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Developing Sustainable Solutions for Integrated Brassica Crop Management
Cate Paull
South Australia Research & Development Institute (SARDI)
Project Number: VG07030
VG07030
This report is published by Horticulture Australia Ltd to pass
on information concerning horticultural research and development undertaken for the vegetables industry.
The research contained in this report was funded by
Horticulture Australia Ltd with the financial support of the vegetables industry.
All expressions of opinion are not to be regarded as expressing the opinion of Horticulture Australia Ltd or any
authority of the Australian Government. The Company and the Australian Government accept no
responsibility for any of the opinions or the accuracy of the information contained in this report and readers should rely
upon their own enquiries in making decisions concerning their own interests.
ISBN 0 7341 2558 5 Published and distributed by: Horticulture Australia Ltd Level 7 179 Elizabeth Street Sydney NSW 2000 Telephone: (02) 8295 2300 Fax: (02) 8295 2399 © Copyright 2011
Horticulture Australia Limited
PROJECT VG07030
(30 October 2007 – 15 November 2010)
FINAL REPORT
Developing Sustainable Solutions for Integrated Brassica Crop
Management
Cate Paull et al.
South Australian Research and Development Institute
Research Providers:
South Australian Research and Development Institute
University of Adelaide
Queensland Department of Primary Industries & Fisheries
November 2010
HAL Project VG07030
Project Leader:
Cate Paull
Entomology Unit
SARDI
GPO Box 397 Adelaide SA 5001
Phone: +61-8-8303-9543
Fax: +61-8-8303-9542
Email: [email protected]
This report details the research and extension delivery undertaken in the above project
on developing sustainable solutions for integrated Brassica crop management. Main
findings, industry outcomes and recommendations to industry along with suggested
areas of future research are discussed.
November 2010 HAL Disclaimer:
Any recommendations contained in this publication do not necessarily represent
current Horticulture Australia Limited policy. No person should act on the basis of
the contents of this publication, whether as to matters of fact or opinion or other
content, without first obtaining specific, independent professional advice in respect of
the matters set out in this publication.
South Australian Research and Development Institute Disclaimer:
IMPORTANT NOTICE. This report is intended as a source of information only.
Although SARDI has taken all reasonable care in preparing this report, neither
SARDI nor its officers accept any liability resulting from the interpretation or use of
the information set out in this report. Information contained in this report is subject to
change without notice. The report is not intended for publication or distribution to
any other person or organisation.
This project has been funded by HAL using the vegetable levy and matched funds
from the Federal Government.
ACKNOWLEDGMENTS
The Project Team acknowledge the funding provided by Horticulture Australia
Limited, the Australian brassica vegetable growers through the vegetable levy, Yates
(Orica) Pty. Ltd., Dupont (Australia) Ltd.,Syngenta Crop Protection Pty. Ltd. and
Dow AgroSciences Australia Ltd. Support from the participating institutions, South
Australian Research and Development Institute (SARDI); University of Adelaide;
Queensland Department of Employment Economic Development (QLD DEEDI) and
Innovation; is also acknowledged.
In addition, the Project team wish to recognize the invaluable assistance provided by
members of the AUSVEG Brassica Grower Steering Committee in helping guide and
oversee the direction of this project, and the growers who co-operated with field trials,
field days, etc. The project team would also like to acknowledge the help and support
provided by Bronwyn Walsh and Elizabeth Minchinton. Specific acknowledgments
are provided at the end of each research and extension report.
The Project leader thanks the team members for their willing co-operation and
openness throughout the Project. Without this goodwill the achievements of this
Project would have been substantially diminished.
THE PROJECT TEAM Greg Baker (SARDI)
David Carey (QLD DEEDI)
Mike Keller (The University of Adelaide)
Chris McIntyre (The University of Adelaide)
Cate Paull (SARDI)
Kevin Powis (SARDI)
Mahbub Rahman (SARDI)
Latif Salehi (SARDI)
Lara Senior (QLD DEEDI)
CONTENTS
Media Summary ------------------------------------------------------------------------------- 6
Technical Summary --------------------------------------------------------------------------- 7
Introduction------------------------------------------------------------------------------------ 11
Research Reports ----------------------------------------------------------------------------- 13
Appendices----------------------------------------------------------------------------------- 133
1 BIOASSAY SCREENING OF FIELD POPULATIONS OF DIAMONDBACK
MOTH IN AUSTRALIAN VEGETABLE CROPS FOR TOLERANCE TO THREE
SYNTHETIC INSECTICIDES AND Bacillus thuringiensis VAR. kurstaki, 2008-10
--------------------------------------------------------------------------------------------------- 13
2 EVALUATION OF SOIL AMENDMENTS FOR BRASSICA PRODUCTION
SYSTEMS---- -------------------------------------------------------------------------------- 28
2.1 THE AFFECT OF COMPOST ON DIVERSITY OF INVERTEBRATES IN
BRASSICA PRODUCTION SYSTEMS.
------------------------------- ------------------------------------------------------------------ 29
2.2 THE EFFECT OF COMPOST ON WHITE BLISTER
---------------------------------------------------------------------------------------- --------- 41
2.3 BENEFITS OF USING COMPOST WITH IN BRASSICA VEGETABLE
PRODUCTION SYSTEMS----------------------------------------------------------------------
-------------------------------------------------------------------------------------------------- 47
3. KEY PREDATORS OF DIAMONDBACK MOTH IN BRASSICA
VEGETABLES------------------------------------------------------------------------------- 53
4.1 IDENTIFYING NATURAL ENEMIES OF EARLY SEASON BRASSICA
PESTS IN UNSPRAYED PLANTINGS AT GATTON RESEARCH STATION------
------------------------------------------------------------------------------------------------- 64
4.2 IDENTIFYING NATURAL ENEMIES OF EARLY SEASON BRASSICA
PESTS IN COMMERCIAL PLANTINGS IN THE LOCKYER VALLEY--------- 80
4.3 COULD A SUMMER CROP BE USED AS A NATURAL ENEMY SOURCE
FOR NEWLY PLANTED BRASSICAS? ----------------------------------------------- 98
4.4 EVALUATION OF THE PREDATORY BEHAVIOUR OF SOME SPIDERS
COMMONLY FOUND IN EARLY SEASON BRASSICA CROPS --------------- 113
5 BRASSICA ICM TOOLKIT CD - INDUSTRY TRAINING ACTIVITIES-----------
------------------------------------------------------------------------------------------------- 123
6. COMMUNICATION AND TECHNOLOGY TRANSFER ACTIVITIES------------
------------------------------------------------------------------------------------------------ 127
Appendices
Appendix 1 List of Morphospecies 133
Appendix 2.1 (I) Identifying natural enemies, trial sites, Gatton Research
Station 137
Appendix 2.1 (II) Weather data 138
Appendix 2.1 (III) Pest species data 139
Appendix 2.1 (IV) Beneficial Fauna 144
Appendix 2.2 (I) Identifying natural enemies, trial sites, commercial
plantings, Lockyer Valley 145
Appendix 2.2 (II) Weather data 159
Appendix 2.2 (III) Pest species data 150
Appendix 2.2 (IV) Beneficial fauna data 160
Appendix 2.3 Weather data 173
Appendix 2.4 Evaluation of the predatory behaviour of some spiders,
experimental set up 174
Appendix 3.1 Brassica ICM Toolkit Training Manual 176
Appendix 4.1 (I) Brassica IPM National Newsletter issue 12 177
Appendix 4.1 (II) Brassica IPM National Newsletter issue 13 178
Appendix 4.1 (III) Brassica IPM National Newsletter issue 14 179
Appendix 4.2 Brassica Research Update 2010 – Survey Questions 180
Appendix 4.3 Results from 2010 survey 183
Appendix 4.4 Natural Enemies in Early Season Brassica 188
Appendix 4.5 2009 Insecticide Resistance Management Strategy 189
6
MEDIA SUMMARY The Australian Brassica vegetable industry has a complex of pests that impact upon
its production and marketing, but Diamondback moth (DBM), Plutella xylostella (L.),
remains the most destructive pest of Brassica vegetables in Australia primarily
because of its ability to rapidly become resistant to insecticides.
This project aimed not only to continue to monitor for insecticide resistance in
national DBM populations but further contribute to the management of DBM, through
integrated pest management (IPM) and integrated crop management (ICM), by
identifying natural enemies, using DNA techniques and identifying natural enemies
important for the management of other pests, specifically those which effect early
season Brassica vegetable crops in Queensland. In response to an extended period of
drought the project also under took to investigate the benefits of compost for Brassica
production systems.
The key outcomes were:
The DBM resistance screening program revealed significant tolerance in field
populations of DBM to the important insecticides Proclaim®, Success
TM2 and
Avatar®, but no evidence of tolerance to Bacillus thuringiensis subsp. kurstaki
products.
Application of compost was shown to provide a number of benefits for
Brassica vegetable production including increased soil carbon and crop yield.
DNA techniques were used to confirm which species of commonly-occurring
natural enemy in Brassica systems consume DBM.
Spiders were confirmed as the natural enemies most likely to impact on early
season Brassica pests in Queensland.
A hands-on training manual and program for growers and industry, on the use
and benefits of the Brassica Integrated Crop Management Tool Kit CD, was
developed and delivered.
Recommendations for practical application and information from research
undertaken in the project were incorporated into a range of extension
activities. These included the production and distribution of three issues of the
“Brassica IPM National Newsletter”, the 2009 version of the “two-window”
Insecticide Resistance Management Strategy, national workshops held in nine
national Brassica vegetable production regions and electronic survey.
IPM and ICM are dynamic, multi-tactic strategies that offer sustainable ways of
managing pests and vegetable production. While outcomes of this project provide
evidence of an increased uptake of IPM by industry, they also identify key elements
which should be the focus of future research and development if the reliability of
these strategies for the Brassica industry is to be enhanced.
Recommendations for future research and development include:
Development of marketing and incentive schemes to further encourage the
uptake of IPM,
Enhancing the range and abundance of natural enemies species, particularly
early season, and
Optimising spray application techniques.
Until such time as these areas are addressed the key recommendations to industry are
to continue to monitor crops to make informed decisions about spray applications
within the guide lines of the IRM strategy and choose insecticides that are least
harmful to natural enemies but effective against DBM.
7
TECHNICAL SUMMARY
The Problem
Diamondback moth (DBM), Plutella xylostella (L.), remains the most destructive pest
of Brassica vegetables in Australia. DBM rapidly evolves insecticide resistance, and
control by natural enemies can be disrupted due to the lack of integrated pest
management (IPM) implementation to more effectively deal with the problem.
Therefore throughout this project monitoring the development of insecticide
resistance within populations of DBM was continued. The project also undertook to
identify the benefits of soil amendments, confirm which natural enemies in Brassica
crops consume DBM and which natural enemies impact on early season Brassica
pests in Queensland. Achieving these objectives has contributed to providing Brassica
growers with improved understanding of IPM and integrated crop management (ICM)
tactics, which have previously been demonstrated to be cost-effective, limit
insecticide resistance and conserve and better incorporate natural enemies into
Brassica vegetable production systems.
The Project Science
Insecticide Resistance Management
Insecticide-resistance screening of DBM populations, collected from vegetable
districts in each state, against three key insecticides registered for use in
Brassica vegetable crops, including Bacillus thuringiensis var kurstaki.
Evaluation of soil amendments for Brassica production systems:
Determined which soil invertebrates occur and what effect compost has on the
diversity and abundance of invertebrates within a Brassica vegetable
production system. In particular, the invertebrates that are associated with
decomposition of post-harvest Brassica residue as well as invertebrate pests
and natural enemies.
Quantified the effect of compost on the quantity of the disease agent A.
candida, white blister in soil.
Quantified the effect that compost had on the soil organic carbon content and
crop yield.
Natural Enemies
Application of DNA techniques to confirm which natural enemies consume
DBM within Brassica crops.
Natural Enemies for Early Season Brassica Pests:
Identified and evaluated the natural enemies of early season Brassica pests in
unsprayed and commercial plantings of Brassica vegetables in Queensland.
Assessed Summer crops as a potential source of natural enemies for plantings
of early season Brassica vegetables.
Evaluated the predatory behaviour of spiders, those most commonly found
early in the season, and their potential to impact on early-season Brassica
pests.
8
The Key Research Findings, Extension Highlights and Industry Outcomes
Insecticide Resistance Management
Insecticide resistance screening of DBM populations from around the nation
identified DBM populations that showed reduced susceptibility to several
newer insecticides, namely emamectin benzoate, indoxacarb and spinosad.
However there was no significant change in the susceptibility of DBM
populations to Bacillus thuringiensis subsp. kurstaki.
o The resistance profile information provided by this study is crucial for
the detection of early shifts in tolerance to these commonly-used
insecticides, and thereby to effect early management responses to
extend the efficacy of the newer, more IPM-compatible insecticides
and gauge the time available for developing alternative controls.
o Based on the screening results we have recommended changes
(cessation or reduction for several years) in emamectin benzoate usage
on properties that have frequently applied this product in the past, to
allow the susceptibility of these DBM populations to this product to
increase back towards pre-selection levels.
Evaluation of soil amendments for Brassica production systems which compared
treatments with and without compost, results include
Identifying 146 invertebrate morphospecies the majority of which were
detritivores. Results from experiments showed there was a significant increase
in diversity of morphospecies from treatments where compost had been added.
Applying compost increased the abundance of mites, springtails and
earthworms, morphospecies which are regarded as important for the
decomposition of plant material. o Future research could identify which invertebrate groups are most
efficient at decomposing plant material and if there is any specificity
with regard to this (e.g. do some species decompose Brassica residues
more efficiently than others, or show preference for plant diseases).
Developing specific probes that were able to be applied in quantitative PCR to
accurately determine the amount of A. candida DNA in soil or tissue samples.
o There is scope to develop this test as a risk analysis tool. However, this
would first require determination of the degree white blister (WB)
viability per amount of pathogen DNA detected in samples. Currently,
there is no indication to what level of disease correlates with varying
amounts of WB DNA detected.
A significant increase in yield was quantified for two years from a single
application of compost. The application of compost also increased organic soil
carbon. Additional benefits of applying compost were also observed.
o In order for these results to be applied across industry, further work
will need to be undertaken to understand nutrient budgets in relation to
compost. For example determining what rate of compost is equivalent
to a specific quantity of fertilizer.
Natural Enemies
DNA methods confirmed that nine species of natural enemy, commonly found
associated with Brassica crops, consume DBM. The brown lacewing
Micromus tasmaniae was the most abundant species and found throughout the
year.
9
o These results have confirmed new candidate natural enemies that
contribute to mortality of DBM. Further investigation of their biology
will identify ways of enhancing their number and therefore increase the
reliability of IPM. Until this information is established it is
recommended that industry continue to employ IPM tactics which
cause the least disruption to these species.
Natural Enemies for Early Season Brassica Pests
Spiders were identified as key predators and therefore an important component
of the beneficial fauna in early season Brassica crops. Spiders were the most
numerous predators, one of the first to arrive in the newly transplanted crops,
and were found consistently at all sampling sites. Theridiids, clubionids and
miturgids were the most abundant foliage-dwelling spiders; lycosids were the
most abundant ground-dwelling spiders.
The presence of a refuge planting was associated with increased numbers of
foliage-dwelling spiders and rove beetles. There was some indication of an
increase in numbers of wolf spiders, native earwigs, lacewings, hoverflies,
Trichogramma and Aphidius, but no evidence that the refuge was the source.
All three spider groups were able to prey upon key Brassica pests
(diamondback moths, cabbage cluster caterpillar, green peach aphid),
consuming between 1.1 and 3.3 lepidopteran larvae a day.
Theridiids were capable of predating late instar DBM larvae up to five times
their own body size. Although these spiders were the least voracious, their
higher relative abundance in the field could allow them to have a large impact
on pests.
o The results from combined field and laboratory experiments suggest
that the three most commonly-found spider groups are capable of
making a substantial contribution to pest suppression in Brassica
vegetable crops. In order for the concept of crop refuges to be
developed into a prescriptive IPM tool for enhancing these and other
populations of natural enemies, future studies should be designed to
assess movement of arthropods between the refuge and the Brassica
crop and large scale commercial trials should conducted.
Communication And Technology Transfer Activities
Website: Information and newsletters from this project have been uploaded,
updated and added to the outputs from previous projects on the following
website.
The Project website link is
www.sardi.sa.gov.au/diamondbackmoth
The following print media items were distributed to over 1200 Brassica
growers and industry representatives;
o Brassica Newsletter: issues 12, 13 and 14 of „Brassica IPM National
Newsletter‟.
o IRM brochure. The integrated resistance management (IRM) schedule
was updated in 2009 to include newly registered insecticidal
chemistries.
o Brassica Integrated Crop Management Toolkit CD (Brassica ICM
toolkit CD).
10
o “Natural Enemies for early season Brassica pests: When Where and
How to identify them” was produced and distributed to QLD growers.
A series of comprehensive workshops were conducted in each of the main
Brassica vegetable production regions of Australia, towards the end of the
project. These workshops combined the following extension activities
o Workshops: Researchers engaged and presented the results from
specific components of the project.
o Training: Hands on training was conducted show growers how to
access and use the Brassica ICM toolkit CD.
o Project Survey: Growers and industry were surveyed at the end of each
workshop.
The key outcome was improved grower awareness about the resources and options
available to increase the adoption of IPM and integrated crop management (ICM)
technologies. Conversely these activities provided an insight on which areas the
industry would prioritise for future research and development.
11
INTRODUCTION
Historical background to project
Diamondback moth (DBM) remains the most destructive pest of Brassica vegetables
worldwide, including Australia. Damage is caused by larvae tunnelling into the heads
of cabbage and Brussels sprouts and by pupal contamination inside cauliflower and
broccoli florets. In extreme cases, produce is rendered unmarketable and damaged
crops are ploughed in.
For the past 50 years the principal control tactic for DBM has been the use of
synthetic insecticides. These treatments invariably disrupt natural enemies, and select
for insecticide resistance in DBM. Due to the progressive development of synthetic
pyrethroid (SP) and organophosphate (OP) resistance in Australia in the 1980‟s and
1990‟s, it became necessary to spray more frequently to achieve control of DBM.
Growers found themselves on a “chemical treadmill”. Despite the increased spraying,
crop losses due to DBM attack continued, often on a larger scale than previously
experienced.
In the late 1990‟s two important developments occurred in Australia. Firstly, a
national industry-funded (HRDC levy) project Advancing the integrated management
of diamondback moth (DBM) in Brassica vegetables, VG97014 was initiated.
Secondly, five new DBM insecticides were sequentially registered for use in Brassica
vegetable crops. These insecticides each have different modes of action and
metabolism, and several are relatively safe to natural enemies. These developments
provided a unique opportunity to improve DBM management and to limit the further
development of insecticide resistance by DBM and other Brassica pests.
Advancing the integrated management of diamondback moth (DBM) in Brassica
vegetables, VG97014, devised and promoted a “two-window” insecticide resistance
management (IRM) strategy in conjunction with AVCARE, and promoted integrated
pest management (IPM) as a method for dealing with Brassica pests. Several things
were actively promoted: the strategic use of insecticides with timing of applications
based on information gained through crop monitoring, techniques to achieve good
spray coverage, the avoidance of tank mixes of multiple insecticides, the use of clean
seedlings, the maintenance of vigorous plants to resist pests and diseases and the use
of crop breaks to reduce DBM numbers and levels of insecticide resistance. Research
into DBM movement between vegetable crops was initiated to improve future IPM
and IRM systems.
Advancing the integrated management of diamondback moth (DBM) in Brassica
vegetables, VG97014, took the first steps in making growers aware of DBM‟s biology
and the potential for improving its management and reducing spraying through crop
monitoring. Growers were able to realize short-term benefits by improving spray
application, substituting the new insecticides and Bacillus thuringiensis for the old
insecticides, and the long-term benefit of an extended lifespan for the new insecticides
by adhering to the “two-window” IRM strategy.
Implementing Pest Management of Diamondback Moth, VG00055, was to enhance
the biological components of the IPM program, and to provide more IPM/IRM tools.
The project was successful and advances were made in further understanding the
12
movement of not only the key pest DBM but associated parasitoids and how
parasitoids may be enhanced. The project also developed specific DNA techniques
which would now enable research to be conducted on a range of natural enemies for
Brassica pests. A number of sophisticated IPM tools were also developed and
disseminated, these included.
The electronic scouting and spray decision plan
The DBM development calculator
The Brassica Integrated Crop Management CD toolkit
Insecticide toxicity chart for beneficial
Why it was undertaken
This project, Developing Sustainable Solutions for Integrated Brassica Crop
Management, VG07030, provided the opportunity to build on some of the advances
made by the project Implementing Pest Management of Diamondback Moth,
VG00055. Development of DNA techniques from the previous project now meant
that the biology of natural enemies could be researched. The advent of a nationwide
drought and the emerging disease issues such as white blister made investigating the
benefits of soil amendments central objectives of the project. Queensland Brassica
growing regions suffer crop damage from a range of early season pests. Hence
determining which natural enemies are most likely to contribute to their control was
also included. Screening field populations of DBM for evidence of significant
deterioration in susceptibility to the newer, more IPM-compatible insecticides was
also a priority. The final objectives of the project were decided on in conjunction
with the Brassica Industry steering committee.
Aims
In undertaking the objectives of the project it is anticipated that this project will
contribute to developing sustainable solutions for IPM and ICM.
Creating a sustainable Brassica industry will ensure economic viability and quality
produce. It will also contribute to enhanced horticultural natural resources by
increasing biodiversity, and by reduction of inputs such as fertilisers, herbicides,
insecticides and fungicides deliver more cost-effective management options.
13
1 BIOASSAY SCREENING OF FIELD POPULATIONS OF
DIAMONDBACK MOTH IN AUSTRALIAN VEGETABLE CROPS
FOR TOLERANCE TO THREE SYNTHETIC INSECTICIDES
AND Bacillus thuringiensis VAR. kurstaki, 2008-10.
Greg Baker and Kevin Powis, South Australian Research and Development Institute
(SARDI).
INTRODUCTION Of the range of insect pests that cause damage to Australian Brassica crops, diamondback
moth (DBM), Plutella xylostella (L.), is the most consistently serious because of its innate
capacity to become resistant to virtually all known insecticides. The project Advancing the
integrated management of diamondback moth (DBM) in Brassica vegetables VG97014 was
responsible for developing the DBM “two-window” insecticide resistance management (IRM)
strategy, which was an international first, and has been successfully adopted in other countries
to help slow resistance development. However, overseas, some DBM populations have
already developed resistance to the newer insecticides Success® and Avatar
®, and screening
studies initiated as part of project National Diamondback Moth project: integrating biological,
chemical and area-wide management of brassica pests VG04004 identified (in a SE QLD
strain) the first-recorded instance internationally of a decline in susceptibility to Proclaim®.
Hence one of the core objectives of this project Developing Sustainable Solutions for
Integrated Brassica Crop Management, VG07030, was to continue monitoring populations of
DBM collected from Australian vegetable crops for their tolerance to the newer insecticides
Success®, Avatar
® and Proclaim
® and to the microbial insecticide Bacillus thuringiensis (B.t.).
High risk DBM populations were targeted as a sentinel activity to provide early warning of
resistance development. The resistance profile information provided by this study is crucial
for the detection of early shifts in tolerance to these commonly-used insecticides, and thereby
to effect early management responses to extend the efficacy of the newer, more IPM-
compatible insecticides and gauge the time available for developing alternative controls. The
results of monitoring activity also assist growers to choose targeted chemical control and
provide cost benefits by reducing the use of those chemicals which are known to be
ineffective.
MATERIALS AND METHODS
DBM Cultures
A susceptible laboratory population of DBM („Waite‟), which has been maintained without
exposure to any insecticides for approximately 18 years, was used as the susceptible reference
strain. Population samples of DBM were collected in 2008 and 2009 from a total of 13
commercial Brassica vegetable crops in the Lockyer Valley (QLD), Sydney Basin (NSW) and
Adelaide Hills (SA) (Table 1). All strains were reared on cabbage seedlings (Brassica
oleracea var. capitata cv. Green Coronet) in the insectary at 25°C (16h L: 8h D). Adult DBM
were provided with 10% honey solution.
14
Table 1: The commercial Brassica vegetable property collection site number, name, location
coordinates, crop type and recent spray records for the 2008 (October 17) and 2009 (October
22) strain collections in the Lockyer Valley, Queensland.
Site
no.
Site name Location ordinates: Crop type Recent spray records
South East
2008:
1 Lowood A 27* 28.047 152*31.656 Cauli Confidor®†
dip, 2 x Decis®, 1
x Lannate®, 1 x Proclaim
®, 1
x Regent®.
2 Lynford 27*28.821 152*27.003 Wombok 3 x Avatar® plus Rogor
®, 3 x
Success® plus Rogor
®.
3 Glenore
Grove
27*30.316 152*24.952 Broccolini 3 x Dominex®, 3 x Bt.
4 Moreton
Vale
27*29.983 152*23.318 Kailan 2 x Fastac®, 1 x Success
®.
5 Lake
Calrendon
27*31.146 152*22.876 Broccolini 2 x Avatar®; 2 x Lannate
®; 1
x Proclaim®.
6 Gatton East 27*33.015 152*18.790 Cauli 3 x Lannate®; 1 x Proclaim
®;
1 x Avatar®.
7 Gatton West 27*34.397 152*15.146 Broccoli 1 x Proclaim®; 1 x Success
®;
1 x Lannate®.
8 Grantham A 27*34.265 152*12.560 Mixed
Brassica
2 x Proclaim®; 2 x Bt.
9 Mt Sylvia A 27*42.556 152*13.385 Broccoli 3 x Bt var aizawai; 2 x
Lannate®; 1 x Lorsban
®.
10 Mt Sylvia B 27*42.556 152*13.385 Cauli 2 x Entrust®; 2 x Bt.
2009:
1 Lowood A 27* 28.053 152*31.646 Cauli
2 Lynford 27*28.694 152*26.837 Cauli
3 Glenore
Grove
27*31.747 152*20.193 Broccolini
4 Moreton
Vale
27*29.983 152*23.318 Broccoli
6 Gatton East 27*32.709 152*18.946 Cauli
7 Gatton West 27*32.860 152*14.859 Broccoli
8 Grantham A 27*34.647 152*11.229 Cabbage/
Cauli
11 Grantham B 27*34.174 152*12.689 Cauli
12 Mt Sylvia C 27*35.443 152*13.844 Cauli
13 Lowood B 27*29.365 152*29.518 Cabbage †Confidor
® ai = imidacloprid; Decis
® ai = deltamethrin; Lannate
® ai = methomyl; Proclaim
®
ai = emamectin benzoate; Regent® ai = fipronil; Avatar
® ai = indoxacarb; Success
® and
Entrust® ai = spinosad; Rogor
® ai = dimethoate; Lorsban
® ai = chlorpyrifos.
15
Insecticides
The insecticides used in this study were Dipel® HG Bio-Insecticide
® (4320 IU mg
-1 Bacillus
thuringiensis subsp. kurstaki, Strain HD-1) supplied by Yates (Orica) Pty. Ltd., Dupont
Avatar®
Insecticide (300 g kg-1
indoxacarb) supplied by Dupont (Australia) Ltd., Proclaim®
Insecticide (44 g kg-1
emamectin benzoate) supplied by Syngenta Crop Protection Pty. Ltd.
and SuccessTM2
NaturalyteTM
Insect Control (240 g L-1
spinosad) supplied by Dow
AgroSciences Australia Ltd..
