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Timed Releases with Neoseiulus californicus as a Biological Control Agent for Tetranychus urticae Koch and its Ecologica...

University of Florida Institutional Repository
Permanent Link: http://ufdc.ufl.edu/UFE0021271/00001

Material Information

Title: Timed Releases with Neoseiulus californicus as a Biological Control Agent for Tetranychus urticae Koch and its Ecological Impact on North Florida Strawberry Fields
Physical Description: 1 online resource (98 p.)
Language: english
Creator: Fraulo, Aimee B
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: biocontrol, florida, koch, mite, north, spider, strawberries, tetranychus, twospotted, urticae
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Twospotted spider mite (TSSM), Tetranychus urticae Koch, is considered to be a key pest in north Florida strawberry fields. Management of TSSM is difficult because it can become resistant to miticides within a year of exposure, making chemical control difficult. As a result, biological control is becoming a popular alternative. Neoseiulus californicus McGregor is known to be an effective biological control agent for TSSM in north Florida strawberries. The objectives of this study were to determine the effect of timed releases with N. californicus to control TSSM throughout the season and also to evaluate the effect of predatory releases on the arthropod communities in the field. We found that N. californicus can control TSSM effectively if released early in the season at an appropriate predator: prey ratio and that N. californicus show a functional response to high densities of TSSM. The Shannon-Weaver index, evenness, and richness measures were used to evaluate the arthropod communities in plots treated with N. californicus. Results showed that N. californicus does not significantly alter the arthropod assemblage in the field. The generalist feeding habits of N. californicus and the natural diversity of the strawberry system may reduce the effect of N. californicus releases on the strawberry system. Finally, we conducted exploratory laboratory studies to correlate TSSM infestation with spectral reflectance values of the leaves. A spectroradiometer was used to collect spectral data from individual leaflets that were infested with known levels of TSSM. Data obtained were used to construct categories of infestation levels at specific spectral regions. Results indicate that TSSM can be detected spectrally at very low levels of infestation. Information obtained from these studies suggests that biological control and spectral imagery could be integrated into a management program to develop an effective precision pest management program.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Aimee B Fraulo.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Liburd, Oscar E.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021271:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021271/00001

Material Information

Title: Timed Releases with Neoseiulus californicus as a Biological Control Agent for Tetranychus urticae Koch and its Ecological Impact on North Florida Strawberry Fields
Physical Description: 1 online resource (98 p.)
Language: english
Creator: Fraulo, Aimee B
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: biocontrol, florida, koch, mite, north, spider, strawberries, tetranychus, twospotted, urticae
Interdisciplinary Ecology -- Dissertations, Academic -- UF
Genre: Interdisciplinary Ecology thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Twospotted spider mite (TSSM), Tetranychus urticae Koch, is considered to be a key pest in north Florida strawberry fields. Management of TSSM is difficult because it can become resistant to miticides within a year of exposure, making chemical control difficult. As a result, biological control is becoming a popular alternative. Neoseiulus californicus McGregor is known to be an effective biological control agent for TSSM in north Florida strawberries. The objectives of this study were to determine the effect of timed releases with N. californicus to control TSSM throughout the season and also to evaluate the effect of predatory releases on the arthropod communities in the field. We found that N. californicus can control TSSM effectively if released early in the season at an appropriate predator: prey ratio and that N. californicus show a functional response to high densities of TSSM. The Shannon-Weaver index, evenness, and richness measures were used to evaluate the arthropod communities in plots treated with N. californicus. Results showed that N. californicus does not significantly alter the arthropod assemblage in the field. The generalist feeding habits of N. californicus and the natural diversity of the strawberry system may reduce the effect of N. californicus releases on the strawberry system. Finally, we conducted exploratory laboratory studies to correlate TSSM infestation with spectral reflectance values of the leaves. A spectroradiometer was used to collect spectral data from individual leaflets that were infested with known levels of TSSM. Data obtained were used to construct categories of infestation levels at specific spectral regions. Results indicate that TSSM can be detected spectrally at very low levels of infestation. Information obtained from these studies suggests that biological control and spectral imagery could be integrated into a management program to develop an effective precision pest management program.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Aimee B Fraulo.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Liburd, Oscar E.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021271:00001


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TIMED RELEASES WITH Neoseiulus californicus AS A BIOLOGICAL CONTROL AGENT
FOR Tetranychusrtrt~t~t~r~rtrt urticae Koch AND ITS ECOLOGICAL IMPACT ON NORTH FLORIDA
STRAWBERRY FIELDS




















By

AIMEE BETH FRAULO


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007































O 2007 Aimee Beth Fraulo


































To my parents who gave me the gift of curiosity and a love of learning









ACKNOWLEDGMENTS

I would like to thank everyone who made this thesis possible. Most importantly I would

like to thank my supervisory committee, Dr. Oscar E Liburd, Dr. Robert McSorley, and Mr.

Stanley Latimer. I am also eternally grateful to Drs. Christian Russell and Matt Cohan for their

help on the imagery analysis. I would also like to thank the staff at the Small Fruit and Vegetable

IPM Laboratory for their moral support, and the staff at the Research and Education Center for

their help with the strawberry maintenance. Finally, I would like to thank my family and friends

for providing unending support through this whole process.












TABLE OF CONTENTS


page

ACKNOWLEDGMENTS .............. ...............4.....


LIST OF TABLES ........._._ ...... .__ ...............7....


LIST OF FIGURES .............. ...............8.....


AB S TRAC T ............._. .......... ..............._ 10...


CHAPTER


1 INTRODUCTION ................. ...............12.......... ......


2 LITERATURE REVIEW ................. ...............16................


Twospotted spider mite ................. ...............16........... ....
Control M ethods ................. ...............18.......... .....
Natural Enemies............... ...............18

Phytoseiulus persimilis ................. ...............19.................
Neoseiulus californicus .............. .. .. ............... .. .........2
Effect of Timing of Predatory Releases on TS SM Populations ........._.._ .... .._.._..........21
Geographic Information Systems in Pest Monitoring .............. ...............23....

3 BIOLOGICAL CONTROL OF TWOSPOTTED SPIDER MITE, Tetranychus urticae
Koch, WITH PREDATORY MITE, Neoseiulus californicus IN GREENHOUSE AND
FIELD EXPERIMENTS .............. ...............27....


Materials and Methods .............. ...............28....
Colony .............. .... ...............28
Greenhouse experiment ............._. ...._... ...............29....
Field Experiment .............. ...............30....
Sampling............... ...............32
Statistical Analysis .............. ...............32....
Re sults........._.__........ ._. ...._ .............3
Laboratory Experiments .............. ...............33....
2005-2006 Field Season .............. ...............33....
2006-2007 Field Season .............. ...............34....
Discussion ............._.. ...._ .. ...............35...
Greenhouse Experiment .............. ...............35....
Field Experiments ............._. ...._... ...............36....
The 2005-2006 Season ............._. ...._... ...............36....
The 2006-2007 Season ............._. ...._... ...............37....












4 EFFECT OF Neoseiulus californicus RELEASES ON ARTHROPOD COMMUNITIES
INT NORTH FLORIDA STRAWBERRY FIELDS .............. ...............50....


M materials and M ethods .............. ...............52....
Statistical analysis............... ...............55
Re sults ................ ...............55.................
Discussion ................. ...............58.................


5 HYPERSPECTRAL IMAGERY DETECTION FOR TWO SPOTTED SPIDER MITE
DAMAGE INT STRAWBERRIES .............. ...............69....


M materials and M ethods .............. ...............71....
Field Plots ................. ...............71.................

Sampling ................. ...............71.................
Spectral Scanning .............. ...............72....
GI S Integration .............. ...............74....
Re sults.............. .... ...............76....

Spectral Analy si s...................... ............ .......7
Accuracy of Categories of Mite Infestation .........___....... ......__..........7

Spectral M ap ............. ...... ._ ...............77...
Discussion ............. ...... ._ ...............77...

Analy si s ............. ...... ...............77...
GIT Application............... ..............7
Future Directions ............. ...... ._ ...............79...


6 CONCLUSIONS .............. ...............85....


APPENDIX


A STRAWBERRY PEST MANAGEMENT SURVEY ......____ ...... .. ............_....88


B FUTURE WORK............... ...............90..


LI ST OF REFERENCE S ............. ...... .__ ...............92..


BIOGRAPHICAL SKETCH .............. ...............98....










LIST OF TABLES


Table page

3-1 Strawberry yield for January, February, and March 2007. ................ ..................4

4-1 Cumulative number of each taxa found in each treatment in the three sampling
periods in yellow sticky traps. ............. ...............61.....

4-2 Cumulative number of each taxa found in each treatment in the three sampling
periods of the pitfall traps. ................ ...............62........... ...

4-3 Cumulative numbers of each taxa in the three visual sampling periods ................... .........63

4-4 Cumulative numbers of each taxa in the three foliar sampling periods.............................63

4-5 Mean values of diversity indices in plots in early-season yellow sticky traps. .................65

4-6 Mean value of diversity indi ces in plots in early- season pitfall trap s............... .... .........._.6 5

4-7 Mean values of diversity indices in plots in mid-season yellow sticky traps. ...................67

4-8 Mean values of diversity indices in plots in mid-season pitfall traps. ............... ...............67

4-9 Mean value of diversity indices in plots in late-season yellow sticky traps. .....................68

4-10 Mean value of diversity indices in plots in late-season pitfall traps. ................ ...............68

5-1 Classification summary of LDA cross-validation of PCA.. ................ ............ .........83

5-2 Accuracy scores for the LDA .............. ...............84....

5-3 Accuracy scores for LDA of Quickbird and SPOTS .............. ...............84....










LIST OF FIGURES


Figure page

3-1 Twospotted spider mite colony maintained in the laboratory for greenhouse
experim ents. .............. ...............39....

3-2 Transferring TSSM from the laboratory colony onto strawberry plants for the
greenhouse trials. ............. ...............39.....

3-3 Mesh cages constructed to contain TSSM and N. californicus during the greenhouse
trials ................ ...............40_. ......

3-4 Maps of the layout of the treatments in the field. ........._._ ..... .__ ......_._.....4

3-5 Twospotted spider mite motiles in greenhouse trials ................. ................ ........ .42

3-6 Twospotted spider mite eggs in the greenhouse trials .............. ...............43....

3-7 Average number of TSSM motiles and eggs per trifoliate on the old strawberry
leaves 2005-2006 field season. ............. ...............44.....

3-8 Weekly average of TSSM motiles per plot on old leaves in 2005-2006 field season. ......44

3-9 Average number of TSSM motiles and eggs per trifoliate on the young strawberry
leaves 2005-2006 field season. ............. ...............45.....

3-10 Weekly average of TSSM motiles per plot on young leaves in 2005-2006 field
season. .............. ...............45....

3-11 Comparison of young and old leaves 2005-2006 season ................. ................ ...._.46

3-12 Comparison of young and old leaves 2006-2007 season within each treatment. ..............46

3-13 Average number of TSSM motiles and eggs on old trifoliates during the 2006-2007
season............... ...............47.

3-14 Average weekly number of TSSM motiles on the old leaves in each treatment. ..............48

3-15 Average number of TSSM motiles and eggs on young trifoliates during the 2006-
2007 field season............... ...............48.

3-16 Average weekly number of TSSM motiles on the young leaves in each treatment. .........49

4-1 Cumulative percent of families found on yellow sticky trap 1-cm squares..............._..._....64

4-2 Most abundant families found on early-season yellow sticky traps between the
treated and untreated plots. ............. ...............64.....











4-3 Most abundant families found in the early-season pitfall traps in the treated and
untreated plots.. ............. ...............65.....

4-4 Most abundant families found in the mid-season yellow sticky traps among the early,
middle and untreated plots. .............. ...............66....

4-5 Most abundant taxa found in the mid-season pitfall traps between the early, middle,
and untreated pl ots ................. ...............66................

4-6 Most abundant families found in the late-season yellow sticky traps in early, middle,
late, and control plots. .............. ...............67....

4-7 Most abundant families found in the late-season pitfall traps in the early, middle,
late, and control plots ................. ...............68................

5-1 Reflectance map of TSSM distribution of the experimental strawberry field, Citra,
F L .............. ...............8 1....

5-2 Variation of the spectral signatures of strawberry leaves at different levels of TS SM
infestation ................. ...............82.................

5-3 Regression of predicted versus observed raw TS SM numbers/leaflet ............... .... ...........82

5-4 Scree Plot of PCA ................. ...............83........... ...









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

TIMED RELEASES WITH Neoseiulus californicus AS A BIOLOGICAL CONTROL AGENT
FOR Tetranychusrtrt~t~t~r~rtrt urticae Koch AND ITS ECOLOGICAL IMPACT ON NORTH FLORIDA
STRAWBERRY FIELDS

By

Aimee Beth Fraulo

August 2007

Chair: Oscar E. Liburd
Major: Interdisciplinary Ecology

Twospotted spider mite (TSSM), Tetranychus urticae Koch, is considered to be a key pest

in north Florida strawberry fields. Management of TSSM is difficult because it can become

resistant to miticides within a year of exposure, making chemical control difficult. As a result,

biological control is becoming a popular alternative. Neoseiulus californicus McGregor is known

to be an effective biological control agent for TSSM in north Florida strawberries. The

obj ectives of this study were to determine the effect of timed releases with N. californicus to

control TSSM throughout the season and also to evaluate the effect of predatory releases on the

arthropod communities in the field. We found that N californicus can control TSSM effectively

if released early in the season at an appropriate predator: prey ratio and that N. californicus show

a functional response to high densities of TSSM. The Shannon-Weaver index, evenness, and

richness measures were used to evaluate the arthropod communities in plots treated with N.

californicus. Results showed that N. californicus does not significantly alter the arthropod

assemblage in the f ield. The generalist feeding habits of N californicus and the natural diversity

of the strawberry system may reduce the effect of N. californicus releases on the strawberry

system. Finally, we conducted exploratory laboratory studies to correlate TSSM infestation with










spectral reflectance values of the leaves. A spectroradiometer was used to collect spectral data

from individual leaflets that were infested with known levels of TSSM. Data obtained were used

to construct categories of infestation levels at specific spectral regions. Results indicate that

TSSM can be detected spectrally at very low levels of infestation. Information obtained from

these studies suggests that biological control and spectral imagery could be integrated into a

management program to develop an effective precision pest management program.









CHAPTER 1
INTTRODUCTION

The strawberry industry began in early 15th century Europe as a collection of small

localized enterprises. The wild fruit was originally used for medicinal purposes and was later

propagated in household gardens. The first records of the modern strawberry trade date from the

colonization of the New World, ca. 16th century (Wilhelm and Sagen 1974). Today, the United

States is one of the top producers of strawberries worldwide. The average yield in the United

States ranks highest in the world, and total harvested area is second only to Poland (Economic

Research Service-USDA 2005). California is the center of strawberry production in the United

States. However, Florida produces 100% of the domestic winter strawberry crop and ranks

second in the country in overall production (Mossler and Nesheim 2002).

Strawberries are the most valuable berry crop in Florida. No other plant bears more fruit

earlier, as soon after planting, nets more profit per acre in such a short period of time, or thrives

in so many different environments (Wilhem and Sagen 1974). In 2003, Florida strawberries had

a market value of $200 million and a production cost of $20,000 per acre (Brown 2003). By the

year 2005, there were 7,300 acres in production comprising approximately three-quarters of the

state's cultivated berry acreage (Economic Research Service-USDA 2005). Exports have been

growing at an average rate of seven percent annually since 1990 (Economic Research Service-

USDA 2006).

In northern Florida, strawberries are grown as an annual crop on a raised bed, or "hill

system". The soil is inj ected with a soil fumigant such as methyl bromide to control soil pests

and pathogens and the beds are covered with black plastic mulch. Drip irrigation is run under the

beds to improve water and nutrient efficiency. This "plasticuture" system mitigates pest and

disease transmission in the field (Mossler and Nesheim 2002).









Strawberries are susceptible to a number of fungal diseases and are host to many

arthropod pests. The most economically important pre-harvest fungal diseases are Botrytis fruit

rot (Botrytis cinerea) and anthracnose fruit rot (Colletotrichum acutatum) (Ellis and Legard

2003). Maj or arthropod pests include coleopterans such as the Strawberry Root Weevil,

Otiorhynchus ovatus (Linnaeus), Black Vine Weevil, Otiorhynchus sulcatus (Fabricus),

Rootworm, Paria fragaria Wilcox, and several species of sap beetles. Homopterous pests

include potato leafhopper, Empoa~sca fabae (Harris), spittlebug, Philaenus spumarius (Linnaeus),

aphids, (Aphididae), and whiteflies, Bemisia tabaci and Trialeurodes spp. Armyworms,

cutworms and strawberry fruitworms (Noctuidae), tarnished plant bugs, (Lygus spp.) and several

species of thrips occur as well (Handly and Price 2003).

The principal pest on strawberry plants is the twospotted spider (TSSM), Tetranychusrtrt~t~t~r~rtrt

urticae Koch (Waite 2002, Oatman et al. 1985, Escudero and Ferragut 2005, Cakmak and

Cobanoglu 2006, Rhodes and Liburd 2006). Twospotted spider mites feed on the leaves by

piercing through the mesophyll layer with its needle-like chelicerae and sucking out the contents

of the cells. This destroys the protective leaf surface, nutrient availability, and decreases

photosynthetic activity, resulting in a speckled or bronzed appearance of the leaves. If severe, the

damage may reduce yields (Sonnevelt et al. 1996, Huffaker et al. 1969, Colfer et al. 2004).

It is a common practice for growers to "scout" their fields to monitor the presence of

TSSM, this includes taking a systematic or random sample of at least 60 leaflets from a field and

inspecting each leaflet for the presence of at least one mite motile (nymph or adult) or egg. Fields

must be monitored regularly at least once per week as TSSMs aggregate quickly into "hot spots".

Leaves can be examined with a 10X hand lens, or under a microscope in a laboratory. When 5%









of the leaves are infested it is generally recommended for growers to take some type of control

action (Greco et al 2004, Handley and Price 2003).

Historically, miticides have been used to control TSSM infestations, but due to increased

resistance, harmful effects to the environment and to non-target organisms, and high costs, many

growers are looking at alternative methods of control (White 2003). There are several known

natural enemies of TSSM, such as the sixspotted thrips, .S chorriblps sexmaculaus, minute pirate

bug, Orius tristicolor (White), and Bigeyed bug, Geocoris punctipes Stal, and brown lacewing

hemerobiidd) (Oatman and Voth 1972). However, predatory mites from the family Phytoseiidae

are known to be among the most effective control agents. Prior to 2006, Phytoseiulus persimilis

Athias-Henriot was the most commonly utilized predatory mite in Florida strawberries (Rhodes

and Liburd 2006). However, the cooler climate that exists in northern Florida during the

production season does not support its viability in this region of the state. Research conducted by

White (2003) found that Neoseiulus californicus (McGregor) is a better choice in north Florida

strawberry fields because of the wide fluctuation in temperature, moisture and humidity.

Neoseiulus californicus is a commercially available phytoseiid mite that is a generalist

type II feeder (McMurtry and Croft, Rhodes and Liburd 2005). It can survive without prey and

for long periods at low temperatures (Hart et al. 2002). It has been used either alone or in

conjunction with P. persimilis for TSSM control (Rhodes et al. 2006). However, the time when

N. californicus should be released, as well as the frequency of applications (releases) has not

been determined (Cakmak and Cobanoglu 2006, Hart et al. 2002). The obj ectives of this study

are to determine the most appropriate time during the growing season for inoculative releases of

N. californicus to control TSSM, to evaluate the effect of predatory releases on naturally

occurring arthropods in the strawberry plant environment, and to establish a pest monitoring










system for growers using geographic information technology (GIT) to detect early damage of

TSSM in strawberries.

A strawberry pest management survey was also administered. The survey was distributed

to growers across the state of Florida to gather information regarding specific pest management

concerns. Questions addressed growers' perceptions of pest problems and their primary concerns

when considering a management plan. The results were compiled and analyzed to help us

develop appropriate management strategies that target growers' specific needs.









CHAPTER 2
LITERATURE REVIEW

Twospotted spider mite

The twospotted spider mite, Tetranychusrtrt~t~t~r~rtrt urticae Koch, belongs to the family

Tetranychidae. It feeds on strawberry (Fargaria spp.) leaves by piercing the photosynthetic sites

of the mesophyll tissue with specialized chelicerae. It pierces the chloroplasts, ingests the

chlorophyll, and collapses the interior structure of the leaf, altering the ability of the leaves to

utilize solar radiant energy, reduces carbon dioxide assimilation and decreases transpiration

(Jansen et al. 1997, Jensen 2005, Shanks and Doss 1989). The twospotted spider mite is a

particularly harmful pest due to its high rate of fecundity and its short life cycle. Females lay an

average of six eggs per day and for a total of 70-100 eggs during a lifetime (Williams 2000). In

high temperatures (>33o C) a female can lay as many as 20 eggs a day and the life cycle

decreases from the average 30 days to seven days (Shanks and Doss 1989, Grostal and Dicke

2000, White and Liburd 2005). Twospotted spider mites also thrive in environments with low

soil moisture. White and Liburd (2005) reported two times as many motiles on plants exposed to

low moisture regimes compared with those exposed to high soil moisture.

Twospotted spider mite develops from a pale yellow egg into a six-legged yellowish-

white larva. It molts two more times becoming an eight-legged protonymph and then

deutonymph before maturing into an adult. Depending on the temperature, it may take between

4-12 days for the mite to mature. Spider mites may live for three weeks as an adult. The female

is about 0.5 mm in length and the male grows to be approximately 0.3 mm (Williams 2000).

Spider mites produce silk from glands located in the palpi to spin fine webs on the underside of

the leaves to protect the colonies from predators and facilitate movement across the leaf. The









webs may also be used for courtship, to protect against weather and miticides, to conserve their

eggs and reduce interguild predation (McMurtry et al 1907, Kranz, 1979, Roda et al. 2000).

During the summer months when TSSM is in a feeding reproductive stage it is a

yellowish green color. The female is globular in shape and has two pronounced dark lateral

"feeding spots" on the abdomen. The male has a more rectangular shape and has similar dark

markings. These markings are lighter and less defined than on the females. During the winter

months, low temperatures and short day length induce diapause in female mites. They cease

feeding and reproduction and become dark red in color. The females over-winter in the soil

(Bollard et al. 1999, Sugasawa et al. 2001). Sex determination is entirely haploid-diploid

(Huffaker et al. 1969). Both male and female TSSM adults are brightly colored ranging from

green to yellow to red. Due to broad morphological differences TSSM has been described with

over 50 different names. The inability for some individuals to successfully mate suggests that T.

urticae may be a species complex (Bollard et al. 1999).

Twospotted spider mite is an important pest on a broad range of agricultural crops. In

strawberries, early season infestation can severely decrease yield (Sugasawa 2001, Rhodes

2005). A high infestation often results in defoliation and a significant reduction in fruit yield.

Yield reduction has been recorded to be as high as 29%, but usually averages between 10-15%

(Walsh 2002, Oatman et al. 1985). Because of its short life cycle, TSSM has the capacity to

become highly resistant to most pesticides in a short period of time. Outbreaks have intensified

over the last few decades due to increased use of pesticides and modern cultural practices

(Huffaker and McMurtry, 1969 and Escudero and Ferragut, 2005). As traditional methods of

chemical control are less effective, and marketability due to chemical residue has become a









social concern, growers are beginning to rely on natural enemies as an alternative to chemical

management systems (Escudero and Ferragut 2005).

Control Methods

Many commercial growers have developed the practice of applying multiple treatments

of chemical pesticides, mainly acaricides, on a calendar basis throughout the season (Villanueva

and Walgenbach 2005). Compounds such as hexythiazox, bifenatzate, abamectin and bifentrhrin

have been heavily relied upon to control arthropod pest infestations. During the last half a

century, concern over resistance of mites to specific miticides and of the deleterious effect that

the miticides have on beneficial predators has increased (Escudero and Ferragut 2005).

Broad spectrum insecticides such as pyrethroids and organophosphates have been shown

in laboratory tests to be harmful to beneficial. These chemicals decrease rates of oviposition,

affect egg numbers and increase rates of mortality in adults. Even reduced-risk compounds have

variable levels of toxicity and sub-lethal effects on reproduction in beneficial (Villanueva and

Walgenbach 2005).

Many growers are investigating alternative methods of control due to the concerns over

chemical tactics. A principal alternative to chemical tactics for management of key arthropod

pests is inundative releases of predatory mites and insects. This practice has been used to manage

TSSM populations. Approximately 40% of Florida' s strawberry growers, particularly in the

southern part of the state, practice a method of biocontrol, which has led to a significant decrease

in chemical applications (Mossler and Nesheim 2002).

Natural Enemies

There are several natural enemies of TSSM. Oatman et al. (1985) identified ten insect

species belonging to families Thripidae, Cecidomyiidae, Coccinellidae, Staphylinidae,

Anthocoridae, Lygaediae, Chrysopodae and Hemerobiidae and nine phytoseiid mite species that









are natural enemies of TSSM. Rondon et al. (2004) conducted laboratory studies measuring rates

of consumption, efficacy and feeding preference by bigeyed bugs, Geocoris punctipes Say,

minute pirate bugs, Orius insidiosus (Say), and the pink spotted lady beetle Coleomegilla

maculata DeGeer. The experiments concluded that these insects do consume spider mites, but

also show a preference for aphids and other phytophagous insects, reducing their effectiveness as

target control agents for TSSM. The most successful predators in suppressing TSSM are the

predaceous phytoseiid mites, Phytoseiulus persimilis and Neoseiulus californicus (Blackwood

and Shausberger 2001, McMurtry and Croft 1997, Jung and Croft 2001, Croft et al. 1998, Sabelis

and Janssen 1994).

Predatory Mites: Phytoseiulus persimilis and N. californicus belong to the family

Phytoseiidae. Phytoseiids are voracious predators of spider mites. They compose one of the

most important families of predatory mites used in biological control systems (Blackwood and

Shausberger 2001). Phytoseiid mites are approximately 0.5 to 0.8 mm and live in topsoil under

leaf litter. They have a pair of needle-like chelicerae which are inserted into the prey and extract

its internal fluids. They range from type I, highly specialized feeders that are genus specific with

regard to prey preference, to type IV generalist feeders that are able to utilize mites, pollen, or

honeydew as an energy source.

Phytoseiulus persimilis

Phytoseiulus persimilis is a type I obligate specialist that is genus specific in terms of its

feeding preferences (McMurtry and Croft 1997). It feeds exclusively on Tetranychusrtrt~t~t~r~rtrt spp.and has

one of the highest rates of population increase and the shortest development time of Phytoseiid

mites (McMurtry and Croft 1997). Phytoseiulus persimilis depends on TSSM to survive and

reproduce. It has been observed to consume up to five times as many TSSM as N. californicus,

and has a greater fecundity (Gilstrap and Friese 1985). With its long setae, it is well adapted to









move over webbed spider mite colonies. As a type I specialist P. persimilis tends to aggregate in

areas of high prey, has high walking activity and aerial dispersal, and is ephemeral and difficult

to maintain as a reliable control agent (Jung and Croft 2001, Croft et al. 1998). It is effective in

the short term, but it over exploits the prey and perishes when the food source is eliminated.

Phytoseiulus persimibis is a more voracious and well adapted predator than N. californicus, but is

unable to survive in temperate climates. (Escudero and Ferragut 2005, Easterbrook 1992).

Neoseiulus califormtcus

Neoseiulus californicus is a type II/III generalist predator, meaning that it can survive on

a variety of live prey as well as on pollen (McMurtry and Croft 1997). It is innately adapted to

strawberry plant structure (Castignoli et al. 1999). As a generalist, it moves further from a central

release point than specialists such as P. persimilis and provides more stable and regulatory pest

suppression (Croft et al. 1998). It is prone to engage in intraguild predation because it is not

dependent solely on TSSMs to survive (Rhodes et al. 2006). In trials combining P. persimilis and

N. californicus, N. californicus continuously displaced P. persimilis (Rhodes et al 2006). Higher

interspecific predation rates are common among generalist phytoseiid species. For N.

californicus, heterospecific feeding may be beneficial in terms of nutrition, development and

oviposition, whereas P. persimilis cannot develop on prey other than Tetranychusrtrt~t~t~r~rtrt spp. and tends

to be cannibalistic when prey densities are low (Walzer and Schausberger 1999).

Neoseiulus californicus has five developmental phases, egg, larva, protonymph,

deutonymph, and adult. The life cycle is half as long as TSSM. It can be completed within four

days, depending on temperature. Neoseiulus californicus lives for approximately 20 days.

Females lay an average of three eggs a day and consume five adult TSSM a day (Krantz 1978,

Escudero and Ferragut 2005). The population corresponds to the increases and decreases of

TSSM (Oatman et al. 1985). While the development rate of phytoseiids is linear and TSSM is









non-linear, high rates of development and consumption enable them to achieve and maintain

control over the TSSM population under the right environmental conditions (Sabelis and Janssen

1994).

Neoseiulus californicus disperses earlier than P. persimilis, has a slower metabolism, a

lower searching efficiency, but a high rate of spatial coincidence with TSSM and can tolerate

starvation (Greco et al. 2004). Neoseiulus californicus has a broad diet range including sap,

honeydew, and pollen and can reproduce on pollen at a comparable rate to a diet of prey

(McMurtry and Croft 1997). Neoseiulus californicus is used widely in Mediterranean regions

where P. persimilis has failed to establish. It is more tolerant to some pesticides and is adapted to

the fluctuations of prey dynamics and a mild climate (Escudero and Ferragut 2005).

Temperature is the most important abiotic factor in predator establishment. It affects

development, survival and reproduction of predatory mites. High temperature fluctuation is the

primary limiting factor that restricts the use ofP. persimilis as a biological control agent

(Escudero and Ferragut 2005). The developmental threshold in N. californicus is estimated to be

9.9oC. Adult females can survive throughout the winter, for over three months under sheltered

conditions. Without entering diapause, or consuming prey, they continue to oviposit and

develop. They have a short generation time and can complete six generations in summer and one

during the winter (Hart et al. 2002).

Effect of Timing of Predatory Releases on TSSM Populations

At high levels of TSSM infestation, the introduction of predatory mites may not be able

to control and maintain TSSM below the economic threshold, which in strawberries is

considered to be between five and 20 motiles per leaf (Oatman 1972, Hardman 2005).

Laboratory and field experiments show that for N. californicus to be an effective biological

control agent, it must be released early in the season when there is a low incidence of spider mite









infestation (Greco et al. 2005). If the predator is released too late in the season when TSSM

population is high and the ratio of TSSM to predator is greater than 10: 1, the released predator

will not have the capacity to consume the pest in high enough numbers to control it to a level

below the economic injury level (Greco et al. 1994).

Other studies have found no relationship between the time when predators are released

and suppression of TSSM. Studies conducted in northern California of Persea mite (Acari:

Tetranychidae) infestations on avacado trees have shown that timing of inundative releases of

various species of predatory mites had no significant effect on the prey population density or on

yield (Hoddle 1998). Another study done in cotton showed similar results, i.e.: there were no

significant differences (P = 0.07) between the early release, late releases (P = 0.06) and the

control (Colfer et al. 2004), nor did releases enhance the natural predator population. However,

in both of these studies, there was a reduction in spider mite populations in all treatments. This

reduction was not attributed to the treatment, but to ecological factors such as plant phylogeny,

climate, and other naturally occurring enemies (Hoddle 1998, Colfer et al. 2004). Plant

physiology has an impact on TSSM population dynamics due to decreasing nutrient availability

from previous mite infestations or other physiological factors (Shanks and Doss 1989, Croft and

Coop 1998). Twospotted spider mite populations naturally begin to decrease after harvest and

with foliar aging (McFarlane and Hepworth 1994).

