Bean Pod Mottle Virus Biology and Management in Iowa Jeffrey Donald Bradshaw Iowa State University

Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations

2007 Bean pod mottle virus biology and management in Iowa Jeffrey Donald Bradshaw Iowa State University

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This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. Bean pod mottle virus biology and management in Iowa

Jeffrey Donald Bradshaw

A dissertation submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

Co-majors: Entomology; Plant Pathology

Program of Study Committee: Marlin E. Rice, Co-major Professor John. H. Hill, Co-major Professor Larry P. Pedigo Matthew E. O’Neal Gary P. Munkvold Daniel S. Nettleton

Iowa State University

Ames, Iowa

2007

UMI Microform 3274880 Copyright 2007 by ProQuest Information and Learning Company. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code.

ProQuest Information and Learning Company 300 North Zeeb Road P.O. Box 1346 Ann Arbor, MI 48106-1346 ii

TABLE OF CONTENTS

ABSTRACT IV

CHAPTER 1. GENERAL INTRODUCTION 1 DISSERTATION ORGANIZATION 1 INTRODUCTION 1 OBJECTIVES 4 LITERATURE REVIEW 5 The bean leaf beetle 5 Bean pod mottle virus 7 Diseases incited, in part, by bean pod mottle virus 8 Host range of bean pod mottle virus 10 Virus transmission by beetles 11 Management of bean pod mottle virus 16 LITERATURE CITED 17 CHAPTER 2. DIGITAL ANALYSIS OF LEAF SURFACE AREA: EFFECTS OF SHAPE, RESOLUTION AND SIZE 29 ABSTRACT 29 INTRODUCTION 29 MATERIALS AND METHODS 30 RESULTS AND DISCUSSION 35 CONCLUSION 37 ACKNOWLEDGEMENTS 38 LITERATURE CITED 39 CHAPTER 3. NO-CHOICE PREFERENCE OF CEROTOMA TRIFURCATA (COLEOPTERA: CHRYSOMELIDAE) TO POTENTIAL HOST PLANTS OF BEAN POD MOTTLE VIRUS (COMOVIRIDAE) IN IOWA 47 ABSTRACT 47 INTRODUCTION 47 MATERIALS AND METHODS 49 RESULTS AND DISCUSSION 54 ACKNOWLEDGEMENTS 57 REFERENCES CITED 57 CHAPTER 4. IDENTIFICATION OF A NOVEL NATURALLY OCCURRING REASSORTANT OF BEAN POD MOTTLE VIRUS (COMOVIRIDAE: COMOVIRUS) FROM A NATIVE PERENNIAL PLANT AND THE MOLECULAR CHARACTERIZATION OF ADJACENT SOYBEAN-FIELD ISOLATES 66 ABSTRACT 66 INTRODUCTION 67 MATERIALS AND METHODS 69 RESULTS 73 DISCUSSION 74 ACKNOWLEDGEMENTS 76 LITERATURE CITED 77 CHAPTER 5. A MANAGEMENT STRATEGY FOR BEAN LEAF BEETLES (COLEOPTERA: CHRYSOMELIDAE) AND BEAN POD MOTTLE VIRUS (COMOVIRIDAE) IN SOYBEAN 92 ABSTRACT 92 INTRODUCTION 93 iii

MATERIALS AND METHODS 96 RESULTS 100 DISCUSSION 108 ACKNOWLEDGEMENTS 110 REFERENCES CITED 111 CHAPTER 6. GENERAL CONCLUSIONS 131

ACKNOWLEDGMENTS 138

ABSTRACT

Bean pod mottle virus (BPMV) and bean leaf beetles, Cerotoma trifurcata (Förster),

both reduce yield and seed quality in soybean, Glycine max (L.). Numerous beetle species

can transmit BPMV; however, recent outbreak populations of bean leaf beetles have

contributed to an epidemic of BPMV in soybean in Iowa. The objective of this research was

to understand or identify the contributing sources of the BPMV epidemic in nature and to

study novel chemical control tactics for the management of this pest complex. To facilitate

the measurement of leaf herbivory of leaves, a tool was developed for the digital measurement of leaf surface area. The effects of shape, size, and capture resolution on digital area measurement were investigated to accurately and precisely estimate leaf surface area.

The results indicated that image capture resolutions of either 118.16 or 236.27 pixels cm-1

(300 or 600 pixels in-1, respectively) had the least bias for a variety of sizes and were least

affected by shape geometry. Eighteen field-collected, perennial plant species were tested for the presence of BPMV and acceptability to bean leaf beetle herbivory. Five new food hosts,

Lespedeza capitata (Michaux), Lotus corniculatus L., Trifolium alexandrinum L., T. ambiguum Bieberstein, and T. incarnatum L., were discovered for bean leaf beetles and one new host, Desmodium illinoense Gray, for BPMV. All of these plant species emerge prior to normal emergence times for soybean in Iowa. The nucleotide and amino acid sequence from the D. illinoense BPMV isolate (I-Di1) was characterized. I-Di1 was determined as a new natural reassortant of BPMV belonging to RNA–1 subgroup I, RNA–2 subgroup II. The nucleotide and amino acid sequences from BPMV isolates (I-P) from an adjacent soybean field were partially characterized. The I-P isolates were all of RNA–1 subgroup II and thus do not appear to be related to I-Di1. However, based on nucleotide sequence analysis the v

within-field isolate diversity is high. Soybean growers desire earlier planting dates and given

the spring-feeding activity of the bean leaf beetle and the potential of early-season injury of

soybean from BPMV infection, early planting dates are at risk. Therefore the effects of seed- applied and foliar insecticides on this pest complex were studied within the context of the

currently-recommended management strategy: the use of insecticides to reduce F0 and F1 bean leaf beetle populations. The use of a seed-applied insecticide to target F0 beetles

(followed by a foliar insecticide application targeting F1 bean leaf beetles) gave the greatest

improvement in yield (0.9 q ha-1 [~ 1.3 bu a-1] at two locations in one year. However, seed quality was protected most if a foliar insecticide was used to suppress F0 and F1 beetles. This

work presents discoveries regarding the host range of bean leaf beetles and BPMV, evidence

for within-field evolution of BPMV, and provides research results for a novel management

tactic for controlling bean leaf beetles and BPMV. 1

CHAPTER 1. GENERAL INTRODUCTION

Dissertation Organization

This dissertation is organized into six chapters. The first chapter is a general introduction and includes research objectives and a literature review relevant to bean leaf beetles, Cerotoma trifurcata (Förster), and Bean pod mottle virus (BPMV). Chapters two through five are either written for submission to or are currently accepted or published in a scientific journal. Chapter two presents the development and evaluation of a tool for surface area measurement. Chapter three reports on a study of the host–range overlap of bean leaf beetles and BPMV. Chapter four is a description of a new strain of BPMV from a prairie area and reports the results of a study of the distribution of BPMV isolates collected in an adjacent soybean field. Chapter five reports on the results of a three-year study using seed–applied and foliar insecticides to control bean leaf beetles for the reduction of BPMV incidence in soybean. Chapter six includes the general conclusions from this dissertation. An acknowledgments section concludes this work.

Introduction

In 2006, the United States produced 870 million quintals (~3.2 billion bushels) of soybeans, Glycine max (L.), with a value of $19.7 billion, on 30.2 million hectares (74.6 million acres) (USDA 2007). This production level represents approximately 37.8% of the world’s soybeans (USDA 2007). Iowa, from its 4.1 million hectares (10.2 million acres) planted, contributed 16.6% of the total U.S. soybean production and 6.3% of the world’s soybean production (USDA 2007). Only Illinois occasionally out-competes Iowa for total

U.S. soybean production. 2

Soybean yield is impacted negatively by pests individually and by pest interactions

(Russin and Boethel 1994). Weed interference to soybean has accounted for most yield loss by resource competition (McWhorter and Patterson 1979). Approximately 95% of soybeans are treated with herbicide in the U.S.; however, weed infestations result in approximately 82 million quintals (300 million bushels) in losses annually (Mortensen 1994). This impact from weeds remains and is substantial when herbicides are either not used or are ineffective (Wax and Stoller 1984, Anderson 1996). In general, pest problems are less prevalent in the northern latitudes and damage is more severe in the southern United States (Way 1994).

However, in the North Central states, insect outbreaks can have a large impact because of the economic dependence afforded to specific crops in this region.

In general, the most damaging arthropods of soybean in the U.S. are the velvetbean caterpillar, Anticarsia gemmatalis Hübner; soybean looper, Pseudoplusia includens

(Walker); green cloverworm, Hypena scabra (Fabricius); Mexican bean beetle, Epilachna varivestis Mulsant; bean leaf beetle, Cerotoma trifurcata (Förster); (Way 1994) and soybean aphid, Aphis glycines Matsumura (Ragsdale et al. 2004). The four most economically important (at least sporatically) arthropod pests of soybean in the North Central states are the twospotted spider mite, Tetranychus urticae Koch (Haile and Higley 2003); green cloverworm, H. scabra (Morjan and Pedigo 2002); soybean aphid, A. glycines (Ragsdale et al. 2004); and bean leaf beetle, C. trifurcata (Krell et al. 2004). The cumulative and additive effects of these pests are not fully understood; however, the economic injury levels (EILs) for

H. scabra and C. trifurcata are known (Pedigo 1994a,b). In general, most EILs may only consider additive effects of multiple pests; however, their interactions may also be important 3

(Hammond 1996). These pest-pest interactions may be very subtle such as those found between pestiferous insects and the plant viruses they transmit.

Currently, there are seven insect orders that contain known plant-pathogenic virus vectors; Orthoptera, Dermaptera, Coleoptera, Lepidoptera, Diptera, Thysanoptera, Hemiptera

(suborders, Homoptera and Heteroptera) (Hull 2002). The suborder Homoptera contain the most insect vectors (~300 species) and the order Coleoptera with 38 species are second most.

According to Demski and Kuhn (1989), 109 viruses occur naturally or by mechanical inoculation in soybeans. Interestingly, in Central America, beetle-transmitted viruses are the largest group of insect-borne viruses of legumes (see Gamez 1983).

Bean leaf beetle populations have gone through large fluctuations during the past decade in the North Central states (Giesler et al. 2002). These large populations have resulted in an apparent increase in the prevalence of Bean pod mottle virus (BPMV); a virus that is efficiently transmitted by the bean leaf beetle (Ghabrial and Schultz 1983). A crucial step toward managing the epidemiology of any disease is to understand the source of inoculum.

Bean pod mottle virus is prevalent throughout the Americas (Milbrath et al. 1975, Pitre et al.

1979, Hopkins and Mueller 1983, Lin and Hill 1983, Ghabrial et al. 1990, Fribourg and Perez

1994, Michelutti et al. 2002, Anjos et al. 1999, Sikora and Murphy 2005) yet no primary source has been identified.

Krell et al. (2003) found a low frequency of transmission from overwintered beetles or seed (0–0.037% and 0–1.6%, respectively). Surveys for host plants that might serve as a reservoir for BPMV have identified Desmodium spp. as a host for BPMV (Moore et al. 1969,

Krell et al. 2003). In fact, Krell et al. (2003) found of 112 plants, representing 23 species, tested for BPMV only 2 plants were positive for BPMV. Both BPMV-positive plants were 4

Desmodium canadense (L.). However, for a wild host plant to be an important source of

inoculum for BPMV in soybean it would also need to be an acceptable host for its insect

vectors. Henn (1989) studied the feeding behavior of bean leaf beetles on a broad range of plants; however, no study has focused specifically on the host acceptance of bean leaf beetles on early-season perennial plants.

Bean leaf beetle populations are governed by abiotic factors such as winter temperature in temperate climates (Lam and Pedigo 2000, Lam et al. 2001a, Carrillo et al.

2005). To exploit this environmental dependence, tools have been developed to predict bean leaf beetle populations to facilitate management decisions (Lam and Pedigo 2000). These

management decisions now include whether to treat soybeans with insecticides early and in

the middle of the growing season (Krell et al. 2004) or to alter planting dates (Pedigo and

Zeiss 1996, Krell et al. 2005) to control bean leaf beetles or to select a soybean variety with field tolerance against BPMV (Hill et al. 2007). Seed-treated insecticides first received registration for use in soybean in 2002 (Rice 2002); however, their effects against bean leaf beetles and BPMV have not been studied extensively.

Objectives

1. Host range biology and ecology

• Develop a technique to reliably measure insect leaf herbivory. To determine

the error rate for using digital image capture for measuring leaves of differing

shapes, sizes, and capture resolution.

• Identify host plants for bean leaf beetles and bean pod mottle virus. To

determine the potential host–plant range overlap between BPMV and its principle

vector in the North Central states. 5

• Characterize isolates of bean pod mottle virus. Determine the strain identity of

isolates discovered from wild perennial hosts and investigate their potential

ecological role in soybean. Some wild host plants have been deemed an important

source of inoculum for BPMV.

2. Disease management

• Evaluate the use of seed-applied insecticides in soybean for managing bean

leaf beetles and BPMV. Regardless of an increased risk to soybean yield and

seed quality from pests and pathogens, growers desire earlier planting dates. In

particular, early–planted soybean is at risk of higher infestations of bean leaf

beetles and early inoculation of BPMV to the crop. Seed-applied insecticides may

provide a novel soybean management strategy for the control of bean leaf beetles

for the suppression of BPMV.

Literature Review

The bean leaf beetle

Until recently (Krell and Rice 2000), Bean pod mottle virus (BPMV) had not been recognized as an economic concern in the North Central states. The bean leaf beetle is the principal vector of BPMV (Mueller and Haddox 1980); however, most research has focused on their injurious feeding on legumes (e.g., Chittenden 1891, Smelser and Pedigo 1992a,

Pedigo and Zeiss 1996, Lam and Pedigo 2000). Adult bean leaf beetles injure soybeans by feeding on leaves, stems, and pods (Smelser and Pedigo 1992ab, Pedigo 1994b). Pod and peduncle-feeding directly decrease pod yield and soybean quality (Smelser and Pedigo 6

1992). The larvae are soil-inhabiting, feeding on leguminous roots and preferring root

nodules (McConnell 1915, Leonard and Turner 1918, Pedigo 1994b).

Bean leaf beetles were first described by Förster in 1771 (see Eddy and Nettles 1930) and are of two (Smelser and Pedigo 1991) or six (Herzog 1968, 1973) base colors and with zero to two spots per elytron. This North American, endemic insect will feed on, in addition to many legumes: stinging nettle, Urtica dioica L.; wood nettle, Laportea canadensis (L.)

Gaud.; and Euonymous atroperperea Jacq. (Helm et al. 1983); pumpkin, Cucurbita pepo L.,

and squash, Cucumis sativus L. (Koch et al. 2004); and corn, Zea mays L. (Metcalf and

Metcalf 1993). Bean leaf beetles are bivoltine in Iowa (Smelser and Pedigo 1991) and

overwinter as adults in soybean fields and woodlands (Lam and Pedigo 2000). After

overwintering, bean leaf beetles emerge and can be found feeding on or infesting perennial

legumes in late April to early May (Smelser and Pedigo 1991). As soon as soybeans emerge,

beetles move into soybean fields (late May), mate, and deposit eggs. The larvae from these

eggs pupate in the soil and give rise to the first generation (late June to early July). The

second generation occurs from August to late September. There is usually a gradual increase

in population density from F1 to F2 generations with most feeding injury to soybeans during

their reproductive growth phase.

In 2001, bean leaf beetle populations reached their greatest abundance within the past

decade having increased ~ 165% of their 1996 levels at one location in Iowa (Bradshaw and

Rice 2003). This population increase statewide, in part, has contributed to an increased

BPMV incidence in Iowa (Yang 1999). In fact, BPMV field-incidence is correlated

positively with bean leaf beetle populations (Mueller and Haddox 1980). The greatest 7

increase in BPMV-infection occurs after the F1-bean leaf beetle density peak (Hopkins and

Mueller 1983).

Bean pod mottle virus

First reported as a viral disease of garden beans by Zaumeyer and Thomas (1949),

BPMV was later found in soybeans (Skotland 1958, Walters 1958) and the first published

report of the virus in Iowa was by Quiniones and Dunleavy (1971). Bean pod mottle virus is

in the Comovirus group that is partly characterized by having two single stranded, positive-

sense RNAs encapsulated by an icosahedral coat protein (Hull 2002, Šutić et al. 1999). The genome of BPMV is expressed by the synthesis and subsequent proteolytic cleavage of large polyproteins; giving rise to five (from RNA–1) (Di et al. 1999) and three (from RNA–2)

(MacFarlane et al. 1991) mature proteins. RNA–1 synthesizes proteins that are important for replication (Di et al. 1999) as evidenced by the ability for RNA–1 to replicate in absence of

RNA–2 (Hull 2002). Additionally, the genetic determinants for severity are found on RNA–1

(Gu and Ghabrial 2005). RNA–2 synthesizes the large and small coat proteins, 58k RNA–2 replication co-factor and movement protein (MacFarlane et al. 1991, Hull 2002).

Based on genetic studies of BPMV there are two subgroups of RNA–1 and RNA–2 in nature (Gu et al. 2002). Both subgroups and also reassortants were identified but only the partial diploid reassortants were molecularly characterized (Gu et al. 2002, Gu et al. 2007).

Interestingly, BPMV infection by the combination of both subgroups of RNA–1 was demonstrated to induce very severe symptoms on soybean (Gu et al. 2007).

On soybeans, BPMV may cause a severe systemic mottling with a puckering of leaves and mottling of pods and seed coats (Stace-Smith 1981); however, symptomatic 8 response varies by soybean variety (Walters 1970, Scott et al. 1974, Windham and Ross

1985, Hill et al. 2007) and soybean stage at inoculation (Windham and Ross 1985, Dorhout and Krell, personal communication). Additionally, the foliar symptoms of BPMV are masked by cool temperatures (Walters 1970).

Since foliar symptoms are an unreliable indication of virus-presence in a crop, molecular techniques, e.g., biotin-avidin double antibody sandwich, enzyme-linked immunosorbent assay (ELISA) has been tested for detection of BPMV in field samples

(Gahbrial and Schultz 1983). Poor yield is another symptom of BPMV; caused by reduced seed size and pod set (Walters 1970) with as much as 36−52% loss in yield for some varieties if inoculated during early growth stages (Hopkins and Mueller 1984). This affect on soybean yield is most severe when soybeans are infected as seedlings (Demski and Kuhn 1989). Seed- infection either does not occur (Skotland 1958, Schwenk 1980) or occurs at a very low infection-rate (Lin and Hill 1983, Krell et al. 2003), with the virus usually present in the seed coat (Schwenk 1980). Additionally, when present, BPMV symptoms can be difficult to distinguish from other viral symptoms (e.g., Soybean mosaic virus, SMV).

Diseases incited, in part, by bean pod mottle virus

The impact of BPMV is not limited to its singular affect on soybeans. For example, soybean doubly infected with BPMV and SMV have a higher titer of BPMV (Calvet and

Ghabrial 1983), reduced nodulation (Tu et al. 1970), and greater yield reduction than soybean infected only with BPMV (Ross 1963, Walters 1970, Calvert and Ghabrial 1983, Demski and

Kuhn 1989). Additionally, SMV is transmitted by the soybean aphid (Wang and Ghabrial

2002, Domier et al. 2007). However, insecticide treatments apparently have no impact when 9

epidemiological growth rates of SMV are high (Burrows et al. 2005). The impact from the

interaction of these two insects and the viruses they transmit is not fully known. Bean pod

mottle virus infection can also delay soybean senescence (Schwenk and Nickell 1980),

occasionally resulting in an increase in seed-borne fungi (e.g., Cercospora spp. and

Phomopsis spp.) (Demski and Kuhn 1989).

Soybean mosaic virus and BPMV can increase susceptibility to Phomopsis seed

decay (Ross 1977, Stuckey et al., 1982, Koning 1999, Koning et al. 2003).The Phomopsis–

Diaporthe complex in soybean results in three diseases: 1) seed decay is incited by

Phomopsis longicolla Hobbs (telomorph unknown), 2) northern stem canker caused by

Diaporthe phaseolorum (Cook and Ellis) Sacc. var. caulivora Athow and Caldwell

(anamorph unknown); and 3) southern stem canker caused by D. phaseolorum f. meridionalis

Morgan-Jones (anamorph unknown), and pod and stem blight is incited by D. phaseolarum var. sojae (Lehman) Wehrmeyer [anamorph Phomopsis phaseoli (Desmaz.) Sacc. Synonym

P. sojae Lehman] (Kmetz et al. 1974, Kmetz et al. 1978, Hobbs et al. 1985, Morgan-Jones

1989). All of these pathogens contribute to Phomopsis seed decay, an important disease complex of soybean, with P. longicolla being the main cause of seed deterioration. This fungal incidence increases with high levels of rain, temperature, and relative humidity

(Kmetz et al. 1979).

Increased susceptibility to Phomopsis seed decay in SMV- and BPMV-infected soybeans apparently is due to the effect these viruses have on senescence. Both viruses cause

a “green stem” or delayed senescence of soybeans (Abney and Ploper, 1994, Koning 1999).

This effectively delays harvest of the beans by causing them to retain moisture for an

extended period, thereby indirectly increasing the severity of Phomopsis seed decay, 10 especially when accompanied by a warm and humid environment. Koning (1999) found the association between SMV and Phomopsis spp. to result in low seed germination and seedling vigor, and suggested planting SMV-resistant varieties to reduce Phomopsis seed decay.

Host range of bean pod mottle virus

The relationship between the bean leaf beetle and BPMV was first reported by Ross

(1963) and the principal vector of BPMV in soybean is the bean leaf beetle (Mueller and

Haddox 1980). However, there are other coleopterous vectors of BPMV within the

Chrysomelidae (Horn et al. 1970, Mabry et al. 2003, Werner et al. 2003), Meloidae (Patel and Pitre 1971), and Coccinellidae (Fulton and Scott 1974). The susceptible host range of

BPMV, by mechanical inoculation, includes plants in the Apocynaceae, Chenopodiaceae, and Fabaceae (=Leguminosae) (subfamilies, Caesalpinioideae and Papilionoideae) and nonsusceptible plant hosts are found in the Compositae, Cruciferae, Cucurbitaceae,

Solanaceae, and Fabaceae (subfamily Papilionoideae) (Brunt et al. 1996). Although transmission has been demonstrated from Desmodium paniculatum (L.) to soybean via bean leaf beetles (Waldbauer and Kogan 1976), the range of possible naturally occurring hosts susceptible to both vector and virus is still unknown. This could be central to the determination of the primary inoculum source of BPMV.

