studies on the behavior and ecology of drosophila …
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STUDIES ON THE BEHAVIOR AND ECOLOGY OF DROSOPHILA SUZUKII (DIPTERA: DROSOPHILIDAE) AND DEVELOPMENT OF IPM STRATEGIES IN
BERRY CROPS
By
LINDSY IGLESIAS
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2018
© 2018 Lindsy Iglesias
To Sean for his support, patience, and laughter throughout this adventure. To my dad for being proud of me always and pushing me towards my goals.
To my mom for making me a strong, dedicated woman.
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ACKNOWLEDGEMENTS
First and foremost, I would like to thank my major advisor, Dr. Oscar Liburd, for
his unwavering support and patience throughout my program. He has been dedicated to
my career goals and taught me invaluable research and professional skills. I feel
fortunate to have had the opportunity to work with him. He is a great mentor and has
become a lifelong colleague and friend. I thank my committee members, Lukasz
Stelinski, Sabine Grunwald, and Xin Zhao for their guidance throughout the research
process and suggestions for my dissertation.
I especially want to thank the members of the UF Fruit and Vegetable IPM Lab
for volunteering their time to assist with field work and sample processing, and for
emotional and professional support – Janine Spies, Bria Biltch, Elena Rhodes, and
Chris Crockett, in particular – and lab members come and gone, Amrit Chhetri, Mary
Diaz, and Nii Soja Torto. I would also like to thank James Colee for his statistical
guidance.
I would like thank the various groups that have been gracious enough to help
fund my program – the University of Florida Entomology and Nematology Department
for funding my doctoral program; the USDA-NIFA Organic Research and Extension
Initiative (OREI), IR-4 Project, Florida Blueberry Growers Association, Florida
Department of Agriculture and Consumer Services, and Southern SARE for research
funding; and the industries who provided the pesticides for my experiments, Dow
AgroSciences, Valent/MGK, Rockwell Labs Ltd., Marrone Bio Innovations, and BioSafe
Systems. I also want to thank all of the growers who allowed me to work on their farms.
Finally, I would like to thank from the bottom of my heart, my family and friends. I
would not be here without you.
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TABLE OF CONTENTS
page
ACKNOWLEDGEMENTS ................................................................................................... 4
LIST OF TABLES ................................................................................................................ 8
LIST OF FIGURES ............................................................................................................ 10
ABSTRACT ........................................................................................................................ 13
CHAPTER
1 INTRODUCTION ........................................................................................................ 15
Blueberry Production .................................................................................................. 15 Blackberry Production ................................................................................................. 17 Pests of Blueberry and Blackberry ............................................................................. 19
2 LITERATURE REVIEW .............................................................................................. 21
Drosophila suzukii (Matsumura) ................................................................................. 21 Identification and Biology ..................................................................................... 21 Pest Status and Injury .......................................................................................... 25 Behavior and Ecology .......................................................................................... 26
Monitoring and Management ...................................................................................... 27 Monitoring ............................................................................................................. 28 Cultural Control .................................................................................................... 30 Biological Control ................................................................................................. 30 Chemical Control .................................................................................................. 32
Justification ................................................................................................................. 33 Objectives.................................................................................................................... 35
3 BLUEBERRY TYPE AND CULTIVAR SUSCEPTIBILITY TO DROSOPHILA SUZUKII OVIPOSITION ............................................................................................. 36
Materials and Methods ............................................................................................... 39 Fly Source Materials for All Studies ..................................................................... 39 Blueberry Source Material ................................................................................... 39 No-Choice Bioassays ........................................................................................... 40 Choice Bioassays ................................................................................................. 40 Berry Characteristics ............................................................................................ 41 Statistical Analysis................................................................................................ 42
Results ........................................................................................................................ 44 Oviposition ............................................................................................................ 44 Survival and Sex Ratio ......................................................................................... 44
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Berry Characteristics and Host Use .................................................................... 45 Discussion ................................................................................................................... 47
4 SPATIO-TEMPORAL DISTRIBUTION OF DROSOPHILA SUZUKII ........................ 60
Materials and Methods ............................................................................................... 64 Experimental Site ................................................................................................. 64 Sampling ............................................................................................................... 65 Data Analysis........................................................................................................ 67
Results ........................................................................................................................ 69 Adult D. suzukii Captures ..................................................................................... 69 Berry Infestation ................................................................................................... 70 Population Distribution of D. suzukii .................................................................... 70 Non-Crop Host Identification ................................................................................ 71
Discussion ................................................................................................................... 72
5 CULTURAL CONTROL AND ALTERNATIVE SPRAY TECHNIQUES FOR DROSOPHILA SUZUKII MANAGEMENT ................................................................. 88
Materials and Methods ............................................................................................... 90 Field Setup ........................................................................................................... 90 Insecticide Applications ........................................................................................ 91 Soil Tillage ............................................................................................................ 92 Sampling ............................................................................................................... 92 Data Analysis........................................................................................................ 94
Results ........................................................................................................................ 94 Discussion ................................................................................................................... 96
6 IDENTIFICATION OF BIORATIONAL INSECTICIDES FOR CONTROL OF DROSOPHILA SUZUKII ...........................................................................................106
Materials and Methods .............................................................................................107 Insecticide Treatments .......................................................................................107 Fruit Dip Bioassays ............................................................................................108 Semi-Field Bioassays .........................................................................................108 Field Trials ..........................................................................................................110 Data Analysis......................................................................................................111
Results ......................................................................................................................113 Fruit Dip Bioassays ............................................................................................113 Semi-Field Bioassays .........................................................................................113 Field Trials ..........................................................................................................114
Blueberries ...................................................................................................114 Blackberries .................................................................................................115
Discussion .................................................................................................................117
7 CONCLUSIONS ........................................................................................................138
LIST OF REFERENCES .................................................................................................140
7
BIOGRAPHICAL SKETCH ..............................................................................................160
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LIST OF TABLES
Table page 3-1 Cultivars of southern highbush and rabbiteye blueberries and the location
from which the samples were taken. ..................................................................... 52
3-2 Mean (±SE) eggs laid, adults emerged, and proportion of eggs surviving to the adult stage in rabbiteye and southern highbush blueberry cultivars in no-choice oviposition assays. ...................................................................................... 52
3-3 Mean (±SE) proportions of eggs laid, adults emerged, and eggs surviving to the adult stage in rabbiteye and southern highbush blueberry cultivars in choice oviposition assays. ...................................................................................... 53
3-4 Sex ratio of D. suzukii adults that emerged from different cultivars of rabbiteye and southern highbush blueberry types in no-choice assays. .............. 54
3-5 Sex ratio of D. suzukii adults that emerged from different cultivars of rabbiteye and southern highbush blueberry types in choice assays. ................... 54
3-6 Mean (±SE) berry characteristics of several rabbiteye and southern highbush blueberry cultivars. ................................................................................................. 55
3-7 Spearman’s correlation coefficients (ρ) and significance values (P) for several berry characteristics and eggs laid, adult emergence and eggs survival rates from laboratory assays in rabbiteye and southern highbush blueberries. ............................................................................................................. 56
4-1 Results of the generalized linear mixed model ANOVAs testing for significance of cultivar, date, cultivar*date interaction, and distance effects for adult D. suzukii capture data in 2016 and 2017. ................................................... 78
4-2 Results of the generalized linear mixed model ANOVAs testing for significance of cultivar, date, cultivar*date, and distance effects for berry samples processed using the salt extraction and incubation methods in 2017. .. 78
4-3 Emerged adults (mean ± standard error) collected from ripe blueberry samples using the incubation method in the 2017 D. suzukii movement study in organic blueberries. ............................................................................................ 79
4-4 Plant species identified in the woods and non-woods margins of the organic blueberry field in the D. suzukii movement study. All plants bare thin-skinned fruits at various times of the year. .......................................................................... 80
5-1 Mean (±SE) female and male adult SWD captured in 2014 and 2015 blackberry studies.................................................................................................100
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5-2 Mean (±SE) arthropods identified on yellow sticky card traps during final week of the 2015 blackberry study. .....................................................................101
6-1 Biorational insecticides treatments for the laboratory fruit dip bioassays and field trial in blackberries ........................................................................................122
6-2 Biorational insecticides treatments used in the semi-field bioassays and field trial in blueberries. ................................................................................................123
6-3 Sex ratio of D. suzukii adults that died from exposure to blackberries dipped is several different biorational insecticides. .........................................................123
6-4 Sex ratio of D. suzukii adults that died from exposure to field blueberries sprayed with several different biorational insecticides in the semi-field bioassays. .............................................................................................................124
6-5 Mean (± SE) number of natural enemies captured on yellow sticky card traps in blueberry field trials. .........................................................................................125
6-6 Mean (± SE) number of natural enemies captured on yellow sticky card traps in blackberry field trials. ........................................................................................127
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LIST OF FIGURES
Figure page 3-1 No-choice bioassay arena with a single blueberry and sugar-water solution in
vial. Photo courtesy of author. ............................................................................... 57
3-2 Bioassay arena used for D. suzukii choice assays. Groups of 10 blueberries of six cultivars of rabbiteye or southern highbush types were secured equidistant from the top of the arena. Photo courtesy of author. .......................... 57
3-3 Discriminant analysis of rabbiteye (gray circles) and southern highbush (black circles) cultivars using berry characteristics (Volume = berry volume, Pen Force = skin penetration force, SSC = soluble solids content). .................... 58
3-4 Linear relationship between the proportion survival and the corresponding skin penetration force of several rabbiteye (gray symbols) and southern highbush (black symbols) blueberry cultivars. ....................................................... 59
4-1 Drosophila suzukii distribution study experimental site at an organic blueberry farm in Citrus County, FL. Circles represent trap locations. Red circles at trap locations are where berry samples are collected. .......................... 81
4-2 Mean number of adult D. suzukii captured in several blueberry cultivars and unmanaged field margins in 2016. * Indicates significant differences among the cultivars in the corresponding week with Tukey Kramer at P ≤ 0.05. ............. 82
4-3 The mean number of adult D. suzukii flies captured in several blueberry cultivars and unmanaged field margins in 2017. ................................................... 82
4-4 Linear relationship between the number of adult D. suzukii captured and the corresponding sample location based on the distance from the center of the blueberry field. ........................................................................................................ 83
4-5 Linear relationship between adult D. suzukii emerged from infested fruit using the incubation method and sample location based on distance from the center of the blueberry field.................................................................................... 84
4-6 Linear relationship between extraction D. suzukii larvae from infested fruit using the salt method and sample location based on distance from the center of the blueberry field. .............................................................................................. 84
4-7 The mean number of D. suzukii extracted from infestation blueberry samples in 2017 using the incubation and salt extraction methods. Bars with different letters indicate significant differences (P ≤ 0.05). .................................................. 85
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4-8 Red-blue plots showing population distribution of adult D. suzukii flies captured in Scentry traps in organic blueberries in 2016. Beginning from left to right are sampling weeks 1 through 3. ............................................................... 86
4-9 Red-blue plots showing population distribution of adult D. suzukii flies captured in Scentry traps in organic blueberries in 2017. Beginning from top left are sampling weeks 1 through 7. ..................................................................... 87
5-1 A single experimental plot layout for the border spray and soil tillage study. .....102
5-2 The mean number of SWD captured by treatment in 2014. Bars with the same letters are not significantly different using Tukey’s HSD (P ≤ 0.05)..........103
5-3 The mean number of SWD captured per trap in 2015. Asterisk (*) indicates significant differences for that week (P ≤ 0.05). ..................................................104
6-1 Average daily temperature (°C) and total daily precipitation (cm) for the duration of the semi-field efficacy trial in blueberries. Black diamonds denote spray applications and circles are when blueberries were collected. .................129
6-2 Average daily temperatures (°C) and precipitation (cm) for the duration of the B) blueberry and B) blackberry field efficacy trials. Black diamonds denote spray applications. ................................................................................................130
6-3 Percent mortality of D. suzukii flies after 72-h exposure to single blackberries dipped in different biorational insecticides. A) Fly mortality after exposure on berries 0 days after treatment (DAT), B) 1 DAT, and C) 3 DAT. ........................131
6-4 The mean number of D. suzukii adults emerged from blackberries dipped in different biorational insecticide treatments. Bars with different letters indicate significant differences with Tukey’s HSD at P ≤ 0.05. .........................................132
6-5 Percent mortality of D. suzukii flies after 72-h exposure to field blueberries sprayed with different biorational insecticides. A) Fly mortality after exposure on berries 1 days after treatment (DAT), B) 4 DAT, and C) 7 DAT. ...................133
6-6 Percent of sub-lethal effects of D. suzukii flies after 72-h exposure to field blueberries sprayed with biorational insecticides. A) Fly mortality after exposure on berries 1 day after treatment (DAT), B) 4 DAT, and C) 7 DAT. .....134
6-7 The number of emerged adults after 72-h exposure to field blueberries sprayed with different biorational insecticides. Bars with different letters are significantly different at α = 0.50 (Tukey’s HSD). ................................................135
6-8 Mean ± SE (standard error) of adult D. suzukii captured per trap in 12 different biopesticide treatments in organic blueberries. Asterisk (*) indicates differences within the treatments for that week (P ≤ 0.05). .................................136
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6-9 Mean ± SE percent infested berries by D. suzukii in 12 different biopesticide treatments in organic blueberries. Asterisk (*) indicates differences within the treatments for that week (P ≤ 0.05). ....................................................................136
6-10 Mean ± SE (standard error) of adult D. suzukii captured per trap in 9 different biopesticide treatments in conventional blackberries. Asterisk (*) indicates differences within the treatments for that week (P ≤ 0.05). .................................137
6-11 Mean and quantiles number of emerged D. suzukii per kilogram in 9 different biopesticide treatments in conventional blackberries. .........................................137
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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
STUDIES ON THE BEHAVIOR AND ECOLOGY OF DROSOPHILA SUZUKII
(DIPTERA: DROSOPHILIDAE) AND DEVELOPMENT OF IPM STRATEGIES IN BERRY CROPS
By
Lindsy Iglesias
May 2018
Chair: Oscar E. Liburd Major: Entomology and Nematology
Drosophila suzukii (Matsumura) is an invasive pest of thin-skinned fruits that
causes severe economic losses. Management of D. suzukii is challenging because of
its short life cycle, wide host range, and its preference for ripening fruit. Current
management programs employ applications of broad-spectrum insecticides, sanitation,
and frequent harvest intervals. The goal of this dissertation research was to study host
fruit oviposition behavior and farmscape distribution of D. suzukii to develop IPM
strategies in small fruit crops. First, we examined how fruit characteristics influenced
host fruit susceptibility to D. suzukii. Berry size, skin penetration force, and soluble
solids were measured for 6 southern highbush and 4 rabbiteye blueberry cultivars.
Oviposition behavior was evaluated in no-choice and choice assays. Larval survival
decreased as skin penetration force increased. Second, we investigated the distribution
of D. suzukii on an organic blueberry orchard and the field margins using Spatial
Analysis using Distance IndicEs (SADIE). Drosophila suzukii adults and berry
infestation were higher closer to the edges of the field. Adults were found in the field
margins all season. Third, we evaluated the effect of between-row tillage and border
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sprays as alternative control tactics for D. suzukii. Border sprays reduced adult flies and
larval infestation significantly below the control. The addition of soil tillage reduced D.
suzukii numbers further but was not significant. Natural enemies were not affected.
Finally, we evaluated the efficacy of biorational insecticides for D. suzukii management
in lab, semi-field, and field studies on blueberries and blackberries. New effective tools
(insecticides) that were identified included, Chromobacterium substugae and sabadilla
alkaloids.
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CHAPTER 1 INTRODUCTION
Blueberry Production
Blueberry production in Florida can be considered small with just 1,902 ha
dedicated to the crop (USDA-NASS 2018). However, the industry, valued at 82.1 mil
USD in 2015, is growing rapidly with an increase from 8.2 to 11.5 mill kg in 2012 and
2015, respectively (NASS-USDA 2018). The high value of Florida’s blueberries is driven
mainly by the early production of fresh blueberries from March through May for
commercial production, as the Chilean industry, the second largest producer of fresh
blueberries in the world, begins to decline (FAO-STAT 2014). The average price per
kilogram of blueberries was 7.30 USD kg-1 in 2015, the highest in the U.S. (NASS-
USDA 2018). The three major blueberry production regions in Florida are the North
Central, which includes Alachua, Marion, Putnam, Sumter, and Lake counties (40% of
area), the South Central, which includes Highlands, Hardee, Desoto, Manatee, and
Sarasota counties (20% of area), and the Central region, which includes Polk, Orange,
Pasco, Hernando, and Hillsborough counties (35% of area) (Williamson et al. 1997).
Organic production of blueberries in Florida has almost doubled since 2011.
Florida growers produced 306,000 kg of organic blueberries on 87 ha and 500,000 kg
on 155 ha in 2011 and 2015, respectively (NASS-USDA 2018). Florida’s organic market
was worth 6.4 mil USD in 2015 (NASS-USDA 2018). In terms of area grown, Florida is
number six in the U.S. but is ranked fourth in sales due to the high prices received
during Florida’s early production season (NASS-USDA 2018).
The blueberry industry in Florida began in the 1950s with the production of the
native rabbiteye blueberry (Vaccinium virgatum Reade), which is tolerant to drought and
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soils with low organic matter (Braswell 2006, Lyrene and Ballington 2006). Blueberry
growers in Florida began to shift to the southern highbush blueberry (V. corymbosum
Linneaus x V. darrowii Camp) in the 1970s (Braswell 2006), which currently makes up
over 80 percent of blueberries grown in the state. Farms of rabbiteye blueberries are
typically small pick-your-own fruit operations in northern Florida (England 2014).
Southern highbush is a complex hybrid of northern highbush (V. corymbosum), a
lowbush evergreen species native to Florida (V. darrowii), and sometimes rabbiteye
blueberries (Lyrene and Ballington 2006), resulting in a species with high fruit quality
that requires fewer chill hours to break winter dormancy (Darnell 2006, Strick 2006).
Southern highbush flower later than rabbiteye but have a shorter fruit development
period of 55 to 60 days (Darnell 2006). Therefore, early ripening cultivars of southern
highbush may be harvested in March, approximately one to two months earlier than
rabbiteye (Braswell 2006), making Florida southern highbush the first U.S. blueberries
to reach the global market. In Florida, the blueberry harvest season ends around May
and July for southern highbush and rabbiteye berries, respectively.
Blueberries are typically grown in single or double rows, with rows approximately
0.6-1.2 m and 1.2-1.8 m apart for southern highbush and rabbiteye, respectively
(Williamson et al. 2006). Most blueberry growers plant multiple cultivars of blueberries
either in blocks or alternating single or multiple rows. The mixed-cultivar system allows
for improved cross-pollination and a longer harvest season using early-, mid-, and late-
season cultivars (Gough 1994). Beds are raised to increase the depth to the water table
and provide ample drainage for the shallow, fibrous root system of the blueberry bushes
(Darnell 2006, Williamson et al. 2006). Blueberries thrive in well-drained, slightly acidic
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soils (4.2-5.2 pH) with at least 2 and 3% organic matter for rabbiteye and southern
highbush, respectively (Bowling 2005, Williamson et al. 2006). Pine bark is used as a
soil amendment or mulch and provides increased moisture retention and organic matter,
weed management and helps maintain soil pH (Williamson et al. 2006). Many blueberry
growers in the southeastern U.S. use a production system called “pine bark culture”
where the bushes are planted directly into beds built of large amounts of pine bark,
rather than directly into soil (Williamson et al. 2006). Synthetic weed fabric may also be
used for weed management and to prevent pine bark from floating away in flood
conditions. Blueberry plantings are fitted with drip irrigation systems to provide water
directly to the root system of the plants. Overhead irrigation is used to protect the
bushes against frost injury during the winter months in most production areas in Florida
(Williamson and Crane 2010)
Blackberry Production
Prior to the 1990s, the U.S. blackberry industry was limited to pick-your-own
operations, local market sales, and processing (Clark 2005). In the late 1990s, cultivars
began to emerge that had firm fruit necessary for packing and shipping beyond local
markets and even across country borders (Clark 2005, Strik et al. 2007). Since then, the
U.S. market has increased its production and in 2016, the U.S. industry was worth 26.4
mil USD and produced 58.3 mil kg on 7,000 ha (FAO-STAT 2017). The main producers
of blackberries in the U.S. are the Pacific Northwest, Michigan, and Arkansas (Anderson
and Crocker 2014); however, with increased customer demand and new cultivars being
developed to tolerate the climatic conditions of the southeastern U.S., production in this
region has more than doubled since 2007 (NASS-USDA 2018). Blackberry production in
Florida is mostly limited to areas in North Central and North Florida, where 124 ha of
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blackberries were grown in 2012 (NASS-USDA 2018). Since 2012, blackberry
production in Florida has become almost 100% organic; growers can receive higher
prices for their product to help recoup costs of management. Organic blackberry
production in Florida tripled from 2011 to 2015, when 24,000 kg and 71,000 kg were
produced, respectively (NASS-USDA 2018).
Blackberries (Rubus spp.) are deciduous woody shrubs with perennial fibrous
roots and biennial stems (canes). During the first year of growth, blackberry grows
primocanes, vegetative shoots that do not produce fruit. The following year, fruit is
produced on canes that were formed the year before which are called floricanes.
Floricanes are usually pruned from the plant after they have produced fruit. Primocane-
fruiting cultivars produce fruit in the first year of growth (Strik et al. 2007). In Florida,
erect blackberry cultivars are typically grown whereby stiff upright primocanes are
produced from the roots or the base of the floricanes, resulting in plants that require less
trellising and tying (Strik et al. 2007, Fernandez et al. 2016). Like blueberries,
blackberries require a certain number of chill hours to break bud dormancy in the winter
months. Cultivars with low chill requirements, such as ‘Arapaho’, ‘Natchez’, and
‘Ouichata’ (Anderson and Crocker 2001), have been successful in Florida. Thornless
cultivars have become popular due to their ease of management (pruning, harvesting)
(Anderson and Crocker 2001, Clark 2005).
In Florida, blackberries are generally planted in single raised beds with well-
drained, slightly acidic soil (5.5-6.5 pH) (Anderson and Crocker 2001). Plants are
planted 0.8-1.2 m apart and trellised using a “V” system with wires on which to secure
canes, which allows for air flow within the canopy and easier harvesting (Strik et al.
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2007, Fernandez et al. 2016). Beds are sometimes mulched with synthetic feed fabric to
reduce weed pressure. Drip irrigation is used to provide water directly to the shallow
root system and prevent excess moisture on blackberry foliage that can lead to disease
(Anderson and Crocker 2001). The harvest season of many blackberry cultivars is
approximately 3-4 weeks in May and June and fruit are harvested by hand (Anderson
and Crocker 2001). Many growers have stands of multiple cultivars with different
ripening dates to increase the length of harvest.
Pests of Blueberry and Blackberry
Blueberry is a deciduous crop and therefore, arthropod pests require
management throughout the year. The blueberry gall midge, Dasineura oxycoccana
(Johnson), is an early season pest that feeds in developing leaf and flower buds,
causing serious bud loss in rabbiteye. Recently, vegetative bud loss has increased in
southern highbush (Sarzynski and Liburd 2003, Liburd et al. 2013). Florida flower thrips,
Frankliniella bispinosa (Morgan), feed on and oviposit in the developing flowers,
reducing the quantity and quality of the fruit (Arévalo-Rodriguez 2006, Arévalo and
Liburd 2007, Williamson et al. 2013). During the post-harvest season, chilli thrips,
Scirtothrips dorsalis Hood, can feed on the meristems of the blueberry shoots and
leaves, causing injury to the leaves, buds, flowers and young fruits (Kumar et al. 2010).
Blueberry bud mite, Acalitus vaccini (Keifer), spends its entire life feeding and
reproducing in the developing flower bud, resulting in hardened, rosetted buds and
scarred or reduced fruit set (Weibelzahl and Liburd 2009, 2010). Since the invasion by
the spotted wing drosophila, Drosophila suzukii (Matsumura), many blueberry growers
who could manage common pests with selective insecticides and cultural controls, have
switched to calendar spray programs consisting mostly of broad-spectrum insecticides.
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Several insect pests may attack blackberries in the southeastern U.S., but flower
thrips (Frankliniella spp.) and stink bugs (Hemiptera: Pentatomidae) appear to be the
most problematic in Florida. The Florida flower thrips, F. bispinosa, the most common
thrips species in Florida, feeds on ovaries, styles, petals and developing fruit, resulting
in reduced quality and quantity of fruit (Arévalo-Rodriguez 2006, Liburd et al. 2014).