Research conducted by Waite (2002) in strawberries supports the "Pest in First" (PIF)

theory, which suggests that pests can be controlled by artificially introducing them into the Hield

and allowing them to establish high population densities for several weeks. Predators are then

introduced at the appropriate ratio. As the pests disperse and spread throughout the Hield, the









predators are already established and maintain adequate control and pest: predator ratio

throughout the season.

Rhodes and Liburd (2006) found that releasing predators one time early in the season

alone and in combination with chemical or another biological control could maintain control of

TSSM throughout the season. There is not yet adequate evidence regarding the affect and

appropriate date of release for predatory mites on strawberries. Biocontrol companies differ in

recommendations regarding general release dates. Koppert Biological systemsTM (Netherlands)

recommend that growers apply N. californicus preventively at 10,000 mites/ha at 21 day

intervals. Biobest Biological Systems TM (Westerlo, Belgium) and Biocontrol NetworkTM

(Brentwood, TN) recommend bi-weekly releases throughout the season, and Green Method

BiocontrolsTM (Nottingham, NH) recommends "as needed" monthly releases (2006). Most

growers release biocontrol agents on a standard calendar basis (Greco et al. 2004).

Geographic Information Systems in Pest Monitoring

Mite damage begins at a cellular level in the mesophyll; therefore, it is difficult to

observe early mite damage with visual inspection and field scouting. Precision insect pest

management (PIPM) is a developing technique that would enable growers to detect and analyze

spatial and temporal distribution of agricultural pest damage before it is visible in their fields.

This enables growers to employ preventative tactics before the pests reach economic threshold.

As N. californicus is able to survive in fields with low mite density (Greco et al. 1994), predators

released before damage is visible may have the potential to prevent crop damage by TSSM

populations, consequently, reducing costs and increasing production (Dayang and Kamaruzaman

1999).

Geospatial Information Technology (GIT) is a set of tools associated with site-specific

precision agriculture. The three main elements consist of Global Positioning System (GPS),










imagery systems, and Geographic Information Systems (GIS). These tools can be used to collect

and monitor information about a pest population that can be illustrated as a density or

topographical map referred to as a "bug map". A variety of biological, chemical, and spectral

data from a field can be integrated and analyzed to create maps of vegetative condition in

relation to pest damage (Brewster 1999, Dayang and Kamaruzaman 1999).

The Global Positioning System (GPS) component is essential in constructing an accurate

Hield map. This system uses a constellation of satellites that provides accurate geographic

position coordinates anywhere in the world. Signals are transmitted from satellites and

compared with the time of transition to the time that they are received by the GPS unit on the

ground. Using triangulation the GPS calculates the user' s exact location. Global positioning

systems have been used to make initial Hield measurements and monitor and manage Hield

operations by using application maps.

Vegetation maps commonly use spectral reflectance images. The reflectance values are

correlated with pest infestations. Instruments such as spectroradiometers or other hyperspectral

imaging systems such as a liquid crystal tunable fi1ter (Cambridge Research Instruments,

Woburn, MA) have been used to obtain reflectance images of physiological stress in a plant. The

values of these spectral responses, or signatures, must be discriminated between by constructing

a spectral library. The library is constructed by isolating distinct areas of the electromagnetic

spectrum that are reflected from the leaves. This response is read as a wavelength (nm). The

wavelengths correspond to different energy reflectance that is related to transpiration and

photosynthetic activity and used to assess the health of a plant (Barnes et al. 1996).

Healthy plants reflect in the green (~550 nm) and absorb in the red spectra (~650 nm).

When plants are damaged, they often lose their ability to synthesize carbon compounds and the









ability for chlorophyll to capture and absorb specific wavelengths of light. They have a much

higher reflectance in the blue and red chlorophyll a and b absorption regions of the spectra and

may appear "chlorotic" or yellowish. The reflectance of near infrared energy is also reduced in a

damaged plant. These physiological changes are the most consistent leaf response to

environmental stress. The optimum ranges of sensing a decrease in chlorophyll production and

absorption are between 535-640 nm and 685-700 nm, blue and red spectra, respectively (Jensen

2005). The relationship between plant stress and pest population enables an imagery system such

as infrared photography or a spectrometer to analyze correlated vegetation spectral reflectance

using indices such as NDVI and infrared: red ratioing (Fitzgerald 2004).

The GPS points may be used to georeference the Hield imagery data when it is input into a

geographic information system such as ArcGIS or ENVI (Fitzgerald 2004). Images can be

positioned within a geographically corrected map and viewed spatially to observe the distribution

of pests and related vegetation stress. The GIS could be used to analyze the pest interaction in the

Hield by using spectral imagery or be integrated into a model used to predict the risk of further

infestation. A user could then query the predictive model and receive a map of proj ected pest

occurrences (Brewster 1999). Geographic information technology has been used extensively in

agricultural crops to determine levels of hydration and nutrient content in the soil. Fitzgerald

(2004) used hyperspectrometry to determine presence/absence of the strawberry spider mite,

Tetranychusrtrt~t~t~r~rtrt turkestani, on cotton.

This technology has potential to reduce information collecting and use of pesticides, but

due to a lack of research on the Hield level, particularly in crops such as strawberries, little

application has been attempted. Although GIT has been used to assess mite damage on cotton









and apple trees (Dayang and Kamaruzaman 1999), cost and time constraints are still limitations

to wide use of this technology (Swinton 2003).









CHAPTER 3
BIOLOGICAL CONTROL OF TWO SPOTTED SPIDER MITE, Tetranychus urticae Koch,
WITH PREDATORY MITE, Neoseiulus californicus IN GREENHOUSE AND FIELD
EXPERIMENTS

Twospotted spider mite (TSSM), Tetranychus urticae Koch, is a maj or pest of

strawberries (Fragaria spp.) throughout the world (Oatman et al. 1985, Cloyd et al. 2006,

Wynam et al. 1979, Walsh et al. 2002, Stonneveld et al. 1996, Huffakker et al. 1969, Sanches et

al. 1979). Its management is of particular concern for growers because it has a rapid lifecycle

that can be less than two weeks and sex determination is exclusively arrenotokous (males are

haploid, females are diploid). Genes that are resistant to a miticide will be directly passed to

offspring. Resistance can occur within a year of exposure to pesticides, making chemical control

difficult (Huffaker et al. 1969, Cross et al. 2001).

Biological control is becoming a popular alternative for many strawberry growers in

north Florida (Rhodes et al. 2006, Rhodes and Liburd 2006). Phytoseiulus persimibis is a

phytoseiid mite that has been commonly used to control TSSM in north Florida strawberry

fields. It is an extremely effective predator, but is classified as a type I specialist, meaning that it

is genus-specific with regard to prey preference (McMurtry and Croft 1997). Phytoseiulus

persimilis exploits its prey and perishes when the food source is eliminated. It is highly sensitive

to chemical miticides and fungicides and is unable to survive in temperate climates (Escudero

and Ferragut 2005, Easterbrook 1992).

Neoseiulus californicus (McGregor) is another phytoseiid that is highly effective in

controlling TSSM. Its use is becoming increasingly more important in north-central Florida

(Liburd et al. 2003, Rhodes and Liburd 2006). As a type II generalist, N. californicus provides

stable and regulatory pest suppression (Croft et al. 1998). Studies by Oatman et al. (1981),

Escudero and Ferragut (2005), Easterbrook (1992), and Croft et al.(1998), have demonstrated










that N. californicus is resistant to many chemical pesticides, and is able to remain viable at

variable temperatures (Hart et al. 2002). Studies conducted in California and in Belgium

evaluating two different rates and times ofN. californicus releases found that TSSM populations

were significantly reduced if N. californicus was present early in the season and if the plots had

low TSSM populations (Oatman et al. 1977). Rhodes et al. (2006) found that N. californicus is

able to maintain more consistent control of TSSM populations compared with P. persimills

throughout the season in north Florida strawberry fields. In that study, N. californicus displaced

P. persimilis in both greenhouse and field experiments.

Biocontrol companies differ in their recommendations for release of N. californicus. For

preventative measures, commercial distributors recommend releasing N. californicus at a rate of

10,000-20,000 mites/ha at 21-day intervals, whereas bi-weekly curative releases of 60,000

mites/ha are recommended for continued suppression of TSSM throughout the season. Most

growers release biocontrol agents on a standard calendar basis (Greco et al. 2004).

In this study, both greenhouse and field experiments were conducted to assess the

effectiveness of N. californicus when released at different times throughout the season in north

Florida strawberries. Greenhouse trials were conducted under controlled conditions to isolate the

effect of the predatory releases from environmental effects. Field experiments were conducted to

validate the results from the greenhouse in a larger strawberry ecosystem. The goal of the study

is to determine the phenological stage in the strawberry system when N. californicus is most

effective in controlling TSSM infestations.

Materials and Methods

Colony

A TSSM colony was maintained in the Small Fruit and Vegetable IPM Laboratory at the

University of Florida, Gainesville, FL .The colony was reared on strawberry transplants









contained in one gallon polyethylene pots. Plants were kept under two 60-watt bulbs, 14L:10D

photoperiod, at approximately 320C (day) and 240C (night) at 35% relative humidity. Plants

were provided with ~250 ml of water three times per week (Figure 3-1).

Greenhouse experiment

To assess the most appropriate time to release predatory mites, four treatments were evaluated

in a completely randomized design with 5 replicates. The treatments included the release of N.

californicus at 5-day intervals: 1) early release on day 0; 2) a middle release on day 5; 3) late

release on day 10; and 4) a control with no predatory releases.

The experiment was conducted in a fiberglass greenhouse at the University of Florida.

Twenty strawberry plants (var. Festival) ~20 cm in height were taken from the shade house at the

Entomology and Nematology Department of the University of Florida. Plants were visually

inspected and hand-cleaned to ensure that there were no initial insects or mites on the leaves.

Each plant was trimmed to four trifoliates. Forty TSSM motiles from the laboratory colony were

distributed evenly (10 mites/trifoliate) on each plant using a probe constructed from a 0.020

stainless steel morpho minutien insect pin (Bioqip, Rancho Dominquez, CA) attached to the stem

of a medical cotton swab (Figure 3-2). Each plant was contained within a mesh cage to reduce

cross contamination. The cages were constructed of galvanized hardware cloth (Garden Plus,

North Wilkesboro, NC) of 0.6-cm mesh, 23 gauge, which was bent into a cylinder (30.5 cm in

height, 14.0 cm in diameter) and covered in no-thrips insect screen, mesh size 81Cl X 81Cl

(Bioquip, Rancho Dominguez, CA). The mesh was attached to the cylinder with a hot glue gun

(Surebonder glue gun, FPC Corp., Wauconda, IL) (Figure 3-3). The greenhouse had natural

light, with no artificial light source added. The temperature averaged between 280 C (day) and

150C (night). Plants were hand-watered with 250 ml of water every five days. Predators were

purchased from Koppert Biological Systems, Romulus, MI. Their viability was tested by









observing them in a Petri dish for 15 minutes to assess level of activity. They were used within

48 hours of observation. The ratio of predator to TSSM was 1:10 respectively for each release.

The ratio was determined by calculating the average number of TSSM motiles from the sample

leaflets in each treatment. The number of motiles found on the leaflets of each treatment were

averaged, multiplied by the total number of leaflets on the plant and divided by 10. The

laboratory trials were conducted three times, March 2006, December 2006, and January 2007.

Each trial lasted approximately 30 days.

Sampling

Plants were sampled every five days by detaching one leaflet from each plant and counting

the number of TSSM and N. californicus motiles and eggs under a dissecting microscope to

determine the effect of the timed releases on TS SM populations.

Statistical Analysis. The data were subjected to statistical analysis using analysis of

variance (ANOVA) and LSD means separation (P < 0.05) using the general linear model (GLM)

procedure of the SAS statistical software package (SAS Institute, 2002). The average number of

TSSM motiles and eggs at five-day intervals were compared across treatments. Twospotted

spider mite motiles and eggs were log transformed to comply with the assumptions of the

ANOVA (SAS Institute, 2002).

Field Experiment

A field experiment was established to validate our greenhouse findings. The field was located

at the University of Florida Plant Science Research and Education Unit near Citra, Florida

(82. 170W, 29.410N). The areas had not been cultivated previously. Prior to planting, the field

was treated with a granulated fertilizer (10-10-10) (N-P205-K20) at a rate of 653.3 kg/ha. Beds

with black polyethylene mulch (1.6 mm thick) were laid using a KenncoTM power bedder

(Ruskin, FL) and the soil was inj ected with methyl bromide: chloropicrin (80:20) at a rate of









326.4 kg/ha. Devrinol (napropamide) was applied between row middles at the rate of 4.32 kg/ha

as a pre-emergent herbicide. Drip irrigation tape was laid under the polyethylene sheets with

emitters every 20.3 cm. Strawberries, variety 'Festival', were planted the first week of October

2005 and 2006 on raised beds. There were six 7.3 m long rows per plot, each bed contained

double rows of transplants 0.3 5 m apart within row and 0.3 5 m between row (24 plants per row).

For the first two weeks overhead irrigation was run one time a day for two hours between the

hours of 10:00 AM and 2:00 PM to keep the young plants cool. After establishment, the

strawberry plants were irrigated by the drip tape on a timer 3 times a day for a half hour at the

rate of 8.7 liters per 100 m (0.65 gal/100 ft). The strawberry plants were fertilized through the

drip irrigation line once weekly with 18.5 kg of ammonium nitrate and 32.7 kg of muriate of

potash per ha. In February, the nitrogen was increased to 27. 1 kg/ha. A fungicide was applied

throughout the season 3 times per week in a rotation of several different products (Abound@

[azoxystrobin], Topsin@ [thiophanate], Alliette@ [aluminum tris], and Serenade@ [Bacillus

subtilis]). No insecticides were applied to the research plots. Weeds were controlled by hoeing

between rows and using an s-tine around the border of the plot. Strawberries were harvested one

time per week beginning in January and increased to two times per week in February to reduce

opportunity for damage by birds and other vertebrates.

The experimental design in the 2005-2006 season was a randomized complete block with

six replications of four treatments. In the 2006-2007 season, there were four replications of the

four treatments. Each plot was 7.3 m2 With an 11 m buffer zone between plots. The treatments

were assigned based on plant phenology and included 1) an early release of N. californicus

(Koppert Biological systems, Romulus, MI) 4 weeks after planting (WAP); 2) a middle release at

eight WAP; 3) a late release at 12-16 WAP; and 4) a control with no releases. The late









application was moved up four weeks in the 2006-2007 season due to high temperatures and

faster accumulation of degree days (DD), resulting in high mite populations. In both seasons, the

late release was applied at approximately 1380 DD at a 100C threshold) (Figure 3-4a,b). During

the first season (2005-2006) TSSM was introduced at a rate of 100 TSSM per plot on 27

February, because numbers present initially were extremely low.

Sampling

Systematic random samples were taken once weekly throughout the season. Each week,

eight trifoliate leaves were taken from each plot, four old and four young leaves. The young

leaves were taken from the upper strata of the crown and the old leaves were taken from the

lower strata. We analyzed the old and young leaves separately since previous research by Croft

and Coop (1998) and Sances et al. (1981) indicated that TSSM occurrence differs with foliar age.

The samples were transported back to the laboratory in Zipper Seal Storage BagsC (American

Value, Goodlettsville, TN) for analysis. Neoseiulus californicus and TSSM motiles and eggs

were counted and recorded using a dissecting binocular microscope (10-20X) (Leica MZ l2.5,

McBain Instruments, Chatsworth, CA).

Statistical Analysis

Twospotted spider mite motiles and eggs were log transformed to standardize the

variances and then subj ected to an Analysis of Variance (ANOVA) and Least Significant

Differences (LSD) test for mean separation (P < 0.05). Twospotted spider mite infestations did

not occur until late in the 2005-2006 season, so the total yield data in each treatment was used to

analyze differences. However, during 2006-2007, TSSM was present throughout the season and

yield was calculated for each month of the harvest period. The yield for each treatment was

compared using an ANOVA followed by an LSD test to separate the means. All statistical

analyses were performed using the SAS system (SAS Institute Inc. 2002).












Laboratory Experiments

Releases of N californicus resulted in significantly lower numbers of TSSM motiles

compared with the control treatment (F = 28.69; df = 4, 33 5; P <0.0001) (Figure 3-5 a). By day

10, the number of TSSM motiles in the early (day 0) and the middle (day 5) N. californicus

release were significantly lower compared with the control treatments (F = 5.80; df = 4, 55; P =

0.002). On days 15 and 25, the late treatment (day 10 release) resulted in significantly fewer

TSSM motiles compared with the early and middle releases (F = 29.83; df = 4, 55; P < 0.0001)

(Figure 3-5 b). The number of TSSM eggs showed a similar trend to the motiles. Significant

differences between the treatments and the control occurred in total eggs accumulated throughout

the trial (F = 39.79; df = 4, 55; P < 0.0001) (Figure 3-6 a). By day 25, significantly fewer eggs

were found in the late treatment compared with the early and middle treatments (F = 6.82; df =

4, 55; P = 0.0005) (Figure 3-6 b).

2005-2006 Field Season

During the first 15 weeks of the season, TSSM population was extremely low. Data were

insufficient to conduct a statistical analysis and to report results. Twospotted spider mite

numbers increased from the time of TSSM introduction on 27 February. The release of N

californicus resulted in significantly fewer TSSM motiles and eggs on the old leaves in the early

(16 November release) and middle (14 December release) treatments compared with the late (22

March release) and control treatments (Figure 3-7). Releases of N californicus in the early and

middle season maintained significantly lower populations of TSSM throughout the season while

the populations in the late and control treatments continued to increase (motiles: F = 22.84; df =

8, 135; P < 0.0001, eggs: F = 44.62; df = 3,135; P < 0.0001) (Figure 3-8). The young leaves also

contained significantly fewer TSSM motiles and eggs in the early and middle releases ofN.


Results










californicus compared with the control (motiles: F = 20. 12, df = 8, 13 5, P < 0.0001; eggs: F =

29.37; df = 3, 135; P < 0.0001) (Figure 3-9). Similar to the results on the old leaves, the N.

californicus releases early in the season significantly suppressed TSSM throughout the season

compared with the late and control treatments (Figure 13-10). The age of the leaves did not

affect TSSM eggs and motiles throughout the season (F = 1.30; df = 1,280; P = 0.3 (Figure 3-

11).

2006-2007 Field Season

Significant differences in TSSM populations did occur between leaf age classes in the second

season (2006-2007). There were no significant differences during the pretreatment period

between any of the treatments in the old leaves (motiles: F = 1.53; df = 3,12; P = 0.3 eggs: F=

1.05; df = 3,12; P = 0.4) or in the young leaves (motiles: F = 0.41; df = 3,12; P= 0.7 eggs:

F=1.58; df = 3,12; P = 0.2). Significant differences began to appear between the treatments in

the old leaves (motiles: F = 5.79 df = 3,12; P = 0.01 eggs: F = 5.46 df = 3,12; P = 0.01) and

young leaves (motiles : F = 3.43; df =3,12; P = 0.05 eggs: F = 3.95 df = 3,12; P = 0.04) on 26

December. The numbers of TSSM motiles and eggs continued to decrease in plots treated with

N. californicus throughout the season and differences between treated and untreated plots

became more statistically significant on 30 January in the old leaves (motiles: F =20.62 df=

3,12; P 0.0001 eggs: F= 6.03 df = 3,12; P = 0.01). However, the young leaves no longer

showed a significant difference between treated and untreated (motiles: F = 1.33 df = 3,12; P =

0.05 eggs: F = 3.95 df = 3,12; P = 0.3). These trends persisted throughout the remainder of the

season. The old leaves contained significantly more TSSM motiles and eggs than the young

leaves in the 2006-2007 season (Figure 3-12).

Overall, old leaves contained significantly fewer TSSM motiles and eggs among the early,

middle and late treatments compared with the control (motiles; F = 13.13; df = 3, 268; P <









0.0001, eggs: F = 6.81; df = 3,268; P = 0.0002) (Figure 3-13). The average weekly number of

TSSM motiles shows that within ca. two weeks after each release, N. californicus was able to

reduce TSSM for the remainder of the season (Figure 3-14). No treatment differences were

observed on the young leaves (motiles: F = 2.26; df = 3, 12; P = 0.08, eggs: F = 0.59; df = 3,12;

P = 0.6) (Figure 3-15). The weekly average number of TSSM on the young leaves was not

significantly different in any of the treatments (Figure 3-16).

Yield: In the 2005-2006 season the yield was not significantly different among treatments

(F = 1.60; df =3,15; P = 0.23 1). The total yield for the control averaged 74.81 7 kg/plot; early

treatment averaged 62.114 kg/plot, middle treatment averaged 64.41 4 kg/plot and late treatment

averaged 59.414 kg/plot.

The average total yield through the 2006-2007 season was not significantly difference

among any of the treatments (F = 0.09; df = 3,12; P = 0.97). The same pattern occurred for yield

collected in January (F = 1.47; df = 6,41; P = 0.2), February (F = 4.84; df = 6,41; P = 0.5), and

March (F = 1.43; df = 6,41; P = 0.98) (Table 3-1).

Discussion

Greenhouse Experiment

The greenhouse experiment demonstrated that one early season release of N californicus

was able to maintain low numbers of TSSM. Within five days of each release, N. californicus

significantly reduced numbers of TSSM in the treated plants compared with the untreated plants.

The early and middle treatments had low initial TSSM populations that remained low with the

introduction of N californicus. Neoseiulus californicus has also been observed in previous

studies to maintain TSSM populations at low densities (McMurtry and Croft 1997). Twospotted

spider mite populations naturally increased in the untreated plants to very high levels. Within

five days of N californicus release, the TSSM populations in the late-treated plants fell sharply










and were significantly (P = 0.05) lower than in the early and middle treatments. The sharp

decline in the late treatments, along with stable control in the early and middle treatments,

indicates that N. californicus demonstrate a functional response with variations in prey density

(Hassell et al. 1976).

Field Experiments.

The Hield experiments in both seasons validate our greenhouse trial that indicates the ability

for N. californicus to control TSSM populations. The number of TSSM recorded during the

2005-2006 Hield season was lower than the 2006-2007 season. Several environmental factors

differed between the two Hield seasons. The 2005-2006 season was the first time the Hield was

used to cultivate strawberries. The lack of host plants prior to the growing season may have

contributed to the absence of TSSM population. Throughout the season there were extreme

temperature fluctuations. Twospotted spider mite populations are sensitive to ambient

temperature. They reproduce rapidly in warm temperatures and populations have been observed

to decrease at cooler temperatures (Hart et al. 2002, White and Liburd 2005). In the 2005-2006

season, there were frequent recurrent freezes throughout the season. The daily low temperature

fell below 00C for a total of 15 days in the 2005-2006 season and only for 2 days in the 2006-

2007 season. The maximum daily temperature ranged from 70C to 320C in 2005-2006 and the

range was 120C to 320C in 2006-2007. (Florida Automated Weather Network, 2007). The colder

temperatures throughout the 2005-2006 season may have helped to suppress the TSSM

population.

The 2005-2006 Season

The 2005-2006 season had low initial TSSM populations in all plots. Within one week of

introduction of TSSM on 27 February, the population in the late-release treatment plots and

control plots rapidly increased throughout the rest of the season. However, N. californicus which









had been released on 16 November (early treatment) and on 14 December (middle treatment) had

been able to establish in strawberry plots without TSSM prey and when TSSM populations

developed, N. californicus was able to maintain consistent control of TSSM to a level

significantly lower compared with the late-release and control treatments. We found no

difference in TSSM occurrence among the age classes of leaves, most likely due to the low

TSSM populations on all leaves throughout the season. The number of TSSM in the early-release

and middle-release treated plots of both old and young trifoliates never exceeded 5 motiles per

trifoliate. The late treatment contained higher numbers of TSSM when the late application ofN.

californicus was released. As a result of low initial predator: prey ratio and the warm

temperatures late in the season, N. californicus never achieved control in the late treatment plots

(Greco 2005). The lack of treatment effect on yield may have been due to the late season

infestation. Plants are more vulnerable to yield loss due to TSSM damage during the critical

vegetative growth period early in the season than they are later in the growing season (Rhodes et

al. 2006, Oatman and Voth 1972 and Sances et al. 1981). Results by English-Loeb and Hestler

(2004) suggest that June bearing varieties like Festival are very tolerant of TSSM damage in

their first year of planting and do not show signs of vegetation or fruit loss.

The 2006-2007 Season

The second season (2006-2007) introduced several new variables. Temperatures were

milder than in the previous year, and the natural vegetative cover that was left unmanaged

between seasons provided abundant habitat for TSSM development. Despite the ecological

challenges of the 2006-2007 season, N. californicus was able to achieve control of TSSM

populations in all the treatments throughout the season with the early and middle release

treatments being significantly lower than the late treatment in the older leaves. We did not see

treatment differences in the young leaves, which may be because of the low numbers of TS SM









found on the younger leaves. Twospotted spider mite aggregated on the older leaves and N.

californicus dispersed to the areas of higher prey density. The lack of treatment effect on the

young leaves is consistent with our greenhouse findings of the tendency for N. californicus to

demonstrate a density-dependent response. However, plots of all treatments contained higher

numbers of TSSM throughout the 2006-2007 season than the 2005-2006 season. Results indicate

that when released at the appropriate ratio (1: 5 to 1: 10 predator: prey), one early release of N

californicus is able to maintain significant control of TSSM throughout a growing season.

However, if initial TSSM populations are too high to achieve an appropriate ratio, as we had in

the 2006-2007 season, a grower may need to apply a miticide to reduce TSSM numbers prior to

an early-season release of N californicus to maintain adequate season long control (Rhodes et al.

2006).

Yield was substantially lower in the 2006-2007 season than in the 2005-2006 season. This

may be due to a combination of factors including a much higher TSSM population in the field

early in the second season, severe bird and squirrel infestation and mid-season nutrient

deficiency. No yield differences in either season could be directly attributed to TSSM damage.

English-Loeb and Hestler (2004) found that reduction in strawberry yield from TSSM varies

with maturity of plant and timing of TSSM infestation. Oatman and Voth (1972) also found that

TSSM presence was not directly correlated with yield loss. However, Walsh (2002) and Oatman

et al. (1985) found that under certain conditions, potential yield reduction due to TSSM

infestation can range from 10%-29%. The relationship between TSSM and berry varies widely

which suggests that it is an ecologically dynamic process and is difficult to test under field

conditions.
























Figure 3-1. Twospotted spider mite colony maintained in the laboratory for greenhouse
experiments.





















Figure 3-2. Transferring TSSM from the laboratory colony onto strawberry plants for the
greenhouse trials.









~I II












Figure 3-3. Mesh cages constructed to contain TSSM and N. californicus during the greenhouse
trials.










I 1 I 1 4 1

131 121


1 2 1 I 1 I


1 4 1 1 3 1
324 ft (98.8 m)


121

141


131


I 1 I


131

I 1 I


141


121


131


121


141


131


24 ft(7.3 m)


6 ft 11 m


O


Nf


Figure 3-4. Maps of the layout of the treatments in the field A) Map of strawberry field 2005-
2006 field season B) Map of strawberry field 2006-2007 field season.


24 ft (7.3~4 ft (7.3 m3
~~rl 1 136R("mr2
EI
1 4 1 I 1 I


O i

O B


204 ft (62.2 m)





















Tr


Middle Late
Treatment


Control


Late
Control


a a


c5- c


Day 0 Day 5 Day 10 Day 15 Day 20 Day 25



Figure 3-5. Twospotted spider mite motiles in greenhouse trials. A) Overall average number of
TSSM motiles. B) Five day interval observations of TSSM motiles per leaflet for
each treatment. Treatments with the same letters are not significantly different from
each other at P < 0.05, according to LSD test performed on log-transformed data.


C


Early








- Early
-Middle
























Middle Late
Treatme nt


Control


b b


Day 0 Day 5 Day 10 Day 15 Day 20 Day 25



Figure 3-6. Twospotted spider mite eggs in the greenhouse trials A) Overall average number of
TSSM eggs. B) Five day interval observations of TSSM eggs per leaflet for each
treatment. Treatments with the same letters are not significantly different from each
other at P < 0.05, according to LSD test performed on log-transformed data.


Ci

Early





- Early
-Middle
Late
Control


T a

































































Figure 3-8. Weekly average of TSSM motiles per plot on old leaves in 2005-2006 field season.
Treatments with the same letters are not significantly different from each other at P <
0.05, according to LSD test preformed on log-transformed data. No letters indicate no
significant differences on a given date.


a motiles
- eggs





- r B b ~~~


I


LU "
-0 5






o


200

1 50

100

50


Early Middle


Late Control


Treatment


Figure 3-7. Average number of TSSM motiles and eggs per trifoliate on the old strawberry
leaves 2005-2006 field season. Treatments with the same letters (A, B for motiles and
a, b for eggs) are not significantly different from each other at P < 0.05, according to
LSD test preformed on log-transformed data.


^ 500
-c
9-450

S400

S350

e!300

e 250

.* 200

I 150

v, 100


50


- Early
- -Middle
Late
Control


-I


8-M ar


15-Mar 22-Mar 29-Mar


5-Apr


12-Apr
























- -


O
200

.150

w"100

S50

0
o
2
o
2


m motiles
m eggs


B b


Bb


Early


Middle


Late


Control


Treatment


Figure 3-9. Average number of TSSM motiles and eggs per trifoliate on the young strawberry
leaves 2005-2006 field season. Treatments with the same letters (A, B for motiles and
a, b for eggs) are not significantly different from each other at P < 0.05, according to
LSD test preformed on log-transformed data.


-350

a300
E
250
I-
L 200

I lo
I 100
v, 50


o 8-


-Middle
Late
- ~ alControl


12-Apr


15-Mar 22-Mar 29-Mar


5-Apr


Figure 3-10. Weekly average of TSSM motiles per plot on young leaves in 2005-2006 field
season. Treatments with the same letters are not significantly different from each
other at P < 0.05, according to LSD test preformed on log-transformed data. No
letters indicate no significant differences on a given data.


aa


-


-Mar


























I I


Young
a Old


LT


Ea rly


Middle


Late


Control


Tre atme nt



Figure 3-11i. Comparison of young and old leaves 2005-2006 season. No significant (P < 0.05)
differences between young and old leaves for any treatment.


S800

700- m Young
a a Old
600
O
S500

400

300

..200 -1b

o 100
0

Early


1


Middle Late


Control


Treatment


Figure 3-12. Comparison of young and old leaves 2006-2007 season within each treatment.
Letters represent difference between young and old leaves at P < 0.05.














S200 a Motiles
180 a Eggs
a 160-
v, 140-
en a
a 120-
100
c* 80-

a C0



o Early Middle Late Control
Tre atme nt




Figure 3-13. Average number of TSSM motiles and eggs on old trifoliates during the 2006-2007
season. Treatments with the same letters (A, B, C for motiles, and a, b) are not
significantly different from each other at P < 0.05, according to LSD test performed
on log-transformed data.










S 2500-
E -- Middle
11 2000-
e! Late
Control
S 1500-



100








20 0
18 -a otle








1 00-
180-



S60 -1 A a A_ a



o Early Middle Late Control
Treatment





Figure 3-15. Average number of TSSM motiles and eggs on young trifoliates during the 2006-
2007 field season.Treatments with the same letters (A, B for motiles and a for eggs)
are not significantly different from each other at P < 0.05, according to LSD test
performed on log-transformed data.












