G G G T T T G G A T C T G C A T G T C A G T T T T T T T A T T G T T G

TP*-1.1,16,17,36,40,47 -2.1,5,24,26,31,34,46 -3.12,21,45 -4.2,9,14,21,31,37 TP**-1.3,8,12,19,22,24,26,33,38,41 -2.8,10,32,35,39,40,45 TP***-1.30 -4.30 TP****-1.20,23 -2.3,4,19,43 TP*****-1.31-9.23,28,32 -2.7,22,27,36,38,44 TP******-1.9,10,39 -3.16,19,20,25,27,35

103

Table 4-7. The mtCO1 sequences that differ among Thrips palmi individuals.

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 Nucleotide position 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 4 5 5 5 5 6 6 3 4 7 2 6 8 3 6 7 8 0 1 2 3 6 8 9 9 0 7 7 7 9 0 4 S. no. Haplotype Ratio 0 4 9 9 0 7 4 7 0 0 8 3 8 9 3 6 3 4 8 2 3 8 8 1 3 1 TP-1.1 34/120 C T A T T T C T T T A A A A A A T T C A T T T A C 2 TP-1.2 1/120 C T A T T T C T T T A A A A A A T T A A T C T A C 3 TP-1.3 1/120 C T A T T T T T T T A A A A A A T T C A T T T A C 4 TP-1.4 1/120 T T A T T T C T T T A A A A A A T T C A T T T A C 5 TP-1.5 1/120 C T A T T T C T C T G A A A A A T T C A T T T A C 6 TP-1.6 1/120 C T A T T T C T T T A A A A A A T T C A C T T A C 7 TP-1.7 1/120 C T G T T T C T T T A A A A A A T T C A T T T A T 8 TP-1.8 1/120 T T A T T T C T T T A A A A A A T T C G T T T A C 9 TP-1.9 1/120 C T A T T T C T T T A A A A A A − − C A T T T A C 10 TP-2.1 1/120 C C A T − C C T T T A G A A A A T T C A T T C A C 11 TP-2.2 1/120 C C A T T C C C T T A A A A G A T T C A T T C A C 12 TP-4.1 1/120 C C A T T C C T T C A A G A A A T T C A T T C A C 13 TP-4.2 1/120 C C A T T C C T T T A A A G A A T T C A T T C G C 14 TP-4.3 1/120 C C A T T C C T T T A A A A A G T T C A T T C G C 15 TP* 73/120 C C A T T C C T T T A A A A A A T T C A T T C A C

TP* -2.11,12,13,19,20,24,26,27,28,29,31,32,35,38,39,40,41,42,43,44,46,48 -3.3,5,7,9,11,14,15,16,18,19,22,23,26,27,35,36,40,41,42,43,44,45, 47,48 -4.8,14,15,16,19,20,21,22,23,24,26,27,28,29,31,32,34,36,37,39,40,42,44,45,46,47,48

104

Table 4-8. The rDNA ITS2 sequences that differ among Frankliniella occidentalis individuals.

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 Nucleotide position 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 4 4 3 3 7 9 2 4 5 6 7 7 3 4 4 5 5 6 8 9 9 9 1 2 8 8 1 3 S. no. Haplotype Ratio 4 7 0 2 7 9 8 9 3 9 7 0 6 2 8 4 9 1 5 9 3 8 6 7 6 2 1 FO-1.1 17/105 A A G A T T C T T G G A C C A T G T T G A T − − G A 2 FO-1.2 1/105 A G G A T T T T T G G A C C A T G T T G A T − − G A 3 FO-1.3 1/105 A A G G T T C T T G G A C C A T G T T G G T − − G A 4 FO-1.4 1/105 A A G A T T C T T G G A C C A T G T T G G C − − G A 5 FO-2.1 1/105 G A G A T T C T C G G A C C A T G T T G G C T T G A 6 FO-3.1 1/105 A A G A C T C T T G A A C C A T G T T G G C T T G A 7 FO-3.2 1/105 A A G A T T C T T G G A C C G T G T T A G C T T G A 8 FO-3.3 1/105 A A G A T T C C T G G A C T A T G T T G G C T T G A 9 FO-3.4 1/105 A A G A T T C T T A G A T C A T G T T G G C T T G A 10 FO-3.5 1/105 A A G A T C C T T G G A C C A C G T T G G C T T T A 11 FO-3.6 1/105 A A G A T T C T T G G A C C A T G T C G G C T T G G 12 FO-4.1 1/105 A A G A T T C T T G G A C C A T T A T G G C T T G A 13 FO-4.2 1/105 A A A A T T C T T G G G C C A T G T T G G C T T G A 14 FO* 76/105 A A G A T T C T T G G A C C A T G T T G G C T T G A