Bioassays
For the bioassay tests 90 mm diameter leaf discs were cut from washed cabbage leaves taken
from plants that were eight weeks old, and embedded with the underside facing upwards into
setting agar in a 90 mm diameter petri dish. Ten third instar larvae were placed on each leaf
disc, and then each petri dish was placed in a Potter spray tower to administer a precise
deposit 3.60±0.163mg/cm2 of the test insecticide using a 4 ml aliquot of the test solution. The
Potter spray tower was calibrated before and after each trial session.
Each concentration of insecticide that was tested was applied to four replicate dishes, thereby
testing a total of 40 larvae per concentration. Once removed from the Potter spray tower the
dishes were covered with plastic film that was secured with a rubber band. Fine holes were
then punched into the plastic film using a micro needle to allow air exchange. The Potter
spray tower was triple rinsed with AR acetone and RO water between each change in
treatment. The treated petri dishes were then held in an incubator at 250C until mortality
assessment.
All test insecticides were initially used in full dose-response bioassays with the „Waite‟
susceptible reference strain to produce baseline mortality responses. For these bioassays a
stock insecticide solution was made up in a 100 ml volumetric flask, and then specific serial
dilution concentrations were made from this stock.
These baseline mortality datasets with the „Waite‟ strain were then analysed by probit
analysis to determine the discriminating dose (DD, the dose that killed 99% of 3rd
instar
„Waite‟ strain larvae) for each chemical.
The F0-F3 generation of the field strains were then challenged with the DD, 5xDD and
10xDD of each test insecticide. It is generally accepted that up to a 5x variability of tolerance
can exist due to natural fitness when compared to a susceptible population, but considered of
concern when tolerance levels of screened populations significantly exceed the 5xDD test
rate. Hence if greater than 5.0% of test larvae survived the 5xDD, the strain was subsequently
tested in a full dose-response bioassay. The 10xDD results were used to help decide the
appropriate dose range for the full dose-response bioassay.
16
Larval mortality was assessed at 48, 48, 72 and 96 hours post-treatment for Dipel®,
SuccessTM2
, Proclaim®
and Avatar® respectively, as these times were each found to provide
the best measure of mortality, and were therefore adopted as the time interval for assessment.
Analysis
Probit analyses on the dose-mortality data were conducted using POLOPLUS, and the doses
at which 50% (LC50) and 99% (LC99) mortality occurred were calculated. Differences in
susceptibility between strains were considered significant when the 95% CL of LC50 values
did not overlap. Resistance ratios (RR) were calculated by dividing the LC50 or LC99 of a field
population by the corresponding LC50 or LC99 for the „Waite‟ susceptible strain.
RESULTS
Table 2. The percentage mortality of 3rd
instar DBM larvae, collected from various
commercial Brassica vegetable crops in the Lockyer Valley, QLD and Sydney Basin, NSW,
2008-10, and exposed to the discriminating dose (DD), 5xDD and 10xDD of SuccessTM2
,
Proclaim® and Avatar
®.
Population*
G
% Mortality
Success® Proclaim®
Avatar®
DD 5 x DD 10 x DD DD 5 x DD 10 x DD DD 5 x DD 10 x DD
1 (2008) F0 90.5 100 100 88.1 100 100 94.8 100 100
3 (2008) F0 85.0 100 100 84.3 89.5 100 100 100 100
5 (2008) F0 87.5 100 100 82.4 100 100 95.1 100 100
6 (2008) F0 60.0 100 100 72.3 92.5 100 87.5 100 100
7 (2008) F0 85.0 100 100 95.0 100 100 87.5 100 100
2 + 4 (2008) F0 72.5 95.0 100 92.5 100 100 95.0 100 100
8 + 9 + 10 (2008) F0 57.5 97.5 100 70.0 90.2 100 76.3 100 100
1+2+3+4+6+7+8+11+12
+13 (2009)
F3 39.0 100 100 41.5 90.9 90.2 77.5 93.0 100
Werombi A (Syd Basin)
(2010)
F0 57.5 97.5 100 85.0 87.5 92.5 72.5 100 100
Werombi B (Syd Basin)
(2010)
F1 95.0 100 100 87.5 100 100 61.9 85.0 100
*The numbers are the property site numbers given in Table 1. Note that the populations collected from some
properties were combined because of the low number of DBM that were able to be collected at these sites.
17
Table 3. The percentage mortality of 3rd
instar DBM larvae, collected from various
commercial Brassica vegetable crops in the Lockyer Valley, QLD and Sydney Basin, NSW,
2008-10, and exposed to the discriminating dose (DD), 5xDD and 10xDD of Dipel® HG Bio-
Insecticide®.
Population*
G
% Mortality
DD 5 x DD 10 x DD
1 (2008) F0 97.5 100 100
3 (2008) F0 97.6 100 100
5 (2008) F0 93.5 100 100
6 (2008) F0 95.3 100 100
7 (2008) F0 95.0 100 100
2 + 4 (2008) F0 100 100 100
8 + 9 + 10 (2008) F0 100 100 100
1+2+3+4+6+7+8+11+12+13 (2009) F3 97.6 100 100
Werombi A (Syd Basin) (2010) F0 97.5 100 100
Werombi B (Syd Basin) (2010) F1 100 100 100
In September 2008 David Carey of QLD DEEDI collected DBM larvae and pupae from ten
commercial Brassica vegetable properties in the Lockyer Valley in SE QLD and mailed them
to SARDI Entomology, Waite Campus, where they were set up in rearing cages for
subsequent resistance screening. However the DBM field densities in the Lockyer Valley
were generally low in 2008, and as a result the numbers of DBM collected from several of the
properties were quite low. As a result we had to combine several of the field strains,
according to geographic proximity, leaving a total of eight strains for bioassay testing.
In October 2009 David Carey again collected and forwarded to SARDI DBM larvae and
pupae from ten commercial Brassica properties in the Lockyer Valley. Field collecting again
proved difficult because the field densities of DBM were generally low, and water restrictions
had lowered the number of growers growing Brassica crops compared to previous season.
Because of the low numbers of DBM collected at each property, to establish a viable lab
culture we unfortunately had to combine all ten collections into the one 2009 culture strain.
In February 2010 Andy Ryland of the Beneficial Bug Company was able to collect and
forward to SARDI DBM larvae from two commercial Brassica properties in the Sydney
Basin.
The discriminating dose bioassay results for these field strains are presented in Tables 2 and
3. As had been found in the 2006 and 2007 surveying of Lockyer Valley Brassica vegetable
populations of DBM, there were a significant number of strains in which some tolerance to
the three synthetic insecticides, relative to the susceptible „Waite‟ strain, was observed. Of
the ten Lockyer Valley and Sydney Basin strains tested in this study, greater than 5.0% larval
survivorship occurred with nine, nine and seven strains when tested with the DD of
SuccessTM2
, Proclaim® and Avatar
® respectively. In turn, greater than 5.0% larval
18
survivorship occurred with nil, five and two strains when tested with the 5xDD of SuccessTM2
,
Proclaim® and Avatar
® respectively, and greater than 5.0% larval survivorship occurred with
nil, two and nil strains when tested with the 10xDD of SuccessTM2
, Proclaim® and Avatar
®
respectively. By contrast, there was no larval survivorship at the 5xDD of Dipel®.
The full-dose response bioassay results for the „Waite‟ susceptible reference strain, the 2008
Lockyer Valley strains, the 2009 „combined‟ Lockyer Valley strain and the 2010 Sydney
Basin strains are presented in Tables 4-7 respectively. In general, these full-dose response
bioassays revealed similar tolerance ratios in these strains collected between September 2008
and February 2010 compared with the previous strains collected and tested in 2006-07 (see
results presented in VG04004 Final Report).
DISCUSSION
These data provide clear evidence of the maintenance of significant tolerance in field
populations of DBM to the important DBM insecticides Proclaim®, Success
TM2 and Avatar
®.
These insecticides have now been used in Australian Brassica vegetable production for almost
ten years.
Although the observed tolerance levels to Proclaim®, Success
TM2 and Avatar
® of most of the
DBM field strains tested in this study are not yet at the point where DBM field control
failures are likely, some of the recorded shifts in susceptibility to these chemicals are
concerning. If we take into account that field spray coverage is generally poor compared to
the laboratory conditions in which these resistance ratios were measured, it is likely that there
may soon be control failure with the use of Proclaim® against some populations of DBM in
the Lockyer Valley. For example, the DD: field use rate ratio for Proclaim® is 60:1. What
this suggests is that the DBM field strain with the 57:1 resistance ratio at the DD (ie. LC99) is
approaching a point where good field control with Proclaim® may be difficult, and ideally
Proclaim® would not be used at this (or for that matter the other two field sites with 21:1 and
19:1 resistance ratios) for the next several years to allow the susceptibility of these DBM
populations to this product to increase back towards pre-selection levels.
In recent years Proclaim® and Success
TM2 have been the lepidopteran insecticides most
commonly used by Gatton vegetable growers (Tim O‟Grady, Bayer, pers. comm..), and this is
perhaps being reflected in these bioassay data. Following the registration of the new Group
28 diamide chemistry (Belt® and Coragen
®) in early 2009, considerable grower usage of these
Group 28 products has occurred. This appears to have reduced the frequency of Proclaim®,
SuccessTM2
and Avatar® usage, which may have helped slow the rate of further decline in
DBM susceptibility to these three insecticides.
Although these results are for Lockyer Valley and Sydney Basin strains of DBM only, they
provide a clear forewarning that varying levels of resistance will be developing in other
Australian Brassica vegetable production areas where these insecticides have now been used
for eight to ten years.
19
The lack of evidence of any significant or incipient change in tolerance to Bacillus
thuringiensis subsp. kurstaki is encouraging, but may reflect the relatively low rate of usage
of Bt products amongst the surveyed growers (Table 1).
These resistance screening findings and the best-practice” IRM messages (which include the
“two-window” CropLife rotation strategy) have been publicized nationally to growers and
other industry stakeholders through several fora. These include the Brassica IPM Newsletter,
presentation by David Carey directly to Lockyer Valley growers, and finally in a national tour
(QLD, TAS, NSW, VIC, SA and WA) in July-August 2010 to growers and consultants in
nine production areas (Greg Baker‟s Powerpoint presentation for the July-August 2010
meetings is attached).
As a result of the registration of two new DBM insecticides in 2009 (the IRAC Group 28
diamides Coragen® (rynaxypyr) and Belt
® (flubendiamide)), the CropLife DBM Two-window
IRM strategy was updated, and new glossy flyers of the three regional versions of the strategy
were distributed to Brassica growers nationally. These two new insecticides have high–level
lepidopteran insecticidal activity, a unique mode of action and appear to be very selective and
„soft‟ to virtually all beneficials. Greg Baker addressed the CropLife Insecticide Resistance
Action Committee on the findings of this project research on 29 April 2010, and discussed the
updated DBM “two-window” IRM strategy and the concerns about managing the increased
resistance risk to the new Group-28 insecticides presented by the new seedling-drench
product Durivo® (chlorantraniliprole plus thiamethoxam) (The Powerpoint presentation is
attached). The proposed use of this product as a nursery-applied seedling drench, the risk that
it presents to the management of resistance to this valuable Group 28 chemistry, and a
proposed strategy in which Durivo® usage is limited to the Group 28 window was also
presented and discussed at the July-August 2010 grower meetings.
Finally, a paper† which reports on a section of this project work, was recently published in the
Journal of Economic Entomology.
†Rahman, M. M., Baker, G.J., Powis, K. J., Roush, R. T. and Schmidt, O. (2010) Induction
and transmission of tolerance to the synthetic pesticide emamectin benzoate in field and
laboratory populations of diamondback moth. Journal of Economic Entomology 103 (4):
1347-1354.
20
Table 4. The LC50 and LC99 estimates (and 95% confidence limits) and slope of the Probit regression line of best fit for 3rd
instar DBM larvae of the
„Waite‟ susceptible reference strain, and the three synthetic insecticides Success®, Proclaim
® and Avatar
® and Bacillus thuringiensis subsp. kurstaki HD-1
strain.
Strain Chemical LC50† 95%CL
† LC99
† 95%CL
† Slope+/-S.E n.
†††
Total n. tested
Waite Susceptible Success® 0.00025 0.00022-0.00029 0.001 0.00074-0.0016 3.87+/-0.462 40 200
(reference strain) Proclaim® 0.000097 0.000082-0.00011 0.00045 0.00033-0.00074 3.46+/-0.405 40 200
Avatar 0.0012 0.00096-0.0014 0.0078 0.0054-0.013 2.80+/-0.303 40 242
Bt 29.68 27.94-37.72 527.1 320.5-1085.6 1.86+/-0.191 40 800 †All concentration values for the three synthetic insecticides are expressed as percent product. The concentration values for Bt are expressed as parts per million.
††
RR is the resistance ratio (see methods). †††
n. is the number of larvae tested per treatment.
Table 5. The LC50 and LC99 estimates (and 95% confidence limits), the resistance ratios (RR) and the slope of the Probit regression line of best fit for 3rd
instar larvae sourced from four DBM strains collected from the Lockyer Valley, QLD in September 2008, assayed with two synthetic insecticides, Success®
and Proclaim®.
Population* Chemical LC50† 95%CL
† RR
†† LC99
† 95%CL
† RR
†† Slope+/-S.E n.
†††
Total n. tested
2 + 4 Success® 0.00065 0.00051-0.00082 2.5 0.016 0.0094-0.0338 9 1.67+/-0.157 40 359
8 + 9 + 10 Success® 0.00081 0.00066-0.00099 3.1 0.00924 0.00611-0.01648 5.2 2.20+/-0.204 40 360
Proclaim® 0.00034 0.00025-0.0005 5.4 0.026 0.0107-0.0974 56.5 1.24+/-0.121 40 361
3 Proclaim® 0.00029 0.00019-0.0004 4.6 0.00974 0.00606-0.0199 21.2 2.08+/-0.238 40 362
6 Proclaim® 0.00057 0.00042-0.00074 9 0.00869 0.00517-0.0192 18.9 1.96+/-0.202 40 363
* The numbers are the property site numbers given in Table 1. All were tested at F1 generation. †All concentration values for the two synthetic insecticides are expressed as percent product.
††RR is the resistance ratio (see methods).
†††n. is the number of larvae tested per treatment.
21
Table 6. The LC50 and LC99 estimates (and 95% confidence limits), the resistance ratios (RR) and the slope of the Probit regression line of best fit for 3rd
instar larvae sourced from four DBM strains collected from the Lockyer Valley, QLD in October 2009, assayed with three synthetic insecticides Success®,
Proclaim® and Avatar
® and Bacillus thuringiensis subsp. kurstaki HD-1 strain.
Population* Chemical LC50† 95%CL
† RR
†† LC99
† 95%CL
† RR
†† Slope+/-S.E n.
†††
Total n. tested
Combined Success® 0.00027 0.00021-0.00034 1.1 0.0045 0.00282-0.00886 4.5 1.913+/-0.198 40 320
(1+2+3+4+6+7+8+11+12+13) Proclaim® 0.0004 0.00031-0.00051 4.1 0.0102 0.006-0.0213 22 1.657+/-0.161 40 320
Avatar 0.0043 0.0031-0.0055 3.6 0.0657 0.0396-0.1461 8.4 1.964+/-0.247 40 280
Bt 21.014 15.935-25.713 0.7 140.3 96.333-268.485 0.3 2.821+/-0.417 40 358
* The numbers are the property site numbers given in Table 1. Tested at F4 generation. †All concentration values for the three synthetic insecticides are expressed as percent product. The concentration values for Bt are expressed as parts per million.
††RR is the resistance ratio (see methods).
†††n. is the number of larvae tested per treatment.
Table 7. The LC50 and LC99 estimates (and 95% confidence limits), the resistance ratios (RR) and the slope of the Probit regression line of best fit for 3rd
instar larvae sourced from four DBM strains collected from the Sydney Basin, NSW in February 2010, assayed with three synthetic insecticides Success®,
Proclaim® and Avatar
® and Bacillus thuringiensis subsp. kurstaki HD-1 strain.
Population* Chemical LC50† 95%CL
† R.F LC99
† 95%CL
† R.F Slope+/-S.E n.
†††
Total n. tested
Werombi A Success® 0.00068 0.00055-0.00083 2.7 0.00843 0.00557-0.01501 8.4 2.123+/-0.194 40 360
Proclaim® 0.00046 0.00034-0.00061 4.7 0.00467 0.00278-0.01083 10 2.311+/-0.218 40 360
Avatar 0.00306 0.00242-0.00371 2.6 0.0237 0.016-0.0445 3 2.614+/-0.333 40 286
Bt 33.28 24.72-42.31 1.1 520.19 318.85-1121.76 1 1.948+/-0.239 40 321
Werombi B Avatar 0.016 0.0099-0.021 13.3 0.196 0.119-0.508 25 2.136+/-0.367 40 204
Proclaim® 0.000208 0.000163-0.000258 2.1 0.00269 0.00172-0.00529 6 2.094+/-0.235 40 287
* Werombi A tested at F1 generation, Werombi B tested at F2 generation. †All concentration values for the three synthetic insecticides are expressed as percent product. The concentration values for Bt are expressed as parts per million.
††RR is the resistance ratio (see methods).
†††n. is the number of larvae tested per treatment.
22
23
24
25
26
27
28
2 EVALUATION OF SOIL AMENDMENTS FOR BRASSICA
PRODUCTION SYSTEMS C. Paull (SARDI)
Introduction Incorporating recycled soil amendments into horticultural systems can have a number of
benefits. In response to growers‟ questions and consultation with other researchers in the
Brassica industry, the application of soil amendments and their potential to complement and
contribute to sustainable Brassica production were investigated within the following three
subsections of this chapter:
2.1 The effect of compost on invertebrates in Brassica production systems
2.2 The effect of compost on white blister
2.3 Benefits of using compost within Brassica vegetable production systems
Sites
All of the experimental work for objective two of this project was conducted at the following
two field sites in South Australia: (1) Lenswood Research Station (LRS) consisted of four
plots, each 16 m x 4 m, two plots with and two without compost; (2) Gumeracha within a
commercial cauliflower production system, six 200m x 1m beds were used, three beds with
and without compost. Each bed was divided into four 50m sub-plots. Compost was spread at a
rate of 170 cubic metres per hectare at both sites and incorporated into the top 7-10 cm of the
existing soil.
Compost
The compost used was a 100% composted green organic waste. Supplied by Jefferies, the
commercial product is produced under quality control and complies with the industry
standard.
29
2.1 THE AFFECT OF COMPOST ON DIVERSITY OF
INVERTEBRATES IN BRASSICA PRODUCTION SYSTEMS. C. Paull (SARDI)
Introduction Invertebrates have been shown to be important in providing and contributing to a number of
key ecosystem services and processes including decomposition, decay of plant material and
subsequent recycling of carbon and nutrients (Hattenschwiller and Gasser 2005), and pest
control (Langellotto and Denno 2004, Bell et al 2008).
However, we know little about specific invertebrate species involved in these processes or
how the application of compost affects the presence and/or abundance of functional groups of
invertebrates in brassica crops such as detritivores, pests and/or predators.
The aims of this research were to determine what effect compost has on the diversity and
abundance of invertebrates with in a brassica vegetable production system. In particular, the
invertebrates that are associated with decomposition of post-harvest brassica residue and the
effects of compost on the pest and predator invertebrates .
Invertebrates - Affect on decomposition:
Post harvest brassica residue is associated with harbouring spores of fungal diseases such as
Albugo candida (white blister; see section 2.2). To determine which invertebrates were
associated with the decomposition of harvested brassica residue over time (and hence which
maybe useful for reducing associated disease pressure), the following experiment was
conducted:
Method:
Decomposition samples consisted of a single piece of harvested cauliflower stem (110gm)
(ordinarily left as post harvest residue). This stem tissue was collected immediately after the
harvest of a commercial cauliflower crop at site 1.
Tissue samples were placed on the soil surface, in three different types of plastic container:
1) PVC tubing, 2) polynet mesh bags and 3) nylon stocking. The containers effectively
excluded different sizes of invertebrates allowing the subsequent collection and measurement
of invertebrates of various size-groups and their relative contribution to decomposition. Mesh
sizes of the polynet and stockings were 1cm 2
and 0.5 mm 2, respectively, providing exclusion
of invertebrates above these sizes. PVC tubing was of 4cm a diameter to allow entry of all
invertebrates. To further understand whether or not post harvest residue would decompose
more completely if the cauliflower was buried, a second group of samples were also buried to
a depth of 7cm.
Two replicates of each of the following six combinations of traps were set up at each of the
four plots at site 1 and four replicates of each were set up at site 2.
1 Cauliflower stem - stocking- surface
2 Cauliflower stem -stocking -buried
3 Cauliflower stem - polynet - surface
4 Cauliflower stem - polynet -buried
5 Cauliflower stem - PVC pipe - surface
6 Cauliflower stem - PVC pipe - buried
Decomposition trials started three weeks after the compost had been spread at sites and the
cauliflower seedlings had been transplanted. Ninety six samples were placed in the field at
site 1 on July 9th 2008 and 192 samples were put in to the field at site 2 on August 13th 2008.
30
At both sites, decomposition samples were randomly placed within the two treatments
(compost or no compost); 4 samples of each type and position were retrieved every month for
four months (96 samples at site 1 and 192 samples at site 2).
After four weeks the first samples were removed from the field sites and, individual samples
were placed in zip-lock bags. Samples were transferred to a laboratory where the cauliflower
pieces were removed from their containers and weighed. The cauliflower and contents of each
bag were then placed in separate Tullgren funnels and the invertebrates extracted over seven
days and stored in 70% alcohol.
Invertebrates were identified to morphospecies and attributed a putative ecological function
by combining information from the literature and identifying morphological characters such
as mouthparts.
To determine what invertebrates were already in the compost when it was delivered, five x
500 gram samples of compost were collected when it was delivered at each of the sites, and
prior to the beginning of the experiment.
Pests:
To determine if there was any influence of compost on pests, such as Plutella xylostella,
diamondback moth (DBM), 15 random cauliflower plants were sampled (searched) from
each of the treatments once a week from August 18th 2008 until harvest .
Data analysis:
The large amount of variation between samples meant that to perform a meaningful statistical
analysis samples had to be pooled across decomposition trap types, periods and sites.
Descriptive statistics have been used to highlight general findings.
Diversity and abundance between treatments was calculated using the Shannon index H′
diversity and J′ evenness used to determine how the abundance of individuals was distributed.
The non-parametric Kolmogrov Smirnov (KS) test was used to test the significance of
differences in diversity between compost and control treatments for each site.
Results:
Taxonomic Classification:
The results of the Tullgren funnel extraction show that over 20,000 individual invertebrates
were extracted from 288 samples. From these, 146 morphospecies were identified (Appendix
1) and included representatives of 18 orders and 54 families.
When the total number of species were compared at an order level, Coleoptera (beetles) was
the most diverse order contributing to 33% of the 149 morphospecies (Fig 1). Fourteen orders
were each represented by 5% or less of morphospecies.
Invertebrate Functional groups:
To determine what impact different invertebrate populations have on an ecosystem, they are
sometimes divided into functional groups. A functional group is a group of organisms that
perform a similar ecological function in an ecosystem. For example, the majority of
nematodes recovered from this study were bacterial feeders and all Neuroptera were
predatory. Through out this study the functional group other refers to morphospecies that
were polyphagous /omnivorous and unconfirmed were those morphospecies where the
functional group remained undetermined.
The division of morphospecies into orders and the proportion of each order by ecological
function is shown in Figs. 1 and 2, respectively. This shows that morphospecies collected
from orders such as Diptera (flies), Collembola (springtails), Annelida (earth worms) and
31
some Acarina (mites) and Nematode (nematodes), were mostly detritivores, and therefore
may play a role in decomposition of plant material.
Acarina
11%
Diptera
27%
Hymenoptera
6%
14 orders each
less than 5%
morphospecies
23%
Coleoptera
33%
Figure 1 Proportion of all collected morphospecies by invertebrate order.
0% 20% 40% 60% 80% 100%
Acarina
Annelida
Araneae
Chilopoda
Coleoptera
Collembola
Dermaptera
Diptera
Hemiptera
Hymenoptera
Isopoda
Lepidoptera
Mollusca
Nematoda
Neuroptera
Psocoptera
Thysanoptera
Tricladida
Ord
er
Detritivores
Predators
Other
Pests
Unconfirmed
Figure 2 Proportion of morphospecies within orders by ecological function.
32
In direct comparison to the high diversity of beetles were the orders Acarina and Collembola,
which were the least diverse but contributed most to the total number of invertebrates at each
site and for each treatment. Not only were they some of the most abundant morphospecies
they were also decomposers, detritivores. For example at site 1, six morphospecies
contributed to over 93% of the arthropods collected from plots without compost (Fig 3 ) and
85% of the arthropods from the plots with compost (Fig 4).
0102030405060708090
100
Dip
tera
Sp
ha
ero
ce
rid
ae
ms
18
Aca
rin
a m
s 4
9
Ne
ma
tod
a m
s 5
Aca
rin
a m
s 9
5
Aca
rin
a/C
arp
og
lyp
hid
ae
ms 3
0
Co
lle
mb
ola
ms 5
1
%
Figure 3 The six most abundant morphospecies as a percentage of the total number of
individuals collected from the treatments without compost at site 1. The letters ms followed
by a number refers to the morphospecies reference number.
0102030405060708090
100
Dip
tera
/S
ca
top
sid
ae
ms 1
6
Aca
rin
a m
s 7
5
Dip
tera
/Cyclo
rra
ha
ph
a m
s 6
3
Aca
rin
a m
s 4
9
Aca
rin
a/C
arp
og
lyp
hid
ae
ms 3
0
Co
lle
mb
ola
ms 5
1
%
Figure 4 The six most abundant morphospecies as a percentage of the total number of
individuals collected from the compost treatments at site one.
33
Similarly, at site 2 only six morphospecies contributed over 89% of the arthropods collected
from samples from the plots without compost (Fig 5) and 90 % from the plots with compost
(Fig 6). Comparison of these graphs, i.e. Fig 3 versus Fig 4 and (Fig 5 versus Fig 6, suggests
that compost increases the abundance of the mite family Carpoglyphidae.
0102030405060708090
100
Aca
rina/
Ora
batid
ms 35
Aca
rina/
Orib
atid
97
Collem
bola
Aca
rina
ms 49
Aca
rina/
Car
pogl
yphi
dae
Nem
atod
a m
s 5
%
Figure 5 Six most abundant morphospecies as a percentage of the total number of individuals
collected from the treatments with out compost at site 2.
0102030405060708090
100
Ann
elida/
Olig
ocha
eta
Collem
bola
Aca
rina
ms 75
Aca
rina
ms 49
Aca
rina/
Car
pogl
yphi
dae
Nem
atod
a m
s 5
%
Figure 6 Six most abundant morphospecies as a percentage of the total number of individuals
collected from the treatments without compost at site 2.
34
At site 2, there were a greater percentage of individuals collected from the compost treatment compared to non compost, at every sample time after the first month (Fig 7).
0
500
1000
1500
2000
2500
3000
3500
4000
4500
Sep-08 Oct-08 Nov-08 Dec-08
Nu
mb
er
of in
ve
rte
bra
tes
No Compost
Compost
Figure 7 Total number of arthropods in samples, each month, from compost and non compost
treatments, at site 2.
Detritivores:
Having determined the most abundantly dominant morphospecies were detritivores, it was of
interest to understand if the compost is having any effect on detritivores. Therefore, we
analysed key groups of detritivores with respect to their relative abundance between
treatments. The results showed that at both sites, there were an increased number of Acarina
(specifically Carpoglyphidae), Annelids and Coleoptera in the compost samples (Figures 8
and 9).