2500 Early
Middle
2000
Late
1500 -1 Control


1000


500

0


c~ ,c~ C~2 C~2 ~002 ~002 ~002
O` MMO`O`
\2~ h~3' h~L' ~~;
;"d:~"~;3~. ;, II JV ,,~L` o~L` 3~0~L`
Week


Figure 3-16 Average weekly number of TSSM motiles on the young leaves in each treatment.
Arrows indicate the release dates of N. californicus.



Table 3-1. Strawberry yield for January, February, and March 2007, with total yield in kg/plot.
Treatment January February March Total Yield


Mean SE
12.7 & 1.4 10.1 + 1.8 10.4 & 1.4 33.0.1 0.86
8.2 & 1.4 8.3 A 1.8 10.0 & 3.1 26.11 0.63
11.8 & 10 9.8 & 2.3 8.2 & 3.1 29.71 1.08
12.21 0.0 10.0 11.4 10.0 & 2.7 32.2 & 0.72
(P < 0.05) differences occurred between treatment means.


Early
Middle
Late
Control
No significant









CHAPTER 4
EFFECT OF Neoseiulus californicus RELEASES ON ARTHROPOD COMMUNITIES IN
NORTH FLORIDA STRAWBERRY FIELDS

Twospotted spider mite (TSSM), Tetranychus urticae Koch, is a key pest on strawberries

(Fragaria x anana~ssa Duchesne) in north Florida. High populations of TS SM can lead to a

significant reduction in foliar and flower development, decreasing the quality and quantity of

mature fruit (Rhodes et al. 2006). Because of its short life cycle and high fecundity, TSSM can

increase rapidly and is able to become highly resistant to most pesticides in a short period of time

(Williams 2000). Outbreaks have intensified over the last few decades due to increased use of

pesticides and modern cultural practices (Huffaker and McMurtry, 1969 and Escudero and

Ferragut, 2005). As traditional methods of chemical control are becoming less effective, and

marketability due to chemical residue has become a social concern, growers are beginning to rely

on natural enemies as an alternative to chemical management systems (Escudero and Ferragut

2005 and Rhodes et al. 2006). Approximately 40% of Florida' s strawberry growers practice

inundative biological control methods (Mossler and Nesheim 2002).

Field studies conducted between 1964-1980 in southern California identified ten insect

species belonging to families Thripidae, Cecidomyiidae, Coccinellidae, Staphylinidae,

Anthocoridae, Lygaediae, Chrysopidae, and Hemerobiidae and nine phytoseiid mite species to be

natural enemies of TSSM (Oatman et al. 1985). Rondon et al. (2004) conducted laboratory

studies with bigeyed bugs, Geocoris punctipes Say, minute pirate bugs, Orius insidiosus (Say),

and the pink spotted lady beetle, Coleomegilla maculata DeGeer, to assess their effectiveness as

predators for TSSM and found that many of these insects prey on TSSM, but also show a

preference for other phytophagous insects.

Predatory mites in the phytoseiid family have been found to be the most effective predators

in controlling TSSM and have been used successfully in glasshouses since 1968 (Kozlova et al.









2005). Two of the most commonly used phytoseiid mites are Phytoseiulus persimilis and

Neoseiulus californicus (McMurtry and Croft 1997 and Cloyd et al. 2006). Oatman et al. (1972)

and Kozlova et al. (2005) found that while P. persimilis is effective in controlling TSSM, as a

Type I specialist predator, it is genus specific with regard to prey preference and tends to

decimate TSSM populations altering the ecosystem. Its introduction leads to significant

intraspecific competition and a disruption of natural predation on TSSM. However, Colfer et al.

(2004) found that releases of generalist species of phytoseiid mites did not enhance or decrease

the diversity or abundance of natural enemy populations. Studies have not been attempted to

assess the effects of N. californicus on the diversity of native arthropods in the field.

Indices to measure diversity in ecological systems have been available for many years

(Magurran 2004). These are numerically expressed to indicate the relative abundance of taxa in

an ecosystem. The most commonly used indices are richness (s), Shannon-Weaver index (H')

(Shannon and Weaver 1949) and evenness index (J) (Pielou 1966). Richness is calculated by the

sum of the taxa present in a system. The Shannon index is the most often used index of

diversity. This index is the negative sum of the proportional abundance of taxa multiplied by the

natural logarithm of the proportional abundance of each taxon:


H'= -E pi Inpi
i=1

Where Pi = the proportional abundance of taxon.


The Shannon Index weighs all taxa proportionately to their abundance in the sample

therefore, reducing bias (Powers and McSorley 2000). Many additional indices have been

developed (Magurran 2004) but the original Shannon index remains widely used, facilitating










comparisons among various studies. The evenness index compares and standardizes the natural

log of richness (s) and ranges from 0-1.



J= H '
In s

Our hypothesis is that inundative releases of N californicus to control TSSM in

strawberries will not negatively impact other key natural enemies and arthropod diversity in the

system. The obj ective of this study is to identify and document common arthropods in the

strawberry system and determine the impact of N californicus releases on the presence and

abundance of these taxa. In addition, we will measure evenness and richness of organisms in the

sy stem.

Materials and Methods

An experiment was conducted at the University of Florida Plant Science Research and

Education Unit, near Citra, FL (82. 170W, 29.410N). The experimental design was a randomized

complete block with four replications and four treatments. Treatments were assigned based on

plant phenology and included: 1) an early release ofN. californicus at four weeks after planting

(WAP), 2) a middle release of N californicus at eight WAP, 3) a late release of N californicus at

12 WAP and 4) a control (no releases). The site was prepared in beds with black polyethylene

mulch (1.6mm) using a KenncoTM power bedder (Ruskin, FL). The soil was inj ected with methyl

bromide: chloropicrin (80:20) at a rate of 326.4 kg/ha per acre two weeks prior to planting.

Strawberries, variety 'Festival', were planted the first week of October on raised beds. There

were 6 rows per plot, each bed contained double rows of transplants 0.3 5 m apart within row and

0.35m between row (24 plants per row). Strawberry plants were fertilized, weeded and sprayed









with fungicides using standard commercial practices (Brown 2003). No insecticides were applied

to the plots.

Preliminary study. A preliminary study was conducted one year prior to the main study to

determine appropriate sample size and to evaluate the indices. Data were collected during the

late season of the 2005-2006 field season at 12 WAP, to assess the season-long effect of N.

californicus released in the early-season, mid-season, and late-season. One yellow sticky

Pherocon@ AM Trap (YST) ( Trece, Inc., Adair, OK) constructed from a 28 cm X 23 cm yellow

board with 59 one cm squares forming a grid on the board was hung on a garden stake 0.3 meters

above the plants. Each trap was placed in the center row of each treatment plot. Traps were

collected weekly and placed into Zipper Seal Storage BagsC (American Value, Dolgencorp, Inc,

Goodlettsville, TN) and brought back to the laboratory to be examined under a dissecting

microscope. Three YSTs were randomly chosen from the samples and each of the 59 one-

centimeter squares on each trap was examined to determine the number of unique families found

on each square. The families that were observed on each square of the YST were counted and

compiled into a comprehensive list. The number of unique families represented on each square

was recorded. The percentage of unique families found on each square was plotted for each

square to create a cumulative frequency distribution. The optimal number of squares was

determined from this distribution to be 28 squares. We used these data to create a sub-sampling

for data analysis in the main study.

Main study. Based on the homogeneity of the preliminary results, field observations, and

previous research by Garcia-Mari and Gonzalez-Samora (1999) indicating that N. californicus

takes approximately two weeks to establish in a field we decided to conduct sampling at one-

month intervals two weeks after each release date to obtain more complete data on the effect of









N. californicus presence in the strawberry Hield throughout the season. Samples were taken in the

2006-2007 Hield season during the early-season (1-2 months after planting), middle-season (3 to

4 months after planting) and late-season (4-5 months after planting). Individuals were identified

to family or genus and counted and recorded using the same method as described in the

preliminary sampling. Data were collected throughout the season and compared to determine the

effect of N californicus releases on interspecific insects and mites in the field with respect to

plant phenology. The treatments were categorized into "treated" and "untreated" in order to

isolate the effect of the N. californicus releases.

In order to avoid bias in the sampling techniques used to assess the diversity of arthropods

present in the Hield, we employed four sampling methods. These methods included 1) In situ

(visual inspection) 2) foliar sampling 3) pitfall traps and 4) yellow sticky traps.

In situ sampling. Twenty-four strawberry plants from the center of the inner rows of each

plot were visually inspected once weekly for two weeks during each sample period. The visual

inspection consisted of a scan for 30-45 seconds per plant. This enabled us to sample the larger

arthropods occurring in the Hield including hymenopterans and some hemipterans and

coleopterans.

Foliar sampling. Four young and four old trifoliates were randomly taken from each

treatment plot once weekly for two weeks between each of the three predatory releases and were

placed into Zipper Seal Storage BagsC and brought back to the laboratory. The leaflets were

visually inspected under the dissecting binocular microscope for leaf dwelling and minute

arthropods such as the thysanopterans and hemipterans.

Pitfall traps. Traps were constructed of a white polypropylene deli containers 14 cm deep

and 10.5 cm in diameter (Fabri-Kal corp. Kalamazoo, MI) Eilled with two cm of 10% dish soap









and water solution. The traps were placed in the soil and under the black plastic mulch in one of

the two center rows of each treatment plot to capture cursorial soil arthropods and soil dwellers,

such as collembola, arachnids, coleopterans, and some hymenopterans (Southwood 1966). The

traps were left in the field for 48 hours each week for a 2-week period between each of the three

predatory releases.

Yellow sticky traps. Traps were placed in one of the two center rows of each plot at foliar

height, approximately 30 cm above ground to capture hymenopteran, dipteran, and other winged

arthropods. The YST were left in the field for 48 hours each week for a two-week period among

each of the three predatory releases. The 28 squares (47% of the trap area) were observed for

analysis.



Statistical analysis

Families of arthropods with the highest relative abundance among treatments were compared

with an analysis of variance (ANOVA) and an LSD means separation to determine differences

between treatments (SAS Institutes, 2002). Families that were present in numbers too low to

conduct meaningful statistical analysis were recorded in a species list for each treatment, but

were included in diversity calculations (Tables 4-1 to 4-4).

Shannon diversity index, evenness, and richness were calculated for each plot and for each

sampling period. The results were subj ected to an ANOVA and means were separated with LSD

(a=0.05) to determine significant differences between the treatments.



Results

Preliminary Study. Twenty-eight 1-cm squares included 90% of the arthropod families

found on the YST (Figure 4-1). Therefore, 28 squares could be analyzed to assess the diversity










on the YSTs.There were no significant differences in level of diversity between any of the

treatments. All measures, Shannon (F = 0.49; df = 3, 12; P = 0.7, evenness (F = 1.3 1; df = 3,12;

P = 0.3), and richness (F = 1.05; df = 3, 12; P = 0.4) indicated that the families found in each

treatment were consistent throughout the trial period and among treatments.

Main Study. In the early season (December 5-16) we compared the plots treated with N.

californicus and untreated plots (controls). On the YST, we recorded insects from seven families:

Aphididae, Cecidomyiidae, Dolichopodidae, Sciaridae, Phoridae, Thripidae, and Chalcidodoidea.

However, no significant differences were found between the treated and untreated plots in five of

the seven families (Figure 4-2), Aphididae (F = 0.07; df = 1, 30; P = 0.8), Cecidomyiidae (F =

0.24; df = 1, 30; P = 0.6), Dolichopodidae (F = 3.21; df = 1, 30; P = 0.9), Sciaridae (F = 0.07; df

= 1, 30; P = 0.8), Muscidae (F = 0.07; df = 1, 30; P = 0.8) and Phoridae (F = 0.22; d f= 1, 30; P

= 0.6). Numbers of Thripidae (F = 4.81; df = 1, 30; P = 0.04) and Chalcidodoidea (F = 8.44; df

= 1, 30; P = 0.01), were higher in the plots treated with N. californicus than those that were

untreated. In the pitfall traps, no significant differences occurred between the treated and

untreated plots for the most abundant taxa, which included Collembola (F = 0.0; df = 1, 30; P =

1), Fomicidae (F = 0.95; df = 1, 30; P = 0.3), Aphididae (F = 0.29; df = 1, 30; P = 0.6) and

Cecidomyiidae (F = 2.81; df = 1, 30; P = 0. 1) (Figure 4-3). Data collected from YST indicate

that the Shannon index (F = 0.24; df = 1, 14; P = 0.6), evenness (F = 0.0; df = 1, 14; P = 1.0),

and richness (F = 1.52; df = 1, 14; P = 0.2) were not significantly different (P = 0.05) between

treatments (Table 4-5). Similarly, data collected from the pitfall traps also indicated no

differences in Shannon index (F = 0.0; df = 1, 14; P = 1.0), evenness (F = 0.20; df = 1, 14; P=

0.7), and richness (F = 0.01; df = 1, 14; P = 0.9) (Table 4-6).










During the mid-season (January 5-16) we recorded no significant (P = 0.05) differences

among plot treatments on the YST for the most abundant families: Chalcidodoidea (F = 0.41; df

= 2,29; P = 0.7), Muscidae (F = 2.69; df = 2, 29; P = 0. 1), Aphididae (F = 0. 15; df = 2, 29; P =

0.9), Sciaridae (F = 0.73; df = 2, 29; P = 0.5), Thripidae (F = 0.78, df = 2, 29, P = 0.5), Phoridae

(F = 0.33; df = 2, 29; P = 0.7) and Cecidomyiidae(F = 0.38; df = 2, 29; P = 0.7) (Figure 4-4). In

the pitfall traps no significant differences among the treatment plots occurred for Collembola, (F;

= 1.26; df = 2, 29; P = 0.3,) Lygeaidae (Pachybrachyus spp.), (F = 1.06; df = 2, 29; P = 0.4) or

spiders (F = 0.46; df = 2, 29; P = 0.6). Numbers of Formicidae were greater (F = 3.39; df = 2,

29; P = 0.05) in plots treated "early" with N. cahifornicus than in untreated plots (Figure 4-5).

On the YSTs, the Shannon index (F = 1.68; df = 2, 13; P = 0.2), evenness (F = 0. 10; df = 2,

13; P = 9), and richness (F = 2.28; df = 2, 13; P = 0. 1) showed no significant (P = 0.05)

difference among the early, middle releases, and the untreated plots (Table 4-7). Likewise, for

the pitfall traps, the Shannon index (F = 2.28; df = 2, 13; P = 0. 1), evenness (F = 0. 19; df = 2,

13; P = 0.8) and richness (F = 0.68; df = 2, 13; p = 0.5) were not-significantly (P = 0.05)

different among treatments (Table 4-8).

On YSTs measured late in the season (February 2-12), no significant differences among

treatments occurred in the following families: Chalcidodoidea (F = 0.3 1; df = 3, 12; P = 0.8),

Sciaridae (F = 0.90; df = 3, 12; P = 0.5), Muscidae (F = 0.24; df = 3, 12; P = 0.9),

Cecidomyiidae, (F = 1.95; df = 3, 12; P = 0.2), Dolichopodidae (F = 1.22, df = 3, 12; P = 0.3),

and Cicadellidae (F = 2.02, df = 3, 12, P = 0.2. (Figure 4-6). In the pitfall traps, there were no

significant differences among treatments for Collembola, (F = 0.35, df = 3, 12, P = 0.8),

Lygeaidae (Pachybrachyus spp.) (F = 0.52, df = 3, 12, P = 0.7), spiders (F = 1.33, df = 3, 12, P =

0.3), or Sciaridae (F = 0.04, df = 3, 12, P = 0.99). (Figure 4-7).









The diversity indices for the YST and the pitfall traps showed no significant differences

among treatments. No differences (P < 0.05) among treatments were demonstrated for YST in

the Shannon index (F = 2.38, df = 2, 13, P = 0.1i), evenness (F = 1.51, df = 2, 13, P = 0.3),

richness (F = 2.34, df = 2, 13, P = 0. 1) (Table 4-9) nor for pitfall traps in the Shannon index (F =

0.56, df = 2, 13, P = 0.7), evenness (F = 1.09, df = 2, 13, P = 0.4) and richness (F = 0. 19, df = 2,

13, P = 0.9) (Table 4-10).

Overall, the visual and foliar samples did not produce sufficient numbers of arthropods to

conduct robust statistical analysis. However, they should not be dismissed since the foliar and

visual counts revealed the presence of phenological trends and important natural predators of

TSSM. Visual inspection during the mid-season revealed high numbers of Pachybrachius spp.

and a dramatic decline in aphid population directly following an increase in syrphid fly

abundance (Table 4-3). Foliar sampling indicated that as the season progressed the abundance of

Coccinellids increased in all treatment plots (personal observation), as did Sixspotted thrips

(.A Ichothli if sexmaculats) and Geocorid bugs (Geocoridae spp.) Late in the season, numbers of

taxa decreased, and an increase in Sciaridae was observed (Table 4-4).

Discussion

As hypothesized, the release of N. californicus did not have a statistically significant effect

on arthropod diversity in the strawberry system. The maj or insect families, which included

Thripidae, Cecidomyiidae, Coccinellidae, Staphylinidae, and Lygaediae, as cited by Oatman et

al. (1985) and Rondon et al. (2004), were observed. We did observe a period in the early season,

which was unseasonably warm, when thrips (Frankliniella spp.) and Chalcidoidea were high in

all plots and significantly higher in the treated plots compared with the untreated plots.

Adult thrips migrate into flowering strawberry crops during warm humid periods of the

growing season. Neoseiulus californicus is a known predator of thrips in some crops, but N.









californicus cannot access them once they take shelter within the styles of the strawberry flowers

(Cross et al, 2001). However, N. californicus may consume natural enemies, allowing thrips to

flourish and indirectly increasing the number of thrips in the system (Cross et al. 2001).

Increased levels of the superfamily Chalcidoidea, all of which are parasitoids of thrips, were

found in significantly higher numbers in the plots with high numbers of thrips indicating a

density dependent correlation.

High numbers of aphids were also found in all treatments during the early-season. Many

species of aphids are known to be pests of strawberry early in the season when the climate is

warm, but populations decrease rapidly as natural predators establish in the system (Jones 1976).

Our observations of decreasing numbers of aphids in conjunction with increased syrphid fly

populations are consistent with studies conducted in north Wales showing that syrphid flies are

effective predators of aphids and can cause considerable reduction in aphid numbers (Cross et al.

2001). Foliar sampling indicated that as the season progressed the abundance of sixspotted thrips

(.A hlothlil'\ sexmaculats) and Geocoridae spp. increased in all treatment plots. These findings

are consistent with previous research by Jones (1976) indicating that predation tends to increase

gradually throughout the season. At the time of the late-season, sampling, arthropod numbers had

declined in all treatments and Sciaridae dominated in all plots. During the mid to late-season

considerable damage to the fruits from bird and squirrel feeding was observed which may have

been a factor in the increase of Sciaridae. Sciaridae have been shown to be attracted to damaged

plant tissue as sources of food and habitat (Jones 1976).

Although we found very few statistically significant differences between treatments during

the early sampling periods, we recorded differences in the arthropod assemblage throughout the

season among all treatments. The high level of richness and insect diversity in the strawberry










system may be a key factor that reduces the effect of N. californicus releases on the structure of

the strawberry system (Jones 1976, Powers and McSorley 2000). One of the natural "services"

provided by ecosystems is the natural control of pest and invasive species (Klein et al. 2006).

The maj ority of arthropods in the strawberry system are generalist feeders. Therefore, abundance

of alternate food sources may mitigate disruption by an introduced predator (Cross et al. 2001).

The dynamics of the arthropod assemblage seem to be more highly related to plant phenology

and ambient weather than to interspecific competition.











Table4-1. Cumulative number of each taxa found in each treatment in the three sampling periods in vellow sticky traps.


December
E M LC
Acanalonidae 2 1 2 1
Aleyrodidae 2 16 26 14
Aphididae 383 643 579 539
Bethylidae 1 -
Bibionidae 5 5 -
Cecidomyiidae 11 10 6 9
Chalcidoidae 34 59 83 91
Chrysomelidae 1
Cicadellidae 2 11 17 5
Coccinellidae 1 -
Cucujidae 1 11 -
Dolichopodidae 7 17 4 3
Drosophilidae 3 -
Ichneumonidae 4 4
Lepidoptera 1 1 -1
Muscidae 8 7 9 30

Nitulidae 2 -
Phloeothripidae 3 2 4 3


January
E ML C

2 17 3 1
12 10 5 11

3 1 -1

10 8 14 4
61 66 78 53
1 1 1


3 3 42

4 3 2




4 3 -



23 13 15 15
1 1 -

10 14 40 9
5 2 -1
23 17 24 8
2 1 -
-1 1
5 82 3
16 17 9 10


February
E ML C




33 26 33 31


3 -1 6
10 7 3 4






17 14 14 19



2 12 -



52 48 94 48
1 11 3
2 11 1
3 21 1
2 44 2
2 85 2


Acanalonidae
Aleyrodidae
Aphididae
Bethylidae
Bibionidae
Braconidae
Cecidomyiidae
Chalcidoidae
Chrysomelidae
(Alticinae spp)
Cicadellidae
Coccinellidae
Dolichopodidae
Drosophilidae
Ichneumonidae
Leiodidae

Lepidoptera
Lygaeidae
(Pachybrachius
spp)
Muscidae
Nitulidae
Phloeothripidae
Phoridae
Psychodidae
Sciaridae
Staphylinidae
Syrphidae
Tachinidae
Thripidae


Aleyrodidae
Aphididae
Cecidomyiidae
Chalcidoidae
Chrysomella
Cicadellidae
Coccinella
Dolichopodidae
Drosophilidae
Ichneumonoidae
Ichneumonoidea
(Braconidae spp)
Lepidoperera spp.
Muscidae
Nitulidae
Lygaeidae
(Pachybrachius
spp)
Phoridae

Psychodidae
Sciaridae
Araneida
Staphylinidae
Syrphidae
Tachinidae
Thripidae


Phoridae
Platygatroidae
Psychodidae
Sciaridae
Staphylinidae
Thripidae


3 16 7 7

1 3 10 -
5 5 50 10

39 39 -23


E = early treatment, M = middle treatment, L = late treatment and C = control.











Table 4-2. Cumulative number of each taxa found in each treatment in the three sampling periods of the pitfall traps.


December
EMLC

1 1 -
19 9 5 9
-1 1

8 7 7 17




1 1 -


41 21 23 31




35 26 6 42




2 2 -


1 1 -
2 32 2
-11 2
1 25 2
3 11 1

2 -


January
EM L C
11 2 6 5
4 -6 2


50 85 132 65

1 1 -
2 1
44 9 2 2


18 21 47 29






4 2 22




2 2 2 4


February
EMLC
1 1 1




1 1 -

10 24 13 39
1 1 11 2
1 1 3
3 5


9 7 14 15

-1 2


Chrysomelidae
(Alticinae spp.)
Aphididae
Apoidea
Bibionidae
Cecidomyiidae
Chalcidodea
Chironomidae
Chrysomelidae
Cicadellidae

Coccinelidae
Collembola
Cucujidae
Drosophilidea
SEliteridae
Formicidae
Ichnueumonidae
Lepidoptera
Miridae
Muscidae
Mutillidae
Nematod e
Phloeothripidae
Phoridae
Sca ria rid ae
Araneida
Staphylinidae
Tettigoniidae
Thripidae


Aphididae
Cecidomyiidae
Chalcidiodea
Cicadelidae
Collembola
Gryllidae
Cucjidae
Drosophilidae
Formicidae
Lygaeidae
(Pachybrachius
spp.)
Miridae
Muscidae
Nitulidae
Phoridae
Scariaridae
Scollidae
Araneida
Staphylinidae
Tettigoniidae
Thripidae


Aphid idae
Ichneumonoidea
(braconidae)
Cecidomyiidae
Chalcidoidae
Chrysomellidae
Collembola
Formicidae
Lygaeidae
Lygaeidae(immature)

Muscidae
Scariaridae
Araneida
Staphalenidae
Thripidae
Vespidae


E = early treatment, M = middle treatment, L = late; C = control.











Table 4-3. Cumulative numbers of each taxa in the three visual sampling periods
December January February
E M L C E M L C E M LC
Tettigoniidae 3 1 3 3 --- 4 7 2 4
Apoidea 6 9 5 3 1 3 2
Syrphidae 3 3 1 4 16 13 6 8 2 1 -1
Araneida 1 1 2 1 8 4 2 -
Lepidoptera 1 1 1 1 -- -- 1 -
Muscidae 1 2 2 2 --- 1 1 2


Chrysomelidae
Coccinelidae
Lygaeidae
(Tristicolor spp)
(pachybrachius
spp)
Sciaridae


1 --- 1
1 -


1 2 -


8 2 6 12


1 --- 1
52 28 39 14


1


ciC adellidae -
E = early treatment, M = middle treatment, L = late treatment and C = control.


Table 4-4. Cumulative numbers of each taxa in the three foliar sampling periods
December January February
E M L C E M L C E M L C
S.sexmaculatus -1 2 2 6 3 10 10 4 1 3 2
Aphididae 43 64 28 40 1 4 4 1 1 -
Aleyrodidae 29 22 22 2 2 2 2 2 -3
Thripidae 7 2 1 1 14 4 14 14 3 3


Chalcidoidae 1 -
Lepidoptera 1 -
Syrphidae
(eggs) -
Lygaeidae
(Geocoridae


6 6 2 9


9 8 9 9 4 5 10 15


spp) ---- 3 -
E= early treatment, M=middle treatment, L=1ate treatment and C=control.























180

0*0




0 5 10 15 20 25
Nurnber of Squares

Figure 4-1. Cumulative percent of families found on yellow sticky trap 1-cm squares.


TT


Early Treatment
a Untreated


e
b~"a
C~Y`
0'


d

~
8


"~p*
o"


9


~-ae
a
~S~:~


Taxon


Figure 4-2.The most abundant families found on early-season yellow sticky traps between the
treated and untreated plots. indicates significant differences (P < 0.05) between
treated and untreated.


-5* L*














9 i m Early Treatment
S8 m Untreated






Taxo

Fiure 4-.Tems bnatfmle on nteeal-esnptaltasi h raen
unrae plt.N in4at( .5 ifeecswr on mn ramns

Tal -.Ma auso iest nie nposi al-esnylo tcytas
Tramn hno ihesEens










Tablre 4-6. Men ale m oft a divrsty indies in ploints i early-season pitfall traps i h rae n



Treatment Shannon Richness Evenness
Meant SE
Early 1.71~0.150 8.00.40 0.81~0.06
Untreated 1.7130.06 73.910.6 0.81~0.04
No significant (P < 0.05) differences with treatment.



































ic


-L


m Early
a Middle
o Untreated


20-



15- ~Li\


~a~'
c~
Q bPO


Taxon


Figure 4-4. The most abundant families found in the mid-season yellow sticky traps among the
early, middle and untreated plots. No significant (P < 0.05) differences among
treatments.


S14


m Early
a Middle
o Untreated


Formicidae


Collembola Lygaeidae Arachnidae
Taxon


Figure 4-5. The most abundant taxa found in the mid-season pitfall traps between the early,
middle, and untreated plots. indicates significantly (P < 0.05) higher numbers of
Formicidae in the early-release treated plots than the untreated plots.










Table 4-7. Mean values of diversity indices in plots in mid-season yellow sticky traps.
Treatment Shannon Richness Evenness
Meant SE
Early 2.20.10 15.511.3 0.810.02
Middle 2.20.03 14.810.9 0.810.02
Untreated 2.110.05 13.30.5 0.810.02
No significant (P < 0.05) differences with treatment.

Table 4-8. Mean values of diversity indices in plots in mid-season pitfall traps.
Treatment Shannon Richness Evenness
Meant SE
Early 1.510.20 8.011.2 0.710.05
Middle 1.30.12 7.511.3 0.710.08
Untreated 1.30.09 6.610.5 0.710.04
No significant (P < 0.05) differences with treatment.


Early
a Middle
a Late
o Control


o,
p"e~
~r
o~:"


~


Taxon


Figure 4-6. The most abundant families found in the late-season yellow sticky traps in early,
middle, late, and control plots. No significant (P < 0.05) difference among treatments.











m Early
a Middle
a Late
o Control


Collembola Sciaridae Lygaeidae Arachnidae
Taxon


Figure 4-7. The most abundant families found in the late-season pitfall traps in the early, middle,
late, and control plots. No significant (P < 0.05) difference among treatments.


Table 4-9. Mean value of diversity indices in plots in late-season yellow sticky traps.
Treatment Shannon Richness Evenness
Meant SE
Early 1.9510.10 0.7510.03 12.810.69
Middle 2.1610.12 0.8510.06 12.810.48
Late 1.6810.20 0.6910.10 11.30.25
Control 1.830.73 0.7710.91 11.00.10
No significant (P < 0.05) differences with treatment.


Table 4-10. Mean value
Treatment Shannon


of diversity indices in plots in late-season pitfall traps.
Richness Evenness
Meant SE
0.6+0.03 9.3+0.85
0.610.01 8.810.30
0.7+0.90 9.0+1.10
0.610.10 8.510.50


Early
Middle
Late
Control


1.30.10
1.30.02
1.510.90
1.410.13


No significant (P < 0.05) differences with treatment.


ii









CHAPTER 5
HYPERSPECTRAL IMAGERY DETECTION FOR TWOSPOTTED SPIDER MITE
DAMAGE INT STRAWBERRIES

Twospotted spider mite (TSSM) Tetranychusrtrt~t~t~r~rtrt urticae Koch is one of the most

economically important pests in strawberries (Fragaria spp.) High infestations of TSSM have

shown to cause leaf chlorosis, cessation or stimulation of plant growth, and reduction in yield

(Oatman et al. 1985, Cloyd et al. 2006, Wynam et al. 1979, Walsh et al 2002, Stonneveld et al.

1996, Huffakker et al. 1969, Sanches et al.1979). As TSSM feed on the underside of the leaf,

they pierce the chloroplast containing palisade and spongy parenchyma cells in the mesophyll

layer at a rate of 18-22 cells/minute (Jeppson et al. 1975, Sanches et al 1979). Chlorotic

symptoms appear when TSSM consume the chloroplasts, which contain chlorophyll, an essential

pigment that absorbs solar radiation for photosynthesis (Smith and Smith 2003, Kiekliewicz

1985). A decrease in radiant energy use (REU) due to the consumption of the chloroplasts

eventually leads to reduction in vegetative growth and yield (Reddall et al. 2004, Sances et al.

1981, Kielkiewicz 1985).

The chloroplasts are organelles within the mesophyll cells that contain pigments and are

the primary catalyst for the light reaction of photosynthesis (Meyer et al. 1973, Smith and Smith,

2003). Each family of pigments (carotenoids, phycobilins, and chlorophylls) absorb strongly in

specific wavelengths (Clm) of the radiant light spectrum. Chlorophyll a and b are the

predominant pigments located in the chloroplasts. They produce the green reflectance of healthy

vegetation and absorb blue (0.43 Clm and 0.45 Clm) and red (0.66 Clm and 0.65 Clm) wavelengths

(Meyer et al. 1973). The light absorbed and stored by the pigments in the chloroplasts is the

principal source of energy for photosynthesis. Twospotted spider mite penetration and salivary

inj section into these cells dissolves and digests the structures and inhibits the function of the

chloroplasts (Kielkiewicz 1985). Cellular injury disrupts the ability for these pigments to absorb









the specific wavelengths in the radiant energy spectrum, making the leaves appear discolored and

chlorotic (Meyer 1973, Jensen 2005). The resulting spectral variation in the visual wavelengths

is one of the most consistent indicators of vegetation health. Leaf stress is evident in variations of

the 0.55-0.64 Clm and ~0.7 Clm wavelengths (Jensen 2005).