Stink bugs, including the southern green stink bug, Nezara viridula (Linnaeus); green
stink bug, Chinavia hilaris (Say); and Euschistus spp., have been reported to feed on
individual fruit drupelets, causing discolored, malformed fruit with an unwanted “stink
bug taste” (Johnson and Lewis 2005, Brennan et al. 2013). Other pests in Florida
include twospotted spider mites (Tetranychus urticae Koch) and rednecked cane borer
(Agrilus ruficollis). Some secondary pests include raspberry crown borer (Pennisetia
marginata), strawberry weevil (Anthonomus signatus), sap beetles (Nitidulidae), and gall
midges (Dasineura spp.) (Johnson and Lewis 2005, Anderson and Crocker 2014).
Similar to blueberries, the invasion by D. suzukii, has forced growers to increase the
number of insecticide applications in order to manage this new pest.
The overall goal of this project is to study the behavior and ecology of Drosophila
suzukii and to develop integrated pest management strategies in berry crops. This pest
has spread rapidly to most berry-growing regions and has caused severe economic
losses. Pest management programs rely mostly on sanitation and broad-spectrum
insecticide applications, with the latter having potential negative effects on non-target
organisms. Understanding the biology and ecology of this may help to develop tactics
that better target D. suzukii behavior and its populations in the field.
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CHAPTER 2 LITERATURE REVIEW
Drosophila suzukii (Matsumura)
Identification and Biology
Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) belongs to the D.
melanogaster species group within the subgenus Sophophora (Bock and Wheeler
1972) and looks similar to other drosophilids. Adult D. suzukii are small (2-4 mm) yellow
to brown flies with large red eyes. The abdominal tergites have unbroken dark bands
along the mid-dorsal line, characteristic of Sophophora (Markow and O’Grady 2006).
The wings of male flies have a single dark spot at the distal end of the R2+3 wing vein.
The wing spot however, may not be fully develop in teneral males and a small
proportion of fully-developed males may lack the spot completely (Hauser 2011).
Identification of D. suzukii males should be confirmed by the presence of sex combs on
the forelegs, a feature characteristic of males in the melanogaster and obscura species
groups (Markow and O’Grady 2006). Drosophila suzukii males possess a pair of
ventrally-facing sex combs located on the first and second tarsal segments of the
forelegs (Hauser 2011). A close wing-spot-bearing relative of D. suzukii, D. biarmipes,
also possesses two sex combs, but they are both located on the first tarsal segment
(Hauser 2011). Female D. suzukii do not possess the wing spots but can be identified
by the shape and structure of the ovipositor. Unlike most drosophilid flies, which oviposit
and feed on overripe or decaying fruit or plant material, D. suzukii are capable of
puncturing the surface of ripe, undamaged fruit in order to lay eggs. The ovipositor of
female D. suzukii has enlarged bristles on the distal tip of the ovipositor which help to
saw into fruit skin (Atallah et al. 2014). Drosophila suzukii also has a much larger and
22
more pointed ovipositor than other relatives D. biarmipes and D. mimetica (Atallah et al.
2014). Although the close relative D. subpulchrella (Takamori et al. 2006) also possess
well-defined bristles, this species has a wider, more blunt ovipositor that prevents it from
penetrating fruits with thicker skin (Atallah et al. 2014).
Currently, D. suzukii cannot be distinguished from other drosophilids by its
immature stages because the morphology is very similar to other drosophilids. Kanzawa
(1939) described the immature stages of D. suzukii. The eggs of D. suzukii are white,
oblong and approximately 0.5 mm by 0.2 mm long. There are two respiratory spiracles
at the distal end of the egg that protrude from the oviposition substrate (fruit) and allow
for gas exchange. Drosophila suzukii larvae are white and taper at both ends, and have
black, hooked mouthparts. The larval instars can be distinguished from each other using
the shape and number of teeth on the mouth hooks (mandibles) and the development of
the anterior spiracles (Van Timmeren et al. 2017). The pupae range from light to dark
brown as they develop and have spiked and caudal spiracles located at the anterior and
posterior ends, respectively. Just prior to eclosion, the red eyes and wing pads of the
adult fly can be seen through the pupal case. Most larvae will leave the fruit and drop to
the soil to pupate at shallow depths; however, some larvae will pupate inside or partially
inside the fruit (Renkema and Devkota 2017, Woltz and Lee 2017).
Drosophila suzukii has a short life cycle and can produce several generations in
a single season (Kanzawa 1939, Walsh et al. 2011). Estimates on full development time
(egg-adult) are highly dependent on temperature, humidity, and substrate. The reported
optimal temperature for D. suzukii development is ~22.0 °C (Kanzawa 1939, Walsh et
al. 2011, Tochen et al. 2014). At the optimal temperature one study reported
23
development time to be ~14.0 d in cherries and blueberries (Tochen et al. 2014),
whereas another reported ~12.8 d on artificial diet (Emiljanowicz et al. 2014). The
discrepancy could be due to the use of different substrates since different substrates
can provide varying levels of nutrients. For example, D. suzukii development differs
based on host fruit species (Hardin et al. 2015, Lee et al. 2016). Furthermore, artificial
diets are created to provide the optimal mixture of necessary nutrients for the insect of
study and could support a faster development time than on natural substrate
(Vanderzant 1974). Humidity is also an important factor affecting D. suzukii
development. In the laboratory, the net reproductive rate and rate of population increase
were both best at relative humidity (RH) levels above 84% and lower trap captures in
the field were associated with lower RH (Tochen et al. 2016). Studies on crop canopy
microhabitats found that more D. suzukii adults and higher fruit infestation was found in
the interior of crop canopies where RH was higher than more exposed areas
(Diepenbrock and Burrack 2017, Rice et al. 2017).
The global range of Drosophila suzukii spans from northern climates to equatorial
climates (Asplen et al. 2015). Previous research on cold hardiness of D. suzukii
indicated that this fly could not overwinter due to its low cold-tolerance (Dalton et al.
2011, Jakobs et al. 2015). Recent studies, however, have shown that D. suzukii
produces a winter morph phenotype when acclimated to periods of cold, which is more
tolerant than the summer morph phenotype (non-acclimated) (Stephens et al. 2015,
Shearer et al. 2016). The winter morph is a larger, darker, form with longer wings, that
can survive up to 115 d in subzero temperatures (Shearer et al. 2016, Wallingford and
Loeb 2016). Larger body size is thought to reduce water loss (Addo-Bediako et al.
24
2001) and provide greater cold tolerance (Mirth and Shingleton 2012), whereas darker
body pigmentation may improve thermal regulation (David et al. 1990). The increased
length of the wings may allow the flies to disperse greater distances in search of
resources (Zerulla et al. 2015). Immature stages are less cold tolerant suggesting that
D. suzukii overwinters in its adult stage (Enriquez and Colinet 2017a). Additionally,
female egg-load and pre-oviposition time (mated to first oviposition event) were higher
and lower, respectively, in winter morph flies (Wallingford et al. 2016). When returned to
optimal conditions, winter morph females began ovipositing immediately (Wallingford et
al. 2016).
The thermal tolerance of D. suzukii has been investigated in recent studies.
There was 100% mortality of adult flies exposed to temperatures above 30°C at 65-70%
RH within 2 h (Eben et al. 2018). Male flies were found to be less heat tolerant than
female flies at temperatures above 34°C and the pupal form was most heat tolerant but
tolerance was reduced at lower humidity (Enriquez and Colinet 2017a). Studies on D.
melanogaster reported signs of sterility at 30°C (Petavy et al. 2001, David et al. 2005).
However, heat-acclimated D. suzukii adults showed no signs of sterility at temperatures
up to 39°C (RH 18-85%) (Eben et al. 2018). The same study found that no adults
eclosed above 30.9°C. These results suggest that average daily temperature
maximums above 32°C very typical of summers in the southeastern U.S, may reduce
populations of D. suzukii as a result of high adult mortality and eclosion rather than
reduced fecundity. Further study into the heat tolerance and sterility of D. suzukii is
important for understanding and predicting population dynamics in warm climates such
as the southeastern U.S.
25
Pest Status and Injury
Drosophila suzukii is an invasive pest of thin-skinned and stone fruits native to
eastern Asia (Kanzawa 1934, Hauser 2011, Walsh et al. 2011, Asplen et al. 2015). The
fly was first detected in Japan in 1916 where it became a pest of cherries (Prunus spp.)
and described by Matsumura in 1931 as the cherry fruit fly (Kanzawa 1934). In the
United States, D. suzukii was first recorded in Hawaii in 1980 (Kaneshiro 1983) and
reached the continental U.S. in Santa Cruz County, California in 2008 in association
with strawberries (Lee, Bruck, Dreves, et al. 2011). Since then D. suzukii has spread
rapidly throughout North America (Walsh et al. 2011), Europe (Calabria et al. 2012, Cini
et al. 2012, Gutierrez et al. 2016), and South America (Deprá et al. 2014, Klesener et al.
2018). The fly was first detected in Florida in Hillsborough County in 2009 (Steck et al.
2009), after which it spread to over 28 counties (Iglesias 2013, Liburd and Iglesias
2013).
The female D. suzukii has a modified ovipositor with large serrations that allows
her to cut into the skin of undamaged, ripening fruits and deposit an egg under the skin
surface (Beers et al. 2011, Hauser 2011, Atallah et al. 2014). This morphological trait is
unlike most other drosophilids that have soft, non-serrated ovipositors best suited for
ovipositing into overripe or damaged fruit (Atallah et al. 2014). Once the eggs hatch, the
larvae remain inside the fruit substrate and feed on the fruit flesh and associated yeasts
(Walsh et al. 2011, Hamby and Becher 2016). The oviposition site creates an entry
point for bacterial and fungal pathogens (Cini et al. 2014) and feeding by larvae results
in soft fruit that deteriorates rapidly. The detection of a single larva in a fruit during
inspection for shipment can result in the rejection of the entire load. Economic losses
have been significant in blueberries, caneberries, cherries, and strawberries in fruit-
26
producing regions of North America as a result of direct crop damage, larval infestations
and increase costs of control (Bolda et al. 2010, Goodhue et al. 2011, eFly SWD
Working Group 2012).
Behavior and Ecology
Drosophila suzukii is a true polyphagous insect with a host range of >100 plant
species (List et al. 2009, Arnó et al. 2016). The host range of D. suzukii includes many
cultivated hosts such as strawberry (Frangaria spp.), blueberry (Vaccinium spp.),
blackberry and raspberry (Rubus spp.), cherry (Prunus spp.) and grape (Vitis spp.)
(Walsh et al. 2011, Burrack et al. 2013, Asplen et al. 2015). Some crops are only
susceptible to attack if previously damaged and are of lesser concern, such as
cranberries (Steffan et al. 2013), muscadine grapes (Grant and Sial 2016), fuzzy
peaches (Stewart et al. 2014), tomatoes (Kanzawa 1939), pears, and apples (Lee et al.
2015). Drosophila suzukii has also been confirmed to utilize many wild, non-crop hosts
(Poyet et al. 2014, Lee et al. 2015, Arnó et al. 2016, Diepenbrock et al. 2016, Kenis et
al. 2016). The ability to utilize a large range of host species has aided in the rapid global
spread of D. suzukii (Adrion et al. 2014, Asplen et al. 2015, Fraimout et al. 2017)
Drosophila suzukii is highly mobile and will migrate in search of resources and
suitable environmental conditions (Mitsui et al. 2010, Klick et al. 2016). Many small and
stone fruit farms are surrounded by unmanaged, semi-natural habitats that contain non-
crop hosts with fleshy, thin-skinned fruits that D. suzukii may utilize in addition to its
commercial hosts (Klick et al. 2016, Pelton et al. 2016, Renkema et al. 2018,
Santoiemma et al. 2018, Thistlewood et al. 2018). Drosophila suzukii has been known
to infest wild blackberry (Rubus spp.) and grape (Vitis spp.), black elderberry
(Sambucus nigra), honeysuckle (Lonicera spp.), and black nightshade (Solanum
27
nigrum) (Poyet et al. 2014, Lee et al. 2015, Arnó et al. 2016, Kenis et al. 2016). Non-
crop hosts provide food, oviposition sites and protection during the non-crop season
after which D. suzukii moves from adjacent unmanaged habitats into cultivated fields as
resources become abundant (ripening of berries) (Liburd et al. 2014, Klick et al. 2016).
The presence of large areas of woodland habitats surrounding cultivated fields correlate
with D. suzukii appearing earlier in cultivated fields (Pelton et al. 2016) and higher adult
and fruit infestation (Santoiemma et al. 2018), necessitating the implementation of
management actions earlier in the season. Furthermore, in warmer geographic regions
such as the southeastern U.S., there is a greater continuity of resources, with the
availability of cultivated host crops throughout most of the year (e.g. December through
August in Florida). On farms where multiple host crops are grown in succession, there is
potential for D. suzukii to move from one crop to another (e.g. strawberry to blueberry to
caneberry to grapes) (Harris et al. 2014a, Pelton et al. 2016).
Monitoring and Management
The arrival of D. suzukii in small fruit production systems caused abrupt changes
to well-established integrated pest management (IPM) programs (Beers et al. 2011,
Bruck et al. 2011, Isaacs et al. 2013, Liburd and Iglesias 2013). Cherry growers in the
Pacific North West states saw high infestation rates within the first year of D. suzukii’s
appearance in California in 2009 (Beers et al. 2011). This resulted in repeated
applications of conventional and reduced-risk pesticides prior to and during harvest
periods especially in Florida. Prior to the arrival of D. suzukii hardly any pesticides were
used during harvest in Florida. At the time growers had zero tools available to them and
there was little knowledge about whether current insecticide chemistries were effective
against D. suzukii.
28
Management of D. suzukii is challenging because of its rapid development
(Emiljanowicz et al. 2014, Tochen et al. 2014), cryptic nature of the immature stages
(Walsh et al. 2011, Woltz and Lee 2017), wide host range (Lee et al. 2015, Arnó et al.
2016, Kenis et al. 2016), and its preference for ripening fruit (Lee et al. 2011, Burrack et
al. 2013, Kinjo et al. 2013). Current management programs for D. suzukii utilize a
combination of cultural and chemical controls based on results of strict monitoring
programs.
Monitoring
An effective trap is designed to detect the pest before damage occurs. In the
case of D. suzukii, growers have struggled to capture D. suzukii before signs of berry
infestation have been found. Monitoring tactics for D. suzukii have evolved rapidly since
the fly’s invasion of North America. The first trapping tools for adult flies used a variety
of cup-like containers with entry holes, baited with food-based liquids, such as apple
cider, white, red wine, and rice vinegars; red and white wines; beer; fruit juices; and
combinations thereof (Landolt et al. 2012, Iglesias et al. 2014, Burrack et al. 2015, Cha
et al. 2015). These traps had to be changed weekly and were not specific to D. suzukii.
For example, Iglesias et al. (2014) found that a clear cup trap baited with apple cider
vinegar (ACV), red wine + ACV, or ACV + red wine + sugar, captured many non-target
insects including other drosophilids, sap beetles (Nitidulidae), thrips (Thripidae), ants
(Formicidae). Non-target captures require additional processing time to identify and
count D. suzukii.
The first trap modifications were to increase the entry hole size, headspace
volume, and bait surface area (Lee et al. 2012, Renkema et al. 2014, Whitener and
Beers 2014) in order to increase D. suzukii captures. Additionally, using a yeast-based
29
bait mixture with sugar and flour increased D. suzukii captures significantly compared to
other food-based lures; however, this monitoring technique still captured significant
numbers of non-target organisms (Kleiber 2013, Iglesias et al. 2014, Burrack et al.
2015). Research began to focus on making the trapping system more specific to D.
suzukii. Modifications of the trap design began to incorporate the colors red and black
based on the color preference of the adult flies (Lee et al. 2012, Basoalto et al. 2013,
Renkema et al. 2014). Finally, a lure based on a 4-component blend of fermentation
volatiles was developed and was shown to be more specific to D. suzukii (Cha et al.
2014, 2015), which is the basis for commercially available lures (Trece’s Pherocon
SWD lure, and Scentry’s SWD lure). The current trapping system is a clear and red
container, with groups of small entry holes on three sides, and is baited with a synthetic,
slow-release lure and a soap-water drowning solution (Scentry Biologicals, Inc., Billings,
MT). The lure attracts other drosophilids but fewer other non-targets (Renkema et al.
2018). Research continues to increase the attractiveness and specificity of the D.
suzukii trapping system.
Monitoring for fruit infestation by larvae has undergone fewer changes. Sampling
includes collecting ripe fruit from the field from which larvae are extracted using either
the salt (Hueppelsheuser 2010, Dreves et al. 2014, Yee 2014) or emergence method
(Iglesias and Liburd 2017a). The salt method involves slightly crushing and flooding fruit
with a high-salt solution. The high-salt environment is meant to expel the larvae from the
fruit where they are counted on the surface of the solution. The emergence method
involves incubating fruit in containers and allowing for adults to emerge. Rather than
counting larvae, the number of emerged adults from the fruit is recorded.
30
Cultural Control
Cultural tactics employed to manage D. suzukii are aimed at inhibiting access to
the host material. Blackberries and blueberries are harvested every 1-3 days during
peak season to decrease the availability of ripening fruit for oviposition (Liburd and
Iglesias 2013, Leach et al. 2017). Unmarketable fruit, whether overripe on the bush or
fallen culled fruit, are collected and disposed of by burying, solarization, burning or
removal off-site in the event these fruit are infested (Haye et al. 2016, Renkema and
Devkota 2017). Exclusion netting has been shown to significantly reduce and delay D.
suzukii infestation in raspberries (Schattman et al. 2015, Leach et al. 2016). Netting can
also alter environmental conditions within the netting yet no differences in fruit quality
were found (Leach et al. 2016). Cultural tactics can require large initial economic
investments such as in the case of exclusion netting, or in terms of labor required for
fruit harvesting and removal (Goodhue et al. 2011, Leach et al. 2016, Mazzi et al. 2017).
Pruning to open up the plant canopy, has been suggested as an effective cultural
control tactic for D. suzukii (Haye et al. 2016) and is currently being investigated.
Biological Control
Biological control strategies are currently being investigated for potential
management of D. suzukii. Currently a commercial biological control agent is not
available. Several surveys of parasitoids of D. suzukii have been conducted in the fly’s
native range (Ideo et al. 2008, Cini et al. 2012, Daane et al. 2016, Zhu et al. 2017),
Europe (Chabert et al. 2012, Rossi Stacconi et al. 2013, Miller et al. 2015, Mazzetto et
al. 2016, Knoll et al. 2017), and North America (Rossi Stacconi et al. 2013, Miller et al.
2015). Two genera of larval parasitoids Ganaspis and Leptolina (Hymenoptera:
Figitidae) have been shown to parasitize larvae in fruit and have a high specificity to D.
31
suzukii (Cini et al. 2012). Pachycrepoideus vindemiae (Rondani) (Hymenoptera:
Pteromalidae), a generalist pupal parasitoid that has been associated with parasitism of
D. melanogaster, has been identified in North America and Europe and shows some
promise of adapting to the new invader D. suzukii (Chabert et al. 2012, Rossi Stacconi
et al. 2013, Miller et al. 2015, Wang et al. 2016). Another generalist pupal parasitoid
found throughout Europe, North America and Japan (Mitsui and Kimura 2010, Rossi
Stacconi et al. 2013), Trichopria drosophilae (Hymenoptera: Diapriidae), also
parasitizes D. suzukii though at a lesser rate than P. vincemiae (Rossi Stacconi et al.
2015, Knoll et al. 2017). Other potential species are in the genus Asobara
(Hymenoptera: Braconidae) and have been found to parasitize D. suzukii in the field
(Mitsui and Kimura 2010, Daane et al. 2016) and the laboratory (Ideo et al. 2008).
Two commonly found predators in blueberry systems, Orius insidiosus
(Hemiptera: Anthocoridae) and Dalotia coriaria (Coleoptera: Staphylinidae), have been
shown to feed on D. suzukii larvae in the laboratory (Renkema et al. 2015, Woltz et al.
2015) and may contribute to natural control of this pest in the field. Drosophila suzukii
tends to pupate in the soil or less frequently, in the fruit (Woltz and Lee 2017). Ground-
dwelling predators, such as carabid beetles, earwigs, and spiders, have been shown to
feed on fruit flies (Tephritidae) that pupate in the soil (Monzó et al. 2011, Renkema et al.
2013), and may also feed on the pupae of D. suzukii. Other studies have investigated
the use of entomophatogenic fungi (Gargani et al. 2013, Woltz et al. 2015) and
nematodes (Woltz et al. 2015) with varying levels of success. Research is continuing to
focus on the potential for biological control for management of D. suzukii.
32
Chemical Control
Most growers rely heavily on chemical controls since there is a zero tolerance for
larvae in fruit (Liburd and Iglesias 2013, Burrack 2014). The most effective insecticide
classes against D. suzukii are organophosphates, synthetic pyrethroids, diamides,
spinosyns, and less so neonicotinoids (Beers et al. 2011, Cini et al. 2012, Haviland and
Beers 2012, Van Timmeren and Isaacs 2013, Diepenbrock et al. 2016, Diepenbrock et
al. 2017). Insecticides target the adult flies since the larval and pupal stages occur
inside the fruit and in the soil, respectively, where insecticides cannot penetrate.
Growers in areas where D. suzukii populations are low use monitoring to guide
application timing (Iglesias pers. observation) but many growers who historically have
high populations on their farms spray on a calendar basis (Diepenbrock et al. 2016,
Diepenbrock et al. 2017). There is also concern about the effects D. suzukii spray
programs have on non-target organisms since the effective compounds tend to be
broad-spectrum in nature.
Rotation of different chemical classes is critical for effective insecticide resistance
management (IRM). Conventional growers have many available compounds with
different chemicals classes that can be used in an IRM program (Beers et al. 2011,
Bruck et al. 2011, Van Timmeren and Isaacs 2013). However, organic berry growers
have a much reduced list of available chemical classes for D. suzukii and even fewer
provide efficacy (Bruck et al. 2011, Liburd and Iglesias 2013, Van Timmeren and Isaacs
2013). Additionally, there is concern that D. suzukii may develop resistance to the most
commonly used, most effective organic compounds as a result of exposure to only a
few chemical classes and its ability to have multiple generations during a season
33
(Tochen et al. 2014). Previous studies have shown that D. suzukii can develop
resistance in the laboratory (Whitener and Beers 2011, Smirle et al. 2017).
Having several effective compounds available for D. suzukii management can
also help to reduce the buildup of insecticide residues on the crop. Maximum Residue
Limits (MRLs) are limits on the level of pesticide residue allowed on a crop imported
from another country. Violations of MRLs could result in the inability to sell to certain
international markets and could have severe economic consequences (Goodhue et al.
2011, Farnsworth 2013).
Justification
Blueberry is a high-value crop in Florida where its production is on the rise. The
crop serves as an alternative to citrus, from which many growers are switching, due to
challenges associated with citrus greening (Huanlongbing disease) vectored by the
citrus psyllid, Diaphorina citri Kuwayama, that has resulted in a yield decrease of 42% in
Florida since 2005 (Singerman and Useche 2016). Additionally, the health benefits of
blueberries have caused an increase in the demand of blueberry consumption (Routray
and Orsat 2011). Blueberries produced in Florida are the first domestic berries on the
market after the Chilean season ends and they are sold primarily for the fresh market
(England 2014). As a result, Florida blueberry market prices are typically high (NASS-
USDA 2018) and the need for effective, economical management options is imperative.
The overall goal of this dissertation research is to study host fruit selection,
oviposition behavior and farmscape distribution of D. suzukii to develop IPM
management tactics and tools that can be used for the sustainable management of D.
suzukii in small fruit crops. Drosophila suzukii has a broad host range that includes
strawberry, blackberry, blueberry, cherry, grapes, and raspberry. The susceptibility of
34
the hosts to egg-laying and infestation by D. suzukii varies. Understanding the berry
characteristics that influence host plant susceptibility may guide the development of new
blueberry cultivars that have less desirable traits for D. suzukii or develop pest
management strategies such as push-pull using trap crops.
Drosophila suzukii is highly mobile and will migrate in search of resources and
suitable environmental conditions. Many berry farms in Florida are surrounded by
unmanaged habitats that contain non-crop hosts and may serve as reservoirs during the
non-cropping season until migration begins into managed fields. Additionally, many
blueberry fields are planted with a mix of different varieties, which may differ in
susceptibility to D. suzukii infestation. Understanding how D. suzukii utilizes the
unmanaged areas and different varieties within the field can help to develop site-specific
and behavior-based tactics.