FO* 2.8,16,22,23,29,30,34,35,37,38,40,41,43,44,45,48 -3.2,3,4,7,8,9,10,11,12,13,14,15,16,17,18,20,22,23,24,25,27,28,30,31,32,33,38,39,41,48 - 4.1,8,9,14,16,18,19,21,22,23,24,25,26,29,30,31,32,33,34,35,36,37,39,40,42,44,45,46,47,48

105

Table 4-9. The mtCO1 sequences that differ among Frankliniella occidentalis individuals.

Mutation number 1 1 1 1 1 1 1 1 1 1 2 2 2 2 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 Nucleotide position 1 1 1 1 1 1 1 2 2 2 2 3 3 3 3 3 4 3 3 3 4 4 8 1 1 3 3 5 8 9 1 5 6 9 0 2 5 8 9 1 S. no. Haplotype Ratio 0 1 4 1 8 8 3 4 3 7 8 9 0 6 2 8 7 3 1 2 3 9 4 1 FO-1.1 1/150 T T T T T A T C A T T T A T A T C T C A G T T 2 FO-1.2 1/150 T T T T C A T T A T T T A T A T T T C G G T T 3 FO-1.3 1/150 T T T T C A T C A T T T G T A T T T C A G C T 4 FO-1.4 2/150 T T T T C G T C A T T T A T A T T T C A G T T 5 FO-1.5 1/150 C T T T C A T C A T T T A T A T T C C A G T T 6 FO-2.1 2/150 T T T T C A C C A T T T A T A T T T C A G T T 7 FO-2.2 1/150 T T T T C A T C A T T T A C A T T T C A G T C 8 FO-2.3 1/150 T T C T C A C C A C T T A T A T T T C A G T T 9 FO-3.1 2/150 T T T T C A T C A T T T A T A T T T T A G T T 10 FO-3.2 2/150 T T T T C A T C G T T T A T A T T T C A G T T 11 FO-3.3 1/150 T C T T C A T C A T T T A T A C T T C A G T T 12 FO-3.4 1/150 T T T T C A T C A T A T A T G T T T C A A T T 13 FO-4.1 1/150 T T T C C A T C A T T C A T A T T T C A G T T 14 FO* 133/150 T T T T C A T C A T T T A T A T T T C A G T T

FO* -1.1,2,3,4,5,6,7,11,12,13,14,15,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,41,43,46 -2.1,2,3,4,5,6,7,9,12,13,14,16, 17,18,19,20,22,23,24,25,,28,29,30,33,34,35 -3.1,2,3,4,5,7,8,9,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,32,33,34,35,37,40, 42,43,44,46,47,48 -4.1,7,8,9,10,11,12,14,15,16,18,19,21,22,23,24,25,26,27,28,29,30,31,32,34,35,36,37,38,39

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SD*-1.20,26 -3.1,7,10,37 SD**-1.27 -3.8,13 SD***-1.5,18,19,28,39 -4.1,4,8,16,20,23,25,29,38 SD****-1.15 - 3.5,6,25,32,48 -4.4,12,18,24,26,28,34,39

Figure 4-1. An unrooted semi strict MP tree generated from rDNA ITS2 sequence obtained from 2 female and 2 male individuals of S. dorsalis. Clones from different individuals have been coded in different colors. Bootstrap values are on the branches. Haplotypes consisting clones of more than one individual have been marked with asterisks. Coding of these haplotypes consists of bold digits denoting the specimen number, which is followed by the clones it exhibited. For example, SD**-1.27 -3.8,13, means shared haplotype SD** consists of one clone (27) from specimen number 1 and two clones (8 and 13) from specimen number 3.