Twospotted spider mite damage also affects the ability of a plant to absorb and reflect

near infrared (NIR) wavebands. Plants have evolved to reflect highly in the infrared wavebands

(0.7-1.1 Clm) to protect the leaf tissue from absorbing too much radiant heat that may lead to the

denaturing of essential proteins. The structure of the mesophyll layer regulates the reflectance of

NIR energy by the internal scattering at the cell wall-air interface (Jensen 2005). Variations in

the reflectance in the region between the red and NIR, known as the "red edge" (~ 0.7 Clm),

indicates plant stress that is often due to dehydration and cellular damage (Jensen 2005, Lillisand

at al. 2003).

The correlation between TSSM damage and reduced photosynthetic function of strawberry

plants has been documented extensively (Reddall et al. 2004, latrou et al. 2004, Kielkiewicz

1985, Sanches et al. 1979, Sanches et al. 1981). However, the effect of physiological inhibitions

on spectral response of strawberry leaves has not been investigated. Studies by Fitzgerald (2004)

and Landeros et al. (2004) have demonstrated that it is possible to detect spectral changes

regarding the presence/absence of pest damage in agricultural fields in larger Hield crops like

cotton.

Our goal is to identify specific regions of the reflectance spectrum that are affected by

TSSM on strawberry leaves and develop a relationship between quantifiable levels of TSSM

infestation and spectral foliar response. This study will provide a foundation for the development

of models to better understand TSSM interactions with strawberry plants. The information can be










integrated with other technologies and tactics into a set of tools known as geographic information

technology (GIT), and used to identify and monitor spectral data from a field that can be

analyzed to create maps of vegetative condition in relation to pest damage (Brewster 1999,

Dayang and Kamaruzaman 1999). Geographic information technology is associated with site-

specific Precision Insect Pest Management (PIPM) programs. Early identification of TSSM

distribution before damage is visible in the field is the initial step to develop a management

program that will have the potential to reduce economic and ecological costs and increase

production in strawberries (Dayang and Kamaruzaman 1999).

Materials and Methods

Field Plots

Our experimental plots were located at the University of Florida Plant Science Research

and Education Unit, near Citra, FL (82. 170W, 29.410N). There were 16 plots of varying levels of

TSSM infestation. Each plot was 7.3 m2 With 11 m buffer between each plot. Within each plot

there were 6 rows of strawberries. Each row had a double row of transplants 0.3 5 m apart within

row and 0.35m between row. Strawberries were planted the first week of October, on raised beds

over black plastic mulch and were fertilized, weeded and sprayed with fungicides using standard

commercial practices (Brown 2003).

Sampling

Twenty mature leaflets of TSSM-infested strawberry plants were taken randomly one

time per week from each of the 16 plots. We collected samples for four weeks between

December 2006 and January 2007. Leaflets were taken back to the Small Fruit and Vegetable

IPM Laboratory at the University of Florida, Gainesville, FL and analyzed under a dissecting

microscope to determine the number of TS SM per leaflet. Each individual leaflet was then put

into a Zipper Seal Storage Bag C (American Value, Dolgencorp, Inc, Goodlettsville, TN) and









labeled with the approximate number of mites found on the leaflet. The leaflets were then

scanned with a Fieldspec@ 3 spectroradiometer (Analytic Spectral Devices, Inc., Boulder, CO) at

the Soil Sciences Laboratory at the University of Florida. The samples were scanned within two

hours after collection to reduce dehydration and foliar damage.

Spectral Scanning

During the scanning process, the spectrometer was re-calibrated with a white reference

every 10 minutes to ensure an accurate spectral reading. Two separate areas of 3.2 cm2 WeTO

scanned on the adaxial (top) side of each leaflet with a spectral lens that was 2 cm diameter.

Each of the selected areas was rotated 900 and rescanned to increase spectral accuracy. The

spectral signature of each wave band between 360 nm and 2480 nm from each reading was

downloaded to a CSV (Comma Separated Values) file. The spectral response was "re-sampled",

and every 10 nm were averaged to condense the 2000 wavebands into 200 wavebands to

facilitate statistical analysis. The data were then derivative transformed, using first derivative

transformation with second order smoothing to finalize the data (Statsoft, Inc. 2005). This

procedure facilitated the detection of variations in the slope of the spectral curves between

wavelengths. The data were exported into an Excel spreadsheet displaying the reflectance value

of each sample in each of the 200 wavebands.

Data Analysis

Raw data were subj ected to a linear regression analysis to assess the correlation and

prediction accuracy of mite numbers with respect to reflectance values. The results were cross-

validated by separating the data into groups of test data and validation data. The test data were

subjected to the regression analysis and then the validation data were applied to the test model to

assess the strength of the model (SAS Institute, Inc. 2002). The data were then subj ected to a

Principal Component Analysis (PCA) to condense the data using SPSS software (SPSS Inc.










2004). Due to high variability in the data revealed by the PCA, we chose to focus on regions of

the spectrum that are directly related with TSSM damage rather than utilizing the entire radiant

spectrum.

Determining Categories of TSSM Infestation. To better describe the correlation between

mite density and leaflet reflectance in a practical representation for growers, we divided the

leaves into three categories: no mites (0 mites); low/moderate infestation (10-60 mites/leaflet);

and high infestation (2 70 mites/leaflet). A Linear Discriminate Analysis (LDA) of the first 5

principal components was performed. Discriminate Analysis is a multivariate statistical

technique that is commonly used to build predictive models of group discrimination based on

observed predictor variables and classify each observation into one of these groups:


dik= a+ bncYII + b21c~ i2... bimrXin +ei
dik is the value of the kth discriminate function for the ith case
a constant
bik is the value of the ith coefficient of the kth function
xil is the value of the ith case of the jth predictor
el ls an error term


The obj ectives of LDA are to investigate differences between groups and create categories

maximizing the variance between groups and minimizing the variance within groups (McCune

and Grace 2004). Data were then cross-validated using the PROC DISCIM CROSSVALIDATE

function in the SAS statistical program for the three categories to determine if the variation of the

spectral differences will significantly discriminate among the levels of mite infestation (SAS

Institute, 2002).

The data were first subj ected to a one-way ANOVA (SPSS Inc. 2004) to reveal regions of

the spectr-um with the greatest statistical differences (P > 0.0000001). Discriminate Analysis was

then conducted on the average of near infrared (NIR) wavelengths (700nm-1000nm), and in the









green wavelengths (560nm-5 80nm). Finally, to test the application of the spectral analysis to

commercially available satellite systems, the LDA was performed on NIR and green

wavelengths at the spectral resolution of SPOT 5 (SPOT Image Corporation, Chantilly, VA) and

Quickbird (GeoVAR, Katy, Texas) satellites.

The results of the LDA were evaluated in an error matrix to assess the level of accuracy

(Jensen 2005). We used four measurements of accuracy to determine the reliability and

appropriateness our classification: 1) total number of samples that were correctly categorized

divided by the total number of remaining samples were calculated to test how accurately the data

were classified (producer' s accuracy) 2) the total number of samples from a category that were

classified in the appropriate category was calculated as a measure of reliability (user' s accuracy)

3) the overall accuracy was determined by dividing the total number of correctly categorized

samples by the total number of samples and 4) kappa analysis (K) was calculated, which is a

measure of agreement or accuracy between predicted classification data and reference data. A

Kappa value of 80% or higher represents high level of accuracy, kappa values between 40% and

80% represent moderate accuracy and a value of less than 40% represents poor accuracy (Jensen

2005).

GIS Integration

To obtain geographic information, we used a Trimble@ XRS GPS unit (Sunnyvale, CA)

with Trimble TerraSync@ software (Sunnyvale, CA). We recorded the subplots and Hield border

as area features by averaging the vertices of each corner of the plots using real time differential

corrections to improve position accuracy. Nine sample points from each plot were recorded as

point features. The features collected with the GPS unit were transferred to Pathfinder Office

3.10 software (Trimble, Sunnyvale, CA) and different ally corrected in the Utilitie s/Differenti al

Correction window using the Differential Correction Wizard to subj ect the data further










geographic correction and increase accuracy. The Palatka base station (81.640W, 29.650N) was

chosen as the base provider to use for reference position. The map was converted into an ESRI

shapefile through the utilities/export dialog box >> new set up >> ESRI shapefile. The GPS map

was then imported into ArcGIS 9. 1 (ESRI Redwoods, CA). The map was re-proj ected into

NAD_1927_UTMzzon 17 through ArcToolbox using the data management

toolb ox>>proj ecti on tool.

To obtain spectral information, we collected leaflets taken from the sample points

previously marked with the GPS map. We transported the leaflets back to the laboratory in

Zipper Seal Storage Bags and counted the number of TSSM on each leaflet using a dissecting

microscope. Using a handheld Fieldspec~~spectrometer (Analytical Spectral Devices, Boulder,

CO) we recorded the reflectance values of each leaflet.

The mite number and reflectance values of each sample leaflet were stored as Microsoft

Excel files. The spread sheet was imported into an Access file and then imported into ArcMap

(ESRI, Redwoods, CA) as a layer using the 'add layer' dialogue box. These data contained field

sample point position, mite number and reflectance value. The attribute table of the GPS sample

points and the reflectance samples were joined through the layer properties dialogue box. The

plots were unioned through the analysis>> overlay>> union function in ArcToolbox. The data

were then converted to raster through the conversion tools>> to raster>> "feature to raster"

function using ArcToolbox.

In the spatial analyst dropdown box in ArcMap, we used interpolate to raster>> inverse

distance weighted (IDW) to create an interpolated image of the mite numbers as they are

distributed on a field level. We then used the raster calculator in the spatial analyst dropdown to

build the expression (Setnull([union]=1, [union]) to set a mask, excluding all the data except









those in the plots. This defined the map extent to only those areas of interest within the plot.

Finally, we used the raster multiplication function in raster calculator to build the expression

([setnull_plots]+1)*rast5, which overlaid the plot area with the interpolated raster layer. The

result was an image displaying the mite distribution only in the plots (Figure 5-1).

Results

Spectral Analysis

The spectral signature of the samples displayed highest variability at the "red edge" (area

between the red and NIR bands) and the green visible region (520nm-580nm). There was a close

relationship between mite infestation and NIR reflectance (Figure 5-2). The TSSM numbers

correlated with reflectance values showed a strong relationship between the variables. The

validation data of mite numbers predicted by wavelength had an R2 = 0.7469 between the

expected and observed responses (Figure 5-3). The principal component analysis (PCA)

condensed the data into 5 principal factors encompassing 89.8% of the variation in the data

(Figure 5-4).

Accuracy of Categories of Mite Infestation

The NIR bands (700nm-1000nm) resulted in 90% of the total samples classified correctly

with a 90% reliability score for the "Hi" category. The "Lo/Mod"category had 94% classified

correctly with 92.5% reliability. The "No" category had 87.5% classified correctly with 87.5%

reliability. The overall accuracy was 92.5% and K = 84.9% The green bands (560nm-580nm)

resulted in 95% correct classification in the "Hi" category with 79.1% reliability. The "Lo/Mod"

category had 90.39% correct classification with 98% reliability. The "No" category had 100%

correct classification with 100% reliability. The overall accuracy was 92.5% and K = 92.4%

(Table 5-1).










The green and NIR bands in commercial satellite platforms, SPOT 5, which has a 500

nm-590 nm green band width and 780 nm 890 nm NIR band width and Quickbird which has a

green band width of 520 nm 600 nm and NIR band width of 760 nm 900 nm were compared.

The green band produced an overall accuracy of 52% and 56%, respectively. The NIR for both

platforms had 96% accuracy (Table 5-2).

The results of the accuracy matrix indicate that the three TSSM classifications selected in this

study are highly accurate in discriminating spectral response in strawberries. The green bands

preformed the best at high resolution and the NIR was highly reliable with lower resolution

sensors.

Spectral Map

The j oined raster and GPS layer created a visual representation of the spatial distribution

of TSSM damage in the field plots. The model indicates that spectral pest detection is possible at

a field level. The data suggest that mite distribution could be identified early through the

reflectance correlation and precise preventative management could be preformed. Figure 5-4

shows the predicted distribution of TSSM within our experimental field. In a GIS, precise areas

can be identified by pointing to a specific area of the map and the geographic coordinates of that

area will be displayed.

Discussion

Analysis

There is a strong correlation between specific levels of mite infestation on strawberry

leaves and alteration in leaf reflectance. However, the PCA analysis revealed that strawberry

leaves reflect a high variation along the radiant spectrum, suggesting that the breadth of variance

in the reflectance is a result of a complex physiological process within the leaf, not all of which

is related to TSSM. The obj ective of the PCA is to condense the data into the smallest number of









components (axes) to represent the strongest covariance among the variables, not necessarily

varying with respect to the experimental variable (McCune and Grace 2002).

Due to the spectrum wide variability we chose to apply the LDA to the green and NIR

regions, which indicated that the highest level of significance and corresponds spatially within

the leaf to TSSM feeding sites. Both regions performed well under laboratory conditions.

Spectral results indicate that a high spectral resolution sensor (~0.3Clm band widths) is highly

effective in discriminating between levels of TS SM infestation based on the variation in both the

green and NIR regions. Fitzgerald (2004) noted that the strawberry spider mite (Tetranychusrt~t~r~rtrt~t~

turkestani Ugarov and Nikolsk) damage in cotton is observable in the 850 nm wavelength, and

subsequent work by Fitzgerald (2005) demonstrated that when using a commercial satellite

platform, spectral variations in the green bands were difficult to detect in the field without

subjecting the data to spectral unmixing. We found that at the lower spatial resolutions of

commercial satellite platforms, the NIR is a good predictor of TSSM damage in strawberries, but

finer resolution sensors are able to detect TSSM more acutely with the green bands.

GIT Application

The ultimate goal of this study is to detect TSSM numbers in a strawberry field before

physiological damage is visible to the human eye. This may allow the application of a

preventative strategy to reduce TSSM population before it becomes uncontrollable for growers.

Large scale technology in conjunction with infrared sensory systems is already in popular use to

detect presence/absence of agricultural pests. In addition to detecting TSSM, our goal is to apply

this technology to monitor the level of TS SM infestation relative to radiant reflective response to

early cellular damage of the strawberry leaves. The use of spectral maps of TSSM distribution in

the field could aid in precision pest management programs.









Future Directions

There are several options of integrating this technology. A practical option is for a

growers association to buy a Hield spectrometer such as a Hield-based Fieldspec 9 3 JR

spectroradiometer (350nm-2500nm) (Analytical Spectral Devices Inc. Boulder, Co). The

instrument can be mounted on a tractor or any field equipment and hooked directly to a GPS.

The foreoptics on the spectrometer has a conical Hield of view which is 250 so the image is

enlarged with respect to the height of the sensor. The high sensitivity of the sensor allows for up

to 20 meters of height above the target with no detectable effect of signal to noise ratio. The

spectral Hiles are stored as binary data and are directly downloadable to the ENVI imagery

processing system (ITT Visual Information Solutions, Boulder,CO) which can operate on a

desktop computer. The binary files store the data as digital numbers in ASD (Microsoft

Advanced Streaming Format description file). In ENVI these files can be exported directly into a

"spectral library" and resampled to the spectral resolution of the image. A raster image is built

from each of the spectra specified by a user. The fieldspec software also includes a post

processor call a Viewspec Pro that can view and convert the binary files into other formats.

Once the image is built in the program it can be analyzed in ENVI or in ArcGIS. In ENVI,

the image can be analyzed through the "basic tools" menu. By choosing regions of interest, the

user can create training samples to conduct a supervised classification and use the maximum

likelihood classification to classify the entire area (field) and then be able to identify regions of

the field at different levels of mite damaged based on the reflectance values defined in this study.

The image can also be analyzed in ArcGIS by importing the image constructed in ENVI with the

bands of interest. The digital number will have been calculated in ENVI and imported into

ArcGIS. In the attribute table in ArcGIS, the user could then use the "query builder" function to

locate each pixel value of known mite infestation. The software will then be able to identify the









pixels of interests in each mite level and enable the user to see the distribution of mite levels in

the field based on the digital number. This technique with the Hieldspec@ is Hield based and the

instruments can be easily mounted on Hield equipment. Similar technology has been used

extensively in soil and nutrient assessment in agricultural Hields. It provides high spectral

resolution images that can be georeferenced when used in conjunction with a GPS and has been

shown to have the spectral capabilities to discriminate between levels of TSSM.
































































D 5 10 20 30 40


Qmighhc Bdm~~lm.FlrU.D 2rM~_1 rI
pRm.- e-..ums.rlnr.. .. n..-l.
.5mmFlmb
hamb 10 8M


11mllC~I~1IC~.~ICrlIll~:III11111[111~:l


Legend

lYite Density



in


Figure 5-1. Reflectance map of TSSM distribution of the experimental strawberry field, Citra,
FL.












Strawberry Leaf Reflectan ce Sig natu res


1.2 100 mites
1 -I 25 mites
S0.8 -4 ie
0 mites
a 0.6
ca <10 mites
t; 0.4







Wav ele ngth


Figure 5-2. Variation of the spectral signatures of strawberry leaves at different levels of TSSM
infestation.





Validation


y= 0.8368x+ 13.014
R2 =0.7469


**

**
* ** *
*
***.


-50 0000 0 0000 500000 100 0000 1500000 200 0000
predicted



Figure 5-3. Regression of predicted versus observed raw TSSM numbers/leaflet.






































14711 1122233394446566667777888999 1 1IIII 1 111111111111 I 1 1 11 11 12222
036925814703892581470369258 1 700001 11222333344456586667778889999000 1
0369258 14703692581470369258 1470389258 1
Component Number

Figure. 5-4.Scree Plot of PCA. Each point on the graph indicates the cumulative percent of the
data for which each factor accounts. The first five factors contain 89.9% of the data.


Table 5-1. Classification summary of LDA cross-validation of PCA. Highlighted percentages on
the diagonal indicate the percent of observations classified correctly.
Epcted
No Lol~lod Hi Total
No
Observations classified 4 4 0 8
Percent classified 50.00% 50.00% 0% 100%
ILolMod
Observations classified 0 50 2 52
O Percent classified 96.15% 3.85% 100%
Hi
Observations classified 0 2 18 20
Percent classified 0% 10.00% 90% 100%
Total 4 58 20 80
Total percent of classified 5% 70% 25% 100%


Scree Plot


I
I m
r
c
c
LU










Table 5-2. Accuracy scores for the LDA
Green Bands (560nm-580nm)
Producers Users Overall K
Accu racy Accu racy Accuracy: coefficient
No mites 100% 100% 92.50% 92.40%
LowlModerate 90.39% 98%
High 95% 79.19%
NIR (700-1000)
No mites 87.50% 87.50% 92.50% 85%
LowlModerate 94.23% 92.50%
High 90% 90%

Table 5-3. Accuracy scores for LDA of Quickbird and SPOTS
Quickbird (760nm-900nm)/Spot5 NIR (780nm-890nm)
Producers Users Overall K
Accu racy Accu racy Accu racy: Coefficient
No mites 100% 89% 93% 86%
LowlModerate 90.38% 90.38%
High 95% 95%
Quickbird Green band( 520nm-600nm)
No mites 87% 22% 56% 31.00%
LowlModerate 61% 89%
High 30% 50%
SPOTS Green (500nm-590nm)
No mites 63% 16% 53% 25%
LowlModerate 60% 89%
High 30% 43%









CHAPTER 6
CONCLUSIONS

The principal management concern of strawberry growers in north Florida is the increasing

incidence of twospotted spider mite (TSSM) and its effect on berry production. Managing TSSM

with miticides is particularly difficult since TSSM has a short lifecycle and resistance can occur

within a year of exposure to chemical treatments. However, many growers are skeptical about

the efficacy of biological control. Growers have indicated that their primary concerns when

considering pest management plans are economic viability and competitiveness in the industry.

According to Shawn Crocker, Executive Director of the Florida Strawberry Growers

Association, fruit and vegetable production is becoming more dynamic and highly mechanized.

Growers are interested in managing their fields to maximize their production, while minimizing

their inputs. The results obtained in our experiments regarding biological control, ecological

studies on the sustainability of this method, and geospatial technology have proven that TSSM

management can be both economically and ecologically efficient.

Our study shows that with minimal inputs from one early season release of the predatory

mite, N. californicus, effective season-long management of TSSM can be achieved. The results

of our first season (2005-2006) indicate that with low initial TSSM densities, N. californicus is

able to provide consistent suppression of TSSM throughout the season. In treated plots, TSSM

never exceeded five motiles per trifoliate. However, there was a higher initial TSSM population

in the 2006-2007 season resulting in a higher ratio of predator to prey than the first season,

reducing the level of effectiveness. The higher season-long average populations of TSSM in the

2006-2007 season indicate that initial prey populations and appropriate prey: predator ratio are

critical factors in establishing control of TSSM. Greco et al. (2005) demonstrated that effective

control seems to be limited by high initial TSSM density. An ideal predator: prey ratio is









considered to be between 1:5 and 1:10 (Greco et al. 2005). Occasional freezes also seem to

reduce TSSM populations. Hart et al. (2001) observed that cool temperatures suppress TSSM

populations while not adversely affecting populations of predatory thripidae, staphiylinidae,

lygaediae, and chalcidioidae. We observed this tendency in our experiments during the 2005-

2006 season.

In the event of high initial TSSM infestation, as we had in the second field season (2006-

2007), N. californicus must be released at extremely high rates to reach the appropriate predator:

prey ratio to achieve adequate control of TSSM. Sabelis and Janssen (1994) confirmed that at

low numbers, N. californicus is not able to reproduce quickly enough to decimate a high

population, as would a more voracious predator such as P. persimilis. When TSSM populations

are high, the number of N. californium needed may be cost prohibitive for many growers. An

alternative, as discussed by Rhodes et al. (2006), is to use an initial reduced-risk miticide, or a

biopesticide to reduce TSSM populations prior to the release of N. californicus.

Neoseiulus californicus do not affect the abundance of beneficial insects or disrupt the

arthropod assemblage in the field. Plots in which N. californicus were released tended to have a

similar arthropod richness and evenness compared with the control plots. The natural diversity in

the strawberry system combined with the generalist feeding habits of N. californicus may

contribute to the ecological stability of the ecosystem (Croft et al. 1998, Klein et al. 2006). The

results indicate that a grower need not worry about the effects of releasing N. californicus on

non-target organisms when this predator is introduced into the field.

The importance of maintaining a healthy ecosystem has led to the development of

precision pest management. Many growers already utilize GPS to manage nutrients, soil, and

moisture (Shawn Crocker, personal communication). The development and application of









geographically referenced imagery analysis regarding TSSM damage is a natural addition to

these strategies. Minimal additions to software capabilities on conventional field equipment

could enable growers to precisely locate spot areas in the field that are developing populations of

TSSM before visible by the human eye. Growers can then respond by treating spot infestations

appropriately, conserving both economic and natural resources.

The concern about resource management and conservation has encouraged the

development of strategies including biological control, precision agriculture, and precision pest

management. The studies presented provide evidence that it is possible to reduce both economic

and chemical inputs in strawberry fields, maintaining a healthy ecosystem and responding to

both consumer and grower concerns regarding the health and marketability of the most valuable

small fruit crop in Florida.





APPENDIX A
STRAWBERRY PEST MANAGEMENT SURVEY

Name :
Size of cultivated strawberry area:


1) What specific pest problems to you encounter (Insect, Weed, Diseases)


Pest


Control Method


2) Are you concerned about twospotted spider mites (TSSM)?


Yes


3) Have you experience yield loss due to TSSM damage, if so what percentage/economic value
of your production was lost?



4) How do you monitor for TSSM?





5) What is your current TS SM management program?


6) Would you be willing to use predators (biolo 'cal control ?
If not why?


No


yes


7) What factors do you consider when deciding on a management program?
(please circle all that apply)
a) economics
b) environmental concerns
c) customer concerns
d) time/labor requirements


This pest management survey was conducted with the help of Florida Strawberry Growers
Association (N = 12). The results are as follows:










1) What pest problems do you encounter?

The commonest pest problems:
30% fungus
50% fungus and birds
20% TSSM

2) How do you monitor for Twospotted spider mite (TSSM)?

Frequency of scouting varies between once a day and once a week and the action threshold
varies:
20% 1 TSSM per leaftlet,
20% 5 TSSM per field of view (FOV) of hand lens
20% 10 TSSM per FOV of hand lens
10% wait until leaves begin to yellow
20% spay regularly so do not have TSSM
10% no formal scouting

3) What is your current management program

90% use chemicals, only the organic growers rely on natural enemies (they do not have a
problem with TSSM)

4) Would you be willing to use biological control?

100% said they would be willing to use biocontrol but the concerns are cost and
compatibility with fungicides and other chemicals used in the field.

5) What factors do you consider when deciding on a management program?

100% are primarily concerned with economics.









APPENDIX B
FUTURE WORK

Objective 1: To determine the appropriate time for inoculative releases of N.

californicus. Our work provides compelling evidence that releasing N. californicus early in the

season can provide stable season-long control of TSSM. However, there are still several

questions to be answered: 1) Greco (2004, 2005) determined that for control of TSSM, N.

californicus needed to be released at a ratio of 1:5 to 1:10 (predator: prey). Further work on

determining the optimal predator: prey ratio in the north Florida strawberry system would be

helpful to verify this assertion; 2) investigating varying levels of TSSM densities on the efficacy

of N. californicus in the field should be conducted. In our greenhouse trials, N. californicus

demonstrated a functional response with prey density. Hassell et al. (1976) support this finding in

laboratory studies. However, this response has not been validated in the field. Releasing N.

californicus at a constant predator: prey ratio in areas of high and low TSSM densities to assess

efficacy of N. californicus would contribute to our understanding of the predator: prey

interaction; 3) future exploration is needed to understand the effect that the timing of TSSM

infestation and plant phenology has on berry yield.

Objective 2: To evaluate the effect of predatory releases on naturally occurring

arthropods. The findings in this study indicate that N. califomicus does not have a significant

impact on the arthropod assemblage in the strawberry system. However, the studies conducted

captured the general distribution of taxa in the system. We found that plant phenology and

ambient weather had an impact on arthropod assemblage in the field, which may affect the

impact of N. califomicus in the system. Repeated trials across seasons in different climactic

conditions should be conducted. In addition, investigating the effect of N. califomicus releases









on taxonomic composition within arthropod families would contribute to a deeper understanding

of the system.

Objective 3. To establish a pest monitoring program using geographic information

technology (GIT). Our laboratory studies have shown that there is a strong correlation between

specific levels of mite infestation on strawberry leaves and alteration in leaf reflectance in the

green and NIR wavebands. However, the application of the laboratory analysis needs to be

verified in the Hield, and an efficient data collection and analysis procedure needs to be

established. Testing the laboratory results in the field under ambient conditions is important to

make this technique practical. To test the results in the Hield, a Hield spectrometer should be

acquired and connected to a GPS. The unit should be mounted onto a tractor, or other Hield

equipment, to collect data from the green and NIR wavebands and input into an imagery analysis

system as outlined in Chapter 5. Finally, the process must be validated by applying it to a

number of Hields and conditions to ensure reliability.










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BIOGRAPHICAL SKETCH

Aimee graduated with her BA in sociology with a concentration in environmental

sociology from Indiana University in 1999. Before entering graduate school, she worked on and

managed several experimental organic farms in both the United States and South Africa. She

also taught marine ecology with the Chesapeake Bay Foundation in Maryland and Save the

Sound in Connecticut. She earned a teaching degree in Montessori elementary education in 2003.

During her master' s work she held a position as a research assistant in the Small Fruit and

Vegetable IPM lab in the Entomology Department at the University of Florida. Her study

focused on biological control of twospotted spider mite in strawberry, an exploration of

arthropod diversity, and geospatial imagery systems as a component of a precision pest

management program.