Drosophila suzukii spends most of its immature life inside the fruit. During this
time the fruit may remain on the bush or fall to the soil due to decay or knockdown from
pesticide equipment or harvesting. Tilling the soil between crop rows may serve to bury
infested fruit and reduce adult emergence. Additionally, D. suzukii utilizes unmanaged
areas during the non-cropping season and migrates into the field as managed crops
begin to fruit. Border sprays of insecticides are selectively applied along the perimeter of
a field and can be useful at delaying or preventing pest invasion from surrounding
environments. Border sprays have been used as an alternative to cover or every-row
sprays and may reduce pesticide effects on the environment and costs associated with
application.
35
Drosophila suzukii is usually managed using prophylactic applications of broad-
spectrum and reduced-risk insecticides. Rotation of different chemical classes is critical
for effective insecticide resistance management (IRM). However, organic berry growers
have a much-reduced list of available chemical classes for D. suzukii. Identifying new
organic and biorational insecticides will provide additional tools to organic and
conventional growers to help prevent insecticide resistance, prolonging the life of
current chemical classes.
Objectives
The overall goal of this project is to study host fruit oviposition behavior and
farmscape distribution of D. suzukii to develop IPM management strategies in small fruit
crops. To do this, I had four research objectives:
1. Identify berry characteristics involved in D. suzukii host selection of southern highbush and rabbiteye blueberry;
2. Investigate and map the spatial and temporal distribution of D. suzukii in southern highbush blueberries and field margins;
3. Evaluate the effect of between-row tillage and border sprays as alternative control tactics for management of D. suzukii; and
4. Test new biorational insecticides for management of D. suzukii in blueberries and blackberries in laboratory, semi-field, and field bioassays.
36
CHAPTER 3 BLUEBERRY TYPE AND CULTIVAR SUSCEPTIBILITY TO DROSOPHILA SUZUKII
OVIPOSITION
Host plant selection is a complex process whereby a set of cues is used to locate
and select host plants for food, reproduction, and/or oviposition. Schoonhoven et al.
(2005) describe the host selection process in two main steps: 1) searching and finding
and 2) selection and acceptance. During the searching phase, the insect begins with
random searching which involves non-directional and directional changes in movement.
Directional changes in movement, or taxes, become possible when the host plant emits
cues that are within range of the insect sensory receptors. These cues may be long
range visual or olfactory cues (Renwick 1989, Schoonhoven et al. 1998). Taxes
eventually result in the insect making plant contact or finding the host. The second
phase begins with evaluation of the plant substrate for acceptance. The insect may use
short range olfactory, mechanosensory, gustatory cues, or a combination thereof to
evaluate whether the substrate is a resource. Acceptance occurs when the insects
begin to feed or oviposit.
Drosophila suzukii (Matsumura) is an invasive vinegar fly species native to
southeast Asia (Kanzawa 1934, Asplen et al. 2015, Gutierrez et al. 2016). Since its first
detection in the continental North America in California in 2008 (Walsh et al. 2011), D.
suzukii has spread rapidly to most of the continent, South America (Deprá et al. 2014),
and Europe (Calabria et al. 2012, Cini et al. 2014). Unlike other drosophilids which have
a soft, blunt ovipositor for laying eggs in damaged or overripe fruit, the female D. suzukii
has a sharp, serrated ovipositor that can puncture marketable, undamaged fruit (Atallah
et al. 2014). There is a zero-tolerance for infested fruit so one developing larvae in a
berry can result in rejection of entire shipments (Burrack et al. 2012).
37
Since Drosophila larvae develop inside the fruit substrate, their mobility is
restricted and they do not actively forage. As such, most of the research on D. suzukii
host selection has been focused primarily on oviposition site selection by the adult
female on various host fruits (Lee et al. 2011, Bellamy et al. 2013, Burrack et al. 2013,
Kinjo et al. 2013, Stewart et al. 2014, Lee et al. 2015, Lasa et al. 2017, Little et al.
2017). The host range of D. suzukii includes many cultivated hosts [strawberry
(Frangaria spp.), blueberry (Vaccinium spp.), blackberry and raspberry (Rubus spp.),
cherry (Prunus spp.), etc.] fruits (Walsh et al. 2011, Burrack et al. 2013, Asplen et al.
2015). Recent studies have shown a difference in D. suzukii’s oviposition preference for
different hosts. Choice bioassays have consistently shown that caneberries
(blackberries and raspberries) are preferred for oviposition over grapes, blueberries,
and strawberries and that ripe fruit are preferred over under- or overripe fruit stages
(Kanzawa 1939, Lee et al. 2011, Bellamy et al. 2013, Burrack et al. 2013). Evaluation of
host preference of two different blueberry species grown in the southeastern U.S.,
southern highbush and rabbiteye, showed that D. suzukii laid more eggs in ripe
southern highbush blueberries than in rabbiteye blueberries (Iglesias 2013).
The common cultivated hosts (strawberry, blackberry, blueberry, cherry, grapes,
and raspberry) have different characteristics with respect to fruit firmness, sweetness
and size. Some mechanisms have been suggested that may influence D. suzukii’s fruit
preferences. Penetration force, the force required to puncture the skin of a fruit during
oviposition, differs among host fruits. For example, raspberries are a very soft fruit and
have a penetration force significantly lower than blueberry, blackberry and strawberry
(Burrack et al. 2013). Several studies have observed a decrease in eggs laid or larvae
38
in fruit as penetration force increased (Lee et al. 2011, Burrack et al. 2013, Kinjo et al.
2013, Arnó et al. 2016). Burrack et al. (2013) also found that no eggs were laid at
penetration forces above 52.00 cN. Soluble solids content (°Brix) has shown a positive
correlation with eggs laid or larvae in fruit (Lee et al. 2011, Arnó et al. 2016). Lee et al.
(2015a) found that the number of eggs laid increases with increase of host fruit pH.
Additionally, color preference tests for D. suzukii have shown a preference for black and
red, which have been used in trap development (Lee et al. 2012, Basoalto et al. 2013,
Kirkpatrick et al. 2016).
Cultivars are developed to produce plants with desirable traits, such as sweeter
fruit, softer/firmer fruit, looser/tighter berry clusters, resistance to pests, and earlier
ripening period. For example, southern highbush (SHB) blueberry (Vaccinium
corymbosum L. × V. darrowii blueberry) cultivars Emerald (U.S. Patent 12165) and
Jewel (U.S. Patent 11807) were developed with very large berry size. Snowchaser (U.S.
Patent 19503) was developed for early fruit ripening. Sweetcrisp (U.S. Patent 20027)
was developed for sweet flavor. Farthing (U.S. Patent 12783) was developed for firm
texture and ability to be mechanically harvested (Williamson et al. 2014). Characteristics
of northern highbush (V. corymbosum L), southern highbush, and rabbiteye blueberry
(RE) (V. virgatum) cultivars vary in surface color, fruit weight, firmness, soluble solids
(sweetness), and pH (Saftner et al. 2008, Gündüz et al. 2015), of which firmness,
sweetness, and pH have been suggested as possible preference mechanisms of D.
suzukii.
The goal of this study was to determine how fruit characteristics play a role in
oviposition behavior of D. suzukii. Understanding the level to which these characteristics
39
influence oviposition may guide the development of new blueberry cultivars that have
less desirable traits to D. suzukii. Furthermore, understanding host preference can help
to develop pest management strategies for D. suzukii.
Materials and Methods
Fly Source Materials for All Studies
Drosophila suzukii were obtained from a laboratory colony initiated February
2011 and maintained at the University of Florida Small Fruit and Vegetable Lab. Colony
is over 50 generations but has been infused periodically with wild-caught flies. Flies are
incubated at 23 °C, relative humidity ~65%, and 16:8 h light: dark cycle. Flies were
reared on an instant, potato-based diet (Formula 4-24, Carolina Biological Supply,
Burlington, NC) in 0.25-L polypropylene bottles (Applied Scientific, Kalamazoo, MI) and
closed with foam plugs (Jaece, North Tonawanda, NY). Flies used in behavioral assays
were sexually mature (4 to 7 d old). Flies were anesthetized using CO2 prior to use in
experiments.
Blueberry Source Material
Blueberries were harvested from research plots at the University of Florida Plant
Science Research and Education Unit in Citra, FL, an organic blueberry farm in
Inverness, FL, and a conventional farm in Homerville, GA. All blueberry bushes were 2-
8 years old and managed using recommended production practices (Williamson et al.
2006). Only fully ripe berries were harvested and used for the study. Two blueberry
types and six cultivars from each type were evaluated (Table 3-1). Berry samples were
collected from four blocks of four bushes that were randomly selected from each
cultivar. A sample of at least 150 ripe berries were collected from each block and
brought back to the laboratory. A subsample of 10 berries per block were inspected
40
using a dissecting microscope for the presence of Drosophila eggs, to ensure that they
were not infested in the field prior to the start of the experiment. A second subsample of
30 berries per block was used for the quality measurements (120 berries per cultivar). A
third subsample of 5 berries per block was used for the no-choice assays (20 berries
per cultivar). The fourth subsample of 10 berries per block was used for the choice
assays (30 berries per cultivar). Quality measurements were taken on berries within 6 h
of harvest. Berries were refrigerated at ~4 °C and allowed to return to room temperature
prior to use in the oviposition assays. All assays were conducted within 8 days from
harvest.
No-Choice Bioassays
No-choice tests were conducted in arenas that consisted of 59-ml plastic cup
(Solo Cup Company, Lake Forest, IL) with vented lids (Fig. 3-1). For each cultivar, there
were 20 replicates per cultivar (five per block). A single berry and a cotton wick
saturated with 5% sugar water were placed in each arena. One male and one female 4-
7-day old flies were transferred to each arena and were allowed to oviposit for 24 h.
Assays were kept at 23 °C, relative humidity ~65%, and 16:8 h light: dark cycle. After 24
h, flies were removed and berries were inspected under a dissecting microscope to
count deposited eggs by counting the respiratory filaments protruding from the berry
skin. Berries were incubated for an additional 14 d to allow for adult emergence, after
which adult flies were anesthetized, counted and sexed.
Choice Bioassays
Choice tests were conducted in a Plexiglas arena (99.1 x 99.1 x 78.7 cm) at
~22.8 °C and 14:10 h light: dark cycle (Fig. 3-2). A triangular divider (33.3 cm from the
top of the arena) separated the left and right sides of the arena. Two side doors allowed
41
for installation of the treatments inside the arena while one door allowed for insertion of
flies. The arena was built on a wooden frame, enclosed with Plexiglas, 59.7 cm from the
ground. A fine mesh screen separated the arena from the frame. A vent located inside
the frame pulled air down through the arena while two pumps located on either side of
the divider pushed air through the arena.
One choice trial consisted of all six cultivars of a blueberry type. Blueberry types
were run separately. Six clusters of 10 berries (one cluster per cultivar) were secured in
clear mesh bags made of fishing net. Clusters were hung from the top of the arena,
below the divider, equidistant from each other and the fly release location at the bottom
center of the arena. Deli cups (30 mL, Solo Cup Company, Lake Forest, IL) with cotton
wicks saturated with 5% sugar water were placed beneath each of the berry clusters.
One hundred 7- to 14-d-old D. suzukii flies (70 females, 30 males) were removed from
the fly colony, anesthetized with CO2 (for 3 s) and placed into a 150 x 15 mm Petri dish
(Fisherbrand, Waltham, MA). The Petri dish was inserted into the arena through the
main door placed into the center of the floor of the arena which allowed flies the option
to move within the arena. Flies remained in the arena for 48 h (1 trail), after which berry
clusters were removed and eggs were counted under a dissecting microscope. Berries
were incubated for an additional 14 d to allow for adult emergence, after which adult
flies were anesthetized, counted and sexed. Trials were repeated three times for each
blueberry type and cultivar positions were rotated between trials to reduce positional
bias.
Berry Characteristics
Blueberry cultivars vary in their fruit shape. For example, ‘Star” has spherical
berries whereas ‘Emerald” has large, flat berries. For this reason, the size was
42
presented as the volume of the berry and was calculated using the equation for the
volume of an ellipsoid (Eq. 3-1), where a, b and c are the major and minor axes of the
ellipses on the x, y, and z planes, respectively.
𝑉 =4
3𝜋𝑎𝑏𝑐 (3-1)
Axis measurements were made using a Vernier dial caliper (Measy 2000,
Kunststoffwerk Buchs, Switzerland). Measurements were made on 30 berries from four
bushes (120 total berries) for each cultivar.
The penetration force is the force required to penetrate the skin of the fruit.
Penetration force was measured using a Mark-10 Series 3 digital force gauge (Wagner
Instruments, Greenwich, CT) fitted with a number two insect pin with the tip removed.
Berry and force gauge were secured to a stand for stability in measurements. To
account for variability of each blueberry fruit, four measurements were taken on each
berry along the central horizontal axis and a mean calculated for use in analysis.
Penetration force were reported as grams of force (gF).
Soluble solids are commonly used as a measure of the sugar content or
sweetness of a fruit (Ruiz-Altisent et al. 2010, Gündüz et al. 2015). The soluble solids
content of the berry was measured using a standard handheld refractometer (model
113ATC, MRC ltd., Holon, Israel). After each berry was punctured for penetration force,
~ 1.0 ml of berry juice was extracted using a pipette and placed onto the refractometer
for measurement. Soluble solids were reported as °Brix.
Statistical Analysis
The no-choice and choice data were analyzed using a generalized linear mixed-
model Analysis of Variance (ANOVA; PROC GLIMMIX, v. 9.4, SAS Institute 2016). For
43
the no-choice analysis, type and cultivar [type] (cultivar nested in type) were the fixed
effects and block was included as a random effect. The number of eggs laid, number of
emerged adults, and proportion survival (total adults emerged/ total eggs laid), were the
response variables. Total eggs laid and adults emerged were fit to a negative binomial
distribution due to the number of zeroes in the response and the Kenward-Roger
method was used to estimate the degrees of freedom and adjust the standard error of
the fixed effects. The proportion survival was fit to a binomial distribution. Means were
separated using Tukey’s HSD multiple comparisons test for cultivar[type]. The sex ratio
of emerged adults in both no-choice and choice tests were analyzed using a Chi-
squared comparison test (PROC FREQ).
In the choice-assays, data were analyzed separately for each blueberry type
since the type trials were conducted independently. Cultivar was the fixed effect and the
position of the fruit in the cage position was included as a random effect. The response
variables for the choice tests were the proportion of eggs laid (total eggs laid in cultivar/
total eggs laid in trial), proportion of emerged adults (total adults emerged in cultivar/
total eggs laid in trial), and the proportion of egg survival (total adults emerged/ total
eggs laid). Berries used in the choice assays were from the same sample so the berries
age range was 1- to 6-d old in trials 1 and 3, respectively. The proportion of eggs laid
and adults emerged were used instead of total numbers to reduce the effects of the trial.
The responses were fit to a binomial distribution with a logit link function. Means were
separated using Tukey’s HSD test for multiple comparisons.
Multivariate procedures were conducted on the block means of the data using
JMP (v. 13.2.0, SAS Institute Inc. 2016). A linear discriminant analysis with the Wilks’
44
Lambda MANOVA was conducted to attempt to separate the blueberry cultivars and
types by their berry characteristics. Non-parametric Spearman’s correlation coefficients
(ρ) were calculated as measures of association among the berry characteristics and
oviposition data. A generalized linear regression was conducted on any berry and
oviposition relationships that were significantly correlated. Differences in all analyses
were considered significant when P ≤ 0.05.
Results
Oviposition
In the no-choice assays, the number of eggs laid did not differ among the
blueberry types (F = 0.04; df = 1, 215.6; P = 0.8373). The mean number of eggs laid in
all RE cultivars was 4.05 ± 0.47 (± SE) and 3.68 ± 0.37 in SHB. However, the number of
eggs laid among the cultivars varied significantly (Table 3-2). In the RE cultivars, the
number of eggs laid was significantly higher in Vernon, Brightwell, Alapaha, and
Powderblue compared to Premier. Vernon and Brightwell had significantly more eggs
than Climax. In SHB, D. suzukii laid more eggs in Jewell and Farthing compared to Star.
More eggs were laid in Farthing than Emerald.
In the choice assays, the proportion of eggs laid in each cultivar was significantly
different for the RE cultivars but not the SHB cultivars (Table 3-3). The proportion of
eggs laid was greater in Powderblue, Vernon, Alapaha, and Brightwell than Premier but
not different from Climax.
Survival and Sex Ratio
In the no-choice assays, the mean number of adults that emerged from infested
berries was not significantly affected by blueberry type (F = 2.82; df = 1, 228; P =
0.0944) or by cultivar in RE or SHB blueberry types (Table 3-2).
45
The proportion survival in the no-choice assays was not affected by blueberry
type (F = 1.99; df = 1, 221; P = 0.1596) but differed significantly among the cultivars in
RE and SHB types (Table 3-2). In RE, significantly more D. suzukii survived in Premier
compared to Powderblue, Vernon, and Brightwell and in Climax compared to Vernon
and Brightwell. In the SHB cultivars, Star, Meadowlark, and Emerald had a higher
proportion surviving than Farthing, and Star more than Jewell and Abundance.
In the choice assays, the proportion of adults emerging was not different among
the RE or SHB (Table 3-3). The proportion survival was also not significantly different
among RE or SHB cultivars (Table 3-3).
The sex ratio of the emerged adults in the no-choice assays was significantly
different in the Alapaha (RE) cultivar only, with more females emerging than males and
the Abundance (SHB) cultivar, with more males emerging than females (Table 3-4). The
sex ratio in the choice assays only differed in the Alapaha (RE) and Abundance (SHB)
cultivars, both with significantly more females emerging than males (Table 3-5).
Berry Characteristics and Host Use
The blueberry types and cultivars differed significantly among all the berry
characteristics (Table 3-6). In terms of berry volume, RE berries were significantly
smaller overall (10.09 ± 0.10 cm3) compared to SHB berries (11.17 ± 0.11 cm3; F =
63.12; df = 1, 1416; P < 0.0001). In the RE cultivars, the berries ranged from the
smallest of 8.65 ± 0.22 (Alapaha) to the largest of 12.88 ± 0.26 cm3 (Vernon). In SHB,
berries ranged from 8.30 ± 0.21 (Abundance) to 13.16 ± 0.23 cm3 (Emerald; Table 3-6).
The soluble solids content (SSC) of RE berries (15.79 ± 0.08 °Brix) was significantly
higher than for SHB blueberries (13.06 ± 0.08 °Brix; F = 63.12; df = 1, 1416; P <
0.0001). The range of SSC in RE cultivars was from 13.48 ± 0.16 in Vernon to 17.11 ±
46
0.18 and 17.04 ± 0.16 °Brix in Brightwell and Climax, respectively. The SHB cultivars
ranged from 12.50 ± 0.22 in Jewell to 14.30 ± 0.22 °Brix in Meadowlark. The skin
penetration force also differed among blueberry types, with RE berries being
significantly firmer (36.87 ± 0.29 gF) than SHB berries (35.42 ± 0.39 gF; F = 38.21; df =
1, 1416; P < 0.0001). Among RE cultivars, Premier had the softest fruit (29.25 ± 0.45
gF) and Brightwell the firmest (43.14 ± 0.55 gF). In the SHB cultivars, the penetration
forces ranged from 28.68 ± 0.43 in Jewell to 43.14 ± 0.55 and 43.14 ± 0.55 gF in
Farthing and Abundance, respectively.
A linear discriminant analysis was conducted on the berry characteristics data to
identify common sources of variability among the RE and SHB cultivars. The Wilks’
Lambda MANOVA was significant (F = 0.007; df = 33, 100.87). Two canonicals
explained 95.9% of the variability among the cultivars, with canonical 1 and 2 explaining
54.4% and 40.9%, respectively (Fig. 3-3). The discriminant rays confirm the negative
relationship between berry volume and penetration force and volume and SSC. The
positive relationship between SSC and penetration force is less apparent. The
discriminant analysis successfully separates blueberry types and cultivars by the three
berry characteristics. The SHB and RE cultivars are grouped together except Vernon
(RE), which is grouped with the SHB cultivars. The cultivars overall are separated into
three groups. Abundance and Farthing, two SHB cultivars with high penetration force
values, are grouped towards the top. Cultivars in the bottom right of the figure (all RE)
have higher SSC and cultivars in the bottom left (all SHB and RE cultivar Vernon) have
a higher berry volume.
47
A multiple correlation analysis was conducted on the block means of all berry
characteristics and bioassay variables (Table 3-7). There was a significant negative
correlation between berry volume and SSC, and berry volume and penetration force,
whereby as berry volume increased, the SSC and skin penetration force decreased.
Penetration force and SSC were positively correlated so as penetration force increased
SSC also increased. In the no-choice assays, the number of eggs laid was positively
correlated with the number of adults that emerged which was positively correlated with
proportion survival (Table 3-7). In the choice assays, the proportion of adults emerged
was positively correlated with proportion survival. The only significant correlation among
the berry characteristics and the assay results was a negative correlation between
penetration force and proportion survival in the no-choice assays (Table 3-7). Proportion
survival followed a significantly negative linear distribution when plotted against
penetration force and explained 15.8 % of the variation (F = 8.61; df = 1, 46; P = 0.0052;
Fig. 3-4).
Discussion
The objective of this study was to investigate whether host use by D. suzukii
varied among different blueberry types and cultivars, and whether berry characteristics
could partially explain host utilization. Our study was consistent with other studies that
showed that blueberry is a suitable host for D. suzukii (Lee et al. 2011, Bellamy et al.
2013, Burrack et al. 2013, Lee et al. 2016). All cultivars evaluated were susceptible to
oviposition and all supported development of eggs to adults. Drosophila suzukii
oviposition and survival differed among the cultivars in the absence of choice (Table 3-
2). These results are inconsistent with a study that showed no differences in egg laying,
emerged adults, or survival in no-choice tests on several southern highbush cultivars
48
from California and Oregon, USA (Lee et al. 2011). Although several of the same
cultivars were evaluated in both studies, environmental conditions and growing
practices are different across the study regions and these conditions can affect berry
characteristics, susceptibility to D. suzukii and nutrient quality (Andersen et al. 2009,
Gündüz et al. 2015). Drosophila suzukii females are selecting oviposition sites that will
provide optimal conditions and dietary needs for larval development. Therefore,
oviposition could be affected by the nutrient quality (i.e. carbohydrates, proteins) in the
fruit (Diepenbrock et al. 2016, Lihoreau et al. 2016) and could explain the inconsistency
of the results.
Drosophila suzukii females did not show an ovipositional preference for SHB
blueberry cultivars when given a choice and the number of eggs laid among RE
cultivars only varied slightly when flies were allowed to choose (Table 3-3). In the field,
D. suzukii would be provided with several blueberry cultivars simultaneously.
Blueberries are typically planted in a mixed-cultivar arrangement to increase the length
of the harvest season and to provide cross-pollination, especially for RE blueberries
(Gough 1994). Survival was also similar for all cultivars. These results are consistent
with results from Lee et al. (2011) and could mean that D. suzukii females do not have a
preference for one cultivar over another. In both studies, the flies were in a laboratory
environment where they were provided with fruits only, and different cultivars were at
relatively close proximity. Other long-range, plant- or habitat-level cues may be
influencing host selection, such as leaf volatiles for host habitat location (Keesey et al.
2015), canopy density and microhabitat conditions (Diepenbrock and Burrack 2017), or
the presence of non-crop hosts (Klick et al. 2016, Pelton et al. 2016). The preference
49
results obtained in the laboratory may not translate to natural field conditions. Burrack et
al. (2013) evaluated field infestation rates of several blackberry and raspberry cultivars,
both hosts of D. suzukii, and found that infestation rates differed among some cultivars.
Whereas Burrack et al. (2013) did not evaluate the different cultivars in the laboratory,
the results suggest the interaction of other host-selection cues and support the need for
evaluating infestation of different blueberry cultivars in the field.
Survivorship of D. suzukii in all cultivars was higher when berry skin was easier
to penetrate. In the no-choice assays, the egg survivorship was negatively correlated
penetration force (Table 3-7). Other studies have found that egg laying decreases with
increasing skin penetration force (Lee et al. 2011, Burrack et al. 2013, Kinjo et al. 2013).