Krell et al. (2003), upon examination of potential primary inoculum sources, estimated a low frequency of BPMV transmission from seed and overwintered bean leaf beetles of 0.037% and 1.6%, respectively. Additionally, of 23 field-collected plant species tested, only Desmodium canadense (L.) was positive for BPMV. Perennial host plants are thought to be an important source for BPMV (Moore et al. 1969, Horn et al. 1970, Stace- 11

Smith 1981, Krell et al. 2003), possibly because of the opportunity for the virus to overwinter

within the plant. However, in Iowa distribution of this host plant does not fully explain the

temporal appearance and ultimate impact of the disease (Krell et al. 2004).

Virus transmission by beetles

Transmission of plant viruses by beetles is multifaceted and can include larvae-host,

beetle-beetle (adults), and beetle-host interactions. Larvae of Phaedon cochleariae

(Fabricious) and Oulema melanous (L.) (Chrysomelidae) transmit plant viruses and, depending on the virus, may be more or less efficient vectors than adults. This variability in virus transmission efficiency is also true for the Mexican bean beetles, Epilachna varivestis

Mulsant (Markham and Smith 1949, Nault et al. 1978). Both adults and larvae of Mexican bean beetles feed on leaves and transmit viruses (Fulton and Scott 1974, Jansen and Staples

1970). In contrast, many chrysomelid larvae are root feeders, and the difficulty of working with this subterranean life-stage probably has contributed to the lack of information on larvae as vectors (Fulton et al. 1987). Likewise, little information exists on the transmission of plant pathenogenic viruses between beetles. However, according to Nault (1997), beetles that transmit “circulative” (but not propagative) viruses should not transmit viruses transovarially.

Additionally, beetles may indirectly become infected by ingesting infected feces (Fulton and

Scott 1980, Fulton et al. 1987). The role of coprophagy in transmission has not been studied in leaf-feeding beetles; however, viruses have been detected in the feces of adults and larvae

(Slack and Fulton 1971, A’Brook and Benigno 1972).

Mode of transmission. Phytophagous insects transmit viruses primarily in three ways (Harrison and Murrant 1984, Agrios 1997). Haustellate insects can carry viruses on 12

their mouthparts; these viruses are termed nonpersistent. Nonpersistant viruses are acquired

quickly on the insect’s mouthparts and remain there for several hours unless the stylet enters beyond the epidermis (Nault 1997). In haustellate and mandibulate insects, some viruses take much longer for acquisition and persist in the vector’s foregut for longer periods; these are termed the semipersistent viruses. Still, other viruses persist for long periods within the vector (sometimes for the life of the animal). These viruses, known as persistent viruses, pass through the gut wall and are found in the hemolymph (and the salivary glands of some

Homoptera). These viruses can pass through the hemolymph to the mouthparts to be introduced again to the host. Some persistent viruses also propagate in their host as is

common in some Homoptera.

Early vector transmission studies reported that beetles transmitted viruses to plants by

a simple mechanical process involving the contamination of mouthparts (Smith 1924).

However, it is currently thought that both foregut-borne and circulative types of virus

transmission are found in some beetles (Nault 1997). Black (1970) defined the term

“circulative” to describe viruses that are ingested, pass through the gut wall into the

hemolymph, and pass to the salivary glands to be discharged with the salivary secretions.

Although some beetles have a circulative-like viral transmission (i.e., virus passes through

the hemolymph), viral transmission in beetles does not fit Black’s (1970) definition of

circulative transmission in two ways: beetles do not have salivary glands (i.e., labial glands)

(Chapman 1998), and beetles may or may not have virus particles in their hemolymph (e.g.,

Slack and Scott 1971, Wang et al. 1992).

Some confusion exists in the literature as to what head glands are present in beetles.

Some authors have stated that beetles have maxillary glands (e.g., Srivastava 1959, Fulton 13 and Scott 1980, Gergerich et al. 1983). However, the Coleoptera do not have maxillary glands according to Snodgrass (1935) and Chapman (1998), but have mandibular glands of unknown function. Chapman (1998) states that there are three glands associated with the gnathal segments of an insect head: maxillary glands (found in the Protura, Collembola,

Heteroptera, and some larval Neuroptera and Hymenoptera), labial glands (found in all major insect orders except the Coleoptera), and mandibular glands (found in the Apterygota,

Blattodea, Mantodea, Isoptera, Coleoptera, and Hymenoptera). Additionally, Srivastava

(1959) reported that labial-gland-like structures are found in the Coccinellidae. If this is true, the function of regurgitant on viruses transmitted by leaf-feeding coccinellids may differ from that of chrysomelids. The maxillary glands may and labial glands do, according to

Chapman (1998), introduce lubricants into the buccal cavities of insects, whereas Srivastava

(1959) defines maxillary glands as not producing saliva. It may be that Chapman (1998) has overlooked Srivastava (1959); however, it is curious that Srivastava (1959) included no reference to Snodgrass (1935) and his discussion of maxillary and mandibular glands.

Mechanism of transmission. Once virus is ingested it can be regurgitated with foregut fluids, pass through the mid-gut into the hemolymph, or be expelled with the feces.

Virus is incorporated into salivary secretions after a single bite, with acquisition increasing with more extensive feeding (Nault 1997). Markham and Smith (1949) suggested that beetle regurgitant may influence virus transmission, which later was confirmed by Gergerich et al.

(1983).

Gergerich et al. (1983) developed a “gross wounding inoculation” technique using a glass cylinder of 7 mm in diameter dipped into infected beetle regurgitant to simulate beetle feeding. Mechanical inoculation of virus (using carborundum dust) with Mexican bean beetle 14

regurgitant efficiently inhibited both beetle- and non-beetle-transmissible viruses at a dilution

≤1:20 (Kopek and Scott 1983, Gergerich et al. 1983), whereas selective transmission was

shown using the gross wounding technique, with three leaf-feeding beetle regurgitants, at a

dilution ≥1:12.5 (Gergerich et al. 1983) (i.e., the titer required for the gross wounding

technique is higher than for mechanical inoculation with virus-infected beetle regurgitant). It

has been concluded that bean leaf beetle, spotted cucumber beetle, Diabrotica

undecimpunctata howardi Barber, and Mexican bean beetle regurgitants contain selective

factor(s) that reduce or prevent infection of plants by non-beetle-transmissible viruses (e.g.,

zucchini yellow mosaic virus, tobacco mosaic virus, tobacco ringspot virus, and the cowpea

strain of tobacco mosaic virus) (Gergerich et al. 1983, Monis et al. 1986).

According to Harrison and Merrant (1984), virus-specific proteins apparently are associated with many (if not all) types of vector transmission. Beetle regurgitant has many enzymes (e.g., proteases, nucleases, and cellulases) that can affect viruses (Gergerich and

Scott 1991, Gergerich et al. 1986, Gergerich and Scott 1988, Langham et al. 1990).

Ribonuclease, found in the regurgitant of leaf feeding beetles, has been shown to elicit a

similar selective, inhibitory effect on non-beetle-transmissible virus as regurgitant (Gergerich

et al. 1986). However, as with beetle regurgitant, ribonuclease does not permanently affect the infectivity of viruses (Monis et al. 1986). Langham et al. (1990) showed that the

regurgitant of bean leaf beetles, spotted cucumber beetles, and Mexican bean beetles can

convert the electrophoretic form of comoviruses. The electrophoretic forms of these viruses

do not have different infectivities when inoculated mechanically or by the gross-wounding

method; however, if incubated in beetle regurgitant in vitro or in vivo, the infectivity is

changed. This change in electrophoretic mobility could result essentially in the activation of a 15

beetle-transmissible virus and the inactivation of non-beetle-transmissible viruses.

Additionally, Lagham et al. (1990) found that beetle regurgitant contained approximately ten

times more protease (which has a digestive affect on virus-coat proteins) than bean sap.

Gergerich and Scott (1988) confirmed that, in general, beetle-transmissible viruses

translocate through plant xylem (and to undamaged cells) whereas non-beetle-transmissible

viruses do not. They concluded that gross wounding inoculation or beetle feeding prevents

infection at the point of virus introduction via regurgitant and that only translocatable viruses

(that can infect non-wounded cells) are viable under these conditions. Further, Gergerich et al. (1991) suggested that the inability of some viruses to translocate is probably due to some virus-surface property (e.g, partial digestion of the coat protein or change in the electrophoretic mobility).

Virus acquired by beetles is retained for a short time in their crop; however, the titer increases with more extensive feeding, (Nault 1997). Depending on the vector-virus combination, viruses may also be found in beetle hemolymph (Slack and Scott 1971; Scott and Fulton 1978; Wang et al. 1992, 1994). Slack and Scott (1971) reported that retention time of the cowpea strain of SMV survives in bean leaf beetle hemolymph for at least 10 days. However, circulative transmission is not required for efficient transmission of the cowpea strain of SMV, Southern bean mosaic virus (SBMV), and BPMV (Wang et al.1992).

In the Homoptera, the presence of plant viruses in hemolymph has been studied more thoroughly (Harrison and Murant 1984, Hull 2002). For example, at the cellular level, receptor-mediated endocytosis (Campbell 1993) is an important mechanism in Luteovirus transmission in aphids. Gildow (1982) found that coated vescicles, containing Luteovirus, can form from the plasmalemma of the accessory salivary glands of aphid vectors. The 16

coated vescicles are then taken up by the microvilli of the salivary canal and virus is thereby

transmitted to a host. Alternatively, the viruses may penetrate the accessory salivary glands

by direct passage through the plasmalemma to the microvilli.

Wang et al. (1994a) confirmed that some beetle-transmittable and non-beetle-

transmittable, circulative viruses pass through the midgut and not the sclerotized, foregut-

lining. They also found that SBMV and the cowpea strain of SMV can pass through the

midgut without any observable damage to the peritrophic membrane.

The digestive physiology of the Coleoptera is poorly understood (Langham et al.

1990). Indeed the same could be said for the virus-vector relationships of beetles and their

hosts. Although trypsin or trypsin-like activity has been suggested as a component of capsid

protein digestion (Langham et al. 1990), more needs to be done to synthesize knowledge of

beetle physiology with virus biology. For example, the digestion of proteins of Aedes spp. mosquitoes are under secretagogue control (see Chapman 1998). Perhaps a similar mechanism is regulating the digestion of coat proteins of viruses; therefore, successfully transmitted viruses may have evolved to avoid the vector’s endopesidases. Although not studied in this work, the mode and mechanism of virus transmission of beetles deserves further investigation. Better understanding of beetle transmission could provide a key insight into how viruses are dispersed in the environment and how new strains arise.

Management of bean pod mottle virus

Damage to soybean from C. trifurcata can be reduced by later planting (Pedigo and

Zeiss 1996, Witkowski and Echtenkamp 1996), host-plant resistance (Hammond et al. 2001,

Lam 2001b, Srinivas et al. 2001), or population suppression by chemical control (Lam et al. 17

2000b, 2001a). Management actions that affect a vector population can impact their

transmissible agents (Perring et al. 1999); however, the affects of C. trifucata management

tools and tactics on BPMV transmission are not fully understood. For example, early-planted

soybeans apparently are more susceptible to BPMV (Giesler et al. 2002); however, Krell et

al. (2005) found that delayed soybean planting inconsistently reduced the seed-borne

incidence of BPMV. Various types of host-plant resistance can reduce C. trifurcata injury to

pods (Lam 2001b) and leaves (Hammond et al. 2001, Srinivas et al. 2001) and, although

pathogen-derived resistance has been developed against BPMV (Reddy et al. 2001), no C.

trifurcata resistance tool has been tested against BPMV. Even trap crops (Newsom and

Herzog 1977) and barrier crops (Gamez and Moreno 1983) have been suggested as possible management tactics. Krell et al. (2004) studied the impact of carefully-timed chemical control of C. trifurcata and reported that a reduction in vector abundance could reduce the

incidence of BPMV, improve yield, and protect seed quality. However, the correct timing of the insecticide application is crucial. This was particularly true for insecticides targeting F0

and F1 populations and has since been a recommended practice for soybean grown for food

and seed in Iowa (Rice et al. 2007).

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CHAPTER 2. DIGITAL ANALYSIS OF LEAF SURFACE AREA: EFFECTS OF SHAPE, RESOLUTION AND SIZE

A paper accepted in the Journal of the Kansas Entomological Society

Jeffrey D. Bradshaw1, Marlin E. Rice1, and John H. Hill2

1Department of Entomology

2Department of Plant Pathology

Iowa State University,

Ames, IA 50011

Abstract

The effects of shape, size, and capture resolution on digital area measurement were

investigated to accurately and precisely estimate leaf surface area. A digital scanner was

used to measure two simple shapes (circle and square) at three resolutions (118.159, 236.270

and 472.441 pixels/cm) and five sizes (3.14, 12.58, 28.29, 50.29, and 78.60 cm2).

Additionally, the accuracy and precision of two digital scanner models were compared using

two shapes (circle and square) of similar size at five resolutions (29.528, 39.370, 59.055,

118.159, 236.270, and 472.440 pixels/cm). A method is described to measure leaf area using

an image histogram and photographic software tools (Photoshop®). This method was

validated by comparison of the digitally captured images to a leaf area meter (LI-COR®

3100). Overall, simple changes in shape have a statistically significant effect on the accuracy

of digital measurements of area for some sizes and resolutions.

Introduction

As early as 1928, photoelectric devices were used to measure leaf area (Květ and

Marshall, 1971). With devices such as the photoelectric planimeter, leaf area could be 30

quantified with a level of precision between 4-100 mm2 depending on a number of settings or

modifications. Then, with computers and more sophisticated light-scanning technology of the

1970’s, electronic leaf area meters allowed measurements as small as 1 mm2 (Kogan and

Turnipseed, 1980) and apparently 0.1 mm2 (LI-COR® Incorporated 2004). The leaf area

meter is still used as the standard for validating new tools and techniques for measuring leaf area (Bowers et al., 1999; O'Neal et al., 2002).

Tools and techniques for analyzing digital images are common in science. Various companies and organizations advertising digital software claim to measure many facets of a digital image (Russ, 2004; NIH, 2007). Additionally, with computer programs that allow batch-processing, large sample sizes could be analyzed efficiently. O’Neal et al. (2002)

demonstrated that an inexpensive, flatbed scanner is an accurate and precise tool for measuring leaf area and herbivory. However, they did not determine the most accurate and precise resolution for image capture. Additionally, the effects of varying shapes and surface areas on accuracy and precision were not described. We adapted a technique, similar to

O’Neal et al. (2002), for use with an image histogram. Using this technique, we determined the effects of shape, size, and image resolution for image analysis and data acquisition, the consistency of the effects of shape and resolution between two digital scanners, and the relative relationship between our described technique and a leaf area meter in measuring leaf area.

Materials and Methods

For all experiments in this study, we used Adobe® Photoshop® (Adobe Systems

Incorporated, 2002) to record repetitive imaging tasks. This was accomplished by using a

GUI (graphical user interface)-based scripting program. Adobe Photoshop terms these 31

scripted programs “actions”. Such scripting or actions allows a series of repetitive tasks to be

recorded and can be run on multiple image files via “automation” or batch processing. To

count pixels in digital images an action was created to automatically open an image file,

display the image histogram (using the “Histogram” function), wait until commanded to exit

the histogram (i.e., press enter), and close the file. This action was combined with a batch

process that we created, that would serially apply the action to all of the files in a directory.

The total pixel count is displayed in the histogram window, labeled “Pixels”, and the number

of black pixels can be determined by resting the computer cursor over the histogram at level

0 and recording the number of pixels (labeled as “Count” within the histogram window). For more intuitive comparisons, digitally scanned areas (in pixels) were converted to square centimeters by dividing the number of black pixels into the number of total square pixels/cm in the images as determined by Photoshop, i.e.,

2 black pixels Area() cm = 2 . ()total pixels cm

Experiment 1

Comparison of shape, size, and resolution for image analysis. To determine the influence

of shape and size on scanner accuracy (i.e., measured area minus expected area) and precision (i.e., standard error of the mean of the measured area) we used two uniform shapes

(circle and square) and scanned them with a digital scanner, Hewlett-Packard™ Scanjet 4670

(Hewlett-Packard Company, L.P., Palo Alto, Calif.). Images were captured with 1 bit per pixel. For each shape five sizes were compared (3.14, 12.58, 28.29, 50.29, and 78.60 cm2).

Shapes were constructed using Photoshop with 472.441 pixels/cm and printed with 472.441

pixels/cm on a Hewlett-Packard Laserjet 4000 TN printer on white paper. One printed image 32

was produced for each shape and size. The printed images were placed image side down on

the scanning surface, held in place by a 8.5 by 11-in. pane of glass, captured from random

locations (n = 8) and rotated at random angles relative to the image-capturing sensor. Printed

images were captured at a bit depth of 1 bit/pixel (black and white).

METHODS JUSTIFICATION FOR EXPERIMENT 1. We hypothesized that the

approach angle of the scanner head to the object being scanned would affect the results of the

calculated area of that object. Therefore, two shapes were chosen for two reasons: First,

circles have a uniform approach angle relative to the scanner’s image-capturing sensor;

therefore, this shape should have an error only associated with the scanner and not due to

changes in perimeter morphology within a given size if placed at random locations upon the

scanning plane. Second, squares do not have a uniform approach angle relative to the

scanner’s image-capture sensor; therefore, a square should have error attributable to the

scanner and perimeter morphology within a given size. Thus, each shape was printed only

once (to minimize printer error) but its position and planar orientation were adjusted before

each replicate scan. The effects of shape and size were tested for three digital resolutions,

118.159, 236.270, and 472.440 pixels/cm.

Experiment 2

Comparison of scanners for image analysis. To test for consistency between digital

scanners, two scanners (Hewlett-Packard Scanjet 4670 and 6300) were compared using a

20.25-cm2 square and a 20.17-cm2 circle. These devices were chosen for three reasons: First,

to simplify our choice among the many brands. Second, we had access to these models.

Third, an assumption that manufactured elements may be more similar within a brand than between brands. Both shapes (n = 8) were scanned at five resolutions; 472.440, 236.270, 33

118.159, 59.055, 39.370, and 29.528 pixels/cm (i.e., 1200, 600, 300, 150, 100, 75 pixels/in).

Image capture was confined to the lower left corner of the scanner bed, otherwise image

capture method was as described for experiment 1.

Experiment 3

CREATING DIGITAL ESTIMATES OF TOTAL LEAF AREA. Adobe Photoshop

was used to create estimates of leaflet area of soybean, Glycine max (L.) (Fabaceae), prior to

herbivory by the bean leaf beetle, Ceratoma trifurcata Förster (Coleoptera: Chrysomelidae),

using injured leaflets as follows (Fig. 1A-C). After all leaflets were digitally scanned (at 1

bit/pixel), and the resulting image saved, an action was created that would open an image of

an injured leaflet (Fig. 1A). The user was then prompted to select an area, using the

“Polygonal Lasso Tool” (Fig. 1B), surrounding the injured area of the leaflet and then to

select the “OK” button to proceed to the next action step. Photoshop then ran the “levels” adjustment function and reduced the tonal range of the selected area to 0 (using the “levels”

adjustment function); thereby converting white pixels to black (Fig. 1C). The adjusted image

was then saved to a new file as an uncompressed, tagged image file format (TIFF). We refer

to these adjusted, leaflet images as the interpolated leaflet area (ILA).

The process described above allowed us to approximately reproduce the area

(although conservatively) of the leaflet prior to beetle herbivory. Where there was herbivory

of the leaflet margin a straight-line selection was drawn across the marginal gap (as

illustrated in Fig. 1B) to facilitate a conservative estimation of consumed leaflet area.

COMPARISON OF LI-COR TO DIGITAL SCANNER. Soybean, var. Clark, leaflets

(n = 22) were exposed to bean leaf beetle feeding in closed 100x15-mm Petri dishes with one

beetle and leaflet per dish. Petri dishes were sealed with black electrical tape to prevent leaf 34

desiccation and maintained at 16:8 L:D at approximately 23.3°C. After 24 hours, leaflets

were removed and pressed until dry. Leaflets then were scanned using a stationary leaf area

meter (LI-COR LI-3100, Lincoln, Neb.) and a Hewlett-Packard™ Scanjet 4670 . Images of

digitally-scanned leaflets were uploaded to a computer (Dell™ OptiPlex GX150 with a

Pentium® 6 processor, Dell USA, Austin, Tex.), captured in black and white (i.e., 1 bit/pixel)

and saved as an uncompressed TIFF (as previously described for batch processing). The ILA

(Fig. 1C), area of the injured leaflet (Fig. 1A) and the amount of consumed leaflet area (the different between the injured leaflet area and the ILA) was determined. For each image the

“Histogram” function was used to measure the number of black pixels in the scanned image

(all pixels at level 0).

The LI-COR 3100 was calibrated using a 50 cm2 metal disk according to manufacture

recommendation for the LI-COR 3100 (LI-COR Incorporated 2004). The LI-COR 3100 has

two resolution modes, 1 mm2 and 0.1 mm2. We operated the scanner at the 1 mm2 resolution

mode as the model that was available to us was not equipped properly for use at a 0.1 mm2–

resolution. Leaflets were scanned as described by Kogan and Turnipseed (1980). Injured

soybean leaflets (n = 22) and printed, cutout copies of their corresponding ILA (printed at

472.441 pixels/cm) were placed on the center of the rotating belt of the meter and the output

recorded. Injured leaflet area, ILA, and consumed leaflet estimates were compared by

regression analysis between the LI-COR 3100 and digital scanner for three scanned

resolutions (118.159, 236.270, and 472.440 pixels/cm).