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1 TIMED RELEASES WITH Neoseiulus californicus AS A BIOLOGICAL CONTROL AGENT FOR Tetranychus urticae Koch AND ITS ECOLOGICAL IM PACT ON NORTH FLORIDA STRAWBERRY FIELDS By AIMEE BETH FRAULO A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007

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2 2007 Aimee Beth Fraulo

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3 To my parents who gave me the gift of curiosity and a love of learning

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4 ACKNOWLEDGMENTS I would like to thank everyone who made this thesis possible. Most importantly I would like to thank my supervisory committee, Dr. Oscar E Liburd, Dr. Robe rt McSorley, and Mr. Stanley Latimer. I am also eternally grateful to Drs. Christian Russell and Matt Cohan for their help on the imagery analysis. I would also like to thank the staff at the Small Fruit and Vegetable IPM Laboratory for their moral supp ort, and the staff at the Res earch and Education Center for their help with the strawberry maintenance. Fina lly, I would like to tha nk my family and friends for providing unending support thro ugh this whole process.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES................................................................................................................ .........8 ABSTRACT....................................................................................................................... ............10 CHAPTER 1 INTRODUCTION..................................................................................................................12 2 LITERATURE REVIEW.......................................................................................................16 Twospotted spider mite......................................................................................................... ..16 Control Methods................................................................................................................ .....18 Natural Enemies................................................................................................................ ......18 Phytoseiulus persimilis ....................................................................................................19 Neoseiulus californicus ...................................................................................................20 Effect of Timing of Predatory Releases on TSSM Populations.............................................21 Geographic Information Syst ems in Pest Monitoring............................................................23 3 BIOLOGICAL CONTROL OF TWOSPOTTED SPIDER MITE, Tetranychus urticae Koch WITH PREDATORY MITE, Neoseiulus californicus IN GREENHOUSE AND FIELD EXPERIMENTS........................................................................................................27 Materials and Methods.......................................................................................................... .28 Colony......................................................................................................................... ....28 Greenhouse experiment...................................................................................................29 Field Experiment.............................................................................................................30 Sampling...................................................................................................................32 Statistical Analysis...................................................................................................32 Results........................................................................................................................ .............33 Laboratory Experiments..................................................................................................33 2005-2006 Field Season..................................................................................................33 2006-2007 Field Season..................................................................................................34 Discussion..................................................................................................................... ..........35 Greenhouse Experiment..................................................................................................35 Field Experiments............................................................................................................36 The 2005-2006 Season.............................................................................................36 The 2006-2007 Season.............................................................................................37

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6 4 EFFECT OF Neoseiulus californicus RELEASES ON ARTHROPOD COMMUNITIES IN NORTH FLORIDA ST RAWBERRY FIELDS................................................................50 Materials and Methods.......................................................................................................... .52 Statistical analysis........................................................................................................... ........55 Results........................................................................................................................ .............55 Discussion..................................................................................................................... ..........58 5 HYPERSPECTRAL IMAGERY DETECTION FOR TWOSPOTTED SPIDER MITE DAMAGE IN STRAWBERRIES..........................................................................................69 Materials and Methods.......................................................................................................... .71 Field Plots.................................................................................................................... ....71 Sampling....................................................................................................................... ...71 Spectral Scanning............................................................................................................72 GIS Integration................................................................................................................74 Results........................................................................................................................ .............76 Spectral Analysis.............................................................................................................76 Accuracy of Categories of Mite Infestation....................................................................76 Spectral Map................................................................................................................... .77 Discussion..................................................................................................................... ..........77 Analysis....................................................................................................................... ....77 GIT Application...............................................................................................................78 Future Directions.............................................................................................................79 6 CONCLUSIONS....................................................................................................................85 APPENDIX A STRAWBERRY PEST M ANAGEMENT SURVEY............................................................88 B FUTURE WORK....................................................................................................................90 LIST OF REFERENCES............................................................................................................. ..92 BIOGRAPHICAL SKETCH.........................................................................................................98

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7 LIST OF TABLES Table page 3-1 Strawberry yield for Janu ary, February, and March 2007.................................................49 4-1 Cumulative number of each taxa found in each treatment in the three sampling periods in yellow sticky traps............................................................................................61 4-2 Cumulative number of each taxa found in each treatment in the three sampling periods of the pitfall traps..................................................................................................62 4-3 Cumulative numbers of each taxa in the three visual sampling periods............................63 4-4 Cumulative numbers of each taxa in the three foliar sampling periods.............................63 4-5 Mean values of diversit y indices in plots in earlyseason yellow sticky traps..................65 4-6 Mean value of diversity indices in plots in early-season pitfall traps................................65 4-7 Mean values of diversit y indices in plots in mid-season yellow sticky traps....................67 4-8 Mean values of divers ity indices in plots in mid-season pitfall traps................................67 4-9 Mean value of diversity indices in plots in late-season yellow sticky traps......................68 4-10 Mean value of diversity indices in plots in late-season pitfall traps..................................68 5-1 Classification summary of LD A cross-validation of PCA................................................83 5-2 Accuracy scores for the LDA............................................................................................84 5-3 Accuracy scores for LDA of Quickbird and SPOT5........................................................84

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8 LIST OF FIGURES Figure page 3-1 Twospotted spider mite colony mainta ined in the laboratory for greenhouse experiments.................................................................................................................... ....39 3-2 Transferring TSSM from the laboratory colony onto strawberry plants for the greenhouse trials.............................................................................................................. ..39 3-3 Mesh cages constructed to contain TSSM and N. californicus during the greenhouse trials......................................................................................................................... ...........40 3-4 Maps of the layout of the treatments in the field...............................................................41 3-5 Twospotted spider mite motiles in greenhouse trials.........................................................42 3-6 Twospotted spider mite e ggs in the greenhouse trials.......................................................43 3-7 Average number of TSSM motiles and eggs per trifoliate on the old strawberry leaves 2005-2006 field season...........................................................................................44 3-8 Weekly average of TSSM motiles per pl ot on old leaves in 2005-2006 field season.......44 3-9 Average number of TSSM motiles and e ggs per trifoliate on the young strawberry leaves 2005-2006 field season...........................................................................................45 3-10 Weekly average of TSSM motiles per plot on young leaves in 2005-2006 field season......................................................................................................................... ........45 3-11 Comparison of young and old leaves 2005-2006 season...................................................46 3-12 Comparison of young and old leaves 2006-2007 season within each treatment...............46 3-13 Average number of TSSM motiles and eggs on old trifoliates during the 2006-2007 season......................................................................................................................... ........47 3-14 Average weekly number of TSSM motiles on the old leaves in each treatment...............48 3-15 Average number of TSSM motiles a nd eggs on young trifoliates during the 20062007 field season.............................................................................................................. ..48 3-16 Average weekly number of TSSM motiles on the young leaves in each treatment..........49 4-1 Cumulative percent of families found on yellow sticky trap 1-cm squares.......................64 4-2 Most abundant families found on early-season yellow sticky traps between the treated and untreated plots.................................................................................................64

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9 4-3 Most abundant families found in the early -season pitfall traps in the treated and untreated plots................................................................................................................ ....65 4-4 Most abundant families found in the midseason yellow sticky traps among the early, middle and untreated plots.................................................................................................66 4-5 Most abundant taxa found in the mid-seas on pitfall traps between the early, middle, and untreated plots............................................................................................................ .66 4-6 Most abundant families found in the late-s eason yellow sticky traps in early, middle, late, and control plots........................................................................................................ .67 4-7 Most abundant families found in the late-s eason pitfall traps in the early, middle, late, and control plots........................................................................................................ .68 5-1 Reflectance map of TSSM di stribution of the experimental strawberry field, Citra, FL............................................................................................................................. ..........81 5-2 Variation of the spectral si gnatures of strawberry leaves at different levels of TSSM infestation.................................................................................................................... .......82 5-3 Regression of predicted versus observed raw TSSM numbers/leaflet...............................82 5-4 Scree Plot of PCA.......................................................................................................... ....83

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10 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science TIMED RELEASES WITH Neoseiulus californicus AS A BIOLOGICAL CONTROL AGENT FOR Tetranychus urticae Koch AND ITS ECOLOGICAL IM PACT ON NORTH FLORIDA STRAWBERRY FIELDS By Aimee Beth Fraulo August 2007 Chair: Oscar E. Liburd Major: Interdisciplinary Ecology Twospotted spider mite (TSSM), Tetranychus urticae Koch, is considered to be a key pest in north Florida strawberry fields. Management of TSSM is difficult because it can become resistant to miticides within a year of exposure, making chemical control difficult. As a result, biological control is beco ming a popular alternative. Neoseiulus californicus McGregor is known to be an effective biological control agent for TSSM in north Florida strawberries. The objectives of this study were to determin e the effect of timed releases with N. californicus to control TSSM throughout the season and also to evaluate the eff ect of predatory releases on the arthropod communities in th e field. We found that N. californicus can control TSSM effectively if released early in the season at an a ppropriate predator: pr ey ratio and that N. californicus show a functional response to high de nsities of TSSM. The Shannon-Weaver index, evenness, and richness measures were used to evaluate th e arthropod communities in plots treated with N. californicus Results showed that N. californicus does not significantl y alter the arthropod assemblage in the field. The ge neralist feeding habits of N. californicus and the natural diversity of the strawberry system may reduce the effect of N. californicus releases on the strawberry system. Finally, we conducted expl oratory laboratory studies to co rrelate TSSM infestation with

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11 spectral reflectance values of the leaves. A spectro radiometer was used to collect spectral data from individual leaflets that were infested with known levels of TSSM. Data obtained were used to construct categories of infesta tion levels at specific spectral regions. Results indicate that TSSM can be detected spectrally at very low le vels of infestation. Information obtained from these studies suggests that biolog ical control and spectral imager y could be integrated into a management program to develop an effec tive precision pest management program.

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12 CHAPTER 1 INTRODUCTION The strawberry industry began in early 15th century Europe as a collection of small localized enterprises. The wild fruit was orig inally used for medicinal purposes and was later propagated in household gardens. The first records of the modern strawberry trade date from the colonization of the New World, ca. 16th century (Wilhelm and Sagen 1974). Today, the United States is one of the top producer s of strawberries worldwide. The average yield in the United States ranks highest in the wo rld, and total harvested area is second only to Poland (Economic Research Service-USDA 2005). California is the center of strawberry pr oduction in the United States. However, Florida produces 100% of th e domestic winter stra wberry crop and ranks second in the country in overall pr oduction (Mossler and Nesheim 2002). Strawberries are the most valuable berry crop in Florida. No other plant bears more fruit earlier, as soon after plan ting, nets more profit per acre in such a short period of time, or thrives in so many different environments (Wilhem an d Sagen 1974). In 2003, Florida strawberries had a market value of $200 million and a production cost of $20,000 per acre (Brown 2003). By the year 2005, there were 7,300 acres in production comprising approxima tely three-quarters of the states cultivated berry acreage (Economic Research Se rvice-USDA 2005). Exports have been growing at an average rate of seven percent annually since 199 0 (Economic Research ServiceUSDA 2006). In northern Florida, strawbe rries are grown as an annual cr op on a raised bed, or hill system. The soil is injected with a soil fumigant such as methyl bromide to control soil pests and pathogens and the beds are covered with blac k plastic mulch. Drip ir rigation is run under the beds to improve water and nutrient efficiency. This plasticuture system mitigates pest and disease transmission in the fiel d (Mossler and Nesheim 2002).

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13 Strawberries are susceptible to a number of fungal diseases and are host to many arthropod pests. The most economically important pre-harvest fungal diseases are Botrytis fruit rot ( Botrytis cinerea ) and anthracnose fruit rot ( Colletotrichum acutatum ) (Ellis and Legard 2003). Major arthropod pests includ e coleopterans such as th e Strawberry Root Weevil, Otiorhynchus ovatus (Linnaeus) Black Vine Weevil, Otiorhynchus sulcatus (Fabricus), Rootworm, Paria fragaria Wilcox and several species of sap beetles. Homopterous pests include potato leafhopper, Empoasca fabae (Harris) spittlebug, Philaenus spumarius (Linnaeus) aphids, (Aphididae) and whiteflies, Bemisia tabaci and Trialeurodes spp Armyworms, cutworms and strawberry fruitworms (Noctuidae), tarnished plant bugs, ( Lygus spp .) and several species of thrips occur as well (Handly and Price 2003). The principal pest on strawberry plan ts is the twospotted spider (TSSM), Tetranychus urticae Koch (Waite 2002, Oatman et al. 1985, Escudero and Ferragut 2005, Cakmak and Cobanoglu 2006, Rhodes and Liburd 2006). Twospotte d spider mites feed on the leaves by piercing through the mesophyll layer with its needle-like chelicerae and sucki ng out the contents of the cells. This destroys the protective le af surface, nutrient availability, and decreases photosynthetic activity, resulting in a speckled or bronzed appearance of the leaves. If severe, the damage may reduce yields (Sonnevelt et al. 1996, Huffaker et al. 1969, Colfer et al. 2004). It is a common practice for growers to scout their fields to mon itor the presence of TSSM, this includes taking a systematic or random sa mple of at least 60 leaflets from a field and inspecting each leaflet fo r the presence of at least one mite motile (nymph or adult) or egg. Fields must be monitored regularly at least once per week as TSSMs aggregate quick ly into hot spots. Leaves can be examined with a 10X hand lens, or under a microscope in a laboratory. When 5%

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14 of the leaves are infested it is generally recomm ended for growers to take some type of control action (Greco et al 2004, Handley and Price 2003). Historically, miticides have been used to c ontrol TSSM infestations, but due to increased resistance, harmful effects to the environment a nd to non-target organisms, and high costs, many growers are looking at alternative methods of control (White 2003). There are several known natural enemies of TSSM, such as the sixspotted thrips, Scolothrips sexmaculaus minute pirate bug, Orius tristicolor (White), and Bigeyed bug, Geocoris punctipes Stal, and brown lacewing (hemerobiid) (Oatman and Voth 1972). However, predator y mites from the family Phytoseiidae are known to be among the most effec tive control agents. Prior to 2006, Phytoseiulus persimilis Athias-Henriot was the most commonly utiliz ed predatory mite in Fl orida strawberries (Rhodes and Liburd 2006). However, the cooler climate that exists in northern Florida during the production season does not support its viability in th is region of the state. Research conducted by White (2003) found that Neoseiulus californicus (McGregor) is a better choice in north Florida strawberry fields because of the wide fluctu ation in temperature, moisture and humidity. Neoseiulus californicus is a commercially available phytosei id mite that is a generalist type II feeder (McMurtry and Croft, Rhodes and Liburd 2005). It can surv ive without prey and for long periods at low temperatur es (Hart et al. 2002). It has b een used either alone or in conjunction with P. persimilis for TSSM control (Rhodes et al. 2006). However, the time when N. californicus should be released, as well as the freque ncy of applications (releases) has not been determined (Cakmak and Cobanoglu 2006, Hart et al. 2002). The objectives of this study are to determine the most appropriate time during the growing season for i noculative releases of N. californicus to control TSSM, to evaluate the eff ect of predatory releases on naturally occurring arthropods in the strawberry plant en vironment, and to establish a pest monitoring

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15 system for growers using geographic information technology (GIT) to detect early damage of TSSM in strawberries. A strawberry pest management survey was al so administered. The survey was distributed to growers across the state of Florida to gather information regarding specific pest management concerns. Questions addressed grow ers perceptions of pest probl ems and their primary concerns when considering a management plan. The resu lts were compiled and analyzed to help us develop appropriate management strategies that target growersspecific needs.

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16 CHAPTER 2 LITERATURE REVIEW Twospotted spider mite The twospotted spider mite, Tetranychus urticae Koch, belongs to the family Tetranychidae. It feeds on strawberry ( Fargaria spp.) leaves by pierci ng the photosynthetic sites of the mesophyll tissue with spec ialized chelicerae. It pierces the chloroplasts, ingests the chlorophyll, and collapses the interior structure of the leaf, alteri ng the ability of the leaves to utilize solar radiant energy, reduces carbon dioxide assimila tion and decreases transpiration (Jansen et al. 1997, Jensen 2005, Shanks and Do ss 1989). The twospotted spider mite is a particularly harmful pest due to its high rate of fecundity and its short life cycle. Females lay an average of six eggs per day and for a total of 70-100 eggs during a lifetime (Williams 2000). In high temperatures (>33 C) a female can lay as many as 20 eggs a day and the life cycle decreases from the average 30 days to seven days (Shanks and Doss 1989, Grostal and Dicke 2000, White and Liburd 2005). Twospotted spider mite s also thrive in environments with low soil moisture. White and Liburd (2005) reported two times as many motiles on plants exposed to low moisture regimes compared with those exposed to high soil moisture. Twospotted spider mite develops from a pa le yellow egg into a six-legged yellowishwhite larva. It molts two more times becoming an eight-legged protonymph and then deutonymph before maturing into an adult. Depe nding on the temperature, it may take between 4-12 days for the mite to mature. Spider mites ma y live for three weeks as an adult. The female is about 0.5 mm in length and the male grow s to be approximately 0.3 mm (Williams 2000). Spider mites produce silk from glands located in the palpi to spin fine webs on the underside of the leaves to protect the colonies from predat ors and facilitate moveme nt across the leaf. The

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17 webs may also be used for courtship, to protect against weather and miticides, to conserve their eggs and reduce interguild predation (McMur try et al 1907, Kranz, 1979, Roda et al. 2000). During the summer months when TSSM is in a feeding reproductive stage it is a yellowish green color. The female is globular in shape and has two pronounced dark lateral feeding spots on the abdomen. The male has a more rectangular shape and has similar dark markings. These markings are lighter and less de fined than on the females. During the winter months, low temperatures and short day length in duce diapause in female mites. They cease feeding and reproduction and become dark red in color. The females over-winter in the soil (Bollard et al. 1999, Sugasawa et al. 2001). Sex determination is entirely haploid-diploid (Huffaker et al. 1969). Both male and female TSSM adults are brightly colored ranging from green to yellow to red. Due to broad morphologi cal differences TSSM has been described with over 50 different names. The inability for some individuals to successfully mate suggests that T. urticae may be a species complex (Bollard et al. 1999). Twospotted spider mite is an important pest on a broad range of agricultural crops. In strawberries, early season infestation can severely decrease yi eld (Sugasawa 2001, Rhodes 2005). A high infestation often results in defoliati on and a significant redu ction in fruit yield. Yield reduction has been record ed to be as high as 29%, but usually averages between 10-15% (Walsh 2002, Oatman et al. 1985). Because of it s short life cycle, TSSM has the capacity to become highly resistant to most pesticides in a short period of time. Outb reaks have intensified over the last few decades due to increased use of pesticides and modern cultural practices (Huffaker and McMurtry, 1969 and Escudero an d Ferragut, 2005). As traditional methods of chemical control are less effec tive, and marketability due to chemical residue has become a

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18 social concern, growers are beginni ng to rely on natural enemies as an alternative to chemical management systems (Escudero and Ferragut 2005). Control Methods Many commercial growers have developed the practice of applying multiple treatments of chemical pesticides, mainly acaricides, on a calendar basis throughout the season (Villanueva and Walgenbach 2005). Compounds such as hexythi azox, bifenatzate, abamectin and bifentrhrin have been heavily relied upon to control arthropod pest infest ations. During the last half a century, concern over resistance of mites to specific miticides and of the deleterious effect that the miticides have on beneficial predators has increased (Escudero and Ferragut 2005). Broad spectrum insecticides such as pyret hroids and organophospha tes have been shown in laboratory tests to be harm ful to beneficials. These chemi cals decrease rates of oviposition, affect egg numbers and increase rates of morta lity in adults. Even reduced-risk compounds have variable levels of toxicity and sub-lethal e ffects on reproduction in bene ficials (Villanueva and Walgenbach 2005). Many growers are investigating alternative methods of contro l due to the concerns over chemical tactics. A principal alternative to ch emical tactics for management of key arthropod pests is inundative releases of pr edatory mites and insects. This pr actice has been used to manage TSSM populations. Approximately 40% of Florida s strawberry growers, particularly in the southern part of the state, practice a method of biocontrol, which has led to a significant decrease in chemical applications (Mossler and Nesheim 2002). Natural Enemies There are several natural enemies of TSSM. Oatman et al. (1985) identified ten insect species belonging to families Thripidae, Cecidomyiidae, Coccinellidae, Staphylinidae, Anthocoridae, Lygaediae, Chrysopodae and Hemer obiidae and nine phytoseiid mite species that

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19 are natural enemies of TSSM. Rondon et al. (20 04) conducted laboratory st udies measuring rates of consumption, efficacy and f eeding preference by bigeyed bugs, Geocoris punctipes Say, minute pirate bugs, Orius insidiosus (Say ) and the pink spotted lady beetle Coleomegilla maculata DeGeer. The experiments concluded that th ese insects do consume spider mites, but also show a preference for aphids and other phytophagous insects, reducing their effectiveness as target control agents for TSSM. The most successful predators in suppressing TSSM are the predaceous phytoseiid mites, Phytoseiulus persimilis and Neoseiulus californicus (Blackwood and Shausberger 2001, McMurtry and Croft 1997, J ung and Croft 2001, Croft et al. 1998, Sabelis and Janssen 1994). Predatory Mites: Phytoseiulus persimilis and N. californicus belong to the family Phytoseiidae. Phytoseiids are voracious predator s of spider mites. Th ey compose one of the most important families of predatory mites used in biological control systems (Blackwood and Shausberger 2001). Phytoseiid mites are approxi mately 0.5 to 0.8 mm and live in topsoil under leaf litter. They have a pair of needle-like chel icerae which are inserted into the prey and extract its internal fluids. They range from type I, highly specialized feeders that are genus specific with regard to prey preference, to t ype IV generalist feeder s that are able to utilize mites, pollen, or honeydew as an energy source. Phytoseiulus persimilis Phytoseiulus persimilis is a type I obligate specialist that is genus specific in terms of its feeding preferences (McMurtry and Croft 1997). It feeds exclusively on Tetranychus spp.and has one of the highest rates of population increase an d the shortest development time of Phytoseiid mites (McMurtry and Croft 1997). Phytoseiulus persimilis depends on TSSM to survive and reproduce. It has been obse rved to consume up to five times as many TSSM as N. californicus and has a greater fecundity (Gilstrap and Friese 1985). With its long setae, it is well adapted to

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20 move over webbed spider mite co lonies. As a type I specialist P. persimilis tends to aggregate in areas of high prey, has high walking activity and aerial dispersal, and is ephemeral and difficult to maintain as a reliable contro l agent (Jung and Croft 2001, Croft et al. 1998). It is effective in the short term, but it over explo its the prey and perishes when the food source is eliminated. Phytoseiulus persimilis is a more voracious and well adapted predator than N. californicus but is unable to survive in temper ate climates. (Escudero and Ferragut 2005, Easterbrook 1992). Neoseiulus californicus Neoseiulus californicus is a type II/III gene ralist predator, meaning that it can survive on a variety of live prey as well as on pollen (McMurtry and Croft 1997). It is innately adapted to strawberry plant structure (Castignol i et al. 1999). As a generalist, it moves further from a central release point than specialists such as P. persimilis and provides more stable and regulatory pest suppression (Croft et al.1998). It is prone to engage in intraguild predation because it is not dependent solely on TSSMs to survive (R hodes et al. 2006). In trials combining P. persimilis and N. californicus N. californicus continuously displaced P. persimilis (Rhodes et al 2006). Higher interspecific predation rates are common among generalist phytos eiid species. For N. californicus, heterospecific feeding may be beneficial in terms of nutrition, development and oviposition, whereas P. persimilis cannot develop on prey other than Tetranychus spp. and tends to be cannibalistic when prey densitie s are low (Walzer and Schausberger 1999). Neoseiulus californicus has five developmental phases, egg, larva, protonymph, deutonymph, and adult. The life cycl e is half as long as TSSM. It can be completed within four days, depending on temperature. Neoseiulus californicus lives for approximately 20 days. Females lay an average of three eggs a day and consume five adult TSSM a day (Krantz 1978, Escudero and Ferragut 2005). The population corre sponds to the increases and decreases of TSSM (Oatman et al. 1985). While the developmen t rate of phytoseiids is linear and TSSM is

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21 non-linear, high rates of development and consump tion enable them to achieve and maintain control over the TSSM population un der the right environmental cond itions (Sabelis and Janssen 1994). Neoseiulus californicus disperses earlier than P. persimilis has a slower metabolism, a lower searching efficiency, but a high rate of spatial coincidence with TSSM and can tolerate starvation (Greco et al. 2004). Neoseiulus californicus has a broad diet range including sap, honeydew, and pollen and can reproduce on pollen at a comparable rate to a diet of prey (McMurtry and Croft 1997). Neoseiulus californicus is used widely in Mediterranean regions where P. persimilis has failed to establish. It is more tolera nt to some pesticides and is adapted to the fluctuations of prey dynamics and a mild climate (Escudero and Ferragut 2005). Temperature is the most important abiotic factor in predator establishment. It affects development, survival and reproduction of predat ory mites. High temperature fluctuation is the primary limiting factor that restricts the use of P. persimilis as a biological control agent (Escudero and Ferragut 2005). Th e developmental threshold in N. californicus is estimated to be 9.9 C. Adult females can survive throughout the winter, for over three months under sheltered conditions. Without entering di apause, or consuming prey, they continue to oviposit and develop. They have a short generation time and can complete six generations in summer and one during the winter (Hart et al. 2002). Effect of Timing of Predatory Releases on TSSM Populations At high levels of TSSM infestation, the intr oduction of predatory mites may not be able to control and maintain TSSM below the ec onomic threshold, which in strawberries is considered to be between five and 20 mo tiles per leaf (Oatman 1972, Hardman 2005). Laboratory and field expe riments show that for N. californicus to be an effective biological control agent, it must be released early in the s eason when there is a low incidence of spider mite

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22 infestation (Greco et al. 2005). If the predator is released too late in the season when TSSM population is high and the ratio of TSSM to predator is greater than 10:1, the released predator will not have the capacity to consume the pest in high enough numbers to control it to a level below the economic injury le vel (Greco et al. 1994). Other studies have found no rela tionship between the time wh en predators are released and suppression of TSSM. Studies conducted in nor thern California of Persea mite (Acari: Tetranychidae) infestations on avacado trees have shown that timing of inundative releases of various species of predatory mites had no significa nt effect on the prey population density or on yield (Hoddle 1998). Another study done in cotton s howed similar results, i.e.: there were no significant differences ( P = 0.07) between the early release, late releases ( P = 0.06) and the control (Colfer et al. 2004), nor did releases enhance the natu ral predator population. However, in both of these studies, there wa s a reduction in spider mite popul ations in all treatments. This reduction was not attributed to the treatment, but to ecological factors such as plant phylogeny, climate, and other naturally occurring enemies (Hoddle 1998, Colfer et al. 2004). Plant physiology has an impact on TSSM population dynami cs due to decreasing nutrient availability from previous mite infestations or other phys iological factors (Shanks and Doss 1989, Croft and Coop 1998). Twospotted spider mite populations natu rally begin to decrease after harvest and with foliar aging (McFarlane and Hepworth 1994). Research conducted by Waite (2002) in strawber ries supports the Pes t in First (PIF) theory, which suggests that pests can be controlled by artificially introducing them into the field and allowing them to establish high population de nsities for several week s. Predators are then introduced at the appropriate ratio. As the pest s disperse and spread throughout the field, the

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23 predators are already established and maintain adequate control and pest: predator ratio throughout the season. Rhodes and Liburd (2006) found that releasi ng predators one time early in the season alone and in combination with chemical or anot her biological control coul d maintain control of TSSM throughout the season. There is not yet ad equate evidence regard ing the affect and appropriate date of release for predatory mite s on strawberries. Biocontrol companies differ in recommendations regarding general release date s. Koppert Biological systems (Netherlands) recommend that growers apply N. californicus preventively at 10,000 mites/ha at 21 day intervals. Biobest Biological Systems (W esterlo, Belgium) and Biocontrol Network (Brentwood, TN) recommend bi-weekly rel eases throughout the season, and Green Method Biocontrols (Nottingham, NH) recommends as needed monthly releases (2006). Most growers release biocontrol agents on a standard calendar basis (Greco et al. 2004). Geographic Information Systems in Pest Monitoring Mite damage begins at a cellular level in the mesophyll; therefore, it is difficult to observe early mite damage with visual inspection and field sc outing. Precision insect pest management (PIPM) is a developi ng technique that would enable growers to detect and analyze spatial and temporal distribution of agricultural pest damage before it is visible in their fields. This enables growers to employ preventative t actics before the pests reach economic threshold. As N. californicus is able to survive in fields with low m ite density (Greco et al. 1994), predators released before damage is visible may have the potential to prevent crop damage by TSSM populations, consequently, reduci ng costs and increasing produc tion (Dayang and Kamaruzaman 1999). Geospatial Information Technology (GIT) is a se t of tools associated with site-specific precision agriculture. The three main elements consist of Global Positioning System (GPS),

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24 imagery systems, and Geographic Information System s (GIS). These tools can be used to collect and monitor information about a pest population that can be illustra ted as a density or topographical map referred to as a bug map. A va riety of biological, chemical, and spectral data from a field can be integr ated and analyzed to create ma ps of vegetative condition in relation to pest damage (Brewster 1999, Dayang and Kamaruzaman 1999). The Global Positioning System (GPS) component is essential in constructing an accurate field map. This system uses a constellation of satellites that provide s accurate geographic position coordinates anywhere in the world. Signals are transmitted from satellites and compared with the time of transmition to the tim e that they are received by the GPS unit on the ground. Using triangulation the GPS calculates the users exact location. Global positioning systems have been used to make initial fiel d measurements and monitor and manage field operations by using application maps. Vegetation maps commonly use sp ectral reflectance images. The reflectance values are correlated with pest infestations. Instruments su ch as spectroradiometers or other hyperspectral imaging systems such as a liquid crystal tuna ble filter (Cambridge Research Instruments, Woburn, MA) have been used to obtain reflectance images of physiological stress in a plant. The values of these spectral responses, or signatures, must be discriminate d between by constructing a spectral library. The library is constructed by isolating distin ct areas of the electromagnetic spectrum that are reflected from the leaves. Th is response is read as a wavelength (nm). The wavelengths correspond to different energy reflectance that is related to transpiration and photosynthetic activity and used to assess the health of a plant (Barnes et al. 1996). Healthy plants reflect in the green (~550 nm ) and absorb in the red spectra (~650 nm). When plants are damaged, they often lose thei r ability to synthesize carbon compounds and the

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25 ability for chlorophyll to capture and absorb spec ific wavelengths of light. They have a much higher reflectance in the blue and red chlorophyll a and b absorption regions of the spectra and may appear chlorotic or yellowish. The reflectance of near infrared energy is also reduced in a damaged plant. These physiological changes are the most consistent leaf response to environmental stress. The optimum ranges of sensing a de crease in chlorophyll production and absorption are between 535-640 nm and 685-700 nm, blue and red spectra, respectively (Jensen 2005). The relationship between plant stress and pe st population enables an imagery system such as infrared photography or a spectrometer to analyze correlated vegeta tion spectral reflectance using indices such as NDVI and infr ared: red ratioing (F itzgerald 2004). The GPS points may be used to georeference th e field imagery data wh en it is input into a geographic information system such as ArcGIS or ENVI (Fitzgerald 2004). Images can be positioned within a geographically corrected map a nd viewed spatially to observe the distribution of pests and related vegetation stre ss. The GIS could be used to anal yze the pest interaction in the field by using spectral imagery or be integrated into a model used to predict the risk of further infestation. A user could then query the predictive model and re ceive a map of projected pest occurrences (Brewster 1999). Geographic informa tion technology has been used extensively in agricultural crops to determine levels of hydr ation and nutrient content in the soil. Fitzgerald (2004) used hyperspectrometry to determine pres ence/absence of the stra wberry spider mite, Tetranychus turkestani, on cotton. This technology has potential to reduce inform ation collecting and use of pesticides, but due to a lack of research on the field level, particularly in cr ops such as strawberries, little application has been attempted. Although GIT has been used to assess mite damage on cotton

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26 and apple trees (Dayang and Kamaruzaman 1999), cost and time constraints are still limitations to wide use of this technology (Swinton 2003).