Our study shows that the survival of eggs to adults also decreases with increasing skin
penetration force. We also found that the penetration force value at which no eggs
would survive to adults was 51.62 gF (50.62 cN), which is similar to a previously
reported maximum value of 52.00 cN above which eggs could not be laid by D. suzukii
(Burrack et al. 2013). This result further demonstrates the importance of skin
penetration force as a host selection cue for ovipositing D. suzukii females. It is possible
that fruit firmness could be manipulated to reduce fruit susceptibility to D. suzukii in the
field. The application of calcium silicate on blueberry fruit could potentially increase fruit
firmness and reduced egg laying by D. suzukii (Lee et al. 2016). However, it is not clear
how this will affect the marketability of the fruit since long-term studies have not been
done. It should be noted that edible fruit coatings were inconsistent in reducing the
number of eggs laid but severely reduced egg survivorship in raspberries (Swoboda-
Bhattarai and Burrack 2014).
50
Recent blueberry breeding programs have been focusing on developing cultivars
that are suitable for machine harvest. Much of the southern highbush blueberry acreage
in the southeastern U.S. destined for the fresh market is harvested by hand (Safley et
al. 2005, Takeda et al. 2013). As the blueberry industry expands, growers are seeing an
increase in labor costs, shortages of labor, and low harvest efficiencies as threats to
sustainability (Takeda et al. 2017). Cultivars suitable for mechanical harvest tend to
have firmer fruit that can withstand some impact by harvesting rods and collection pans
in the harvesting equipment (Takeda et al. 2017). We tested three machine-harvestable
cultivars, Abundance, Farthing, and Meadowlark. Of these, Farthing and Abundance
both had the highest penetration forces recorded (Table 3-6). These cultivars had
similar numbers of eggs laid compared to other cultivars but had the lowest proportion
survival. Meadowlark, which had a low penetration force in our study, is promoted for
mechanical harvest for its loose berry clusters and medium berry detachment force
rather than for very firm fruit (U.S. Patent 21553). We did not see a correlation between
eggs laid and penetration force so these cultivars do not appear to be any less
susceptible to attack than other cultivars.
Overall, the rabbiteye blueberry cultivars were smaller, sweeter, and firmer than
the southern highbush cultivars (Table 3-6), which is consistent with other studies on
the textural characteristics of the blueberry types (Bremer et al. 2008, Gündüz et al.
2015). Southern highbush is softer and has shown to be more preferred to D. suzukii
than rabbiteye (Iglesias 2013). Whether D. suzukii prefers southern highbush berries
over rabbiteye is not critically important since the seasons of these two blueberry types
only briefly overlap in the southeastern U.S. In Florida, the southern highbush season
51
typically ends in May whereas rabbiteye begins in May. However, populations of D.
suzukii in one host can influence populations in neighboring hosts (Harris et al. 2014a,
Klick et al. 2016, Pelton et al. 2016). Plantings of southern highbush could serve as a
resource to support population growth, resulting in higher D. suzukii populations in
rabbiteye.
Understanding pest host selection behavior can have implications for pest
management. Our study further demonstrates the negative relationship between fruit
firmness and host suitability for D. suzukii. Additionally, berries that are smaller, sweeter
and softer may better support survivorship and population growth. This information may
lead to the development of cultivars with firmer fruit to help reduce population growth of
D. suzukii. Fruit that is too firm however, may be unacceptable to the consumer whose
desires must be considered during breeding and cultivar development.
52
Table 3-1. Cultivars of southern highbush and rabbiteye blueberries and the location from which the samples were taken.
Type Cultivar Sample Locationa
Southern Highbush Abundance Inverness Emerald Citra Farthing Inverness Jewel Citra Meadowlark Inverness Star Citra Rabbiteye Alapaha Homerville Brightwell Citra Climax Citra Powderblue Citra Premier Citra Vernon Homerville
a All locations were in Florida, except Homerville (Georgia)
Table 3-2. Mean (±SE) eggs laid, adults emerged, and proportion of eggs surviving to
the adult stage in rabbiteye and southern highbush blueberry cultivars in no-choice oviposition assays.
Blueberry Type Cultivar Eggs Laid Adults Emerged
Proportion Survivala
Rabbiteye Alapaha 4.35 ± 1.33ab 1.35 ± 0.46 0.26 ± 0.07ab
Brightwell 5.55 ± 0.94a 0.30 ± 0.13 0.14 ± 0.05c
Climax 1.85 ± 0.90bc 0.45 ± 0.18 0.22 ± 0.07ab
Premier 0.80 ± 0.33c 0.35 ± 0.20 0.16 ± 0.10a
Powderblue 4.00 ± 0.81ab 0.50 ± 0.22 0.36 ± 0.28bc
Vernon 7.75 ± 1.55a 0.85 ± 0.26 0.12 ± 0.04c
F 7.16 1.99 9.55
df 5, 210.3 5, 192.9 5, 221
P < 0.0001* 0.0822 < 0.0001*
Southern Highbush Abundance 2.90 ± 0.81abc 0.15 ± 0.11 0.03 ± 0.03bc
Emerald 2.10 ± 0.84bc 0.30 ± 0.18 0.08 ± 0.06ab
Farthing 5.95 ± 0.78ab 0.15 ± 0.08 0.04 ± 0.02c
Jewell 6.50 ± 1.13a 0.80 ± 0.30 0.12 ± 0.04bc
Meadowlark 2.90 ± 0.74abc 0.60 ± 0.23 0.29 ± 0.11ab
Star 1.75 ± 0.63c 0.50 ± 0.24 0.34 ± 0.14a
F 3.73 1.85 7.09
df 5, 199.5 5, 228 5, 221
P 0.0037* 0.1042 < 0.0001*
* Indicates significance at P ≤ 0.05. Columns within blueberry types with different letter indicate a statistical significance at P ≤ 0.05. aTotal number of adults emerged/ total number of eggs laid.
53
Table 3-3. Mean (±SE) proportions of eggs laid, adults emerged, and eggs surviving to
the adult stage in rabbiteye and southern highbush blueberry cultivars in choice oviposition assays.
Blueberry Type Cultivar Proportion Eggs Laida
Proportion Adults Emergedb
Proportion Survivalc
Rabbiteye Alapaha 0.17 ± 0.04a 0.07 ± 0.03 0.09 ± 0.04
Brightwell 0.16 ± 0.03a 0.17 ± 0.09 0.24 ± 0.13
Climax 0.11 ± 0.01ab 0.08 ± 0.06 0.16 ± 0.13
Premier 0.11 ± 0.01b 0.44 ± 0.28 0.27 ± 0.16
Powderblue 0.27 ± 0.03a 0.13 ± 0.07 0.09 ± 0.05
Vernon 0.19 ± 0.06a 0.11 ± 0.07 0.08 ± 0.04
F 10.6 0.92 0.43
df 5, 7 5, 7 5, 7
P 0.0037* 0.5174 0.8119
Southern Highbush Abundance 0.17 ± 0.01 0.14 ± 0.02 0.12 ± 0.05
Emerald 0.14 ± 0.02 0.20 ± 0.03 0.18 ± 0.08
Farthing 0.12 ± 0.01 0.15 ± 0.02 0.17 ± 0.07
Jewell 0.20 ± 0.03 0.13 ± 0.07 0.13 ± 0.07
Meadowlark 0.18 ± 0.01 0.19 ± 0.03 0.14 ± 0.07
Star 0.18 ± 0.05 0.19 ± 0.03 0.21 ± 0.15
F 3.95 0.48 0.13
df 5, 7 5, 7 5, 7
P 0.0507 0.7833 0.9809
* Indicates significance at P ≤ 0.05. Columns within blueberry types with different letter indicate a statistical significance at P ≤ 0.05. aTotal eggs laid in cultivar/ total eggs laid in trial. bTotal adults emerged in cultivar/ total eggs laid in trial. cTotal number of adults emerged/ total number of eggs laid.
54
Table 3-4. Sex ratio of D. suzukii adults that emerged from different cultivars of rabbiteye and southern highbush blueberry types in no-choice assays.
Blueberry Type Cultivar Female SWD
Male SWD
χ2 df P
Rabbiteye Alapaha 8 19 4.482 1 0.052*
Brightwell 1 5 2.667 1 0.219
Climax 5 4 0.111 1 1.000
Premier 5 2 1.286 1 0.453
Powderblue 6 4 0.400 1 0.754
Vernon 8 9 0.059 1 1.000
Total 37 39 0.053 1 0.909
Southern Highbush Abundance 2 1 0.333 1 1.000
Emerald 2 4 0.667 1 0.688
Farthing 2 1 0.333 1 1.000
Jewell 10 6 1.000 1 0.455
Meadowlark 7 5 0.333 1 0.774
Star 5 5 0.000 1 1.000
Total 27 23 0.320 1 0.672
* Indicates significance at P ≤ 0.05 Table 3-5. Sex ratio of D. suzukii adults that emerged from different cultivars of
rabbiteye and southern highbush blueberry types in choice assays.
Blueberry Type Cultivar Female SWD
Male SWD
χ2 df P
Rabbiteye Alapaha 10 1 7.364 1 0.012*
Brightwell 11 14 0.360 1 0.690
Climax 11 6 1.471 1 0.332
Premier 9 12 0.429 1 0.664
Powderblue 8 10 0.222 1 0.815
Vernon 10 2 5.333 1 0.384
Total 62 42 3.846 1 0.062
Southern Highbush Abundance 17 6 5.261 1 0.035*
Emerald 14 15 0.035 1 1.000
Farthing 13 12 0.040 1 1.000
Jewell 19 13 1.125 1 0.377
Meadowlark 15 14 0.035 1 1.000
Star 15 12 0.333 1 0.701
Total 93 72 2.673 1 0.119
* Indicates significance at P ≤ 0.05
55
Table 3-6. Mean (±SE) berry characteristics of several rabbiteye and southern highbush blueberry cultivars.
Blueberry Type Cultivar Volume (cm3) SSC (°Brix) Pen Force (gF)
Rabbiteye Alapaha 8.65 ± 0.22e 15.77 ± 0.19b 39.25 ± 0.57b
Brightwell 9.35 ± 0.17cd 17.11 ± 0.18a 43.14 ± 0.55a
Climax 10.02 ± 0.20bc 17.04 ± 0.16a 36.26 ± 0.61c
Premier 10.72 ± 0.24b 15.34 ± 0.15b 29.25 ± 0.45e
Powderblue 8.95 ± 0.16de 16.04 ± 0.17b 41.24 ± 0.66ab
Vernon 12.88 ± 0.26a 13.48 ± 0.16c 32.08 ± 0.49d
F 52.31 53.31 97.41
Df 5, 1416 5, 1292 5, 1416
P < 0.0001 < 0.0001 < 0.0001
Southern Highbush Abundance 8.30 ± 0.21e 12.74 ± 0.16bc 49.14 ± 0.64a
Emerald 13.16 ± 0.23a 13.23 ± 0.13b 31.66 ± 0.45b
Farthing 9.39 ± 0.18d 14.30 ± 0.22a 46.04 ± 0.51a
Jewell 11.78 ± 0.27bc 12.50 ± 0.22c 28.68 ± 0.43c
Meadowlark 11.59 ± 0.25c 13.09 ± 0.16b 31.95 ± 0.63b
Star 12.64 ± 0.23ab 13.12 ± 0.16b 26.16 ± 0.49d
F 79.86 9.7638 282.81
Df 5, 1416 5, 1292 5, 1416
P < 0.0001 < 0.0001 < 0.0001
* Indicates significance at P ≤ 0.05. Columns within blueberry types with different letter indicate a statistical significance at P ≤ 0.05. SSC = Soluble Solids Content, Pen Force = Penetration Force.
56
Table 3-7. Spearman’s correlation coefficients (ρ) and significance values (P) for several berry characteristics and eggs laid, adult emergence and eggs survival rates from laboratory assays in rabbiteye and southern highbush blueberries.
Variable Statistics
V2 V3 V4 V5 V6 V7 V8 V9
Berry Volume (V1)
ρ P
-0.4012 0.0047*
-0.7231 < 0.0001*
0.0060 0.9676
0.1817 0.2164
0.1524 0.3010
-0.0033 0.9845
0.1969 0.2497
0.1455 0.3972
SSC (V2) 0.3219 0.0257*
-0.0703 0.6347
-0.0444 0.7647
0.0110 0.9409
-0.1255 0.4658
-0.1590 0.3542
-0.1458 0.8354
Penetration Force (V3)
0.2810 0.0530
-0.2709 0.0625
-0.3981 0.0051*
-0.0053 0.9756
-0.2740 0.1058
-0.1952 0.2540
Eggs Laida (V4) 0.4222 0.0028*
-0.1264 0.3919
0.2474 0.1457
-0.2677 0.1145
-0.3528 0.0348*
Adults Emergeda (V5)
0.7619 < 0.0001*
0.1430 0.4055
-0.2587 0.1277
-0.2910 0.0851
Proportion Survivala (V6)
-0.0655 0.7044
-0.1746 0.3084
-0.1011 0.5572
Prop. Eggs Laidb (V7)
0.1009 0.5581
-0.4158 0.0117*
Prop. Adults Emergedb (V8)
0.7951 < 0.0001*
Proportion Survivalb (V9)
* Indicates significance at P ≤ 0.05. SSC = Soluble Solids Content. aData from no-choice assays. bData from choice assays.
57
Figure 3-1. No-choice bioassay arena with a single blueberry and sugar-water solution
in vial. Photo courtesy of author.
Figure 3-2. Bioassay arena used for D. suzukii choice assays. Groups of 10 blueberries
of six cultivars of rabbiteye or southern highbush types were secured equidistant from the top of the arena. Photo courtesy of author.
58
Figure 3-3. Discriminant analysis of rabbiteye (gray circles) and southern highbush
(black circles) cultivars using berry characteristics (Volume = berry volume, Pen Force = skin penetration force, SSC = soluble solids content). Circles represent the 95% confidence intervals of the means.
59
Figure 3-4. Linear relationship between the proportion survival and the corresponding skin penetration force of several rabbiteye (gray symbols) and southern highbush (black symbols) blueberry cultivars. Eggs Surviving = 0.583 – 0.011*Pen Force. Dashed lines represent the 95% confidence limits for the fitted line.
60
CHAPTER 4 SPATIO-TEMPORAL DISTRIBUTION OF DROSOPHILA SUZUKII
Agricultural field margins play an important role in the agroecosystem. Field
margins are habitat for pests and beneficial insects and can affect neighboring crop
fields (Landis et al. 2000, Bianchi et al. 2006, Roubos et al. 2014). Several agricultural
pest species have been found to inhabit field margins including, the Colorado potato
beetle Leptinotarsa decemlineata Say (Weisz et al. 1996), plum curculio Conotrachelus
nenuphar (Herbst) (Lafleur et al. 1987), Nearctic leafhopper Scaphoideau titanus Ball
(Lessio et al. 2014), Asian citrus psyllid Diaphorina citri Kuwayama (Boina et al. 2009),
codling moth Cydia pomonella L (Basoalto et al. 2010), and the newly invasive
Drosophila suzukii (Matsumura) (Klick et al. 2016, Pelton et al. 2016, Swoboda
Bhattarai 2017).
Drosophila suzukii (Diptera: Drosophilidae) is an invasive pest of thin-skinned
small fruits (Walsh et al. 2011, Asplen et al. 2015). Since it first detection in North
America in California in 2008, D. suzukii has spread throughout most of the country
(Hauser 2011, Walsh et al. 2011, Burrack et al. 2012). Unlike other drosophilids, the
female D. suzukii has a serrated ovipositor that she uses to puncture the skin of
undamaged, ripening fruits to lay an egg beneath the skin surface (Atallah et al. 2014).
Drosophila suzukii is highly polyphagous and will oviposit in both crop and non-crop
hosts (Lee et al. 2011, Burrack et al. 2013, Lee et al. 2015, Arnó et al. 2016, Kenis et al.
2016). This fly is also highly mobile and will migrate in search of hosts or suitable
environmental conditions (Mitsui et al. 2010, Klick et al. 2016, Kirkpatrick et al. 2017).
Field margins are habitat for numerous fruit-bearing wild D. suzukii host species
and could play a role in D. suzukii in the neighboring crop fields (Lewis 1969, Holland et
61
al. 2005, Boina et al. 2009, Basoalto et al. 2010, Klick, Yang, Walton, et al. 2016).
These areas can provide alternate resources (food and oviposition sites), protection, or
suitable environmental conditions to support population development. Many wild hosts
of D. suzukii have been identified within unmanaged areas adjacent to cultivated host
plantings in the U.S. and Europe, including wild blackberry (Rubus spp.), American
pokeweed (Phytolacca americana), various Prunus spp., honeysuckle (Lonicera spp.),
elderberry (Sambucus spp.), dogwood (Cornus spp.), bittersweet (Solanum dulcamara)
and hairy (S. villosum) nightshades, wild Vaccinium spp., and grapes (Vitis spp.) (Poyet
et al. 2014, Lee et al. 2015, Arnó et al. 2016, Diepenbrock et al. 2016, Kenis et al.
2016). Research on the spatial dynamics of D. suzukii found that adult fly populations
were significantly higher in raspberry fields that were adjacent to unmanaged areas with
wild ‘Himalaya’ blackberry (Rubus armeniacus Focke) than without wild blackberry
(Klick et al. 2016). Furthermore, infestation in blackberries was higher at the field, which
were closer to wooded areas, than the center of the plot (Swoboda Bhattarai 2017).
Further understanding of this behavior could help in the development of IPM and site-
specific pest management (SSPM) programs.
Pest spatial patterns may also be affected by mixed cropping systems. Many
blueberry growers plant multiple cultivars of blueberries in alternating single or multiple
rows. The mixed-cultivar system allows for improved cross-pollination and a longer
harvest season by combining early-, mid-, and late-season cultivars (Gough 1994).
Cultivars are developed to possess desirable traits, such as sweeter/firmer fruit,
soft/firm fruit, looser/tighter berry clusters, higher fruit load, resistance to pests, or earlier
ripening period. In the laboratory, D. suzukii has shown variation in oviposition
62
preference for berries with different characteristics, such as firmness, pH, soluble solids
(sweetness), and size (Lee et al. 2011, Burrack et al. 2013, Lee et al. 2016). Preference
also varied between different cultivars of blueberry, blackberry, and wine grape cultivars
over others (Lee et al. 2011, Kinjo et al. 2013). In the field, infestation rates in berries
differed among both blackberry and raspberry cultivars (Burrack et al. 2013), suggesting
that there may be an opportunity for SSPM for D. suzukii management.
Spatial patterns of counts have been described using several different frequency
distribution models and using a combination of the sample mean (x̅) and variance (s2)
calculations. Populations that fit the binomial distribution have s2 < x̅ and display a
regular or uniform distribution. Populations that fit the Poisson distribution have s2 = x̅
and are considered to be random, whereby there is an equal opportunity for each
individual to occupy any point in space. Populations that fit the negative binomial
distribution have a s2 > x̅ and are described as being clumped or contagious
(Southwood and Henderson 2000). In addition to the models described above, there are
several conventional indices that have been used to describe spatial patterns, such as
Green’s Index (Green 1966) and Taylor’s Power Law (Taylor 1961, 1984); however,
these indices do not take into account the effect of sample location.
Spatial Analysis by Distance IndicEs (SADIE) is a method that evaluates the non-
randomness of a population and takes into account the spatial dependency of
individuals in the population (Perry 1995a, 1995b). SADIE calculates the effort it would
take the individuals in the sample to rearrange themselves into a uniform, or regular,
spatial pattern (Perry 1995b, 1996). The SADIE algorithm moves individuals in the
sample population from their initial location to new locations resulting in a population
63
distribution that is increasingly regular (Perry 1995b). The algorithm calculates the
distance to regularity, D, by counting the number of moves required to reach regularity
(Perry 1995a, 1995b). To test for randomness, SADIE generates a number of random
simulations, S, of this process and calculates the distance to regularity of the
simulations, Drand. The number of values of Drand less than the sample distance to
regularity, R, is noted. The probably, Pa, of a result that is aggregated is Pa = R/S.
Indices are used to describe the level of spatial pattern in data. The index of
aggregation, Ia, is calculated by Ia = D/Ea, where D is the distance to regularity of the
sample and Ea is the average value of Drand over S simulations. The values of Ia = 1
indicate a randomly distributed spatial pattern, while Ia > 1 indicates an aggregated
distributed (Perry et al. 1999).
The SADIE output is used to create red-blue contour maps that indicate areas of
population aggregations in terms of patches and gaps. Patches are areas of high counts
of individuals in the population that are close to each other, whereas gaps are areas of
zero or very low counts (Perry et al. 1999). SADIE has been used to evaluate spatial
patterns of many highly mobile insect species, including western flower thrips,
Frankliniella occidentalis (Pergande), in cucumber greenhouses (Park et al. 2009),
blueberry gall midge, Dasineura oxycoccana (Johnson), in blueberries (Rhodes et al.
2014), stinkbugs in cotton (Reay-Jones et al. 2010), and D. suzukii (Klick et al. 2016).
There are benefits to using SADIE for describing spatial patterns compared to
traditional approaches. First, SADIE does not require that the sampling design is a grid
with equally-spaced sampling locations since the locations of samples are included in
the algorithm (Korie et al. 2000). Consequently, non-uniform sampling patterns are
64
useful, for example, when the sampling universe landscape is heterogeneous (Perry
1995a). Second, SADIE operates on the idea that individuals in the population move.
SADIE compares the sample counts to extreme distributions (random and uniform) by
calculating the distance the individuals would have to move to reach these extreme
distributions. These distributions are biologically relevant because they relate
specifically to the spatial behavior of the individuals in the population (Taylor et al. 1978,
Perry 1981, 1995b). Third, SADIE includes the sample locations (spatial data) in the
algorithm. Including the spatial data means that each “move” of an individual from the
sample to an extreme distribution is a distance not just a number (Perry 1995b). Finally,
SADIE can be utilized without much training in more powerful geographic information
systems (GIS) but provides important spatial information for researchers in many fields.
Analysis of insect spatial patterns can be used to guide additional monitoring or
management actions, and has potential to reduce pesticide inputs (Klick et al. 2016).
The objective of this study is to investigate and map the spatial and temporal distribution
of D. suzukii in southern highbush blueberries and their adjacent unmanaged areas.
Materials and Methods
Experimental Site
The experimental site was the same for both 2016-2017 field seasons. The
experimental plot was located at an organic blueberry farm in Citrus County, Florida.
The farm was 4 hectares and was surrounded by unmanaged mixed hardwood and
swamp to the north and west, an unmanaged wooded windbreak (~2 m wide) and
paved road to the south, and blueberries (non-organic) to the east. The plot began in
the unmanaged mixed hardwood and swamp to the north (woods), transected through
the blueberry field and ended in the windbreak (non-woods) to the south (Fig. 4-1). The
65
area of the plot was approximately 1.5 hectares. All of the blueberry bushes within the
experimental plot were approximately 4-6 years old and planted in single rows (2-m
wide running north and south) with pine bark mulch. Bushes were planted 1 m apart in a
mixed manner to enhance cross-pollination. Blueberry bushes were managed using
standard practices including pruning, irrigation, and fertilization.
When the blueberries began to ripen, a grid of 72 traps for capturing adult D.
suzukii was established 15.2 m apart along 6 transects from the north side (woods) to
the south side (non-woods) of the site. On each transect, a single trap was placed in the
wooded and non-wooded areas of the site approximately 1 m into the edge. Due to
variation in the length of blueberry rows, the number of traps along each transect within
the blueberry field was different (Fig. 4-1). Traps were hung in the shaded center of the
blueberry or non-crop bush approximately 1 m from the ground. All trap locations were
georeferenced using a Garmin Dakota 20 (Garmin Ltd., Olathe, Kansas).
Sampling
The Scentry trap and lure system (Scentry Biologicals, Inc., Billings, MT) was
used for trapping adult D. suzukii flies. In place of a liquid drowning solution, an
insecticidal strip (2.54 x 1.27 cm, VaportapeTM, Hercon Environmental, Emigsville, PA)
impregnated with 2,2-dichlorovinyl dimethyl phosphate (DDVP) was placed inside the
trap to kill insects that entered the trap. Insecticidal strips remained in the traps
throughout the study. A white sticky card was cut into a circle (9.25 cm diameter) and
placed into the trap along the bottom with the sticky side facing up to captured knocked
out insects. The white sticky card was replaced weekly with a fresh sticky card. The
adult traps were serviced weekly for 3 and 7 weeks in 2016 and 2017, respectively. In
2016, the season began and ended early due to a warm winter and the grower was
66
ready to hedge the bushes after week 3 of the study. To service the adult traps, the
sticky card samples were covered with plastic wrap, returned to the lab and stored at -
20°C until the samples are ready for processing. Samples were processed by counting
the number of male and female D. suzukii. Trap lures were changed after 3 weeks and
insecticidal strips remained in the traps for the entirety of the study.