Statistical analysis

All experiments were randomized designs. Proc Mixed was used for factorial

analyses (SAS Institute, 2004) and regression analysis was completed using the JMP 35

statistical package (SAS Institute, 2004). The residual plot of the observed data by the

predicted data for differing sizes (experiment 1) and resolutions (experiment 2) of two shapes

revealed a pattern of symmetric variance about the mean. Therefore, size (experiment 1) and resolution (experiment 2) were treated as repeated measures, using resolution as the repeated

subject, in comparisons between scanners. A variance components model was used to

describe the covariance structure in the data. Describing the covariance in this way allowed

for variance structures that, if left undescribed in the model, would violate assumptions of

homogeneity of variance in the factorial analysis. Observation of the studentized residuals

revealed no outliers. In this study, bias is defined as the observed value minus the standard

value.

Results and Discussion

Experiment 1

An object’s shape, size, and the scanned resolution can affect the accuracy and

precision of the measurement of area for some sizes and resolutions (F = 6.66; df = 8, 210;

P < 0.0001) (Table 1). In general there is an increase in bias and loss in precision as size

increases for the highest resolution. Additionally, the lowest resolution tended to

underestimate area while, conversely, the highest resolution overestimated area. The highest

resolution, 472.441 pixels/cm, recorded the smallest (-0.002 ± 0.002) and largest (0.548 ±

0.021) bias, for 3.14-cm2 circles and 78.6-cm2 squares, respectively (Table 1). According to comparisons of three-way interactions (shape*resolution*size) the highest resolution had the least stable bias between sizes within any one shape (Table 1). However, the bias of the highest resolution was statistically similar within, but not between, the largest size classes,

50.28 and 78.6 cm2 of the two shapes. 36

The bias of the two lowest resolutions, 118.159 and 236.27 cm2, were statistically

similar for all sizes and shapes except for the largest size, 78.6 cm2. Similar to the highest

resolution, the bias was statistically similar within, but not necessarily between the largest

size classes (Table 1).

Experiment 2

Overall, the HP 4670 ( X¯ bias = 0.005 ± 0.001 cm2) had significantly less bias

(F = 3074.15, df = 1, 168, P < 0.0001) than the HP 6300 ( X¯ bias = -0.085 ± 0.001 cm2) for

shapes of approximately 20 cm2. Additionally, the HP 6300 underestimated area for all

resolutions and shapes (Table 1) while the HP 4670 overestimated for both shapes at the

lowest resolutions (29.528 and 39.37 pixels/cm) and the square shape at 59.055 pixels/cm

(Table 2). If shapes are combined, the HP 4670 had its lowest bias at 59.055 pixels/cm ( X¯

bias = 0.001 ± 0.003 cm2) and at 39.37 pixels/cm ( X¯ bias = 0.052 ± 0.003 cm2) for the HP

6300. However, in this experiment these “best resolutions” are for one size only and did not

incorporate the error attributed to varying the size of the scanned object.

Experiment 3

Soybean leaflets (either ILA or injured leaflets) scanned with a leaf area meter explain approximately 94% of the variation in digitally scanned leaflets regardless if scanned at 118.159, 236.270, and 472.440 pixels/cm (Figs. 2 and 3). The difference between the ILA and injured leaflets revealed that about 3% of variation in leaf consumption is left unexplained (Fig. 4) regardless of capture resolution. This assay had a small amount of feeding; therefore, the leaf area meter would be expected to be less accurate than a leaflet measured by digital scanner (O’Neal et al. 2002). Additionally, the LI-COR 3100 and 3000

series are known to have a larger margin of error for small areas, as much as ± 6-10% for 37

areas of 1 cm2 or smaller with the error rate increasing for “complex shapes” for the LI-COR

3100C (LI-COR Incorporated, 2004).

Conclusion

These data indicate that using resolutions of either 118.159 or 236.27 pixels/cm (300 or 600 pixels/in, respectively) is sufficient for area measurement by digital scanner. These resolutions are accurate and precise for a variety of sizes and are relatively unaffected by slight changes in an object’s geometry. When comparing three scan resolutions that have a similar bias for circles and squares (118.159, 236.27, and 472.441 pixels/cm [Tables 2 and

3]) significant differences are found when the shape sizes change (Table 1). However, at least for the HP 4670, some resolutions (e.g., 118.159 and 236.27 pixels/cm) are largely unaffected by changes in shape and size (i.e., areas between 3.14 and 50.28 cm2). For very

small objects (≤ 3.14 cm2) it may be acceptable to use higher resolutions (i.e., 472.441 pixels/cm) especially for shapes that do not vary much in size. However, for example, experiments involving different plants with widely varying leaf sizes may suffer from random area-measurement errors.

The digital scanners compared in this study differ in one key component; maximum

optical density. The image-scanning device for the HP 4670 (944.882 maximum pixels/cm)

could be roughly four times more sensitive as the HP 6300 (236.27 maximum pixels/cm).

The technology that enables this higher optical density may explain the difference in the

area-measurement accuracy between these two scanners. Additionally, the distance between

the image capturing sensor and the scanned object may vary between these two scanners.

However, both of these are systematic errors and would not adversely affect measurement if

confined to one scanner model. 38

The described technique for measuring leaf area produces measurements that are

similar to the LI-COR leaf area meter. As described by O’Neal et al. (2002) the digital scanner is an accurate and precise tool for measuring leaf area and this is true for several scanner resolutions (Figs. 2, 3, and 4). Therefore, the above-described errors apparently are very similar between the two devices. However, according to LI-COR Incorporated (2004), measuring “complex shapes” (e.g., roots) under the highest resolution on the LI-COR 3100

(0.1 cm2) will result in error approximately 5% higher than “normal leaves”. Because of the

significant linear relationship between digital scanners and the LI-COR, it is likely that this

error may afflict both. In fact both the leaf area meter and the digital scanners used in this study rely on the same basic technology, a linear sensor, to scan an object (some digital scanners use a CCD or charge-coupled device).

These results may help guide the selection of leaf shapes, sizes, and measurement tools for laboratory assays that challenge foliar pests with standard (e.g., lethal dose assays)

or non-standard (e.g., assays involving multiple plant-species) leaf sections.

Acknowledgements

We thank Jessica L. Chisham, Department of Statistics, Iowa State University for

assistance with statistical analysis. This study was supported, in part, by the North Central

Soybean Research Program and the Iowa Soybean Promotion Board. Mention of a

proprietary product does not constitute an endorsement by the authors or Iowa State

University. 39

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Adobe Systems Incorporated. 2002. Adobe® Photoshop®, Release 7.0.1. Adobe Systems

Incorporated, San Jose, CA.

Bowers, G.R., M.M. Kenty, M.O. Way, J.E. Funderburk, and J.R. Strayer. 1999.

Comparison of three methods for estimating defoliation in soybean breeding

programs. Agronomy Journal. 91:242−247.

Kogan, M., and S.G. Turnipseed. 1980. Soybean growth and assessment of damage by

arthropods pp. 5−29. In M. Kogan, D. C. Herzog (eds.), Sampling methods in soybean

entomology. Springer-Verlag, New York, 587 pp.

Květ, J., and J.K. Marshall. 1971. Assessment of leaf area and other assimilating plant

surfaces pp. 517−555. In Z. Šesták, J. Čatský, P. G. Jarvis, (eds.), Plant

photosynthetic production: manual of methods. Dr. W. Junk, The Hague. 818 pp.

LI-COR Incorporated. 2004. LI-3100C Area meter instruction manual. Lincoln, NE.

[NIH] National Institutes of Health. 2007. NIH Image Manual (V1.61). Online:

http://rsb.info.nih.gov/nih-image/manual/contents.html [Last accessed: 30 May 2007].

O'Neal, M.E., D.A. Landis, and R. Isaacs. 2002. An inexpensive, accurate method for

measuring leaf area and defoliation through digital image analysis. Journal of

Economic Entomology 95:1190−1194.

Russ, J. 2004. The Image analysis cookbook, version 6. Online:

http://www.reindeergraphics.com/tutorial/index.shtml [Last accessed: 30 May 2007].

SAS Institute. 2004. SAS Help and Documentation, version 9.1.3. SAS Institute, Cary, NC. Table 1. Mean bias (cm2) ± standard error of the mean for five standard areas of two shapes for three resolutions.

Shape Size ( X¯ ± SE cm2) *†

Shape Resolution 3.14 12.58 28.29 50.28 78.6 (pixels/cm) Circle 472.441 -0.002 ± 0.002e 0.059 ± 0.004d 0.143 ± 0.006bc 0.213 ± 0.019bc 0.464 ± 0.021a

236.27 -0.026 ± 0.002e 0.009 ± 0.006e 0.007 ± 0.009e 0.036 ± 0.015de 0.134 ± 0.018bcd

118.159 -0.024 ± 0.001e -0.017 ± 0.004e -0.051 ± 0.011e -0.087 ± 0.016e 0.031 ± 0.021de

Square 472.441 0.014 ± 0.002e 0.027 ± 0.005e 0.111 ± 0.008cd 0.182 ± 0.017bc 0.548 ± 0.021a 40 236.27 0.009 ± 0.002e -0.016 ± 0.006e 0.017 ± 0.012e -0.014 ± 0.014e 0.217 ± 0.017bc

118.159 0.005 ± 0.002e -0.016 ± 0.007e 0.025 ± 0.01e -0.020 ± 0.006e 0.210 ± 0.019bc

* Mean bias (measured – expected value) was calculated from 8 replicates.

†Averages followed by the same letter are not statistically different (P < 0.05). Three-way interaction (shape*resolution*size) was statistically significant (F = 6.66; df = 8, 210; P < 0.0001). Multiple comparisons of three-way interactions were calculated using Proc Mixed and least squares method with adjusted values according to Tukey test. Because of symmetric variance between sizes, size was used as a repeated effect and variance components were used to define the covariance structure. Table 2. Mean bias ± standard error of the mean for two shapes (a 20.25 cm2 square and 20.17 cm2 circle) and six scanner resolutions for the HP 4670

Resolution ( X¯ ± SE pixels/cm) *†

Shape 29.528 39.37 59.055 118.159 236.27 472.441

Circle 0.017 ± 0.006bc 0.03 ± 0.005b -0.011 ± 0.004cde -0.033 ± 0.004f -0.029 ± 0.003ef -0.025 ± 0.002cdef

Square 0.066 ± 0.006a 0.06 ± 0.005a 0.009 ± 0.005bc -0.004 ± 0.005cd -0.01 ± 0.007cde -0.015 ± 0.008cdef

* Mean bias (measured – expected value) was calculated from 8 replicates.

† Averages followed by the same letter are not statistically different (P < 0.05). Two-way interaction (shape*resolution) was 41

statistically significant (F = 3.07; df = 5, 84; P = 0.0135). Multiple comparisons of two-way interactions were calculated using

Proc Mixed and least squares method with adjusted values according to Tukey test. Because of symmetric variance of between resolutions, resolution was used as a repeated effect and variance components were used to define the covariance structure. Table 3. Mean bias ± standard error of the mean for two shapes (a 20.25 cm2 square and 20.17 cm2 circle) and six scanner resolutions for the HP6300

Resolution ( X¯ ± SE pixels/cm) *†

Shape 29.528 39.37 59.055 118.159 236.27 472.441

Circle -0.096 ± 0.002ab -0.048 ± 0.003d -0.069 ± 0.001c -0.1 ± 0.001ab -0.091 ± 0.003b -0.057 ± 0.004cd

Square -0.105 ± 0.006a -0.057 ± 0.003cd -0.099 ± 0.002ab -0.105 ± 0.002a -0.106 ± 0.002a -0.095 ± 0.004ab

* Mean bias (measured – expected value) was calculated from 8 replicates. 42 † Averages followed by the same letter are not statistically different (P < 0.05). Two-way interaction (shape*resolution) was

statistically significant (F = 19.94; df = 5, 84; P < 0.0001). Multiple comparisons of two-way interactions were calculated using

Figure 1. Process by which leaf area can be interpolated from an injured leaf. An area of an

injured leaf (A) is selected (B) with the “Polygonal Lasso tool” in Adobe® Photoshop®, including the injured leaf margin as shown, and the pixel levels reduced to zero to interpolate the leaf area (C) prior to injury. 44

Figure 2. Regression of interpolated soybean leaflet area as measured by digital scanner (HP

4670), at 118.159 (F = 316.22; df = 1, 21; P < 0.0001) 236.27 (F = 319.75; df = 1, 21; P <

0.0001), and 472.44 (F = 310.6; df = 1, 21; P < 0.0001) pixels/cm, on leaf area meter (LiCor

3100).

Figure 3. Regression of injured−soybean leaflet area as measured by digital scanner (HP

4670), at 118.159 (F = 301.33; df = 1, 21; P < 0.0001) 236.27 (F = 305.16; df = 1, 21; P <

0.0001), and 472.44 (F = 303.74; df = 1, 21; P < 0.0001) pixels/cm, on leaf area meter

(LiCor 3100).

Figure 4. Regression of soybean leaflet area consumed as measured by digital scanner (HP

4670), at 118.159 (F = 681.56; df = 1, 21; P < 0.0001) 236.27 (F = 702.95; df = 1, 21; P <

0.0001), and 472.44 (F = 694.74; df = 1, 21; P < 0.0001) pixels/cm, on leaf area meter

(LiCor 3100).

CHAPTER 3. NO-CHOICE PREFERENCE OF CEROTOMA TRIFURCATA (COLEOPTERA: CHRYSOMELIDAE) TO POTENTIAL HOST PLANTS OF BEAN POD MOTTLE VIRUS (COMOVIRIDAE) IN IOWA

A paper published in the Journal of the Economic Entomology 100(3): pp. 808-814

Jeffrey D. Bradshaw1, Marlin E. Rice1, and John H. Hill2

1Department of Entomology

2Department of Plant Pathology

Iowa State University,

Ames, IA 50011

Abstract

To better understand the naturally occurring host range of Bean pod mottle virus

(BPMV) and its principal vector, 18 field-collected, perennial plant species were tested for the presence of BPMV. We determined, by no-choice assay, the preference of these plants by bean leaf beetle, Cerotoma trifurcata (Förster), herbivory relative to soybean, Glycine max

(L.). New food hosts for adult bean leaf beetles include: Lespedeza capitata (Michaux), Lotus

corniculatus L., Trifolium alexandrinum L., T. ambiguum Bieberstein, and T. incarnatum L.

Desmodium illinoense Gray is discovered as a new naturally occurring host for BPMV.

Introduction

The bean leaf beetle, Cerotoma trifurcata (Förster) (Coleoptera: Chrysomelidae), is

endemic to North America and a long-known pest of peas, Vigna spp. (McConnell 1915),

beans, Phaseolus spp. (Chittenden 1891, Eddy and Nettles 1930, Aguyoh et al. 2004), and

soybean, Glycine max (L.) (Eddy and Nettles 1930, Higley and Boethel 1994). The recent 48

need to understand the population dynamics (Lam et al. 2001, Carrillo et al. 2005) and

management (Lam et al. 2002, Krell et al. 2004, Koch et al. 2005, Krell et al. 2005) of the

bean leaf beetle is probably a response to dramatic increases in its abundance (Bradshaw and

Rice 2003, Krell et al. 2003). This abundance is positively correlated to Bean pod mottle

virus (BPMV) incidence in soybean (Hopkins and Mueller 1984); therefore, large vector

populations have likely contributed to an apparent increase in this virus in the northcentral

United States (Bradshaw and Rice 2003).

Bean pod mottle virus, discovered in 1947 (Zaumeyer and Thomas 1948), is a

common pathogen of soybean in the Americas (Milbrath et al. 1975, Pitre et al. 1979,

Hopkins and Mueller 1983, Lin and Hill 1983, Ghabrial et al. 1990, Fribourg and Perez 1994,

Michelutti et al. 2002, Anjos et al. 2004, Sikora and Murphy 2005). It is of serious concern for soybean seed production in the United States (Giesler et al. 2002). This viral disease results in yield and quality losses in soybean (Quiniones et al. 1971, Horn et al. 1973, Myhre et al. 1973, Hopkins and Mueller 1984, Ragsdale 1984, Giesler et al. 2002, Krell et al. 2003); however, “field tolerance” recently has been reported (Hill et al. 2006).

Although the principal vector of BPMV is the bean leaf beetle (Mueller and Haddox

1980), there are other coleopterous vectors within the Chrysomelidae (Horn et al. 1970,

Mabry et al. 2003, Werner et al. 2003), Meloidae (Patel and Pitre 1971), and Coccinellidae

(Fulton and Scott 1974). The susceptible host range of BPMV, by mechanical inoculation, includes plants in the Apocynaceae, Chenopodiaceae, and Fabaceae (=Leguminosae)

(Caesalpinioideae and Papilionoideae) and nonsusceptible plant hosts are found in the

Compositae, Cruciferae, Cucurbitaceae, Solanaceae, and Fabaceae (Papilionoideae) (Brunt et al. 1996). Although vector transmission has been demonstrated from Desmodium 49

paniculatum (L.) to soybean via bean leaf beetles (Waldbauer and Kogan 1976), the range of possible naturally occurring hosts susceptible to both vector and virus is still unknown. This

could be central to the determination of the primary inoculum source of BPMV.

thought to be an important source for BPMV (Moore et al. 1969, Horn et al. 1970, Stace-

Smith 1981, Krell et al. 2003), possibly because of the opportunity for the virus to overwinter

within the plant. However, in Iowa, distribution of this host plant does not fully explain the temporal appearance and ultimate impact of the disease (Krell et al. 2004).

There is a lack of intensive, replicated sampling for most potential host-species for

BPMV. Furthermore, bean leaf beetle feeding has been observed on some BPMV hosts

(Krell et al. 2003) and host preference has been shown for some Fabaceae (Henn 1989); however, the acceptability of most perennial legumes to bean leaf beetles has not been determined. Therefore, the objective of this study was to investigate the potential host-range overlap between the bean leaf beetle and presence of BPMV in nature.

Materials and Methods

Bean leaf beetle no-choice preference assays. Female bean leaf beetles, determined by their large size and darkened frons (Kogan et al. 1980, Sims et al. 1984), were field- collected from Medicago sativa L. using a 20-cm sweep net in May, 2004 and 2005. They

were held in groups of three in 9-cm Petri dishes for 48 hours (maintained at 24ºC at 16:8 50

light/dark cycle) without access to food or water to cull out weak beetles, to insure that

beetles had similar levels of hunger, and to allow beetles to acclimatize to test conditions.

Following acclimatization, beetles (three per Petri dish) were given access to one leaflet (with the dish lid and bottom sealed together with electrical tape to prevent moisture loss) from one of the following leguminous fabacious species in 2004 (10 plants of each species were collected the day of the experiment and 6 of the 10 were assayed): Amorpha

canescens Pursh, Astragalus cicer L., Glycine max L. (cv. Mark RR), Lotus corniculatus L.,

Medicago sativa L., Melilotus officinalis (L.) [white sweet clover], M. officinalis [yellow

sweet clover], Petalostemum purpureum (F.), Robinia pseudoacacia L., Securigera varia

(L.), Trifolium ambiguum Bieberstein, Trifolium hybridum L., Trifolium pratense L., and

Trifolium repens L. In 2005, the following hosts were used (10 plants of each species were

collected and 3 of the 10 were assayed): A. canescens, G. max (cv. Mark RR), L.

corniculatus, M. officinalis, R. pseudoacacia, Trifolium. alexandrinum L., T. ambiguum, T.

incarnatum (F.), and T. pratense. Dishes were maintained at 24ºC at 16:8 light/dark cycle for

24 (in 2004) or 48 hours (in 2005) after which leaflets were removed and pressed until dry.

All plants were collected from the Field Extension Education Laboratory, Iowa State

University (Boone Co., IA) except for R. pseudoacacia (collected from McHose Park, Boone

Co., IA).

These plant species were chosen because they were perennial, their vegetative growth

overlapped with the emergence of overwintered C. trifurcata populations (i.e., they

potentially could be primary inoculum sources for BPMV), and they were available free of

pesticides. Beetle abundance was limiting to this study during 2004 and 2005; therefore, 51

more plants were collected than assayed. However, all ten plants were retained for virus

assays.

In 2006, bean leaf beetles were collected at a prairie near Ames, IA (N42°07′48′′,

W093°33′32′′). Two legumes dominated this location, Desmodium illinoense Gray and

Lespedeza capitata Michaux, which had heretofore never been reported as hosts for C.

trifurcata or BPMV; however, both had visual evidence of bean leaf beetle injury. Ten plant

samples (a nearly complete census from this locality) of both species (one leaflet each) were

collected and tested using the conditions described except one bean leaf beetle was used per

dish and the feeding period was for 60 hours. For purposes of comparison, 10 G. max (cv.

Williams) leaflets (grown under glasshouse conditions) were included in this experiment as a

control.

Leaflet area measurement. Leaflet images were captured with a digital scanner

(Hewlett-Packard™ Scanjet 4670, Hewlett-Packard Co.., Houston, TX) in black and white

(i.e., 1 bit/pixel) at 286.12 pixels/cm, uploaded to a computer (Dell OptiPlex GX150 with a

Pentium 6 processor, Dell USA, Austin, TX) and saved as an uncompressed TIF using

Adobe® Photoshop® 7.0.1 (Adobe Systems Incorporated, San Jose, CA). We previously

determined that the measurement of 2-dimensional objects acquired at 286.12 pixels/cm is

not adversely affected by variations in shape or size (unpublished data). For each image the

“Histogram” function in Adobe® Photoshop® was used to count pixels. For more intuitive

comparisons, digitally scanned areas (in pixels) were converted to square centimeters by

dividing the number of black pixels into the number of total square pixels/mm in the images

black pixels as determined by Photoshop®, i.e., Area (mm2 ) = (total pixles/mm)2 52

For 2006 experiments, area measurements were taken as described except by

capturing leaflet images in 16-bit color. Injured areas were selected with the “magic wand

tool” or “color selection tool” because the skeletonization of the D. illinoense leaflets was

such that a very close-knit leaflet skeleton remained in injured areas, which was not

accurately captured as a 1-bit image. The area of the selected area was determined using the

image “histogram” as described above.