0
10
20
30
40
50
60
70
80
90
100
Acarina
Carpoglyphidae
Annelids Collembola Coleoptera Diptera
Detritivores
%
Compost
No Compost
Figure 8 Major groups of detritivores and the relative percentages of each, sampled from
each treatment at site 1.
35
0
10
20
30
40
50
60
70
80
90
100
Aca
rina/
Orib
atids
Aca
rina/
Car
poglyp
hida
e
Ann
elids
Coleo
pter
a
Collem
bolla
Diptera
Nem
atod
es
Detritivores
% A
bu
nd
an
ce
Compost
No Compost
Figure 9 Major groups of detritivores and the relative percentages of each, sampled from
each treatment at site 2.
Pests:
Determining which morphospecies were pests was done subjectively in the context of brassica
vegetable production. For example, although some of the invertebrates may be seen as pests
in a different context, snails and Plutella xylostella diamondback moth (DBM) were the only
pests relevant to brassica production and their numbers were very low. A total of 11 snails
were sampled from site 2 (seven from the compost treatment and five from the control
treatment). The numbers of DBM larvae per plant were low and did not exceed an average
2.25 larvae per plant, in either the composted or non composted treatments. However there
were more DBM larvae in the plants from the compost treated bays up until just before
harvest when the numbers of larvae from each of the treatments were similar (Fig 10).
0
1
2
3
4
5
6
13/10/2008
20/10/2008
27/10/2008
3/11/2008
10/11/2008
17/11/2008
24/11/2008
No
DB
M la
rva
e p
er
pla
nt (m
ea
n)
Compost
No Compost
Figure 10 The mean number of DBM larvae per plant from each treatment at site 2 (n =15).
36
Predators:
Similar to the detritivore analysis, to understand if the compost was having any effect on
predators we looked at key groups of predators and compared their abundance between
treatments for site 2 (Fig 11). There were approximately three times more spiders (Araneae)
two times Carabid beetles (predatory) and 5% more Staphylinid beetles (also predatory),
collected from samples from the compost plots compared samples with no compost. There
were only two morphospecies of spider collected from the decomposition samples and 99% of
these individuals were tiny Linyphiids.
0
10
20
30
40
50
60
70
80
90
100
Araneae Chilopoda Coleoptera
Carabidae
Coleoptera
Staphylinidae
Hymenoptera
Predators
%
Compost
No Compost
Figure 11 Major groups of predatory invertebrates and the relative percentages of each,
sampled from each treatment at site 2.
Diversity – Compost vs No Compost:
At each site the Shannon diversity index (H′) for the compost treatments is greater than for the
non composted, indicating that the compost may be associated with greater diversity and
abundance of invertebrates (Table 1). Results of the KS test support this and show that the
difference in diversity between the two treatments at each site was significant. These results
are also reflected in the cumulative frequency distribution for all of the species (Figs 12 and
13). These graphs show the small number of species that contribute most of the specimens
collected at each site and for each treatment, and also reflect the comparative evenness (J′ )
between treatments for each site.
Table 1 Statistical measure of invertebrate diversity and evenness of different treatments, for
each site (* represents a significant result).
Compost No Compost D Max D critical
Site One
H′ 1.84 1.39 0.194 0.023 *
J′ 0.45 0.35
Site Two
H′ 1.94 1.63 0.152 0.026 *
J′ 0.42 0.36
Shannon diversity index H′ =diversity J′ =evenness
Kolmogorov Smirnov test significant at P < 0.05
37
Site One
0
10
20
30
40
50
60
70
80
90
100
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61
Species Rank
Cu
mu
lati
ve
Pe
rce
nt
% Compost
No Compost
Figure 12 Cumulative frequency distribution of ranked species from most to least abundant at
Site 1.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
10
0
rank
Cu
mu
lati
ve
%
Compost
No Compost
Figure 13 Cumulative frequency distribution of ranked species from most to least abundant
Site 2.
38
Decomposition:
The mean weight of the cauliflower tissue that remained after samples were removed from the
field is presented (Figs 14a, b and c). Samples that were initially buried maintained their
weight for a longer period compared to samples placed on the soil surface. After three months
none of the samples were recognisable as pieces of cauliflower, and by the forth sampling
period all had reached a similar advanced state of decomposition and weighed less than 5
gms.
a
0
20
40
60
80
100
120
1 2 3 4
Time -Months
Me
an
we
igh
t o
f sa
mp
le g
m
NS COMP
NS
NB COMP
NB
b
0
20
40
60
80
100
120
1 2 3 4
Time - Months
Me
an
we
igh
t o
f sa
mp
les g
m
SS COMP
SS
SB COMP
SB
c
0
20
40
60
80
100
120
1 2 3 4
Time - Months
Mean w
eig
ht of sam
ple
s g
m
PS C OMP
PS
PB C OMP
PB
Figure 14 Mean weight of decomposition samples over time for samples in a) polynet, b)
stocking and c) PVC pipe. S = samples from surface of soil, B = buried samples and COMP
= samples from composted treatments (n = 4). Due to the variation error bars were not added.
Time one = one month after August 13th 2008, the start of the experiment.
39
Discussion:
Of the 149 morphospecies identified in this study the majority were characterised as
detritivores. There was a greater diversity of morphospecies from the compost treatments
compared to treatments without compost, and this was statistically significant for both sites.
Results from sampling plants show that even though the average numbers of DBM larvae per
plant were low there were more DBM from the compost treatment midway through the
development and growth of the cauliflower crop. Numbers of DBM larvae did not exceed an
average of 2.25 per plant and numbers of larvae per plant for each of the treatments were
similar at harvest. There is some evidence that compost can affect above-ground pest and prey
interactions and abundance. For example, one study linked decreased aphid populations when
the predators were in high abundance, to areas where compost had been applied (Bell et al
2008). However, there could be many interacting variables that can affect such interactions
and there was no such link evident from this study. This is due in part to the focus of the study
on decomposition as opposed to predator/prey interactions.
The compost significantly affected the abundance of a small number of morphospecies, most
notably the mites, Collembola and earthworms each of which are regarded as important for
decomposing plant material. There was some indication that as compost increased the
abundance of groups of detritivores and therefore may have a beneficial use in promoting
invertebrate-mediated decomposition of disease-laden plant material. Previous work has
shown Collembola and earthworms to respond to fresh organic matter (Brady and Weil
1999),we are not aware of any work undertaken to see if they contribute to the suppression of
soil borne pathogens. Morphospecies from site 2 (a commercial property) may be a better
reflection of industry-relevant diversity and abundance, as this site has been under continual
cultivation for a longer period compared to site one, which was fallow for two years prior to
this study.
Compost and predators:
Interestingly, previous work has shown that the diet of the tiny Linyphiid spiders (belonging
to the sub family Erigoninae) is made up mainly of Collembola, small flies and homopteran
bugs (Nyffeler 1999). The detection of some of these organisms in coexisting populations in
this study may indicate the same trophic interaction is occurring at the study sites.
Amongst the most abundant Coleopteran morphospecies were tiny Staphylinidae belonging to
the subfamily Alocharianae Adult Alocharianae are known to prey on fly maggots including
the pest Delia radicum (cabbage root fly) the larval stage of alocharine beetles are parasitic on
fly pupa (Balog et al 2008).
Conclusion:
Results from this work have provided a valuable insight into the diversity of predominately
soil detritus dwelling arthropods. The results show that the application of compost not only
increases diversity of arthropods but also their abundance. Although an increase in abundance
was only evident in a small number of morphospecies, all were detritivores that may play an
important role in decomposition of plant material which can potentially harbour brassica
diseases.
There was no evidence to suggest that post-harvest residues were decomposed to a greater
degree if buried or left on the soil surface. The application (or not) of compost also had no
effect on relative levels of decomposition. However, results did indicate that it takes at least 4
months for stems left after postharvest of cauliflower, to decompose.
What still remains unknown are establishing indicative ratios for interspecific interactions; for
example, what might be more instructive is the ratio of Alocharianae compared to fly larvae.
If such a ratio is similar in compost as it is without compost, this could represent what is
40
refererred to as a zero sum gain. Another key area of research is to identify which invertebrate
groups are most efficient at decomposing plant material and if there is any specificity with
regard to this (e.g. do some species decompose brassicas more efficiently than others, or show
preference for brassicas). These data would allow commercial brassica production systems to
be tailored to advantage the species providing most benefit. In addition, it would allow testing
of the effect of different compost types and application regimes.
The lack of complete information or research opportunity makes it difficult to provide
specific management recommendations that can be enacted with confidence. However, there
is no evidence from this study to suggest there are any negative effects in relation to
arthropods from adding compost which provides a range of established benefits such as
nutrition, soil structure and moisture conservation.
Acknowledgements:
We would like to acknowledge the generous support and in-kind contribution from the
Newman family for access to their property and constructive discussions, and Jefferies Soils
for the supply and delivery of over 50 m3 of compost to the experimental sites. Also, thanks
go to staff at the Lenswood Research Centre and Dr. Peter Crisp for advice on soil moisture
measurement, soil sample analysis and mite identification.
References:
Balog, A., V. Marko, et al. (2008). Patterns in distribution, abundance and prey preferences of
parasitoid rove beetles Aleochara bipustulata (L.) (Coleoptera : Staphylinidae, Aleocharinae)
in Hungarian agroecosystems. North-Western Journal of Zoology 4(1): 6-15.
Bell, J. R., M. Traugott, et al. (2008). Beneficial links for the control of aphids: the effects of
compost applications on predators and prey. Journal of Applied Ecology 45(4): 1266-1273.
Brady, N. C. and Weil, R.R. 1999. Organisms and ecology of the soil. In The Nature and
Properties of soils. Pp 404-445. Brady, N.C., Weil, R.R., Eds., Prentice Hall New Jersey.
Cassagne, N., C. Gers, et al. (2003). Relationships between Collembola, soil chemistry and
humus types in forest stands (France). Biology and Fertility of Soils 37(6): 355-361.
Hattenschwiler, S. and P. Gasser (2005). Soil animals alter plant litter diversity effects on
decomposition. Proceedings of the National Academy of Sciences of the United States of
America 102(5): 1519-1524.
Nyffeler, M. (1999). Prey selection of spiders in the field. Journal of Arachnology 27(1):
317-324.
Langellotto, G. A. and R. F. Denno (2004). Responses of invertebrate natural enemies to
complex-structured habitats: a meta-analytical synthesis. Oecologia 139(1): 1-10.
41
2.2 THE EFFECT OF COMPOST ON WHITE BLISTER
C. Paull and L. Salehi (SARDI)
Background:
White blister (WB), Albugo candida, has emerged as a serious fungal disease of Brassicas.
One of the key strategies for reducing the prevalence of this disease is the use of resistant
Brassica varieties, despite some evidence to suggest that the resistance of some of these
varieties may be beginning to break down (Liz Minchinton pers. comm.). A review of the
literature shows that there are conflicting data regarding the efficacy of compost application
in reducing or controlling soil borne pathogens (Hoitink and Fahy 1986; Noble and Coventry
2005) however, to date no work has been undertaken to see what effect compost has on WB.
Determining the effect compost has on WB however has been challenging primarily because
white blister is an obligate parasitic oomycete which makes culturing it difficult. The primary
inoculum of WB consists of oospores which are soil borne or carried on plant material as a
contaminant. These oospores are known to survive for long periods; 10-20 years under dry
conditions (Rimmer et al 2007). After brassica crops are harvested, a large amount of post-
harvest residue remains which can harbour pathogens such as WB. The fact that WB is related
to brassica post-harvest crop residue means that any experimental method should reflect
decomposition of the disease under field conditions. Based on this information we decided to
monitor for WB using fresh plant material collected from infected broccoli.
Before we could quantify what effect compost has on white blister we needed to develop a
method that would accurately measure the disease. Quantitative assessment of a disease
ordinarily requires the development of a dose-response curve (used a reference) for a
particular measurement technique which is produced by inoculating a substrate of interest
with a solution of a known concentration of pathogen. We engaged the help of the SARDI
soil and plant health division who developed a quantitative PCR (qPCR) which we were able
to use to accurately quantify the amount of WB in any substrate including the experimental
samples.
As part of the research to investigate the benefits of compost in brassica vegetable production,
we report on the following experiment undertaken to investigate the effect of organic compost
on the quantity of the disease agent A. candida, WB, in soil. Our null hypothesis was that the
mean amount of WB in soil would be equal to the amount of WB in soil that has had compost
added, HO: μ1 = μ2. To test this hypothesis the following randomised semi-field experiment
was conducted at the Lenswood Research Centre, Lenswood, South Australia.
METHODOLOGY
Soil Treatments
Commercial Soil:
Soil samples were taken from a commercial vegetable growing property in the Adelaide Hills,
34°49.574‟S 138°54.246‟E. Soil was collected on December the 9th 2009, directly after a
broccoli crop that was heavily infected with WB had been harvested, and the post-harvest
plant residue had been shredded. To reduce the extreme variability evident in previous pilot
experiments, composite sampling was employed. Composite sampling combines a number of
independent samples to form an experimental/sampling unit. In this case, soil samples were
mixed and divided equally into two pots to create a comparable, dependent paired
experimental unit.
Samples were composed of 20 hand trowels of soil which were taken every five meters within
a 150 m row. The soil was thoroughly mixed (producing10 L of soil) and then divided into
42
two portions. To ensure thorough mixing, each of the two portions was mixed separately by
hand and then reincorporated into a single sample. This process was repeated three times
before the 10L of soil was finally divided into two black plastic pots, each of was 8.5 L
capacity. The pots were consecutively numbered and 30 pairs of soil samples (60 pots) were
taken from each of five randomly sampled rows of broccoli, a total of 3000 soil samples (300
pots or 150 paired pots).
Sterilised Soil:
To provide a negative control (experimental units without white blister) and comparative
treatments, 150 paired pots were set up using SARDI-sterilised University of California soil
mix.
To investigate the effect of compost, a pot from each one of the 300 pairs was chosen at
random, and compost was added to it. Compost was mixed into either the commercial or
sterile soil treatments at a ratio of one part compost to five parts soil, prior to being inoculated
with WB (see below).
Inoculations - White Blister
The 150 paired pots containing soil obtained from a commercial grower were assumed to
contain a naturally occurring population of WB, and 150 paired pots with sterile soil were
assumed to contain no WB. To create experimental conditions that better reflected post-
harvest field conditions, 200 pairs of pots were inoculated in one of two ways: 1) 100 pairs
(50 pairs of commercial soil plus 50 pairs of sterile soil = 200 pots) were inoculated with
pieces of broccoli infected with WB, and; 2) similarly, another 100 pairs were inoculated with
dried and ground broccoli leaf which was infected with WB.
Inoculation - WB infected Broccoli pieces:
Plant material was collected prior to harvest, from a commercial broccoli crop that displayed
obvious signs of WB disease.
Composite samples of infected broccoli were assembled by cutting 3 cm portions of
hypertrophied tissue from 10 individual WB-infected broccoli plants. Each portion was then
divided in half symmetrically, and the two lots of 10 halves (a dependent pair) were combined
and placed in poly mesh bags (mesh size 10mm).
Inoculation - WB infected dry ground Broccoli leaf:
Leaves from broccoli plants infected with WB, were dried in an incubator for 5 days at 40°C.
Five dried leaves, each leaf taken from a different individual plant, were combined, crushed
and placed in a stainless steel grinder (each lot ground for three seconds, three times). Ground
leaf material was then screened through a 1mm2 mesh sieve. Using this process, 95% of
sieved ground leaf particles were less than 0.5 mm in size. The ground broccoli leaf powder
was then divided into two equally weighted portions, a dependent pair.
Inoculating - Soil Treatments
A core of soil, 30 cm3 in volume, was removed using a corer constructed from PVC water
pipe. The core of soil was removed from the centre of the pot mixed with the ground dry leaf
material. This mixture of soil and inoculum was then returned to fill the core cavity. Similarly
a soil core, 30 cm3 in volume, was removed and a mesh bag was placed in hollow where the
soil core had been removed. Contents of the soil core were emptied over the mesh bag to fill
the hollow.
In summary, 100 pots (or 50 dependent pairs of experimental units) were treated in one of
following six ways, with or without compost:
1 commercial soil +/- compost
2 commercial soil +/- compost + diseased broccoli tissue
3 commercial soil +/- compost + dried and ground infected leaf tissue
43
4 commercial soil +/- compost (control)
5 commercial soil +/- compost + diseased broccoli plant tissue
6 commercial soil +/- compost + dried and ground infected leaf tissue
Each pair within the 600 hundred pots, were randomly positioned in a shade house at six
different positions. Commercial broccoli crops are irrigated; therefore each pot received
approximately 30ml of water per day, via drip irrigation. From observation, this supplied
enough water to keep pots damp without any visible runoff.
Samples for PCR Analysis:
To quantify the amount of WB DNA in the experimental units, a soil core was taken from the
centre of each pot using a corer constructed from PVC storm-water pipe. The volume of the
sampling corer was 60 cm3, which was larger than the initial inoculation core. Sixty paired
pots were randomly chosen and sampled each month for five months. After each inoculation
and during final sampling, any equipment such as the soil corers, were sterilised by washing
in bleach, and then checked for residual debris before being double rinsed and drained prior to
reuse. The contents of sample cores were emptied into zip lock bags, mixed thoroughly and
labelled accordingly. Samples were then delivered to the SARDI Plant Research Centre at
Waite, for qPCR analysis.
Each pair of samples for each of six treatments, was replicated 10 times (10 pairs = 20 pots x
6 treatments = 120 pots). Sixty pairs of pots were removed for sampling each month for 5
months. The first sampling period was four days after the experiment began on December the
28th 2009.
Measuring the amount of Albugo candida DNA using Quantitative PCR
Albugo candida DNA was quantified by real-time PCR using DNA extracted from soil
samples of up to 500 g dry weight, using the methods described by Ophel Keller et al. (2008)
and Riley et al. (2009). The probe and primer sequences for both assays are presented in
Table 1. Real-time PCR was performed using TaqMan® MGB probes and QuantiTect Probe
PCR kit Master Mix (Qiagen), in 10 µl reactions in 384 well plates. The ABI PRISM®
7900HT Sequence Detection System was used and thermal cycling conditions were: 50ºC for
2 min. to allow UNG (uracil-N-glycosylate) pre-treatment of the reaction and prevent carry
over contamination of dU -containing DNA from previous reactions; an initial denaturation
temperature of 95ºC for 15 min to activate Taq Polymerase, followed by 40 cycles of
denaturation at 95 ºC for 15 s and an annealing/extension step at 60ºC for 1 min.
The assay was designed using sequence information on GenBank and specificity against other
known fungal pathogens was evaluated using spores of obligate parasites Bremia lactucae
(which causes lettuce downy mildew) and Plasmopara viticola, which causes grape downy
mildew. DNA standards were prepared by separate 10-fold dilutions ranging from 200 pg to 2
fg DNA /µl, (standard DNA was extracted from Gga isolate 137T).
The qPCR returned a measure of picograms pg of WB DNA per gram of sampled soil (
pgDNA/g ).
44
Table 1. Primer and probe sequences for real-time quantitative PCR assays for Albugo
candida
Oligonucleotide Sequence 5‟ to 3‟
Forward primer CGCCATATGCAACGCTTCTT
Reverse primer CATCAGCTTCCAACCTTACGGTC
Probe 6FAM CGGTTAGCCCACACA MGBNFQ
Analysis
All data were pooled across the five sampling periods and log transformed prior to statistical
analysis Dependant paired sample data were analysed using a matched pairs analysis and
tested using a T-test for two dependent samples (or Wilcoxon matched-pairs signed ranks
test), using R statistical software (R Development Core Team 2010). Back-transformed means
from log transformations are presented in (table 1).
Results
The resultant mean values of the quantitative PCR indicates that there is a general trend that
the amount of WB decreases over time for all soil treatments, i.e. sterile and commercial both
+/- compost (Figures 1 and 2).
Sterile Soil
0.01
0.10
1.00
10.00
100.00
1000.00
1 2 3 4 5
Time
me
an
pg
DN
A/g No Comp (control)
Comp (control)
NoComp gr
Comp gr
NoComp tis
Comp tis
Figure 1 The mean amount of WB DNA detected by q PCR for each of the sterile soil
samples (n=10)
45
Commercial soil
0.01
0.10
1.00
10.00
100.00
1 2 3 4 5
Time
me
an
pg
DN
A/g No Compost
Comp
No Comp gr
Comp gr
No Comp tis
Comp tis
Figure 2. The mean amount of WB DNA detected by qPCR for each of the
commercial soil samples (n=10).
However, there was no significant difference detected between the amount of WB DNA in
treatments with or without compost (Table 2). Therefore, under the experimental conditions
used here, there was no evidence to support the hypothesis that the application of compost
reduces the amount of WB present. Thus, in this case, our null hypothesis is upheld.
Table 2 The amount of Albugo candida DNA detected in paired soil samples using qPCR.
pg Albugo DNA/sample (mean ± SD)a
Sterile Soil Commercial Soil
Inoculation
Method No Compost Compost No Compost Compost
None 0.01 ± 2.25 0.01 ± 2.09 0.06 ± 6.51 0.05 ± 7.29
Ground Leaf 0.27 ± 11.33 0.24 ± 22.96 0.78 ± 10.79 0.99 ± 11.81
Fresh Tissue 3.04 ± 24.13 5.83 ± 12.98 1.01 ± 32.27 2.03 ± 25.86
a (Wilcoxon matched pair test, n=50)
46
Discussion: The advantage of developing and using a qPCR assay was that it allowed us to design an
experiment which better reflected the biology of this disease under commercial production
and field conditions. In order to detect any potential effect, a high rate of compost was used
based on previous work which had shown that the suppressive effects of composts usually
increase with the rate of application (Noble 2005). The results of this experiment show that
the application of composted green organics did not significantly affect the amount of white
blister DNA present in samples. Success or failure of soil amendments is dependent on many
environmental variables such as moisture and temperature, as well as the type of raw material
used to produce the compost. For example, Phytophthora spp. (also oomycetes) have been
shown to be inhibited by composts prepared from specifically hardwoods and pinebark
(Hoitink and Fahy 1986).
Conclusions:
Therefore, although we were unable to show that compost affected WB DNA levels our work
did result in development of specific probes that are able to be applied in qPCR to accurately
determine the amount of A. candida DNA, in soil or tissue samples. There may be some scope
to develop this test as a commercial risk analysis tool. However, this would first require
determination of the degree WB viability per amount of pathogen DNA detected in samples.
Currently, there is no indication to what level of disease correlates with varying amounts of
WB DNA detected, a factor which is also regulated by many environmental variables.
Nevertheless, we have developed a useful research tool to produce answers to these questions
and other important aspects of WB epidemiology and management.
Acknowledgements:
The QPCR test was designed by Diane Hartley, CSIRO and evaluated by Herdina, Plant and
Soil Health (SARDI). Their expertise along with constructive discussion and advice from
Alan McKay, Russell Burns, Kathy Ophel- Keller (SARDI Plant and Soil Health) Greg Baker
(SARDI Entomology) and Elizabeth Minchinton (VIC DPI) through out this section of the
project is gratefully acknowledged.
References:
Hoitink, H. A. J. and P. C. Fahy (1986). Basis for the control of soilborne plant-pathogens
with composts. Annual Review of Phytopathology 24: 93-114.
Noble, R. and E. Coventry (2005). Suppression of soil-borne plant diseases with composts: A
review. Biocontrol Science and Technology 15(1): 3-20.
Ophel-Keller, K., A. McKay, et al. (2008). Development of a routine DNA-based testing
service for soilborne diseases in Australia. Australasian Plant Pathology 37(3): 243-253.
R Development Core Team (2010). R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL:
http://www.R-project.org.25http://cran.r-project.org/doc/Rnews/72
Riley, I. T., S. Wiebkin, et al. (2010). Quantification of roots and seeds in soil with real-time
PCR. Plant and Soil 331(1-2): 151-163.
Rimmer, R.S., Shattuck, V.I., and Buchwaldt, L. (2007), Compendium of Brassica Diseases.
1st edition., APS Press, Inc., St. Paul, MN, USA, 117 pages.
47
2.3 BENEFITS OF USING COMPOST WITH IN BRASSICA
VEGETABLE PRODUCTION SYSTEMS.
C.Paull (SARDI)
There are a number of benefits of adding compost to crops such as improvement to soil
structure, increase in biodiversity which is linked to nutrient release and availability and soil
health (Kennedy 1999, Bowden et al 2010). Conducting experiments to establish the effect
of compost on invertebrates (section 2.1) and disease (section 2.2) provided an opportunity
to quantify the effect that compost had on other crop production parameters. Here we report
on the effect compost had on organic carbon content and crop yield.
METHOD
Cauliflower Yield – 2008:
Cauliflowers were planted at both sites in June 2008 at both sites 1 and 2.
At site 1, each plot, two with and two without compost ,were planted with 150 cauliflower
seedlings variety „Arctic‟. Each seedling was planted with a measured amount of Osmocote
slow release fertiliser (20 gms) for composted and no compost treatments. The fertiliser was
the only additional input. When the cauliflowers reached maturity 20 cauliflowers that were
considered to be of market quality were randomly harvested from each of the four plots and
the curds were weighed.
At site 2, a commercial crop, 3 bays with and out compost were also planted with cauliflower
var „Arctic‟. The commercial grower managed this crop and made sure any other production
activities such as application of gypsum and fertiliser were uniform across both composted
and un composted bays.
We relied on the grower to inform us when the crop had reached maturity. Only cauliflowers
that were of marketable quality were assessed. Staff cutting the curds were unaware that there
was an experimental assessment and cut the cauliflowers as usual. Cauliflowers from the two
treatments were kept separate and 120 curds from each treatment were weighed into empty
bins.
Cauliflower Yield -2009:
There was an opportunity to repeat the yield experiment again for the second season using the
previous composted plots at site 1. At site 2 the site was changed but the design was the same.
That is the beds that were used to plant the cauliflowers had the same compost at the same
rate applied and at the same time as the as in the 2008 experiment. The bays with and
without compost had also been used to grow cauliflowers in 2008. The crops were planted
and managed in exactly the same way as the crop in 2008. This would enable us to assess
whether or not the rate of compost used in 2008 would have an effect on a cauliflower crop
for a second year in succession.
Cauliflower Yield -2010:
To begin to understand how long the benefits of a single application of compost might last.
Cauliflowers were again planted at site 1 for a third season. Unfortunately an unprecedented
cold winter meant that the cauliflower plants „bolted‟ and none of them reached marketable
quality or maturity.
A third years assessment could not be undertaken at site 2 as the grower had applied compost
to all of the production area.
Soil Sampling and Organic Carbon:
48
There had been no previous organic soil amendments added to either of these sites prior to
these experiments. Site 1 had been fallow for over two years and site 2 had been under
commercial cauliflower, leek and lettuce rotation and production for many years.
To assess the level of organic carbon the soil for each crop from compost and no- compost
treatments were sampled. Each soil sample consisted of 40 x 10 cm soil cores taken randomly
in a zig zag fashion from plots using a 10 x 100mm stainless steel soil corer. The 40 soil cores
were combined and placed in a zip lock back and submitted for independent testing for
organic carbon levels. In 2009 samples had to be sent to an alternative laboratory after the
laboratory used in 2008 ceased to exist.
One soil sample was taken from each of the four plots at site 1 in 2008 prior to applying
compost. Sampling of site 1 was repeated in 2009, one year after the compost had been
spread. At site 2, four soil samples were taken from each of the compost and no compost
treatments. Sampling at site was conducted after seedlings were planted in August 2008 and
again in August 2009.
Water use efficiency:
Initially some attempt was made to measure the effect that compost had on soil moisture.