Drosophila suzukii larvae were monitored weekly in the field and adjacent areas
at every other trap location (samples). Infestation was evaluated by collecting ripe fruit
from plants surrounding the trap. In 2016, only 20 ripe fruits were collected, which failed
to capture significant infestation. Therefore in 2017, 50 fruits were collected for each
sample. Blueberries were collected randomly from the middle and bottom of bushes
within 3.8 m on either side of the trap along the transect (blueberry row). For samples
from wild hosts in the adjacent areas, ripe fruit (up to 50 fruits) were collected within 2 m
of the trap along the transect. Due to the density of the wooded area, the samples were
collected along the border of the adjacent area.
All fruit samples were processed using two commonly used methods for
assessing berry infestation: the salt method (25 fruit) (Hueppelsheuser 2010, Dreves et
al. 2014, Yee 2014) and incubating method (25 fruit) (Iglesias and Liburd 2017a). Fruit
processed using the salt method were placed in a clear, 1-L food container (Glad,
Oakland, CA) and lightly smashed by applying pressure to berries. A solution of 301.2 g
of table salt (Publix Super Markets Inc., Lakeland, FL) and 3.8 L of deionized water was
poured into the container to completely cover the fruit. The fruit were agitated for ~5 min
to encourage larvae to leave the fruit. Larvae floating on the surface of the solution were
counted with the help of a hand lens. Alternatively, fruit samples processed using the
67
incubation method were placed in individual rearing containers (Glad, Oakland, CA) and
incubated in an environmental chamber for at least 2 wk at 23 °C, 16: 8 light : dark cycle
and ~65% relative humidity. We suspected that the ability of these methods for
detecting D. suzukii in fruit would be different and therefore, used both methods for
comparison.
Data Analysis
The adult D. suzukii captures for years 2016 and 2017 were analyzed using a
generalized linear mixed model (PROC GLIMMIX, SAS v. 9.4, SAS Institute 2016).
These models included a fixed effect (cultivar), random effect (trap), and sampling date
as a type one autoregressive repeated measure effect. The effects of interest to the
study were date, cultivar, cultivar*date, distance and distance*date. The distance term
was the distance from the center of each transect. Distance was centered at zero and
the absolute value included in the model because we expected adult captures and berry
infestation to increase towards the margins of the plot. A check variable, included in the
model to determine whether the distance relationship was different going towards the
different margins (woods and non-woods), was not significant; therefore, the
relationship was the same going towards both margins. The distance*date effect was
not significant, so it was removed from the model for simplification.
Berry infestation was measured by the number of larvae emerged using the salt
test and number of emerged adults using the incubation method. The berry infestation
data in 2016 was insufficient for the multi-factor mixed model analysis used for the adult
capture data because very few larvae or adults were collected from berry samples in
week 3 only. In 2017, the emergence data were analyzed using the same
autoregressive generalized linear mixed model as the adult data with the distance*date
68
effect removed due to non-significance. Dates that had zero infested berry samples and
locations where no fruit were available to collect samples were also removed from the
analysis.
For both the adult capture and infestation analyses, the Restricted Maximum
Likelihood (REML) method was used to estimate the model parameters and the Akaike
Information Criteria (AIC) were used to determine the fit of the model. Tukey-Kramer
adjusted multiple comparisons test was used to separate differences where appropriate
(P ≤ 0.05) since our design was unbalanced (Kramer 1956). All data were square root
transformed to increase the model fit and meet the model assumptions.
Spatial Analysis using Distance IndicEs (SADIE) was used to evaluate the spatial
aggregation of D. suzukii adult flies and berry infestation. SADIE does not allow missing
values in the analysis so any data points with missing values were omitted from the
analysis. For example, no ripe fruit were available in the woods or non-woods adjacent
areas in either year so those samples were removed from the SADIE input dataset. The
SADIE output provides the probability (P) that the distribution is random, an
aggregation index (Ia), which measures how aggregated the distribution is, and a
clustering index (ν) which tells how strongly each count contributes to a patch (area of
high counts) or a gap (area of low values) (Perry 1995a, 1995b). The clustering index is
used to visualize the distribution as red-blue plots, or heat maps, and produces the
patches in gaps (Perry et al. 1999). On the maps, red and blue areas represent
aggregations of high counts and low counts, respectively. The darker an area on the
map, the more aggregated the counts.
69
Results
Adult D. suzukii Captures
In 2016, the mean number of D. suzukii was significantly affected by cultivar,
date, and the date*cultivar interaction (Table 4-1). On 12 May, significantly more adult
flies were captured in Emerald than in Jewel and Windsor but not more than traps in
both field margins (woods and non-woods; Fig. 4-2). The number of adult flies captured
was not significantly affected by distance (Table 4-1). The overall number of adult D.
suzukii captured throughout the study was low with 4 adults being the maximum number
captured in a trap on any date.
In 2017, the number of adult flies captured in Scentry traps was significantly
affected by the cultivar, date, and the cultivar*date interaction (Table 4-1). In general,
the numbers of flies captured in the adjacent areas were higher than in the blueberry
traps and Windsor had the lowest captures each week (Fig. 4-3). On 30 Mar, captures
in both field margins (woods and non0woods) had significantly higher captures than the
Windsor cultivar. On 6 Apr, the woods had significantly higher adult flies than all the
traps in the blueberry cultivars and similar numbers as the non-woods. On 13 Apr, the
non-woods saw higher captures than all blueberry cultivars and the woods margin. On
the week of 20 Apr, significantly more adults were captured in the non-woods than the
traps in the blueberry cultivars and woods, and Jewel had more flies than Windsor. On
27 Apr, there were more flies captured in the woods than in Windsor. The number of
flies captured were not significantly different on 4 May. On the final week, 11 May, the
woods captures were significantly higher than Jewel and Windsor.
The adult captures were also significantly affected by distance (Table 4-1). Traps
captured the lowest numbers in the center of the field and increased the further away
70
from the center the traps were located (Fig. 4-4). The highest numbers were found in
the woods and non-woods margins adjacent to the field.
Berry Infestation
Berry infestation was very low in 2016; no larvae were recovered using the salt
test and only 10 total adult D. suzukii emerged using the incubation method (data not
presented).
In 2017, the number of emerged D. suzukii from infested berry samples using the
incubation method was significantly affected by date and distance but not the cultivar or
the cultivar*date interaction (Table 4-2). There were significantly more emerged D.
suzukii on 6 Apr than 13 Apr, 20 Apr, or 4 May (Table 4-3). The number of emerged
adults increased as distance from the center of the plot increased (Fig. 4-5). The
number of larvae that were extracted from berry samples using the salt method was
significantly affected by the date and distance but not cultivar or the cultivar*date
interaction (Table 4-2). The only sampling date that was significant was 6 Apr when
significantly more larvae were extracted in Jewel than in Windsor (Table 4-3). The
number of larvae found in fruit increased with increasing distance from the center of the
plot (Fig. 4-6). Overall, the number of D. suzukii extracted using the incubation method
was significantly higher than the salt method (Fig. 4-7).
Population Distribution of D. suzukii
In 2016, the SADIE results showed that the distribution of the adult flies was
significantly aggregated on weeks 1 and 3 (Fig. 4-8). In week 1, there was an
aggregation of high counts along the southeastern corner of the plot in the Emerald
cultivar and in the non-woods margin. The aggregation in the southeastern corner of the
plot in week 1 was less aggregated in week 3. A small aggregation was seen along the
71
northeastern field edge and woods margin. Overall, many traps collected zero flies each
week, which is shown in the large aggregations of zeroes throughout most of the
experimental plot in weeks 1 and 3.
In 2017, the SADIE analysis showed a significantly aggregated distribution of
adult D. suzukii captures in weeks 1 through 4 (Fig. 4-9). Small aggregations of flies
were present along the non-woods margin and edge of the field in week 1. These
aggregations were less pronounced in week 2 but developed into a large aggregation in
weeks 3 and 4 that expanded further into the southern side of the field. Aggregations
were present in the woods margin and along the northern edge of the field in weeks 1
and 2 but were less pronounced in the following weeks. Although the distributions were
not significantly aggregated in weeks 5 through 7, there were high numbers of D.
suzukii captured in areas where aggregations of flies were captured earlier in the
season. For example, traps in the non-woods margin and Emerald blueberries in the
southeastern corner of the plot and the woods margin and Emerald in the northeastern
corner of the plot, continued to capture high numbers of D. suzukii throughout the study.
Additionally, there were large areas in the center of the plot where low or no flies were
captured. The berry infestation data was not significantly aggregated at any sampling
week.
Non-Crop Host Identification
Several plant species were identified in the woods and non-woods margins in
both years of the study (Table 4-4). Some plant species were present in both margins,
including greenbrier (Smilax spp.), lantana (Lantana camara), wild grapes (Vitis
rotundifolia), wild blackberry (Rubus spp.), and Virginia creeper (Parthenocissus
quinquefolia). Both margins had the same species richness each year, with 8 and 5
72
species in the non-woods and woods, respectively. However, the total number of
individual plants was higher in the non-woods in 2016 and higher in the woods in 2017.
Several of the plants identified had fruit available at the time of the study however, only
one species, L. camara, had ripe fruit available.
Discussion
Understanding pest spatial and temporal behavior and landscape ecology is
important when developing integrated pest management programs (Kogan 1998, Way
and Van Emden 2000, Bianchi et al. 2006, Cumming and Spiesman 2006). In our study,
D. suzukii distributions were aggregated along the field edges and margins and were
more influenced by the distance to the field edge than the different blueberry cultivars.
Adult captures varied by blueberry cultivar; however, when examining the spatial
patterns of D. suzukii, flies were aggregated at field edges of different cultivars rather
than being aggregated in areas of specific cultivars. Furthermore, adult captures and
berry infestation increased with increasing distance from the center of the field.
Aggregations of insects along agricultural field edges is fairly commonly and has been
documented for Tetranychus urticae (Koch) in cotton (Wilson and Morton 1993),
Brevicoryne brassicae L. in canola fields (Severtson et al. 2015), Diaphorina citri
Kuwayama in citrus groves (Sétamou and Bartels 2015), and Rhagoletis mendax
Curran in blueberries (Rodriguez-Saona et al. 2018). Some of the mechanisms that
have been found to influence edges effects include different microclimate conditions,
with temperature, humidity, solar radiation, and wind being the mechanisms most
studied (reviewed in Nguyen and Nansen 2018), access to resources in adjacent
habitats to field edges (Ponsero and Joly 1998, Tuell et al. 2009, Gruber et al. 2011),
and multi-trophic species interactions such as predation and parasitism (Roland and
73
Kauppp 1995, Ries and Fagan 2003). The mechanisms that explain edge effect of D.
suzukii in our study are unclear. Mark-recapture methods using food-based proteins
have shown that natural populations of D. suzukii visited field margins inhabited by wild
host ‘Himalayan’ blackberry before being captured in adjacent raspberry fields (Klick et
al. 2014, Klick et al. 2016). Swoboda Battarrai (2017) used double-sided interception
traps in field margins and captured flies on both sides, suggesting that flies were moving
in both directions across the field margin. It is possible that adult flies migrate from
adjacent field margins into cultivated crops as susceptible fruit became available in the
field and continue to move bilaterally across the field margin during the season. If flies
are using field margins as refuges visiting these areas multiple times throughout the
season, future management strategies could target these areas.
We also found that there were higher numbers of D. suzukii flies captured in the
field margins than in the blueberry field. This is logical since the field was being
managed using organic insecticides throughout the study period, whereas the field
margins were left unmanaged. These results suggest that D. suzukii may be utilizing
unmanaged margins even while susceptible fruit is available in the field. Most research
has focused on the benefits that field margins have on natural enemies and their impact
on natural biological control in the field (Altieri and Schmidt 1986, Landis et al. 2000,
Marshall and Moonen 2002, Bianchi et al. 2006, Roubos et al. 2014); however, several
recent studies have shown how adjacent unmanaged habitats are benefitting pests. For
example, upland forests habitats adjacent to blueberry fields had a positive effect on R.
mendax fly numbers in the field (Rodriguez-Saona et al. 2018) and stink bug injury
(including the invasive Halyomorpha halys) was higher in tomato fields with a larger
74
forested edge (Rice et al. 2014). Drosophila suzukii adult flies were also captured earlier
in raspberry on farms with larger wooded edges (Pelton et al. 2016). One reason for the
high numbers in adjacent areas may be the availability of alternative hosts. Drosophila
suzukii has been shown to infest numerous non-crop fruits found in field margins in
North America (Lee et al. 2015), Europe (Arnó et al. 2016, Kenis et al. 2016), and Japan
(Kanzawa 1934, 1939). The presence of non-crop hosts can become sources of pest
population build-up if left unmanaged and can increase pressure in the field, especially
along field edges. Klick et al. (2016) found that populations of D. suzukii were higher in
blackberry fields adjacent to margins with ‘Himalaya’ blackberry (Rubus armeniacus)
than in fields adjacent to margins without blackberry. Rhagoletis mendax populations in
lowbush blueberry fields were found to be influenced by margins with bunchberry,
Cornus canadensis (Renkema et al. 2014). In our study, of the many fruit-bearing plants
that were identified in the margins, only Lantana camara had thin-skinned ripe fruit
available. However, none were found infested with D. suzukii in the field and when
mature female D. suzukii were exposed to L. camara in the lab, eggs were laid on the
surface of the fruit only (Iglesias unpublished), suggesting that L. camara may not be a
suitable host for D. suzukii. Other studies have also captured D. suzukii when ripe fruit
were not available (Harris et al. 2014b), which could indicate that D. suzukii is using
these field margins for other reasons.
Another reason D. suzukii populations were high in the margins could be the
presence of dietary supplements. Plants species in field margins may provide sugar
resources for D. suzukii in the form of extrafloral nectaries (Chin et al. 2013) or flower
blossoms (Tochen et al. 2016). Also, a diversity of yeasts are present in natural habitats
75
which play important dietary roles with Drosophila species by providing necessary
protein and lipid sources (Lachance 2006, Hardin et al. 2015, Hamby and Becher 2016).
Unmanaged field margins may also provide sites for overwintering. For example, plum
curculio, C. nenuphar, will migrate from apple orchards after the season into adjacent
woodland areas to hibernate in leaf litter (Lafleur et al. 1987). Drosophila suzukii has a
“reproductively quiescent” overwintering stage that is highly melanized and cold-tolerant
(Dalton et al. 2011, Gutierrez et al. 2016, Shearer et al. 2016). Studies suggest that D.
suzukii may overwinter as an adult in protected microhabitats (Kanzawa 1939, Zerulla et
al. 2015), which wooded natural habitats may provide. This could have implications for
D. suzukii population dynamics, monitoring, and management in the early season
(Pelton et al. 2016).
We evaluated fruit infestation using two different sampling methods, salt
extraction and berry incubation, both of which are used throughout the D. suzukii
literature (Burrack et al. 2015, Diepenbrock et al. 2016, Klick et al. 2016, Diepenbrock et
al. 2017, Iglesias and Liburd 2017a, 2017b, Rice, Short, et al. 2017). The salt extraction
method is recommended for use by growers, consultants, and Extension personnel
because results can be obtained immediately in the field (Isaacs et al. 2013, Liburd and
Iglesias 2013, Burrack 2014), whereas in the incubation method D. suzukii must be
allowed to develop to adults prior to counting, which can take 10-14 d (Kanzawa 1939,
Emiljanowicz et al. 2014, Tochen et al. 2014). However, the results from our study
showed that the salt extraction method was inferior to the incubation method at
detecting infestation. This discrepancy could be the result of sample size. In 2016, only
10 fruit were selected for each processing method (20 total per sample). Since no
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larvae were detected in any of the samples, the sample size was increased to 25 fruit
per method (50 total per sample) in 2017. The increased infestation rates we found in
2017 may have been the result of actual infestation in the field or the increased sample
size. However, adult fly numbers were also higher in 2017 so infestation was likely to
have been higher as well. The poor performance of the salt extraction method could
also be the result of low infestation rates and the small size of the second and third
instar larvae. First and second instar Drosophila larvae are ~0.6 and ~2.1 mm long,
respectively (Kanzawa 1939), and can be easy to miss when searching through fruit
pulp using the salt extraction method. A standardized method for processing fruit
samples using the salt extraction method has recently been developed to increase
detection of small early instar larvae (Van Timmeren et al. 2017). Since there is a zero-
tolerance for larvae in fruit, a fruit sample processing method that accurately detects
larvae is essential.
The results of our study provide understanding of the landscape level behavior of
a highly mobile invasive pest. Understanding how insects move within the landscape
and what mechanisms contribute to edge-biased distributions of insect pests can be
used to optimize monitoring and site-specific management strategies. Some of these
strategies target the pests as they move from margins into the field such as border
sprays (Chouinard et al. 1992, Trimble and Vickers 2000, Carroll et al. 2009, Klick et al.
2016, Iglesias and Liburd 2017a), attract and kill spray baits (Prokopy et al. 2003, Rice
et al. 2017), perimeter mass trapping (Cohen and Yuval 2000), and monitoring
programs (Prokopy et al. 2003). Future studies would benefit from investigating the
77
mechanisms involved in D. suzukii spatial distributions and how management strategies
can target field edges.
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Table 4-1. Results of the generalized linear mixed model ANOVAs testing for significance of cultivar, date, cultivar*date interaction, and distance effects for adult D. suzukii capture data in 2016 and 2017.
a Degrees of Freedom (DF) are reported as numerator, denominator Table 4-2. Results of the generalized linear mixed model ANOVAs testing for
significance of cultivar, date, cultivar*date interaction, and distance effects for berry samples processed using the salt extraction and incubation methods in 2017.
Method Effect DFa F P-Value
Salt Extraction cultivar 2, 57 1.13 0.3317
date 3, 57 15.63 < 0.0001*
cultivar*date 6, 57 1.92 0.0932
distance 1, 57 7.4 0.0086*
Incubation cultivar 2, 81 2.03 0.1373
date 4, 81 3.67 0.0084*
cultivar*date 8, 81 0.71 0.6815
distance 1, 81 4.06 0.0471* a Degrees of Freedom (DF) are reported as numerator, denominator
Year Effect DFa F P-Value
2016 cultivar 4, 121 3.06 0.0193*
date 2, 121 3.83 0.0244*
cultivar*date 8, 121 2.25 0.0285*
distance 1, 121 0.17 0.6846
2017 cultivar 4, 360 5.98 0.0001*
date 6, 360 7.75 < 0.0001*
cultivar*date 24, 360 3.47 < 0.0001*
distance 1, 360 5.13 0.0242*
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Table 4-3. Emerged adults (mean ± standard error) collected from ripe blueberry samples using the incubation method in the 2017 D. suzukii movement study in organic blueberries.
Effect Level Incubationa Salt Extractionb
Date 3/30/2017 0.360 ± 0.174ab 0.004 ± 0.003b 4/06/2017 1.123 ± 0.238a 0.112 ± 0.025a 4/13/2017 0.111 ± 0.066b -* 4/20/2017 0.037 ± 0.037b 0.002 ± 0.002b 4/27/2017 - - 5/04/2017 0.067 ± 0.067b 0.020 ± 0.013b Cultivar Emerald 0.461 ± 0.115 0.029 ± 0.015 Jewel 0.346 ± 0.134 0.041 ± 0.011 Windsor 0.000 ± 0.000 0.039 ± 0.031
Columns with different letters indicate significant differences using Tukey-Kramer test at P ≤ 0.05. *Missing values are the result of removal of the corresponding week from analysis because no fruit were infested. a Reported as emerged adults. b Reported as extraction larvae.
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Table 4-4. Plant species identified in the woods and non-woods margins of the organic blueberry field in the D. suzukii movement study. All plants bare thin-skinned fruits at various times of the year.
Year Family Species Name Common Name Non-Woods Woods Total
Fruit Present
Ripe Fruit Present
2016 Adoxaceae Sambucus spp. Elderberry - 1 1
Ericaceae Vaccinium spp. Blueberry 1 - 1
Phytolaccaceae Phytolacca
americana Pokeweed - 1 1
Rosaceae Prunus caroliniana Laurel cherry 2 - 2 Yes
Rosaceae Rubus spp. Wild blackberry 4 - 4
Rubiaceae Paederia foetida Skunkvine 8 - 8 Yes
Rutaceae Citrus spp. Citrus tree 1 - 1
Smilacaceae Smilax spp. Greenbrier 156 47 203 Yes
Verbenaceae Lantana camara Lantana 9 64 73 Yes Yes Vitaceae Vitis rotundifolia Wild grape 18 36 54 Yes
Totals Individual Plants 199 149 348
Different Species 8 5
2017 Bignoniaceae Campsis radicans Trumpet Creeper 4 - 4
Rosaceae Prunus caroliniana Laurel cherry 5 - 5 Yes
Rosaceae Rubus spp. Wild Blackberry 6 18 24
Rosaceae Prunus spp. Prunus Tree 2 - 2 Yes
Smilaceae Smilax spp. Greenbrier 28 61 89 Yes
Verbenaceae Lantana camara Lanatana - 59 59 Yes Yes
Vitaceae Vitis rotundifolia Wild Grape 5 33 38 Yes
Vitaceae Ampelopsis arborea
Peppervine 5 - 5 Yes
Vitaceae Parthenocissus quinquefolia
Virginia Creeper 6 10 16 Yes
Totals Individual Plants 61 181 242
Different Species 8 5
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Figure 4-1. Drosophila suzukii distribution study experimental site at an organic blueberry farm in Citrus County, FL. Circles represent trap locations. Red circles at trap locations are where berry samples are collected.
82
Figure 4-2. Mean number of adult D. suzukii captured in several blueberry cultivars and
unmanaged field margins in 2016. * Indicates significant differences among the cultivars in the corresponding week with Tukey Kramer at P ≤ 0.05.
Figure 4-3. The mean number of adult D. suzukii flies captured in several blueberry
cultivars and unmanaged field margins in 2017.
*
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
05/12/16 05/16/16 05/20/16 05/24/16
Me
an
Ad
ult
SW
D C
ap
ture
d
Date
Emerald
Jewel
Non-Woods
Windsor
Woods
*
* *
*
* *
0
5
10
15
20
25
30
Me
an
Ad
ult
SW
D C
olle
cte
d
Date
Emerald
Jewel
Non-Woods
Windsor
Woods
83
Figure 4-4. Linear relationship between the number of adult D. suzukii captured and the
corresponding sample location based on the distance from the center of the blueberry field. Negative and positive distances move towards the woods and non-woods margins, respectively. CI = Confidence Interval.
0
10
20
30
40
50
60
-80 -60 -40 -20 0 20 40 60 80
D. s
uzu
kii A
du
lts
Ca
ptu
red
Distance (m)
95% CIs Trendline
84
Figure 4-5. Linear relationship between adult D. suzukii emerged from infested fruit
using the incubation method and sample location based on distance from the center of the blueberry field. Negative and positive distances move towards the woods and non-woods margins, respectively. CI = Confidence Interval.
Figure 4-6. Linear relationship between extraction D. suzukii larvae from infested fruit
using the salt method and sample location based on distance from the center of the blueberry field. Negative and positive distances move towards the woods and non-woods margins, respectively. CI = Confidence Interval.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
-60 -40 -20 0 20 40 60
Em
erg
ed
Ad
ult
D. s
uzu
kii
Distance (m)
Trendline 95% CIs
0.00
0.10
0.20
0.30
0.40
0.50
-60 -40 -20 0 20 40 60
Ex
tra
cte
d D
. s
uzu
kiii
La
rva
e
Distance (m)
Trendline 95% CIs
85
Figure 4-7. The mean number of D. suzukii extracted from infestation blueberry samples
in 2017 using the incubation and salt extraction methods. Bars with different letters indicate significant differences using the Welch’s t-Test for unequal variances (P ≤ 0.05).
a
b
0.00
0.10
0.20
0.30
0.40
0.50
Incubation Salt Extraction
Me
an
D. s
uzu
kii /
Fru
it
Processing Method
86
Figure 4-8. Red-blue plots showing population distribution of adult D. suzukii flies captured in Scentry traps in organic blueberries in 2016. Beginning from left to right are sampling weeks 1 through 3. Red areas = high count aggregations, blue areas = low count aggregations. P < 0.05 indicates a significantly aggregated distribution.
87
Figure 4-9. Red-blue plots showing population distribution of adult D. suzukii flies captured in Scentry traps in organic
blueberries in 2017. Beginning from top left are sampling weeks 1 through 7. Red areas = high count aggregations, blue areas = low count aggregations. P < 0.05 indicates a significantly aggregated distribution.