Bean pod mottle virus host assays. Ten samples each of the afforementioned field-

collected plants were tested for presence of BPMV by enzyme-linked immunosorbent assay

(ELISA), western blot assay, and polymerase chain reaction (PCR). For ELISA and western

blot, samples were taken from the same plants used for the no-choice beetle assay, extracted

in 0.05M phosphate buffered saline with 0.05% Tween-20 (PBST), pH 7.2, and held at -

20°C. Samples of plant species (except D. illinoense and L. capitata) were combined and

concentrated using 2-ml filtration devices with a 30,000-MW filter (Millipore Corporation,

Billerica, MA) and centrifuged at 4,500 x g for 1 hour. The ELISA and western blot

procedures were similar to Krell et al. (2003). Desmodium illinoense and L. capitata were extracted in PBST, pH 7.2, containing 2% polyvinylpolypyrrolidone (PVPP) and 1% sodium hydrosulfite. The later extraction buffer was found to eliminate false positives (by ELISA) for many legumes (J.D.B, unpublished data) and simplified the search for BPMV hosts by

ELISA.

To further exclude the possibility of a false positive, total RNA was extracted from immuno-positive plants and tested by reverse-transcription PCR (RT-PCR). Plant samples from immuno-positive plants were collected into liquid N2 and stored at -80°C. To extract

total RNA, approximately 100 μg of frozen plant tissue was added to 1 ml Trizol, vortexed 53

for 15 min at room temperature, then 300 μl of choroform was added and the sample was

vortexed for 10 min. Samples were centrifuged at 3,900 x g at 4°C for 10 min and the

supernatant was extracted twice more with chloroform. The RNA was precipitated from the supernatant by addition of an equal volume of cold (-20°C), ribonuclease-free 70%

isopropanol followed by incubation for 30 min at room temperature. The preparation was

centrifuged at 18,320 x g at 4°C to recover the pellet which was washed using 300μl of cold

(-20°C), ribonuclease-free 70% ethanol. The pellet was air-dried for ~5 min and suspended in

ribonulease-free distilled water.

Reverse transcription and PCR protocols were followed according to Takara, version

3.0 (Takara Bio Inc., Otsu, Japan), using random 9-mers for reverse transcription primers and

BPMV, RNA–1-specific forward (3′-TGTGCTACCATTGCAGTTTCTA-5′) and reverse (3′-

AAGTTTGGTCTACAACATAATGA-5′) PCR primers. Avian myeloblastosis virus reverse transcriptase was used for RNA transcription and Ex Taq-HS™ (Takara Bio Inc., Otsu,

Japan) was used as a DNA polymerase for PCR. The dNTPs for the PCR are supplied in this

Takara kit as a separate reagent. Conditions for reverse transcription were 30°C (10 min),

42°C (60 min), 94°C (5 min), 4°C (hold) and for PCR were 94°C (2 min), 32 cycles [94°C

(30 sec), 52°C (30 sec), 68°C (5 min)], 68°C (15 min), 8°C (hold) using a MiniCycler™

thermocycler (M J research, Watertown, MA).

Data analysis. Data were analyzed using the mixed model procedure in SAS (PROC

MIXED, SAS Institute 2002-2003). For leaflet area consumed, analysis of variance was used to determine differences between host-plant herbivory. Estimates were considered 54

statistically significant if the P-value <0.05 and comparisons were different where their 95% confidence interval for the estimate did not overlap.

Results and Discussion

Bean leaf beetle food host assays. Two issues were considered in assessment of bean leaf beetle herbivory. First, the likely host range on perennial legumes and second, a comparison of herbivory on potential hosts plants with that on soybean. To assess the first issue, the number of leaflets with any feeding were counted and if greater than one, the plant species was assumed to be a likely host (i.e., an acceptable host). To assess the second issue, estimates of leaflet area consumed were compared to soybean to indicate a degree of preference relative to soybean.

The following perennial plants were determined as acceptable hosts for adult bean leaf beetles in Iowa: Desmodium illinoense, Lotus corniculatus (new host), Robinia

pseudoacacia, Trifolium alexandrinum (new host), T. ambiguum (new host), T. incarnatum

(new host), T. pretense, T. repense, and L. capitata (new host) (Table 1). Additionally, for L.

capitata, T. ambiguum, and D. illinoense, one of us (J.D.B.) has observed and found evidence

of bean leaf beetle feeding on leaflets of these plants in nature during May and June.

Overall, soybean was the most acceptable host plant in this study, i.e., had the

greatest proportion of leaflets with herbivory (Table 1). Additionally, as compared with

soybean, most perennial hosts support significantly less herbivory (Table 1). However, because of leaflet thickness, the area of herbivory on D. illinoense may represent an underestimate. Natural host plants of the bean leaf beetle (e.g., L. capitata and D. illinoense)

received significantly less herbivory than soybean (Table 1, 2006 experiment). Herbivory on

T. ambiguum was significantly less in 48 hours of exposure than soybean, but it was not 55

significantly less within 24 hours (Table 1, 2004 and 2005 experiment). This indicates that

the rate of herbivory may differ between hosts; however, there were half the replicates in

2005 as in 2004. Every test plant received some feeding. However, some received <0.01mm2 of herbivory in 24 hours which is well within the random error for the scanner used in this study, ±0.06 mm2 (unpublished data). Therefore, pairwise comparisons for herbivory ≤0.06

mm2 are not meaningful. In the final assay, both D. illinoense and L. capitata received

significantly less feeding than soybean (Table 2, 2006 experiment). However, D. illinoense

received more feeding than L. capitata.

It is interesting that some species (e.g., T. repens) received an average herbivory of

<0.01 mm2 with more than half of the leaflets receiving some herbivory (Table 1, 2004

experiment). Although, leaflets in this experiment apparently did not differ greatly in

observed thickness (unpublished data), physical factors can mediate C. trifurcata preference,

e.g., trichome density (Lam and Pedigo 2001). The involvement of chemical host factors in

C. trifurcata host preference has not been studied.

Bean pod mottle virus host assay. Of all the tested plants only D. illinoense was positive for BPMV by ELISA, western blot (Fig. 1) and RT-PCR (Fig. 2). On a western blot, sap extracted from D. illinoense gave bands that corresponded to the large and small coat

protein subunits of BPMV and corresponded to similar bands in a BPMV-infected soybean

plant. Additionally, of the 10 D. illinoense tested, all 10 were positive for BPMV.

Furthermore, RT-PCR of the total RNA from D. illinoense leaflets yielded the expected

product size for an RNA–1 cDNA-specific primer pair (Fig. 2B). This is the first report of

BPMV from D. illinoense. 56

Many plants (e.g., A. canescens, T. pratense, and R. pseudoacacia) yielded false

positives by ELISA, as was similarly noted by Krell et al. (2003), via PBST sap extraction.

However, sap extracted from R. pseudoacacia (used as a false-positive control in this test),

D. illinoense and L. capitata, using PBST containing PVPP and sodium hydrosulfite resulted

in no false positives when compared to sap extracted in PBST alone. Similar results have

been noted when extracting sap from various legumes (unpublished data).

The bean leaf beetle may have a broader host range (Table 2) than the natural host

range for BPMV. Searches for the natural reservoir for this virus have often found

Desmodium spp. as an important source for this virus (Moore et al. 1969, Walters and Lee

1969, Lee and Walters 1970, Krell et al. 2003). Of the plant species listed on the Virus

Identification Data Exchange database (Brunt et al. 1996) as hosts of BPMV, about 16 are

susceptible and 21 are non-susceptible; however, these are based primarily on mechanical

inoculations. Species such as T. incarnatum are listed as susceptible hosts while T. pratense

and T. rapens are non-susceptible. In this study, BPMV was not found to occur naturally in any of these hosts. If BPMV requires the activity of certain ribonucleases for efficient transmission (Gergerich et al. 1986, Gergerich and Scott 1988a, 1988b), and if some legumes contain factors that inhibit ribonuclease activity, there may be a discontinuity between the natural host range of BPMV by mechanical inoculation and that by beetle transmission.

Plants such as T. ambiguum and L. capitata were negative for BPMV even though

bean leaf beetle herbivory and many beetles were found on these plants. If such plants truly

represent non-susceptible hosts for BPMV, it may be possible that bean leaf beetles “clean”

themselves of virus in nature. Further, such BPMV non-hosts could be used as a trap crop for both virus and bean leaf beetles. 57

Sixteen species of Desmodium spp. are found in Iowa (USDA 2006) and, of these,

three are now known to be susceptible to BPMV in nature (Moore et al. 1969, Krell et al.

2003). Other Desmodium spp. should be assayed to determine the wild-host range of this

virus. The distribution and abundance of these hosts are not well known in Iowa; however, this knowledge may be helpful in understanding BPMV epidemics. Furthermore, simply identifying a susceptible host plant is insufficient to determine its potential impact on the pathosystem. Bean pod mottle virus exists as more than one subgroup population in nature

(Gu et al. 2002) that is associated with varying degrees of symptom severity. The

Desmodium BPMV isolate found in this study is currently being characterized.

Acknowledgements

We thank R. O. Pope for assistance in locating and identifying plants used in this

study, A. L. Eggenberger and C. Zhang for their insight and suggestions concerning

molecular methods. This research was funded in part by the Iowa Soybean Association and

the North Central Soybean Research Program. This journal paper of the Iowa Agriculture and

Home Economics Experiment Station, Ames, Iowa, Project No. 3608, was supported, in part,

by Hatch Act and State of Iowa funds.

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2005 (48 h) Amorpha canescens Pursh lead plant 0.01 -5.2 5.2 0.0278 1/3 Glycine max (L.) soybean (cv. Mark RR) 13.44 8.2 18.6 3/3 Lotus corniculatus L. birdsfoot trefoil 1.57 -3.6 6.8 2/3 Melilotus officinalis (L.) white sweet clover 0.02 -5.2 5.2 1/3 Robinia pseudoacacia L. black locust 0.52 -4.7 5.7 2/3 Trifolium alexandrinum L. berseem clover 0.21 -5.0 5.4 3/3 Trifolium ambiguum Bieberstein kura clover 2.20 -3.0 7.4 3/3 Trifolium incarnatum (F.) crimson clover 1.21 -4.0 6.4 3/3 Trifolium pratense L. red clover 0.69 -4.5 5.9 2/3

2006 (60 h) Desmodium illinoense (L.) Illinois ticktrefoil 1.34 -1.3 4.0 0.0001 10/10 Glycine max (L.) soybean (cv. Williams) 9.42 6.7 12.1 9/10 Lespedeza capitata (Michaux) roundhead lespedeza 0.15 -2.5 2.8 3/10 1 aMean area consumed is estimated from three (years 2004 and 2005) or one (year 2006) beetles per leaflet. 63

Table 2. Food plants of adult Cerotoma trifurcata (Förster) Family Scientific nameab Common name(s)ab Reference Fabaceae Amphicarpaea bracteata (L.) American hogpeanut Chittenden 1897 Desmodium canadense (L.) showy ticktrefoil Krell et al. 2003 Desmodium canescens (L.) hoary ticktrefoil McConnell 1915 Desmodium cuspidatum largebract ticktrefoil Waldbauer and Kogan 1976c (Muhlenberg Ex Willdenow) Desmodium illinoense Gray Illinois ticktrefoil Waldbauer and Kogan 1976cd Desmodium laevigatum (Nuttall) smooth ticktrefoil Chittenden 1897 Desmodium paniculatum (L.) panicledleaf Moore et al. 1969 ticktrefoil Desmodium tortuosum (Swartz) dixie ticktrefoil Chittenden 1898, Eddy and Nettles 1930 Glycine max (L.) soybean McConnell 1915 Lespedeza capitata (Michaux) roundhead lespedeza —d Lespedeza spp. - Chittenden 1891 Lotus corniculatus L. birdsfoot trefoil —d Phaseolus lunatus L. sieva bean Henn 1989 Phaseolus vulgaris L. kidney bean Chittenden 1897 Robinia pseudoacacia L. black locust Chittenden 1897d Strophostyles helvola (L.) amberique-bean (Waldbauer and Kogan 1976)c Trifolium alexandrinum L. Egyptian clover —d Trifolium ambiguum Bieberstein kura clover —d Trifolium pratense L. red clover Davis 1950d Trifolium incarnatum L. crimson clover —d Trifolium repens L. white clover Henn 1989 Vigna aconitifolia (Jacquin) moth bean McConnell 1915 Vigna angularis (Wildenow) adzuki bean Henn 1989 Vigna radiata (L.) mung bean Henn 1989 Vigna unguiculata (L.) blackeyed pea Henn 1989 Vigna u. sesquipedalis (L.) yardlong bean Henn 1989 Wisteria floribunda (Wildenow) Japanese wisteria Staines 1986 Celastraceae Euonymus atropurpureus burningbush Helm et al. 1983 Jacquin Urticaceae Urtica dioica L. stinging nettle Helm et al. 1983 Laportea canadensis (L.) Canadian woodnettle Helm et al. 1983 Cucurbitaceae Cucurbita pepo L.e (i.e., pumpkin var. Koch et al. 2004 'Magic lantern' and squash var. 'Turk's turbin') Cucumis sativus L. e garden cucumber Koch et al. 2004 Poaceae Zea mays L. corn Metcalf and Metcalf 1993 aScientific and common names taken from the PLANTS database (USDA 2006). bPlant species are listed as food plants where direct herbivory is reportedly observed or where eggs are found near the plant. cIndirect evidence—host-plant evidence based on the presence of eggs. dThis record is reported first or confirmed in this manuscript. eOnly the cucurbit varieties and common names were provided by Koch et al. (2004). Cucurbita pepo and Cucumis sativus are inferred for pumpkin and squash, respectively.

Figure 1. Western blot for the detection of Bean pod mottle virus (BPMV) in Desmodium illinoense. (A) Protein marker, units in molecular mass (kDa). (B) BPMV-infected soybean (cv. Williams) sap. (C) Non-infected soybean (cv. Williams) sap. (D) BPMV-infected Desmodium illinoense from total protein extraction. Solid bars to the left of image indicate expected position for the three bands associated with BPMV coat protein—large protein, 41kDa, and small protein, ~22kDa (consisting of two migration forms).

Figure 2. Total extracted RNA (A—marker left lane in kb, sample right lane) and cDNA from reverse-transcription polymerase chain reaction of Bean pod mottle virus RNA–1 (using a primer pair with an expected product size of 1.037Kb) from Desmodium illinoense (B— marker left lane in kb, sample right lane) in ethidium bromide-stained agarose gel.

CHAPTER 4. IDENTIFICATION OF A NOVEL NATURALLY OCCURRING REASSORTANT OF BEAN POD MOTTLE VIRUS (COMOVIRIDAE: COMOVIRUS) FROM A NATIVE PERENNIAL PLANT AND THE MOLECULAR CHARACTERIZATION OF ADJACENT SOYBEAN-FIELD ISOLATES

A paper to be submitted to Phytopathology

Jeffrey D. Bradshaw1, Chunquan Zhang2, John H. Hill2, and Marlin E. Rice1

1Department of Entomology

2Department of Plant Pathology

Iowa State University,

Ames, IA 50011

Abstract

A recent epidemic of Bean pod mottle virus (BPMV), transmitted primarily by the

bean leaf beetle, Cerotoma trifurcata (Förster), has caused economic losses in major US

soybean growing regions. Previous genetic studies have shown that the bipartite virus BPMV

has two subgroups of RNA–1 and RNA–2 that can naturally reassort. Based on cloning and

sequencing, the two molecularly characterized reassortants are diploid, i.e. they contain

RNA–1 from both subgroup I and II. Furthermore, the dipoid nature of these two reassortants is the underlying mechanism for very severe symptoms. We have discovered a novel naturally occurring BPMV reassortant from Desmodium illinoense Gray (designated I-Di1)

with a combination of subgroup I, RNA–1 and subgroup II, RNA–2. Based on

symptomology tests, this newly identified reassortant caused mild to moderate symptoms on

three representative soybean varieties: Clark L67-3776, Essex, and William’s L78-379.

Extensive reverse-transcription PCR and sequencing confirmed the existence of only one

type of RNA–1 from I-Di1. Furthermore, BPMV isolates were collected from a soybean field

adjacent to the type locality of I-Di1. Based on molecular characterization and phylogenetic

analysis the soybean isolates are different than I-Di1. Additionally there is a surprising

amount of genetic diversity among these soybean isolates considering they were collected

along a 720-m transect. Our results indicate the co-existance of two BPMV subgroups of

RNA–1 in adjacent habitats and reveal the genetic diversity that may be important for BPMV disease epidemics.

Introduction

Bean pod mottle virus (Comoviridae: Comovirus), BPMV, has a bipartite positive- strand genome consisting of RNA–1 and RNA–2 that are independently encapsidated (14).

Based on genetic studies of natural isolates there are two subgroups of RNA–1 and RNA–2.

Both subgroups, including natural reassortants, were identified but only the partial diploid reassortants were molecularly characterized (10, 11). Interestingly, BPMV infection by the combination of both subgroups of RNA–1 induce very severe symptoms on soybean (10).

The genome of BPMV is expressed by the synthesis and subsequent proteolytic cleavage of large polyproteins; giving rise to five (from RNA–1) (3) and three (from RNA–2) (20) mature proteins. RNA–1 synthesizes proteins that are important for replication (3) as evidenced by the ability for RNA–1 to replicate in absence of RNA–2 (14). RNA–2 synthesizes the large and small coat proteins, 58k RNA–2 replication co-factor and movement protein (14, 20).

In soybean, Glycine max (L.), BPMV causes the severe reduction of both yield and

seed quality (8); however, these symptoms are cultivar (12) and environmentally (17)

dependent. The symptom severity of BPMV maps to RNA–1; specifically the proteinase co-

factor (Co-Pro) and helicase (Hel) genes (9). The combination of two subgroups of RNA–1,

even though they are both mild or moderate, can induce very severe symptoms as compared

to those induced by a severe strain’s single component RNA–1. The nature of BPMV

symptom severity illustrates the importance of viral genetic diversity in soybean (10).

Bean pod mottle virus was first discovered in Phaseolus vulgaris cv. Tendergreen by

Zaumeyer and Thomas in 1948 (32) and the first isolate was partially described by Lee and

Walters in 1970 (18) as a strain of BPMV-like "desmodium mottle" from Desmodium

paniculatum. More recently, BPMV has been identified from D. canadense (15) and D.

illinoense (2)—both discoveries made within the framework of host range surveys for

BPMV. Interestingly, one control strategy recommends the treatment of non-crop areas with

herbicide to kill off weeds (e.g. Desmodium spp.) to reduce natural sources of infection to

soybean via C. trifurcata transmission (6). While having an apparently narrow host range (2,

15), BPMV is unique in having numerous species of leaf-feeding beetles (5, 13, 19, 23, 24,

31) reported as vectors. Some beetle vectors, e.g., Cerotoma trifurcata (Förster), are very

efficient and can acquire and transmit BPMV with one bite and remain viruliferous for days

(7).

A recent study (2) reported that D. illinoense is both an acceptable host for C.

trifurcata and a host for BPMV. This study confirmed the host status of D. illinoense based on field-collected plants from a state-managed prairie area in Story County, Iowa. Further, they indicated that D. illinoense may be important in the disease cycle of BPMV in soybean.

In soybean BPMV has a low seed transmission rate, 0−0.037% (15), reduced viability within

diapausing insect vectors, 0−1.6% (15), and apparently few alternate host plants (2, 15). Thus

the predominant epidemiological source of the economically important BPMV isolates

remains ambiguous.

Herein we molecularly characterize the Desmodium BPMV isolate discovered by

Bradshaw et al. (2). Additionally, BPMV isolates from an adjacent soybean field were collected and partially characterized.

Materials and Methods

Isolate description. A BPMV isolate from D. illinoense was collected on June 2006

and its RNA extracted as described in Bradshaw et al. (2). To improve the stability of the

sample during handling for subsequent analyses, a 50−µl aliquot of RNA was reverse-

transcribed (RT) to first-strand cDNA using random primers and stored at -20ºC. First-strand

cDNAs were subjected to polymerase chain reaction (PCR) as needed. Conditions for RT-

PCR were followed according to Takara, version 3.0 (Takara Bio Inc., Otsu, Japan), using

random 9-mers as reverse transcription primers and universal or strain-specific PCR primers

(Table 1). For PCR, RNA–1 cDNA products were made using primer pairs (forward/reverse)

specific for RNA–1; BP-5'end-for/R1-798-rev, R1-235-for/R1-2267-rev, R1-1208-for/R1-

4704-rev, R1-1989-for/R1-3963-rev, and R1-4572-for/R1-3'Cla-rev and RNA–2; BP-5'end-

for/R2-622-rev, R2G7-437-for/R2G7-3227-rev, R2-1673-for/R2-2187-rev, and R2-2187-

for/R2-3'Cla-rev. To determine the strain identity of soybean BPMV isolates cDNA samples

were sequenced on a 3730xl DNA analyzer (Applied Biosystems, Foster City, CA) using a

four-color dye system and completed by The DNA Facility, Office of Biotechnology, Iowa

State University.

For sequencing RNA–1 and RNA–2, primers for overlapped cDNA products were

used (Table 1) for different regions of RNA–1 and RNA–2. Contigs were assembled together

using version 10.3.0 (Informax Inc., Frederick, MD) and the final identical consensus sequence will be deposited into NCBI with accession number (in process).

The resulting sequence was compared to the following BPMV isolates: KY-G7

(RNA–1 and RNA–2; Genbank accessions NC_003496 and NC_003495, respectively), K-

Ha1 (RNA–1and RNA–2; Genbank accessions AF394606 and AF394607, respectively), K-

Ho1 (RNA–1and RNA–2; Genbank accessions AF394608 and AF394609, respectively), and

IL-Cb1 (RNA–1; Genbank accessions AY744932 and AY744931 and RNA–2; Genbank

accession AY744933).