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27 CHAPTER 3 BIOLOGICAL CONTROL OF TWOSPOTTED SPIDER MITE, Tetranychus urticae Koch WITH PREDATORY MITE, Neoseiulus californicus IN GREENHOUSE AND FIELD EXPERIMENTS Twospotted spider mite (TSSM), Tetranychus urticae Koch, is a major pest of strawberries ( Fragaria spp.) throughout the world (Oatman et al. 1985, Cloyd et al. 2006, Wynam et al. 1979, Walsh et al. 2002, Stonneveld et al. 1996, Huffakker et al. 1969, Sanches et al. 1979). Its management is of particular con cern for growers because it has a rapid lifecycle that can be less than two weeks and sex determ ination is exclusively arrenotokous (males are haploid, females are diploid). Genes that are resistant to a miticide will be directly passed to offspring. Resistance can occur within a year of exposure to pesticides, making chemical control difficult (Huffaker et al 1969, Cross et al. 2001). Biological control is becoming a popular alte rnative for many strawberry growers in north Florida (Rhodes et al. 2006, Rhodes and Liburd 2006). Phytoseiulus persimilis is a phytoseiid mite that has been commonly used to control TSSM in north Florida strawberry fields. It is an extremely effective predator, but is classified as a type I specialist, meaning that it is genus-specific with regard to prey preference (McMurtry and Croft 1997). Phytoseiulus persimilis exploits its prey and perishes when the food source is elimin ated. It is highly sensitive to chemical miticides and fungicides and is unable to survive in temperate climates (Escudero and Ferragut 2005, Easterbrook 1992). Neoseiulus californicus (McGregor) is another phytoseiid that is highly effective in controlling TSSM. Its use is becoming increasing ly more important in north-central Florida (Liburd et al. 2003, Rhodes and Liburd 2006). As a type II generalist, N. californicus provides stable and regulatory pest s uppression (Croft et al.1998). St udies by Oatman et al. (1981), Escudero and Ferragut (2005), Ea sterbrook (1992), and Croft et al.(1998), have demonstrated

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28 that N. californicus is resistant to many chemical pesticid es, and is able to remain viable at variable temperatures (Hart et al. 2002). Studies conducted in California and in Belgium evaluating two different rates and times of N. californicus releases found th at TSSM populations were significantly reduced if N. californicus was present early in the season and if the plots had low TSSM populations (Oatman et al. 1977). Rhodes et al. (2006) found that N. californicus is able to maintain more consistent cont rol of TSSM populations compared with P. persimilis throughout the season in north Florida strawberry fields. In that study, N. californicus displaced P. persimilis in both greenhouse and field experiments. Biocontrol companies differ in thei r recommendations for release of N. californicus For preventative measures, commercial distributors recommend releasing N. californicus at a rate of 10,000-20,000 mites/ha at 21-day intervals, whereas bi-weekly curative releases of 60,000 mites/ha are recommended for continued suppr ession of TSSM througho ut the season. Most growers release biocontrol agents on a standard calendar basis (Greco et al. 2004). In this study, both greenhouse and field e xperiments were conduc ted to assess the effectiveness of N. californicus when released at different times throughout the season in north Florida strawberries. Greenhouse tr ials were conducted under contro lled conditions to isolate the effect of the predatory releases from environmen tal effects. Field experi ments were conducted to validate the results from the gree nhouse in a larger strawberry ecosystem. The goal of the study is to determine the phenological stage in the strawberry system when N. californicus is most effective in controlling TSSM infestations. Materials and Methods Colony A TSSM colony was maintained in the Small Fruit and Vegetable IP M Laboratory at the University of Florida, Gainesville, FL .The colony was reared on strawberry transplants

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29 contained in one gallon polyethyl ene pots. Plants were kept unde r two 60-watt bulbs, 14L:10D photoperiod, at approximately 32C (day) and 24C (night) at 35% relative humidity. Plants were provided with ~250 ml of water three times per week (Figure 3-1). Greenhouse experiment To assess the most appropriate time to release pr edatory mites, four treatments were evaluated in a completely randomized design with 5 replic ates. The treatments included the release of N. californicus at 5-day intervals: 1) early release on day 0; 2) a middle release on day 5; 3) late release on day 10; and 4) a control with no predatory releases. The experiment was conducted in a fibergla ss greenhouse at the University of Florida. Twenty strawberry plants (var. Festival) ~20 cm in height were taken from the shade house at the Entomology and Nematology Department of the Un iversity of Florida. Plants were visually inspected and hand-cleaned to ensu re that there were no initial insects or mites on the leaves. Each plant was trimmed to four trifoliates. Forty T SSM motiles from the laboratory colony were distributed evenly (10 mites/trifoliate) on each plant using a probe constructed from a 0.020 stainless steel morpho minutien in sect pin (Bioqip, Rancho Dominquez, CA) attached to the stem of a medical cotton swab (Figure 3-2). Each plant was contained within a mesh cage to reduce cross contamination. The cages were constructed of galvanized hardware cloth (Garden Plus, North Wilkesboro, NC) of 0.6-cm mesh, 23 gauge, which was bent into a cylinder (30.5 cm in height, 14.0 cm in diameter) and covered in no -thrips insect screen, mesh size 81 X 81 (Bioquip, Rancho Dominguez, CA). The mesh was at tached to the cylinder with a hot glue gun (Surebonder glue gun, FPC Corp., Wauconda, IL) (Figure 3-3). The greenhouse had natural light, with no artificial light source added. The temperature av eraged between 28 C (day) and 15C (night). Plants were hand-watered with 250 ml of water every five days. Predators were purchased from Koppert Biological Systems, Ro mulus, MI. Their viability was tested by

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30 observing them in a Petri dish for 15 minutes to assess level of activity. They were used within 48 hours of observation. The ratio of predator to TSSM was 1:10 respectively for each release. The ratio was determined by calculating the aver age number of TSSM motiles from the sample leaflets in each treatment. The number of mo tiles found on the leaflets of each treatment were averaged, multiplied by the total number of l eaflets on the plant and divided by 10. The laboratory trials were conducted three times, March 2006, December 2006, and January 2007. Each trial lasted approximately 30 days. Sampling Plants were sampled every five days by det aching one leaflet from each plant and counting the number of TSSM and N. californicus motiles and eggs under a dissecting microscope to determine the effect of the timed releases on TSSM populations. Statistical Analysis The data were subjected to stat istical analysis using analysis of variance (ANOVA) and LSD means separation (P < 0.05) using the genera l linear model (GLM) procedure of the SAS statistical software package (SAS Institute, 2002). The average number of TSSM motiles and eggs at five-day intervals were compared across treatments. Twospotted spider mite motiles and eggs were log transformed to comply with the assumptions of the ANOVA (SAS Institute, 2002). Field Experiment A field experiment was established to validat e our greenhouse findings. The field was located at the University of Florida Plant Science Rese arch and Education Unit near Citra, Florida (82.17W, 29.41N). The areas had not been cultiv ated previously. Prior to planting, the field was treated with a granulated fertilizer (10-10-10) (N-P2O5-K2O) at a rate of 653.3 kg/ha. Beds with black polyethylene mulch (1.6 mm thic k) were laid using a Kennco power bedder (Ruskin, FL) and the soil was injected with met hyl bromide:chloropicrin (80:20) at a rate of

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31 326.4 kg/ha. Devrinol (napropamide) was applied be tween row middles at the rate of 4.32 kg/ha as a pre-emergent herbicide. Dr ip irrigation tape was laid under the polyethylene sheets with emitters every 20.3 cm. Strawberries, variety Festiv al, were planted the first week of October 2005 and 2006 on raised beds. There were six 7.3 m long rows per plot, each bed contained double rows of transplants 0.35 m apart within ro w and 0.35 m between row (24 plants per row). For the first two weeks overhead irrigation was run one time a day for two hours between the hours of 10:00 AM and 2:00 PM to keep the you ng plants cool. After establishment, the strawberry plants were irrigated by the drip tape on a timer 3 times a day for a half hour at the rate of 8.7 liters per 100 m (0.65 gal/100 ft). The st rawberry plants were fertilized through the drip irrigation line once weekly with 18.5 kg of ammonium nitrate and 32.7 kg of muriate of potash per ha. In February, the nitrogen was in creased to 27.1 kg/ha. A fungicide was applied throughout the season 3 times per week in a ro tation of several different products (Abound [azoxystrobin], Topsin [thiophanate], Allie tte [aluminum tris], and Serenade [ Bacillus subtilis ]). No insecticides were applied to the res earch plots. Weeds were controlled by hoeing between rows and using an s-tine around the border of the plot. Strawberries were harvested one time per week beginning in January and increased to two times per week in February to reduce opportunity for damage by birds and other vertebrates. The experimental design in the 2005-2006 s eason was a randomized complete block with six replications of four treatments. In the 20062007 season, there were four replications of the four treatments. Each plot was 7.3 m with an 11 m buffer zone between plots. The treatments were assigned based on plant phenology and included 1) an early release of N. californicus (Koppert Biological systems, Romu lus, MI) 4 weeks after planting (WAP); 2) a middle release at eight WAP; 3) a late release at 12-16 WAP; and 4) a contro l with no releases. The late

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32 application was moved up four weeks in the 2006-2007 season due to high temperatures and faster accumulation of degree da ys (DD), resulting in high mite populations. In both seasons, the late release was applied at a pproximately 1380 DD at a 10C thre shold) (Figure 3-4a,b). During the first season (2005-2006) TSSM was introduced at a rate of 100 TSSM per plot on 27 February, because numbers present initially were extremely low. Sampling Systematic random samples were taken on ce weekly throughout th e season. Each week, eight trifoliate leaves were taken from each plot, four old and four young leaves. The young leaves were taken from the upper strata of the crown and the old leaves were taken from the lower strata. We analyzed the old and young leaves separately since prev ious research by Croft and Coop (1998) and Sances et al. (1981) indicated that TSSM occurrence differs with foliar age. The samples were transported back to the labo ratory in Zipper Seal Storage Bags (American Value, Goodlettsville, TN) for analysis. Neoseiulus californicus and TSSM motiles and eggs were counted and recorded using a dissecting binocular microscope (10-20X) (Leica MZ12.5, McBain Instruments, Chatsworth, CA). Statistical Analysis Twospotted spider mite motiles and eggs were log transformed to standardize the variances and then subjected to an Analys is of Variance (ANOVA) and Least Significant Differences (LSD) test for mean separation ( P < 0.05). Twospotted spider mite infestations did not occur until late in the 2005-2006 season, so the to tal yield data in each treatment was used to analyze differences. However, during 2006-2007, TSSM was present throughout the season and yield was calculated for each month of the harv est period. The yield for each treatment was compared using an ANOVA followed by an LSD test to separate the means. All statistical analyses were performed using the SA S system (SAS Institute Inc. 2002).

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33 Results Laboratory Experiments Releases of N. californicus resulted in significantly lower numbers of TSSM motiles compared with the control treatment ( F = 28.69; df = 4, 335; P < 0.0001) (Figure 3-5 a). By day 10, the number of TSSM motiles in the early (day 0) and the middle (day 5) N. californicus release were significantly lower comp ared with the control treatments ( F = 5.80; df = 4, 55; P = 0.002). On days 15 and 25, the late treatment (day 10 release) resulted in significantly fewer TSSM motiles compared with the early and middle releases ( F = 29.83; df = 4, 55; P < 0.0001) (Figure 3-5 b). The number of TSSM eggs show ed a similar trend to the motiles. Significant differences between the treatments and the cont rol occurred in total eggs accumulated throughout the trial ( F = 39.79; df = 4, 55; P < 0.0001) (Figure 3-6 a). By da y 25, significantly fewer eggs were found in the late treatment compared with the early and middle treatments ( F = 6.82; df = 4, 55; P = 0.0005) (Figure 3-6 b). 2005-2006 Field Season During the first 15 weeks of the season, TSSM population was extremely low. Data were insufficient to conduct a statisti cal analysis and to report results. Twospotted spider mite numbers increased from the time of TSSM introduction on 27 Febr uary. The release of N. californicus resulted in significantly fewer TSSM motiles and eggs on the old leaves in the early (16 November release) and middl e (14 December release) treatment s compared with the late (22 March release) and control treatmen ts (Figure 3-7). Releases of N. californicus in the early and middle season maintained significantly lower p opulations of TSSM throughout the season while the populations in the late and control tr eatments continued to increase (motiles: F = 22.84; df = 8, 135; P < 0.0001, eggs: F = 44.62; df = 3,135; P < 0.0001) (Figure 3-8). The young leaves also contained significantly fewer TSSM motiles and eggs in the early and middle releases of N.

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34 californicus compared with the control (motiles: F = 20.12, df = 8, 135, P < 0.0001; eggs: F = 29.37; df = 3, 135; P < 0.0001) (Figure 3-9). Similar to the results on the old leaves, the N. californicus releases early in the season significa ntly suppressed TSSM throughout the season compared with the late and control treatments (Figure 13-10). The age of the leaves did not affect TSSM eggs and motiles throughout the season ( F = 1.30; df = 1,280; P = 0.3 (Figure 311). 2006-2007 Field Season Significant differences in TSSM populations did occur between l eaf age classes in the second season (2006-2007). There were no significant differences du ring the pretreatment period between any of the treatments in the old leaves (motiles: F = 1.53; df = 3,12; P = 0.3 eggs: F= 1.05; df = 3,12; P = 0.4) or in the young leaves (motiles: F = 0.41; df = 3,12; P= 0.7 eggs: F= 1.58; df = 3,12; P = 0.2). Significant differences began to appear between the treatments in the old leaves (motiles: F = 5.79 df = 3,12; P = 0.01 eggs: F = 5.46 df = 3,12; P = 0.01) and young leaves (motiles : F = 3.43; df =3,12; P = 0.05 eggs: F = 3.95 df = 3,12; P = 0.04) on 26 December. The numbers of TSSM motiles and eggs continued to decrease in plots treated with N. californicus throughout the season and differences between treated and untreated plots became more statistically significant on 30 January in the old leaves (motiles: F = 20.62 df = 3,12; P < 0.0001 eggs: F= 6.03 df = 3,12; P = 0.01). However, the young leaves no longer showed a significant difference between treated and untreated (motiles: F = 1.33 df = 3,12; P = 0.05 eggs: F = 3.95 df = 3,12; P = 0.3). These trends persisted th roughout the remainder of the season. The old leaves contained significantl y more TSSM motiles and eggs than the young leaves in the 2006-2007 season (Figure 3-12). Overall, old leaves contained significantly fewer TSSM motiles and eggs among the early, middle and late treatments compared with the control (motiles; F = 13.13; df = 3, 268; P <

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35 0.0001, eggs: F = 6.81; df = 3,268; P = 0.0002) (Figure 3-13). The av erage weekly number of TSSM motiles shows that within ca. two weeks after each release, N. californicus was able to reduce TSSM for the remainder of the season (F igure 3-14). No treatme nt differences were observed on the young leaves (motiles: F = 2.26; df = 3, 12; P = 0.08, eggs: F = 0.59; df = 3,12; P = 0.6) (Figure 3-15). The weekly average numb er of TSSM on the young leaves was not significantly different in any of the treatments (Figure 3-16). Yield: In the 2005-2006 season the yi eld was not significantly different among treatments ( F = 1.60; df =3,15; P = 0.231). The total yield for the contro l averaged 74.8 7 kg/plot; early treatment averaged 62.1 kg/plot, middle treatment averaged 64.4 4 kg/plot and late treatment averaged 59.4 kg/plot. The average total yield through the 2006-2007 season was not significantly difference among any of the treatments ( F = 0.09; df = 3,12; P = 0.97). The same pattern occurred for yield collected in January ( F = 1.47; df = 6,41; P = 0.2), February ( F = 4.84; df = 6,41; P = 0.5), and March (F = 1.43; df = 6,41; P = 0.98) (Table 3-1). Discussion Greenhouse Experiment The greenhouse experiment demonstrated that one early season release of N. californicus was able to maintain low numbers of T SSM. Within five days of each release, N. californicus significantly reduced numbers of TS SM in the treated plants compar ed with the untreated plants. The early and middle treatments had low initial TSSM populations that remained low with the introduction of N. californicus Neoseiulus californicus has also been observed in previous studies to maintain TSSM populations at low densities (McMurtry a nd Croft 1997). Twospotted spider mite populations naturally increased in th e untreated plants to very high levels. Within five days of N. californicus release, the TSSM populations in th e late-treated plants fell sharply

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36 and were significantly ( P = 0.05) lower than in the early and middle treatments. The sharp decline in the late treatments, along with stable control in the early and middle treatments, indicates that N. californicus demonstrate a functional response with variations in prey density (Hassell et al. 1976). Field Experiments The field experiments in both s easons validate our gr eenhouse trial that in dicates the ability for N. californicus to control TSSM populations. The num ber of TSSM recorded during the 2005-2006 field season was lower than the 2006-2007 season. Several environmental factors differed between the two field seasons. The 2005-2006 season was the first time the field was used to cultivate strawberries. The lack of hos t plants prior to the growing season may have contributed to the absence of TSSM populat ion. Throughout the season there were extreme temperature fluctuations. Twospotted spider mite populations are sensitive to ambient temperature. They reproduce rapidly in warm temperatures and populati ons have been observed to decrease at cooler temperatures (Hart et al. 2002, White and Li burd 2005). In the 2005-2006 season, there were frequent recurrent freezes throughout the season. The daily low temperature fell below 0C for a total of 15 days in the 2005-2006 season and only for 2 days in the 20062007 season. The maximum daily temperature ranged from 7C to 32C in 2005-2006 and the range was 12C to 32C in 2006-2007. (Florida Automated Weather Network, 2007). The colder temperatures throughout the 2005-2006 season ma y have helped to suppress the TSSM population. The 2005-2006 Season The 2005-2006 season had low initial TSSM populati ons in all plots. Within one week of introduction of TSSM on 27 February, the popula tion in the late-releas e treatment plots and control plots rapidly increased throughout the rest of the season. However, N. californicus which

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37 had been released on 16 November (early treatment) and on 14 D ecember (middle treatment) had been able to establish in strawberry plots without TSSM prey and when TSSM populations developed, N. californicus was able to maintain consistent control of TSSM to a level significantly lower compared w ith the late-release and cont rol treatments. We found no difference in TSSM occurrence among the age cl asses of leaves, most likely due to the low TSSM populations on all leaves throughout the season. The number of TSSM in the early-release and middle-release treated plots of both old and young trifoliates never exceeded 5 motiles per trifoliate. The late treatment c ontained higher numbers of TSSM when the late application of N. californicus was released. As a result of low initial predator: prey ratio and the warm temperatures late in the season, N. californicus never achieved control in the late treatment plots (Greco 2005). The lack of treatment effect on yield may have been due to the late season infestation. Plants are more vul nerable to yield loss due to TS SM damage during the critical vegetative growth period early in the season than they are later in the growing season (Rhodes et al. 2006, Oatman and Voth 1972 and Sances et al 1981). Results by English-Loeb and Hestler (2004) suggest that June bearing varieties like Festival are very tolerant of TSSM damage in their first year of planting and do not show signs of vegetation or fruit loss. The 2006-2007 Season The second season (2006-2007) introduced seve ral new variables. Temperatures were milder than in the previous year, and the na tural vegetative cover that was left unmanaged between seasons provided abundant habitat for TSSM development. De spite the ecological challenges of the 2006-2007 season, N. californicus was able to achieve control of TSSM populations in all the treatmen ts throughout the season with the early and middle release treatments being significantly lower than the late treatment in the older leaves. We did not see treatment differences in the young leaves, which may be because of the low numbers of TSSM

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38 found on the younger leaves. Twospotted spider m ite aggregated on the older leaves and N. californicus dispersed to the areas of higher prey de nsity. The lack of treatment effect on the young leaves is consistent with our greenhouse findings of the tendency for N. californicus to demonstrate a density-dependent response. However, plots of a ll treatments contained higher numbers of TSSM throughout the 2006-2007 seas on than the 2005-2006 season. Results indicate that when released at the appropr iate ratio (1: 5 to 1: 10 predat or: prey), one ear ly release of N. californicus is able to maintain significant cont rol of TSSM throughout a growing season. However, if initial TSSM populations are too high to achieve an appropriat e ratio, as we had in the 2006-2007 season, a grower may need to apply a miticide to reduce TSSM numbers prior to an early-season release of N. californicus to maintain adequate seas on long control (Rhodes et al. 2006). Yield was substantially lower in the 20062007 season than in the 2005-2006 season. This may be due to a combination of factors includi ng a much higher TSSM population in the field early in the second season, severe bird and squirrel infestation and mid-season nutrient deficiency. No yield differences in either season could be direc tly attributed to TSSM damage. English-Loeb and Hestler (2004) found that redu ction in strawberry yield from TSSM varies with maturity of plant and timi ng of TSSM infestation. Oatman and Voth (1972) also found that TSSM presence was not directly correlated with yield loss. Ho wever, Walsh (2002) and Oatman et al. (1985) found that under certain conditions, potential yield reduction due to TSSM infestation can range from 10%-29%. The relatio nship between TSSM and berry varies widely which suggests that it is an ecologically dynami c process and is difficu lt to test under field conditions.

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39 Figure 3-1. Twospotted spider mite colony ma intained in the laboratory for greenhouse experiments. Figure 3-2. Transferring TSSM fr om the laboratory colony onto strawberry plants for the greenhouse trials.

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40 Figure 3-3. Mesh cages constr ucted to contain TSSM and N. californicus during the greenhouse trials.

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41 1 2 3 4 1 3 2 4 2 4 1 3 3 2 4 1 4 1 3 2 1 4 2 3 24 ft (7.3 m) 24 ft 36 ft (11 m) 36 ft 204 ft (62.2 m) 324 ft (98.8 m)N A 7.3 m 204 ft (62.2 m) 204 ft (62.2 m)24 ft(7.3 m) 36 ft (11 m) C M L E 2 C E M M E C L E L M C( 11 m)N L Rep 1Rep 2Rep 4 Rep 3B Figure 3-4. Maps of the layout of the treatments in the field A) Map of strawberry field 20052006 field season B) Map of strawb erry field 2006-2007 field season.

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42 0 10 20 30 40 50 60 Early MiddleLateControl TreatmentTotal No. of TSSM Motiles per leafletbc a cA 0 10 20 30 40 50 60 70 80 90 100 Day 0Day 5Day 10Day 15Day 20Day 25No. of TSSM Motiles per Leaflet Early Middle Late Control a b b c a b b b a b c bc a b b b a b b c B Figure 3-5. Twospotted spider mite motiles in gr eenhouse trials. A) Overall average number of TSSM motiles. B) Five day interval observ ations of TSSM motiles per leaflet for each treatment. Treatments with the same le tters are not significantly different from each other at P < 0.05, according to LSD test perf ormed on log-transformed data.

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43 0 5 10 15 20 25 30 35 40 45 50 Early MiddleLateControl TreatmentTotal No. of TSSM Eggs per Leafletc bb aA 0 10 20 30 40 50 60 70 80 90 100 Day 0Day 5Day 10Day 15Day 20Day 25No. of TSSM Eggs per Leaflet Early Middle Late Control a a a b a a b b a b c c a a b b b b b cB Figure 3-6. Twospotted spider mite eggs in the greenhouse trials A) Overall average number of TSSM eggs. B) Five day interval observati ons of TSSM eggs per leaflet for each treatment. Treatments with the same letter s are not significantly different from each other at P < 0.05, according to LSD test performed on log-transformed data.

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44 0 50 100 150 200EarlyMiddleLateControl TreatmentNo. of Motiles and Eggs per Trifoliate (Old) motiles eggs B B A A b b a a Figure 3-7. Average number of TSSM motiles and eggs per trifoliate on the old strawberry leaves 2005-2006 field season. Treatments with the same letters (A, B for motiles and a, b for eggs) are not significan tly different from each other at P < 0.05, according to LSD test preformed on log-transformed data. 0 50 100 150 200 250 300 350 400 450 500 8-Mar15-Mar22-Mar29-Mar5-Apr12-AprNo. of TSSM Motiles per Treatment Plot (Old) Early Middle Late Control a a b b Figure 3-8. Weekly average of TSSM motiles pe r plot on old leaves in 2005-2006 field season. Treatments with the same letters are not si gnificantly different from each other at P < 0.05, according to LSD test preformed on log-tr ansformed data. No letters indicate no significant differences on a given date.

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45 0 50 100 150 200EarlyMiddleLateControl TreatmentNo. Motiles and Eggs per Trifoliate (Young) motiles eggs b b a a B B A A Figure 3-9. Average number of TSSM motiles a nd eggs per trifoliate on the young strawberry leaves 2005-2006 field season. Treatments with the same letters (A, B for motiles and a, b for eggs) are not significan tly different from each other at P < 0.05, according to LSD test preformed on log-transformed data. 0 50 100 150 200 250 300 350 8-Mar15-Mar22-Mar29-Mar5-Apr12-AprNo. of TSSM Motiles per Treatment Plot (Young) Early Middle Late Control a a b b Figure 3-10. Weekly average of TSSM motile s per plot on young leaves in 2005-2006 field season. Treatments with the same letters are not significantly different from each other at P < 0.05, according to LSD test prefor med on log-transformed data. No letters indicate no significant differences on a given data.

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46 0 20 40 60 80 100 120 140 160 180 EarlyMiddleLateControl TreatmentNo.of TSSM Motiles and Eggs per Treatment Young Old Figure 3-11. Comparison of young and old leaves 2005-2006 season. No significant ( P < 0.05) differences between young and ol d leaves for any treatment. 0 100 200 300 400 500 600 700 800 900 EarlyMiddleLateControlTreatmentNo. of TSSM Motiles on Old and Young Trifolates Young Old a b b b b a a a Figure 3-12. Comparison of young and old leaves 2006-2007 season within each treatment. Letters represent difference be tween young and old leaves at P < 0.05.

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47 0 20 40 60 80 100 120 140 160 180 200 EarlyMiddleLateControl TreatmentNo. of Motiles and Eggs perTrifoliate (Old) Motiles Eggs C C B A bb b a Figure 3-13. Average number of TSSM motiles and eggs on old trifoliates during the 2006-2007 season. Treatments with the same letters (A, B, C for motiles, and a, b) are not significantly different from each other at P < 0.05, according to LSD test performed on log-transformed data.

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48 0 500 1000 1500 2000 250011 / 14 / 20 06 11 / 28 / 20 06 12 / 12 / 2 006 1 2/ 2 6/ 2 006 1/9/ 20 07 1/ 2 3/ 20 0 7 2/6/ 20 07 2/20/ 2 00 7 3 / 6/ 20 0 7DateAverage No. of TSSM per Treatment (Old) Early Middle Late Control Figure 3-14. Average weekly number of TSSM mo tiles on the old leaves in each treatment. Arrows indicate the release dates of N. californicus. 0 20 40 60 80 100 120 140 160 180 200 EarlyMiddleLateControl TreatmentNo. TSSM Motilesper Trifoliate (Young) motiles eggs ABB AAa a aa Figure 3-15. Average number of TSSM motile s and eggs on young trifoliates during the 20062007 field season.Treatments with the same letters (A, B for motiles and a for eggs) are not significantly different from each other at P < 0.05, according to LSD test performed on log-transformed data.

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49 0 500 1000 1500 2000 250011/14/20 0 6 1 1 /28/2006 1 2 /12 / 200 6 1 2/ 26 /2 00 6 1/9/2007 1/23/2007 2 /6 /2 00 7 2/2 0 /2 00 7 3/ 6 /20 0 7WeekAverage No. of TSSM Motiles (Young) Early Middle Late Control Figure 3-16 Average weekly number of TSSM mo tiles on the young leaves in each treatment. Arrows indicate the release dates of N. californicus Table 3-1. Strawberry yield for January, Februa ry, and March 2007, with total yield in kg/plot. Treatment January February March Total Yield Mean SE Early 12.7 1.4 10.1 1.8 10.4 1.4 33.0. 0.86 Middle 8.2 1.4 8.3 1.8 10.0 3.1 26.1 0.63 Late 11.8 10 9.8 2.3 8.2 3.1 29.7 1.08 Control 12.2 0.0 10.0 .4 10.0 2.7 32.2 0.72 No significant (P < 0.05) differences occurred between treatment means.

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50 CHAPTER 4 EFFECT OF Neoseiulus californicus RELEASES ON ARTHROP OD COMMUNITIES IN NORTH FLORIDA STRAWBERRY FIELDS Twospotted spider mite (TSSM), Tetranychus urticae Koch, is a key pest on strawberries ( Fragaria x ananassa Duchesne) in north Florida. High populations of TSSM can lead to a significant reduction in foliar and flower development, decreasing the quality and quantity of mature fruit (Rhodes et al. 2006). Because of its short life cycle and hi gh fecundity, TSSM can increase rapidly and is able to become highly resi stant to most pesticides in a short period of time (Williams 2000). Outbreaks have intensified over th e last few decades due to increased use of pesticides and modern cultural practices (H uffaker and McMurtry, 1969 and Escudero and Ferragut, 2005). As traditional me thods of chemical control are becoming less effective, and marketability due to chemical residue has become a social concern, growers are beginning to rely on natural enemies as an alternative to chemi cal management systems (Escudero and Ferragut 2005 and Rhodes et al. 2006). Approximately 40% of Floridas strawberry growers practice inundative biological control met hods (Mossler and Nesheim 2002). Field studies conducted between 1964-1980 in sout hern California identified ten insect species belonging to families Thripidae, Cecidomyiidae, Coccinellidae, Staphylinidae, Anthocoridae, Lygaediae, Chrysopidae, and Hemer obiidae and nine phytoseiid mite species to be natural enemies of TSSM (Oatman et al. 1985 ). Rondon et al. (2004) conducted laboratory studies with bigeyed bugs, Geocoris punctipes Say, minute pirate bugs, Orius insidiosus (Say ) and the pink spotted lady beetle, Coleomegilla maculata DeGeer, to assess their effectiveness as predators for TSSM and found that many of th ese insects prey on TSSM, but also show a preference for other phytophagous insects. Predatory mites in the phytoseiid family have been found to be the most effective predators in controlling TSSM and have been used successf ully in glasshouses since 1968 (Kozlova et al.