88
CHAPTER 5 CULTURAL CONTROL AND ALTERNATIVE SPRAY TECHNIQUES FOR
DROSOPHILA SUZUKII MANAGEMENT
Drosophila suzukii (Matsumura) (Diptera: Drosophilidae) is an invasive fruit fly
pest of small and stone fruits, that has spread throughout much of North America and
Europe (Walsh et al. 2011, Burrack et al. 2012, Cini et al. 2012). The female D. suzukii
has a modified ovipositor with large serrations that allows her to cut into the skin of
undamaged (due to physical or pest injury), ripening fruits and deposit an egg under the
skin surface (Lee et al. 2011, 2015a). The larvae hatch and feed on the fruit flesh and
associated yeasts (Starmer and Aberdeen 1990, Walsh et al. 2011, Hamby et al. 2012),
causing fruit to become unmarketable. Economic losses have been significant in
blueberries, caneberries, cherries, and strawberries in fruit-producing regions of North
America as a result of direct crop damage and increase costs of control (Bolda et al.
2010, Goodhue et al. 2011, eFly 2012).
Drosophila suzukii, also known as the spotted wing drosophila (SWD), is highly
mobile and will migrate in search of resources and suitable habitats (Mitsui et al. 2010,
Klick et al. 2016). Many berry farms in Florida are surrounded by unmanaged, semi-
natural habitats that contain non-crop hosts with fleshy, thin-skinned fruits that D.
suzukii may utilize, in addition to its commercial hosts (Iglesias, Liburd, and Grunwald
unpublished, Gilbert and Stys 2004). Drosophila suzukii has been known to infest wild
blackberry (Rubus spp.) and grape (Vitis spp.), black elderberry (Sambucus nigra),
honeysuckle (Lonicera spp.), and black nightshade (Solanum nigrum) (Poyet et al.
2014, Lee et al. 2015b, Arnó et al. 2016, Kenis et al. 2016). Non-crop hosts provide
food, oviposition sites, and protection during the non-crop season after which, D. suzukii
moves from adjacent unmanaged habitats into cultivated fields as resources become
89
abundant (ripening of berries) (Liburd et al. 2015, Klick et al. 2016). Large percentages
of woodland habitat in the surrounding landscape correlates with D. suzukii appearing
earlier in cultivated fields (Pelton et al. 2016), necessitating earlier management actions
be taken during the cropping season. Furthermore, in warmer geographic regions such
as the southeastern U.S., there is greater resource continuity, with the availability of
cultivated host crops throughout most of the year (e.g. December through August in
Florida). On farms where multiple host crops are grown in succession, there is potential
for D. suzukii to move from one crop to another (e.g. blueberry to caneberry in the north
and strawberry to blueberry in the south).
Management tactics that take advantage of this behavior can contribute to a
successful, long-term integrated pest management (IPM) program for D. suzukii. Border
sprays are selectively applied along the perimeter of a field and can be useful at
delaying or preventing pests migrating from surrounding environments. Border sprays
have been used as an alternative to cover or every-row sprays and may reduce
pesticide residues on the crop and for protection of within field non-target organisms
including pollinators. Border sprays can also reduce the potential for fruit knockdown
due to application equipment (Chouinard et al. 1992, Prokopy et al. 2003, Carroll et al.
2009, Klick et al. 2016). In the past border sprays have been used successfully to
control plum curculio (Conotrachelus nenuphar) (Chouinard et al. 1992), brown
marmorated stink bug (Halyomorpha halys) (Blaauw et al. 2015), apple maggot
(Rhagoletis pomonella) and codling moth (Cydia pomonella) (Trimble and Vickers 2000)
in orchard systems. Since D. suzukii is thought to utilize non-crop hosts in the
surrounding areas of fields and to migrate into fields as resources become available
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(Liburd et al. 2015, Klick et al. 2016), we hypothesize that the establishment of a
pesticide border around the field will reduce D. suzukii population within the field.
Cultural control tactics are part of an IPM program and can be used to reduce the
use of insecticides. Organic growers rely heavily on cultural controls for D. suzukii
management due to the limited number of effective organic chemical tools registered for
D. suzukii (Bruck et al. 2011, Van Timmeren and Isaacs 2013). Currently, soil tillage has
not been evaluated for D. suzukii management. Soil tillage manages weeds by
uprooting them or by burying seeds to depths that will reduce germination and
development (Ozpinar 2006, Rial-Lovera et al. 2016). The mixing effect of tillage on
soils can also reduce soil moisture and bury pest larvae (Blevins et al. 1971, Brandt
1992). Drosophila suzukii spends its larval stage inside in the host fruit where it is
protected from desiccation, sun exposure, and predation, after which it will pupate
inside or partially inside the fruit and in the soil (Walsh et al. 2011, Woltz and Lee,
2017). Infested fruit can fall to the ground due to rot, during harvest, or as a result of
pesticide application equipment (Klick et al. 2016), prior to adult emergence. The
objective of this study was to evaluate the effect of between-row tillage and border
sprays as alternative control tactics for management of D. suzukii in organic
blackberries.
Materials and Methods
Field Setup
The experiments were conducted during 27 June to 16 July 2014 and 29 May to
25 June 2015. The 2014 experiment was started late in the season and therefore was
only carried out for three weeks (4 weeks in 2015). Experimental plots were located on
an organic commercial blackberry farm in Alachua County, Florida
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(29°35′17″N 82°5′2″W). The experiment was established in blackberry, Rubus fruticosus
L. (Rosaceae) which was located on the south side of the farm. In years 1 and 2, the
plots were adjacent to an unmanaged, woody habitat on the south side and organic
southern highbush blueberries (Vaccinium corymbosum L. x V. darrowi) to the north.
Plots were situated from north to south because D. suzukii had been captured in traps
in both adjacent areas and the pressure was similar. In year 1, a water runoff area
bordered the plot to the west and blackberries to the east. In year 2, the plot was
adjacent to blackberries to the west and an open field to the east. The blackberry plants
were 4-5 years old and planted 0.9 m apart with 3.7-m aisles between rows. Plants
were trellised with wires on which to secure canes at heights of 1 and 2 m. Plants were
managed using standard grower practices that included pruning, fertilizer, and irrigation
(Andersen and Crocker 2014). Aisles were mowed on a regular basis as part of the
grower’s management program. No insecticides (other than those used in the
treatments) were applied to the plots during the experiments. There is a natural
infestation of D. suzukii because this species has been captured at this farm in previous
years (Liburd et al. unpublished data).
The experiment was a completely randomized two-factor split plot design with 8
replicates. The whole plot treatment factors were with border spray or without border
spray, and subplot factors were till and no till (control). The individual plot size was 0.16
ha and consisted of three to five rows of organic blackberries (var. Natchez). Each plot
was separated by a 6.1-m-wide buffer zone of unpaved road (Fig. 5-1).
Insecticide Applications
All applications were made using an air blast sprayer (model: storm 828,
Leinbachs Inc., Rural Hall, NC. Spinosad (Entrust®, Dow AgroSciences, Indianapolis,
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IN). A pre-treatment application at the manufacturers labelled rate, 0.4 L/ha, was made
to all plots 7 days prior to the start of the experiment. This was done to help standardize
D. suzukii populations in each plot since the experiments were started when some
ripening fruit were already present in the field. Spinosad is registered and
recommended for use in organic blackberries in Florida for control of adult D. suzukii
flies only and has a residual toxicity of 7 days (Van Timmeren and Isaacs 2013, Liburd
and Iglesias 2013). Pre-experimental trap captures and fruit samples (2015 only) were
taken and no differences in adult D. suzukii or fruit infestation were found among the
treatment plots. In border treatments, an insecticide, Azera®, with active ingredients of
azadirachtin (1.2%) and pyrethrins (1.4%) (MGK, Minneapolis, MN) was applied three
times as a border spray beginning 27 June 2014 and 29 May 2015 at a 7 to 10-d
interval at the manufacturers labeled rate of 2.4 L/ha. Applications were made with only
one side of the airblast sprayer active, directed into the crop. The pressure of the
sprayer was adjusted so that the spray distance was approximately 3 m into the
blackberry planting.
Soil Tillage
A 5-ft rototiller (Howse Implement Company, Inc. East Laurel, MS) was used to
till the aisles of the subplot treatments designated “till”. The rototiller speed was ~1.6
km/min at a depth of ~15 cm. The first till was performed at the start of the experiment
and was repeated once at 7- and 14-d intervals in 2014 and 2015, respectively. The
subplots designated as “no till” were left untilled for the entire study (control).
Sampling
In 2014 and 2015, traps for capturing adult D. suzukii were constructed using 1-L
clear plastic cups with lids and 51, 4-mm holes around the center of the cup (Iglesias et
93
al. 2014). Traps were baited with 200 mL of yeast and sugar-water mixture. The bait
was made with 4.2 g of yeast (Fleischmann’s RapidRise, ACH Food Companies, Inc.,
Cordova, TN), 11 g white granulated sugar (Publix, Lakeland, FL), 200 mL tap water,
and 0.3 mL odorless dish detergent (Palmolive Pure and Clear, Colgate-Palmolive
Company, New York, NY). Bait was premixed in bulk at the Small Fruit and Vegetable
IPM (SFVIPM) Lab at the University of Florida and brought to the field (approximately 1
h later). Eight traps were hung randomly throughout each subplot (32 total) by securing
them 1 m from the ground inside the blackberry bush. Traps were serviced weekly for
three (2014) and four (2015) weeks by replacing bait content with fresh bait and
transporting samples back to the SFVIPM lab for male and female D. suzukii
identification.
Fruit samples were collected weekly to evaluate fruit infestation by D. suzukii in
2015 only. Fruit samples were not taken in 2014 due to low fruit load on the grower’s
farm. Approximately 100-200 g of ripe blackberries were collected from four randomly
selected sample locations in each subplot. Fruit was collected before the application of
the border sprays the same morning, 7 to 10 days after the previous application. Fruit
samples were weighed and placed in plastic rearing containers with mesh lids (Glad,
Oakland, CA) and were kept in incubators maintained at 23°C, 16:8 light: dark cycle and
~65% relative humidity for two weeks to allow D. suzukii adults to emerge. Male and
female D. suzukii were identified and reported as number of D. suzukii emerging per kg.
Natural enemies were assessed using yellow sticky cards (15.2 by 20.3 cm,
Pherocon AM, Great Lakes IPM, Vestaburg, MI) in the final week of 2015 only. Cards
were established in four randomly selected locations in each subplot and were attached
94
to the blackberry plant 2 m from the ground using a twist tie. After 7 d in the field, the
cards were transported back the laboratory where pests and natural enemies were
identified.
Data Analysis
Data from the field studies in 2014 and 2015 were analyzed separately. Data
were transformed when necessary to normalize the distribution and homogenize the
variances. Transformed data were analyzed using a two-way repeated measures
ANOVA with treatment, week, and treatment*week as the fixed effects. Treatment
differences were separated using Tukey’s Honestly Significant Differences (HSD) test.
All analyses were completed using JMP Pro Software (ver. 11.1.1, SAS Institute 2013).
Differences were considered significant when P ≤ 0.05.
Results
In the 2014 study, treatment had a significant effect on the number of adult D.
suzukii captured in traps (F = 4.12; df = 3, 83; P = 0.0089). However, the treatment
interaction with time (week) was not significant (F = 1.64; df = 6, 83; P = 0.1465). Border
spray treatments, with and without the addition of tillage, captured significantly fewer D.
suzukii than the unsprayed, no till treatment (control, Fig. 5-2). The unsprayed treatment
with tillage was not significantly different than any of the other treatments. The addition
of tillage did not have a significant effect on the number of D. suzukii captured. In 2014,
there were more female flies captured in the control than the border treatments (F =
4.48; df = 3, 83; P = 0.0058) but there were no differences in male captures (F = 0.39; df
= 3, 83; P = 0.759, Table 5-1).
In 2015, treatment had an effect on the mean D. suzukii captured over time (F =
2.73; df = 9, 112; P = 0.0065, Fig. 5-3). The mean number of D. suzukii was significantly
95
different among the treatments in week 1 (F = 4.23; df = 3, 28; P = 0.0138), week 3 (F =
3.97; df = 3, 28; P = 0.0178), and week 4 (F = 5.87; df = 3, 28; P = 0.0031). The pattern
of adult D. suzukii captures was similar for all three weeks as well as the results from
the 2014 study. The mean number of D. suzukii in both border spray treatments was
significantly lower than the unsprayed, no till treatment (control). As in 2014, the
addition of tillage did not have a significant effect on the number of adult flies captured.
In 2015, both female (F = 2.97; df = 9, 112; P = 0.0033) and male (F = 2.09; df = 9, 112;
P = 0.0361) fly numbers also varied by week and treatment (Table 5-1). The number of
female flies was greater in the control than in all other treatments in week 4 (F = 6.59; df
= 9, 112; P = 0.0016). There were significantly more male flies captured in the control
than in either of the border spray treatments in week 4 (F = 5.77; df = 9, 112; P =
0.0033). The number of males in the tilled treatment without the border spray was not
different than the other treatments.
In 2015, treatment had a significant effect on berry infestation by D. suzukii over
time (F = 3.54; df = 9, 47; P = 0.002, Fig. 5-4). The mean number of emerged D. suzukii
kg-1 of blackberries was significant among treatments in week 4 only (F = 71.90; df = 3,
12; P < 0.0001). In week 4, both border spray treatments had significantly fewer D.
suzukii emerge kg-1 than the unsprayed treatments.
Yellow sticky cards were evaluated for pests and natural enemies in 2015 only
(Table 5-2). Only 1 female D. suzukii was found in all treatments. More Thripidae and
Aphidae were found in the tilled border treatments, but were not significant. There were
significantly more Cicadellidae in the control than the tilled border treatment. A diverse
array of parasitoid families were identified on the sticky card samples; the most common
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being Encyrtidae, Platygastridae, and Aphelinidae. However, parasitoids did not differ
by treatment.
Discussion
Our results confirmed our hypothesis and show that border sprays can be utilized
to reduce populations of D. suzukii in organic blackberry fields. We found that border
spray treatments, with and without the addition of soil tillage had fewer D. suzukii than
plots without border sprays. Border sprays can be useful against pests that migrate from
surrounding environments (Chouinard et al. 1992, Trimble and Solymar 1997, Blaauw et
al. 2015. Though we did not evaluate fly presence in surrounding areas or migration in
this study, D. suzukii has been shown to utilize wild hosts in wooded areas surrounding
blueberries, blackberries, and raspberries (Lee et al. 2015b, Liburd et al. 2015, Briem et
al. 2016) and as a result, can increase pressure on adjacent crops (Klick et al. 2016).
Klick et al. (2016) found that D. suzukii captures were higher in raspberry fields that
were adjacent to wild ‘Himalaya’ blackberry (Rubus armeniacus Focke) than fields that
were not in close proximity. In unmanaged, semi-natural areas adjacent to cultivated
blueberries, a decrease in D. suzukii adults coincided with an increase of adults in the
blueberry fields (Liburd et al. 2015). Furthermore, D. suzukii was captured earlier in
raspberry fields when adjacent to wooded areas containing wild host plants (Pelton et
al. 2016).
Since border sprays can target pests migrating from adjacent environments,
timing of applications must be considered. Border sprays used for codling moths in
apples are applied during periods when larvae are expected to be hatching in adjacent
areas and adult flies are active as indicated by monitoring traps (Trimble and Vickers
2000). Applications of border sprays for control of plum curculio in apples are made
97
during a several-week period when adults are on the ground along the perimeter of the
orchard before entering the orchard itself (Chouinard et al. 1992). Border sprays may be
most effective for controlling D. suzukii when applied at the beginning of the season
when flies are beginning to migrate into the field from adjacent areas. Early season
border sprays can save effective reduced-risk insecticides with limited applications for
later use such as at peak harvest when D. suzukii population pressure is highest and
the need for insecticide application is the greatest. One of the challenges to border
spray timing is that available monitoring tools using various food-based lures and cup-
like traps differ in their ability to detect the first presence of D. suzukii in the field
(Basoalto et al. 2013, Iglesias et al. 2014, Burrack et al. 2015). Monitoring with current
tools alone may not provide an accurate early warning of fly movement into the field.
Temperature-dependent models are being developed for D. suzukii and can be useful
for predicting when D. suzukii will appear (Wiman et al. 2014). Future studies
investigating the use of border sprays should focus on how to better time border sprays
to coincide with movement of the flies into and out of the fields.
An effective IPM program must be sustainable, conserve natural enemies, and
exert little or no impact on non-target species. Some insecticides used for managing D.
suzukii, may have negative impacts on pollinators and natural enemies (Biondi et al.
2012, Barbosa et al. 2015). Border sprays serve as an insecticidal tactic that can reduce
the negative impacts on beneficial insects while still providing some level of control for
key pests (Van Driesch et al. 1998, Klick 2016). Results from our study showed that
neither border sprays nor soil tillage affected the population of predators or parasitoids
within the blackberry fields. Beneficial insects within the interior of the field could
98
continue providing pollination services and natural control of other blackberry pests
such as sap beetles (Nitidulidae), flower thrips (Thripidae), and scarab beetles
(Scarabidae).
We chose the active ingredients pyrethrins and azadirachtin for the border spray,
because this combination of compounds is labeled for organic use, has a short reentry
interval (12 h), no pre-harvest interval and can be used in rotation with other
compounds for D. suzukii control such as spinosad (IRAC class 5). Pyrethrins (IRAC
class 3A) are sodium channel modulators, a class of insecticides that have shown to
have some efficacy against D. suzukii in lab and field trials (Bruck et al. 2011, Van
Timmeren and Isaacs 2013). However, most insecticides in class 3A are not approved
for organic use. On their own, pyrethrins are commonly used in rotational programs for
D. suzukii in organic production, though with fair to good control in systems with high fly
pressure (Bruck et al. 2011, Van Timmeren and Isaacs 2013). Azadirachtin (IRAC Class
UN) is a botanical insecticide and a derivative of neem oil that acts as an antifeedant
and insect growth regulator (Dayan et al. 2009). Neem oil has insecticidal effects on D.
suzukii (Bruck et al. 2011, Erland et al. 2015) and has been associated with reduced
lethal effects on natural enemies (Beloti et al. 2015, Gontijo et al. 2015, Nikolova et al.
2015). The combination of pyrethrins and azadirachtin can serve as an insecticide with
multiple modes of action and has been shown to be effective at reducing both adult D.
suzukii captures in the field and larval infestations in blackberries and blueberries
(Iglesias and Liburd unpublished). Other approved organic insecticides could also be
used in a border spray application.
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Collecting and disposing of fallen fruit can be labor intensive, even for small
operations. In both of our field studies, tilling the aisles between the rows of blackberries
to bury fallen fruit, with or without the border spray, did not have a significant effect on
adult captures or larval infestation. However, data from both years of our study showed
a similar pattern amongst the treatments. It is possible that the effect of soil tillage is
minimal and was not captured in this study. Burying infested fruit in the lab, has shown
to be effective at reducing the emergence of D. suzukii adults by 70-100% when buried
5 – 10 centimeters below the ground (Rodriguez-Saona and Abraham unpublished).
This shallow tillage depth can be reached by standard tillers owned by most farmers.
However, whether fallen fruit is fully buried using these tillage practices is unknown and
should be further investigated. It is also unknown whether fallen fruit reaches the aisles
or remains under the bush, where tilling is impossible.
Overall our study confirms that border sprays can be an effective method of
control for D. suzukii. In addition, border sprays have the potential to reduce the amount
of insecticide sprayed on the field, insecticide effects on natural enemies, and overall
cost of management. Soil tillage may be a possible method for reducing emerging D.
suzukii populations from infested fruit in the field; however, further investigation as to its
effect is needed. Border sprays should be incorporated into an IPM program for
managing D. suzukii populations. New questions arise that need further research,
including whether border sprays are as effective in high pressure systems and how to
maximize the effect of border sprays with application timing based on D. suzukii
movement. Furthermore, quantifying fruit fall and burial would help to elucidate the
economic benefits of soil tillage versus current grower practices of fruit removal.
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Table 5-1. Mean (±SE) female and male adult SWD captured in 2014 and 2015 blackberry studies.
2014 2015
Entire Study† Week 1 2 3 4
Female Female
Border Till 0.4 ± 0.1b 0.0 ± 0.0 0.9 ± 0.3 0.0 ± 0.0 0.1 ± 0.1b
No Till 0.6 ± 0.3b 0.0 ± 0.0 0.5 ± 0.2 0.3 ± 0.3 0.8 ± 0.3b No Border Till 0.8 ± 0.3ab 0.4 ± 0.2 0.3 ± 0.2 0.6 ± 0.3 0.8 ± 0.4b
No Till 1.5 ± 0.4a 0.4 ± 0.2 0.4 ± 0.2 0.9 ± 0.4 3.6 ± 1.0a
Male Male Border Till 0.2 ± 0.1 0.1 ± 0.1 0.5 ± 0.4 0.0 ± 0.0 0.1 ± 0.1b
No Till 0.2 ± 0.1 0.0 ± 0.0 0.0 ± 0.0 0.1 ± 0.1 0.0 ± 0.0b No Border Till 0.3 ± 0.1 0.3 ± 0.2 0.0 ± 0.0 0.5 ± 0.4 0.5 ± 0.3ab
No Till 0.3 ± 0.1 0.5 ± 0.3 0.1 ± 0.1 0.4 ± 0.2 3.4 ± 1.2a
Values followed by different letters are significantly different across treatments within sex and year. Differences are considered significant when P ≤ 0.05. †Treatment*week interaction was not significant for female (F = 1.98; df = 6, 83; P = 0.0773) or male SWD (F = 0.48; df = 6, 83; P = 0.8248).
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Table 5-2. Mean (±SE) arthropods identified on yellow sticky card traps during final week of the 2015 blackberry study.
Border No Border
Arthropod Till No Till Till No Till F, P
Pests SWD Female 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 1.00, 0.436
SWD Male 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 ̶
SWD Total 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 1.00, 0.436
Z. indianus 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 ̶
Other Drosophilidae 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 ̶
Cercopidae 0.5 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 3.00, 0.088
Thripidae 38.0 ± 6.9 38.8 ± 14.3 19.0 ± 7.6 29.8 ± 12.1 0.60, 0.630
Aleyrodidae 1.8 ± 0.3 0.8 ± 0.5 3.8 ± 1.3 3.0 ± 1.4 1.67, 0.242
Aphidae 5.5 ± 1.8 4.0 ± 1.3 1.5 ± 0.6 0.8 ± 0.5 3.29, 0.072
Elateridae 0.5 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 3.00, 0.088
Cicadellidae 3.3 ± 1.7b 4.5 ± 1.6ab 8.3 ± 2.9ab 13.8 ± 2.4a 4.14, 0.042* Natural Enemies
Anthocoridae (Orius spp.) 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 1.00, 0.436
Aranae 1.3 ± 0.8 1.0 ± 1.0 0.5 ± 0.3 0.0 ± 0.0 0.65, 0.604
Ceraphronidae 1.0 ± 0.4 0.3 ± 0.3 0.0 ± 0.0 0.3 ± 0.3 2.45, 0.130
Signiphoridae 2.0 ± 0.4 0.3 ± 0.3 1.0 ± 0.6 0.3 ± 0.3 3.41, 0.066
Encyrtidae 10.8 ± 3.2 26.3 ± 6.1 15.3 ± 5.1 13.0 ± 1.5 2.31, 0.145
Platygastridae 15.3 ± 1.0 19.3 ± 4.2 10.5 ± 2.3 12.8 ± 4.0 1.66, 0.243
Aphelinidae 0.5 ± 0.3 19.3 ± 11.0 1.5 ± 0.6 0.5 ± 0.5 2.74, 0.105
Ichneumonidae 0.3 ± 0.3 0.3 ± 0.3 0.8 ± 0.8 1.0 ± 0.7 0.48, 0.705
Trichogrammatidae 0.3 ± 0.3 0.5 ± 0.5 1.5 ± 1.2 0.5 ± 0.5 0.51, 0.683
Mymaridae 2.0 ± 0.9 3.5 ± 1.3 3.3 ± 1.4 3.0 ± 1.7 0.65, 0.604
Figitidae 0.8 ± 0.5 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 2.25, 0.152
Braconidae 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 1.00, 0.436
Perilampidae 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 1.00, 0.436
Diapriidae 0.0 ± 0.0 0.0 ± 0.0 0.5 ± 0.5 0.0 ± 0.0 1.00, 0.436
Unknown Parasitoids 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.5 ± 0.5 0.67, 0.590
Total parasitoids 32.8 ± 3.5 69.5 ± 20.1 35.3 ± 8.1 31.8 ± 5.5 2.87, 0.096
*Asterisk denotes significant differences (P ≤ 0.05). Values followed by different letters are significantly different.