To determine the differential symptomatic response of host plants to the Desmodium

BPMV isolate three soybean varieties (Clark L67-3127 [n = 8], Williams L78-379 [n = 4],

and Essex [n = 3]) and four species of Desmodium (D. canadense, D. illinoense, D.

paniculatum, and D. sessifolium, [n = 5 for each species]) were mechanically inoculated with

BPMV-infected leaf sap prepared from field-collected D. illinoense leaflets. The inoculum

was prepared using 5 leaflets of D. illinoense ground in ~10 ml of ice-cold PBS mixed with

600-mesh carborundum. Soybean plants were rub inoculated (one plant left non-inoculated)

at the V1-V2 stage (4) and four Desmodium plants inoculated (one plant left non-inoculated) at the three-four unifoliate leaf stage (Desmodium has several unifoliate leaves before the

first true leaf). All plants were potted separately (except Clark L67-3127 which was planted

two per pot) in 9 x 12-cm pots and maintained under green house conditions. All plants were

tested prior to inoculation using a biotin-avidin double antibody sandwich, enzyme-linked

immunosorbent assay (ELISA) to ensure that plants were not infected with BPMV (data not

shown). Once symptoms developed, photographs of plants were taken with a digital camera.

Isolate distribution in soybean. To determine if the BPMV isolate from Desmodium discovered by Bradshaw et al. (2) was a potential epidemiological source in soybean, a

~720−meter transect of 18 samples from a nearby soybean field were collected (Fig. 1).

Fifteen soybean samples were arbitrarily collected in 10-15 step intervals in a South to North

direction and three additional subsamples were collected near sample 15 on September 5,

2006 to attempt to increase a likelihood for finding BPMV isolates related to the isolate

previously collect from the prairie area. The soybeans were at a late reproductive stage (i.e.,

lower leaves were yellowing and beginning to drop). The uppermost fully expanded leaves

were collected into plastic bags and stored in an insulated cooler with dry ice. Samples were

brought back to the laboratory and separately ground in liquid N2 and stored in 2-ml microcentrifuge tubes at -80°C.

To determine the proportion of BPMV infected plants along the sample transect, 300

µg of the ground tissue from each sample was mixed into 1 ml of 0.05M phosphate-buffered

saline, pH = 7.15, with 0.05% tween-20 (PBST) (vortexed for 15 min. to facilitate the

extraction of sap into solution) and tested by ELISA.

To determine the strain identity of the BPMV isolates collected from soybean,

samples were extracted as for ELISA, subjected to immunocapture RT-PCR and the resulting

cDNA sequenced. For immunocapture thin-walled PCR tubes (100 µl) were loaded with 50

µl of polyclonal anti-BPMV antibody, capped, and incubated for ~12 hours at 24°C.

Following incubation the antibody was withdrawn and the tubes dried in a fume hood for 15

min. Next 100 µl of extracted sap per sample was added to the treated tubes and then

incubated for ~12 hours at 4°C. Following incubation, sap was withdrawn and the tubes were

rinsed quickly two times with PBST and dried in a fume hood for 15 min. After drying, 20-µl

of RT reagent was mixed and added into the tubes. We used Takara kit, version 3.0 (Takara

Bio Inc., Otsu, Japan), with random 9-mers for RT primers and BPMV primers specific for

RNA–1 (Table 1). Avian myeloblastosis virus reverse transcriptase was used for RNA

transcription, and Ex Taq-HS (Takara Bio Inc.) was used as a DNA polymerase for PCR. The

dNTPs for the PCR are supplied in this Takara kit as a separate reagent. The conditions for

immunocapture RT were 42°C (1 min, viral coat protein denaturation), 30°C (10 min, reverse

transcription), 42°C (30min, elongation), 94°C (5 min, reverse transcriptase inactivation),

and 4°C (hold). The primer pairs (forward/reverse) BP-5’end-for/R1-2267-rev and R1-1208-

for/R1-4704-re (Table 1) were used to produce RNA–1 cDNA of BPMV isolates from the

soybean samples. The PCR reaction parameters were followed according to instructions,

Takara version 3.0.

To determine the strain identity of soybean BPMV isolates cDNA samples were

sequenced using the aforementioned procedure for the Desmodium BPMV isolate. Primers

R1-1208-for and R1-1989-for (Table 1) were used for sequencing of the cDNA from BP-

5’end-for/R1-2267-rev. Primers R1-1989-for and R1-2616-rev (Table 1) were used for sequencing of the cDNA from R1-1208-for/R1-4704-rev. From these reactions an ~1.4-Kb contiguous fragment was aligned and compared with BPMV isolates: KY-G7 (Genbank accession NC_003496), K-Ha1 (Genbank accession AF394606), K-Ho1 (Genbank accession

AF394608), IL-Cb1 subgroup I (Genbank accession AY744931) and II (Genbank accession

AY744932) and the BPMV isolate described herein.

Data analysis. Vector NTI version 10.3.0 (Informax Inc., Frederick, MD) was used

for sequence analysis, alignments, and for the selection of primers. CLC Free Workbench

(CLC Bio, Cambridge, MA) was used to construct phylograms using the unweighted pair

group method using arithmetic averages (UPGMA) or neighbor-joining method with 1000

bootstrap replicates.

Results

The deduced nucleotide sequence of the BPMV isolate from D. illinoense (I-Di1)

resulted in RNA–1 and RNA–2 with about 6,005 (Fig. 2) and 3,693 (Fig. 3) bases,

respectively. The translation of the ORF of RNA–1 resulted in an expected polyprotein of

1,851 amino acids (Fig. 4). The translation of ORF 1 and ORF 2 of RNA–2 resulted in an

expected polyprotein of 1,018 and 916 amino acids (Fig. 4), respectively. I-Di1 shares

85.5−99.1% nucleic acid (NA) identity and 95.7−99.8% amino acid (AA) similarity with

RNA–1 of isolates K-Han, K-Hop, K-G7, IL-Cb1 (subgroup I) and IL-Cb1 (subgroup II)

(Table 2). I-Di1 shares 86.2−98.8% NA identity and 95.5−99.5% AA similarity with RNA–2

of isolates K-Han, K-Hop, K-G7, IL-Cb1 (subgroup I) (Table 2).

Phylogenetic analysis of amino acids of I-Di1 resulted in 100% bootstrap support

(according to UPGMA) for grouping RNA–1 with subgroup I isolates and RNA–2 with

subgroup II isolates (Fig. 5). Mechanical inoculation of I-Di1 to any Desmodium spp. did not

yield infection. However, all Clark L67-3127, Essex, William’s L78-379, and soybean

varieties were ELISA positive 17–40 dpi (data not shown) with generally mild symptoms

(Fig. 6) apparent 30–50 dpi. Systemically−infected leaves had a green mottling and blistering on Williams L78-379 (Fig. 6A and B), light blistering on Clark L67-3127 (Fig. 6C and D) and yellow mottling with a few blisters and slowed growth on Essex (Fig. 6E and F).

Of the 18 BPMV isolates collected from an adjacent soybean field (Iowa-Prignitz isolates 1–18, I-P[1-18]) 88% were ELISA positive for BPMV (using an absorbance threshold, mean of four wells plus 4 x SD). Comparative alignment of, from a subset of

ELISA-positive isolates, an 1,453 base pair RNA–1 (nucleotides 1262−1285) sequence

fragment from I-P1, I-P3, I-P11, I-P12, I-P13, I-P14, I-P16, I-P17, and I-P18 shared > 80%

NA identity with I-Di1 (84.3–84.9% NA identity), IL-Cb1 (subgroup I) (84.3-85.5% NA

identity), IL-Cb1 (subgroup II) (98.2–98.7% NA identity), K-G7 (84.6–85.3 NA identity), K-

Ha1 (98.1–98.7% NA identity), and K-Ho1 (84.6–85.3% NA identity) (Table 3). No I-P

isolates shared 98.3−99.2% NA identity with each other (Table 4).

Phylogenetic analysis of the nucleotide sequence of the I-P isolates gave 67.3% bootstrap support, based on the neighbor-joining method, for two origins for these isolates

(Fig. 7). No spatial trends were evident in the clustering of isolates except that some isolates

that were collected next to each other (e.g., I-P12 and I-P13, and I-P17 and I-P18) were

clustered together.

Discussion

Desmodium spp. are hosts to several families of positive-sense RNA viruses, e.g.,

Bromoviridae (27) Comoviridae (2, 15, 18, 21, and 22) Geminiviridae (28), and Tymoviridae

(30). Of the comoviruses, CPMV (21), BPMV (2, 15, 22) and a BPMV-like virus (18) have been reported from Desmodium spp. However, this is the first report of the full nucleotide

sequence of a Comovirus from Desmodium and the first report of this BPMV reassortant in

nature. Based on NA and AA sequence comparisons and phylogenetic analysis, BPMV

isolate I-Di1 belongs to RNA–1 subgroup I and RNA–2 subgroup II (Table 2, Fig. 5). This

subgroup combination was documented in Gu, et al. (10); however, their finding was derived

from an infectious transcript and not a field-collected isolate. Therefore, I-Di1 represents a novel reassortant in nature. Inoculation of I-Di1 to three varieties of soybean resulted in mild foliar symptoms (Fig. 6A–E) that developed to moderate symptoms by ~ 4 months post

inoculation (data not shown). This result is consistent with the mild reaction on soybean cv.

Essex given by the RNA–1 subgroup I, RNA–2 subgroup II pseudorecombinant reported by

Gu et al. (10).

All sequenced soybean isolates were most similar to RNA–1 subgroup II, based on comparisons of RNA–1 NA identity (Table 3) with much within-field heterogeneity between

I-P isolates (Table 4). Although RNA–2 of these isolates may be related to I-Di1, symptom severity is governed by RNA–1 (9) for which RNA–1 subgroup I is most mild (10). Thus it is unlikely that I-Di1 could be the only source for an economically important epidemic within this soybean field. Furthermore, because RNA–1 from I-Di1 belongs to subgroup I, these isolates may not be related. However, this crop was planted with an ~76.2-cm row spacing

and likely > 40,000 seeds per hectare; therefore, it is possible that the within-field diversity

reported here is an underrepresentation of the total isolate diversity. Still, it is noteworthy that

I-Di1 and the I-P isolates, only separated by ~ 50−60 meters of woodland habitat, apparently belong to different strains.

The degree of BPMV isolate diversity from within this ~720-m transect of soybean was unexpectedly high. For example, isolates such as I-P1 and I-P3, collected less than

100−m apart apparently have a nucleotide divergence rate of 1.2% (Table 4). A recent study

of the natural populations of Alaskan isolates of Barley yellow dwarf virus (BYDV) and

Cereal yellow dwarf virus (CYDV), both aphid-transmitted RNA viruses, revealed <1%

sequence divergence (25). However, their diversity study was based on the coat protein gene of BYDV and CYDV and thus may be more evolutionarily constrained. That is for other aphid-transmissible viruses, virus acquisition is an evolutionary bottleneck (1).

The ~1.4 Kb product sequenced from I−P isolates corresponded to 23 bp of the C-

terminus of the proteinase cofactor (Co-Pro) and most (N-terminus to nucleotide 2713) of the helicase (Hel) gene. Bean pod mottle virus symptoms map to RNA–1 with both the Co-Pro

and Hel genes being important for symptom severity (9). In fact, the Hel gene alone can

affect symptom severity between subgroup I strains. Therefore, diversity in nucleotide

substitution within the Hel gene may have a measurable impact on crop performance.

It is not known through what route BPMV RNA–1 subgroup II was introduced into

this soybean field. At least two insect vectors of BPMV feed on Desmodium and soybean; C.

trifurcata (2, 15) and Odontata horni Smith (2, 31). Given the preference of C. trifurcata for

D. illinoense and soybean (2), the importance of partial diploid strains in symptom severity

(10), and potential impact of early-season beetle activity on the BPMV management (16), a

severe epidemic may occur should these two strains be mixed via beetle feeding (e.g., 7, 29).

Phylogenetic analysis indicates at least two possible origins of these I-P isolates (Fig.

7). There are two to three temporally-separated populations of bean leaf beetles during the

soybean growing season in Iowa (16, 26). It may be that the diversity of BPMV is related to

the two to three, separate immigration events of the bean leaf beetle. Thus the difficulty of

managing BPMV (16) may be related to a complex molecular epidemiology.

Acknowledgements

We thank R. O. Pope for locating and identifying the plants of native plants used in

this study. We thank R. Pringnitz and Hertz Farm Management Inc. (Neveda, IA) for access

to their property. We thank A. L. Eggenberger for insight and suggestions. This research was funded in part by the Iowa Soybean Association and the North Central Soybean Research

Program. This journal paper of the Iowa Agriculture and Home Economics Experiment

Station, Ames, Iowa, Project No. 3608, was supported, in part, by Hatch Act and State of

Iowa funds.

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Table 1. Primers used in PCR and sequencing reactions for BPMV isolates. Nameabc Sequence BP-5'end-for TATTAAAATTTTCATAAGATTTGAAATTTTG R1-235-for ATATAGGACTTCGTGTCAGATT R1-481-rev TTCAGTATCCTCCTCACAGC R1-688-for TGCATATCATTTTCAGCATTTTGT R1-798-rev ATAGAGAGAGCCAAGTCTGC R1-1208-for TGTGCTACCATTGCAGTTTCTA R1-1989-for TGATGATTTTGCTGCTGTT R1-2267-rev AAGTTTGGTCTACAACATAATGA R1-2246-for CATTATGTTGTAGACCAAACTT R1-2616-rev ATGAGCATTGTCTCTGAAGC R1-3363-rev TCAGGATCATACACATGCCA R1-3609-for GGAAACAAGATGTAAGCATTGAATAT R1-3843-rev ACTCCCTCTTGACTATCAAC R1-3963-rev AACACACTTGGAATCTTATCAC R1-4572-for GGACTGGTTTGGCAAATAGACTGTT R1-4704-rev CCACCACCAAGACTGTTTATCA R1-5031-for GTGATAACATCACCATCACT R1-5050-rev AGTGATGGTGATGTTATGAC R1-5427-for TGTTGAGCATTGACTTGTT R1-5445-rev AACAAGTCAATGCTCAACA R1-5888-for GTTGATGAGTGTCCTTTTGCATT R1-5910-rev AATGCAAAAGGACACTCATCAAC R1-3'Cla-rev CCATCGATTTTTTTTTTTTTTTTTTTTATATTTAAACAC

R2G7-437-for ACTTGGGCATTGGTGCAAATGT R2-622-rev AATGTAGATCAACAAGGTATACAGATGC

R2G7-949-for ACTTCTTACTGATGGGAAGTTGTA R2-1673-for GGTGCTGGTTCACATTCTTC

R2G7-2135-for TGGAATCCTGCTTGTACAAAAGCA R2-2187-for GTTCTGATGCATGGAGTTTGGAA R2-2187-rev TTCCAAACTCCATGCATCAGAAC

R2G7-2748-for TGGCTGATGGGTGCCCATATT R2-3177-for CCTCATTGGTACAAGTGTTT

R2G7-3227-rev CAAAGTGCTCTGTACTATTACT R2-3604-rev AATAGGCAGAGCATACTCA R2-3'Cla-rev CCATCGATTTTTTTTTTTTTTTTTTTTAAAATAACACAC a Primers are named according to RNA type (R1 or R2), genomic location (based on K-G7 sequence), and direction. Subscript "G7" indicates primers that are specific for subgroup 2 RNA, all other primers are universal. b The BP-5'end-for primer is universal for both RNA–1 and RNA–2. c The primers with 3'Cla contain Cla1 restriction sites to enable the transcription of the polyadenelated C-terminus.

Table 2. Percentage amino acid similarity (below diagonal) and nucleic acid identity (above diagonal) of RNA–1 and RNA–2 sequences from BPMV isolates.

RNA–1 K-Ha1 K-Ho1c K-G7 IL-Cb1 IL-Cb1 I-Di1 ab (II) (I) (I) (I) (II) (I) K-Ha (II) ⎯ 85.8 85.5 85.8 98.4 85.9 K-Ho1 (I) 97.2 ⎯ 98.1 99.1 86.0 98.2 K-G7 (I) 95.8 97.9 ⎯ 97.8 85.6 97.8 IL-Cb1(I) 97.0 99.5 97.7 ⎯ 86.0 97.9 IL-Cb1(II) 99.8 97.2 95.7 96.9 ⎯ 85.7 I-Di1 (I) 97.1 99.2 97.9 99.1 97.0 ⎯

RNA–2 K-Ha1 K-Ho1 K-G7 IL-Cb1 I-Di1 (II) (II) (I) (I) (II) K-Ha (II) ⎯ 98.8 86.6 86.7 97.8 K-Ho (II) 99.5 ⎯ 86.9 87.0 98.0 K-G7 (I) 97.5 96.5 ⎯ 96.6 86.2 IL-Cb1 (I) 96.6 96.9 97.9 ⎯ 86.4 I-Di1 (II) 98.9 98.9 95.5 96.1 ⎯ a Strain subgroup classification indicated in parenthesis. b Genbank accession numbers for fully-sequenced and submitted isolates: RNA–1; AY744932 (IL-CB1, subgroup II), AY744931 (IL-CB1, subgroup I), AF394606 (K-Ha1), AF394608 (K-Ho1), and K-G7 (NC_003496) and RNA–2; AY744933 (IL-Cb1), AF394607 (K-Ha1), AF394609 (K-Ha1), and NC_003495 (K-G7). c Isolate K-Ho1 and IL-Cb1 exist as partial diploid reassortants in nature.

Table 3. Percentage nucleic acid identity between RNA–1 of Bean pod mottle virus isolates collected from a single soybean field in Story County, Iowa (I-P1…18) and fully-sequenced isolates.

I-Di1a IL-Cb1bc IL-Cb1 K-G7 K-Ha1 K-Ho1 (I) (I) (II) (I) (II) (I) I-P1 84.9 85.5 98.6 85.3 98.7 85.3 I-P3 84.8 85.1 98.4 85.0 98.4 85.0 I-P11 84.6 85.0 98.6 85.0 98.4 84.8 I-P12 84.4 84.6 98.1 84.8 98.3 84.6 I-P13 84.4 84.9 98.4 84.8 98.3 84.8 I-P14 84.4 84.7 98.7 84.6 98.3 84.6 I-P16 84.4 84.4 98.6 84.6 98.5 84.7 I-P17 84.6 84.6 98.7 84.9 98.6 84.8 I-P18 84.3 84.3 98.2 84.9 98.1 84.6

a Comparison of 1,453 base-pair fragments. Subgroup designation for fully-sequenced isolates in parenthesis. b Genbank accession numbers for fully-sequenced and submitted isolates: AY744932 (IL- CB1, subgroup II), AY744931 (IL-CB1, subgroup I), AF394606 (K-Ha1), AF394608 (K- Ho1), and K-G7 (NC_003496). c Isolate IL-Cb1 and K-Ho1 exist as partial diploid reassortants in nature.

Table 4. Percentage nucleic acid identity between RNA–1 of Bean pod mottle virus isolates collected from a single soybean field in Story County, Iowa. Based on a 1,453 base-pair fragments.

I-P1 I-P3 I-P11 I-P12 I-P13 I-P14 I-P16 I-P17 I-P18 I-P1 ⎯ 98.8 98.8 98.5 99.1 98.8 99.1 99.2 98.6 I-P3 ⎯ 98.5 98.4 98.7 98.6 98.6 98.8 98.1 I-P11 ⎯ 98.8 98.6 98.4 98.8 99.0 98.4 I-P12 ⎯ 98.3 98.5 98.6 98.8 98.1 I-P13 ⎯ 98.6 99.0 99.1 98.4 I-P14 ⎯ 98.6 98.7 98.1 I-P16 ⎯ 99.2 98.5 I-P17 ⎯ 99.0 I-P18 ⎯

Figure 1. Orthophoto map (1 meter per pixel resolution) of collection localities of Bean pod mottle virus isolates. Line indicates the approximate vector traveled (~720 meters) for the collection of soybean isolates I-P1, I-P3, I-P11, I-P12, I-P13, I-P14 I-P16, I-P17, and I-P18 (with I-P1 collected at southern and I-P15 collected at northern end). Arrow indicates the type locality for I-Di1, ~ 42° 07′ 48′′ N, 093° 33′ 32′′ W.

Figure 2. Annotated nucleotide sequence of RNA–1 from Bean pod mottle virus isolate I-Di1 with its single open reading frame (ORF) denoted.

Figure 3. Annotated nucleotide sequence of RNA–2 from Bean pod mottle virus isolate I-Di1 with its two open reading frames (ORF) denoted.

RNA–1 amino acid sequence

RNA–2 amino acid sequence

Figure 4. Annotated amino acid sequence derived from the open reading frames (ORF) of RNA–1 and RNA–2 of Bean pod mottle virus isolate I-Di1. Gray arrows indicate proteolytic cleavage sites. Line interrupting RNA–2 amino acid denotes the N−terminus of the polyprotein product from ORF 2.

RNA–1

RNA–2

Figure 5. Phylogenetic estimates of Bean pod mottle virus (RNA–1 and RNA–2) polyproteins according to unweighted pair group method using arithmetic averages. The numbers indicate the number of bootstrap replicates out of 1000 that resulted in the conserved node for the comparison of polyproteins deduced by amino acid sequences. The published isolates have the following accession numbers: RNA–1; AY744932 (IL-CB1, subgroup II), AY744931 (IL-CB1, subgroup I), AF394606 (K-Ha1), AF394608 (K-Ho1), and K-G7 (NC_003496) and RNA–2; AY744933 (IL-Cb1), AF394607 (K-Ha1), AF394609 (K-Ha1), and NC_003495 (K-G7). Isolates IL-Cb1 and K-Ho1 exist as partial diploid reassortants in nature.

Figure 6. Representative soybean plant of varieties, William’s L78 (A and B), Clark L67- 3127 (C and D), and Essex (E and F) infected (B, D, and F) or uninfected (A, C, and E) with Bean pod mottle virus isolate I-Di1. Photographs are 32 (D), 43 (B), 52 (F) dpi.