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51 2005). Two of the most commonly used phytoseiid mites are Phytoseiulus persimilis and Neoseiulus californicus (McMurtry and Croft 1997 and Cloyd et al. 2006). Oatman et al. (1972) and Kozlova et al. (2005) found that while P. persimilis is effective in controlling TSSM, as a Type I specialist predator, it is genus specific with regard to prey preference and tends to decimate TSSM populations altering the ecosy stem. Its introduction leads to significant intraspecific competition and a disruption of natural predation on TSSM. However, Colfer et al. (2004) found that releases of gene ralist species of phytoseiid mite s did not enhance or decrease the diversity or abundance of natural enemy popul ations. Studies have not been attempted to assess the effects of N. californicus on the diversity of native arthropods in the field. Indices to measure diversity in ecological systems have been available for many years (Magurran 2004). These are numerically expressed to indicate the relative abundance of taxa in an ecosystem. The most commonly used indices are richness ( s ), Shannon-Weaver index ( H ) (Shannon and Weaver 1949) and evenness index ( J ) (Pielou 1966). Richness is calculated by the sum of the taxa present in a system. The Sh annon index is the most often used index of diversity. This index is the negative sum of the proportional abundance of taxa multiplied by the natural logarithm of the proporti onal abundance of each taxon: s H= pi ln pi i=1 Where Pi = the proportional abundance of taxon. The Shannon Index weighs all taxa proportiona tely to their abundance in the sample therefore, reducing bias (Pow ers and McSorley 2000). Many a dditional indices have been developed (Magurran 2004) but the original Shannon index rema ins widely used, facilitating

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52 comparisons among various studies. The evenness index compares and standardizes the natural log of richness (s) and ranges from 0-1. J =H ln s Our hypothesis is that inundative releases of N. californicus to control TSSM in strawberries will not negatively impact other ke y natural enemies and arthropod diversity in the system. The objective of this study is to id entify and document common arthropods in the strawberry system and determine the impact of N. californicus releases on the presence and abundance of these taxa In addition, we will measure evenne ss and richness of organisms in the system. Materials and Methods An experiment was conducted at the Universi ty of Florida Plant Science Research and Education Unit, near Citra, FL (82.17W, 29.41 N). The experimental design was a randomized complete block with four replications and f our treatments. Treatments were assigned based on plant phenology and included: 1) an early release of N. californicus at four weeks after planting (WAP), 2) a mi ddle release of N. californicus at eight WAP, 3) a late release of N. californicus at 12 WAP and 4) a control (no releases). The site was prepared in beds with black polyethylene mulch (1.6mm) using a Kennco power bedder (Ruski n, FL). The soil was injected with methyl bromide: chloropicrin (80:20) at a rate of 326.4 kg/ha per acre two weeks prior to planting. Strawberries, variety Festival, were planted the first week of October on raised beds. There were 6 rows per plot, each bed contained double rows of transplants 0.35 m apart within row and 0.35m between row (24 plants per row). Strawberry plants were fertili zed, weeded and sprayed

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53 with fungicides using standard commercial practi ces (Brown 2003). No insecticides were applied to the plots. Preliminary study A preliminary study was conducted one year prior to the main study to determine appropriate sample size and to evalua te the indices. Data we re collected during the late season of the 2005-2006 field season at 12 WA P, to assess the season-long effect of N. californicus released in the early-season, mid-s eason, and late-season. One yellow sticky Pherocon AM Trap (YST) ( Trece, Inc., Adair, OK) constructed from a 28 cm X 23 cm yellow board with 59 one cm squares forming a grid on the board was hung on a garden stake 0.3 meters above the plants. Each trap was placed in the center row of each treatment plot. Traps were collected weekly and placed into Zipper Seal Storage Bags (American Value, Dolgencorp, Inc, Goodlettsville, TN) and brought back to the la boratory to be examined under a dissecting microscope. Three YSTs were randomly chosen from the samples and each of the 59 onecentimeter squares on each trap was examined to determine the number of unique families found on each square. The families that were observe d on each square of the YST were counted and compiled into a comprehensive list. The number of unique families represented on each square was recorded. The percentage of unique families found on each square was plotted for each square to create a cumulative frequency dist ribution. The optimal number of squares was determined from this distribution to be 28 square s. We used these data to create a sub-sampling for data analysis in the main study. Main study Based on the homogeneity of the prelim inary results, field observations, and previous research by Garc ia-Mari and Gonzalez-Samora (1999) indicating that N. californicus takes approximately two weeks to establish in a field we decided to conduct sampling at onemonth intervals two weeks after ea ch release date to obtain more complete data on the effect of

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54 N. californicus presence in the strawberry field throughout the season. Samples were taken in the 2006-2007 field season during the earl y-season (1-2 months after pl anting), middle-season (3 to 4 months after planting) and late-season (4-5 mont hs after planting). Individuals were identified to family or genus and counted and recorded using the same method as described in the preliminary sampling. Data were collected throug hout the season and compared to determine the effect of N. californicus releases on interspecific insects and mites in the field with respect to plant phenology. The treatments were categorized into treated and untreated in order to isolate the effect of the N. californicus releases. In order to avoid bias in the sampling techniques used to as sess the diversity of arthropods present in the field, we employed four sa mpling methods. These methods included 1) In situ (visual inspection) 2) foliar sampling 3) pitfall traps and 4) yellow sticky traps. In situ sampling Twenty-four strawberry plants from the center of the inner rows of each plot were visually inspected once weekly for two weeks during each sample period. The visual inspection consisted of a scan for 30-45 seconds per plant. This enabled us to sample the larger arthropods occurring in the field includi ng hymenopterans and some hemipterans and coleopterans. Foliar sampling Four young and four old trifoliate s were randomly taken from each treatment plot once weekly for two weeks between each of the three predatory releases and were placed into Zipper Seal Storage Bags and brought back to the laboratory. The leaflets were visually inspected under the dissecting binocul ar microscope for leaf dwelling and minute arthropods such as the thys anopterans and hemipterans. Pitfall traps. Traps were constructed of a white polypropylene deli containers 14 cm deep and 10.5 cm in diameter (Fabri-Kal corp. Kalam azoo, MI) filled with two cm of 10% dish soap

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55 and water solution. The traps were placed in the soil and under the black plastic mulch in one of the two center rows of each treatme nt plot to capture cursorial so il arthropods and soil dwellers, such as collembola, arachnids, coleopterans and some hymenopter ans (Southwood 1966). The traps were left in the field for 48 hours each week for a 2-week period between each of the three predatory releases. Yellow sticky traps Traps were placed in one of the tw o center rows of each plot at foliar height, approximately 30 cm above ground to ca pture hymenopteran, dipteran, and other winged arthropods. The YST were left in the field for 48 hours each week for a two-week period among each of the three predatory releases. The 28 squa res (47% of the trap area) were observed for analysis. Statistical analysis Families of arthropods with th e highest relative abundance am ong treatments were compared with an analysis of variance (ANOVA) and an LSD means separation to determine differences between treatments (SAS Institutes, 2002). Fam ilies that were present in numbers too low to conduct meaningful statistical analysis were r ecorded in a species list for each treatment, but were included in diversity cal culations (Tables 4-1 to 4-4). Shannon diversity index, evenness, and richness were calculated for each plot and for each sampling period. The results were subjected to an ANOVA and means were separated with LSD ( =0.05) to determine significant diffe rences between the treatments. Results Preliminary Study Twenty-eight 1-cm squares included 90% of the arthropod families found on the YST (Figure 4-1). Therefore, 28 square s could be analyzed to assess the diversity

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56 on the YSTs.There were no signifi cant differences in level of diversity between any of the treatments. All measures, Shannon ( F = 0.49; df = 3, 12; P = 0.7, evenness ( F = 1.31; df = 3,12; P = 0.3), and richness ( F = 1.05; df = 3, 12; P = 0.4) indicated that the families found in each treatment were consistent throughout the trial period and among treatments. Main Study. In the early season (December 5-16) we compared the plots treated with N. californicus and untreated plots (controls). On the YST, we recorded insects from seven families: Aphididae, Cecidomyiidae, Dolichopodidae, Sciari dae, Phoridae, Thripidae, and Chalcidodoidea. However, no significant differences were found between the treated a nd untreated plots in five of the seven families (Figure 4-2), Aphididae ( F = 0.07; df = 1, 30; P = 0.8), Cecidomyiidae ( F = 0.24; df = 1, 30; P = 0.6), Dolichopodidae ( F = 3.21; df = 1, 30; P = 0.9), Sciaridae ( F = 0.07; df = 1, 30; P = 0.8), Muscidae ( F = 0.07; df = 1, 30; P = 0.8) and Phoridae ( F = 0.22; d f= 1, 30; P = 0.6). Numbers of Thripidae ( F = 4.81; df = 1, 30; P = 0.04) and Chalcidodoidea ( F = 8.44; df = 1, 30; P = 0.01), were higher in th e plots treated with N. californicus than those that were untreated. In the pitfall traps, no significant differences occurred between the treated and untreated plots for the most abundant taxa, which included Collembola ( F = 0.0; df = 1, 30; P = 1), Fomicidae ( F = 0.95; df = 1, 30; P = 0.3), Aphididae ( F = 0.29; df = 1, 30; P = 0.6) and Cecidomyiidae ( F = 2.81; df = 1, 30; P = 0.1) (Figure 4-3). Data co llected from YST indicate that the Shannon index ( F = 0.24; df = 1, 14; P = 0.6), evenness ( F = 0.0; df = 1, 14; P = 1.0), and richness ( F = 1.52; df = 1, 14; P = 0.2) were not signifi cantly different ( P = 0.05) between treatments (Table 4-5). Similarly, data collected from the pitfall traps also indicated no differences in Shannon index ( F = 0.0; df = 1, 14; P = 1.0), evenness ( F = 0.20; df = 1, 14; P = 0.7), and richness ( F = 0.01; df = 1, 14; P = 0.9) (Table 4-6).

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57 During the mid-season (January 5-16) we recorded no significant ( P = 0.05) differences among plot treatments on the YST for the most abundant families: Chalcidodoidea ( F = 0.41; df = 2,29; P = 0.7), Muscidae ( F = 2.69; df = 2, 29; P = 0.1), Aphididae ( F = 0.15; df = 2, 29; P = 0.9), Sciaridae ( F = 0.73; df = 2, 29; P = 0.5), Thripidae ( F = 0.78, df = 2, 29, P = 0.5), Phoridae ( F = 0.33; df = 2, 29; P = 0.7) and Cecidomyiidae( F = 0.38; df = 2, 29; P = 0.7) (Figure 4-4). In the pitfall traps no significant differences among th e treatment plots occurred for Collembola, ( F = 1.26; df = 2, 29; P = 0.3,) Lygeaidae ( Pachybrachyus spp.), ( F = 1.06; df = 2, 29; P = 0.4) or spiders ( F = 0.46; df = 2, 29; P = 0.6). Numbers of Formicidae were greater ( F = 3.39; df = 2, 29; P = 0.05) in plots trea ted early with N. californicus than in untreated plots (Figure 4-5). On the YSTs, the Shannon index ( F = 1.68; df = 2, 13; P = 0.2), evenness ( F = 0.10; df = 2, 13; P = 9), and richness ( F = 2.28; df = 2, 13; P = 0.1) showed no significant ( P = 0.05) difference among the early, middle releases, and th e untreated plots (Table 4-7). Likewise, for the pitfall traps, the Shannon index ( F = 2.28; df = 2, 13; P = 0.1), evenness ( F = 0.19; df = 2, 13; P = 0.8) and richness ( F = 0.68; df = 2, 13; p = 0.5) were not-significantly ( P = 0.05) different among treatments (Table 4-8). On YSTs measured late in the season (Feb ruary 2-12), no signifi cant differences among treatments occurred in the fo llowing families: Chalcidodoidea (F = 0.31; df = 3, 12; P = 0.8), Sciaridae ( F = 0.90; df = 3, 12; P = 0.5), Muscidae ( F = 0.24; df = 3, 12; P = 0.9), Cecidomyiidae, ( F = 1.95; df = 3, 12; P = 0.2), Dolichopodidae ( F = 1.22, df = 3, 12; P = 0.3), and Cicadellidae ( F = 2.02, df = 3, 12, P = 0.2. (Figure 4-6). In the p itfall traps, there were no significant differences among treatments for Collembola, ( F = 0.35, df = 3, 12, P = 0.8), Lygeaidae ( Pachybrachyus spp.) ( F = 0.52, df = 3, 12, P = 0.7), spiders ( F = 1.33, df = 3, 12, P = 0.3), or Sciaridae ( F = 0.04, df = 3, 12, P = 0.99). (Figure 4-7).

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58 The diversity indices for the YST and the pitf all traps showed no significant differences among treatments. No differences ( P < 0.05) among treatments were demonstrated for YST in the Shannon index ( F = 2.38, df = 2, 13, P = 0.1), evenness ( F = 1.51, df = 2, 13, P = 0.3), richness ( F = 2.34, df = 2, 13, P = 0.1) (Table 4-9) nor for pitfa ll traps in the Shannon index ( F = 0.56, df = 2, 13, P = 0.7), evenness ( F = 1.09, df = 2, 13, P = 0.4) and richness ( F = 0.19, df = 2, 13, P = 0.9) (Table 4-10). Overall, the visual and foliar samples did not produce sufficient numbers of arthropods to conduct robust statistical analysis. However, th ey should not be dismissed since the foliar and visual counts revealed the pres ence of phenological trends and im portant natural predators of TSSM. Visual inspection during the mi d-season revealed high numbers of Pachybrachius spp. and a dramatic decline in aphid population di rectly following an increase in syrphid fly abundance (Table 4-3). Foliar sampling indicated that as the season prog ressed the abundance of Coccinellids increased in all treatment plots (p ersonal observation), as did Sixspotted thrips ( Scolothrips sexmaculats ) and Geocorid bugs ( Geocoridae spp.) Late in the season, numbers of taxa decreased, and an increase in Sc iaridae was observed (Table 4-4). Discussion As hypothesized, the release of N. californicus did not have a statistic ally significant effect on arthropod diversity in the strawberry system. The major insect families, which included Thripidae, Cecidomyiidae, Coccinellidae, Staphylin idae, and Lygaediae, as cited by Oatman et al. (1985) and Rondon et al. (2004), were observed. We did observe a period in the early season, which was unseasonably warm, when thrips ( Frankliniella spp.) and Chalcidoidea were high in all plots and significantly higher in the treated plots compared with the untreated plots. Adult thrips migrate into flowering strawbe rry crops during warm humid periods of the growing season. Neoseiulus californicus is a known predator of thrips in some crops, but N.

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59 californicus cannot access them once they ta ke shelter within the styles of the strawberry flowers (Cross et al, 2001). However, N. californicus may consume natural enemies, allowing thrips to flourish and indirectly increasi ng the number of thrips in th e system (Cross et al. 2001). Increased levels of the superfamily Chalcidoidea, all of which are parasitoids of thrips, were found in significantly higher numbers in the plot s with high numbers of thrips indicating a density dependent correlation. High numbers of aphids were also found in all treatments during the early-season. Many species of aphids are known to be pests of stra wberry early in the season when the climate is warm, but populations decrease rapidly as natura l predators establish in the system (Jones 1976). Our observations of decreasing numbers of aphi ds in conjunction with increased syrphid fly populations are consistent with studies conducted in north Wales showing that sy rphid flies are effective predators of aphids a nd can cause considerable reducti on in aphid numbers (Cross et al. 2001). Foliar sampling indicated that as the seas on progressed the abundance of sixspotted thrips ( Scolothrips sexmaculats ) and Geocoridae spp. increased in all trea tment plots. These findings are consistent with previous re search by Jones (1976) indicating th at predation tends to increase gradually throughout the season. At the time of the late-season, sampling, arthropod numbers had declined in all treatments and Sciaridae dominat ed in all plots. During the mid to late-season considerable damage to the fruits from bird and squirrel feeding was observed which may have been a factor in the increase of Sciaridae. Scia ridae have been shown to be attracted to damaged plant tissue as sources of food and habitat (Jones 1976). Although we found very few statistically signifi cant differences betw een treatments during the early sampling periods, we recorded differe nces in the arthropod assemblage throughout the season among all treatments. The high level of ri chness and insect diversity in the strawberry

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60 system may be a key factor that reduces the effect of N. californicus releases on the structure of the strawberry system (Jones 1976, Powers and Mc Sorley 2000). One of th e natural services provided by ecosystems is the natu ral control of pest and invasi ve species (Klein et al. 2006). The majority of arthropods in the strawberry sy stem are generalist feeders. Therefore, abundance of alternate food sources may mitigate disruption by an introduced predator (Cross et al. 2001). The dynamics of the arthropod assemblage seem to be more highly related to plant phenology and ambient weather than to interspecific competition.

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61Table4-1. Cumulative number of each taxa found in each treatm ent in the three sampling periods in yellow sticky traps. December January February E M L C E M L C E M L C Acanalonidae 2 1 2 1 Acanalonidae 4133 Aleyrodidae 4 Aleyrodidae 2 16 26 14 Aleyrodidae 21731 Aphididae 6613 Aphididae 383 643 579 539 Aphididae 1210511 Cecidomyiidae 4681 Bethylidae 1 Bethylidae 2 Chalcidoidae 33263331 Bibionidae 5 5 Bibionidae 311 Chrysomella 222 Cecidomyiidae 11 10 6 9 Br aconidae 2135 Cicadellidae 7217 Chalcidoidae 34 59 83 91 Cecidomyiidae 108144 Coccinella 316 Chrysomelidae 1 Chalcidoidae 61667853 Dolichopodidae 1 0734 Cicadellidae 2 11 17 5 Chrysomelidae 111 Drosophilidae 1 Coccinellidae 1 (Alticinae spp) Ichneumonoidae 3844 Cucujidae 1 11 Cicadellidae 3342 Ichneumonoidea Dolichopodidae 7 17 4 3 Coccinellidae 432 (Braconidae spp) 1 Drosophilidae 3 Dolichopodidae 2445 Lepidoperera spp. 1 Ichneumonidae 4 4 Drosophilid ae 4121 Muscidae 17141419 Lepidoptera 1 1 1 Ichneumonidae 43 Nitulidae 212 Muscidae 8 7 9 30 Leiodidae 111 Lygaeidae Nitulidae 2 Lepidoptera 1 (Pachybrachius spp) 1452 Phloeothripidae 3 2 4 3 Lygaeidae Phoridae 2612 Phoridae 3 16 7 7 (Pachybrachius spp) 361 Psychodidae 21 Platygatroidae 1 Muscidae 23131515 Sciaridae 52489448 Psychodidae 1 3 10 Nitulidae 11 Araneida 1113 Sciaridae 5 5 50 10 Phloeothripidae 1 Staphylinidae 2111 Staphylinidae 2 Phoridae 1014409 Syrphidae 3211 Thripidae 39 39 23 Psychodidae 521 Tachinidae 2442 Sciaridae 2317248 Thripidae 2852 Staphylinidae 21 Syrphidae 11 Tachinidae 5823 Thripidae 1617910 E = early treatment, M = middle treatment L = late treatment and C = control.

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62Table 4-2. Cumulative number of each taxa found in each treatment in the three sampling periods of the pitfall traps. December January February E M L C E M L C E M L C Chrysomelidae Aphididae 11265 Aphididae 111 (Alticinae spp.) 1 1 Cecidomyiidae 462 Ichneumonoidea Aphididae 19 9 5 9 Chalcidiodea 121 (braconidae) 1 Apoidea 1 1 Cicadelidae 1 Cecidomyiidae 1 Bibionidae 2 Collembola 508513265 Chalcidoidae 11 Cecidomyiidae 8 7 7 17 Gryllidae 1 Chrysomellidae 1 Chalcidodea 4 3 2 Cucjidae 11 Collembola 10241339 Chironomidae 2 Drosophilid ae 21 Formicidae 11112 Chrysomelidae 1 Formicidae 44922 Lygaeidae 113 Cicadellidae 1 1 Lygaeidae Lygaeidae(immature)35 Coccinelidae 1 (Pachybrachius spp.) 18214729 Muscidae 2 Collembola 41 21 23 31 Miridae 1 Scariaridae 971415 Cucujidae 1 Muscidae 1 Araneida 311 Drosophilidea 2 Nitulidae 1 Staphalenidae 12 Eliteridae 1 Phoridae 1 Thripidae 1 Formicidae 35 26 6 42 Scariaridae 4212 Vespidae 1 Ichnueumonidae 1 Scollidae 1 Lepidoptera 2 Araneida 4322 Miridae 1 Staphylinidae 1 Muscidae 2 2 Tettigoniidae 1 Mutillidae 1 Thripidae 2224 Nematode 2 Phloeothripidae 1 1 Phoridae 2 3 2 2 Scariaridae 1 1 2 Araneida 1 2 5 2 Staphylinidae 3 1 1 1 Tettigoniidae 2 Thripidae 1 5 3 1 E = early treatment, M = middle treatment, L = late; C = control.

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63 Table 4-3. Cumulative numbers of each taxa in the three visual sampling periods December January February E M L C E M L C E M L C Tettigoniidae 3 1 33 4 7 24 Apoidea 6 9 53 0 1 32 Syrphidae 3 3 14 161368 2 1 1 Araneida 11 2184 2 Lepidoptera 1 1 11 1 Muscidae 1 2 22 1 12 Chrysomelidae 1 1 1 Coccinelidae 1 12 1 Lygaeidae (Tristicolor spp) 1 (pachybrachius spp) 82612 1 1 Sciaridae 52 28 3914 Cicadellidae 1 E = early treatment, M = middle treatment, L = late treatment and C = control. Table 4-4. Cumulative numbers of each taxa in the three foliar sampling periods December January February E M L C E M L C E M L C S.sexmaculatus 1 2 2 631010 413 2 Aphididae 43 64 28 40 144 11 Aleyrodidae 29 22 22 2 2222 3 Thripidae 7 2 1 1 1441414 3 3 Chalcidoidae 1 Lepidoptera 1 662 9 Syrphidae (eggs) 9899 4510 15 Lygaeidae (Geocoridae spp) 3 9 E= early treatment, M=middle treatment, L=late treatment and C=control.

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64 Figure 4-1. Cumulative percent of families found on yellow sticky trap 1-cm squares. 0 10 20 30 40 50 60 70 80 90 100A ph i d ida e T hr i p idae C h alcid oi d ae Cec i do myiidae Dolic o pod i dae Sciaridae M u scidaeTaxonNo. of Individuals/YST Early Treatment Untreated** Figure 4-2.The most abundant families found on ear ly-season yellow sticky traps between the treated and untreated plots. i ndicates significant differences ( P < 0.05) between treated and untreated.

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65 0 1 2 3 4 5 6 7 8 9Col l embola For m icid ae Ap h ididae CecidomyiidaeTaxonNo. of Individuals per Pitfall Trap Early Treatment Untreated Figure 4-3. The most abundant fam ilies found in the early-season pitf all traps in the treated and untreated plots. No significant ( P < 0.05) differences were found among treatments. Table 4-5. Mean values of dive rsity indices in plots in earl y-season yellow sticky traps. Treatment Shannon Richness Evenness Mean SE Early 1.06.50 11.5.0 0.44.05 Untreated 1.13.07 13.3.0 0.44.03 No significant ( P < 0.05) differences with treatment. Table 4-6. Mean value of diversity indices in plots in early-season pitfall traps Treatment Shannon Richness Evenness Mean SE Early 1.7.15 8.0.40 0.8.06 Untreated 1.7.06 7.9.65 0.8.04 No significant ( P < 0.05) differences with treatment.

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66 0 5 10 15 20C h al ci doidea Muscidae Ap h ididae Sciarid a e T hripidae P h orid ae C e ci do m yi i da eTaxonNo. of Individuals/ YST Early Middle Untreated Figure 4-4. The most abundant families found in the mid-season yellow sticky traps among the early, middle and untreated plots. No significant ( P < 0.05) differences among treatments. 0 2 4 6 8 10 12 14 16 CollembolaLygaeidaeArachnidaeFormicidae TaxonNo. of Individuals/ Pitfall Trap Early Middle Untreated* Figure 4-5. The most abundant ta xa found in the mid-season pitf all traps between the early, middle, and untreated plots. indicates significantly ( P < 0.05) higher numbers of Formicidae in the early-release treated plots than the untreated plots.

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67 Table 4-7. Mean values of dive rsity indices in plots in mi d-season yellow sticky traps. Treatment Shannon Richness Evenness Mean SE Early 2.2.10 15.5.3 0.8.02 Middle 2.2.03 14.8.9 0.8.02 Untreated 2.1.05 13.3.5 0.8.02 No significant ( P < 0.05) differences with treatment. Table 4-8. Mean values of di versity indices in plots in mid-season pitfall traps. Treatment Shannon Richness Evenness Mean SE Early 1.5.20 8.0.2 0.7.05 Middle 1.3.12 7.5.3 0.7.08 Untreated 1.3.09 6.6.5 0.7.04 No significant ( P < 0.05) differences with treatment. 0 5 10 15 20 25 30 35 40C h al ci doidea Sciarid ae Muscidae C e ci do m yi i da e Dolicopodidae C i c ade ll i d aeTaxonNo. of Individuals/YST Early Middle Late Control Figure 4-6. The most abundant families found in the late-season yellow sticky traps in early, middle, late, and control plots. No significant ( P < 0.05) difference among treatments.

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68 0 2 4 6 8 10 12 14 16 CollembolaSciaridaeLygaeidaeArachnidae TaxonNo. of Individuals/Pitfall Trap Early Middle Late Control Figure 4-7. The most abundant fam ilies found in the late-season pitfa ll traps in the early, middle, late, and control plots. No significant ( P < 0.05) difference among treatments. Table 4-9. Mean value of divers ity indices in plots in late -season yellow sticky traps. Treatment Shannon Richness Evenness Mean SE Early 1.95.10 0.75.03 12.8.69 Middle 2.16.12 0.85.06 12.8.48 Late 1.68.20 0.69.10 11.3.25 Control 1.83.73 0.77.91 11.0.10 No significant ( P < 0.05) differences with treatment. Table 4-10. Mean value of diversity indices in plots in late-season pitfall traps. Treatment Shannon Richness Evenness Mean SE Early 1.3.10 0.6.03 9.3.85 Middle 1.3.02 0.6.01 8.8.30 Late 1.5.90 0.7.90 9.0.10 Control 1.4.13 0.6.10 8.5.50 No significant ( P < 0.05) differences with treatment.

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69 CHAPTER 5 HYPERSPECTRAL IMAGERY DETECTION FOR TWOSPOTTED SPIDER MITE DAMAGE IN STRAWBERRIES Twospotted spider mite (TSSM) Tetranychus urticae Koch is one of the most economically important pe sts in strawberries ( Fragaria spp.) High infestations of TSSM have shown to cause leaf chlorosis, cessation or stimulation of plan t growth, and reduction in yield (Oatman et al. 1985, Cloyd et al. 2006, Wynam et al. 1979, Walsh et al 2002, Stonneveld et al. 1996, Huffakker et al. 1969, Sanches et al.1979). As TSSM feed on the underside of the leaf, they pierce the chloroplast containing palis ade and spongy parenchyma cells in the mesophyll layer at a rate of 18-22 cells/minute (Jepps on et al. 1975, Sanches et al 1979). Chlorotic symptoms appear when TSSM consume the chlor oplasts, which contain ch lorophyll, an essential pigment that absorbs solar radiation for phot osynthesis (Smith and Smith 2003, Kiekliewicz 1985). A decrease in radiant energy use (REU) due to the consumption of the chloroplasts eventually leads to reduction in vegetative gr owth and yield (Reddall et al. 2004, Sances et al. 1981, Kielkiewicz 1985). The chloroplasts are organelles within the mesophyll cells that contain pigments and are the primary catalyst for the light reaction of photosynthesis (Meyer et al. 1973, Smith and Smith, 2003). Each family of pigments (carotenoids, ph ycobilins, and chlorophylls) absorb strongly in specific wavelengths (m) of the ra diant light spectrum. Chlorophyll a and b are the predominant pigments located in the chloroplas ts. They produce the green reflectance of healthy vegetation and absorb blue (0.43 m and 0.45 m) and red (0.66 m and 0.65 m) wavelengths (Meyer et al. 1973). The light abso rbed and stored by the pigments in the chloroplasts is the principal source of energy for photosynthesis. Tw ospotted spider mite penetration and salivary injection into these cells dissolves and digests the structures and inhibi ts the function of the chloroplasts (Kielkiewicz 1985). Cellular injury di srupts the ability for thes e pigments to absorb

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70 the specific wavelengths in the radiant energy sp ectrum, making the leaves appear discolored and chlorotic (Meyer 1973, Jensen 2005). The resulting spectral variati on in the visual wavelengths is one of the most consistent indi cators of vegetation heal th. Leaf stress is evid ent in variations of the 0.55-0.64 m and ~0.7 m wavelengths (Jensen 2005). Twospotted spider mite damage also affects th e ability of a plant to absorb and reflect near infrared (NIR) wavebands. Plants have evol ved to reflect highly in the infrared wavebands (0.7-1.1 m) to protect the leaf ti ssue from absorbing too much radi ant heat that may lead to the denaturing of essential proteins. The structure of the mesophyll layer regulates the reflectance of NIR energy by the internal scatte ring at the cell wall-air interf ace (Jensen 2005). Variations in the reflectance in the region be tween the red and NIR, known as the red edge (~ 0.7 m), indicates plant stress that is often due to dehydr ation and cellular damage (Jensen 2005, Lillisand at al. 2003). The correlation between TSSM damage and reduc ed photosynthetic function of strawberry plants has been documented extensively (Re ddall et al. 2004, Iatrou et al. 2004, Kielkiewicz 1985, Sanches et al. 1979, Sanches et al. 1981). However, the effect of physiological inhibitions on spectral response of strawberry leaves has not been investigated. Studies by Fitzgerald (2004) and Landeros et al. (2004) have demonstrated th at it is possible to detect spectral changes regarding the presence/absence of pest damage in agri cultural fields in larger field crops like cotton. Our goal is to identify specific regions of the reflectance spectrum that are affected by TSSM on strawberry leaves and develop a rela tionship between quantifiable levels of TSSM infestation and spectral foliar response. This st udy will provide a foundation for the development of models to better understand TSSM interactions with strawberry plants. The information can be

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71 integrated with other technologies and tactics into a set of tools known as geographic information technology (GIT), and used to identify and mon itor spectral data from a field that can be analyzed to create maps of vegetative conditi on in relation to pest damage (Brewster 1999, Dayang and Kamaruzaman 1999). Geographic inform ation technology is associated with sitespecific Precision Insect Pest Management (P IPM) programs. Early id entification of TSSM distribution before damage is vi sible in the field is the initial step to develop a management program that will have the potential to re duce economic and ecological costs and increase production in strawberries (Dayang and Kamaruzaman 1999). Materials and Methods Field Plots Our experimental plots were located at the Un iversity of Florida Plant Science Research and Education Unit, near Citra, FL (82.17W, 29.41 N). There were 16 plots of varying levels of TSSM infestation. Each plot was 7.3 m with 11 m buffer between each plot. Within each plot there were 6 rows of strawberries. Each row had a double row of transplants 0.35 m apart within row and 0.35m between row. Strawberries were plan ted the first week of October, on raised beds over black plastic mulch and were fertilized, weed ed and sprayed with fungicides using standard commercial practices (Brown 2003). Sampling Twenty mature leaflets of TSSM-infested strawberry plan ts were taken randomly one time per week from each of the 16 plots. We collected samples for four weeks between December 2006 and January 2007. Leaflets were taken back to the Small Fruit and Vegetable IPM Laboratory at the University of Florida, Gainesville, FL and analyzed under a dissecting microscope to determine the number of TSSM per leaflet. Each individual leaflet was then put into a Zipper Seal Storage Bag (American Va lue, Dolgencorp, Inc, Goodlettsville, TN) and

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72 labeled with the approximate nu mber of mites found on the leafle t. The leaflets were then scanned with a Fieldspec 3 spectroradiometer (A nalytic Spectral Devices, Inc., Boulder, CO) at the Soil Sciences Laboratory at the University of Florida. The samples were scanned within two hours after collection to reduce de hydration and foliar damage. Spectral Scanning During the scanning process, the spectrometer was re-calibrated with a white reference every 10 minutes to ensure an accurate spectral reading. Two separate areas of 3.2 cm were scanned on the adaxial (top) side of each leafle t with a spectral lens that was 2 cm diameter. Each of the selected areas was rotated 90 a nd rescanned to increase spectral accuracy. The spectral signature of each wave band between 360 nm and 2480 nm from each reading was downloaded to a CSV (Comma Separated Values) file. The spectral response was re-sampled, and every 10 nm were averaged to condens e the 2000 wavebands into 200 wavebands to facilitate statistical analysis. The data were th en derivative transformed, using first derivative transformation with second order smoothing to fi nalize the data (Stats oft, Inc. 2005). This procedure facilitated the detecti on of variations in the slope of the spec tral curves between wavelengths. The data were exported into an Ex cel spreadsheet displaying the reflectance value of each sample in each of the 200 wavebands. Data Analysis Raw data were subjected to a linear regr ession analysis to assess the correlation and prediction accuracy of mite numb ers with respect to reflectance values. The results were crossvalidated by separating the data in to groups of test data and valid ation data. The test data were subjected to the regression analysis and then the validation data were applied to the test model to assess the strength of the model (SAS Institute, Inc. 2002). The data were then subjected to a Principal Component Analysis (PCA) to conde nse the data using SPSS software (SPSS Inc.