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Figure 5-1. A single experimental plot layout for the border spray and soil tillage study.
103
Figure 5-2. The mean number of SWD captured by treatment in 2014. Bars with the
same letters are not significantly different using Tukey’s HSD (P ≤ 0.05).
b
b
ab
a
0
0.5
1
1.5
2
2.5
Till No till Till No till
Border No border
Me
an
SW
D c
ap
ture
d / t
rap
/ w
ee
k
Treatment
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Figure 5-3. The mean number of SWD captured per trap in 2015. Asterisk (*) indicates
significant differences for that week (P ≤ 0.05).
**
*
0
1
2
3
4
5
6
7
8
9
10
4 Jun 12 Jun 18 Jun 25 Jun
Me
an
SW
D c
ap
ture
d / t
rap
Sampling date
Bordertill
Borderno till
Nobordertill
Noborderno till
105
Figure 5-4. The mean number of SWD emerged kg-1 in 2015. Asterisk (*) indicates
significant differences for that week (P ≤ 0.05).
*
0
20
40
60
80
100
120
140
4 Jun 12 Jun 18 Jun 25 Jun
Me
an
SW
D e
me
rge
d k
g-1
of
bla
ck
be
rrie
s
Sampling date
Bordertill
Borderno till
No bordertill
No borderno till
106
CHAPTER 6 IDENTIFICATION OF BIORATIONAL INSECTICIDES FOR CONTROL OF
DROSOPHILA SUZUKII
Management for Drosophila suzukii (Matsumura) consists of cultural, chemical,
and post-harvest tactics (Isaacs et al. 2013, Liburd and Iglesias 2013, Diepenbrock et
al. 2017). However, most growers rely heavily on chemical controls since there is a zero
tolerance for larvae in fruit (Liburd and Iglesias 2013, Burrack 2014). The most effective
insecticide classes against D. suzukii are organophosphates, synthetic pyrethroids,
diamides, spinosyns, and less so neonicotinoids (Beers et al. 2011, Cini et al. 2012,
Haviland and Beers 2012, Van Timmeren and Isaacs 2013, Diepenbrock et al. 2016,
Diepenbrock et al. 2017). Insecticides target the adult flies since the larval and pupal
stages occur inside the fruit and in the soil, respectively, where insecticides cannot
penetrate. Growers in areas where D. suzukii populations are low use monitoring to
guide application timing (Iglesias pers. observation) but many growers who historically
have high populations on their farms spray on a calendar basis (Diepenbrock et al.
2016, Diepenbrock et al. 2017). There are also concerns regarding the effects of D.
suzukii spray programs on non-target organisms since the effective insecticides tend to
be broad-spectrum in nature.
Rotation of different chemical classes is critical for effective insecticide resistance
management (IRM). Conventional growers have many available compounds with
different chemical classes that can be used in an IRM program (Beers et al. 2011, Bruck
et al. 2011, Van Timmeren and Isaacs 2013). However, organic berry growers have a
much reduced list of available chemical classes for D. suzukii and even fewer provide
efficacy (Bruck et al. 2011, Liburd and Iglesias 2013, Van Timmeren and Isaacs 2013).
Additionally, there is concern that D. suzukii may develop resistance to the most
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commonly used, most effective organic compounds as a result of exposure to only a
few chemical classes and its ability to have multiple generations during a season
(Tochen et al. 2014). Previous studies have shown that D. suzukii can develop
resistance in the laboratory (Whitener and Beers 2011, Smirle et al. 2017).
Having several effective compounds available for D. suzukii management can
also help to reduce the buildup of insecticide residues on the crop. Violations of
Maximum Residue Limits (MRLs) could result in the inability to sell to certain
international markets and could have severe economic consequences (Goodhue et al.
2011, Farnsworth 2013).
Identifying new organic biopesticides will provide additional tools to organic and
conventional growers to help prevent insecticide resistance, prolonging the life of
current chemical classes, reduce the buildup of insecticide residues, and reducing the
impacts on non-target beneficials. The specific objectives of this study are to evaluate
the efficacy of biorational insecticides for D. suzukii in 1) laboratory fruit dip assays, 2)
semi-field bioassays, and 3) field trials.
Materials and Methods
Insecticide Treatments
Nine (Table 6-1) and 12 (Table 6-2) insecticide treatments were evaluated in
blackberries and blueberries, respectively. Insecticides were mixed at the
manufacturer’s recommended rate with water. The control treatments were water only.
In the semi-field assays, treatments were applied using a CO2-powered sprayer fitted
with a 4-nozzle boom (95.25 cm length, nozzles 31.75 cm apart) at a rate of 749 L
water/ ha. In the field trails, treatments were applied using an airblast sprayer at a rate
of 468 L water/ ha.
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Fruit Dip Bioassays
Ripe organic blackberries were purchased from the grocery store and rinsed
thoroughly with deionized water. Berries were dipped in insecticide treatment solutions
for 30 s and allowed to air dry on filter paper under a fume hood for 1-2 h or until dry.
The residual effects of the insecticides on D. suzukii were assessed at 1 and 3 DAT.
These berries remained on filter paper at room temperature under a fume hood for 1 or
3 d prior to being used in the bioassays. After the berries were dried or after 1 or 3 DAT,
one treated blackberry was placed in a bioassay arena constructed of a 59-ml plastic
cup with a vented lid (Solo Cup Company, Lake Forest, Illinois). Four 7-10 d old adult D.
suzukii flies (1 male, 2 females) were transferred from the aforementioned laboratory
colony to the bioassay arena and remained there for 72 h. A cotton wick soaked with
deionized water was provided to the flies. Bioassay arenas were held at 23 °C, ~65%
RH, and 16:8 [L: D] h. Each treatment was replicated four times and treatments were in
a completely randomized design.
Fly mortality was recorded at 24, 48, and 72 h for each DAT and all flies removed
from the arenas after 72 h. Bioassays were incubated for an additional 14 d, after which
emerged adult male and female D. suzukii were counted.
Semi-Field Bioassays
The semi-field site was established in southern highbush blueberries (Vaccinium
corymbosum L. x V. darrowi Camp), located at the University of Florida Plant Science
Research and Education Unit (PSREU) in Citra, FL. The blueberry plot was 62.2 X 59.4
m with 16 rows that are 1-m wide and separated by a 1.9-m grass buffer zone. There
was an additional buffer row between the control and the insecticide treatments to
ensure minimal drift. Each row consisted of 50 bushes, 4-6 years old, planted 1 m apart.
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There were five cultivars, each with two sets of five bushes, in each row. Plants were
watered daily using drip irrigation and no other chemicals were used for pest
management. Daily temperature (°C), relative humidity (%), and precipitation (cm) data
were collected using FAWN (Florida Automated Weather Network, Gainesville, FL).
Bioassay arenas for the semi-field study were constructed using a 1-L plastic deli
container with a mesh lid (Choice, Lancaster, PA). Each arena consisted of a 35-mL
plastic vial (Fisherbrand, Waltham, MA) filled with tap water in which a foam stopper
(Jaece Industries, Inc., North Tonawanda, NY) and two branches were placed. The vial
was secured in a 30-mL deli cup (Solo Cup Company, Lake Forest, IL) to prevent
movement within the arena and fly mortality. A 30-mL cup with a cotton wick was filled
with 10 percent sugar water solution and secured inside the arena.
The adult D. suzukii flies were obtained from a laboratory colony as described in
chapter 1. Five female and five male 7-10-day-old flies were anesthetized with CO2 and
inserted into each arena. Flies were allowed to acclimate for 1 h and oviposit for an
additional 72 h. The arenas were positioned on a laboratory bench in a completely
randomized design under grow lights with a 16:8 h light: dark cycle at a mean
temperature of 22.8°C.
After 1, 4, and 7 DAT eight branches from blueberry bushes were clipped from
each treatment in the field, placed in resealable plastic bags (two branches per bag) in
an ice cooler, and transported back to the FVIPM laboratory in Gainesville, FL.
Branches were at least 7 cm long and have 10 ripe blueberries available. Any additional
berries were removed to standardize the number of berries per arena. Two branches
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were inserted into each bioassay arena (replicate) for a total of 4 replicates per
treatment.
Adult mortality was assessed every 24 h for 72 h. Flies that died as a result of
factors unrelated to the treatment (i.e. drowning, vial movement) were omitted from the
analysis. After 72 h, adult flies were discarded and berries were incubated at 23°C,
~65% RH, and 16:8 [L:D] h in polystyrene cups (Solo Cup Company, Lake Forest,
Illinois). After 14 d, adult male and female SWD were identified and counted.
Field Trials
The blueberry experiment was conducted at a certified organic blueberry farm in
central Florida. The experiment was a randomized complete block design with 13
treatments and four replicates. Each plot consisted of a 7.6-m row of single-planted
blueberry bushes, spaced 1 m apart. Blueberry plants were 3- to 5-year-old southern
highbush type with mixed cultivars of Meadowlark and Farthing. Black weed fabric and
pine bark were used as mulch. Blueberries were watered daily with drip irrigation, and
no other chemicals were used for pest management for the duration of the study.
The blackberry experiment was conducted at a conventionally management
blackberry farm in South Georgia. The experiment was a randomized complete block
design with nine treatments and four replicates. Each plot consisted of a 7.6-m row of 3-
to 5-year-old blackberry bushes of the Alapaha cultivar, spaced 1.2 m apart. Plants
were trellised with wires on which to secure canes at 1 and 2 m. Beds were covered
with reflective mulch. Blackberries were watered daily with drip irrigation, and no other
chemicals were used for pest management for the duration of the study.
The treatments in the blueberries (Table 2) and blackberries (Table 3) were
applied four times at 7-d intervals. Daily temperature (°C), relative humidity (%), and
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precipitation (cm) data were collected using FAWN (Florida Automated Weather
Network, Gainesville, FL) at the blueberry site and the Georgia Automated
Environmental Monitoring Network (www.georgiaweather.net) at the blackberry site.
Adult D. suzukii were sampled weekly using clear plastic cup traps with entry
holes around the center, baited with 200-ml of a yeast sugar water mixture (Iglesias et
al. 2016). One trap was hung with a twist tie in each plot in the center of the bush.
Samples were collected by pouring bait into collection containers and transporting them
back to the Small Fruit and Vegetable IPM Lab at the University of Florida for male and
female SWD identification. Bait was replaced with 200 ml of fresh yeast sugar water
mixture.
In the blueberry study, berry infestation was evaluated by collecting 10 ripe
berries weekly from each plot (40 per treatment). In the blackberry study, berries varied
in size so infestation was standardized by weight rather than number of berries.
Samples of 100-200 g of ripe blackberries were randomly collected from each plot. All
samples were incubated in clear plastic cups (Solo Cup Company, Lake Forest, Illinois),
at 23°C, ~65% RH, and 16:8 [L:D] h. After 14 d, adult male and female D. suzukii were
identified and counted.
Beneficial insects were evaluated using yellow sticky traps (Great Lakes IPM,
Vestaburg, MI). Three yellow sticky traps (YST) were randomly hung throughout each
treatment (39 in blueberries, 27 in blackberries) using a twist tie to secure them 2 m
from the ground, in the center of the bush.
Data Analysis
The data from the fruit dip and semi-field bioassays were analyzed using
repeated measures mixed-model ANOVA in SAS (PROC GLIMMIX, v. 9.4, SAS
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Institute 2016). For the mortality and sub-lethal effects (semi-field only) data, the fixed
effects were DAT, treatment, treatment*DAT, hour, hour*treatment, hour*DAT, and
hour*treatment*DAT treatment. Hour was the repeated effect and replicate was included
as the random effect. Interaction effects with hour in both studies were not significant
and were removed to simplify the model. For the adult emergence, hour was not
included as a fixed effect since emergence was only collected once. Tukey’s multiple
comparisons post-hoc test was conducted where appropriate (P ≤ 0.05). Mortality data
were square root transformed and emergence data log+1 transformed (semi-field only)
to reduce the variability of the residuals and increase the model fit. A chi-square
analysis was conducted to evaluate the proportion of female and male mortality and
sub-lethal effects for each treatment. Prior to analysis of the adult emergence data,
Spearman’s non-parametric correlation coefficients (ρ) were calculated to evaluate the
correlation between the number of females dead, the total number dead, and the
number of adults emerged.
In both field studies, the adult capture data and the emergence data in the
blueberry trial, were transformed to reduce the variability of the residuals and increase
the model fit. Date were analyzed using a repeated- measures, mixed-model ANOVA
with treatment, week, and treatment*week as the fixed effects. Replicate was included
in the model as the random effect. The emergence data for the blackberry trial were
analyzed using a non-parametric Kruskal-Wallis test and Wilcoxon all pairs when
significant. Treatment differences were separated using Tukey’s HSD (JMP, SAS
Institute 2013). Differences were considered significant at α = 0.05.
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Results
Fruit Dip Bioassays
Adult D. suzukii mortality was significantly affected by the DAT*treatment
interaction (F = 2.55; df = 16, 295; P = 0.0010). At 0 DAT, the treatments with Entrust
(Entrust, Entrust/ Vera HI) resulted in 100% mortality (Fig. 6-1A). Vera HI and Cim LO/
Vera HI were not significantly different. Vera LO was not significantly different than Cim
HI, Cim LO, Grandevo, and the control, which all had mortality < 21%. At 1 DAT, both
Entrust treatments also had 100% mortality (Fig. 6-1B). Vera HI did not differ from the
Entrust treatments or the Cim LO/ Vera HI treatment. Cim HI, Cim LO, Grandevo, and
the control were not different and mortality < 8%. On 3 DAT, mortality was the same at 0
DAT (Fig. 6-1C). There were significantly more females dead in the Vera HI and Cim
LO/ Vera HI treatments (Table 6-3).
The number of adults emerged was not significantly correlated with the total
number (ρ = 0.1460, P = 0.1315) or number of female flies (ρ = 0.1769, P = 0.0671).
The mean number of adults emerged was significantly affected by treatment (F = 86.22;
df = 8, 78; P < 0.0001) but not the DAT*treatment interaction (F = 1.62; df = 16, 78; P =
0.0820). The Entrust treatments both had no adults emerge (Fig. 6-2). Vera HI was not
significantly different than both Entrust treatments but lower than Cim LO/ Vera HI. Cim
HI, Cim LO and the control had the highest number of adults emerging (> 67).
Semi-Field Bioassays
Mortality of adult D. suzukii was significantly affected by the DAT*treatment
interaction (F = 6.08; df = 24, 372; P < 0.0001). At 1 DAT, only the treatments with
Entrust had greater mortality that then control (Fig. 6-3A). Mortality was < 75% in all
treatments. At 4 and 7 DAT, mortality dropped significantly compared to 1 DAT (Fig. 6-
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3B, C). None of the treatments were different than the control and mortality was not
higher than 6.6% (Veratran D HI) and 9.5% (Azera/ Grandevo) at 4 and 7 DAT,
respectively. The sex ratio of dead adult flies was significantly different in the Oxidate
treatment only, whereby more males were dead than females (Table 6-4).
The sub-lethal effects were reported as flies that had reduced activity (i.e.
reduced response to light, reduced response to touch, could not right themselves when
on their backs). Sub-lethal effects were significantly different by the DAT*treatment
interaction (F = 1.94; df = 12, 372; P = 0.0055). At 1 DAT, Entrust/ Venerate had higher
sub-lethal effects than Azera/ Venerate but none of the treatments were different than
the control (Fig. 6-4A). On 4 DAT, only Entrust, Azera/ Entrust, and Azera had
significantly higher sub-lethal effects than the control (Fig. 6-4B). Finally, on 7 DAT, only
Oxidate was higher than the control (Fig. 6-4C).
The number of emerged adults was highly negatively correlated with the total (ρ
= -0.2417, F = 0.0024) and female (ρ = -0.2430, F = 0.0022), so the higher the total and
female mortality the lower the number of emerged adults. The number of adults
emerged per berry was not significantly different t by treatment (F = 1.65; df = 12, 114;
P = 0.0874) or by the DAT*treatment interaction (F = 1.34; df = 24, 114; P = 0.1543).
Field Trials
Blueberries
The number of adult D. suzukii captured was significantly affected by the
DAT*treatment interaction (F = 3.87; df = 44, 177; P < 0.0001; Fig. 6-8). We began
seeing differences in week 2, when the overall numbers of D. suzukii began to increase.
Numbers in the control, Entrust and Venerate treatments were significantly higher than
all other treatments. In week 3, more D. suzukii were captured in the control, Entrust,
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Venerate, and Entrust/ Venerate than all other treatments. In week 4 and 5, the control,
Entrust, and Venerate had the highest captures. In week 5, Entrust/ Venerate and Vera
HI had higher captures than the remaining treatments.
Results from the berry samples showed that the percent of berries infested with
D. suzukii larvae differed by week throughout the study (F = 1.81; df = 55, 177; P <
0.0074, Fig. 6-9). No infestation was observed until week 3. The only treatments with
infested fruit were the control, Entrust, Venerate, Entrust/ Venerate, and Vera HI. In
week 4, the control had the highest rate of infestation at 20 ± 7.1%. In week 5, Entrust
had a greater percentage of berries infested that the control (12.5 ± 6.3%). The control,
Entrust/ Venerate, Venerate, and Vera HI, were higher than the remaining treatments.
Yellow sticky cards were used to evaluate natural enemies in each treatment
(Table 6-3). There were no differences in the number of predators found in each
treatment. Of the parasitoids found on the cards, only those belonging to the families
Aphelinidae and Pteromalidae, as well as the total number of parasitoids were
significantly different by treatment. There were significantly more aphelinids captured in
the Azera/ Grandevo treatment and pteromalids captured in the Azera/ Entrust
treatment than in the control. The total number of parasitoids captured was greater in
the Vera HI than in the Venerate, Entrust, Entrust/ Grandevo, and Azera/ Venerate
treatments but none of the treatments were significantly different from the control.
Blackberries
Results from the adults SWD traps showed that the DAT*treatment interaction
was significant (F = 1.61; df = 24, 103.3; P = 0.05). The mean number of SWD captured
was significantly different in week 1 (F = 3.15; df = 8, 27; P = 0.0118) and 3 (F = 2.98; df
= 8, 25; P = 0.0172). In week 1, Cimexa LO/ Veratran D HI, Entrust, and Veratran D HI
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captured significantly fewer than the control, Cimexa HI and LO, Entrust/ Veratran D HI,
and Grandevo. Veratran D LO was not significantly different than any of the treatments.
In week 2, the overall numbers in all treatments decreased from the first week, not
exceeding 1 fly/trap. In week 3, mean numbers reached 26.5 flies/ trap. Cimexa LO,
Grandevo, Veratran D HI and LO had significantly lower captures than Entrust and
Entrust/ Veratran D HI treatments. Veratran D HI had fewer captures than Cimexa LO/
Veratran D HI and Veratran D LO had fewer captures than the control. The overall
mean SWD numbers decreased again in week 4.
Results from the berry samples showed that the mean ranks of SWD larvae kg-1
were significantly different among the nine insecticide treatments (H = 18.37, df = 8, P =
0.0186, Fig. 6-11). Cimexa (HI and LO), Entrust, Veratran D LO and Grandevo had no
infested samples by SWD throughout the study and were ranked significantly different
than the control. Overall, infestation was low in all samples with the control having 5
emerged SWD kg-1 of blackberries.
Pests and natural enemies were evaluated in each treatment during the final
week of the trial in blackberries. There were no differences in the number of predators
found in each treatment. Of the parasitoids found on the cards, only
Trichogrammatidae, Platygastridae, Ceraphronidae, and total parasitoids were
significantly different by treatment. There were more trichogrammatids in the control
than in the Grandevo, Veratran D LO and CimeXa LO treatments. Platygastrids were
higher in the CimeXa LO/ Vera Hi treatment than CimeXa Hi and Grandevo. There were
more ceraphronids in the control than in the Grandevo treatment. Overall, there were
117
more parasitoids found in the CimeXa LO/ Vera HI treatment than the Veratran D HI,
CimeXa HI, Entrust, Grandevo, and Veratran D LO treatments.
Discussion
The objective of this study was to identify new potential biorational insecticides
for management of D. suzukii in organic berry production. Chromobacterium subtsugae
(Grandevo) was found to provide control of adult and larval D. suzukii in the field trials
but mortality in the laboratory or semi-field bioassays was low. In our field trials,
treatments with C. subtsugae alone or in a tank mix with another biorational insecticide,
all reduced adult captures and infestation. Chromobacterium subtsugae has been
shown to reduce the number of larvae found in fall red raspberries (Fanning et al. 2018)
and serve as an effective insecticide in a rotational program with spinosad in rabbiteye
blueberries (Rosensteel and Sial 2017). In our laboratory or semi-field studies, however,
adult mortality was not different than the control and interestingly, adult emergence was
significantly lower than the control in the laboratory fruit dip assays (Fig. 6-4). It is
possible that C. subtsugae has some curative effects on D. suzukii (Wise et al. 2015).
Chromobacterium subtsugae is a biopesticide with multiple modes of action, including
repellency, oral toxicity, reduced egg hatch, and reduced fecundity, that target insect
and mite pests (Marrone Bio Innovations, 2015). Since in this study, only adult
emergence was measured, it is unclear whether C. subtsugae may be acting as an
oviposition deterrent or reducing egg hatch or larval survival. Furthermore, if C.
subtsugae has some repellent properties, this could explain the discrepancy between
adult mortality in the field trials and the laboratory trials, since field trials allow for fly
movement and fruit choice. Additional investigation is needed to understand the mode
of action of C. subtsugae and its efficacy in the field.
118
Sabadilla alkaloids (Veratran D) also provided control of D. suzukii adults and
larval infestation in both trials and had minimal effects on natural enemies. This
biorational insecticide has been shown to provide control of D. suzukii in red raspberries
when rotated with spinosad (Fanning et al. 2018). Sabadilla has a mode of action
similar to that of the pyrethrins, which are non-systemic insecticides with contact action,
that cause a loss of nerve function, paralysis, and death (Dayan et al. 2009). In our
study, there was no additional control provided by the higher rate of sabadilla. In fact,
there were more adult D. suzukii captured in plots with the higher rate of sabadilla than
in the lower rate in the final week of the study. Additionally, 7.5 and 5% of berries
sampled from the higher rate plots were infested with D. suzukii in weeks 3 and 5,
respectively, whereas no infested berries were found in the low treatment. Furthermore,
the number of total parasitoids varied in the high and low rates in both trials. This
insecticide may benefit from a change in formulation. The current formulation of
sabadilla is a wettable powder and the particle size is similar to sand. The large particle
size required constant agitation and clogged the spray nozzle on several occasions.
The discrepancy in the efficacy of the low and high application rates of sabadilla may be
a result of poor coverage due to large particle size.
The most commonly used organic insecticide for management of D. suzukii is
spinosad (Entrust). Unsurprisingly, spinosad provided 100% adult mortality and 0%
infestation through 3 DAT on blackberries in the laboratory (Fig. 6-3, 6-4). In the field
trials, adult captures in spinosad treatments were not different than the control but berry
infestation was reduced. Adult captures using traps in small field trials do not
necessarily indicate a failure of the product. In small field trials such as the one in this
119
study (~ 0.5 ha) where > 36 traps were established in close proximity, it is possible for
interference among the attractive traps, whereby traps are attracting flies from other
treatment plots. Recent studies have shown that the current commercial lure used for D.
suzukii (Scentry Biologicals, Inc., Billings, MT) has a plume reach of only 3 m. This may
be affected by the crop, environmental conditions (temperature, humidity, wind speed),
and lure age (Kirkpatrick et al. 2018) so may differ in orchards in Florida. Spinosad has
been shown to provide excellent control of D. suzukii adults and infestation in several
other studies in multiple berry crops (Bruck et al. 2011, Van Timmeren and Isaacs
2013). However, in California and Oregon, populations of D. suzukii in some organic
fields are showing signs of reduced susceptibility to spinosad (Atallah et al., 2014). The
identification of new classes of effective insecticides that can be rotated with spinosad is
critical for managing D. suzukii, a multivoltine pest with high reproductive potential.
Environmental conditions can impact the efficacy of insecticides in the field.