Figure 7. Neighbor-joining phylogram of Bean pod mottle virus isolates collected along a 720-m transect in soybean. The numbers indicate the number of bootstrap replicates out of 1000 that resulted in the conserved node for the comparison of nucleotide sequences from a 1,453 base pair fragment.

CHAPTER 5. A MANAGEMENT STRATEGY FOR BEAN LEAF BEETLES (COLEOPTERA: CHRYSOMELIDAE) AND BEAN POD MOTTLE VIRUS (COMOVIRIDAE) IN SOYBEAN

A paper to be submitted to the Journal of Economic Entomology

Jeffrey D. Bradshaw1, Marlin E. Rice1, and John H. Hill2

1Department of Entomology

2Department of Plant Pathology

Iowa State University,

Ames, IA 50011

Abstract

Cerotoma trifurcata Förster (Coleoptera: Chrysomelidae) and Bean pod mottle virus

(Comoviridae) (BPMV) act together to reduce yield and seed quality of soybean, Glycine

max (L.). Field experiments were conducted to evaluate the effects of systemic, seed-applied and foliar-applied insecticides for the management of this pest complex at three locations, in central, northeastern, and northwestern Iowa during 2002−2004. Seed-applied insecticide

was evaluated within the context of a currently recommended management program for Iowa

(i.e., insecticide applications that target emerging overwintered beetles, F0, and the first

seasonal generation, F1). The experimental treatments included seed-applied (thiamethoxam

[0.3–0.5 g ai kg-1] or clothianidin [47.32 ml ai kg-1]) and foliar-applied (lambda cyhalothrin

[16.83–28.05 g ai ha-1] or esfenvalerate [43.74–54.69 g ai ha-1]) insecticides. Applications of

the foliar insecticides were timed, according to the experimental treatment, to target F0, F1 or both F0 and F1 populations of C. trifurcata. Our results confirm that insecticides timed at F0 and F1 populations of C. trifurcata can reduce virus incidence and improve both yield and

seed color. Furthermore, seed-applied insecticides may be a more reliable option for F0- targeted insecticide within this management strategy. The greatest yield improvement (0.9 q

-1 -1 ha [~1.3 bu a ]) was achieved if the F0-targeted insecticide was a seed-applied systemic.

Introduction

The adult bean leaf beetle, Cerotoma trifurcata Förster (Coleoptera: Chrysomelidae),

causes economic damage to soybean by feeding on leaves, stems, and pods (Smelser and

Pedigo 1992a−b, Pedigo and Zeiss 1996) and its pest status has been elevated further by its

transmission of Bean pod mottle virus (Comoviridae) (BPMV) (Giesler et al. 2002). This

virus reduces soybean yield (Horn 1973, Hopkins and Mueller 1984) and quality (Hill et al.

2007). Furthermore, the effects of BPMV on soybean yield are synergistic with those of

Soybean mosaic virus (SMV) (Ross 1968, Anjos et al. 1992), a seed- and aphid-transmitted

pathogen common in soybean (Steinlage et al. 2002).

Although transmitted by several species of Coleoptera (Horn et al. 1970, Patel and

Pitre 1971, Fulton 1974, Mabry et al. 2003, Werner et al. 2003), BPMV is most efficiently

transmitted by C. trifurcata whose populations have undergone dramatic changes in

abundance in recent years (Giesler et al. 2002). Recently, annual peak abundance at a single

location in Iowa reached 165% of their 1996 levels (Bradshaw and Rice 2003). These

changes in abundance are likely regional and presumably the incidence and prevalence of

BPMV has increased as a result. In Iowa, BPMV is ubiquitous (Krell et al. 2004) and is apparently most prevalent and incidence highest (Robertson and Nutter 2006) where C.

trifurcata survival is high (Rice and Pope 2004).

In Iowa, C. trifurcata overwinter as adults (Kogan et al. 1974, Waldbauer and Kogan

1976, Smelser and Pedigo 1991), primarily in woodlots (Lam and Pedigo 2000a), and are

94 bivoltine (Smelser and Pedigo 1991); often resulting in three population maxima

(overwintered population = F0, first generation = F1, and second generation = F2) throughout the season. Although soybean is a preferred host (Henn 1989, Bradshaw et al. 2007), there are several hosts available to C. trifurcata prior to soybean emergence (Bradshaw et al.

2007). Some hosts, e.g., Desmodium spp., may be particularly important as they may be a prevalent source of inoculum for BPMV (Moore 1969, Krell et al. 2003, Bradshaw et al.

2007). The early-season acquisition of virus may be compounded by its ability to remain viable within beetles in diapause or to be seed transmitted in soybean (Krell et al. 2003). Due to the transmission efficiency of this beetle (Patel and Pitre 1976, Wang et al. 1992) and the possibility of many adults entering emergent soybean fields, early-season controls have been recommended (Krell et al. 2004).

Damage to soybean from C. trifurcata can be reduced by later planting (Pedigo and

Zeiss 1996, Witkowski and Echtenkamp 1996), host-plant resistance (Hammond et al. 2001,

Lam 2001b, Srinivas et al. 2001), or population suppression by chemical control (Lam et al.

2000b, 2001a). Management actions that affect a vector population can impact their transmissible agents (Perring et al. 1999); however, the affects of C. trifucata-management tools and tactics on BPMV transmission are not fully understood. For example, early-planted soybean apparently are more susceptible to BPMV (Giesler et al. 2002); however, Krell et al.

(2005) found that delayed soybean planting inconsistently reduced the seed-borne incidence of BPMV. Various types of host-plant resistance can reduce C. trifurcata injury to pods (Lam

2001b) and leaves (Hammond et al. 2001, Srinivas et al. 2001) and, although pathogen- derived resistance has been developed against BPMV (Reddy et al. 2001) and field tolerance may exist (Hill et al. 2007), no C. trifurcata resistance tool has been tested against BPMV.

Krell et al. (2004) studied the impact of carefully-timed chemical control of C. trifurcata and reported that a reduction in vector abundance could reduce the incidence of BPMV, improve yield, and protect seed quality. This was particularly true for insecticides targeting F0 and F1 populations and has since been a recommended practice for soybean grown for food and seed in Iowa (Rice et al. 2007).

However, the use of insecticides for the suppression of viral vectors has been used in many crop systems with variable results. Roughly 47% of virus pathosystems that have been managed with insecticides have failed to reduce virus incidence (Perring et al. 1999).

Although the insecticidal control of Coleoptera as viral vectors is poorly understood, insecticides are used commonly in soybean for the management of C. trifurcata and,

according to Krell et al. (2004), insecticidal control can reduce BPMV incidence if carefully

timed against the appropriate adult beetle population. Regardless of pestiferous hazards,

soybean growers desire varieties that tolerate early planting dates (for Iowa this includes

dates between late April to early May) with the expectation of improved or equivalent yield

(Pedersen 2006). Because later planting is currently undesirable and the genetic tools for

resistance to these pestiferous agents are not yet available to growers, insecticidal controls

have been more heavily pursued to manage this pest complex.

Some insecticides, such as the pyrethroid lambda-cyhalothrin, have demonstrated

both suppression of C. trifurcata abundance as well as long residual activity (Hammond

1996) with an apparent antifeedant quality (Dobrin and Hammond 1985) in soybean.

Additionally, lambda-cyhalothrin can suppress C. trifurcata populations at low application rates (Rice and O'Neal 2007). For these reasons Krell et al. (2004) chose this chemical for C.

trifurcata suppression to reduce the impact of virus on soybean. Importantly, Krell (et al.

2004) also noted that insecticides must be applied as soon as adult F0 adults arrive in the field

if the control is to be effective.

Cerotoma trifurcata can cause injury and transmit BPMV to soybean as soon as the

plants emerge (Ross 1969, Walters 1970, Hopkins and Mueller 1984, Ragsdale 1984).

However, spring rainfall may hinder proper timing of foliar−applied insecticides for suppression of early-season BPMV vectors. Systemic seed-applied insecticides may be effective for managing F0 populations of C. trifurcata because of their efficacy at low

application rates (Rice, unpublished data) and because they are applied to seed prior to

planting. Additionally, neonicotinoids (e.g., thiamethoxam, imidacloprid, and clothianidin)

are less toxic than foliar-applied insecticides to mammals (e.g., rat oral LD50 = 5,523

[Syngenta Crop Protection 2005] , ≤4,690 [Bayer CropScience 2007], and ≤ 2,000 mg/kg

[Bayer CropScience 2006] of body weight, for lambda-cyhalothrin, thiamethoxam, and

clothianidin, respectively) and predaceous Heteroptera (Boyd and Boethel 1998).

The objectives of this study were to evaluate F0- and F1-targeted C. trifurcata

chemical control tactics for the management of C. trifurcata and BPMV. The emphasis was

to determine the effects a seed-applied insecticide might have on C. trifurcata populations

and how this would affect BPMV incidence in soybean. These effects were tested relative to

the recommendations of Krell et al. (2004) (the use of an early plus mid-season foliar

insecticide application). Each application timing of this management strategy was tested

using two management tools (seed-applied or foliar-applied insecticide).

Materials and Methods

Experimental design. Field studies were geographically distributed at three locations

in Iowa during 2002−2004. Experimental plots were located at Northwest, Northeast, and

Central Iowa State University Research and Demonstration Farms, in O’Brien, Floyd, and

Story counties, respectively (subsequently referred to as northwest, northeast or central).

Northwest was abandoned in 2004 due to weather-related crop loss. Within each field, 7

(2002) or 8 (2003−2004) experimental treatments were applied in a randomized complete

block design with each experimental unit of ~279 m2 (consisting of 12 rows of soybean, each

30.5 m long) having 4 (in 2002) or 8 (in 2003-2004) replicates of Kruger 277 or Mark 0124

soybean cultivars, respectively. Both soybean cultivars were glyphosate resistant, soybean

cyst nematode resistant and glyphosate herbicide was used as needed according to common

weed management practices. To minimize interplot interference between experimental units,

only the center six rows received an experimental treatment. Experimental blocks were

separated by at least 9.14 m of untreated soybean. Insecticidal treatments were applied either

to seed or foliage (Table 1) with foliar insecticides applied by tractor and boom sprayer at

first sighting of F0 (around soybean stage VC-V1 [Fehr 1971]) and F1 (around soybean stage

V6-R1) beetles.

Among locations, planting dates ranged from 25 April−7 May (2002), 17−24 May

(2003), and 28 April−3 May (2004). Although Krell et al. (2005) reported that variation in

planting dates has little effect on BPMV incidence, early planting dates were used to maximize C. trifurcata colonization of plots (Pedigo and Zeiss 1996) and to maximize the

potential for early transmission of BPMV. These dates span early to normal planting times for soybeans in Iowa (Pedersen 2006) and plant emergence was expected to coincide with F0

C. trifurcata immigration (Smelser and Pedigo 1991).

Insect sampling. Cerotoma trifurcata were sampled weekly from soybean emergence

(VE) until leaf drop (~R7). Early-stage soybeans are too short and delicate for sweep-net

sampling; therefore, soybean stages VE-V4 were sampled by five in situ counts of a 5-m

length of row per experimental unit. When plants reached stage V4-V5, 20-sweep sampling

units were taken from the middle six rows in each experimental unit with a 38-cm diameter

sweep net, bagged, and returned to the laboratory for counting. Soybean development was

estimated as described by Fehr et al. (1971). Relative emergence of adult beetles was

determined by counting teneral individuals within sweep-net samples.

BPMV incidence. Soybeans were sampled for BPMV after the peak of the F0, F1, and F2 C. trifurcata populations (3 sampling times) in 2002; at the beginning and after the

peak of each population (6 sampling times) in 2003; and at the beginning and after the peak

of F0 and F1 populations and at the beginning of F2 (5 sampling times) population in 2004.

Samples were taken from the middle four rows of each treatment by systematically

collecting, in approximately 5−m intervals, the uppermost, expanded leaves of 20 plants per treatment (5 leaves from each sampling row). Leaves were collected into plastic bags, according to experimental unit, stored on ice and brought back to the laboratory. Sap was extracted from each leaf using a leaf grinder (Ravenel Specialties Corp., Seneca, SC) with phosphate-buffered saline (0.05 M sodium phosphate, 0.15 M sodium chloride, containing

2% Tween-20, pH=7.15). The leaf grinder was washed with ~20-30 ml of distilled water between extractions. Sap was stored in 2-ml microcentrifuge tubes and held at -20°C.

Individual samples were then robotically transferred using a Tecan Genesis 150TM (Tecan

US, Durham, NC) to 96 well deep-well plates, for compact storage and efficient transfer to immunoassay plates, and stored at -20°C. Samples were then transferred to immunoassay

plates for biotin-avidin double antibody sandwich, enzyme-linked immunosorbent assay

(ELISA). This assay was completed as described by Krell et al. (2004) except for the use of a

microtiter 96 Plate WasherTM (Tecan US, Durham, NC), a robotic ELISA-plate washer

programmed for seven cycles rinsing and aspiration. Following plate washing, each plate was

pat dried on paper toweling.

Seed assessments. The proportion of discolored or mottled seed, seed weight, and

relative amount of virus antigen in a sample were determined from a single random sample

of 100 seeds harvested from each experimental unit. Individual seeds were counted as

mottled if any discoloration was observed. Yield was determined by harvesting the center 2

(2002) or 6 rows (2003 and 2004), and recording the 13%-moisture-corrected weight.

Relative levels of virus (BPMV or SMV) antigen in seed were determined as previously

described (Krell et al. 2005, Hill et al. 2007). Because SMV can be synergistic with BPMV

(Ross 1968, Quiniones et al. 1971, Anjos et al. 1992), and because its symptoms are identical

to that of BPMV, the relative antigen level of SMV was also determined. In this analysis a

value of 1.0 or less indicates virus antigen was not detected.

Data analysis. Data were analyzed using a mixed model ANOVA, PROC MIXED

(SAS 2006), with blocks within locations declared as a random source of variance for means

comparisons for estimated total C. trifurcata abundance, pathogen incidence, and yield data.

Data were combined where there was no significant interaction of treatment by location. For

comparisons of treatment effects, data were analyzed separately by year. For comparisons of

temporal C. trifurcata abundance between treatments, overall effects of treatment, date, and treatment by date were determined using a repeated measures analysis. The repeated subject

(treatment by block) was modeled using a spatial power (using sampling date as the source of repeated variability) type of covariance structure and block was declared as a random source of variation. For repeated measures analysis, each year and location were treated separately

100

because of differing correlations of covariance structures for the date effect using PROC

MIXED (SAS 2006). Treatment comparisons were analyzed further by date via Dunnett’s

Test for differences with an untreated control to derive the mean significant difference with

the control using PROC MIXED (SAS 2006). Denominator degrees of freedom for repeated

measures were calculated using the Satterthwaite method. Count data were transformed by

the square root of (y + 0.375) to stabilize the variance if indicated as necessary by residual

plot examination (Kuel 2000).

Disease incidence was calculated using a generalized linear mixed model, PROC

GLIMIXED (SAS 2006), to derive the area under the antigen incidence curve the results of

which were compared by ANOVA, PROC MIXED (SAS 2006). Counts of discolored seed

were analyzed using PROC GLIMIXED (SAS 2006). Estimates are expressed as means ± SE

unless otherwise indicated. Times are in day of year unless otherwise stated. Overall F- values are notated as Fndf, ddf and t-values as tddf.

Results

Interactions of year by location. Overall there was a significant location by year

interaction for all response variables measured in this study (Fig. 1A-G). While there was a

marked decrease in total vector abundance (Fig. 1A), the area under the antigen incidence

curve (AUAIC) for BPMV remained the same between years 2002 and 2003 (Fig. 1B) for all

locations. This interaction followed a similar trend by location in relative amounts of BPMV

antigen in seed (Fig. 1C), while a very low incidence of SMV antigen was detected in seed in

2003 (Fig. 1D). Seed quality improved from 2002 to 2004 (Fig. 1E) as did yield (Fig. 1F);

However, seed weight was more variable, especially between 2002 and 2003 (Fig. 1G).

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Vector control. Because year had a stronger influence on total C. trifurcata

abundance relative to location (Fig. 1A; year: F2, 322 = 4217.46; P < 0.0001; location: F2, 14 =

40.92; P < 0.0001) and some changes were made between years (e.g., insecticide application

rates), estimates of total beetle abundance were analyzed by year. Overall the estimated total

beetle populations (based on pooled averages from all study locations; pooled from in-row

and sweep net samples) declined significantly 754.39±10.36, 31.65±7.51, and 3.45±9.29 (F2,

354 = 2095.14, P < 0.0001) from 2002–2004, respectively (Fig. 1A). Of these adults,

approximately 8, 11, and 14% C. trifurcata from 2002−2004, respectively, were determined

to be teneral (i.e., unsclerotized).

Assuming a decreased mobility during their teneral period (Chapman 1998), teneral beetles may be more likely to have emerged from within plots than fully sclerotized adults.

Therefore, the total seasonal abundance of teneral adults may provide an indication of relative emergence from within an experimental unit and therefore treatment effects. Based on these relative counts of teneral beetles, seed treatment or seed treatment plus a foliar insecticide significantly reduced the total estimated emergence at the northeast location in

2002 (Table 2) and all locations in 2003 and 2004 (Table 2).

In 2002, although the addition of an F1-targeted insecticide had no significant effect

on estimated total C. trifurcata abundance at the central and northeast location (Table 3), any

F1-targeted insecticide had significantly fewer beetles than an untreated control at the

northwest site (Table 3). At northwest F0- plus F1-targeted insecticide program resulted in

388.69±47.8 fewer beetles than an F0-targeted insecticide alone regardless of the insecticides

used. This result is based on a contrast comparison of F0 minus F0- plus F1-targeted

insecticide treatment (t54 = 8.13, P < 0.0001).

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In 2003, the F0-targeted insecticide treatments alone had fewer total beetles than an untreated control (Table 3). The F1-targeted treatments had slightly higher total beetle

abundance at the northwest location, with F0- plus F1-targeted insecticide program having

11.98±2.98 more total C. trifurcata relative to a single F0-targeted insecticide. This result is

based on a contrast comparison of F0 insecticide minus F0- plus F1-targeted insecticide

treatment (t147 = 4.02, P < 0.0001). However, this contrast comparison was not significant for

northeast (t147 = 0.21, P < 0.8310) or northwest (t147 = 1.38, P < 0.1685).

The results for 2004 were similar to 2003 in that the F0-targeted insecticide treatments

had fewer total beetles (Table 3). This was particularly true for treatments that included seed-

applied insecticides.

Temporal effects. Significant changes were measured in the temporal abundance of

bean leaf beetles in all years (Tables 4 and 5). Overall treatment effects were statistically

significant at northeast and northwest in 2002, all locations in 2003, and northeast in 2004 for

VE−V4 (in-situ counts, Table 4) soybean stages. For V5−R7 soybean stages, overall

treatment effects were statistically significant at northeast and northwest in 2002 and 2003

(sweep-net counts, Table 5).

A temporal analysis by sample date indicated that some insecticidal treatments

significantly reduced beetle abundance during times of increasing abundance for some

locations (Figs. 2−4). Although there was no significant treatment effects at the central

location in 2002 as revealed by the overall analysis (Table 4, Fig. 2A), F0-targeted

insecticides significantly reduced F0 abundance relative to control at northeast (Fig. 2B; day

150: F6, 18 = 3.31, P = 0.0224; day 157: F6, 18 = 12.65, P < 0.0001) and northwest (Fig. 2C;

day 148: F6, 18 = 20.19, P < 0.0001; day 155: F6, 18 = 17.27, P < 0.0001) locations. In 2003,

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central (Fig. 3A; day 155: F7, 49 = 2.90, P = 0.0128; day 161: F7, 19 = 7.31, P < 0.0001),

northeast (Fig. 3B; day 161: F7, 49 = 11.80, P < 0.0001; day 167: F7, 49 = 4.80, P = 0.0004)

and northwest (Fig. 3C; day 155: F7, 49 = 9.17, P < 0.0001; day 167: F7, 49 = 3.78, P = 0.0024)

locations had significantly reduced F0 populations via F0-targeted insecticides. In 2004 there

were no significant insecticide effects at the central location (Table 4 and 5, Fig. 4A) and

only two days of insecticidal reduction on C. trifurcata populations at northeast (Table 4,

Fig. 4B; day 155: F7, 49 = 7.36, P < 0.0001; day 160: F7, 49 = 3.04, P = 0.0097).

For all years, the response of F1 and F2 populations to insecticides generally was more

variable than that of F0 populations. There were no significant overall treatment effects for

central in 2002 (Table 5, Fig. 2A). However, F1-targeted applications reduced C. trifurcata abundance below that of a control at northeast (Fig. 2B; day 190: F7, 49 = 21.81, P < 0.0001;

day 197: F6, 18 = 4.18, P = 0.0084; day 231: F6, 18 = 7.79, P = 0.0003; day 242: F6, 18 = 8.08, P

= 0.0002) and northwest (Fig. 2C; day 192: F6, 18 = 3.23, P = 0.0246; day 197: F6, 18 = 4.82, P

= 0.0042; day 211: F6, 18 = 4.14, P = 0.0088; day 233: F6, 18 = 4.81, P = 0.0043; day 239: F6,

18 = 8.15, P = 0.0002; day 246: F6, 18 = 12.50, P < 0.0001; day 253: F6, 18 = 7.03, P = 0.0006) in 2002; and central (Fig. 3A; day 204: F7, 49 = 8.98, P < 0.0001), northeast (Fig. 3B; day

202: F7, 49 = 7.52, P < 0.0001; day 209: F7, 49 = 3.14; P = 0.0081; day 225: F7, 49 = 7.54, P <

0.0001; day 254: F7, 49 = 8.37, P < 0.0001) and northwest (Fig. 3C; day 203: F7, 49 = 3.98, P =

0.0016) in 2003. The central location was not affected by insecticides in 2004 (Table 4, Fig.