Blue: Specimen no.1, Red: Specimen no. 2, Green: Specimen no. 3, Dark blue: Specimen no. 4, Brown: Shared haplotype

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TP*-1.1,16,17,36,40,47 -2.1,5,24,26,31,34,46 -3.12,21,45 -4.2,9,14,21,31,37 TP**-1.3,8,12,19,22,24,26,33,38,41 -2.8,10,32,35,39,40,45 TP***-1.30 -4.30 TP****-1.20,23 -2.3,4,19,43 TP*****-1.31-9.23,28,32 -2.7,22,27,36,38,44 TP******-1.9,10,39 -3.16,19,20,25,27,35

Figure 4-2. An unrooted semi strict MP tree generated from rDNA ITS2 sequence obtained from 2 female and 2 male individuals of T. palmi. Clones from different individuals have been coded in different colors. Bootstrap values are on the branches.

Blue: Specimen no.1, Red: Specimen no. 2, Green: Specimen no. 3, Dark blue: Specimen no. 4, Brown: Shared haplotypes

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FO*-2.8,16,22,23,29,30,34,35,37,38,40,41,43,44,45,48 -3.2,3,4,7,8,9,10,11,12,13,14,15,16,17,18,20,22,23,24,25,27,28,30,31,32,33,38,39,41,48 - 4.1,8,9,14,16,18,19,21,22,23,24,25,26,29,30,31,32,33,34,35,36,37,39,40,42,44,45,46,47,48

Figure 4-3. An unrooted semi strict MP tree generated from rDNA ITS2 sequence obtained from 2 female and 2 male individuals of F. occidentalis. Clones from different individuals have been coded in different colors. Bootstrap values are on the branches.

Blue: Specimen no.1, Red: Specimen no. 2, Green: Specimen no. 3, Dark blue: Specimen no. 4, Brown: Shared haplotypes

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CHAPTER 5 SUMMARY

In the insect order Thysanoptera, the genus Scirtothrips Shull contains more than

100 thrips species, among which 10 species have been reported as serious pests of agricultural crops (Rugman-Jones et al. 2006). Within this devastating genus,

Scirtothrips dorsalis Hood is an emerging pest of various economically important host crops in the United States. Scirtothrips dorsalis is a polyphagous pest with more than

100 reported hosts among 40 different families of plants (Mound and Palmar 1981).

However, in the past two decades increased globalization and open agricultural trade has resulted in the expansion of the geographical distribution and host range of the pest. In a recent study, Kumar et al. (2012) reported this pest attacking 11 different hosts at a fruit nursery in Homestead, Florida. Interestingly, they were found to reproduce on nine plant taxa that had never been reported as hosts in the literature.

The small size and cryptic nature of adults and larvae enables S. dorsalis to inhabit microhabitats of a plant and in the field, often making monitoring and the identification difficult. Scirtothrips dorsalis’ life stages may occur on meristems and other tender tissues of all above ground parts of host plants. Consequently, the opportunity of trans- boundary transportation of S. dorsalis through the trade of plant materials is high.

Existence of any variation in phenotypic and genetic makeup of such a pest makes identification much more difficult. Thus, the overall goal of this study was i) to develop a reliable and accurate technique to identify S. dorsalis from single specimens and ii) to determine the extent of morphological and genetic variations in populations of S. dorsalis.