Theta probs (Measurement Engineering Australia T Bugs) were used to measure soil moisture
data from crops at both sites. Water measurement was discontinued after consultation with
the grower and colleagues when it was decided that measuring the effect on yield in the
cauliflower crop would be more informative. This was primarily because vegetables require
constantly high soil moisture content which requires frequent irrigation. Working in a
commercial field situation it wasn‟t possible to control with confidence and accuracy the
amount of water delivered to our experimental plots with out specialised instrumentation and
greater control water application to small areas.
Economic viability of using compost:
It was not possible to do an comprehensive economic analysis primarily because some data
was regarded as unavailable such as the nutrient trade of between adding compost compared
to adding fertiliser. The rate of compost applied to the experimental areas for this research
was used was considered a high rate. In conjunction with discussions with the grower we
undertook a basic cost benefit analysis based on the yield results alone. This took in to
account the rate at which compost was applied in this study, the costs of compost, transport
and application, if yield constantly showed a 10% increase between compost and no compost
a profit would only begin being realised at after a second crop or after year two.
Data analysis:
Yield data from site 1 was failed test of normality and therefore was analysed using a non
parametric Kruskal Wallis test (H) using R statistical software (R Development Core Team
2010). Yield data from site 2 was analysed using two sample t test using Microsoft Excel.
Results:
Yield 2008
At site 1 there was a significant difference between the average weight of cauliflower curds
for each of the two treatments at both sites. The curds from the two plots with out compost at
site 1 had a mean weight between 450 and 495 grams for curds from plots 1 and 3
respectively (Fig 1). The curds from plot 2 (with compost) were almost twice the weight a
mean value of 1018 gms. The curds from plot 4 (with compost) weighed almost three times
more a mean weight of 1300 gms (Fig 2).
49
At site 2 curds cut from bays with out compost had an average weight of 2572 gms compared
to curds grown in soil with compost were almost 10% heavier and each curd had an average
weight of 2850gms (Fig 2).
0
200
400
600
800
1000
1200
1400
1600
Plot 1 No Comp Plot 2 Comp Plot 3 No Comp Plot 4 Comp
Me
an
cu
rd w
eig
ht
(gm
s)
Figure 1. Mean weight of cauliflower curds from plots at site 1 with and without compost
2009 (n=20) H = 267.9302 df 3 p= 0.0001
2300
2400
2500
2600
2700
2800
2900
3000
No Comp Comp
Mean
cu
rd w
eig
ht
(gm
s)
Figure 2. Mean weight of cauliflower curds from plots at site 2 with and without compost
2008 t (118) =0.0000317, p<0.001.
Yield 2009:
There was a significant difference between the average weight of cauliflower curds for each
of the two treatments at both sites in the second year (Figs 3 and 4). However at site 1 the
mean weights for curds from compost and no compost treatments were both less than the
mean values from the previous year although the curds from the compost plots weighed 250 –
300 grams more.
The average weight of curds from the commercial crop site 2 from both treatments were also
less but there was still a 10% increase in the average weight of curds from the composted
bays when compared to curds grown with out compost.
50
0
100
200
300
400
500
600
700
800
Plot 1 No Comp Plot 2 Compost Plot 3 No Comp Plot 4 Compost
Me
an
cu
rd w
eig
ht
(gm
s)
Figure 3. Mean weight of cauliflower curds from plots at site 1 with and without compost
2009 (n=20) H=60.23,3d.f.,p<0.0001.
1800
1850
1900
1950
2000
2050
2100
2150
2200
2250
No Compost Compost
Me
an
cu
rd w
eig
ht
(gm
s)
Figure 4. Mean weight of cauliflower curds from plots at site 2 with and without compost
2009 t (258) =0.0001366, p<0.001.
Organic Carbon:
Results from the soil samples show that in the plots with compost there was twice as much
organic carbon compared to the plots where compost had been added (Fig 5). Similarly the
soil samples analysed from site 2 also showed an increase in soil organic matter between
treatments, a 4% increase in 2008 and a 3% increase in 2009 (Fig 6). However it also shows
that organic carbon increased for both treatments in 2009.
0
5
10
15
20
Plot 1 Plot 2 Compost Plot 3 Plot 4 Compost
Org
an
ic C
arb
on
%
(w
/w)
Figure 5. The amount of organic carbon measured for site 1 plots with and with out compost
2009.
51
0
5
10
15
20
2008 2009
Me
an
Org
an
ic C
arb
on
% (
w/w
)
No Compost
Compost
Figure 6. The amount of organic carbon measured for site 2 plots with and with out compost
(n = 4).
Discussion:
The results from cauliflower yield show a significant increase in the average weight
cauliflower curds from plants which were grown in soil amended with compost compared to
those grown without. This result is more pronounced at site 1. This is likely due to reduced
use of inputs, only a quantity of slow release fertiliser under each seedling compared to the
commercial site where gypsum and fertiliser were added to both treatments as part of a
standard commercial brassica production activities.
Although there was a significant increase in yield from the second year and second crop of
cauliflowers from the initial application of compost, overall curd weight for both treatments at
both sites was down. While these results could be influenced by seasonal variables, this result
was also more pronounced at site 1 and therefore may indicate the degree to which the benefit
of compost on yield decreases over time when there are no other inputs.
It is generally understood that an increase in soil carbon results in increased soil health
(Andrenelli et al 2010). The results from this study also showed that there was a higher
organic carbon from soils where compost had been applied. There is a noticeable increase in
organic soil carbon at site 2 for the second year for both treatments. This may have been
influenced by the change in site. However it is clear that the samples taken from bays with
compost have increased soil carbon compared to those with out.
Inputs such as mineral fertilizers, herbicides and insecticides are added to agricultural systems
are usually undertaken with the goal of maximising productivity and economic returns.
Nitrogen is the most expensive nutrient to manage in horticultural environments (Gaskell and
Smith 2007). A simple analysis of costs and benefits was undertaken by the grower. This
indicated that for the rate of compost used in this study and based on the yield results a profit
would begin to be realised at the end of year two or after the second crop. What isn‟t clear
from this study is what amount of compost application required would off set or is equivalent
to a given amount of fertilizer. It is worthwhile mentioning that the grower observed a
number of other benefits of using compost that were not directly quantified during the study
these included:
Increased water infiltration – water did not pool on bed surfaces
Reduced mud splash on curds
Less soil compaction
Increased and even curd development meant reduced number of passes to complete
the crop harvest.
Generally plants were more healthy
52
Weeds were observed to be better controlled in the first year but not the second where weed
growth was observed to increase. This is similar to what was measured in work by in wheat
crops (Bell 2008).
Conclusion
The results from cauliflower yield data, recorded from a single application of compost over
two seasons 2008/2009 showed that there was a significant difference an increase in yield
between cauliflower grown with compost compared to those grown with out. More broadly
the results translate as a 10% increase in crop yield each year, for two years, from a single
application of compost. Those plots which received compost also showed an increase in soil
carbon, a positive indication of soil health.
Where it is economically feasible application of compost is likely to have positive
consequences for brassica vegetable production.
The calculations for cost and benefits of applying compost were based on results of yield and
direct cost of compost supply and spreading. This was because more detailed information did
not exist for this production system. To undertake a comprehensive cost benefit analysis what
is also required is greater understanding or an evaluation of what rate of compost is equivalent
to a specific quantity of fertilizer. We therefore recommend further work be undertaken to
understand nutrient budgets in relation to compost.
Acknowledgements:
We would like to acknowledge the generous support and in-kind contribution from the
Newman family for access to their property and constructive discussions and Jefferies Soils,
for the supply and delivery of over 50 m3 of compost to the experimental sites. Staff at the
SARDI Lenswood Research Centre, Dr Peter Crisp‟s assistance for advice of soil moisture
measurement, and soil sample analysis.
References:
Andrenelli, M. C., E. Batistoni, G. Brandi, R. Papini, S. Pellegrini, R. Piccolo and N.
Vignozzi (2010). Soil organic matter increase: comparison between two strategies.
Agrochimica 54(2): 79-90.
Bell, J. R., M. Traugott, et al. (2008). Beneficial links for the control of aphids: the effects of
compost applications on predators and prey. Journal of Applied Ecology 45(4): 1266-1273.
Bowden, C. L., G. K. Evanylo, X. Zhang,, E.H. Ervin and Seiler, J.R. (2010). Soil Carbon
and Physiological Responses of Corn and Soybean to Organic Amendments. Compost
Science & Utilization 18(3): 162-173.
Gaskell, M. and R. Smith (2007). Nitrogen sources for organic vegetable crops.
Horttechnology 17(4): 431-441.
Gonzalez, M., E. Gomez, R.Comese, M. Quesada and M. Conti. (2010). Influence of organic
amendments on soil quality potential indicators in an urban horticultural system. Bioresource
Technology 101(22): 8897-8901.
Kennedy, A.C., 1999. Bacterial diversity in agroecosystems. Agricultural Ecosystems and
Environment. 74, 65-76.
53
3. KEY PREDATORS OF DIAMONDBACK MOTH IN BRASSICA
VEGETABLES.
Chris McIntyre (The University of Adelaide)
INTRODUCTION
Predators are important biological control agents of Brassica pests including Plutella
xylostella, the diamondback moth (DBM) (Furlong et al. 2004). To date, however the
identities and relative abundance of important predators throughout the year have not
been widely investigated. Understanding these aspects of natural enemies would help
Brassica growers and pest management specialists to make better informed decisions
about maintaining predators for the biological control of insect pests in Brassica
crops.
The diamondback moth is the most serious pest of Brassica crops worldwide (Talekar
and Shelton 1993). The widespread and increasing problem of DBM developing
resistance to many insecticides and a general desire to reduce insecticide use have
made DBM a focus for developing integrated pest management (IPM) strategies
(Sarfraz et al. 2005). An integral part of IPM is the use of parasitoids and predators to
suppress pests. While much research to date has been conducted on parasitoids, there
has been little focus on predators. In part, this has been due to the difficulty in
determining the diets of predators. Arthropod predators rarely leave detectable parts
of prey behind, and prey parts are difficult to identify microscopically. The
development of DNA-based techniques has enabled diet to be studied in greater detail,
without the need to observe prey remains or monitor predator behaviour (Symondson
2002). DNA-based analysis of Brassica predators in southern Australia, developed
prior to this study confirmed that at least 12 species of predators feed on DBM
(Hosseini 2007). However, this study involved limited sampling of predators and so
was not able to examine fluctuations in predator numbers and consumption of DBM
over the course of a year.
The aim of this study was to develop a greater understanding of the role that predators
play in assisting the control of DBM by sampling predators and DBM at two sites
over the course of one year and examining predator diets using DNA analysis to
determine which predators consume DBM at what times of year.
METHODS
Predator survey
Monthly surveys were conducted over the course of a year at two commercial
Brassica vegetable properties located at Gumeracha and Currency Creek in South
Australia. Sample sites were randomly selected from broccoli crops at the farms
54
where plants were taller than 30 cm. A vacuum sampling device was used to collect
predators. Sampling was conducted along ten randomly selected 5 m transects for 50
seconds. All predators were recorded immediately and placed on ice to delay DNA
degradation. Numbers of adult DBM were also recorded. To assess the population of
DBM at each sampling time and site, an outer leaf, an inner leaf and a middle leaf
were removed and DBM eggs, larvae and pupae were counted from three randomly
selected plants prior to vacuum sampling.
Previous work has indicated that wolf spiders are likely to be important predators of
DBM (Hosseini 2007). Because wolf spiders are difficult to collect using vacuum
sampling and are more active at night, three additional trips at night were made to
collect wolf spiders using spotlight techniques and hand trapping. Night time vacuum
samples were also taken at these times, however due to the low numbers of predator
specimens, the data are not presented here.
Data analysis
Numbers of individuals of each predator species and DBM numbers from each
sampling trip were pooled and the totals used in analysis. Mean number of predators
and standard deviation were calculated for each species and for total predators. Insect
numbers were analysed for normality using the Shapiro-Wilk test and as they were
found to be normally distributed a Pearson correlation was conducted to assess the
relationship between DBM and predators at the two sites.
Molecular analysis
Predators were transported to the laboratory and were immediately placed in a -20 °C
freezer until DNA could be extracted from them. DNA was extracted from predator
guts using the technique of Boom et al. (1990), as modified by Hosseini (2007). Very
small predators were not gutted, instead they were extracted whole.
To determine if the predator had consumed DBM, extracted DNA was amplified
using PCR with DBM-specific primers DBM-F-2 (5′-
TGTTTATCCTCCTTTATCTTCA-3′) and DBM-R1-1 (5′-
CTCCTGCAGGATCAAAGAAG-3′) (Hosseini et al. 2008). Remaining DNA was
placed in cold storage to potentially provide an opportunity for later re-testing to
determine consumption of pests other than DBM.
RESULTS
DBM numbers at both sites were similar throughout the course of the study (Figure
1). Numbers were low at both sites in the months of June, July and August, rising in
spring and peaking in October. At Gumeracha numbers fell after October with the
55
lowest level seen in February. At Currency Creek, numbers of DBM remained high
until February, when a dramatic drop in DBM population was seen. After March,
populations began rising again.
Total predator numbers broadly followed a similar pattern to DBM numbers, with two
peaks seen in spring and autumn but with much higher variability between the sites
(Figure 1). At Gumeracha, predator numbers peaked in May, with a smaller peak in
November, while at Currency Creek predator numbers peaked in November, with a
smaller peak in April. The ratio of DBM to predators varied widely at both sites,
reaching a low of 1:9 in May 2010 at Gumeracha and a peak of 10:1 in January 2010
at Currency Creek.
56
Table 1a: Predators collected using vacuum sampling at Gumeracha.
Jun 2009 Jul 2009 Aug 2009 Sep 2009 Oct 2009 Nov 2009 Dec 2009 Jan 2010 Feb 2010 Mar 2010 Apr 2010
May
2010 Jun 2010 Total Mean St. Dev
Transverse ladybird 3 5 6 2 0 0 0 3 0 0 0 2 1 22 1.69 2.06
Wolf spider 1 0 0 0 2 0 4 0 0 1 0 3 1 12 0.92 1.32
Carabid beetle 0 0 0 0 2 0 1 0 0 0 1 0 0 4 0.31 0.63
Other spider 0 1 2 1 0 0 0 0 0 1 0 0 0 5 0.38 0.65
Brown lacewing 6 3 0 1 12 18 3 0 0 4 8 7 1 63 4.85 5.38
Spotted amber ladybird 0 0 1 0 0 0 0 0 0 0 0 2 0 3 0.23 0.60
Earwig 0 0 0 0 0 0 2 8 0 0 0 1 0 11 0.85 2.23
Pacific damsel bug 0 0 0 3 1 0 4 0 0 0 8 10 0 26 2.00 3.39
Staphylinid beetle 0 0 0 0 1 0 0 0 0 0 1 0 0 2 0.15 0.38
Total 10 9 9 7 18 18 14 11 0 6 18 25 3 148 11.38 6.98
Table 1b: Predators collected using vacuum sampling at Currency Creek.
Jun 2009 Jul 2009 Aug 2009 Sep 2009 Oct 2009 Nov 2009 Dec 2009 Jan 2010 Feb 2010 Mar 2010 Apr 2010
May
2010 Jun 2010 Total Mean St. Dev
Transverse ladybird 2 0 0 0 0 0 3 0 0 2 5 4 3 19 1.46 1.81
Wolf spider 0 0 0 0 0 0 1 0 0 0 0 0 1 2 0.15 0.38
Carabid beetle 0 0 1 0 0 0 0 1 0 0 0 0 0 2 0.15 0.38
Other spider 0 0 1 0 0 0 0 0 2 0 3 1 0 7 0.54 0.97
Brown lacewing 9 1 0 0 27 44 2 0 0 2 0 2 5 92 7.08 13.33
Spotted amber ladybird 5 2 0 0 0 0 0 3 0 1 0 0 0 11 0.85 1.57
Earwig 0 0 0 0 1 0 0 0 0 1 0 0 0 2 0.15 0.38
Pacific damsel bug 2 0 0 7 4 1 0 1 0 0 4 1 0 20 1.54 2.18
Staphylinid beetle 0 0 0 0 0 2 1 0 0 0 0 0 0 3 0.23 0.60
Total 18 3 2 7 32 47 7 5 2 6 12 8 9 158 12.15 13.23
57
a)
0
10
20
30
40
50
60
70
80
Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
Sampling date
Num
ber
of
arh
tro
po
ds
collect
ed
0
10
20
30
40
50
60
70
80
90
Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
Sampling date
Num
ber
of
art
hro
pods
collect
ed
b)
Figure 1. Seasonal fluctuations in total predator (solid line) and DBM (dashed line)
numbers over the course of the year from June 2009 – June 2010 at Gumeracha (a)
and Currency Creek (b).
The most consistently collected predator at both sites was the brown lacewing,
Micromus tasmaniae (Table 1). Brown lacewings represented 42.6% and 58.2% of the
total sampled predator fauna at the Gumeracha and Currency Creek sites, respectively.
Damsel bugs, Nabis kinbergii, were the next most commonly collected predators,
representing 17.6% of the collected predators at Gumeracha and 12.7% at Currency
58
Creek. The third commonly collected predator was the transverse ladybird, Coccinella
transversalis. This species represented 14.9% of the collected predators at Gumeracha
and 12.0% at Currency Creek. No other species was collected more than 12 times at
either site.
On average at Gumeracha 1.2 predators were collected per 5 metre transect, with a
monthly standard deviation of 0.76, while at Currency Creek an average of 2.1
predators were collected per 5 metre transect, with a monthly standard deviation of
1.91 (Table 1).
The populations of DBM and predators at Gumeracha (r = 0.277, p = 0.395) and
Currency Creek (r = 0.456, p = 0.12) were positively correlated but the correlations at
were not significant. (Figure 2).
0
10
20
30
40
50
0 10 20 30 40 50 60 70 80
Number of DBM collected
Num
ber
of
pre
dato
rs c
ollect
ed
Figure 2. Relationship between the abundance of DBM and predators from
Gumeracha (□) and Currency Creek (▲) Trend lines indicate square of correlation
coefficient (R2) between numbers of DBM and numbers of predators at Gumeracha
(solid line) and Currency Creek (dashed line).
Molecular analysis
More than 20 percent of all the nine predatory arthropod species that were collected
during the survey were confirmed to have consumed DBM DNA (Figure 3). More
than 40% of damsel bugs contained DBM DNA, while 30 percent or more of
lacewings, spiders and carabid beetles were also confirmed to have consumed DBM.
The level of consumption found in spotted amber ladybirds, transverse ladybirds and
earwigs was lower, but still above 20%.
59
0% 20% 40% 60% 80% 100%
Damsel bug
Brown lacewing
Carabid beetle
Other spider
Wolf spider
Transverse ladybird
Earwig
Hippodamia ladybird
Staphylinid beetle
Pre
dato
r sp
eci
es
Percent of predators containing DBM
n = 5
n = 14
n = 13
n = 41
n = 14
n = 46
n = 155
n = 12
n = 6
Figure 3: Detection rate for DBM in predators with DNA extracted and amplified
with DBM specific primers.
DISCUSSION
DBM numbers at both sites followed the expected pattern through out the 12 month
study given their close developmental relationship with temperature. The maximum
and minimum temperature thresholds for DBM development are 34 °C and 8 °C
respectively, therefore there were low numbers seen in winter and late summer (Liu et
al. 2002). No stage is capable of surviving prolonged severe winter conditions,
however the more temperate conditions seen in southern Australia permit a number of
DBM to survive over winter and prolonged periods of high temperature can also
reduce moth populations (Gu 2009). Wet conditions also mean that moths are less
likely to be actively flying and thus less likely to be collected using the vacuum
sampler. Discussions with growers revealed that DBM numbers during the latter part
of the study were considered unusually low and that the cabbage butterfly Pieris
rapae was causing more damage than DBM at that time, particularly at Gumeracha.
The numbers of predators collected for each sampling period were generally lower
than that seen in the previous study conducted at the same sites in February – March
2007. Hosseini (2007) surveyed crops in which no insecticides had been applied. The
level of DBM and other pests in these crops would have been considered unacceptable
in an ordinary commercial crop. This study utilised crops under commercial
cultivation that were treated for pests, principally using Bt, when DBM became a
significant problem. The lack of prey caused by applying Bt sprays may have reduced
predator numbers. All commonly found species of predators tested were found to
60
consume at least some DBM. There was a wide fluctuation in the ratio of predators to
DBM. This difference is likely to be due to lag time as predator populations build up
following an expansion in moth population, migration of moths and predators into and
out of the fields and other factors.
The brown lacewing Micromus tasmaniae was by far the most commonly collected
species in the vacuum samples. Brown lacewings are principally known as predators
of aphids (Leathwick 1989), but are also known to be general omnivores (Stelzl
1991). However, research conducted in parallel to this project has revealed that brown
lacewing adults and larvae do not readily consume DBM larvae or adults. They do
however voraciously consume DBM eggs (Hogendoorn et al., unpublished data).
Therefore, the high rate of DBM detected in the guts of brown lacewings is likely to
be due to widespread consumption of DBM eggs. In addition, brown lacewings have a
low temperature threshold for development, high efficiency at converting prey to
eggs, rapid development and short generation time (25 days at 23 °C), long adult life,
high fecundity and continuous overlapping generations (Leathwick 1989).
These attributes make brown lacewing an almost ideal candidate for use in the
management of diamondback moth, both in terms of encouraging natural populations
and inundative release at times when DBM eggs are present. Mass rearing techniques
for brown lacewing have been developed (Simeonidis 1995) but to date, brown
lacewing has not been used for inundative release in a field environment, although it
has seen limited use in greenhouses. Little work has been done on the economics of
mass rearing and inundative release of brown lacewings, however the inundative
release of the green lacewing Chrysoperla carnea in the field has been judged to be
economically unviable (Senior and McEwen 2001). Research on the mass rearing of
green lacewings is ongoing and developments in artificial diet and mass release
techniques are promising (Nordlund 2001).
The highest rate of prey detection was found in the damsel bug N. kinbergii. Damsel
bugs feed on insect larvae and other soft bodied prey using their piercing mouthparts.
Although young damsel bugs in particular will also feed on aphids (Nguyen 2008), it
appears likely given the high detection rate of DBM that the most common prey of N.
kinbergii in Brassica crops are DBM larvae and pupae, as well as the larvae and pupae
of other lepidopteran species when present. Damsel bugs are unlikely to be a suitable
candidate for mass rearing and inundative release and instead efforts should focus on
managing and enhancing natural populations.
The third potentially important predator of DBM identified in the Brassica crops was
the transverse ladybird, C. transversalis. The main diet of transverse ladybirds is
aphids (Omkar and James 2004), but C. transversalis will readily consume DBM eggs
and smaller larvae. Larger larvae are sometimes eaten, but do not appear to form a
preferred item of diet (Lankin, unpublished data).
61
It is clear from this work that despite the three key predators being brown lacewing,
damsel bugs and transverse ladybirds, there are also a number of other predatory
species that contribute to suppression of DBM. The sampling technique used may
have over-represented small flying insects and under represented arthropods found in
the interior of plants and on the ground, as well as heavier insects. As vacuum
sampling was carried out during the day, nocturnal predators may have also been
missed. Several vacuum samples were also taken at night but, possibly owing to the
presence of dew, almost no predators were found (data not shown). Wolf spiders
(Lycosidae) in particular are likely to be missed by vacuum sampling as they are both
nocturnal and ground dwelling. The presence of DBM DNA in predators should not
be considered a definitive sign of predatory behaviour as some predators such as
earwigs are also scavengers and DNA may have come from the consumption of DBM
frass or dead insects. DBM DNA in a predator‟s gut may also indicate that the
predator has eaten another predator that had eaten DBM. Secondary predation may be
tested for using PCR (Sheppard et al. 2005).
Conclusions and Recommendations
Results from this work indicate that brown lacewings have the potential to contribute
to reducing DBM in commercial Brassica vegetable production system but also have
the potential to be used in inundative releases and IPM programs. Not only were the
lacewings the most consistent predator throughout the year, but more than 34 % tested
positive for the presence of DBM DNA. As eggs are the only stage of DBM
consumed by lacewings, it is likely that they could significantly reduce the population
of DBM prior to hatching and therefore significantly reduce DBM damage to Brassica
plants. Damsel bugs and transverse ladybirds have also been identified as important
predators of DBM. The use of IPM techniques, especially minimising the use of
broad-spectrum insecticide, should encourage these predators and enable DBM
numbers to be significantly suppressed. Based on these results we would recommend
further work be undertaken to quantify the impact of Micromus tasmaniae on DBM
populations in an inundative release as part of an IPM program.
Acknowledgements
This research was sponsored by a scholarship provided by Horticulture Australia
Limited. I gratefully acknowledge Graeme and John Pitchford and Steve and John
Newman for allowing this research to take place on their properties; Mike Keller and
Katja Hogendoorn and Cate Paull, for supervision and advice and Nicolas LeCatre
and Ole Rechner for assistance in the field and in sorting samples.
62
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Omkar, James BE (2004) Influence of prey species on immature survival,
development, predation and reproduction of Coccinella transversalis Fabricius (Col.,
Coccinellidae). Journal of Applied Entomology 128, 150-157.
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Sarfraz M, Keddie AB, Dosdall LM (2005) Biological control of the diamondback
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Senior LJ, McEwen PK (2001) The use of lacewings in biological control. In
'Lacewings in the Crop Environment'. (Eds PK McEwen, TR New and AE
Whittington) pp. 296–302. (Cambridge University Press: Cambridge)
Sheppard SK, Bell J, Sunderland KD, Fenlon J, Skervin D, Symondson WOC (2005)
Detection of secondary predation by PCR analyses of the gut contents of invertebrate
generalist predators. Molecular Ecology 14, 4461-4468.
Simeonidis A (1995) Development of a mass rearing technique for the Tasmanian
brown lacewing, Micromus tasmaniae Walker. Masters thesis, Lincoln University.
Stelzl M (1991) Untersuchungen zu Nahrungsspektren mitteleuropäischer
Neuropteren-Imagines (Neuropteroidea, Insecta). Journal of Applied Entomology 111,
469-477.
Symondson WOC (2002) Molecular identification of prey in predator diets.
Molecular Ecology 11, 627-641.
Talekar NS, Shelton AM (1993) Biology, ecology, and management of the
diamondback moth. Annual Review of Entomology 38, 275-301.
64
4.1 IDENTIFYING NATURAL ENEMIES OF EARLY SEASON
BRASSICA PESTS IN UNSPRAYED PLANTINGS AT GATTON
RESEARCH STATION
L. Senior (Agri-Science QLD, DEEDI)
Introduction
In Queensland, early season pests such as centre grub (Hellula sp), cabbage cluster caterpillar
(Crocidolomia sp), heliothis (Helicoverpa sp), thrips (Thrips tabaci, Frankliniella
occidentalis) and silverleaf whitefly (Bemisia tabaci) can cause substantial crop loss if left
unchecked. While previous research has contributed to an understanding of the biology of
these pests, little is known about the predators and parasitoids associated with them. Only
through increasing our knowledge of early season natural enemies can we evaluate their
potential for managing early season pests. This objective was divided into the following four
parts:
4.1 Identifying natural enemies of early season brassica pests in unsprayed plantings at Gatton
Research Station
4.2 Identifying natural enemies of early season brassica pests in commercial plantings in the
Lockyer Valley
4.3 Could a summer crop be used as a natural enemy source for newly planted brassicas?
4.4 Evaluation of the predatory behaviour of some spiders commonly found in early season
brassica crops
The first part of the objective focussed on quantifying the diversity of natural enemies in early
season plantings of different brassica crops. Trials were conducted at the Gatton Research
Station, where crops could be grown without use of chemical insecticides, thus providing a
comparison for work conducted in commercial crops (described in the next chapter). As
inappropriate chemical control of early season pests is likely to disrupt the IPM strategy
established for diamondback moth later in the growing season, it is important to establish the
natural enemies that occur when no insecticide is applied.