4A) and only one day at the northeast location had a significant reduction C. trifurcata abundance via F1-targeted applications (Fig. 4B; day 195: F7, 49 = 2.71, P = 0.0187).

In 2002, all locations had late-season populations (F1 and F2) of C. trifurcata that exceeded the economic injury level for pod damage (Fig. 5A) but not in 2003 (Fig. 5B) or

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2004 (Fig. 5C). Additionally, in 2002, distinct F1 and F2 populations could only be detected

at the northwest location (Fig. 5A). Although not the target of the insecticide program in this

study, no F0 or F1 control strategy maintained F2 populations below economic injury levels

for late-season pod damage. However, the onset of an economic F2 population was delayed

by about 15 days by the application of an F1-targeted insecticide at northwest (data not

shown).

An F0- plus an F1-targeted insecticide program reduced C. trifurcata abundance

through calendar dates 168−267 by 1.50±0.16 (t312 = 9.33, P < 0.0001) beetles via the

addition of the F1-targeted insecticide in 2002 at northwest. This result is based on a contrast

comparison of F0 minus F0- plus F1-targeted insecticide treatments at northwest.

Additionally, as similarly reported for total beetle counts, C. trifurcata populations increased by 0.13±0.06 (t195 = 2.16, P = 0.0318) through calendar dates 169−251 at central in 2003

with the addition of the F1-targeted insecticide in a F0- plus F1-targeted insecticide program.

Virus control. As with C. trifurcata abundance, BPMV incidence generally declined

between 2002 and 2004; however, overall incidence in 2003 was statistically similar to 2002

(Fig. 1B), based on the AUAIC. In addition to this temporal trend, virus incidence was

generally higher at the central location for each year. This trend agrees with the current

understanding of BPMV prevalence in Iowa – that BPMV increases in a north to south

direction (Robertson and Nutter 2006). Additionally, even in years where total C. trifurcata abundance never exceeded 30 individuals total (2004, Table 3), the AUAIC was never below

20% incidence (Figs. 1B and 6A-C), i.e., the minimum economic level for BPMV incidence

(Horn et al. 1973). In 2002, a seed-applied insecticide alone significantly reduced the AUAIC

(Fig. 6A; F6, 54 = 2.48, P = 0.0340). Additionally, An F0- plus an F1-targeted insecticide

105

program increased the AUAIC by 11.98±2.98% (t147 = 4.02, P = 0.0001) via the addition of

the F1-targeted insecticide in 2003 at central. This result is based on a contrast comparison of

F0 minus F0- plus F1-targeted insecticide treatments at northwest. However, this increase in

incidence did not surpass that of the untreated control. There were no significant effects of

treatment on AUAIC in 2004 (Fig. 6C).

Although virus incidence detection in seed was not useful in this study for detecting

pairwise treatment differences (Fig. 7A-F), there were significant year and location effects

(Fig. 1C). The overall treatment effects were only significant in 2002 at central (Fig. 7A: F6,

54 = 3.83, P = 0.003) for which a thiamethoxam seed application alone resulted in a high

relative amount of BPMV in seed. Additionally, when seed was assayed for SMV, only 2003

had detectable amounts of SMV (Fig 2D); however, the average relative amount of antigen

was not significantly greater than 1 (i.e., its 95% confidence interval includes 1). This indicates that while SMV was detected, the amount present was not significantly greater than

the nonspecific ELISA-reaction of healthy seed. Therefore, synergistic interactions between

BPMV and SMV were not likely.

Agronomic effects. Yield generally was highest in treatments with F0 plus F1- targeted insecticide applications (Figs. 8A-E); however, yields were only statistically significant in two out of the 5 location years. Overall, there was no significant treatment effect on yield in 2002 (Fig. 8A); however, there was a significant treatment effect in 2003

(Fig. 8B: F7, 147 = 4.94, P = <0.0001) and 2004 (Fig. 8E: F7, 98 = 4.43, P = 0.0003). An F0- plus an F1-targeted insecticide program increased yield via the addition of an F1-targeted

insecticide in 2003 at the central location by 1.42±0.54 q/ha (~2.11 bu/a) (t147 = 2.63, P =

0.0094) northeast by 1.67±0.54 q/ha (~2.49 bu/a) (t147 = 3.11, P = 0.0023), and northwest by

106

1.55±0.54 q/ha (~2.31 bu/a) (t147 = 2.89, P = 0.0045) based on a contrast comparison of F0

minus F0- plus F1-targeted insecticide treatments. The F1-targeted insecticide resulted in

lower yield in 2004, with the same contrast comparison revealing a 2.26±0.63 q/ha (~3.36

bu/a) (t98 = 3.61, P = 0.0005) decrease in yield at northeast with the addition of an F1- targeted insecticide based on a contrast comparison of F0 minus F0- plus F1-targeted

insecticide treatments.

Treatment had a significant effect on seed-coat discoloration for 2002 (Figs. 9A-C;

F6, 54 = 9.40, P < 0.0001) and 2003 (Fig. 9D-E; F7, 146 = 2.48, P = 0.0196) with significant

interactions of location by treatment for both years (2002: F12, 54 = 2.82, P = 0.0046; 2003:

F14, 146 = 2.94, P = 0.0006). However, there were no significant effects of treatment, location,

or treatment by location for 2004 (Fig. 9F). Overall, the F1-targeted insecticide significantly

improved seed color (Fig. 9B, C, and D). An F0- plus F1-targeted insecticide strategy resulted

in ~5-10% fewer mottled seeds via the addition of a F1-targeted insecticide (2002, northwest:

t54 = 4.74, P < 0.0001; 2003, northeast: t146 = 3.73, P = 0.0003) based on a contrast

comparison of F0 minus F0- plus F1-targeted insecticide treatments. However, this

improvement in seed color was less consistent if the F0-targeted insecticide was applied as a

seed treatment in 2002 (Fig. 9B and C). In fact, an F1-targeted insecticide alone was often

sufficient to protect seed color (Fig. 9B, C, and D).

Location had a significant effect on 100-seed weight for all years (2002: F2, 9 = 30.30,

P = 0.0001; 2003: F2, 21 = 241.54, P < 0.0001; 2004: F1, 14 = 2822.04, P < 0.0001) and

location by treatment effects (Fig. 2G) for 2002 (F12, 54 = 3.27, P = 0.0014) and 2003 (F14, 147

= 4.37, P < 0.0001). There were no significant pairwise treatment effects in 2002 (Fig. 10A and B). However, treatments only had a significant effect on 100-seed weight for 2003 (Fig.

107

10C−E, F7, 147 = 7.82, P < 0.0001) and 2004 (Fig. 10F, F7, 98 = 3.71, P = 0.0013). In general

the addition of a F1-targeted insecticide significantly reduced seed weight by 0.59 ± 0.23,

0.52 ± 0.12, and 0.22 ± 0.10 g/100-seeds from 2002-2004, respectively, relative to a F0-

targeted treatment (Fig. 10B: t54 = 2.62, P = 0.0113; Fig. 10E: t147 = 4.53, P < 0.0001; Fig.

10F: t147 = 4.53, P < 0.0001). This relationship between reduced seed weight, with the addition of F1-targeted insecticides, held even though different soybean varieties were used

in 2002 than in 2003-2004.

Vector management costs in this study were approximately $30.27/ha ($12.25/a) for

2002 and $33.30/ha ($13.48/a) for 2003 and 2004, for F0- plus F1-targeted foliar insecticides.

If a seed-treated insecticide is used as the F0-targeted insecticide, management costs were

$36.28/ha ($14.68/a) (at central and northwest seeding rate) or $37.20/ha ($15.06/a) (at

northeast seeding rate), assuming a 163,000-seed bag, — based on a value of $23.26/q

($6.33/bu) (the average crop value for soybean between 2002 and 2004).

Given these management costs the gain thresholds were 1.30-1.43 q/ha (1.93-2.13 bu/a) for F0- plus F1-targeted foliar insecticides and 1.56-1.59 q/ha (2.32-2.38 bu/a) if a seed-

treated insecticide is used as the F0-targeted insecticide. The yield of the F0- plus F1-targeted

insecticide strategy exceeded the gain threshold if a seed-applied insecticide was used as the

F0-targeted insecticide in 2003 at the northeast and northwest locations (increasing about 1.1

q/ha [~1.6 bu/a] over the gain threshold). These gain-threshold calculations do not include

penalties (e.g., yield reduction associated with management activities or discounted prices

due to grain quality).

108

Discussion

Seed-applied insecticide by itself significantly reduced the AUAIC of BPMV in an

outbreak year, 2002. The use of a foliar insecticide to target F0 and F1 C. trifurcata may have

numerically increased the AUAIC for some insecticides, in some years (Fig 6A−C).

However, only in 2002 did any treatment have a significantly lower AUAIC relative to an untreated control. Furthermore, in this year all treatments had a numerically lower AUAIC than the untreated control. Our findings agree with Daniels (2004) and indicate that BPMV can be reduced by the use of seed-applied insecticides (a treatment targeting F0 vector populations). However, further study is needed to understand how these treatments affect the

temporal progression of BPMV.

As reported by Perring et al. (1999), some externally−borne viruses can increase in

incidence in response to some insecticides. Furthermore, Pederson et al. (2007) reported an increase in BPMV incidence with the use of foliar insecticides timed to suppress soybean aphid, Aphis glycines Matsumura, abundance. In this study there was no statistically

significant increase in virus incidence with the use of insecticides applied to suppress C.

trifurcata abundance (Fig. 6A−C). The trend in this study for reduced virus incidence in

response to foliar insecticide applications targeting F0-, F1-beetles is similar to that found by

Krell et al. (2004) and is the basis for their recommendation.

The results presented here support Krell et al. (2004) that F0-targeted insecticides can

suppress F1 populations and that the success of an F1-targeted insecticide strongly depends on

the seasonal dynamics of C. trifurcata. That is, during years of high C. trifurcata abundance

(e.g., 2002), the onset of a large F1 vector population may be difficult to manage by

109

insecticidal control alone. Even when seasonal population growth is greatly suppressed (Fig.

1B), the rate of transmission apparently is not sufficiently reduced to significantly improve

yield (Fig. 8A) when vector populations are large. Additionally, the AUAIC remained within

range of economic injury (Horn et al. 1973, Hopkins and Mueller 1984) throughout this study

yet a significant yield response to treatments was measured at two locations in 2003 and one

location in 2004.

Yield was greatest for northeast and northwest locations in 2003 if both F0 and F1 populations of C. trifurcata were targeted (Fig. 8B). Therefore, these yield improvements

may be attributable to reductions in direct damage from C. trifurcata. Although soybean

aphids were also present in 2003, their abundance peaked after the insecticide application for

F1-C. trifurcata population (unpublished data) and insecticides, as applied in this study, do

not prevent economic injury from soybean aphids (Johnson et al. 2007). However, economic injury from all of these pests is likely not mutually exclusive and reductions in insect and viral pests may interact to affect soybean yield. Furthermore, a reduction in yield in response to foliar insecticide, as in the northeast location in 2004 (Fig. 8E), may be related to the

suboptimal insecticide timings on soybean aphids and contributing to pest resurgence

(Johnson et al. 2007).

Grain quality is an important factor in the value of soybean grown for export (USDA

2006). This study supports the findings of Krell et al. (2004) that a F0- plus F1-targeted

insecticide strategy (using lambda-cyhalothrin for both applications) may keep grain within acceptable quality standards. However, seed-coat color is regulated by a family of genes

(Takahashi and Abe 1999, Senda et al. 2002, Senda et al. 2004) some of which are affected by the environment. This genotype by environment interaction is variety dependent and

110

seems to affect the phenotypic expression of BPMV on soybean seed coats (Krell et al. 2005,

Hill et al. 2007). Because of these interactions it may prove difficult to manage for soybean

quality in light of earlier planting times (Pedersen 2006) without the use of more reliable management tools.

There can be benefits to yield with an F0 plus F1-targeted insecticide application and

the maximum yield gain is achieved when a seed-applied insecticide is used as the F0- targeted insecticide (Fig. 8B). However, these yield benefits may be offset under some situations with poorly-colored grain when a seed-applied insecticide is used (Fig. 9D).

Because the success of this management program depends on the seasonal dynamics of C.

trifurcata, consistent suppression of both C. trifurcata and BPMV is challenging; therefore,

caution should be taken in its recommendation. These results further clarify the need to

discover and exploit the mechanisms of resistance to C. trifucata and BPMV.

Acknowledgements

We thank Al Eggenberger and M. Reza Hajimorad for their insight and suggestions

concerning molecular methods. We thank David Starrett, David Haden, and Kenneth

Pecinovski for field management activities. This research was funded in part by the Iowa

Soybean Association and the North Central Soybean Research Program. This journal paper

of the Iowa Agriculture and Home Economics Experiment Station, Ames, Iowa, Project No.

3608, was supported, in part, by Hatch Act and State of Iowa funds.

111

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Table 1. Experimental treatments for management of bean leaf beetle and Bean pod mottle virus, 2002−2004. Experimental Population treatment Active ingredient Application substrate (rate) Formulation targeta 2002 -1 1 Thiamethoxam seed (0.3 g ai kg ) Cruiser F0 -1 2 Clothianidin seed (47.32 ml ai kg ) Poncho F0 -1 3 Thiamethoxam + λ- seed (0.3 g ai kg ) + foliage (28.05 g ai Cruiser + Warrior F0 + F1 cyhalothrin ha-1) -1 4 λ-cyhalothrin foliage (16.83 g ai ha ) Warrior F0 -1 5 λ-cyhalothrin foliage (28.05 g ai ha ) Warrior F1 -1 6 λ-cyhalothrin foliage (16.83 g ai ha ) + foliage (28.05 Warrior F0 + F1 g ai ha-1) 7 Untreated control — — — 2003 and 2004 -1 1 Thiamethoxam seed (0.5 g ai kg ) Cruiser F0 116 -1 2 Thiamethoxam + λ- seed (0.5 g ai kg ) + foliage (21.91 g ai Cruiser + Warrior F0 + F0 cyhalothrin ha-1) -1 3 Thiamethoxam + λ- seed (0.5 g ai kg ) + foliage (28.05 g ai Cruiser + Warrior F0 + F1 cyhalothrin ha-1) -1 4 λ-cyhalothrin foliage (21.91 g ai ha ) Warrior F0 -1 5 λ-cyhalothrin foliage (28.05 g ai ha ) Warrior F1 -1 6 λ-cyhalothrin foliage (21.91 g ai ha ) + foliage (28.05 Warrior F0 + F1 g ai ha-1) -1 7 Esfenvalerate foliage (43.74 g ai ha ) + foliage (54.69 Asana F0 + F1 g ai ha-1) 8 Untreated control — — — a F0=arrival of overwintered Cerotoma trifurcata, F1=at emergence of first generation C. trifurcata.

Table 2. Total counts (mean ± SE) of teneral adult Cerotoma trifurcata from insecticidal treatments applied to affect the incidence of Bean pod mottle virus. 2002 2003 2004 Treatmenta Central b NortheastNorthwest Combined locations Combined locations Clothianidin 7.04 ± 0.55 4.86 ± 0.55b 10.32 ± 0.55 NA NA Thiamethoxam 7.45 ± 0.55 5.51 ± 0.55ab 10.39 ± 0.55 1.17 ± 0.16de 1.31 ± 0.19b Thiamethoxam NA NA NA 1.25 ± 0.16de 1.26 ± 0.19b

+ λ-cyhalothrin (F0) Thiamethoxam 7.05 ± 0.55 4.91 ± 0.55b 9.27 ± 0.55 1.00 ± 0.16e 1.62 ± 0.19ab

+ λ-cyhalothrin (F1)

λ-cyhalothrin (F0) 7.70 ± 0.55 6.84 ± 0.55ab 11.58 ± 0.55 2.03 ± 0.16b 1.78 ± 0.19ab

λ-cyhalothrin (F1) 7.13 ± 0.55 5.00 ± 0.55ab 9.88 ± 0.55 2.07 ± 0.16b 1.98 ± 0.19a

λ-cyhalothrin (F0+F1) 7.21 ± 0.55 6.39 ± 0.55ab 9.20 ± 0.55 1.53 ± 0.16bcd 1.75 ± 0.19ab 117

Esfenvalerate (F0+F1) NA NA NA 1.36 ± 0.16cde 1.55 ± 0.19ab untreated control 6.62 ± 0.55 7.54 ± 0.55a 10.57 ± 0.55 2.87 ± 0.16a 2.08 ± 0.19a Analysis of effects subdivided by year (2002−2003) and location (central, northeast, and northwest Iowa). Data for locations were combined where the interaction of location by treatment was not statistically significant (P < 0.05). Means (LS-means) and standard errors were calculated based on PROC MIXED (SAS 2006). a Symbol in parenthesis indicates the target population (F0 or F1 C. trifurcata populations) for which the foliar insecticides, λ- cyhalothrin and esfenvalerate, were applied against. b Means followed by the same letter, within locations, are not statistically different (P < 0.05). No letters indicate no statistically significant differences (P < 0.05). Means transformed by sqrt(y + 0.375). Table 3. Total counts (mean ± SE) of fully sclerotized, adult Cerotoma trifurcata from insecticidal treatments applied to affect the incidence of Bean pod mottle virus. 2002 2003 2004 Treatmenta Central b Northeast Northwest Central Northeast Northwest Combined locations Clothianidin 799.50 ± 67.27 687.75 ± 67.27 726.50 ± 67.27bc NA NA NA NA Thiamethoxam 735.67 ± 67.27 808.00 ± 67.27 865.00 ± 67.27ab 29.88 ± 4.86b 19.25 ± 4.86c 18.63 ± 4.86b 17.88 ± 2.87bc Thiamethoxam

+ λ-cyhalothrin (F0)NA NA NA 35.13 ± 4.86ab 16.63 ± 4.86c 24.00 ± 4.86ab 16.69 ± 2.87c Thiamethoxam 800.75 ± 67.27 750.75 ± 67.27 444.50 ± 67.27cd 40.86 ± 4.86ab 18.00 ± 4.86c 22.13 ± 4.86ab 21.63 ± 2.87abc

+ λ-cyhalothrin (F1)

λ-cyhalothrin (F0) 723.50 ± 67.27 986.50 ± 67.27 867.00 ± 67.27ab 35.75 ± 4.86ab 33.50 ± 4.86bc 26.63 ± 4.86ab 23.00 ± 2.87abc

λ-cyhalothrin (F1) 802.00 ± 67.27 785.75 ± 67.27 470.25 ± 67.27cd 47.13 ± 4.86ab 45.00 ± 4.86ab 39.00 ± 4.86a 25.50 ± 2.87ab

λ-cyhalothrin (F0+F1) 782.50 ± 67.27 824.25 ± 67.27 330.75 ± 67.27d 44.00 ± 4.86ab 28.13 ± 4.86bc 29.13 ± 4.86ab 24.25 ± 2.87abc

Esfenvalerate (F0+F1)NA NA NA 47.50 ± 4.86ab 30.88 ± 4.86bc 30.38 ± 4.86ab 21.63 ± 2.87abc untreated control 789.00 ± 67.27 986.75 ± 67.27 813.50 ± 67.27ab 52.63 ± 4.86a 53.63 ± 4.86a 31.38 ± 4.86ab 26.69 ± 4.86a Analysis of effects subdivided by year (2002−2003) and location (central, northeast, and northwest Iowa). Data for locations were combined where the interaction of location by treatment was not statistically significant (P < 0.05). Means (LS-means) and 118 standard errors were calculated based on PROC MIXED (SAS 2006). a Symbol in parenthesis indicates the target population (F0 or F1 C. trifurcata populations) for which the foliar insecticides, λ- cyhalothrin and esfenvalerate, were applied against. b Means followed by the same letter, within locations, are not statistically different (P < 0.05). No letters indicate no statistically significant differences (P < 0.05). 119

Table 4. Overall tests of significance for temporal and treatment effects on Cerotoma trifurcata abundance (in-situ counts), in VE−V4 stage soybean, for the management of Bean pod mottle virus in Iowa.

Sample date b c Year Location rangea Effect ndf, ddf F P 2002 Central 132−160 Trt 6, 30.5 1.59 0.1837 Time 4, 74.7 111.02 <0.0001 Trt X Time 24, 74.7 2.07 0.0091 Northeast 141−164 Trt 6, 81 11.03 <0.0001 Time 3, 81 109.09 <0.0001 Trt X Time 18, 81 4.80 <0.0001 Northwest 139−162 Trt 6, 36.2 19.44 <0.0001 Time 3, 63 76.33 <0.0001 Trt X Time 18, 63 5.15 <0.0001

2003 Central 155−161 Trt 7, 49 8.86 <0.0001 Time 1, 56 8.64 0.0048 Trt X Time 7, 56 1.66 0.1390 Northeast 149−161 Trt 7, 40.8 7.14 <0.0001 Time 2, 92.1 19.92 <0.0001 Trt X Time 14, 92.1 2.73 0.0021 Northwest 148−159 Trt 7, 70 13.02 <0.0001 Time 2, 127 3.96 0.0214 Trt X Time 14, 127 6.06 <0.0001

2004 Central 131−158 Trt 7, 49.7 0.70 0.6709 Time 4, 135 4.26 0.0028 Trt X Time 28, 135 1.30 0.1637 Northeast 138−159 Trt 7, 114 5.64 <0.0001 Time 3, 186 3.96 0.0091 Trt X Time 21, 186 2.89 <0.0001 Data analyzed using a repeated measures analysis of variance with treatment by block as a repeated subject. a Dates through which analysis was derived expressed as day of year. b Effects are experimental treatment (Trt), day of year (Time), and interaction (Trt X Time). c Degrees of freedom calculated using the Satterthwaite method.

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Table 5. Overall tests of significance for temporal and treatment effects on Cerotoma trifurcata abundance (sweep-net counts), in V5−R7 stage soybean, for the management of Bean pod mottle virus in Iowa.