Previous studies have found that rainfall of as little as 1.25 cm can significantly reduce
the efficacy of insecticides in the field (Van Timmeren and Isaacs 2013, Diepenbrock et
al. 2016, Gautam et al. 2016). In the semi-field bioassays, the significant reduction in
overall adult mortality between 1 and 4 DAT (Fig. 6-5) was likely due to a 1-cm rain
event that occurred within a 2-hr period at 2 DAT (Fig. 6-1). During the blueberry and
blackberry field trials there were multiple rain events that occurred after the second and
third applications, respectively (Fig. 6-2), after which, the number of adult D. suzukii
captured increased. Rainfall also increases the relative humidity of an agroecosystem,
which provides favorable conditions for D. suzukii development and can lead to rapid
population increases (Tochen et al. 2016, Enriquez and Colinet 2017b, Van Timmeren
120
et al. 2017, Eben et al. 2018). Regular rain events and constant humid conditions are
common during blueberry and blackberry seasons in the southeastern U.S and
therefore, residual protection of susceptible fruit is imperative. The addition of adjuvants,
i.e. detergents/ stickers, may be used to enhance the residual activity of insecticides on
D. suzukii through rain events (Gautam et al. 2016).
Recent research has shown the potential to enhance the efficacy of organic
insecticides by increasing fly exposure to the insecticide. For instance, adding
phagostimulants such as sucrose or yeasts, to insecticide mixtures may increase the
effects of insecticides by stimulating feeding by the flies and increasing exposure time
with the insecticide (Cowles et al. 2015, Knight et al. 2016). Timing insecticide
applications with D. suzukii activity may also increase the effects of insecticides.
Drosophila suzukii are crepuscular throughout most of the year; they are active at dawn
and dusk (Van Timmeren et al. 2017). Knowing when the appropriate time to treat the
field is can significantly improve insecticide effectiveness. Finally, canopy management
in the way of pruning, may create less suitable environments for D. suzukii and improve
insecticide spray coverage (Sial et al. 2015, Tochen et al. 2016, Diepenbrock and
Burrack 2017).
As a result of our study, we identified several new compounds, Chromobacterium
subtsugae (Grandevo) and sabadilla alkaloids (Veratran D), with new modes of action
that may be used in a rotational program with common broad-spectrum insecticides for
control of D. suzukii, with minimal effect on natural enemies. Integrated resistance
management is crucial to extend the life of the currently effective compounds for
121
managing this devastating pest while progress continues towards a more integrated
approach to D. suzukii management
122
Table 6-1. Biorational insecticides treatments for the laboratory fruit dip bioassays and field trial in blackberries
Trt # Compound Active Ingredient Rate Notes
1 Untreated (Control)
-- --
2 Entrust SC Spinosad 0.44 L/ha
3 Veratran D HI Sabadilla Alkaloids 16.8 kg/ha
4 Entrust SC Spinosad 0.44 L/ha Tank Mix
Veratran D HI Sabadilla Alkaloids 16.8 kg/ha
5 Veratran D LO Sabadilla Alkaloids 9 kg/ha
6 Cimexa HI Amorphous Silica Gel 11.2 kg/ha Tank Mix
PolyTaxi Soap (adjuvant) 203 ml/L water
7 CimeXa LO Amorphous Silica Gel 5.6 kg/ha Tank Mix
PolyTaxi Soap (adjuvant) 2 ml/L water
8 CimeXa LO Amorphous Silica Gel 5.6 kg/ha Tank Mix
PolyTaxi Soap (adjuvant) 203 ml/L water
Veratran D HI Sabadilla Alkaloids 16.8 kg/ha
9 Grandevo Chromobacterium subtsugae
3.4 kg/ha
Trt = Treatment
123
Table 6-2. Biorational insecticides treatments used in the semi-field bioassays and field trial in blueberries.
Trt # Compound Active Ingredient Rate Notes
1 Untreated (Control) -- --
2 Entrust SC Spinosad 0.44 L/ha
3 Grandevo Chromobacterium subtsugae
3.4 kg/ha
4 Venerate XC Burkholderia spp. 4.7 L/ha
5 Entrust SC Spinosad 0.44 L/ha Tank Mix
Grandevo C. subtsugae 2.2 kg/ha
6 Entrust SC Spinosad 0.44 L/ha Tank Mix
Venerate XC Burkholderia spp. 4.7 L/ha
7 Veratran D LO Sabadilla Alkaloids 9 kg/ha
8 Veratran D HI Sabadilla Alkaloids 11.2 kg/ha
9 Oxidate 2.0 Hydrogen Dioxide, Peroxyacetic Acid
5 ml/L H2O
10 Azera* Pyrethrins+azadirachtin 2.9 L/ha
11 Azera Pyrethrins+azadirachtin 2.9 L/ha Tank Mix
Entrust SC Spinosad 0.44 L/ha
12 Azera Pyrethrins+azadirachtin 2.9 L/ha Tank Mix
Grandevo C. subtsugae 2.2 kg/ha
13 Azera Pyrethrins+azadirachtin 2.9 L/ha Tank Mix
Venerate XC Burkholderia spp. 4.7 L/ha
* Azera was not evaluated in the blueberry field trial. Table 6-3. Sex ratio of D. suzukii adults that died from exposure to blackberries dipped
is several different biorational insecticides.
Treatment Female Male χ2 df P
Entrust 108 108 0 1 1.000
Entrust/ Vera HI 108 108 0 1 1.000
Vera HI 47 71 4.881 1 0.034*
Cim LO/ Vera HI 24 60 15.429 1 < 0.001*
Vera LO 27 39 2.181 1 0.175
Cim HI 5 10 1.667 1 0.302
Cim LO 3 6 1 1 0.508
Grandevo 4 4 0 1 1.000
Control 3 0 - - -
* Indicates significant difference with Pearson’s Exact Chi-Squared test at P ≤ 0.05.
124
Table 6-4. Sex ratio of D. suzukii adults that died from exposure to field blueberries sprayed with several different biorational insecticides in the semi-field bioassays.
Treatment Female Male χ2 df P
Entrust 15 17 0.125 1 0.860
Entrust/ Grandevo 23 31 1.185 1 0.341
Entrust/ Venerate 11 21 3.125 1 0.110
Azera/ Entrust 15 13 0.143 1 0.851
Azera/ Venerate 9 10 0.053 1 1.000
Grandevo 10 8 0.222 1 0.815
Oxidate 4 13 4.765 1 0.049*
Vera HI 8 10 0.222 1 0.815
Vera LO 5 2 1.286 1 0.453
Azera/ Grandevo 3 9 3.000 1 0.146
Azera 3 4 0.143 1 1.000
Venerate 0 4 - - -
Control 2 2 0.000 1 1.000
* Indicates significant difference with Pearson’s Exact Chi-Squared test at P ≤ 0.05.
125
Table 6-5. Mean (± SE) number of natural enemies captured on yellow sticky card traps in blueberry field trials.
Azera
/ E
ntr
ust
Azera
/ G
randevo
Azera
/ V
enera
te
Contr
ol
Entr
ust/
Gra
ndevo
Entr
ust/
Venera
te
Entr
ust
Gra
ndevo/
Oxid
ate
/ V
enera
te
Gra
ndevo
Venera
te
Vera
tran
D
HI
Vera
tran
D
LO
Sta
tistics
(F, P
)
Predators
Ara 0.7 ± 0.3 0.3 ± 0.3 0.0 ± 0.0 2.3 ± 0.9 0.0 ± 0.0 0.3 ± 0.3 1.7 ± 0.3 0.3 ± 0.3 1.3 ± 0.9 1.0 ± 0.6 2.3 ± 1.2 0.3 ± 0.3 2.14, 0.0576
Anth 0.3 ± 0.3 1.0 ± 1.0 1.0 ± 0.6 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 1.0 ± 0.6 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.97, 0.4965
Coc 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 1.0 ± 0.6 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 1.95, 0.0838
Odo 0.0 ± 0.0 0.7 ± 0.7 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 1.0 ± 0.6 0.7 ± 0.7 0.0 ± 0.0 1.15, 0.3683
Pre Tot 1.0 ± 0.0 2.0 ± 2.0 1.3 ± 0.3 3.7 ± 0.9 0.0 ± 0.0 0.7 ± 0.3 1.7 ± 0.3 1.3 ± 0.9 1.7 ± 0.7 2.3 ± 0.9 3.0 ± 0.6 0.7 ± 0.3 1.70, 0.1352
Parasitoids
Brac 0.3 ± 0.3 2.0 ± 1.2 0.7 ± 0.3 0.7 ± 0.7 1.0 ± 0.6 0.3 ± 0.3 0.0 ± 0.0 3.7 ± 3.7 2.0 ± 1.5 0.0 ± 0.0 15.0±11.6 1.3 ± 0.9 1.35, 0.2590
Mym 6.7 ± 1.5 6.3 ± 3.4 0.7 ± 0.3 1.0 ± 0.6 1.7 ± 1.2 4.7 ± 0.7 0.0 ± 0.0 4.3 ± 2.3 4.7 ± 1.2 2.7 ± 2.7 5.0 ± 0.6 4.0 ± 1.0 1.91, 0.0904
Trich 2.0 ± 1.0 1.3 ± 0.3 0.0 ± 0.0 0.7 ± 0.7 0.7 ± 0.7 2.7 ± 1.2 0.0 ± 0.0 1.3 ± 0.7 0.3 ± 0.3 0.7 ± 0.7 0.7 ± 0.7 1.3 ± 0.9 1.35, 0.2604
Ency 15.0±7.0 13.3 ± 4.3 3.3 ± 1.5 3.7 ± 3.2 3.3 ± 1.2 5.3 ± 0.7 0.3 ± 0.3 4.7 ± 2.0 9.0 ± 1.2 2.0 ± 1.5 10.7 ± 5.7 5.7 ± 2.4
5.56, 0.0754
Plat 9.7 ± 1.3 8.7 ± 1.9 6.7 ± 1.8 7.0 ± 4.7 4.0 ± 1.2 8.7 ± 3.2 2.3 ± 0.7 6.3 ± 1.2 10.7±1.3 3.0 ± 3.0 16.0 ± 5.3 10.7±1.5 3.75, 0.0676
Beth 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.91, 0.5465
Aph 4.3±1.8 abc
11.0±1.2a
0.0±0.0 c
1.7±1.7 bc
0.3±0.3 c
3.0±1.0 bc 0.0±0.0c
4.7±2.4 abc
9.0±2.1 ab
1.0±1.0 c
7.0±2.5 abc
2.0±1.5 bc
5.71, 0.0002*
Cera 2.0 ± 0.6 5.0 ± 1.2 0.0 ± 0.0 2.0 ± 1.2 1.0 ± 0.6 2.7 ± 1.5 0.0 ± 0.0 2.3 ± 1.2 3.0 ± 1.5 0.7 ± 0.7 7.7 ± 3.0 2.7 ± 1.7 2.66, 0.0217
Diap 1.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 2.3 ± 2.3 0.0 ± 0.0 0.7 ± 0.3 0.3 ± 0.3 1.0 ± 0.6 2.0 ± 0.6 1.3 ± 0.9 1.7 ± 1.2 0.7 ± 0.3 0.80, 0.6424
126
Table 6-5. Continued
Azera
/ E
ntr
ust
Azera
/ G
randevo
Azera
/ V
enera
te
Contr
ol
Entr
ust/
Gra
ndevo
Entr
ust/
Venera
te
Entr
ust
Gra
ndevo/
Oxid
ate
/ V
enera
te
Gra
ndevo
Venera
te
Vera
tran
D
HI
Vera
tran
D
LO
Sta
tistics
(F, P
)
Fig 0.0 ± 0.0 1.3 ± 0.9 0.0 ± 0.0 0.3 ± 0.3 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 1.0 ± 0.6 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 1.65, 0.1473
Eulo 0.7 ± 0.7 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.7 ± 0.3 0.3 ± 0.3 0.3 ± 0.3 0.3 ± 0.3 1.0 ± 0.6 0.99, 0.4802
Chal 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.3 ± 0.3 0.0 ± 0.0 0.3 ± 0.3 0.3 ± 0.3 0.73, 0.7027
Eury 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 1.00, 0.4744
Sign 1.3 ± 0.3 0.7 ± 0.3 0.3 ± 0.3 0.3 ± 0.3 0.0 ± 0.0 0.0 ± 0.0 0.0 ± 0.0 2.7 ± 1.3 1.0 ± 0.0 0.0 ± 0.0 1.0 ± 0.6 2.7 ± 1.7 2.11, 0.0608
Ich 0.0 ± 0.0 1.0 ± 1.0 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.3 ± 0.3 0.0 ± 0.0 0.7 ± 0.7 0.7 ± 0.7 0.0 ± 0.0 0.0 ± 0.0 0.3 ± 0.3 0.64, 0.7805
Pter 0.7±0.3a 0.0±0.0b 0.0±0.0b 0.0±0.0b 0.0±0.0b 0.0±0.0b 0.0±0.0b 0.0±0.0b 0.3±0.3 ab 0.0±0.0b 0.0±0.0b 0.0±0.0b
2.32, 0.0412*
Par Tot 43.7±11.7abc
52.3±8.7 ab
11.7±3.5bc
21.0±11.5abc
12.7±1.8bc
32.0±6.7abc
3.0±1.2 c
32.7±13.2abc
44.7±3.8 abc
12.3±10.8 bc
66.0±18.7a
33.0±6.1 abc
10.23, 0.0024*
* Indicates differences using ANOVA (α = 0.05). Means with different letters are significantly different using Tukey’s HSD test. Ara=Aranae, Anth=Anthocoridae, Coc=Coccinellidae, Odo=Odonata, Pre=Predator, Brac=Braconidae, Mym=Myramidae, Trich=Trichogrammatidae, Ency=Encyrtidae, Plat=Platygastridae, Beth=Bethylidae, Aph=Aphelinidae, Cera=Ceraphronidae, Diap=Diapriidae, Fig=Figitidae, Eulo=Eulophidae, Chal=Chalcidae, Eury=Eurytomidae, Sign=Signiphoridae, Ich=Ichneumonidae, Pter=Pteromalidae, Par=Parasitoid
127
Table 6-6. Mean (± SE) number of natural enemies captured on yellow sticky card traps in blackberry field trials.
Cim
eX
a H
I
Cim
eX
a L
o
Cim
eX
a L
O/
Vera
tran
D
HI
Contr
ol
Entr
ust
Entr
ust/
Vera
tran
D
HI
Gra
ndevo
Vera
tran
D
HI
Vera
tran
D
LO
Sta
tistics
(F, P
)
Predators
Ara 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 1.33 ± 0.67 0.33 ± 0.33 0.33 ± 0.33 0.00 ± 0.00 0.67 ± 0.33 0.00 ± 0.00 1.97, 0.1109
Geo 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.88, 0.5548
Cara 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 1.00, 0.4690
Pre Tot 0.00 ± 0.00 0.00 ± 0.00 0.67 ± 0.33 1.67 ± 0.88 0.33 ± 0.33 0.33 ± 0.33 0.00 ± 0.00 1.00 ± 0.58 0.00 ± 0.00 2.08, 0.0943
Parasitoids
Brac 0.67 ± 0.67 2.00 ± 1.53 0.67 ± 0.33 2.00 ± 2.00 0.33 ± 0.33 0.33 ± 0.33 2.00 ± 0.00 1.00 ± 0.00 2.00 ± 1.15 0.62, 0.7491
Mym 3.33 ± 0.88 9.33 ± 4.18 13.33 ± 4.10 15.67 ± 4.33 4.00 ± 1.00 4.67 ± 0.33 9.67 ± 3.28 7.00 ± 1.73 8.67 ± 0.67 2.29, 0.0689
Trich 3.00 ± 1.53ab 0.33 ± 0.33b 3.67 ± 0.33ab 6.00 ± 1.15a 1.00 ± 0.58b 2.33 ± 0.33ab 1.33 ± 0.67b 3.00 ± 1.15ab 1.33 ± 0.33b 4.30, 0.0049*
Ency 1.33 ± 0.88 1.67 ± 0.33 1.67 ± 1.20 1.33 ± 0.88 2.33 ± 0.33 1.33 ± 0.67 1.33 ± 0.67 1.00 ± 1.00 1.67 ± 0.88 0.22, 0.9834
Plat 8.00 ± 1.53b 17.00 ± 2.00ab 31.00±4.58a 19.00±3.46 ab
11.00±5.00 ab
25.67±8.37ab 8.00±2.31b 15.00±3.06 ab
17.33±4.33 ab
3.20, 0.0193*
Beth 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.88, 0.5548
Aph 0.67 ± 0.33 0.33 ± 0.33 1.67 ± 0.67 0.33 ± 0.33 1.00 ± 1.00 1.67 ± 0.33 3.00 ± 1.53 0.67 ± 0.33 1.67 ± 0.33 1.52, 0.2190
Cera 8.33 ± 2.33ab 8.33 ± 0.88ab 4.67 ± 1.45ab 9.67 ± 3.18a 7.00 ± 1.15ab 5.67 ± 1.67ab 0.67 ± 0.33b 5.00 ± 1.15ab 2.33 ± 0.88ab 3.16, 0.0204*
Diap 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 1.00 ± 0.58 0.00 ± 0.00 0.00 ± 0.00 1.85, 0.1326
Fig 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.33 ± 0.33 0.33 ± 0.33 0.33 ± 0.33 0.50, 0.8405
128
Table 6-6. Continued
Cim
eX
a H
I
Cim
eX
a L
o
Cim
eX
a L
O/
Vera
tran
D
HI
Contr
ol
Entr
ust
Entr
ust/
Vera
tran
D
HI
Gra
ndevo
Vera
tran
D
HI
Vera
tran
D
LO
Sta
tistics
(F, P
)
Eulo 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.67 ± 0.67 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.90, 0.5369
Peri 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 1.00, 0.4690
Sign 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 1.00 ± 1.00 0.00 ± 0.00 0.00 ± 0.00 1.33 ± 0.33 0.00 ± 0.00 0.67 ± 0.33 1.77, 0.1495
Ich 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.88, 0.5548
Pter 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.33 ± 0.33 0.33 ± 0.33 0.33 ± 0.33 0.00 ± 0.00 0.63, 0.7465
Eupel 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.33 ± 0.33 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 1.00, 0.4690
Par Tot 26.00±5.20c 39.67±4.48 abc
57.33±7.88a 55.67±8.41 ab
27.00±7.00c 43.33±9.39 abc
29.33±4.98c 33.67±4.33c 37.33±4.33bc 3.17, 0.0199*
* Indicates differences using ANOVA (α = 0.05). Means with different letters are significantly different using Tukey’s HSD test. Ara=Aranae, Geo=Geocoridae, Cara=Carabidae, Pre=Predator, Brac=Braconidae, Mym=Myramidae, Trich=Trichogrammatidae, Ency=Encyrtidae, Plat=Platygastridae, Beth=Bethylidae, Aph=Aphelinidae, Cera=Ceraphronidae, Diap=Diapriidae, Fig=Figitidae, Eulo=Eulophidae, Eulo=Eulophidae, Peri=Perilampidae, Sign=Signiphoridae, Ich=Ichneumonidae, Pter=Pteromalidae, Eupel=Eupelmidae, Par=Parasitoid
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Figure 6-1. Average daily temperature (°C) and total daily precipitation (cm) for the
duration of the semi-field efficacy trial in blueberries. Black diamonds denote spray applications and circles are when blueberries were collected and brought to the lab for exposure to D. suzukii.
0.0
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Figure 6-2. Average daily temperatures (°C) and precipitation (cm) for the duration of
the B) blueberry and B) blackberry field efficacy trials. Black diamonds denote spray applications.
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Figure 6-3. Percent mortality of D. suzukii flies after 72-h exposure to single
blackberries dipped in different biorational insecticides. A) Fly mortality after exposure on berries 0 days after treatment (DAT), B) 1 DAT, and C) 3 DAT. Bars with different letters are significantly different at α = 0.50 (Tukey’s HSD).
a ab
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Figure 6-4. The mean number of D. suzukii adults emerged from blackberries dipped in
different biorational insecticide treatments. Bars with different letters indicate significant differences with Tukey’s HSD at P ≤ 0.05.
d dcd
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Figure 6-5. Percent mortality of D. suzukii flies after 72-h exposure to field blueberries
sprayed with different biorational insecticides. A) Fly mortality after exposure on berries 1 days after treatment (DAT), B) 4 DAT, and C) 7 DAT. Bars with different letters are significantly different at α = 0.50 (Tukey’s HSD).
ab
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Figure 6-6. Percent of sub-lethal effects of D. suzukii flies after 72-h exposure to field
blueberries sprayed with different biorational insecticides. A) Fly mortality after exposure on berries 1 day after treatment (DAT), B) 4 DAT, and C) 7 DAT. Bars with different letters are significantly different at α = 0.50 (Tukey’s HSD).
ab aba
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Figure 6-7. The number of emerged adults after 72-h exposure to field blueberries
sprayed with different biorational insecticides. Bars with different letters are significantly different at α = 0.50 (Tukey’s HSD).
0
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Figure 6-8. Mean ± SE (standard error) of adult D. suzukii captured per trap in 12
different biopesticide treatments in organic blueberries. Asterisk (*) indicates differences within the treatments for that week (P ≤ 0.05).
Figure 6-9. Mean ± SE percent infested berries by D. suzukii in 12 different biopesticide
treatments in organic blueberries. Asterisk (*) indicates differences within the treatments for that week (P ≤ 0.05). Treatments not showing in figure had 0% larval infestation for the duration of the experiment.
*
*
*
*
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Control
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Entrust
Grand/Oxi/Vener
Grandevo
Venerate
Veratran Hi
Veratran Lo
*
*
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Entrust/Venerate
Entrust
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Grandevo
Venerate
Veratran Hi
Veratran Lo
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Figure 6-10. Mean ± SE (standard error) of adult D. suzukii captured per trap in 9
different biopesticide treatments in conventional blackberries. Asterisk (*) indicates differences within the treatments for that week (P ≤ 0.05).
Figure 6-11. Mean and quantiles number of emerged D. suzukii per kilogram in 9 different biopesticide treatments in conventional blackberries.
*
*
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1 2 3 4Me
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VeraHi
VeraLo
138
CHAPTER 7 CONCLUSIONS
At the conclusion of this study, we have learned about the behavior and ecology
of an important pest of small fruits, Drosophila suzukii, and developed tactics that can
be used in IPM programs for management of this pest. We found that the host fruits of
D. suzukii vary in their berry characteristics and that skin penetration force plays a role
in the suitability of that host for fly development. This new knowledge can be used to
guide breeding programs to develop cultivars of host fruits that have thicker skins or
firmness and may assist in population control of D. suzukii. Growers may be able to
manipulate fruit firmness by modifying current water and nutrient regimens to help
manage D. suzukii.
As a result of our study, we also found that D. suzukii populations are colonizing
unmanaged field margins and moving into cultivated fields as fruit become susceptible.
Furthermore, flies and fruit infestation were higher closer to the field edges. This
information can guide the development of control tactics that target populations of D.
suzukii where they are most prevalent such as management of non-crop hosts,
conservation biological control, or border sprays. We evaluated the use of border sprays
(into the crop edges) in blackberries that would target D. suzukii adults as they migrated
from the field margins into the crop. We found that border sprays are effective at
reducing D. suzukii numbers in the field. Further research would benefit from evaluating
whether border sprays could be effective in larger fields or fields with higher
populations.
In the field margins we identified several wild fruit-bearing plants that are
potential or confirmed hosts of D. suzukii. The only plant that had ripe fruit during the
139
time of our study, Lantana camara, was never found to be infested with D. suzukii in the
field and females would not oviposit on fruits in the lab. These results suggest that D.
suzukii is utilizing field margins during the blueberry season for reasons other than
feeding and reproducing in ripe fruits.
Finally, we found new compounds with new modes of action that may be used in
a rotational program with common broad-spectrum insecticides for control of D. suzukii,
with minimal effect on natural enemies. Our results indicate that Chromobacterium
subtsugae (Grandevo) and sabadilla alkaloids (Veratran D) were effective at reducing
adult presence and berry infestation in blueberries.
140
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BIOGRAPHICAL SKETCH
Lindsy Iglesias grew up in Tampa, Florida. She graduated with her bachelor’s
degree in environmental science with a minor in sustainability studies from the
University of Florida in 2010. Lindsy pursued her master’s degree with Dr. Oscar Liburd
in the Interdisciplinary Ecology program at the University of Florida. For her thesis, she
studied the distribution of a new invasive pest, Drosophila suzukii, in Florida berry
crops, and developed effective trap and lure systems for monitoring this pest. She
continued working with Dr. Liburd during her doctoral program studying behavior and
ecology of D. suzukii to development sustainable IPM strategies. Lindsy would like to
use her knowledge of applied ecology and pest management to help growers protect
their crops, their workers, and the environment.