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Accurate identification of S. dorsalis is a fundamental requirement in development of effective quarantine and management strategies. Using Scanning Electron

Microscopy (SEM), high resolution images of adults and larvae of S. dorsalis were produced which will assist growers and extension personnel in identifying the pest with greater ease. Furthermore, a comparison of morphological traits of S. dorsalis populations from different geographical regions was conducted which can help in understanding the phenotypic variation of this pest. Specimens of S. dorsalis were obtained from five distinct geographical regions: New Delhi, India; Shizouka, Japan;

Negev, Israel; St. Vincent; and Florida, United States. Fourteen morphological characters of each of 10 adult specimens of S. dorsalis were measured and compared among the five populations. No significant differences were observed between the body lengths of the various S. dorsalis populations, which ranged from 0.85 mm (Negev) to

0.98 mm (Florida). When comparing 12 morphological characters, no significant differences were detected among the New Delhi, St. Vincent, Negev and Florida populations. However, when S. dorsalis adult specimens from the populations of each of these four regions were compared with specimens from the Shizouka population, significant differences were detected for two or five morphological characters, depending on the population. Thus, speciemens from the Japan population are more robust (i.e., mesothorax and metathorax is longer and wider, abdomen is wider) than specimens from the other populations. In addition, the mean lengths of body size among different populations did not vary directly or inversely with latitude.

Morphological and molecular techniques were coupled to develop a novel, quick, reliable and simple diagnostic method for identifying individual thrips specimens.

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Individual specimens (larvae and adults) of S. dorsalis are first subjected to morphological identification using high-resolution SEM. Then, the gold/palladium sputter coated thrips specimens are further processed for DNA extraction and PCR assay for molecular identification. The results of the study indicated that the sequence results of both mtCO1 and ITS2 rDNA genes of individual larvae and adults of S. dorsalis were in agreement with the taxonomic identifications conducted using SEM. Our results suggest that the two techniques together could be used to validate the identification of various thrips species using single specimens.

The genetic characterization of three economically important thrips species,

Scirtothrips dorsalis, Frankliniella occidentalis (Pergande) and Thrips palmi Karny was conducted using the mtCO1 and ITS rDNA genes. The high level of inter- and intragenomic variation of the ITS gene in all the three of the species would most likely preclude the use of this gene in molecular identification of the species. However, less intragenomic and intraspecific variation was observed in the conserved mitochondrial

CO1 region of the three pest species, indicating that this gene might be more useful for their taxonomic characterization. Results from different studies confirmed the existence of morphological and genetic variation in population of S. dorsalis that suggests the possibility of this species being a cryptic species complex.

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BIOGRAPHICAL SKETCH

Vivek Kumar was born in a small village named Ghoghardiha pertaining to

Madhubani district of Bihar in India. He received his bachelor’s degree in botany

(honors) at Sri Guru Teg Bahadur Khalsa College, University of Delhi, India. In the same year, he met his wife Garima Kakkar who was also a fellow student at the class and they got married after a span of 10 years. Vivek earned his master’s degree in agrochemicals and pest management from University of Delhi in 2005. After receiving master’s degree he worked as Senior Research Fellow at Department of Entomology,

Indian Agricultural and Research Institute under direction of Dr. A.V. N. Paul. In August

2007, he began a new journey and started his doctoral program at Department of

Entomology and Nematology, University of Florida. His doctoral work under supervision of Dr. Dakshina R. Seal was focused on studying morphological and genetic variation in population of an invasive thrips species, chilli thrips Scirtothrips dorsalis Hood. He received doctoral degree in spring 2012. Besides his Ph. D. project, he was also involved in several side projects in his lab. During his doctoral program, he received 7 different awards or scholarships for academic achievement and his contribution towards agricultural research. He also attended several regional, national or international conferences and presented/coauthored in more than 25 (4 invited) conference papers.

During his doctoral program, he published 9 refereed journal articles and 5 non refereed articles and meeting proceedings. After completion of doctoral program, he will be joining Dr. Lance Osborne’s lab at the University of Florida, to work as postdoctoral research associate. His long-term goal is to pursue a research career in the innovative

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and exciting field of entomology at the cutting edge of nature and technology to improve existing crop protection strategies and develop novel methods of pest control.

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