Methods
Trial design
Trials were carried out at Gatton Research Station (Gatton, south-east Queensland) in early
season, unsprayed plantings of broccoli (var. Atomic), cabbage (var. Warrior), cauliflower
(var. Freemont) and Chinese cabbage (var. Matilda). Seedlings were transplanted in
February, representative of an early season planting in the Lockyer Valley region. The final
assessment was made when the majority of the crops were ready for harvest, approximately
ten weeks after transplantation.
The trial was laid out in four replicate blocks, each measuring approximately 20 m x 50 m.
Each block was divided into four, and each quarter planted with a different brassica type (Fig.
1). The layout of the brassica types within each block were randomised between replicates.
Brassica plantings each measured 9 m x 24 m, separated by an unplanted buffer zone of 2 m.
Plantings were in double rows, with 1.5 m between bed centres. Spacings between plants
within the rows were 0.33 m for broccoli and Chinese cabbage, 0.66 m for cabbage and
cauliflower (industry standard). Photographs of the trial site are displayed in appendix 2.1 (I).
65
Figure. 1 Layout of a replicate block
Crop management
The crop was overhead irrigated as necessary where in-crop rainfall was not sufficient.
Weather data for the trial period are presented in appendix 2.1 (II). Herbicide (RoundUp
Max) was applied 22 days post transplantation (20/3/09), and Chinese cabbage were treated
with Kocide DF copper spray to control bacterial rot at 41 days post transplantation (8/4/09).
Two applications of Bacillus thuringiensis (Bt; Xentari® and Dipel®) were made to reduce
high numbers of Crocidolomia larvae, which would have caused unacceptable levels of
damage to the crops if left untreated (25/3/09 and 1/4/09).
Sampling methods
Several sampling methods were used in order to ensure a representative range of species was
collected. Due to the large quantities of arthropods encountered during the sampling process,
the majority were identified to the level of family only, although genus and species were
noted where possible.
Visual inspections of the plants were performed at approximately weekly intervals
commencing one week post transplantation and finishing ten weeks post transplantation
(detailed in table 1). At each inspection, five (8 and 10 week assessments) or ten (all
remaining assessment dates) plants of each crop type were selected at random. The plant and
the ground immediately surrounding the plant were examined carefully and all fauna logged.
Plants in the outer rows were excluded from sampling.
At the 4, 8 and 10 week post transplantation assessments, the selected plants were harvested
and placed in sealed bags for examination in the laboratory (destructive sampling). The
plants were kept in bags until examination, and all were inspected within 24 hours of harvest.
For all other weekly assessments intact plants were examined in situ.
20 m
50 m
24 m
9 m
(12 rows)
Bro
cco
li
Cab
bag
e
Cau
lifl
ow
er
Ch
ines
e ca
bb
age
66
Sampling for parasitism was performed to monitor for the presence of lepidopteran and
whitefly parasitoids. Cabbage white and diamondback moth larvae and pupae were collected
on 25th and 28
th May, and whitefly scales were sampled on 5
th, 11
th and 12
th June. Random
collections were made from each crop in each block, with the exception of Chinese cabbage
due to very low populations of the relevant pests. Samples were maintained under ambient
laboratory conditions and monitored for emergence of the adult pest or parasitoid.
Monitoring continued for one week after emergence of the last individual.
Yellow sticky traps were placed in the crop for approximately weekly periods from 30th March
to 5th May, replaced at each sampling assessment (table 1). Traps were positioned
approximately 40 cm above the ground and oriented such that the sticky surfaces faced
north/south. One trap was placed in each replicate of each crop type. Exact counts of
beneficials were made; pest species were assessed on a scale from 1 (low) to 3 (high).
Pitfall traps were placed in the plots for the duration of the trial. Each pitfall trap consisted of
a 320 ml plastic drinking cup buried in the soil with the lip level with the surface. A hole
made in the base of this larger cup allowed drainage. A second, slightly smaller cup (275 ml)
was placed within the first and filled with water plus a few drops of detergent. Each trap was
covered with a plastic disc (18 cm diameter) supported approximately 3 cm above ground
level by three steel nails, to prevent the trap from filling with rain/irrigation water. The traps
were removed at approximately weekly intervals, the contents emptied and logged, and the
water replaced. Three traps were placed in each replicate of each crop, arranged along a
diagonal from the innermost to the outermost corner of the plot.
Table 1. Trial dates
Date * Days post
transplantation
Activity
26/2/09 0 Seedlings transplanted
6/3/09 8 Assessment 1
First pitfall traps placed
9/3/09 - On farm sampling: sites 1 and 2
11/3/09 13 Assessment 2
16/3/09 18 Assessment 3
23/3/09 25 Assessment 4 (destructive sample)
25/3/09 27 1st Bt spray applied (Xentari®)
30/3/09 32 Assessment 5
Sticky traps placed in plots
1/4/09 34 2nd
Bt spray applied (Dipel®)
6/4/09 39 Assessment 6
Sticky traps replaced
15/4/09 48 Assessment 7
Sticky traps replaced
20/4/09 53 Assessment 8 (destructive sample, 5 plants per replicate)
21/4/09 54 Sticky traps replaced
27/4/09 60 Assessment 9
28/4/09 61 Sticky traps replaced
5/5/09 68 Assessment 10 (destructive sample, 5 plants per replicate)
Sticky traps collected
* Where activities took place over more than one day (e.g. destructive sampling), the date on
which the majority of work took place is given.
67
Statistical analysis
Each beneficial group was analysed separately using a general linear model (GLM) with
Wald tests to determine whether terms could be dropped from the regression model, followed
by LSD tests to distinguish between means. Where few individuals of a particular predator
group were recorded, cumulative numbers across the trial period were subjected to ANOVA
followed by LSD tests. All tests were reported at the 0.05 significance level. Results of
direct inspection of intact plants, and of destructively sampled plants were considered
together.
Results
Pest species
Detailed results are presented in appendix 2.1 (III.)
Lepidoptera
Cabbage cluster caterpillar (Crocidolomia pavonana) was the most abundant and most
damaging lepidopteran pest in all crops. In broccoli, cabbage and cauliflower, numbers
increased from the 4th week post transplantation onwards, necessitating a control spray
with Dipel® to prevent complete crop loss. C. pavonana was less damaging in Chinese
cabbage, where the population peaked early in the trial (4 weeks post transplantation).
Cluster caterpillar (Spodoptera litura) was found in increasing numbers in the latter part
of the trial (6 week post transplantation onwards). Numbers peaked in broccoli earlier
than in cabbage or cauliflower; numbers in Chinese cabbage remained relatively low.
Centre grub (Hellula hydralis) peaked early in the trial (4 weeks post transplantation),
and was most abundant in Chinese cabbage.
Cabbage white (Pieris rapae) occurred at moderate levels, mainly towards the latter part
of the trial (7 weeks post transplantation onwards). It was not a significant pest in the
Chinese cabbage.
Diamondback moth (Plutella xylostella), heliothis (Helicoverpa sp.) and loopers
(Chrysodeixis sp.) occurred at low levels.
Sucking insects
Aphids occurred at moderate to high levels in all crops from transplantation onwards.
They were observed in extremely high numbers in Chinese cabbage. Myzus persicae
dominated in all brassica types; some Brevicoryne brassicae occurred towards the end of
the trial.
Silverleaf whitefly (Bemisia tabaci) were most abundant in broccoli, followed by
cauliflower then cabbage, with numbers increasing steadily over the trial period.
Although whitefly adults were found in Chinese cabbage they did not reproduce in this
crop.
Thrips were most prevalent at the seedling stage, decreasing as the plants matured.
There were no apparent differences between the crop types.
Leafhoppers/jassids and green vegetable bugs occurred in low numbers, and were more
abundant in the Chinese cabbage than the other crops.
Although exact counts were not made, data from yellow sticky traps confirmed the
findings of the visual inspections: jassids and aphids were trapped in greater numbers in
Chinese cabbage than other crops; whitefly were lowest in Chinese cabbage and highest
in broccoli; thrips occurred in similar numbers in all crops.
68
Other pests
Other foliage-dwelling pests such as Rutherglen bugs and flea beetles were recorded on
occasion.
Ground-dwelling insects such as cutworm, wireworm, false wireworm, vegetable weevil,
crickets, earwigs and millipedes were recorded from pitfall traps.
Beneficial species
A list of all beneficial fauna logged during the trial is presented in appendix 2.1 (IV).
Results of visual inspections
Overview
Beneficial fauna occurring early in the season mostly comprised predators; parasitism of all
pest species was low throughout the trial period. Spiders were the most abundant predator
group in all but the Chinese cabbage, and were the first predators to arrive in the newly
planted crops. Predatory insects first began to appear three weeks post transplantation.
However, with the exception of Chinese cabbage, a substantial number and variety of
predatory insects were not observed until the latter part of the trial (Figs. 2 - 5).
There were more predators (particularly ladybirds) and a greater variety of predators in
Chinese cabbage compared to the other brassica types (table 2). The second highest predator
numbers were found in the cauliflower.
Table 2. Cumulative foliage-dwelling predators and their relative abundance (%) logged
through visual inspection over the trial period
Predator group Broccoli Cabbage Cauliflower Chinese cabbage
Spiders 203 (79.6%) 182 (82.7%) 367 (85.3%) 361 (20.1%)
Ladybirds 7 ( 2.7%) 15 ( 6.8%) 11 ( 2.6%) 842 (46.8%)
Lacewings 19 ( 7.5%) 4 ( 1.8%) 11 ( 2.6%) 129 ( 7.2%)
Hoverflies 14 ( 5.5%) 6 ( 2.7%) 20 ( 4.7%) 297 (16.5%)
Predatory bugs 12 ( 4.7%) 13 ( 5.9%) 21 ( 4.9%) 169 ( 9.4%)
Total 255 220 430 1798
69
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
6th
March
11th
March
16th
March
23rd
March
30th
March
6th
April
15th
April
20th
April
27th
April
5th May
No.
pre
dato
rs p
er
pla
nt
Other predators
Ants
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders on ground
Spiders on foliage
Figure 2. Number of predators logged from broccoli (mean per plant)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
6th
March
11th
March
16th
March
23rd
March
30th
March
6th
April
15th
April
20th
April
27th
April
5th May
No.
pre
dato
rs p
er
pla
nt
Other predators
Ants
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders on ground
Spiders on foliage
Figure. 3 Number of predators logged from cabbage (mean per plant)
70
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
6th
March
11th
March
16th
March
23rd
March
30th
March
6th
April
15th
April
20th
April
27th
April
5th May
No.
pre
dato
rs p
er
pla
nt
Other predators
Ants
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders on ground
Spiders on foliage
Figure. 4 Number of predators logged from cauliflower (mean per plant)
0
5
10
15
20
25
30
35
6th
March
11th
March
16th
March
23rd
March
30th
March
6th
April
15th
April
20th
April
27th
April
5th May
No.
pre
dato
rs p
er
pla
nt
Other predators
Ants
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders on ground
Spiders on foliage
Figure. 5 Number of predators logged from Chinese cabbage (mean per plant). Note: Y-axis
scale differs from that in figures. 2 to 4
Spiders
Spiders comprised the largest predator group. They were grouped into those found on the
ground and those found on foliage.
Over 60% of spiders found on the ground were Lycosidae. Others recorded from the ground
were unidentified ground-dwelling hunting spiders, plus a few thought to be foliage-dwelling
71
species which had become dislodged from the plant. The actual percentage of lycosids was
probably higher, as only those that could be identified with confidence were recorded as
lycosids, all others being recorded as unidentified. There were significantly fewer lycosids in
broccoli than any other crop but no significant differences amongst the other crops (Wald
Statistic = 19.39, P < 0.001).
Where possible, the spiders found on the foliage were categorised according to family (Fig.
6). The majority of those that could be identified were Theridiidae: 38% to 56% dependent
on crop type. However, it is possible that some similar spiders were included in error, due to
difficulties in identifying these small spiders in the field. Many spiders found on the foliage
could not be identified with confidence, particularly juveniles and very small spiders. The
majority of these were small web-dwelling types, and it is likely that a large proportion of
them were actually unidentified Theridiidae, as well as other families such as Tetragnathidae,
Araneidae and Linyphiidae. The second most numerous type of foliage-dwelling spider in all
crops except Chinese cabbage was the sac or night-stalking spiders (Clubionidae and
Miturgidae, formerly both in the „catch-all‟ family Clubionidae), comprising 7 to 15%
depending on crop type. Other spiders logged from the foliage included Salticidae, Araneidae
and Oxyopidae.
Three specimens, representative of each of the three most commonly observed groups
(Lycosidae, Theridiidae, Clubionidae/Miturgidae) were collected and sent to Owen Seeman at
the Queensland Museum (Brisbane) for expert identification. Identifications were: Artoria sp.
(Lycosidae), Cryptachaea veruculata (formerly Achaearanea) (Theridiidae), Cheiracanthium
gilvum (Miturgidae) (two specimens) and Clubiona sp. (Clubionidae) (one specimen).
0
10
20
30
40
50
60
70
80
90
100
Broccoli Cabbage Cauliflower Chinese cabbage
Cu
mu
lati
ve n
o.
sp
iders
Unidentified
Salticidae
Oxyopidae
Clubionidae/Miturgidae
Araneidae
Theridiidae
Figure. 6 Family composition of foliage-dwelling spiders (cumulative numbers logged per
crop over the trial period)
72
The number of theridiids found in the four crops varied over time (Wald statistic = 47.83, P <
0.01) (Fig. 7). Numbers were highest in broccoli at the start of the trial, and in cauliflower
later in the trial (table 3).
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
3-Mar 10-Mar 17-Mar 24-Mar 31-Mar 7-Apr 14-Apr 21-Apr 28-Apr 5-May
Nu
mb
er
of
sp
iders
per
pla
nt
Broccoli
Cabbage
Cauliflower
Chinese cabbage
Figure. 7 Number of Theridiidae logged from each brassica crop (mean per plant)
Table 3. Effect of crop on mean number of Theridiidae per groups of sampled plants over
time (back transformed data). For each date, means followed by same letter do not differ
significantly.
Date Crop
Broccoli Cabbage Cauliflower Ch. cabbage
6/3/09 1.0 a 1.0 a 0.5 a 0.7 a
11/3/09 2.9 a 1.4 a 1.2 a 1.2 a
16/3/09 2.4 a 1.0 ab 1.2 ab 0.2 b
23/3/09 1.2 ab 0.5 a 2.2 ab 2.4 b
30/3/09 2.9 a 0.7 b 3.4 a 2.6 a
6/4/09 3.1 a 2.9 a 7.0 b 4.1 ab
15/4/09 3.1 ab 1.7 a 7.9 c 5.5 bc
20/4/09 1.9 a 2.4 a 6.7 b 5.3 b
27/4/09 2.6 a 3.8 a 12.5 b 5.0 a
5/5/09 5.3 ab 2.9 a 7.2 b 6.0 b
More clubionids were logged from cauliflower, and more salticids from Chinese cabbage
compared with the other crops (table 4). Numbers of other foliage-dwelling spiders
(Oxyopidae, Araneidae and Thomisidae) were too low to allow statistical analysis.
73
Table 4. Effect of crop on mean cumulative numbers of Clubionidae and Salticidae (back
transformed data). For each spider group, means followed by same letter do not differ
significantly.
Spider group Crop
ANOVA Broccoli Cabbage Cauliflower Ch. cabbage
Clubionidae 5.0 a 4.2 a 13.5 b 6.2 a F = 6.05
P < 0.05
Salticidae 0.9 a 1.4 a 1.2 a 8.6 b F = 12.65
P = 0.001
Predatory insects
The most abundant predatory insects were ladybirds (Coccinellidae), lacewings (almost
exclusively brown lacewings, Hemerobiidae), hoverflies (Syrphidae), predatory bugs (a
variety including brokenbacked bugs, Taylorilygus pallidulus; brown smudge bugs,
Deraeocoris signatus; assassin bugs, Reduviidae; pirate bugs, Orius spp.; big eyed bugs, not
identified to species) and ants (Formicidae). Also recorded but not analysed statistically were
small numbers of native earwigs, centipedes and predatory thrips.
Numbers of ladybirds in the four crops varied over time (Wald statistic = 49.71, P < 0.001).
Higher numbers of this insect were found in the Chinese cabbage compared to any other crop
(table 5). Lacewings, hoverflies and predatory bugs were also found in greater numbers in
Chinese cabbage than any other crop (table 6). Crop type had no effect on numbers of ants
(table 6).
Table 5. Effect of crop on mean number of ladybirds (larvae, pupae and adults) per group of
sampled plants over time (back transformed data). For each date, means followed by same
letter do not differ significantly.
Date Crop
Broccoli Cabbage Cauliflower Ch. cabbage
6/3/09 0 0 0 0
11/3/09 0 0 0 0
16/3/09 0.2 a 0.2 a 0.2 a 1.2 a
23/3/09 0.0 a 0.5 a 0.5 a 2.2 a
30/3/09 0.2 a 0.2 a 0.0 ab * 3.9 b
6/4/09 0.7 a 0.2 a 0.7 a 4.9 b
15/4/09 0.0 ab * 0.5 a 1.0 a 13.0 b
20/4/09 0.0 ab * 0.7 a 0.0 ab * 21.1 b
27/4/09 0.2 a 0.2 a 0.2 a 66.6 b
5/5/09 0.2 a 1.0 a 0.0 ab * 93.9 b
* The reported „no significant difference‟ for these groups is due to the fact that all values
were zero, resulting in large standard errors
74
Table 6. Effect of crop on mean cumulative numbers of lacewings, hoverflies, predatory bugs
and ants (back transformed data). For each predator group, means followed by same letter do
not differ significantly.
Predator group Crop
ANOVA Broccoli Cabbage Cauliflower Ch. cabbage
Lacewings
(larvae, pupae,
adults)
4.1 a 0.7 a 1.9 a 28.2 b
F = 11.72
P < 0.005
Hoverflies
(larvae, pupae) 2.7 a 0.6 a 3.2 a 65.6 b
F = 23.03
P < 0.001
Predatory bugs
(nymphs, adults) 2.5 a 2.7 a 5.2 a 41.5 b
F = 38.55
P < 0.001
Ants
(adults) 2.2 a 6.4 a 4.4 a 10.7 a
F = 2.91
P > 0.05
Parasitoids
Visual inspections of the plants found very low levels of parasitism throughout the trial
period. Parasitised aphids were first observed approximately 6 weeks post seedling
transplantation (6th April), however aphid mummies were not found on every sampled plant
and percentage parasitism per plant rarely exceeded 10%. Parasitism of Lepidoptera was
extremely low throughout the trial period, recorded only occasionally. Parasitism of cabbage
white larvae with Cotesia sp. was first observed 4 weeks post transplantation (23rd
March);
parasitism of diamondback moth pupae with Diadegma semiclausum) was observed from 7
weeks post transplantation (15th April). One looper larva was found parasitised with
Litomastix sp. and a cabbage cluster caterpillar was parasitised with Microplitis sp..
Results of sampling for parasitism
Samples of whitefly, diamondback moth and cabbage white butterfly were collected and
monitored for parasitism. Chinese cabbage was excluded from sampling as it was not
possible to collect sufficient insects from this crop.
Whitefly scales
Eretmocerus sp. was the dominant whitefly parasitoid (table 7). Unfortunately, whitefly
emergence and natural mortality were not recorded. Therefore the percentage parasitism
figures cannot be viewed as an accurate representation of parasitism levels in the crop.
Table 7. Effect of crop on parasitism of whitefly scale
Broccoli Cabbage Cauliflower
Eretmocerus sp. emergence 14 (10.6%) 9 (9.3%) 4 (3.2%)
Encarsia sp. emergence 0 0 2 (1.6%)
Total number scales collected 132 97 124
75
Diamondback moth larvae and pupae
D. semiclausum was the only parasitoid to emerge from sampled DBM (table 8).
Table 8. Effect of crop on parasitism of diamondback moth
Broccoli Cabbage Cauliflower
D. semiclausum emergence 5 (27.8%) 3 (42.8%) 6 (46.1%)
DBM emergence 8 (44.4%) 2 (28.6%) 3 (23.1%)
Natural mortality 5 (27.8%) 2 (28.6%) 4 (30.8%)
Total number DBM collected 18 7 13
Cabbage white larvae and pupae
Cabbage white were parasitised with Pteromalus puparum and tachinid flies (not identified to
species) (table 9). No Cotesia sp. were found during this sampling process, although cabbage
white larvae parasitised with Cotesia sp. were observed during the visual sampling
assessments.
Table 9. Effect of crop on parasitism of cabbage white
Broccoli Cabbage Cauliflower
Tachinid fly emergence 4 (23.5%) 1 ( 6.7%) 3 (15.8%)
P. puparum emergence 1 ( 5.9%) 0 5 (26.3%)
Cabbage white emergence 10 (58.8%) 10 (66.7%) 11 (57.9%)
Natural mortality 2 (11.8%) 4 (26.7%) 0
Total number collected 17 15 19
Results of sampling with sticky traps
Parasitoids
Parasitoids trapped over the trial period were: Eretmocerus sp. and Encarsia sp. (whitefly
parasitoids); D. semiclausum (DBM parasitoid); P. puparum (cabbage white parasitoid).
Eretmocerus sp. was the dominant whitefly parasitoid, confirming the findings of the
parasitism experiments. Trap catches of both Eretmocerus sp. and Encarsia sp. were
generally lower in the Chinese cabbage than the other crops (tables 10 and 11).
There was no significant effect of crop on cumulative numbers of trapped P. puparum (table
11). Numbers of trapped D. semiclausum were too low to allow statistical analysis (table 11).
Table 10. Effect of crop on mean number of Eretmocerus sp. per sticky trap over time (back
transformed data). For each date, means followed by same letter do not differ significantly.
Trapping period Crop
Broccoli Cabbage Cauliflower Ch. cabbage
30/3/09 – 6/4/09 8.9 a 8.7 a 7.1 a 0.7 b
6/4/09 – 15/4/09 10.6 ab 12.2 a 6.6 bc 4.9 c
15/4/09 – 21/4/09 4.2 a 2.6 a 2.4 a 3.8 a
21/4/09 – 28/4/09 5.7 a 1.2 bc 2.6 b 0.5 c
28/4/09 – 5/5/09 20.2 a 10.4 b 15.8 a 4.0 c
76
Table 11. Effect of crop on mean numbers of Encarsia sp. (main effects, GLM), P. puparum
(cumulative, ANOVA) (back transformed data) and D. semiclausum (data insufficient for
statistical analysis). Means followed by the same letter do not differ significantly.
Parasitoid Crop ANOVA /
GLM (Wald statistic) Broccoli Cabbage Cauliflower Ch cabbage
Encarsia sp. 2.8 ab 2.1 ac 3.2 b 1.4 c WS = 18.35
P < 0.001
D. semiclausum 3.3 2.0 3.8 6.8 N/A
P. puparum 10.0 4.4 7.6 4.6 F = 0.83
P > 0.05
Predators
The most abundant predators captured on sticky traps were predatory bugs (mainly
brokenbacked bugs and pirate bugs) and ladybirds (transverse, Coccinella transversalis;
variable, Coelophora inaequalis; three-banded, Coelophora inaequalis; minute two-spotted,
Diomus notescens; common spotted, Harmonia conformis). Although white collared
ladybirds were observed on occasion during visual inspections of the plants, these insects
were not logged from sticky traps. Very low numbers of lacewings, hoverflies, spiders
(various families) and soldier beetles (Chauliognathus pulchellus) were also trapped.
More predatory bugs and ladybirds were trapped in the Chinese cabbage compared with the
other crops (table 12), corresponding with the findings of the visual inspections. Insufficient
numbers of lacewings, spiders, hoverflies and soldier beetles were trapped to allow statistical
analysis.
Table 12. Effect of crop on mean cumulative trapped predatory fauna (predatory bug and
ladybird data are back transformed). For each predator group, means followed by the same
letter do not differ significantly.
Predator group Crop Test result
(ANOVA) Broccoli Cabbage Cauliflower Ch cabbage
Predatory
bugs 2.9 ab 1.1 a 7.1 bc 11.9 c
F = 4.81
P < 0.05
Ladybirds 2.5 a 5.5 a 3.4 a 30.0 b
F = 13.14
P = 0.001
Results of pitfall trapping
The following ground-dwelling predators were logged from pitfall traps: spiders (mainly
lycosids); ants; common brown (native) earwigs (Labidura truncata); ground beetles
(Carabidae); centipedes (Chilopoda, only three trapped) (Fig. 8). Small numbers of foliage-
dwelling predators (e.g. ladybird larvae) were also trapped but not logged. There was a
significant effect of crop on trap catch of ants and native earwigs (table 13).
77
Table 13. Effect of crop on mean numbers of lycosid spiders, ants (main effects, GLM),
carabid beetles and native earwigs (cumulative, ANOVA) (back transformed data). For each
predator group, means followed by same letter do not differ significantly.
Predator group Crop ANOVA /
GLM (Wald statistic) Broccoli Cabbage Cauliflower Ch cabbage
Lycosid spiders 2.0 2.3 2.3 1.7 WS = 4.62
P > 0.05
Ants 2.6 ab 3.6 a 1.9 b 2.5 ab WS = 9.68
P < 0.05
Carabid beetles 1.0 1.4 2.7 1.4 F = 0.37
P > 0.05
Native earwigs 24.8 a 39.1 b 42.9 b 10.8 c F = 22.04
P < 0.001
0
0.5
1
1.5
2
2.5
3
3.5
4
Broccoli Cabbage Cauliflower Chinese cabbage
No
. p
red
ato
rs p
er
trap
per
assessm
en
t
Ants
Ground beetles
Native earwigs
Lycosid spiders
Figure 8. Ground-dwelling predators logged from pitfall traps in each crop type (mean per
trap per assessment)
Discussion
Cabbage cluster caterpillar was the most abundant and most damaging lepidopteran pest
species in all crops, although it was less problematic in Chinese cabbage than the other
brassica types. Other Lepidoptera species occurred in comparatively low numbers, although
more centre grub were found in Chinese cabbage than other crops. Aphids and silverleaf
whitefly were the dominant sucking pests in the majority of the brassica types: aphids were
particularly abundant in the Chinese cabbage, and whitefly in the broccoli.
There were more predators (particularly ladybirds) and a greater variety of predators in
Chinese cabbage than broccoli, cabbage or cauliflower. This was probably primarily due to
the large aphid population in the Chinese cabbage, which would have attracted
aphidophagous predators such as ladybirds, lacewings and hoverflies. However, numbers of
78
predatory insects in Chinese cabbage began to increase relative to the other brassicas before
the difference in aphid populations became apparent, implying that the effect in this crop was
not due to aphids alone. Previous experiments have found that white collared ladybirds
(Hippodamia variegata) are better able to forage on Chinese cabbage than on broccoli,
cabbage or cauliflower (Nolan, 2007). It is possible, therefore, that ladybirds have a
preference for Chinese cabbage over other brassica types, which contributed to the higher
numbers found in this crop.