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73 2004). Due to high variability in the data reveal ed by the PCA, we chose to focus on regions of the spectrum that are directly related with TSSM damage rather than utilizing the entire radiant spectrum. Determining Categories of TSSM Infestation To better describe the correlation between mite density and leaflet reflectance in a practic al representation for growers, we divided the leaves into three categories: no mites (0 mites) ; low/moderate infestation (10-60 mites/leaflet); and high infestation ( 70 mites/leaflet). A Linear Discrimi nate Analysis (LDA) of the first 5 principal components was performed. Discrimina te Analysis is a multivariate statistical technique that is commonly used to build predictive models of group discrimination based on observed predictor variables and classify each observation into one of these groups: The objectives of LDA are to investigate di fferences between groups and create categories maximizing the variance between groups and mi nimizing the variance within groups (McCune and Grace 2004). Data were then cross-vali dated using the PROC DISCIM CROSSVALIDATE function in the SAS statistical program for the thr ee categories to determine if the variation of the spectral differences will significantly discriminate among the levels of mite infestation (SAS Institute, 2002). The data were first subjected to a one-way ANOVA (SPSS Inc. 2004) to reveal regions of the spectrum with the greatest statistical differences ( P > 0.0000001). Discriminate Analysis was then conducted on the average of near infrared (NIR) wavelengths (700nm-1000nm), and in the dik= a+b1kXi1+b2kXi2 bknXin+ei dik is the value of the k th discriminate function for the i th case a constant bik is the value of the i th coefficient of the k th function xi1 is the value of the i th case of the j th predictor ei is an error term

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74 green wavelengths (560nm-580nm). Finally, to test the applicati on of the spectral analysis to commercially available satellite systems, the LDA was performed on NIR and green wavelengths at the spectral reso lution of SPOT 5 (SPOT Image Corporation, Chantilly, VA) and Quickbird (GeoVAR, Katy, Texas) satellites. The results of the LDA were evaluated in an error matrix to assess the level of accuracy (Jensen 2005). We used four measurements of accuracy to determine the reliability and appropriateness our classification: 1) total number of samples th at were correctly categorized divided by the total number of remaining samples we re calculated to test how accurately the data were classified (producers accur acy) 2) the total number of samp les from a category that were classified in the appropriate category was calculate d as a measure of reliability (users accuracy) 3) the overall accuracy was determined by dividing the total number of correctly categorized samples by the total number of samples and 4) kappa analysis (K) was calculated, which is a measure of agreement or accuracy between predic ted classification data and reference data. A Kappa value of 80% or higher represents high le vel of accuracy, kappa values between 40% and 80% represent moderate accuracy and a value of less than 40% represents poor accuracy (Jensen 2005). GIS Integration To obtain geographic information, we us ed a Trimble XRS GPS unit (Sunnyvale, CA) with Trimble TerraSync software (Sunnyvale, CA). We recorded the subplots and field border as area features by averaging the vertices of each corner of the plots us ing real time differential corrections to improve position accuracy. Nine samp le points from each plot were recorded as point features. The features co llected with the GPS unit were transferred to Pathfinder Office 3.10 software (Trimble, Sunnyvale, CA) and differenti ally corrected in the Utilities/Differential Correction window using the Differential Corr ection Wizard to subject the data further

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75 geographic correction and increa se accuracy. The Palatka base station (81.64W, 29.65N) was chosen as the base provider to use for refere nce position. The map was c onverted into an ESRI shapefile through the util ities/export dialog box >> new set up >> ESRI shapefile. The GPS map was then imported into ArcGIS 9.1 (ESRI Redw oods, CA). The map was re-projected into NAD_1927_UTM_zone 17 through ArcToolbox using the data management toolbox>>projection tool. To obtain spectral information, we collected leaflets taken from the sample points previously marked with the GPS map. We transported the leaflets back to the laboratory in Zipper Seal Storage Bags and counted the numbe r of TSSM on each leaflet using a dissecting microscope. Using a handheld Fieldspecspectrom eter (Analytical Spectral Devices, Boulder, CO) we recorded the reflectance values of each leaflet. The mite number and reflectance values of each sample leaflet were stored as Microsoft Excel files. The spread sheet was imported into an Access file and then imported into ArcMap (ESRI, Redwoods, CA) as a layer using the add layer dialogue box. These data contained field sample point position, mite number and reflectance value. The attribute table of the GPS sample points and the reflectance samples were joined through the layer prop erties dialogue box. The plots were unioned through the analysis>> overlay>> union function in ArcToolbox. The data were then converted to raster through the conve rsion tools>> to raster >> feature to raster function using ArcToolbox. In the spatial analyst dropdown box in ArcMap, we used interpolate to raster>> inverse distance weighted (IDW) to create an interpolat ed image of the mite numbers as they are distributed on a field level. We then used the ra ster calculator in the sp atial analyst dropdown to build the expression (Setnull([uni on]=1, [union]) to set a mask, excluding all the data except

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76 those in the plots. This defined the map extent to only those areas of interest within the plot. Finally, we used the raster multiplication function in raster calculator to build the expression ([setnull_plots]+1)*rast5, which overlaid the plot area with the interpolated raster layer. The result was an image displaying the mite di stribution only in the plots (Figure 5-1). Results Spectral Analysis The spectral signature of the samples displayed highest variability at the red edge (area between the red and NIR bands) and the green visible region (520nm-580nm ). There was a close relationship between mite infestation and NI R reflectance (Figure 5-2). The TSSM numbers correlated with reflectance values showed a st rong relationship between the variables. The validation data of mite numbers predicte d by wavelength had an R = 0.7469 between the expected and observed responses (Figure 5-3) The principal component analysis (PCA) condensed the data into 5 principal factors en compassing 89.8% of the va riation in the data (Figure 5-4). Accuracy of Categories of Mite Infestation The NIR bands (700nm-1000nm) resulted in 90% of the total samples cl assified correctly with a 90% reliability score for the Hi cat egory. The Lo/Modcategory had 94% classified correctly with 92.5% reliability. The No categ ory had 87.5% classified correctly with 87.5% reliability. The overall accuracy was 92.5% a nd K = 84.9% The green bands (560nm-580nm) resulted in 95% correct classification in the H i category with 79.1% reliability. The Lo/Mod category had 90.39% correct classification with 98% reliability. The No category had 100% correct classification with 100% reliabilit y. The overall accuracy was 92.5% and K = 92.4% (Table 5-1).

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77 The green and NIR bands in commercial sa tellite platforms, SPOT 5, which has a 500 nm-590 nm green band width and 780 nm 890 nm NIR band width and Quickbird which has a green band width of 520 nm 600 nm and NIR ba nd width of 760 nm 900 nm were compared. The green band produced an overall accuracy of 52% and 56%, respectively. The NIR for both platforms had 96% accuracy (Table 5-2). The results of the accuracy matrix indicate that the three TSSM cl assifications selected in this study are highly accurate in discriminating spectra l response in strawberries. The green bands preformed the best at high resolution and the NIR was highly reliable with lower resolution sensors. Spectral Map The joined raster and GPS layer created a visu al representation of the spatial distribution of TSSM damage in the field plots. The model indi cates that spectral pest detection is possible at a field level. The data suggest that mite di stribution could be identified early through the reflectance correlation and precise preventative management could be preformed. Figure 5-4 shows the predicted distribution of TSSM within our experimental field. In a GIS, precise areas can be identified by pointing to a specific area of the map and th e geographic coordinates of that area will be displayed. Discussion Analysis There is a strong correlation be tween specific levels of mite infestation on strawberry leaves and alteration in leaf reflectance. Howeve r, the PCA analysis revealed that strawberry leaves reflect a high variation along the radiant sp ectrum, suggesting that the breadth of variance in the reflectance is a result of a complex physiological process with in the leaf, not all of which is related to TSSM. The objective of the PCA is to condense the data into the smallest number of

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78 components (axes) to represent the strongest covariance among the variables, not necessarily varying with respect to the experime ntal variable (McCune and Grace 2002). Due to the spectrum wide variability we c hose to apply the LDA to the green and NIR regions, which indicated that the highest level of significance a nd corresponds spatially within the leaf to TSSM feeding s ites. Both regions performed well under laboratory conditions. Spectral results indicate that a high spectral resolution sensor (~0.3m band widths) is highly effective in discriminating between levels of T SSM infestation based on th e variation in both the green and NIR regions. Fitzgerald (2004) not ed that the strawbe rry spider mite ( Tetranychus turkestani Ugarov and Nikolsk) damage in cotton is observable in the 850 nm wavelength, and subsequent work by Fitzgerald (2005) demonstr ated that when using a commercial satellite platform, spectral variations in the green bands were difficult to detect in the field without subjecting the data to spectral unmixing. We fou nd that at the lower spatial resolutions of commercial satellite platforms, th e NIR is a good predictor of TSSM damage in strawberries, but finer resolution sensors are able to detect TSSM more acutely with the green bands. GIT Application The ultimate goal of this study is to detect TSSM numbers in a strawberry field before physiological damage is visible to the human eye. This may allow the application of a preventative strategy to reduce TSSM population before it becomes uncontrollable for growers. Large scale technology in conjunction with infrared sensory systems is already in popular use to detect presence/absence of agricultural pests. In addition to detecting T SSM, our goal is to apply this technology to monitor the leve l of TSSM infestati on relative to radiant reflective response to early cellular damage of the strawb erry leaves. The use of spectra l maps of TSSM distribution in the field could aid in precision pest management programs.

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79 Future Directions There are several options of integrating th is technology. A practical option is for a growers association to buy a field spectromete r such as a field-based Fieldspec 3 JR spectroradiometer (350nm-2500nm) (Analytical Spectral Device s Inc. Boulder, Co). The instrument can be mounted on a tractor or any field equipment and hooked directly to a GPS. The foreoptics on the spectrometer has a conical fi eld of view which is 25 so the image is enlarged with respect to the height of the sensor. The high sensitivity of the sensor allows for up to 20 meters of height above the target with no detectable effect of si gnal to noise ratio. The spectral files are stored as binary data and are directly downloadabl e to the ENVI imagery processing system (ITT Visual Information So lutions, Boulder,CO) which can operate on a desktop computer. The binary files store the data as digital numbers in ASD (Microsoft Advanced Streaming Format description file). In ENVI these files can be exported directly into a spectral library and resampled to the spectral resolution of the image. A raster image is built from each of the spectra specified by a user. The fieldspec software also includes a post processor call a Viewspec Pro that can view and c onvert the binary files into other formats. Once the image is built in the program it can be analyzed in ENVI or in ArcGIS. In ENVI, the image can be analyzed through the basic t ools menu. By choosing regions of interest, the user can create training samples to conduct a supervised classificati on and use the maximum likelihood classification to classify the entire area (field ) and then be able to identify regions of the field at different levels of mite damaged ba sed on the reflectance values defined in this study. The image can also be analyzed in ArcGIS by im porting the image constructed in ENVI with the bands of interest. The digital number will have been calculated in ENVI and imported into ArcGIS. In the attribute table in ArcGIS, the user could then use the que ry builder function to locate each pixel value of known mite infestation. The software will then be able to identify the

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80 pixels of interests in each mite level and enable the user to see the distribution of mite levels in the field based on the digital number. This techni que with the fieldspec is field based and the instruments can be easily mounted on field equi pment. Similar technology has been used extensively in soil and nutrient assessment in agricultural fields. It provides high spectral resolution images that can be georeferenced when used in conjunction with a GPS and has been shown to have the spectral capabilities to discriminate between levels of TSSM.

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81 Figure 5-1. Reflectance map of TSSM distribution of the experiment al strawberry field, Citra, FL.

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82 Strawberry Leaf Reflectance Signatures0 0.2 0.4 0.6 0.8 1 1.2W360 W520 W680 W840 W1000 W1160 W1320 W1480 W1640 W1800 W1960 W2120 W2280 W2440WavelengthReflectance Value 100 mites 25 mites 40 mites 90 mites <10 mites Figure 5-2. Variation of the spectral signatures of strawberry leaves at different levels of TSSM infestation. Validationy = 0.8368x + 13.014 R2 = 0.74690 50 100 150 200 250 -50.00000.000050.0000100.0000150.0000200.0000 predictedobserved Figure 5-3. Regression of predicted versus observed raw TSSM numbers/leaflet.

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83 Figure. 5-4.Scree Plot of PCA. Each point on the graph indicates the cumulative percent of the data for which each factor accounts. The first five factors contain 89.9% of the data. Table 5-1. Classification summary of LDA crossvalidation of PCA. Highlighted percentages on the diagonal indicate th e percent of observations classified correctly. Expected No Lo/Mod Hi Total No Observations classified 4408 Percent classified 50.00% 50.00%0%100% Lo/Mod Observations classified 050252 Percent classified 96.15% 3.85%100% Hi Observations classified 021820 Percent classified 0%10.00% 90% 100% Total 4582080 Observed Total percent of classified 5%70%25%100%

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84 Table 5-2. Accuracy scores for the LDA Green Bands (560nm-580nm) Producers Accuracy Users Accuracy Overall Accuracy: K coefficient No mites 100% 100%92.50%92.40% Low/Moderate 90.39% 98% High 95% 79.19% NIR (700-1000) No mites 87.50% 87.50%92.50%85% Low/Moderate 94.23% 92.50% High 90% 90% Table 5-3. Accuracy scores for LDA of Quickbird and SPOT5 Quickbird (760nm-900nm)/Spot5 NIR (780nm-890nm) Producers Accuracy Users Accuracy Overall Accuracy: K Coefficient No mites 100% 89%93% 86% Low/Moderate 90.38% 90.38% High 95% 95% Quickbird Green band( 520nm-600nm) No mites 87% 22%56%31.00% Low/Moderate 61% 89% High 30% 50% SPOT5 Green (500nm-590nm) No mites 63% 16%53%25% Low/Moderate 60% 89% High 30% 43%

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85 CHAPTER 6 CONCLUSIONS The principal management concern of strawberry growers in north Flor ida is the increasing incidence of twospotted spider mite (TSSM) a nd its effect on berry production. Managing TSSM with miticides is particularly difficult since T SSM has a short lifecycle and resistance can occur within a year of exposure to chemical treatme nts. However, many growers are skeptical about the efficacy of biological control. Growers have indicated that their primary concerns when considering pest management plans are economic viability and competitiveness in the industry. According to Shawn Crocker, Executive Dir ector of the Florida Strawberry Growers Association, fruit and vegeta ble production is becoming more dynamic and highly mechanized. Growers are interested in managing their fiel ds to maximize their production, while minimizing their inputs. The results obtaine d in our experiments regarding biological control, ecological studies on the sustainability of this method, a nd geospatial technology ha ve proven that TSSM management can be both economical ly and ecologically efficient. Our study shows that with minimal inputs from one early season rele ase of the predatory mite, N. californicus, effective season-long management of TSSM can be achieved. The results of our first season (2005-2006) indicate that with low initial TSSM densities, N. californicus is able to provide consistent suppression of TSSM throughout the season. In treated plots, TSSM never exceeded five motiles per trifoliate. Howe ver, there was a higher initial TSSM population in the 2006-2007 season resulting in a higher ratio of predator to prey than the first season, reducing the level of effectiveness. The higher season-long average populations of TSSM in the 2006-2007 season indicate that initial prey populati ons and appropriate prey : predator ratio are critical factors in establishing control of TSSM. Greco et al. (2 005) demonstrated that effective control seems to be limited by high initial TSSM density. An ideal pred ator: prey ratio is

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86 considered to be between 1:5 and 1:10 (Greco et al. 2005). Occasional freezes also seem to reduce TSSM populations. Hart et al. (2001) obs erved that cool temper atures suppress TSSM populations while not adversely a ffecting populations of predator y thripidae, staphiylinidae, lygaediae, and chalcidioidae. We observed this tendency in our e xperiments during the 20052006 season. In the event of high initial TSSM infestati on, as we had in the second field season (20062007), N. californicus must be released at extremely high ra tes to reach the appropriate predator: prey ratio to achieve adequate control of TSSM. Sabelis and Jan ssen (1994) confirmed that at low numbers, N. californicus is not able to reproduce qui ckly enough to decimate a high population, as would a more vor acious predator such as P. persimilis When TSSM populations are high, the number of N. californium needed may be cost prohibi tive for many growers. An alternative, as discussed by Rhodes et al. (2006), is to use an initial reduc ed-risk miticide, or a biopesticide to reduce TSSM popula tions prior to the release of N. californicus. Neoseiulus californicus do not affect the abundance of be neficial insects or disrupt the arthropod assemblage in the field. Plots in which N. californicus were released tended to have a similar arthropod richness and evenness compared with the control plots. Th e natural diversity in the strawberry system combined with the generalist feeding habits of N. californicus may contribute to the ecological stabil ity of the ecosystem (Croft et al. 1998, Klein et al. 2006). The results indicate that a grower need not worry about the effects of releasing N. californicus on non-target organisms when this predat or is introduced into the field. The importance of maintaining a healthy eco system has led to the development of precision pest management. Many growers already utilize GPS to manage nutrients, soil, and moisture (Shawn Crocker, personal communi cation). The development and application of

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87 geographically referenced imagery analysis rega rding TSSM damage is a natural addition to these strategies. Minimal additions to software capabilities on conventional field equipment could enable growers to precisely locate spot areas in the field th at are developing populations of TSSM before visible by the human eye. Growers can then respond by treati ng spot infestations appropriately, conserving both econo mic and natural resources. The concern about resource management and conservation has encouraged the development of strategies includ ing biological control, precision agriculture, and precision pest management. The studies presented provide evid ence that it is possible to reduce both economic and chemical inputs in strawberry fields, ma intaining a healthy ecosystem and responding to both consumer and grower concerns regarding the health and marketability of the most valuable small fruit crop in Florida.

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88 APPENDIX A STRAWBERRY PEST MANAGEMENT SURVEY Name: _________________________________________________ Size of cultivated strawberry area: ___________________________ 1) What specific pest problems to you encounter (Insect, Weed, Diseases) Pest Control Method _______________________ _____________________ _______________________ _____________________ _______________________ _____________________ 2) Are you concerned about twospotted spider mites (TSSM)? Yes No 3) Have you experience yield loss due to TSSM da mage, if so what per centage/economic value of your production was lost? ______________________________________________________________________________ __________________________________________________________________ 4) How do you monitor for TSSM? ______________________________________________________________________________ ______________________________________________________________________________ ____________________________________________________________ 5) What is your current TSSM management program? ______________________________________________________________________________ ______________________________________________________________________________ ____________________________________________________________ 6) Would you be willing to use predators (biological control)? yes No If not why? ______________________________________________________________________________ ______________________________________________________________________________ ____________________________________________________________ 7) What factors do you consider when deciding on a management program? (please circle all that apply) a) economics b) environmental concerns c) customer concerns d) time/labor requirments This pest management survey was conducted wi th the help of Florida Strawberry Growers Association (N = 12). The results are as follows:

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89 1) What pest problems do you encounter? The commonest pest problems: 30% fungus 50% fungus and birds 20% TSSM 2) How do you monitor for Twospotted spider mite (TSSM)? Frequency of scouting varies between once a day and once a week and the action threshold varies: 20% 1 TSSM per leaftlet, 20% 5 TSSM per field of view (FOV) of hand lens 20% 10 TSSM per FOV of hand lens 10% wait until leaves begin to yellow 20% spay regularly so do not have TSSM 10% no formal scouting 3) What is your current management program 90% use chemicals, only the organic growers rely on natural enemies (they do not have a problem with TSSM) 4) Would you be willing to use biological control? 100% said they would be willing to use biocontrol but the concerns are cost and compatibility with fungicides and other ch emicals used in the field. 5) What factors do you consider when deciding on a management program? 100% are primarily concerned with economics.

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90 APPENDIX B FUTURE WORK Objective 1: To determine the appropriat e time for inoculative releases of N. californicus. Our work provides compelling evidence that releasing N. califor nicus early in the season can provide stable season-long control of TSSM. However, there are still several questions to be answered: 1) Greco (2004, 2005) determined that for control of TSSM, N. californicus needed to be releas ed at a ratio of 1:5 to 1:10 (p redator: prey). Further work on determining the optimal predator: prey ratio in the north Florida strawberry system would be helpful to verify this assertion; 2) investigati ng varying levels of TSSM densities on the efficacy of N. californicus in the field should be c onducted. In our greenhouse trials, N. californicus demonstrated a functional response with prey de nsity. Hassell et al. (1976 ) support this finding in laboratory studies. However, this response has no t been validated in th e field. Releasing N. californicus at a constant predator: prey ratio in areas of high and low TSSM densities to assess efficacy of N. californicus would contribute to our understanding of the predator: prey interaction; 3) future explora tion is needed to understand the effect that the timing of TSSM infestation and plant phenology has on berry yield. Objective 2: To evaluate the effect of predatory releases on naturally occurring arthropods. The findings in this study indicate that N. californicus does not have a significant impact on the arthropod assemblage in the stra wberry system. However, the studies conducted captured the general distribution of taxa in the system. We found th at plant phenology and ambient weather had an impact on arthropod asse mblage in the field, which may affect the impact of N. californicus in the system. Repeated trials across seasons in different climactic conditions should be conducted. In addition, investigating the effect of N. californicus releases

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91 on taxonomic composition within arthropod families would contribute to a deeper understanding of the system. Objective 3. To establish a pest monito ring program using geographic information technology (GIT). Our laboratory studies have shown that there is a strong correlation between specific levels of mite infestati on on strawberry leaves and altera tion in leaf reflectance in the green and NIR wavebands. However, the applica tion of the laboratory analysis needs to be verified in the field, and an efficient data collection and analysis procedure needs to be established. Testing the laboratory results in th e field under ambient conditions is important to make this technique practical. To test the results in the field, a field spectrometer should be acquired and connected to a GPS. The unit should be mounted onto a tractor, or other field equipment, to collect data from the green and NI R wavebands and input into an imagery analysis system as outlined in Chapter 5. Finally, the process must be validated by applying it to a number of fields and conditi ons to ensure reliability.

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92 LIST OF REFERENCES Blackwood, J. S., P. Schausberger, and B. A. Croft. 2001. Prey-stage preference in generalist and specialist Phytoseiid mites (A cari: Phytoseiidae) when offered Tetranychus urticae (Acari:Tetranychidae) eggs and larva. Environ Entomol 30: 1103-1111. Bolland, H. R., Gutierrez, and C. H. W. Flechtman. 1998. World Catalogue of the spider mite family Tetranychidae. Brill Academic Publishing, Leiden, Netherlands. Brewster, C. C., J. C. Allen, and D. D. Kopp. 1999. IPM from space: Using satellite imagery to construct regional crop maps for studying crop-insect interaction. Am Entomol 45: 105115. Brown, M. 2003. Florida strawberry produc tion and marketing, pp. 31-42. In N. F. Childers [ed.], The Strawberry: A Book for Growers, Ot hers. Dr. Norman F. Childers Publications, Winter Park, FL Cakmak, I., and S. Cobanoglu. 2006. Amblyseius californicus (McGregor, 1954) (Acari: Phytoseiidae), a new record for the Turkish fauna. Turk J Zoo. 30: 55-58. Castagnoli, M., M. Liguori, and S. Simoni. 1999. Effects of two different host plants on biological features of Neoseiulus californicus (McGregor). Int J Acarol 25: 145-150. Cloyd, R. A., C. L. Galle, and S. R. Keith. 2006. Compatibility of three miticides with predatory mites Neoseiulus californicus McGregor and Phytoseiulus persimilis AthiasHenriot (Acari: Phytoseiid ae). HortScience 41: 707-710. Colfer, R. G., J. A. Rosenheim, L. D. Godfrey, and S. L. Hsu. 2004. Evaluation of large-scale releases of western predatory mite for spider mite control in cott on. Biol Control 30: 1-10. Croft, B. A., and L. B. Coop. 1998. Heat units, release rate, prey density, and plant age effects on dispersal by Neoseiulus fallacis (Acari:Phytoseiidae) after inoculation into strawberries. J Econ Entomol 91: 94-100. Croft, B. A., L. N. Monetti, and P. D. Pratt. 1998. Comparative life histories and predation types: are Neoseiulus californicus and N. fallacis (Acari: Phytoseiidae) similar type II selective predators of spider mite? Environ Entomol 27: 531-538. Cross, J. V., M. A. Easterbrook, A. M. Crook D. Crook, J. D. Fitzgerald, P. J. Innocenzi, C. N. Jay, and M. G. Solomon. 2001. Review: Natural Enemies and Biocontrol of Pests of Strawberry in North and Central Europe. Biocontrol Sci Tech 11: 165-216. Dayang, A. I., and J. Kamaruzaman. 1999. Geospatial information technologies for Malaysian agriculture in the next millennium, Seminar on Repositioning Agriculture Industry in the Next Millennium., University of Ma laysia, Serdang, Selangor, Malaysia. Easterbrook, M. A. 1992. The possibility for control of two-spotted spider mite Tetranychus urticae on strawberries in the UK. Biocontrol Sci Tech 2: 235-245.

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93 Ellis, M., and D. E. Legard. 2003. Integrated Pest Management of Strawberry Diseases in Perennial Systems, pp. 103-110. In N. F. Childers [ed.], The Strawberry: A book for growers, others. Dr. Norman F. Child ers Publications, Winter Park, FL. English-Loeb, G., and S. Hesler. 2004. Economic impact of the twospotted spider mites ( Tetranychus urticae ) on strawberries grown as a pere nnial. New York Fruit Quarterly 12. Escudero, L. A., and F. Farragut. 2005. Life-history of predatory mites Neoseiulus californicus and Phytoseiulus persimilis (Acari: Phytoseiidae)on f our spider mites species as prey, with special reference to Tetranychus evansi (Acari: Tetranychid ae). Biol Control 32: 378-384. Fitzgerald, G. L., S. J. Maas and W. R. Detar. 2004. Spider mite detection and canopy component mapping in cotton using hyperspectra l imagery and spectral mixture analysis. Precis Agric 5: 275-289. Fitzgerald, G. L., P. J. Pinter, D. J. Hunsaker, and T. R. Clarke. 2005. Multiple shadow fractions in spectral mixture analysis of a cotton canopy. Remote Sensing of the Environment 97: 526-539. Florida Automated Weather Network (FAWN) 2004 University of Florida IFAS extension. FAWN. Gainesville, FL. Last updated May 2007. http://fawn.ifas.ufl.edu/data/. [date retrieved April 2007] Garcia-Mari, F., and J. E. Gonzalez-Zamora. 1999. Biological control of Tetranychus urticae (Acari:Tetranychidae) with na turally occurring predators in strawberry plantings in Valencia, Spain. Exp Appl Acarol 23: 487-495. Gilstrap, F. E., and D. D. Friese. 1985. The predatory potential of Phytoseiulus persimilis, Amblyseius californicus and Metaseiulus occidentalis (Acarina: Phytoseiidae). Int J Acarol 11: 163-168. Greco, N. M., G. T. Tetzlaff, and G. G. Liljesthrom. 2004. Presence-absence sampling for Tetranychus urticae and its predator Neoseiulus californicus (Acari: Tetranychidae;Phytoseiidae) on strawbe rries. Int J Pest Manage 50: 23-27. Greco, N. M., N. E. Sanchez, and G. G. Liljesthrom. 2005. Neoseiulus californicus (Acari:Phytoseiid) as a potential control agent of Tetranychus urticae (Acari: Tetranychidae): effect of pe st/predator ratio on pest abundance on strawberry. Exp Appl Acarol 37: 57-66. Grostal, P., and M. Dicke. 2000. Recognizing one's enemies: a functional approach to risk assessment by prey. Behav Ecol Sociobiol 47: 258-264. Handley, D. T., and J. F. Price. 2003. Insect and mite damage in strawberries, pp. 94-102. In N. F. Childers [ed.], The Strawberry: A book for growers, others. Dr. Norman F. Childers Publications, Winter Park, FL.

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94 Hardman, J. M., I. Klaus, N. Jensen, J. L. Franklin, and D. Moreau. 2005. Effects of dispersal, predators (Acari: Phytoseiid), weather, and ground cover treatments on populations of Tetranychus urticae (Acari: Tetranychidae) in a pple orchards. Hort Entomol 98: 862-874. Hart, A. J., J. S. Bale, A. G. Tullett, M. R. Worland, and K. F. A. Walters. 2002. Effects of temperature on the establishment potential for the predatory mite Amblyseius californicus McGregor (Acari: Phytoseiid) in th e UK. J Insect Physiol 48: 593-599. Hassel, M.P., J.H. Lawton, J,H. Beddington. 1976 The components of arthropod predation: the prey death rate. J Anim Ecol. 45: 135-164 Hoy, M. A., H. E. Van de Baan, J. J. R. Groot, and R. P. Field. 1984. Aerial movements of mites in almonds: implications for pe st management. Calif Agric 38: 21-23. Huffaker, C. B., M. Van De Vrie, and J. A. McMurtry. 1969. The ecology of Tetranychid mites and their natural control. Annu Rev Entomol 14: 125-174. Iatrou, G., C. M. Cook, S. G., and T. Lanaras. 1995. Chlorophyll fluorescence and leaf chlorophyll content of bean l eaves injured by spider mite s (Acari: Tetranychidae). Exp Appl Acarol 19: 581-591. Janssen, A., J. Bruin, G. Jacobs, R. Schraag, and M. W. Sabelis. 1997. Predators use volatiles to avoid prey patches with conspecifics. J Anim Ecol 66: 223-232. Jensen, J. R. 2005. Introductory digital imag e processing: a remote sensing perspective. Pearson Prentice Hall, Upper Saddle River, NJ. Jeppson, L. R., H. H. Ke ifer, and E. W. Baker. 1975. Mites injurious to economic plants. University of California Press, Berkeley, CA. Jones, M. G. 1976. The Arthropod Fauna of a Winter Wh eat Field. The J Appl Ecol 13: 61-85. Jung, C., and B. A. Croft. 2001. Ambulatory and aerial disp ersal among specialist and generalist predatory mites (Acari: P hytoseiidae) Environ Entomol 30: 1112-1118. Kielkiewicz, M. 1985. Ultrastructural changes in strawber ry leaves infested by two-spotted spider mites. Entomol Exp Appl 37: 49-54. Klein, A. M., I. Steffan-Dewenter, and T. Tscharntke. 2006. Rain forest promotes tropic interactions and diversity of trap-nesting hymenoptera in adjacent agroforestry. J Anim Ecol 75: 315-323. Krantz, G. W. 1978. Manual of Acarology. Oregon State Un iversity Press, Corvallis, OR. Landeros, J., L. P. Guevara, M. H. Badii, A. E. Flores, and A. Pamanes. 2004. Effect of different densities of the twospotted spider mite Tetranychus urticae on CO2 assimilation, transpiration, and stomata behaviour in rose leaves. Exp Appl Acarol 32: 187-198.

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95 Lillesand, T. M., R. W. Kiefer, and J. W. Chipman. 2004. Remote sensing and image interpretation. John Wile y and Sons, Madison, WI. Magurran, Anne. 2004. Measuring Biological Diversity. Bl ackwell Publishing. Malden, MA McCune, B., and J. B. Grace. 2002. Analysis of Ecological Communities. MJM Software Design, Corvallis, OR. McMurtry, J. A., and B. A. Croft. 1997. Life-styles of phytoseiid mites and their roles in biological control. Annu Rev Entomol 42: 291-321. Meyer, B. S., D. B. Anderson, R. H. Bohning, and D. G. Fratianne. 1973. Introduction to Plant Physiology. D. Van Nost rand Company, New York, NY. Mossler, M. A., and O. N. Nesheim. 2002. Florida Crop/Pest Manageme nt Profiles: Strawberry. IFAS Extension.PI037. University of Florida. Gainesville, FL. NASS-USDA. 2006. Non-citrus and nuts, 2005 preliminary summery p 18 In NASS-USDA [ed]. national Agricultural Statistics Service (NASS) and United states Department of Agriculture (USDA), Arlington, VA. NASS-USDA. 2007. Non-citrus and nuts, 2006 preliminary summery p 15 In NASS-USDA [ed]. national Agricultural Statistics Service (NASS) and United states Department of Agriculture (USDA), Arlington, VA Oatman, E. R., M. E. Badgley, and G. R. Platner. 1985. Predators of the two-spotted spider mite on strawberry. California Agriculture January-February: 9-12. Oatman, E. R., J. A. McMurtry, F. E. Gilstrap, and V. Voth. 1977. Effect of releases of Amblyseius californicus on the twospotted spider mite on strawberry in Southern California. Journal of Econ Entomol 70: 638-640. Oatman, E. R., and V. Voth. 1972. An ecological study of the twospotted spider mite on strawberry in southern California. Environ Entomol 1: 34-39. Powers, L. E., and R. McSorley. 2000. Ecological Principles of Agriculture. Delmar. Thomson Learning. Albany, NY. Raworth, D. A. 1990. Predators Associated with the tw ospotted spider mite, Tetranychus urticae, on strawberry at Abbotsford, BC, and de velopment of non-chemical mite control. J Entomol Soc BC 87: 59-67. Reddall, A., V. O. Sadras, L. J. Wilson, and P. C. Gregg. 2004. Physiological responses of cotton to two-spotted spider mite damage. Crop Sci 44: 835-846. Rhodes, E. M., and O. E. Liburd. 2005. Predatory mite, Neoseiulus californicus (McGregor) (Arachnida:Acari:Phyto seiidae). IFAS Extension. IN639. University of Florida, Gainesville, FL.

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98 BIOGRAPHICAL SKETCH Aimee graduated with her BA in sociology with a concentration in environmental sociology from Indiana University in 1999. Before entering graduate school, she worked on and managed several experimental organic farms in both the United States and South Africa. She also taught marine ecology with the Chesap eake Bay Foundation in Maryland and Save the Sound in Connecticut. She earned a teaching degree in Montessori elementary education in 2003. During her masters work she held a position as a research assistant in the Small Fruit and Vegetable IPM lab in the Ento mology Department at the Univ ersity of Florida. Her study focused on biological control of twospotted spider mite in st rawberry, an exploration of arthropod diversity, and geospati al imagery systems as a component of a precision pest management program.