Sample date a b c Year Location range Effect ndf, ddf F P 2002 Central 169−266 Trt 6, 75.9 0.05 0.9994 Time 14, 189 191.53 <0.0001 Trt X Time 84, 189 1.06 0.3629 Northeast 171−270 Trt 6, 284 8.84 <0.0001 Time 14, 289 159.23 <0.0001 Trt X Time 84, 289 1.44 0.0146 Northwest 168−267 Trt 6, 312 20.47 <0.0001 Time 14, 312 220.67 <0.0001 Trt X Time 84, 312 3.01 <0.0001

2003 Central 169−251 Trt 7, 195 2.02 0.0549 Time 12, 410 204.22 <0.0001 Trt X Time 85, 410 0.88 0.7670 Northeast 167−263 Trt 7, 217 12.48 <0.0001 Time 13, 442 113.76 <0.0001 Trt X Time 91, 442 2.80 <0.0001 Northwest 167−261 Trt 7, 254 3.36 0.0019 Time 13, 387 220.67 <0.0001 Trt X Time 91, 387 1.32 0.0386

2004 Central 165−246 Trt 7, 665 1.81 0.0816 Time 11, 665 86.31 <0.0001 Trt X Time 77, 665 0.97 0.5597 Northeast 166−245 Trt 7, 169 1.64 0.1273 Time 10, 277 117.37 <0.0001 Trt X Time 70, 277 0.93 0.6301 Data analyzed using a repeated measures analysis of variance with treatment by block as a repeated subject. a Dates through which analysis was derived expressed as day of year. b Effects are experimental treatment (Trt), day of year (Time), and interaction (Trt X Time). c Degrees of freedom calculated using the Satterthwaite method.

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1000 0.16 A 0.14 E 800 0.12 600 0.10 0.08

C. trifurcata 400 0.06 0.04 Total Total 200 0.02 0 Proportion discolored seed 0.00

60 60 55 B 50 F 50 40 45 40 30 35 AUAIC (%)

Yield (q/ha)Yield 20 30 10 25 20 0

4.0 17 3.5 C 16 G 3.0 15 14 2.5 13 2.0 12 1.5 11 1.0 10 Relative antigen (BPMV) 0.5 (g/100Seed seeds)weight 9 2002 2003 2004

1.2 D 1.1 central 1.0

0.9 northwest

0.8 northeast Relative antigen (SMV) 0.7 2002 2003 2004 Figure 1. Location by year interactions, mean ± margin of error (95% CI), for estimated total seasonal abundance of Cerotoma trifurcata (A), area under the anitigen incidence curve (AUAIC) of Bean pod mottle virus (BPMV) (B), relative amount of BPMV antigen in seed (C), relative amount of Soybean mosaic virus antigen in seed (D), proportion discolored soybean seeds (E), yield (F), and 100-seed weight (G) in experiments to reduce Cerotoma trifurcata abundance and BPMV incidence in 2002, 2003, and 2004 in soybean in Iowa.

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Figure 2. Difference between means of Cerotoma trifurcata counts in central (A), northeast (B) and northwest (C) Iowa in 2002 (relative abundance of the untreated control minus treatment plots). Estimates inside the gray area are not different from the control according to the minimum significant difference of Dunnett’s t test. Treatments are seed-applied neonicotinoids (C and P) or a pyrethroid (W) applied to target the onset of F0 or F1 C. trifurcata populations. Foliar application dates for central: F0W = day 138 (May 18), F1W = day 184 (July 3); northeast: F0W = day 148 (May 28), F1W = day 183 (July 2); and northwest: F0W = day 144 (May 24), F1W = day 189 (July 8).

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Figure 3. Difference between means of Cerotoma trifurcata counts in central (A), northest (B) and northwest (C) Iowa in 2003 (relative abundance of the untreated control minus treatment plots). Estimates inside the gray area are not different from the control according to the minimum significant difference of Dunnett’s t test. Treatments are seed-applied neonicotinoids (C and P) or a pyrethroid (W and A) applied to target the onset of F0 or F1 C. trifurcata populations. Foliar application dates for central: F0W or F0A = day 155 (June 4), F1W or F1A = day 195 (July 14); northeast: F0W or F0A = day 152 (June 1), F1W or F1A = day 194 (July 13); and northwest: F0W or F0A = day 151 (May 31), F1W or F1A = day 196 (July 17).

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Figure 4. Difference between means of Cerotoma trifurcata counts in central (A) and northeast (B) Iowa in 2004 (relative abundance of the untreated control minus treatment plots). Estimates inside the gray area are not different from the control according to the minimum significant difference of Dunnett’s t test. Treatments are seed-applied neonicotinoids (C and P) or a pyrethroid (W and A) applied to target the onset of F0 or F1 C. trifurcata populations. Foliar application dates for central: F0W or F0A = day 141 (May 20 [June 12 for northeast]), F1W or F1A = day 183 (July 1) and northeast: F0W or F0A = day 140 (May 19), F1W or F1A = day 190 (July 8).

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300 A 250 central northeast 200 northwest

150

100

0 30 B 25

Average per 20 sweeps 5

0 18 16 C 14 12 10 8 6 4 2 0 120 140 160 180 200 220 240 260 280 Day of year

Figure 5. Mean ± SE (errors calculated by date) abundance of Cerotoma trifurcata in untreated plots at central, northeast, and northwest locations in Iowa, in 2002 (A), 2003 (B) and 2004 (C).

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Figure 6. Area under the antigen incidence curve (AUAIC = average total antigen incidence as a function of day of year) of soybean from experiments to reduce Cerotoma trifurcata and BPMV in 2002 (A), 2003 (B), and 2004 (C). Data combined from central, northeast, and northwest Iowa (P > 0.05 for all location by treatment interactions within years). Treatments (2002): C = Cruiser, P = Poncho, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Treatments (2003−2004): C = Cruiser, A = Asana, W = Warrior, F0 = early-season, F1 = mid-season, check = untreated control. Means grouped by the same lowercase letter are significantly different (P < 0.05). There was no significant location by treatment interaction (P < 0.05).

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Figure 7. Mean ± SE relative BPMV antigen in soybean seeds from experiments to reduce Cerotoma trifurcata abundance and BPMV incidence in 2002 (grey bars), 2003 (white bars), and 2004 (hatched bars). Data from central (A), northeast (B), northwest (C, E) Iowa, or central and northeast combined (D, F). Treatments (2002): C = Cruiser, P = Poncho, W = Warrior, F0 = early-season population target, F1 = mid-season population target, X = untreated control. Treatments (2003−2004): C = Cruiser, A = Asana, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Treatment means based on ELISAs, with normalized hydrolysis times, of a pooled 100 seeds from each experimental unit and compared to an uninfected 100-seed control. Means grouped by the same lowercase letter are significantly different (P < 0.05). Data grouped by location based on significant location by treatment interactions (P < 0.05).

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Figure 8. Mean ± SE yield in experiments to reduce Cerotoma trifurcata abundance and BPMV incidence in 2002 (grey bars), 2003 (white bars), and 2004 (hatched bars). Data from central, northeast, and northwest combined (A), northeast and northwest combined (B), central (C, D), and northeast (E) Iowa. Yields were standardized to 13% moisture. Treatments (2002): C = Cruiser, P = Poncho, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Treatments (2003⎯2004): C = Cruiser, A = Asana, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Means grouped by the same lowercase letter are significantly different (P < 0.05). Data grouped by location based on significant location by treatment interactions (P < 0.05).

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Figure 9. Mean ± SE proportion mottled soybean seeds per 100 in experiments to reduce Cerotoma trifurcata abundance and BPMV incidence in 2002 (grey bars), 2003 (white bars), and 2004 (hatched bars). Data from central (A), northeast (B, D), and northwest (C), central and northwest combined (E) and central, northeast, and northwest Iowa combined (F). Treatments (2002): C = Cruiser, P = Poncho, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Treatments (2003⎯2004): C = Cruiser, A = Asana, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Treatment means based on one 100-seed count from each experimental unit. Means grouped by the same lowercase letter are significantly different (P < 0.05). Data grouped by location based on significant location by treatment interactions (P < 0.05).

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Figure 10. Mean ± SE 100-seed weight (g) of soybean seeds harvested from experiments to reduce Cerotoma trifurcata abundance and BPMV incidence in 2002 (grey bars), 2003 (white bars), and 2004 (hatched bars). Data from central and northwest combined (A), northeast (B, D), central (C) northwest (E) and central, northeast, and northwest Iowa combined (F). Treatments (2002): C = Cruiser, P = Poncho, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Treatments (2003⎯2004): C = Cruiser, A = Asana, W = Warrior, F0 = early-season population target, F1 = mid-season population target, check = untreated control. Means grouped by the same lowercase letter are significantly different (P < 0.05). Data grouped by location based on significant location by treatment interactions (P < 0.05).

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CHAPTER 6. GENERAL CONCLUSIONS

The objectives of this research were to understand the biology of BPMV and the bean

leaf beetle and to complement our current understanding of their biology and ecology to

facilitate their management. According to Southwood (1995) the direct measurement of plant

herbivory is probably the most meaningful measure of the effects of insects on plants. To

better understand the effects of digital measurements of herbivory we built on O’Neal et al.

(2002) and measured the contributing sources of error for digitally measuring an objects two-

dimensional size and shape. These measurements were needed for understanding the

accuracy and precision of leaf area measurement. Interestingly, using a digital scanner at its

highest capture resolution does not necessarily yield the most accurate and precise

measurement of two-dimensional area. This is particularly true as one progresses toward

larger surface areas. This may be due to the accumulation of small errors associated with

each pixel in the estimation of area as each pixel essentially represents a sample of area. Our

understanding of the effects of surface area and shape on leaf-measurement allowed us to

choose capture resolutions, with known measurement bias and error, for studies of leaf

herbivory.

The food plants of the Galerucinae (including the genera Diabrotica, and Cerotoma) are of particular importance to the North Central states, including the plant families

Cucurbitaceae, Fabaceae, and Poaceae (Jolivet and Verma 2002); However, the degree to which these host plants contribute to plant virus disease cycles is poorly known. This research indicates that the host range of the bean leaf beetle may be more specious than that for BPMV. In fact, the natural host range of BPMV may be very limited as only Glycine and

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Desmodium have been discovered as natural reservoirs of this virus Krell et al. (2003). Some beetle food hosts (e.g., kura clover, Trifolium ambiguum) could not be found infected with

BPMV even though they were acceptable, highly preferred hosts, and much feeding and evidence of feeding of this plant by bean leaf beetles was observed in nature. This is important because it leads to two interesting questions. First, can bean leaf beetles cleanse themselves of BPMV on BPMV non-host plants? Second, could such host plants that are also highly preferred by the bean leaf beetle be used as early-season trap crops (e.g., Newsom and

Herzog 1977)?

These host-range studies have confirmed that the native plant Desmodium illinoense is a food host of the bean leaf beetle (Waldbauer and Kogan 1976) and discovered a new native host, Lespedaza capitata. Even though these plants occupy nearly the same space and phenology, every D. illinoense was positive and every L. capitata was negative for BPMV in this prairie area. This again alludes to a potential for the bean leaf beetle to cleanse themselves of BPMV in nature. That is, even on uninfected soybean BPMV titers apparently deplete to non-transmissible amounts over time (Ghabrial and Shultz 1983). The interactions between bean leaf beetles, its hosts, and BPMV in the natural landscape deserves further study. However, importantly, D. illinoense was discovered as a host of BPMV in nature. This finding was confirmed by ELISA, Western immunoblot assay, and RT−PCR (using primers specific for RNA–1 of BPMV and universal for the known strains of BPMV).

This research describes a novel natural reassortant isolate of BPMV (called I-Di1).

The full nucleotide sequence of this isolate was characterized and identified to belong to subgroup I, RNA–1 and subgroup II, RNA–2. Very little is known about the distribution of plant viruses through the landscape and new initiatives have only just begun to explore

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viruses in natural systems (Wren et al. 2006). Less still is known about the epidemiology of

plant virus strains.

We sampled along a transect of soybean plants for BPMV with two objectives. First,

does isolate I-Di1 act as a local source of inoculum? Second, what is the distribution of

BPMV isolates across this landscape? We did not find any BPMV isolates that contained

RNA–1 that was related to I-Di1. On the contrary, all of the BPMV isolates sampled from

soybean were of subgroup 2, RNA–1. Interestingly we found a high nucleotide sequence

heterogeneity between the BPMV isolates collected from soybean. There was little apparent

spatial or temporal pattern of similarity between the isolates. However, hierarchical cluster

analysis indicated at least two origins of BPMV RNA–1 in this field. It may be that the origin

of BPMV isolate diversity within this field correlates with the immigration events of the bean

leaf beetle. Furthermore, the RNA–1 nucleotide fragment sequenced in this study was mostly

from the helicase (Hel) gene. The Hel gene of BPMV is a determinant, in part, of symptom

severity (Gu and Ghabrial 2005). This variability in a gene that is responsible for symptom

severity in soybean could be central to the challenge of developing a reliable management

program centered solely on the chemical suppression of vectors. This research will contribute

both to our fundamental understanding plant RNA viruses and to a better understanding of

the dynamics affecting management of disease.

The results from the management study indicate that the use of a foliar insecticide to

target F0 and F1 C. trifurcata may have numerically increased the AUAIC for some

insecticides, in some years relative to a seed treatment alone. However, only in 2002 did any treatment have a significantly lower AUAIC relative to an untreated control. Furthermore, in this year all treatments had a numerically lower AUAIC than the untreated control. As

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reported by Perring et al. (1999), some externally−borne viruses can increase in incidence in

response to some insecticides. Furthermore, Pederson et al. (2007) reported an increase in

BPMV incidence with the use of foliar insecticides timed to suppress soybean aphid, Aphis

glycines Matsumura, abundance. In this study there was no statistically significant increase in

virus incidence with the use of insecticides applied to suppress C. trifurcata abundance.

However, these results support Krell et al. (2004) that F0-targeted insecticides can

suppress F1 populations and that the success of an F1-targeted insecticide strongly depends on

the seasonal dynamics of bean leaf beetles. That is, during years of high beetle abundance the

onset of a large F1 vector population may be difficult to manage by insecticidal control alone.

Yield was most improved if both F0 and F1 populations of C. trifurcata were targeted.

Economic injury from all pests is probably not mutually exclusive and reductions in insect

and viral pests may simultaneously affect soybean yield.

Grain quality is an important factor in the value of soybean grown for export (USDA

2006). This study supports the findings of Krell et al. (2004) that a F0- plus F1-targeted

insecticide strategy (using lambda-cyhalothrin for both applications) may keep grain within acceptable quality standards. Although, seed-coat color is regulated by a family of genes

(Takahashi and Abe 1999, Senda et al. 2002, Senda et al. 2004), some of which are affected

by the environment, our research concerning the within-field variability of the Hel gene

indicates yet another level of underappreciated complexity.

This research indicates a yield gain in soybean with the use of an F0 plus F1-targeted insecticide application strategy against bean leaf beetles. Furthermore, yield is improved when a seed-applied insecticide is used as the F0-targeted insecticide. However, these yield

benefits may be offset under some situations with poorly-colored grain when a seed-applied

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insecticide is used. Because the success of this management program depends on the seasonal

dynamics of C. trifurcata, caution should be taken in its recommendation. Further research

should further exploit and discover mechanisms of resistance to C. trifucata and BPMV to

find a more consistent and reliable management tool.

Literature Cited

Ghabrial, S. A. and F. J. Schultz. 1983. Serological detection of bean pod mottle virus in bean leaf beetles. Phytopathology 73: 480-483.

Gu, H. C. and S. A. Ghabrial. 2005. The Bean pod mottle virus proteinase cofactor and putative helicase are symptom severity determinants. Virology 333: 271-283.

Jolivet, P. and K. K. Verma. 2002. Food and feeding, Ch. 4. In Biology of leaf beetles.

Intercept Ltd. Andover, United Kingdom.

Krell, R. K., L. P. Pedigo, J. H. Hill, and M. E. Rice. 2003. Potential primary inoculum

sources of Bean pod mottle virus in Iowa. Plant Disease 87: 1416-1422.

Krell, R. K., L. P. Pedigo, J. H. Hill, and M. E. Rice. 2004. Bean leaf beetle (Coleoptera :

Chrysomelidae) management for reduction of bean pod mottle virus. Journal of Economic

Entomology 97: 192-202.

Newsom, L. D. and D. C. Herzog. 1977. Trap crops for control of soybean pests. Louisiana

Agriculture 20: 14-15.

O'Neal, M.E., D.A. Landis, and R. Isaacs. 2002. An inexpensive, accurate method for

measuring leaf area and defoliation through digital image analysis. Journal of Economic

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Pedersen, P., C. R. Grau, E. M. Cullen, N. C. Koval, and J. H Hill. 2007. Potential for

integrated management of soybean virus disease. Plant Disease In press.

Perring, T. M., N. M. Gruenhagen, and C. A. Farrar. 1999. Management of plant viral

diseases through chemical control of insect vectors. Annual Review of Entomology 44: 457-

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Senda, M., A. Jumonji, S. Yumoto, R. Ishikawa, T. Harada, M. Niizeki, and S. Akada.

2002. Analysis of the duplicated CHS1 gene related to the suppression of the seed coat pigmentation in yellow soybeans. Theoretical and Applied Genetics 104: 1086-1091.

Senda, M. C. Masuta, S. Ohnishi, K. Goto, A. Kasai, T. Sano, J-S. Hong, and S.

MacFarlane. 2004. Patterning of virus-infected Glycine max seed coat is associated with

suppression of endogenous silencing of chalcone synthase genes. The Plant Cell. 16:

807−818.

Southwood. T. R. E. 1995. Estimates based on products and effects of insects, Ch. 8. In

Ecological methods with particular reference to the study of insect populations, 2nd ed.

Champman and Hall, London, United Kingdom.

Takahashi, R. and J. Abe. 1999. Soybean maturity genes associated with seed coat

pigmentation and cracking in response to low temperatures. Crop Science 39: 1657-1662.

[USDA] United States Department of Agriculture, Grain Inspection, Packers &

Stockyards Administration. 2006. United States standards for soybeans. Federal

Waldbauer, G. P., and M. Kogan. 1976. Bean leaf beetle: Phenological relationship with

soybean in Illinois. Environmental Entomology 5: 35-44.

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ACKNOWLEDGMENTS

There are many individuals who have contributed to the successful completion of this

research. Contributions have been made in many ways, some obvious and some more

indirect. The following individuals receive my sincerest thanks!

Professor Marlin Rice, as my entomological co-advisor, has lent me his time and

resources and afforded me many, many broadly applicable opportunities. He has been an

exceptional role model for my education in extension entomology, supportive research, and

grant writing. I also appreciate the international opportunities he has given me. These

experiences have enriched my life deeply.

Professor John Hill, as my phytopathological co-advisor, has lent me his time, laboratory resources, financial support, and his molecular insights. He has been a source of encouragement and aided in my confidence to explore areas of research that continue to

expand my experience well beyond my academic background. I will endeavor to make

virology a part of my long-term research goals.

Professors, Gary Munkvold, Dan Nettleton, Matt O’Neal, and Larry Pedigo have

provided me with their time in reviewing this document and their guidance by serving on my

graduate committee. I especially appreciate Professor Nettleton’s time and statistical

expertise.

Although not entirely germane to this document I additionally thank Professor Larry

Pedigo for extending an invitation to me to join him in High Society Big Band. Music has

always been an important part of my life and the opportunity to play regularly in a large jazz

ensemble has been a highlight of my extracurricular activities at Iowa State.

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Professor Jon Tollefson gave his valuable insights and suggestions for the initial proposal of study.

Many employees performed their duties exceptionally well and include: Sharon

Burkhalter, Lindsey Gereszek, Michelle Hsu, Anna Mortvedt, Colin Parrott, Trevor Plett,

Brad Pottebaum, John Schomberg, Yeow Seng, Meghan Smith, Justin Strohman, Lu

Weiting, and Sam Xu. I especially thank Michelle Hsu and Yeow Seng for their infectious task-oriented methodology.

Tera Nyholm and Katie Bradshaw helped me coat, block, aspirate, and “bang out”

>1,020 96-well ELISA plates.

David Haden, Ken Pecinovski, and Dave Starrett provided valuable field management expertise and operations.

I thank Clara Alarcon and all her laboratory employees at Pioneer/DuPont for tolerating my intrusion into their lab space. A special thanks to Ben Jayne who served as my contact for operating the robots in the robotics lab at Pioneer/DuPont. Thanks to Thomas

Doerge for expediting the funding provided by and allocation of resources for Pioneer’s assistance with our project. Pioneer/DuPont helped to make my ELISA samples much more manageable.

Special thanks to Adrian Moses, Syngenta, for expediting the insecticidal treatment of seeds for our management study.

Many insightful conversations and advice was provided by Drs. Al Eggenberger,

Reza Hajimorad, and Chunquan “Chris” Zhang. I especially thank Al for selflessly donating his time to instruct me in various molecular techniques.

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Thanks to Dave Dorhout for being a jovial officemate and for offering solicited opinions.

Dr. Rayda Krell offered much initial insight and assistance at the start of this project.

Thank you!

Dr. Royce Bitzer provided his insights and suggestions regarding the presentation of

results and the interpretation of matters of ecological importance.

Special thanks to Rich Pope who gave his time to help me locate potential host plants

for BPMV. Additionally, I have much gratitude for his keen observation of the patches of

Desomodium illinoense from which the new BPMV isolate was extracted. For me this serendipitous discovery has been a highlight of my graduate research.

Also the Departments of Entomology and Plant Pathology have given their support of my pursuit of a co-major in their respective disciplines.

John VanDyk provided valuable technical assistance and sympathy when my Seagate harddrive (Seagate LLC.) critically and irreversibly failed while containing much precious data.

A very special thanks to Don and Vicki Bradshaw for years of support, for encouraging me to pursue my interests, and for allowing a little boy to play with bugs. I also owe Pauline and Ernest Smith Sr. my gratitude, in memoriam, for their deep love and encouragement of my academic pursuit.

I especially thank Katie Bradshaw for her patience, encouragement, and support throughout my graduate career.