Spiders were the most abundant predator type in all crops except Chinese cabbage. Ground-
dwelling spiders mainly comprised Lycosidae. Of those foliage-dwelling spiders that were
identified, Theridiidae were most numerous, with the combined Clubionidae/Miturgidae
forming the second largest group. Only small numbers of other foliage-dwelling families
were recorded. Visual sampling found fewer lycosids in broccoli than the other brassica
types. This difference was apparent from approximately five weeks post transplantation
onwards, so may have been due to differences in crop cover or availability of prey. However,
pitfall trapping failed to find any differences between the crops. Distribution of foliage
dwelling spiders in the different brassica types varied according to family: theridiids were
more numerous in broccoli compared to other brassicas when plants were at the late seedling
stage, but more abundant in cauliflower later in the trial; clubionids/miturgids were found in
higher numbers in cauliflower than the other brassicas; numbers of salticids were highest in
the Chinese cabbage.
The most numerous foliage-dwelling predatory insects were ladybirds, brown lacewings,
hoverflies and predatory bugs. Whereas spiders were found in newly transplanted seedlings,
predatory insects were not observed until at least three weeks post transplantation, and large
populations did not develop until plants were close to harvest. Ladybirds were generally the
first of the foliage-dwelling predatory insects to be found in the crops. All foliage-dwelling
predatory insects were most abundant in Chinese cabbage, with no differences between the
other three brassica crops.
Ground-dwelling predatory insects included ants, common brown (native) earwigs and small
numbers of carabid beetles. More brown earwigs were found in the cauliflower and cabbage
than the broccoli, with fewest in the Chinese cabbage.
Rates of parasitism were low for all pest species. Parasitism of the following pests was
observed during the trial: aphids, whitefly, diamondback moth, cabbage white, looper (single
incidence) and cabbage cluster caterpillar (single incidence).
Eretmocerus sp. was the most numerous of the parasitoids trapped on sticky traps. Both
trapping and sampling for parasitism found it to be the dominant whitefly parasitoid. This
differs from findings of surveys conducted in 2007 and 2008 (Subramaniam et al., 2010), in
which Eretmocerus sp. dominated early in the season, but was replaced by Encarsia sp. from
mid to late April onwards. In the current trial, numbers of Encarsia sp. remained low
throughout the trial period (until early June). This may be a reflection of a general decline in
numbers of Encarsia sp. following the innundative releases of Eretmocerus sp. (S.
Subramaniam, pers. comm.). Fewer Eretmocerus sp. and Encarsia sp. were trapped in
Chinese cabbage than the other brassica crops, reflecting the low numbers of whitefly scale in
this crop.
Numbers of all other parasitoids were low. Parasitised aphids were not observed until
approximately six weeks post seedling transplantation (6th April), and numbers remained low
throughout the trial. D. semiclausum was the only diamondback moth parasitoid logged
during the trial period. Preliminary trials performed in 2008 found that Diadromus collaris
and Oomyzus sp. were not present until later in the season (August). Parasitism of cabbage
white larvae with Cotesia sp. was observed occasionally during visual inspections of plants.
79
However, P. puparum and tachinid flies were the only parasitoids that emerged from cabbage
whites sampled for monitoring of parasitism.
A variety of sampling methods were employed. Visual inspection of intact and destructively
sampled plants gave broadly similar results, although more pests and predators were generally
recorded through destructive sampling. This was particularly so for Chinese cabbage (and
cabbage to a lesser extent), due to the compact structure of these plants. It is therefore
possible that inspection of intact plants would fail to detect the presence of very low numbers
of insects.
Use of sticky traps and visual inspection of plants gave similar results for the sucking pests,
predatory bugs and ladybirds. However, sticky traps caught very few lacewings or hoverflies;
therefore it appears that trapping is not appropriate for monitoring these predators.
Pitfall trapping resulted in large catches of some pest insects (e.g. earwigs, crickets,
wireworms). However, with the exception of native earwigs, few beneficial species were
trapped, and no difference between crops could be detected.
Conclusions
Parasitism was low throughout the trial; predators are therefore an important component
of the beneficial fauna in early season brassica crops.
Of the predators, spiders were the most abundant in the majority of brassica types, and the
first predators to arrive in the newly transplanted crop. The dominant spider families
were Lycosidae, Theridiidae and Clubionidae/Miturgidae.
There were differences in abundance of predatory fauna between the four brassica crops,
however it is likely that this was primarily due to differences in abundance of prey.
Chinese cabbage had the highest numbers of predators and sucking pests; with the
exception of centre grub, numbers of lepidopteran pests were low.
Cauliflower had the second highest predator abundance.
A range of sampling methods should ideally be used to monitor beneficial species:
o Visual inspection of plants (particularly destructive sampling) is a good method
for detecting most species, although small, quick-moving and nocturnal species
can be missed.
o Sticky traps can be used to monitor for flying insects such as parasitoids,
ladybirds and predatory bugs, but catch few hoverflies or lacewings.
o Pitfall trapping is used for monitoring ground-dwelling predators, many of which
are nocturnal; however this method is time-consuming and can be difficult to set
up correctly.
Acknowledgements
I gratefully acknowledge Madaline Healey, Mary Firrell, Darren Williams, Ron Herman and
Carolyn Church for technical and field assistance; Dr Mike Furlong (project collaborator,
University of Queensland); Gatton Research Station farm staff; Susan Fletcher (biometrician).
References
Nolan, B. (2007) Using Hippodamia ladybird in brassica integrated pest management. Final
report for HAL project VG04017.
Subramaniam, S., Gunning, R., Sivasubramaniam, V., Firrell, M., Nolan, B., Lovatt, J., Kay,
I. & Heisswolf, S. (2010) Development and promotion of IPM strategies for silverleaf
whitefly in vegetables. Final report for HAL project VG05050.
80
4.2 IDENTIFYING NATURAL ENEMIES OF EARLY SEASON
BRASSICA PESTS IN COMMERCIAL PLANTINGS IN THE
LOCKYER VALLEY
L. Senior (Agri-Science QLD, DEEDI) and M. Healey (Agri-Science QLD, DEEDI)
Introduction
On-station trials carried out in unsprayed brassica plantings at Gatton Research Station in
2009 documented the beneficial complex from transplanting to harvest (section 4.1).
Following these trials, the second part of the objective focussed on sampling at growers‟
properties in the Lockyer Valley region. The aim was to determine whether a similar type
and incidence of natural enemies would be found in commercial crops, and whether the
natural enemy complex varied between different farm sites with different management
practices.
Methods
Sampling was carried out in commercial plantings of broccoli, cauliflower and cabbage at
three vegetable farms in the Lockyer Valley region (south-east Queensland) (photographs
presented in appendix 2.2 (I)). Crops were transplanted in February, representative of an
early season planting in this region. Two sites were sampled at each of the three farms.
Sampling sites
Farm 1
Location: Mt Whitestone
Crops under assessment: broccoli and cauliflower, planted 10th February 2010, representing
the first brassica plantings of the season at this property. The two sampling sites were
situated approximately 400 m apart.
Pesticide use: organic farmer; Bacillus thuringiensis (Bt) was applied at approximately
weekly intervals; neem oil (azadirachtin) was applied intermittently, more frequently to the
cauliflower.
Other information: Trichogramma wasps were released for control of heliothis and other
lepidopteran pests.
Farm 2
Location: Grantham
Crops under assessment: cabbage, planted 15th February 2010. The first brassica planting at
this property (broccoli and cabbage) had occurred several weeks previously. The two
sampling sites were: an area of commercial cabbage crop treated according to the grower‟s
normal practices (referred to as „sprayed‟); an area of unsprayed cabbage located at the end of
the row of commercial crop (referred to as „unsprayed‟, however spray drift into the area
occurred on at least one occasion). Approximately 10 m of unsprayed crop separated the two
areas.
Pesticide use: not organic; insecticides applied were Proclaim® (emamectin benzoate),
Coragen® (chlorantraniliprole), Bt and one application of Success® (spinosad) (not found to
be effective).
81
Farm 3
Location: Glenore Grove
Crops under assessment: broccoli and a mixed brassica planting, planted 22nd
February 2010.
The first brassica planting at this property (broccoli, cauliflower, cabbage) had occurred
approximately two weeks previously. The broccoli was an area of commercial crop treated
according to the grower‟s normal practices (referred to as „sprayed‟). The mixed brassica
planting (broccoli, cabbage and cauliflower) was entirely untreated (referred to as
„unsprayed‟). The two areas were situated approximately 1 km apart.
Pesticide use: organic farmer; Bt was applied at approximately weekly intervals; Entrust®
(spinosad) was applied intermittently.
Other information: the unsprayed planting was located close to a creek and, as no weed
control was performed, developed large populations of weeds. The sprayed planting was
located close to a stand of native vegetation, which had been planted to encourage natural
enemies
Sampling methods
Visual inspections of plants were carried out approximately weekly from transplantation
onwards (table 1). Thirty plants were inspected at each site, at each assessment, following the
same procedure as for the on-station trials (section 4.1). Any parasitism of aphids,
lepidopteran eggs or lepidopteran larvae was noted. Five pitfall traps and five yellow sticky
traps were placed at each of the six sites and changed approximately twice weekly from
transplantation onwards (table 1). Due to the large quantities of arthropods encountered
during the sampling process, the majority were identified to the level of family only, although
genus and species were noted where possible.
Table 1. Trial dates
Date Days post
transplantation
Activity
10/2/10 Farm 1 - 0 Farm 1 seedlings transplanted
15/2/10 Farm 2 - 0 Farm 2 seedlings transplanted
15/2/10 Farm 1 - 5 (1st) Farm 1 assessment; pitfall and sticky traps set up
22/2/10
Farm 1 - 12 (2nd
)
Farm 2 - 7 (1st)
Farm 3 - 0
Farm 1 assessment and traps changed
Farm 2 assessment; pitfall and sticky traps set up
Farm 3 seedlings transplanted
26/2/10 Farm 1 - 16
Farm 2 - 11
Farm 1 traps changed
Farm 2 traps changed
5/3/10 Farm 3 - 11 (1st) Farm 3 assessment (NB traps NOT set up)
5/3/10 Farm 1 - 23 (3
rd)
Farm 2 - 18 (2nd
)
Farm 1 assessment and traps changed
Farm 2 assessment and traps changed
8/3/10 Farm 1 - 26 (4
th)
Farm 2 - 21 (3rd
)
Farm 1 assessment and traps changed
Farm 2 assessments
9/3/10 Farm 2 - 22
Farm 3 - 15 (2nd
)
Farm 2 traps changed
Farm 3 assessment; pitfall and sticky traps set up
12/3/10
Farm 1 - 30
Farm 2 - 25
Farm 3 - 18
Traps changed
15/3/10
Farm 1 - 33 (5th)
Farm 2 - 28 (4th)
Farm 3 - 21
Farm 1 assessment and traps changed
Farm 2 assessment and traps changed
Farm 3 changed (no assessment)
17/3/10 Farm 3 - 23 (3rd
) Farm 3 assessment
19/3/10
Farm 1 - 37
Farm 2 - 32
Farm 3 - 25
Traps changed
82
22/3/10
Farm 1 - 40 (6th)
Farm 2 - 35 (5th)
Farm 3 - 28 (4th)
Farm 1 assessment and traps changed in broccoli only
Farm 2 and traps changed
Farm 3 assessment and traps changed
24/3/10 Farm 1 - 42 Farm 1 assessment and traps changed in cauliflower
26/3/10
Farm 1 - 44
Farm 2 - 39
Farm 3 - 32
Traps changed
29/3/10
Farm 1 - 47 (7th)
Farm 2 - 42 (6th)
Farm 3 - 35 (5th)
Assessments and traps changed
6/4/10
Farm 1 - 55
Farm 2 - 50
Farm 3 - 43
Traps changed
9/4/10
Farm 1 - 58 (8th)
Farm 2 - 53 (7th)
Farm 3 - 46 (6th)
Assessments and traps changed
12/4/10
Farm 1 - 61 (9th)
Farm 2 - 56 (8th)
Farm 3 - 49 (7th)
Final assessments and traps collected
Results
Results are presented as the average number of pest or beneficial arthropods per sampled
plant (n = 30), sticky trap (n = 5) or pitfall trap (n = 5) at each assessment date. Where data
are summarised across the trial period, results are presented as the average number of insects
per plant/trap for one standard assessment: results for all plants/traps across all assessments
were pooled, then divided by the number of plants (30) or traps (5) and by the number of
assessments. Differing planting dates at the three properties meant that the sites were
sampled for differing periods of time; hence cumulative data would not have provided a valid
comparison between sites.
Weather data for the trial period are presented in appendix 2.2 (II).
Pest species
Detailed results are presented in appendix 2.2 (III).
Lepidoptera (results of visual inspections of plants)
Numbers of Lepidoptera were generally very low, rarely exceeding three larvae per plant even
in the unsprayed plantings. Cabbage cluster caterpillar (Crocidolomia pavonana) (Fig. 1)
and cluster caterpillar (Spodoptera litura) (Fig. 2) were the main lepidopteran species at the
majority of sites, and the only lepidopteran pests occurring in significant numbers early in the
crop.
Other lepidopteran species included cabbage white (Pieris rapae), centre grub (Hellula
hydralis), heliothis (Helicoverpa sp.) and diamondback moth (Plutella xylostella). The
incidence of these species varied between sites. Very small numbers of loopers
(Chrysodeixis sp.) were also observed.
83
0
0.5
1
1.5
2
2.5
3
3.5
4
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
larv
ae p
er
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure 1. Number of cabbage cluster caterpillar larvae logged from plants at each site (mean
per plant, n = 30)
0
0.5
1
1.5
2
2.5
3
3.5
4
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
larv
ae p
er
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure 2. Number of cluster caterpillar larvae logged from plants at each site (mean per plant,
n = 30)
Sucking insects (results of visual inspections of plants and sticky trapping)
Aphids (exclusively Myzus persicae) were the dominant sucking pest at farms 1 and 3, as
monitored using visual inspections of plants (Fig. 3). Sticky trapping and counts from plants
84
gave similar results, with the traps providing earlier detection. Very few aphids were
recorded from plants at farm 2, although they were caught on the sticky traps.
0
5
10
15
20
25
30
35
40
45
50
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
ap
hid
s p
er
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 3 Number of aphids logged from plants at each site (mean per plant, n = 30)
Silverleaf whitefly (Bemisia tabaci) were the second most abundant sucking pest at farms 1
and 3 when monitored using visual inspections of plants, and the most dominant at farm 2
(Fig. 4). The two sampling methods (sticky traps and inspection of plants) produced similar
results.
0
2
4
6
8
10
12
14
16
18
20
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
wh
itefl
y a
du
lts p
er
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 4 Number of silverleaf whitefly adults logged from plants at each site (mean per
plant, n = 30)
85
Thrips and leafhoppers were caught in large numbers on sticky traps; however few of these
pests were detected during visual inspections of plants.
Other pests
Other foliage-dwelling pests such as flea beetles and Rutherglen bugs were recorded at very
low levels. Ground-dwelling pests such as earwigs, crickets and wireworms were recorded
from pitfall traps.
Beneficial species
Detailed results are presented in appendix 2.2 (IV).
Foliage-dwellers
Overview
Visual inspections found that spiders were the most abundant predator type, and one of the
first predators to arrive in the newly planted crops. Predatory insects did not appear on the
plants until three to five weeks post transplantation. Small numbers of spiders and adult
predatory insects were caught on sticky traps throughout the trial period. There was no
apparent similarity between results of the visual inspections and sticky trap catches.
Parasitism was low throughout the trial period.
Foliage-dwelling spiders
The majority of the foliage-dwelling spiders were theridiids (28% to 48% depending on site)
and unidentified spiders (many of which were juvenile, web-building types) (Fig. 5).
Clubionidae and Miturgidae (formerly both in the „catch-all‟ family Clubionidae) together
comprised the second largest group, although the relative proportion varied greatly between
sites (between 5% and 41%). The Araneidae formed a substantial component of the spider
fauna at farm 1, as did Thomisidae at the farm 1 cauliflower site.
Comparing the different sites, the greatest number and diversity of foliage-dwelling spiders
were found at the farm 1 sites (Fig. 5). The fewest were found at farm 3 unsprayed; numbers
of theridiids and unidentified spiders were particularly low at this site. Surprisingly, there
were more foliage spiders in the sprayed than unsprayed site at farm 3. Populations of
foliage-dwelling spiders at farm 1 increased steadily over the first few weeks post
transplantation (Fig. 6). Spider populations at farms 2 and 3 were more variable.
86
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Farm 1
(organic)
broccoli
Farm 1
(organic)
cauliflower
Farm 2
(conventional)
unsprayed
Farm 2
(conventional)
sprayed
Farm 3
(organic)
unsprayed
Farm 3
(organic)
sprayed
Grower site
No
. sp
iders
per
pla
nt
per
assessm
en
tTheridiidae Araneidae
Tetragnathidae Clubionidae/Miturgidae
Oxyopidae Salticidae
Thomisidae Unidentified
Figure. 5 Family composition of foliage-dwelling spiders logged during visual inspections of
plants (mean per plant per one standard assessment)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
15/02/10 22/02/10 1/03/10 8/03/10 15/03/10 22/03/10 29/03/10 5/04/10 12/04/10
Date
Nu
mb
er
of
sp
iders
per
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 6 Number of foliage-spiders logged from plants at each site (mean per plant, n = 30)
87
Foliage-dwelling predatory insects
The most abundant foliage-dwelling predatory insects were ladybirds, hoverflies, predatory
bugs and lacewings (almost exclusively brown lacewings, Hemerobiidae). The relative
abundance of these predators varied according to sampling site and sampling method (Figs. 7
and 8).
Visual assessments of the predatory insects found that they generally appeared on the plants at
least three weeks after planting (Fig. 9). However, sticky trapping found that many of these
predators (particularly hoverflies and ladybirds) were present in the sampling area from the
first assessment onwards (Fig. 10). Although there was considerable variation between sites,
ladybirds were generally one of the first predatory insects to appear on the plants; predatory
bugs and large numbers of hoverflies tended to appear later.
Comparing the different sites, visual assessments suggested that the foliage-dwelling
predatory insects were generally more abundant at farm 1 than the other sites, with the
exception of ladybirds at farm 3 unsprayed (Fig. 7). The fewest were found at farm 2. There
were generally more predatory insects at the unsprayed than sprayed sites, and more predatory
insects in the farm 1 cauliflower than broccoli.
Sticky trap results were dissimilar to the results of visual assessments of plants. For instance,
whereas very few hoverflies were detected on plants at farm 2, large numbers of this insect
were caught on sticky traps relative to the other sites.
0.00
0.02
0.04
0.06
0.08
0.10
0.12
Farm 1
(organic)
broccoli
Farm 1
(organic)
cauliflower
Farm 2
(conventional)
unsprayed
Farm 2
(conventional)
sprayed
Farm 3
(organic)
unsprayed
Farm 3
(organic)
sprayed
Site
No
. p
red
ato
ry i
nsects
per
pla
nt
per
assessm
en
t
Ladybirds
Lacewings
Hoverflies
Predatory bugs
Figure. 7 Comparison of foliage-dwelling predatory insects logged from plants at each site
(mean per plant per one standard assessment)
88
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Farm 1
(organic)
broccoli
Farm 1
(organic)
cauliflower
Farm 2
(conventional)
unsprayed
Farm 2
(conventional)
sprayed
Farm 3
(organic)
unsprayed
Farm 3
(organic)
sprayed
Site
No
. p
red
ato
ry i
nsects
per
trap
per
assessm
en
t
Ladybirds
Lacewings
Hoverflies
Predatory bugs
Figure. 8 Comparison of foliage-dwelling predatory insects logged from sticky traps at each
site (mean per trap per one standard assessment)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
pre
dato
ry i
nsects
per
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 9 Number of foliage-dwelling predatory insects logged from plants at each site (mean
per plant, n = 30)
89
0
0.5
1
1.5
2
2.5
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
pre
dato
ry i
nsects
per
trap
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 10 Number of foliage-dwelling predatory insects logged from sticky traps at each site
(mean per trap, n = 5)
Ground-dwellers
Ground-dwelling beneficials (spiders, common brown/native earwigs, ground beetles and
rove beetles) were assessed using pitfall traps. Centipedes were also trapped occasionally.
As very large numbers of ants were trapped on occasion, results for these insects are
presented separately. Visual inspection of plants was not used to monitor ground-dwelling
beneficials, as it was in the 2009 on-station trial, due to the difficulties in spotting these
predators reliably.
Spiders (mainly Lycosidae) were the most abundant ground-dwelling predator trapped at the
majority of sites (Fig. 11). They were found consistently at all sites throughout the trial
period. The ground-dwelling predatory insects varied considerably between sites (Fig. 11).
For instance, more common brown earwigs were trapped in the farm 1 cauliflower than any
other site; numbers of all predatory insects were particularly low at farm 2; ground beetles
were higher at farm 3 unsprayed than sprayed.
Unlike the foliage-dwelling predators, the majority of the ground-dwellers were generally
present from the first assessment onwards, and did not tend to increase in number as the crop
matured (Fig. 12).
90
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Farm 1
(organic)
broccoli
Farm 1
(organic)
cauliflower
Farm 2
(conventional)
unsprayed
Farm 2
(conventional)
sprayed
Farm 3
(organic)
unsprayed
Farm 3
(organic)
sprayed
Site
No
. p
red
ato
rs p
er
trap
per
assessm
en
t
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
Figure. 11 Comparison of ground-dwelling predators logged from pitfall traps at each site
(mean per trap per one standard assessment)
0
2
4
6
8
10
12
14
26/2/10 5/3/10 12/3/10 19/3/10 26/3/10 2/4/10 9/4/10
Date collected
Nu
mb
er
pre
dato
ry i
nsects
per
trap
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 12 Number of ground-dwelling predators logged from pitfall traps at each site (mean
per trap, n = 5)
91
Ants
Ants were monitored using pitfall traps and visual assessments of the plants and surrounding
area. They were present at all sites, throughout the sampling period (Figs. 13 and 14). The
ants were localised in their distribution: in several cases large numbers of ants were present in
only one of the five pitfall traps, or around only a couple of the 30 sampled plants at each site.
The two sampling methods (trapping and visual assessments) gave very different results. For
instance pitfall trapping indicated a large ant population at farm 1 broccoli, whereas visual
assessments detected relatively few ants at this site compared to others.
0
0.5
1
1.5
2
15-Feb 22-Feb 1-Mar 8-Mar 15-Mar 22-Mar 29-Mar 5-Apr 12-Apr
Date
Nu
mb
er
of
an
ts p
er
pla
nt
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 13 Comparison of numbers of ants logged from plants and immediately surrounding
area at each site (mean per plant, n = 30)
0
5
10
15
20
25
30
35
40
15-Feb 22-Feb 1-Mar 8-Mar 15-Mar 22-Mar 29-Mar 5-Apr 12-Apr
Date collected
Nu
mb
er
of
an
ts p
er
trap
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 14 Comparison of numbers of ants logged from in pitfall traps at each site (mean per
trap, n = 5)
92
Parasitoids
Parasitoids were assessed using sticky trapping. A wide range of species was trapped;
however catches at all sites were dominated by Trichogramma sp. and catch of other species
was low (Fig. 15). Moreover, very few parasitised insects were observed during visual
inspections of the plants.
Other than Trichogramma, the most common species trapped were the whitefly parasitoid
Eretmocerus sp., the diamondback moth parasitoid Diadegma sp. and the lepidopteran egg
parasitoid Telenomus sp.. The lepidopteran larval parasitoid Litomastix sp. formed a
significant component of the trap catch at the farm 3 sprayed site.
Notably, aphid parasitism was extremely low. Only two aphid parasitoids (Aphidius sp.) were
trapped over the entire trial period, both from the same site (farm 1 cauliflower). Likewise,
no aphid parasitism was observed at any time at farms 2 or 3, and only a very few aphid
mummies were observed during the final two assessments at farm 1 (less than 5% parasitism).
Although there was variation between sites, trap catch tended to peak between the 19th and
26th March (Fig. 16). The largest trap catches were found at farm 1 broccoli, and the lowest at
farm 3 unsprayed. Trap catch was much lower at the unsprayed than the sprayed farm 3 site.
0
1
2
3
4
5
6
7
8
9
10
11
Farm 1
(organic)
broccoli
Farm 1
(organic)
cauliflower
Farm 2
(conv)
unsprayed
Farm 2
(conv)
sprayed
Farm 3
(organic)
unsprayed
Farm 3
(organic)
sprayed
Site
No
. p
ara
sit
oid
s p
er
trap
per
assessm
en
t
Other Parasitoid
Aphidius
Trichopoda
Encarsia
Eretmocerus
Litomastix
Cotesia
Diadromus
Diadegma
Microplitis
Telenomus
Trichogramma
Figure. 15 Comparison of parasitoids logged from sticky traps at each site (mean per trap per
one standard assessment)
93
0
5
10
15
20
25
30
35
40
22-Feb 1-Mar 8-Mar 15-Mar 22-Mar 29-Mar 5-Apr 12-Apr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Farm 1 broccoli
Farm 1 cauliflower
Farm 2 unsprayed
Farm 2 sprayed
Farm 3 unsprayed
Farm 3 sprayed
Figure. 16 Comparison of total parasitoids (all species) caught on sticky traps at each site
(mean totals per trap, n = 5)
Discussion
The lepidopteran pest complex was dominated by C. pavonana and S. litura. The 2009 on-
station trial (section 4.1) also found C. pavonana to be dominant, whereas numbers of S.
litura in the current study were substantially higher than the 2009 trial. Conversely, numbers
of H. hydralis were somewhat lower than the 2009 trial.
Aphids (M. persicae) were the dominant sucking pest at the majority of sites, followed by
silverleaf whitefly, a similar finding to the 2009 on-station trial. Cabbage aphid (Brevicoryne
brassicae) was not found at any time. Numbers of thrips were very low at all sites, unlike the
2009 trial, in which thrips were found to cause some damage early in the life of the crop.
Higher numbers of silverleaf whitefly were recorded in farm 1 broccoli compared with the
cauliflower, confirming the 2009 on-station results. At farm 3, there were more aphids and
whitefly adults on the sprayed than unsprayed plants, which may have been related to the
higher numbers of ladybirds and hoverflies in the unsprayed plots.
Spiders formed the largest proportion of foliage- and ground-dwelling predators at the
majority of sites, confirming the findings of the 2009 on-station trial. Spiders were
particularly important during the first three weeks post-transplantation, during which time
they were the only predators found on the plants.
Theridiids formed the largest group of identified foliage-dwelling spiders at all sites, followed
by the combined clubionid/miturgid group. Unlike the 2009 trial, Araneidae and Thomisidae
were abundant at some sites. Populations of foliage-dwelling spiders at both farm 1 sites
displayed a similar pattern to the 2009 trial, increasing steadily as the crop matured. Spider
populations at farms 2 and 3 were more variable, possibly due to the impact of pesticide
sprays or, in the case of the farm 3 unsprayed site, due to competition with other predators.
There were fewer spiders at the unsprayed than sprayed site at farm 3. Examining the family
composition of the foliage-dwelling spiders, Clubionidae formed a large component at the
94
unsprayed site; the number of theridiids and unidentified spiders (mainly juveniles and small
species) was much lower in the unsprayed site compared to the sprayed. This may have been
due to the much larger number of predatory insects (particularly ground beetles and ants) at
the unsprayed site, which could have competed with the spiders, particularly the small
theridiids and juveniles: Sanders & Platner (2007) found that high densities of ants negatively
affected the abundance of web-building spiders such as Linyphiidae in dry grassland.
Unlike the 2009 trial, no clear difference in foliage-dwelling spider numbers was apparent
between the cauliflower and broccoli crops. However, as the two crops in the current trial
were not grown under identical conditions (as they were in the 2009 trial), a number of other
factors could have impacted on the spider populations.
There were more foliage-dwelling spiders and a greater variety of these spiders at farm 1
compared to any of the other sites. Because of the variation between sites it is not possible to
pinpoint any definitive reasons for this difference. However, some possible contributing
factors are the larger populations of aphids and whitefly, less use of pesticides harmful to
beneficials, and organic supplementation of soil at farm 1.
The current trial confirmed the 2009 findings that the most abundant foliage-dwelling
predatory insects were ladybirds, brown lacewings, hoverflies and predatory bugs, and that
these first appeared on the plants at least three weeks after planting. Ladybirds generally
appeared first, followed by lacewings and then hoverflies. As hoverfly adults do not settle on
plants and hence were not included in the visual inspection counts, it is logical that it would
take longer for these insects to be detected on the plants. Many of these predators
(particularly hoverflies and ladybirds) were caught on sticky traps from the first assessment
onwards, implying that they were present in the vicinity almost immediately following
transplantation, but that it took some time for a population to develop in the crop. It is likely
that this was associated with developing aphid populations, the preferred prey of hoverflies,
ladybirds and lacewings.
The greatest numbers of hoverflies and lacewings on the plants were found at farm 1, and the
highest numbers of ladybirds at the farm 3 unsprayed site. The fewest hoverflies and
lacewings were found at the three sites exposed to pesticides: farm 2 sprayed, farm 2
unsprayed (spray drift) and farm 3 sprayed. This finding indicates that hoverflies and
lacewings may have been particularly sensitive to pesticide use. However, it is also likely
that the differences were due in part to a correlation with aphid populations, which were
particularly low at the farm 2 sites. Differing aphid populations cannot explain the lower
numbers of predatory insects at the farm 3 sprayed site compared to unsprayed, as the peak
aphid population was actually slightly higher at the sprayed site. However, the location of the
farm 3 unsprayed plot close to a creek, and presence of large numbers of weeds, may have
contributed to the higher numbers of ladybirds and hoverflies at this site relative to the
sprayed crop.
Ground-dwelling predators varied considerably between sites. This variation could have been
due to any of a number of factors, such as soil type, pesticide use and surrounding habitat
type.
Many more common brown (native) earwigs were trapped from the farm 1 cauliflower
compared with the other sites, including the farm 1 broccoli. This correlates with the finding
of the 2009 trial, where significantly higher numbers of native earwigs were found in
cauliflower compared to broccoli. However, as the two crops at farm 1 were not grown under
identical conditions, other factors could have accounted for the difference in earwig
populations, and the correlation between the 2009 and 2010 trials may be coincidental.
95
The high numbers of ground beetles (many of them bombardier beetles) trapped at the farm 3
unsprayed site were most likely due to this site‟s proximity to a creek, a preferred habitat of
the bombardier beetle. Notably, particularly low numbers of ground beetles were found at
both sites at the non-organic farm 2.
Lycosid spiders formed the main component of the pitfall-trapped predators at the majority of
the sites and were trapped consistently throughout the trial period, unlike the ground-dwelling
predatory insects. Overall, most lycosids were trapped at farm 2. It is possible that this was
due to the low numbers of ground beetles and hence lack of competition. Likewise, at farm 3,
the large numbers of ground beetles at the unsprayed site could have accounted for the lower
numbers of lycosids at this site compared with the sprayed crop. Lang (2003) found that
removing ground beetles doubled numbers of Lycosidae in a winter wheat field.
Ants were found at all sites, throughout the trial period. The beneficial effects of ants are
uncertain: although they prey on a variety of pest species, they can protect aphids from attack
by other predators and have a negative impact on other beneficial species. The two methods
used to monitor the ants (pitfall traps and visual assessments of the plants and surrounding
area) gave very different results, largely due to the localised distribution of these insects. It is
likely that neither method gave an accurate assessment of ant activity.
The dominant parasitoid trapped at all sites was Trichogramma sp., accounting for between
52 and 77% of parasitoids trapped over the trial period. In contrast, very few Trichogramma
were trapped in the 2009 on-station trial. The large numbers of trapped adults in the 2010
trial did not appear to translate into high levels of parasitism, as no parasitised eggs were
observed. Moth eggs were checked for parasitism (black pigmentation) in the field during
sampling, however as samples were not collected to monitor parasitoid emergence, it is
possible that some parasitised eggs were overlooked.
The greatest numbers of Trichogramma were trapped at the farm 1 broccoli site. This grower
carried out regular releases of Trichogramma pretiosum throughout the trial period, in both
the broccoli and cauliflower crops. It is thought the lower trap catch from the cauliflower was
due to applications of neem oil, made more frequently to this crop. Reports of the effect of
neem on parasitoids are mixed, although it is classified as harmful according to the
International Organisation for Biological and Integrated Control of Noxious Animals and
Plants (IOBC) (Boller et al., 2005). Trap catch of Trichogramma at the two farm 2 sites was
similar to farm 1 cauliflower. Although releases of this wasp had been made several years
previously, none were made at this property during the trial period, hence trap catches were
the result of an established background population. Interestingly, catches of Trichogramma at
farm 3 were substantially lower at the unsprayed site compared with the sprayed. This may
have been due in part to the presence of suitable habitat (woody native vegetation) situated
close to the sprayed block. Another explanation is the much higher population of predators at
the unsprayed site. Knutson (1998) summarised studies which found that predators such as
predatory bugs, lacewing larvae and spiders can greatly reduce the impact of Trichogramma
by feeding on parasitised and unparasitised eggs.
A wide range of parasitoids other than Trichogramma were also trapped. The most
commonly occurring of these were Eretmocerus sp., Diadegma sp. and Telenomus sp..
However, numbers of these parasitoids were low (for example, on average less than one
Eretmocerus wasp was found per trap per assessment) and very few parasitised insects were
observed during visual inspections of the plants, correlating with the low incidence of
parasitism observed in the 2009 trial. Eretmocerus sp. was the dominant whitefly parasitoid,
and Diadegma sp. the dominant diamondback moth parasitoid, again correlating with the
2009 trial findings.
96
Aphid parasitoids were notable for their absence for the majority of the trial period.
Parasitism was not observed until 9th April, confirming the findings of the 2009 trial, where
parasitised aphids were first observed on 6th April. This indicates the importance of predators
for suppression of aphids early in the season.
Conclusions
Spiders were a key predator, particularly in the first few weeks post seedling
transplantation: theridiids and clubionids/miturgids were the most abundant foliage-
dwelling spiders; lycosids were the most abundant ground-dwelling spiders.
Foliage-dwelling predatory insects (ladybirds, lacewings, hoverflies and predatory bugs)
were often present in the vicinity of the newly planted crop. However, they did not
appear on the plants until at least three weeks after planting. Predatory insect populations
were probably linked both to pesticide use and to pest populations.
A variety of ground-dwelling predators were present from transplantation onwards:
lycosids were the dominant ground-dwelling predator, found consistently at all sites
throughout the trial period; ground-dwelling predatory insects (common brown earwigs,
ground beetles and rove beetles) varied considerably between sites.
Ants were abundant at all sites from transplantation onwards, but the contribution of these
insects to pest suppression is not known.
Parasitoid activity was low early in the season, with the exception of Trichogramma
(large numbers trapped at all sites). Notably, aphid parasitoids were absent until early
April.
There were some indications of an impact of farm management practices on beneficials,
as follows:
o Foliage-dwelling spiders were more abundant and more diverse at farm 1
(organic) compared to the other sites.
o Hoverflies and lacewings were most abundant at farm 1 and least abundant at the
sites exposed to pesticides. This may have been due to pesticide use and/or aphid
populations.
o Ladybirds were most abundant at the unsprayed farm 3 site and least abundant at
the sites exposed to pesticides. Again this was probably linked to aphid
populations as well as pesticide use.
o Ground beetles were least abundant at farm 2, the least beneficial-friendly
property.
o Trichogramma is thought to have been adversely affected by applications of
neem oil.
There was some indication of intraguild competition:
o Lycosid populations appear to have been inversely linked to ground beetle
populations.
o Foliage-dwelling spiders and Trichogramma may have been adversely affected
by large populations of predatory insects.
A combination of sampling methods (sticky trapping, inspections of plants, pitfall
trapping) is recommended to monitor beneficials.
o Sticky trapping was found to be a useful method for detecting parasitoids.
o The presence of predatory insects such as hoverflies on sticky traps did not
correlate with their presence on the plants.
o Pitfall trapping is recommended for ground-dwelling predators, but is time-
consuming to perform.
97
Acknowledgements
We gratefully acknowledge Darren Williams, Carolyn Church, Robert Mitchell, Mary Firrell
and Ron Herman for technical and field assistance; Gary Harm, Derek Schultz and Troy
Huggins for allowing access to their brassica crops; David Carey for assistance with finding
suitable field sites.
References
Boller, E.F., Vogt, H., Ternes, P. & Malavolta, C. (2005) Working document on selectivity of
pesticides. Internal newsletter issued by the International Organisation for Biological and
Integrated Control of Noxious Animals and Plants. Available on-line at: http://www.iobc-
wprs.org/ip_ipm/03022_IOBC_PesticideDatabase_2005.pdf
Knutson, A. (1998) The Trichogramma manual, A guide to the use of Trichogramma for
biological control with special reference to augmentative releases for control of bollworm and
budworm in cotton. B-6071 Agricultural Communications, Texas Agricultural Extension
Service, The Texas A&M University System, 42 pp.
Lang, A. (2003) Intraguild interference and biocontrol effects of generalist predators in a
winter wheat field. Oecologia 134, 144-153
Sanders, D. & Platner, C. (2007) Intraguild interactions between spiders and ants and top-
down control in a grassland food web. Oecologia 150 (4), 611-624
98
4.3 COULD A SUMMER CROP BE USED AS A NATURAL
ENEMY SOURCE FOR NEWLY PLANTED BRASSICAS?
L. Senior (Agri-Science QLD, DEEDI) and M. Healey (Agri-Science QLD, DEEDI)
Introduction
The short-term nature and constant rotation of horticultural crops, such as brassicas, makes it
difficult for natural enemies to become established; beneficial arthropods must colonise the
crop from local habitats such as field edges, adjacent bushland or riparian borders (Wissinger,
1997). Sampling of early season brassica crops (sections 4.1 and 4.2) found that it took
several weeks for populations of natural enemies to develop in newly transplanted seedlings.
Although small numbers of some predators (e.g. spiders) were present immediately following
planting, many predatory insects were absent for at least two weeks. It would be
advantageous to enhance natural enemy numbers while the crop is at this vulnerable stage.
Numerous studies have examined the manipulation of agricultural land to increase landscape
diversity and thereby increase the abundance and diversity of predators and parasitoids
(reviewed in Bianchi et al., 2006). Growers may be reluctant to sacrifice land for use as
refuges for beneficials if there is no profit return. As a result, the use of cash crops such as
lucerne (Mensah, 2002) and sorghum (Prasifka et al., 1999) as refuges has been explored in
broadacre agriculture. However, this technique has not often been used in horticultural
cropping systems. In south-east Queensland, sorghum and lucerne are commonly grown
during the summer period. Retention of a portion of a summer grown cash crop could
provide a refuge for natural enemies prior to the planting of the winter brassica crop.
A small-scale, unreplicated preliminary trial was carried out with the aim of exploring
whether established summer crops (sorghum and lucerne) could be used as refuges for natural
enemies, thereby increasing beneficial numbers in an adjacent brassica planting.
Methods
Trial design
Trials were carried out at Gatton Research station (Gatton, south-east Queensland) from late
March to mid June 2010. The trial was sited on three blocks. In two blocks, broccoli
seedlings (var. Aurora) were transplanted next to an established summer crop: sorghum
(planted November 2009 for a midge-resistant breeding trial) or lucerne (planted June 2007 as
a cover/commercial crop). In the third block, broccoli was transplanted into an area of bare
earth (control). This trial was performed as a supplement to the main project objective. As
such minimal resources were available, hence the trial was not replicated, each treatment
consisting of a single block.
Seedling transplantation occurred on 29th March 2010. Each broccoli planting measured 12 m
x 12 m and was situated approximately 4 m from the sorghum or lucerne refuge. An area of
bare, weed-free earth (10 m minimum) was maintained around the other three sides of the
broccoli. The control broccoli planting was surrounded on all sides by bare earth extending a
minimum of 10 m, the closest area of vegetation being a grass laneway. Broccoli plantings
were in double rows, with 1.5 m between bed centres and 0.33 m between plants (industry
standard spacings).
99
Crop management
Broccoli crops were overhead irrigated as necessary where in-crop rainfall was not sufficient.
Weather data for the trial period are presented in appendix 2.3. Insecticides were not used in
either refuge planting; however, the sorghum received an application of herbicide (fluroxypyr
and glyphosate plus the adjuvant Hasten) on 28th April. It should be noted that canola oil (on
which Hasten is based) has been found to have moderately harmful to harmful side effects
against the parasitoids Aphidius rhopalosiphi and Trichogramma cacoeciae (Boller et al.,
2005). Cutting of the lucerne occurred approximately two weeks prior to the transplantation
of the broccoli seedlings (17th March) and again on 15
th April and 9
th June.
Sampling methods
Three sampling methods were used: visual inspections of plants in situ, pitfall traps and
yellow sticky traps.
Visual inspections of plants were conducted weekly. At each assessment, 10 (1st and 2
nd
assessments) or 20 (subsequent assessments) broccoli plants were inspected per block.
Pitfall traps were placed in the trial blocks for four days prior to seedling transplantation
(three traps in the refuge crop, three in the area to be transplanted) in order to sample the
background population of ground-dwelling predators. These traps were sampled on two
occasions (26th and 29
th March), then removed.
Six sticky traps and ten pitfall traps were installed in each block the day following seedling
transplantation and sampled twice-weekly throughout the trial period. Sticky traps and pitfall
traps were placed in pairs facing towards and away from the refuge planting (Figs. 1 and 2).
The aim was to compare trap catches from each direction and hence obtain an indication of
the direction of arthropod movement between the refuge and the broccoli crop. Sticky traps
were made directional by exposing one sticky surface. The pitfall traps were made directional
by the placement of a clear plastic „V‟ shaped barrier to one side of the trap, facing towards or
away from the refuge planting, using the method described in Hossain et al. (2002).
Pairs of sticky traps were placed just within the refuge crop, in the centre of the broccoli
planting, and in the bare earth on the far side of the broccoli. Pairs of pitfall traps were placed
in the refuge crop, in the gap between the refuge and the broccoli, in the broccoli (two pairs)
and in the earth on the far side of the broccoli. By placing traps in a transect line through the
refuge, the broccoli crop and beyond, the aim was to explore any change in population of
arthropods with increasing distance from the refuge planting.
100
Figure. 1 Placement of traps in trial block
Figure. 2 Trial block
Broccoli
Pitfall trap facing
towards lucerne
refuge
Pitfall trap facing
away from lucerne
refuge
Wire fence
(protection
against hares)
Lucerne
refuge
101
Results
Results of visual assessments of plants are presented as the average number of pest or
beneficial arthropods per sampled plant (n = 20 for the majority of assessments) at each
sampling date.
Results of pitfall trap sampling, including the two pre-transplant assessments, are presented as
the average number of arthropods per trap at each assessment date. Catches from the refuge
(n = 2) and broccoli (n = 4) plantings were examined separately, with no distinction made
between traps facing towards or away from the refuge. Catches from traps placed in the bare
earth and the gap between the refuge and broccoli are not reported, as results did not indicate
any variation in trap catch according to distance from the refuge.
Likewise, results of sticky trap sampling are presented as the average number of insects per
trap at each assessment date, with catches from traps placed in the refuge (n = 2) examined
separately to those from the broccoli (n = 2) and no distinction made according to trap
direction. Catches from traps placed in the bare earth are not reported as results did not
indicate any effect of distance from refuge on trap catch.
Where examination of average catch from pairs of traps indicated a possible effect of refuge,
data from the two traps in each pair (towards and away) were examined separately. In all
cases there were no consistent differences between catch from traps facing towards or away
from the refuge planting.
Pest species
Foliage-dwellers
Lepidopteran pests were sampled through visual inspection of plants. Cabbage cluster
caterpillar (Crocidolomia pavonana) (Fig. 3) and cluster caterpillar (Spodoptera litura) (Fig.
4) were the two most abundant lepidopteran pests. Numbers of both species were generally
slightly lower in the lucerne-adjacent broccoli than the control. However, numbers of cluster
caterpillars were higher in the sorghum-adjacent broccoli than control.
0
2
4
6
8
10
12
6/4/10 13/4/10 20/4/10 27/4/10 4/5/10 11/5/10 18/5/10 25/5/10 1/6/10 8/6/10 15/6/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
Sorghum
Lucerne
Control
Figure. 3 Number of cabbage cluster caterpillar larvae in broccoli (mean per plant, n = 20)
102
0
1
2
3
4
5
6
7
8
9
6/4/10 13/4/10 20/4/10 27/4/10 4/5/10 11/5/10 18/5/10 25/5/10 1/6/10 8/6/10 15/6/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
Sorghum
Lucerne
Control
Figure. 4 Number of cluster caterpillar in broccoli (mean per plant, n = 20)
Sucking pests were sampled using a combination of visual inspections of plants and yellow
sticky traps. Aphids (Myzus persicae) were the dominant sucking pest. Visual inspections of
broccoli plants found aphid populations to be highest in the sorghum block and lowest in the
control (Fig. 5). Sticky traps placed in the broccoli also found an initial peak in the sorghum-
and lucerne-adjacent crop, after which numbers declined to control levels (Fig. 6). However,
catches from traps placed in the refuges were much lower in the sorghum or lucerne plantings
than in the control. This suggests that the sorghum and lucerne refuges may not have been the
source of the increased aphids in the adjacent broccoli.
0
10
20
30
40
50
60
70
6/4/10 13/4/10 20/4/10 27/4/10 4/5/10 11/5/10 18/5/10 25/5/10 1/6/10 8/6/10 15/6/10
Date
Nu
mb
er
of
ap
hid
s p
er
pla
nt
Sorghum
Lucerne
Control
Figure. 5 Number of aphids in broccoli (mean per plant, n = 20)
103
0
50
100
150
200
250
300
6/04
/10
13/0
4/10
20/0
4/10
27/0
4/10
4/05
/10
11/0
5/10
18/0
5/10
25/0
5/10
1/06
/10
8/06
/10
Date traps collected
Nu
mb
er
of
ap
hid
s p
er
trap
Sorghum
Lucerne
Control
Figure. 6 Number of aphids on traps placed in broccoli (mean per trap, n = 2)
Visual inspections of plants found very low numbers of whitefly, thrips and leafhoppers.
Examination of sticky traps placed in the broccoli found no clear or consistent differences
between numbers of whitefly or thrips in the three blocks. Sticky trap catches of leafhoppers
were higher from traps placed in broccoli adjacent to lucerne compared with the control, and
more leafhoppers trapped in the lucerne refuge compared with the control, suggesting that the
leafhoppers were originating from the lucerne.
Ground-dwellers
Ground-dwelling pests were sampled with pitfall traps. Only black earwigs (Nala lividipes)
were trapped in numbers sufficient to allow comparison between blocks. Numbers of black
earwigs were higher in the broccoli crop adjacent to the lucerne compared with the control
over the first circa three weeks post seedling transplantation (Fig. 7). However, catch from
traps placed in the lucerne refuge was comparable to the control.
104
0
1
2
3
4
5
6
7
8
26/3/10 9/4/10 23/4/10 7/5/10 21/5/10 4/6/10
Date traps collected
Nu
mb
er
of
earw
igs p
er
trap
Sorghum
Lucerne
Control
Figure. 7 Number of black earwigs in pitfall traps placed in broccoli (mean per trap, n = 4).
The first two assessments (26th and 29
th March) represent trap catch prior to seedling
transplantation (n = 3)
Beneficial species
Foliage-dwellers
Foliage-dwelling spiders were sampled through visual inspection of plants. Broccoli adjacent
to sorghum developed a larger spider population than broccoli in the control block (Fig. 8).
These spiders mostly comprised theridiids (64%), with clubionids/miturgids forming the
second largest group of identified spiders (7%).
0
0.5
1
1.5
2
2.5
3
6/4/10 13/4/10 20/4/10 27/4/10 4/5/10 11/5/10 18/5/10 25/5/10 1/6/10 8/6/10 15/6/10
Date
Nu
mb
er
of
sp
iders
per
pla
nt
Sorghum
Lucerne
Control
Figure. 8 Number of foliage-dwelling spiders in broccoli (mean per plant, n = 20)
Foliage-dwelling predatory insects logged through visual inspection of plants included
ladybirds, brown lacewings and hoverflies (Figs. 9 to 11, aphid data included for
105
comparison). More hoverflies and lacewings were logged from broccoli adjacent to sorghum
or lucerne compared with the control block, although numbers were very low in all blocks.
There was no apparent effect of refuge on ladybirds.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
6/4/
10
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/10
20/4
/10
27/4
/10
6/5/
10
12/5
/10
17/5
/10
24/5
/10
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10
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10
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/10
Date
Nu
mb
er
of
pre
dato
rs p
er
pla
nt
0
10
20
30
40
50
60
70
Nu
mb
er
of
ap
hid
s p
er
pla
nt
Hoverflies
Lacewings
Ladybirds
Aphids
Figure. 9 Number of predatory insects in broccoli adjacent to a sorghum refuge (mean per
plant, n = 20)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
6/4/
10
13/4
/10
20/4
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27/4
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12/5
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17/5
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10
8/6/
10
15/6
/10
Date
Nu
mb
er
of
pre
dato
rs p
er
pla
nt
0
10
20
30
40
50
60
70
Nu
mb
er
of
ap
hid
s p
er
pla
nt
Hoverflies
Lacewings
Ladybirds
Aphids
Figure. 10 Number of predatory insects in broccoli adjacent to a lucerne refuge (mean per
plant, n = 20)
106
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
6/4/
10
13/4
/10
20/4
/10
27/4
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6/5/
10
12/5
/10
17/5
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24/5
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1/6/
10
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10
15/6
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Date
Nu
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er
of
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dato
rs p
er
pla
nt
0
10
20
30
40
50
60
70
Nu
mb
er
of
ap
hid
s p
er
pla
nt
Hoverflies
Lacewings
Ladybirds
Aphids
Figure. 11 Number of predatory insects in broccoli with no adjacent refuge (control) (mean
per plant, n = 20)
Ground-dwellers
Ground-dwelling predators were sampled using pitfall traps. The most numerous were wolf
spiders (Lycosidae), common brown earwigs (Labidura truncata) and rove beetles
(Staphylinidae). Too few ground beetles were trapped to allow comparison between blocks.
Trap catch of lycosid spiders from broccoli was initially highest in the control block. From
the mid-point of the trial onwards control catch was zero, whereas pitfalls in the lucerne-
adjacent broccoli continued to trap small numbers of spiders (Fig. 12). However, there was
no difference in refuge trap catches between blocks.
0
0.5
1
1.5
2
2.5
26/3/10 9/4/10 23/4/10 7/5/10 21/5/10 4/6/10
Date traps collected
Nu
mb
er
of
sp
iders
per
trap
Sorghum
Lucerne
Control
Figure. 12 Number of lycosid spiders in pitfall traps placed in broccoli (mean per trap, n = 4).
The first two assessments (26th and 29
th March) represent trap catch prior to seedling
transplantation (n = 3)
107
Catches of common brown (native) earwigs were consistently higher in pitfall traps placed in
broccoli adjacent to lucerne compared with the control (Fig. 13). However, trap catch from
the refuge crops was no higher in lucerne than the control.
0
1
2
3
4
5
6
26/3/10 9/4/10 23/4/10 7/5/10 21/5/10 4/6/10
Date traps collected
Nu
mb
er
of
nati
ve e
arw
igs p
er
trap
Sorghum
Lucerne
Control
Figure. 13 Number of native earwigs in pitfall traps placed in broccoli (mean per trap, n = 4).
The first two assessments (26th and 29
th March) represent trap catch prior to seedling
transplantation (n = 3)
Catches of rove beetles were generally higher in pitfall traps placed in sorghum-adjacent
broccoli compared with control broccoli (Fig. 14). Trap catch from pitfalls placed in the
refuge crops was extremely low; however, no rove beetles were recovered from the control
(bare) refuge area until the penultimate assessment, compared with an occasional individual
trapped in the sorghum and lucerne refuges (Fig. 15).
0
0.5
1
1.5
2
2.5
3
3.5
4
26/3/10 9/4/10 23/4/10 7/5/10 21/5/10 4/6/10
Date traps collected
Nu
mb
er
of
rove b
eetl
es p
er
trap
Sorghum
Lucerne
Control
Figure. 14 Number of rove beetles in pitfall traps placed in broccoli (mean per trap, n = 4).
The first two assessments (26th and 29
th March) represent trap catch prior to seedling
transplantation (n = 3)
108
0
0.5
1
1.5
26/3/10 9/4/10 23/4/10 7/5/10 21/5/10 4/6/10
Date traps collected
Nu
mb
er
of
rove b
eetl
es p
er
trap
Sorghum
Lucerne
Control
Figure. 15 Number of rove beetles in pitfall traps placed in refuge crop (mean per trap, n =
2). The first two assessments (26th and 29
th March) represent trap catch prior to seedling
transplantation (n = 3)
Parasitoids
A range of parasitoid wasp species were trapped (table 1). Only potential parasitoids of
brassica crop pests were identified; other wasps were recorded as unidentified.
Table 1. Cumulative trap catch of parasitoids over the trial period (cumulative mean per trap,
n = 2)
Parasitoid Parasitises
Traps placed in broccoli Traps placed in refuge
Sorghum
block
Lucerne
block
Control
block
Sorghum
block
Lucerne
block
Control
block
Trichogramma Moth eggs 100 41.5 52 16.5 33 22.5
Telenomus Moth eggs 13.5 7.5 8 18 16 5.5
Microplitis Moth larvae 6.5 4.5 3 28.5 5 2
Heteropelma Moth larvae 2 0 2.5 2.5 0 1.5
Diadegma Moth larvae 17.5 15 12 35.5 17 7.5
Diadromus Moth pupae 4.5 4 1.5 9 6 1.5
Cotesia Moth larvae 7 6 2 3.5 6 2.5
Litomastix Moth larvae 6.5 3 1.5 390 6 1
Eretmocerus Whitefly 3 6 5 3 0.5 0.5
Aphidius Aphids 31 32 21 6 15 1.5
Trissolcus GVB eggs 4.5 0.5 0.5 5.5 2.5 0.5
Unidentified myrmarid 20 24 9 25 41 5
Other unidentified parasitoids 27 26 19.5 34.5 29.5 21
Examining the refuge trap data, large differences between cumulative trap catch from the
three blocks were observed for some parasitoid species: Litomastix sp., Diadegma sp. and
Microplitis sp. catches were all substantially higher in the sorghum than control. However,
there was no corresponding increase in trap catch from the adjacent broccoli. Although some
species of these wasp genera are known parasitoids of brassica pests, trapped specimens were
109
not identified beyond genus. It is therefore possible that they were not associated with
brassica pests and hence were not trapped in the broccoli crop.
The most numerous parasitoids caught on traps placed in the broccoli were Trichogramma sp.
(a parasitoid of moth eggs) and Aphidius sp. (an aphid parasitoid); hence data for each of
these species are considered individually. Broccoli trap catch of other parasitoid species was
low, and in most cases cumulative catches from broccoli in each of the three blocks were
similar.
Examination of trap catch of Trichogramma wasps over time reveals that the higher
cumulative catch from traps placed in the sorghum was due to a single assessment, with no
consistent differences between the three blocks over time (Fig. 16). There were no
differences in catch from traps placed in the refuge. Moth egg parasitism in all blocks was
too low to discern differences.
0
5
10
15
20
25
30
6/4/
10
13/4
/10
20/4
/10
27/4
/10
4/5/
10
11/5
/10
18/5
/10
25/5
/10
1/6/
10
8/6/
10
Date traps collected
Nu
mb
er
of T
rich
og
ram
ma p
er
trap
Sorghum
Lucerne
Control
Figure. 16 Number of Trichogramma on traps placed in broccoli (mean per trap, n = 2)
Trap catch of Aphidius wasps was higher in sorghum-adjacent broccoli compared with the
control on several occasions (Fig. 17). However, this did not result in any consistent
difference in percentage parasitism of aphids between the three blocks. Catches from refuge
traps were too low to discern any clear differences between blocks.
110
0
1
2
3
4
5
6
7
6/4/
10
13/4
/10
20/4
/10
27/4
/10
4/5/
10
11/5
/10
18/5
/10
25/5
/10
1/6/
10
8/6/
10
Date traps collected
Nu
mb
er
of A
ph
idiu
s p
er
trap
Sorghum
Lucerne
Control
Figure. 17 Numbers of Aphidius on traps placed in broccoli (mean per trap, n = 2)
Discussion
Evidence for an effect of refuge on beneficial populations was mixed. Numbers of some
predators were higher in refuge-adjacent broccoli compared to the control: lycosid spiders
and native earwigs in the lucerne block; rove beetles and foliage-dwelling spiders in sorghum;
hoverflies and lacewings in both sorghum and lucerne. However, in most cases there was
little or no evidence to suggest that these predators originated from the refuge. Differences in
populations of hoverflies and lacewings between blocks may have been linked to differing
aphid populations rather than any direct effect of the refuge. Furthermore, pitfall trap catches
of all ground-dwelling predators were very low, making it difficult to make meaningful
distinctions between blocks.
The most convincing effect was found for foliar-dwelling spiders: although numbers were
low, differences between the sorghum and control blocks over the latter part of the trial were
clear and warrant further investigation. The foliar-dwelling spiders in broccoli adjacent to
sorghum mostly comprised theridiids (64%), with clubionids/miturgids forming the second
largest group (7%). Laboratory feeding experiments (section 4.4) found that both of these
types of spiders were able to prey upon key brassica pests, suggesting that they are capable of
making a contribution to pest suppression in brassicas.
Effects of the refuges on parasitoid species were also inconclusive. Trap catches of
Trichogramma (moth egg parasitoid) and Aphidius (aphid parasitoid) were increased in
sorghum-adjacent broccoli compared with the control, but there was no evidence that
sorghum was the source, and no increase in parasitism of moth eggs or aphids. Numbers of
some caterpillar parasitoids (Litomastix, Diadegma and Microplitis) were higher in the
sorghum refuge than the control, but there was no corresponding increase in the adjacent
broccoli crop. It is therefore likely that the trapped species were not specific to any of the
more numerous pest Lepidoptera present in the broccoli during the trial: populations of
Lepidoptera other than cabbage cluster caterpillar and cluster caterpillar were low. Parasitism
of moth larvae in all blocks was too low to determine any effect of refuge.
111
There was little evidence of suppression of pests in refuge-adjacent broccoli. Numbers of
cabbage cluster caterpillar and cluster caterpillar were slightly lower in broccoli adjacent to
lucerne compared with the control, but there was no evidence that differences were due to
increased natural enemy activity.
Numbers of cluster caterpillar, aphids and black earwigs were increased in refuge-adjacent
broccoli compared to the control. However, there was no indication that the refuge crop was
the source of these pests. Increases may have been due to an indirect effect of the refuge (e.g.
sorghum could have resulted in a more sheltered environment in the broccoli by acting as a
windbreak), or may have been unrelated to the presence of a refuge (e.g. differing nutrient
levels in the three blocks). A large leafhopper population in the lucerne refuge appeared to
result in higher initial numbers in the adjacent broccoli crop; however this insect is not a
significant pest of brassicas.
In conclusion, although there were some indications of a beneficial effect of sorghum and
lucerne plantings on populations of some natural enemies, evidence was far from conclusive.
Unfortunately, a planned attempt to use fluorescent dye to investigate movement of
beneficials failed, as dye was not detected in any arthropods recovered from the trial. Further,
examination of sticky trap and pitfall trap catches found no effect of trap direction (facing
towards or away from refuge) on trap catch, and no effect of increasing distance from the
refuge on numbers of trapped arthropods. It is possible that any differences were not detected
due to the mobility of the arthropods and the small-scale nature of the trial.
As a supplement to the main focus of the project, this trial was designed as a preliminary
exploration of the use of sorghum and lucerne refuges to enhance natural enemy populations.
Consequently, although it has provided an indication of the effect of refuge plantings, it was
not intended to provide definitive evidence; a large-scale, replicated trial is required before
any firm conclusions can be drawn. Future studies should be designed to assess movement of
arthropods between the refuge and the brassica crop. Replication and use of large-scale trial
blocks would help to mitigate the influence of external factors (e.g. nearby vegetation,
landscape variability) and mobility of arthropods.
Conclusions
The presence of a refuge planting was associated with increased numbers of some natural
enemies. This was most evident in the case of foliage-dwelling spiders and rove beetles.
Some other predators (wolf spiders, native earwigs, lacewings, hoverflies) and parasitoids
(Trichogramma, Aphidius) were higher in broccoli adjacent to a refuge, but there was no
evidence that the refuge was the source.
Some pests (cabbage cluster caterpillar, cluster caterpillar) were reduced in broccoli
adjacent to one or more refuge plantings; however there was no evidence to link pest
suppression to increased natural enemy activity.
Some pests (cluster caterpillar, aphids, black earwigs) were higher in one or more refuge-
adjacent plantings compared with the control, but there was no evidence to suggest this
was a direct result of the refuge.
A large-scale, replicated trial is required to investigate these preliminary findings further.
Acknowledgements
We gratefully acknowledge Darren Williams, Robert Mitchell, Carolyn Church and Mary
Firrell for technical and field assistance, and the farm staff at Gatton Research Station.
112
References
Bianchi, F.J.J.A., Booij, C.J.H. & Tscharntke, T. (2006) Sustainable pest regulation in
agricultural landscapes: a review on landscape composition, biodiversity and natural pest
control. Proceedings of the Royal Society B 273, 1715 - 1727
Boller, E.F., Vogt, H., Ternes, P. & Malavolta, C. (2005) Working document on selectivity of
pesticides. Internal newsletter issued by the International Organisation for Biological and
Integrated Control of Noxious Animals and Plants. Available on-line at: http://www.iobc-
wprs.org/ip_ipm/03022_IOBC_PesticideDatabase_2005.pdf
Hossain, Z., Gurr, G., Wratten, S. & Raman, A. (2002) Habitat manipulation in lucerne
Medicago sativa: arthropod population dynamics in harvested and „refuge‟ crop strips.
Journal of Applied Ecology 39, 445 - 454
Mensah, R.K. (2002) Development of an integrated pest management programme for cotton.
Part 1: establishing and utilizing natural enemies. International Journal of Pest Management
48 (2), 87-94
Prasifka, J.R., Krauter, P.C., Heinz, K.M., Sansone, C.G. & Minzenmayer, R.R. (1999)
Predator conservation in cotton: using grain sorghum as a source for insect predators.
Biological Control 16, 223-229
Wissinger, S.A. (1997) Cyclic colonization in predictably ephemeral habitats: a template for
biological control in annual crop systems. Biological Control 10, 4-15
113
4.4 EVALUATION OF THE PREDATORY BEHAVIOUR OF
SOME SPIDERS COMMONLY FOUND IN EARLY SEASON
BRASSICA CROPS
L. Senior (Agri-Science QLD, DEEDI) and M. Healey* (Agri-Science QLD,
DEEDI)
* During the project an opportunity arose for additional experiments to be carried out by M.
Healey as part of her BSc Honours research project, thus extending the quantity of work that
could be performed for this part of the project objective. These experiments form part of the
work described in this chapter.
Introduction
Sampling of brassica plantings (sections 4.1 and 4.2) found that spiders were a key predator in
early season crops, particularly in the first few weeks post-transplantation. Spiders were
dominated by three groups: tangle-web (Theridiidae) and sac/night-stalking
(Clubionidae/Miturgidae) spiders on the foliage; wolf spiders (Lycosidae) on the ground.
There is a growing body of evidence that spiders play an important role in limiting pest
outbreaks in a wide variety of agroecosystems (Carroll, 2009; Marc et al., 1999; Maloney et
al, 2003; Riechert 1999; Riechert & Bishop, 1990). However, specific information on their
predatory potential is limited. Moreover, due to difficulties with spider taxonomy (Pearce et
al., 2004) and accurately identifying spiders in the field (Marc et al., 1999), they are often
treated as a single group; little attention is given to the impact of specific species or even
families, which can vary considerably between cropping types. Some exceptions are Nyffeler
et al. (1994a) and Nyffeler (1999), who reviewed studies examining prey selection and diet
composition in several spider families, including the Theridiidae and Lycosidae. Carroll
(2009) described the role of spiders in vineyards; this author considered that several spiders,
including Cheiracanthium inclusum (Miturgidae) and Theridion spp. (Theridiidae) have a
particularly high IPM value.
Laboratory experiments were undertaken with the aim of exploring the predatory potential of
each of the three spider groups most commonly found in early season brassica crops.
Experiments were performed to examine selection of prey species, rate of predation and (for
the theridiids only) effect of prey size and spider size on predation.
Methods
Spiders
Spiders from three families/groups were assessed: Theridiidae, Lycosidae and
Clubionidae/Miturgidae. Clubionid and miturgid spiders were both formerly in the „catch-all‟
family Clubionidae. As these two families were not distinguished during field sampling
experiments, they were treated as one group for the purpose of these experiments. Spiders
were not identified beyond family, nor were they sexed, however where possible spiders of
similar appearance and size were selected for use in experiments.
Spiders were collected from unsprayed brassica plantings at Gatton Research Station (Gatton,
south-east Queensland) in the weeks prior to use in each experiment. They were held at ca.
10 °C and provided with a water source (damp dental wick). Where duration of storage was
in excess of 14 days they were also provided with food (Drosophila melanogaster), however
in all cases spiders were starved for a minimum of four days prior to use in experiments. Four
114
days was determined as an optimum starvation period through prior experimentation and
based on previous spider predation studies (Gavish-Regev et al., 2009; Li et al., 1997).
Prey
Prey items used in experiments were larvae of diamondback moth (DBM, Plutella xylostella),
larvae of cabbage cluster caterpillar (CCC, Crocidolomia pavonana) and green peach aphids
(aphids, Myzus persicae). Insects were obtained from cultures maintained at Gatton Research
Station (DBM and aphids) and the School of Life Sciences, University of Queensland (DBM
and CCC). Additional material was field collected where necessary.
Experimental method type 1 – Petri dish
A single spider was placed in a Petri dish (90 cm diameter) and provided with a choice of two
prey items. The prey were placed on a cabbage or broccoli leaf disc (3 – 5 cm diameter; size
and brassica type standardised in each test) and allowed to settle before being placed into the
Petri dish.
Experimental method type 2 – enclosed broccoli seedling
Potted broccoli seedlings (ca. 15 cm high, 5 leaf stage) were enclosed within small cages
consisting of a clear plastic cylinder (105 mm diameter, 250 mm high) with mesh-covered
ventilation holes in the side and top. The prey items were placed on the seedling and allowed
to settle (minimum 30 minutes), after which time the plants were checked to ensure all prey
were still present. A single spider was placed in each arena. Theridiids and
clubionids/miturgids were placed onto one of the leaves of the plant; lycosids were placed on
the soil surface at the base of the plant. Control replicates (no spider present) were included
to account for natural mortality of the prey species.
1. Selection of prey species (Petri dish method)
Experiments were performed with theridiids, clubionids/miturgids and lycosids, each
provided with a choice of one larval DBM and one larval CCC. Moth larvae of equal size
were selected for experiments. The spiders were observed at intervals and the first prey item
attacked was recorded. Where a prey selection was not made within the experimental period,
or where both prey items were consumed and the first selection not observed, the replicate
was recorded as void. Replication varied according to availability of spiders: 40 lycosids, 62
theridiids and 32 clubionids/miturgids were assessed.
2. Selection of prey species (enclosed seedling method) part 1
Experiments were performed with theridiids, clubionids/miturgids and lycosids, each
provided with one larval DBM and one larval CCC. Moth larvae of equal size were selected
for experiments. Ten replicates were performed with theridiids and clubionids/miturgids, 30
replicates were performed with lycosids and 30 replicates were set up with prey items but no
spider (controls). Observations were made at intervals and the first prey item attacked was
recorded. Where no prey selection was made or the first choice not observed, the replicate
was recorded as void.
3. Selection of prey species (enclosed seedling method) part 2
Experiments were performed with theridiids, clubionids/miturgids and lycosids, each
provided with one larval CCC and one adult aphid. Ten replicates were performed for each
spider type and control (no spider). Observations were made as for the previous test.
4. Predation rates on two prey species (enclosed seedling method)
Experiments were performed with theridiids, clubionids/miturgids and lycosids, each
provided with five DBM or five CCC. Moth larvae of equal size were selected for
experiments. Ten replicates were performed for each spider type provided with each prey
species. An additional ten control replicates were performed for each prey species with no
115
spider present. Observations were made daily up to four days post set-up. At each
assessment the numbers of live, dead and missing larvae per plant were recorded.
5. Predation rates of clubionid/miturgid spiders (enclosed seedling method)
A single clubionid/miturgid spider was provided with five late instar DBM larvae.
Observations were made daily up to four days post set-up. At each assessment the numbers
of live, dead and missing larvae per plant were recorded. Any missing or pupating larvae
were replaced, such that each spider was provided with five prey items every day. Ten
replicates were performed with a spider present, and five replicates with no spider present
(control).
6. Selection of prey size by theridiids (Petri dish method)
Theridiid spiders were grouped according to size (abdomen width): small (1 – 2 mm) and
large (2 – 3.5 mm). Each spider was provided with two DBM larvae: one small (2 – 3 mm in
length) and one large (4 – 5 mm in length). A total of 155 theridiid spiders were assessed,
comprising 77 small and 78 large spiders. Observations were made at intervals, the first prey
item attacked was recorded, and any failures to choose or unobserved choices recorded as
void.
7. Predation rates of large and small theridiid spiders (enclosed seedling method)
Theridiid spiders were grouped according to size as for the previous test. Each spider was
provided with five equally sized DBM larvae. Ten replicates were performed for each of the
large and small spiders and for the no spider controls. Observations were made daily up to
four days post set-up. At each assessment the numbers of live, dead and missing larvae per
plant were recorded.
Statistical analysis Any missing prey items were assumed to have been eaten by the spiders. Where controls
were included, data were corrected to take into account natural mortality not due to the
spiders. The Sun-Shepard formula (Püntener, 1981) was used in experiment 2, where there
was a non-uniform population:
100*%100
%%%
controlinChange
controlinChangetreatmentspiderinMortalitymortalityCorrected
An adaptation of Abbott‟s formula (Gavish-Regev et al., 2009) was applied in experiments 4,
5 and 7, where there was a uniform population:
preyofnumberoriginalcontrolinpreysurvivingNumber
treatmentspiderinpreysurivingNumbersurvivalpreyCorrected *
Corrected prey survival was then used to calculate corrected prey consumption by the spiders.
Data resulting from experiments 1, 2, 3 and 6 were subjected to chi-square analysis.
Data resulting from the 24 hour assessment of experiment 4 were subjected to two-way
analysis of variance (ANOVA), followed by least significant difference (LSD) tests to
distinguish between the group means. Data were transformed (arcsine transformation of
proportion live larvae remaining) in order to meet the assumptions of the statistical test.
Data resulting from the 24 hour assessment of experiment 7 were subjected to one-way
ANOVA. Data were transformed (arcsine transformation of proportion live larvae remaining)
in order to meet the assumptions of the statistical test.
116
Results
1. Selection of prey species (Petri dish method)
There was a significant association between spider type and prey selection (χ2 = 12.17, P <
0.005). Lycosid spiders selected DBM more frequently than CCC larvae; theridiids selected
CCC more frequently than DBM; clubionids/miturgids exhibited no clear prey preference
(table 1). The number of void replicates due to non-observation of first choice was high for
the clubionid/miturgid spiders as many of these nocturnal spiders consumed both prey items
during the night.
Table 1. Prey selection using the Petri dish method
Spider No.
reps
Prey selection Void
DBM CCC No choice Not observed
Lycosidae 40 29 (72.5%) 7 (17.5%) 3 (7.5%) 1 (2.5%)
Theridiidae 62 20 (32%) 27 (44%) 6 (10%) 9 (14%)
Clubionidae/Miturgidae 32 10 (31%) 7 (22%) 2 (6%) 13 (41%)
2. Selection of prey species (enclosed seedling method) part 1
There was a significant association between spider type and prey selection (χ2 = 11.41, P =
0.01) (table 2); however, as many expected values were less than 5, this result should be
interpreted with caution. Lycosid spiders selected CCC more frequently than DBM larvae.
Choices of theridiids (which selected more CCC) and clubionids/miturgids (which selected
more DBM) were based on very few replicates.
Table 2. Prey selection using the enclosed seedling method (control corrected percentage data
in brackets)
Spider No.
reps
Prey selection Void
DBM CCC No choice Not observed
Lycosidae 30 8 (19%) 18 (59%) 2 2
Theridiidae 10 1 (0%) 5 (48%) 4 0
Clubionidae/Miturgidae 10 7 (67%) 1 (7%) 2 0
Control (no spider) 30 3 1 - -
3. Selection of prey species (enclosed seedling method) part 2
Chi-square analysis found no significant association between spider type and prey selection
(χ2 = 5.25, P > 0.05); however, as many expected values were less than 5, this result should be
interpreted with caution. Selection of aphid or CCC prey for each spider type is displayed in
table 3.
Table 3. Prey selection using the enclosed seedling method
Spider No.
reps
Prey selection Void
Aphid CCC No choice Not observed
Lycosidae 10 6 3 1 0
Theridiidae 10 2 7 1 0
Clubionidae/Miturgidae 10 5 3 1 1
Control (no spider) 10 1 0 - -
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4. Predation rates on two prey species (enclosed seedling method)
Several uneaten DBM larvae were observed to pupate prior to the end of the experiment (day
3 onwards). As the spiders did not prey on pupae, this effectively reduced the number of prey
items available, biasing results from the second half of the experiment. Therefore results
from the first (24 hour) assessment only were subjected to statistical analysis.
After 24 hours there was a significant effect of spider (lycosid, theridiid, clubionid/miturgid
or no spider control) on the number of surviving prey (F = 16.52, P < 0.001) (table 4): all
treatments containing a spider resulted in fewer surviving prey compared to the control
treatment, but there were no significant differences between the three spider families. There
was no effect of prey species (F = 0.04, P > 0.05) and no interaction between spider type and
prey type (F = 1.52, P > 0.05).
Table 4. Cumulative number of dead, moribund and missing (presumed eaten) larvae (means
± standard errors); control corrected data, where different from pre-corrected data, in square
brackets
Spider Prey Days after set-up
1 2 3 4
Lycosidae DBM 1.9 (± 0.43) 3.0 (± 0.45) 3.9 (± 0.38) 4.2 (± 0.36)
CCC 2.9 (± 0.50) 4.0 (±0.49) 4.6 (± 0.22) 4.8 (± 0.13)
Theridiidae
DBM 2.6 (± 0.60) 3.0 (± 0.63) 3.1 (± 0.60)
[3.0]
3.2 (± 0.63)
[3.1]
CCC 1.7 (± 0.47)
[1.6]
2.4 (± 0.50)
[2.3]
3.1 (± 0.43)
[2.9]
3.9 (± 0.43)
[3.8]
Clubionidae/Miturgidae
DBM 3.3 (± 0.60) 3.6 (± 0.52) 3.9 (± 0.46) 4.3 (± 0.33)
CCC 2.6 (± 0.69) 2.9 (± 0.67)
[2.8]
3.2 (± 0.59)
[3.0]
3.5 (± 0.60)
[3.3]
Control (no spider) DBM 0 (± 0) 0.1 (± 0.10) 0.2 (± 0.13) 0.2 (± 0.13)
CCC 0.1 (± 0.1) 0.2 (± 0.13) 0.4 (± 0.22) 0.6 (± 0.31)
5. Predation rates of clubionid/miturgid spiders (enclosed seedling method)
Prey consumption (non-cumulative) of clubionid/miturgid spiders over four consecutive 24
hour periods is displayed in table 5. Many DBM larvae had begun to pupate by the fourth day
of the trial, reducing the available prey and thus making data from the fourth day unreliable.
The average prey consumption was therefore between 1.1 (control corrected) and 1.9 late
instar DBM larvae.
Table 5. Number of dead, moribund and missing (presumed eaten) larvae (means ± standard
errors); control corrected data, where different from pre-corrected data, in square brackets
Treatment Days after set-up
1 2 3 4
Spider 1.2 (± 0.36) 1.9 (± 0.41) 1.4 (± 0.43)
[1.1]
0.9 (± 0.28)
[0.7]
Control (no spider) 0 (± 0) 0 (± 0) 0.4 (± 0.24) 0.2 (± 0.20)
6. Selection of prey size by theridiids (Petri dish method)
There was no significant association between spider size and prey size (χ2 = 0.52, P > 0.05).
Although not a significant effect, large spiders selected slightly more small prey than large,
whereas small spiders selected equal numbers of small and large prey (table 6). Spiders as
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small as 1 mm (abdomen width) were able to successfully attack DBM larvae up to 5 mm in
length, i.e. approximately five times their own body size. A large proportion of theridiids
failed to make a choice within the experimental period. This figure was higher for the large
than the small spiders.
Table 6. Prey size selection by theridiids using the Petri dish method
Spider size No.
reps
Prey selection Void
Large prey Small prey No choice Not observed
Large spiders 78 16 (21%) 22 (28%) 32 (41%) 8 (10%)
Small spiders 77 23 (30%) 23 (30%) 26 (34%) 5 (6%)
Total 155 39 (25%) 45 (29%) 58 (37%) 13 (8%)
7. Predation rates of large and small theridiid spiders (enclosed seedling method)
Several uneaten DBM larvae were observed to pupate prior to the end of the experiment,
reducing the number of prey items available to the spiders over the latter part of the trial;
therefore only the 24 hour data were subjected to statistical analysis. Large theridiid spiders
consumed slightly more DBM larvae than small spiders over the initial 24 hour period (table
7); however this difference was not statistically significant (F = 1.47, P > 0.05).
Table 7. Cumulative number of dead, moribund and missing (presumed eaten) larvae (means
± standard errors); control corrected data, where different from pre-corrected data, in square
brackets
Spider size Time after set-up
3.5 hours 1 day 2 day 3 day 4 day
Small 1.1 (± 0.35) 1.7 (± 0.47) 1.8 (± 0.42)
[1.7]
2.1 (± 0.55)
[2.0]
2.6 (± 0.60)
[2.4]
Large 1.4 (± 0.27) 2.4 (± 0.56) 2.6 (± 0.52)
[2.5]
2.8 (± 0.49)
[2.7]
3.0 (± 0.42)
[2.9]
Control (no spider) 0 (± 0) 0 (± 0) 0.2 (± 0) 0.2 (± 0) 0.3 (± 0)
Discussion
Prey selection
Experiments were conducted to determine whether the three spider groups exhibited any
preference when presented with different brassica pests. Responses were found to differ
according to spider type and experimental method.
In Petri dish experiments, lycosid spiders exhibited a clear preference for DBM over CCC.
However, results were reversed when tested in a more complex arena (an enclosed seedling).
In a no-choice test slightly more CCC were consumed, although this was not a statistically
significant difference. Lycosid spiders therefore appear more likely to prey upon CCC than
DBM when tested using the enclosed seedling method. The differences between spider prey
preferences in the two test environments may have been due to the differing behaviours of the
two prey species; the DBM tended to be more active than the CCC when confined in a Petri
dish, which may have made them more of a target to the hunting lycosids. This difference in
prey behaviour was not apparent in the more complex arena.
In an unpublished trial, gut analysis of field-collected lycosids found that more of these
spiders tested positive for CCC than DBM (M. Furlong, pers. comm.), correlating with the
findings of the current study. It was hypothesised that this may be due to differences in the
119
life history of the two pests: pre-pupae of CCC spend time foraging on the soil surface, where
they may be encountered by ground-dwelling lycosids, whereas all life stages of DBM are
foliar-dwelling. In the current study, however, it was observed that lycosid spiders frequently
moved up onto the seedlings during the experiments (photograph displayed in appendix 2.4).
This indicates that these spiders are not restricted to feeding on pests located on the soil
surface, but will actively hunt for prey on the foliage.
Results were less clear-cut for the two foliar-dwelling spider groups (theridiids and
clubionids/miturgids). These spiders tended to make a prey selection less quickly than the
lycosids, with the result that the number of observed prey choices was lower. Theridiids
selected more CCC than DBM in both the Petri dish and the enclosed seedling experiments,
whereas clubionids/miturgids selected slightly more DBM than CCC in both experiments.
However, differences in numbers of selected prey in the Petri dish experiment were marginal
and results of the enclosed seedling method were based on very low replication. Results
therefore suggest that while both spider types will readily prey upon DBM and CCC larvae
under laboratory conditions, further replication is required to confirm any prey preferences
indicated in these preliminary experiments.
The three spider groups were also presented with a choice between CCC and aphids.
Preliminary results based on a small number of selections found that lycosids and
clubionids/miturgids selected aphids slightly more often than CCC, whereas the reverse was
true of theridiids. Results suggest that all spiders were able to prey upon aphids as well as
CCC.
In conclusion, despite some differences in prey preference, all spiders tested were able to prey
upon DBM, CCC and aphids under laboratory conditions. Reviewing the literature,
clubionids and miturgids are significant predators of caterpillars in particular, as well as
leafhoppers, aphids and a variety of other pest species (Carroll, 2009; Maloney et al., 2003).
Theridiids and lycosids also have a wide prey range, but the diet of these spiders appears to
vary considerably depending on spider species and habitat. For example, Hosseini et al.
(2007) found that the percentage of lycosids testing positive for a variety of lepidopteran pests
varied markedly depending on spider species and collection location. It is likely, therefore,
that prey selection in the field is governed to a large extent by availability.
Predation rates
In a no-choice experiment, theridiids consumed the fewest prey items over the initial 24 hour
period (an average of 1.6 CCC / 2.6 DBM). Lycosids consumed slightly more (2.9 CCC / 1.9
DBM) and clubionids/miturgids were the most voracious (2.6 CCC / 3.3 DBM). An
experiment with differently sized theridiid spiders produced similar results: small and large
theridiids consumed an average of between 1.7 and 2.4 DBM larvae, respectively, over the
initial 24 hours. A further experiment performed with clubionids/miturgids found that these
spiders consumed an average of between 1.1 and 1.9 late instar DBM larvae a day.
Results cannot be extrapolated to the field situation without supporting studies: in the field
spiders are thought to feed well below their maximum capacity (Nyffeler et al., 1992).
However, findings give an indication of the relative predatory capabilities of the three spider
groups. The relative abundance of each type of spider should also be taken into account when
considering potential impact on pests. For instance, although clubionids/miturgids were the
most voracious in laboratory trials, typically no more than one spider was found on a plant in
the field, whereas often many of the less voracious theridiids were found on a single plant.
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Effect of prey size and spider size on predation in theridiid spiders
Laboratory and field experiments have found that spiders generally feed on prey that are
smaller than themselves (reviewed in Nyffeler et al., 1994b). As a consequence it could be
expected that small spiders such as theridiids may have a limited effect on many brassica
pests. Experiments were therefore conducted, firstly to determine whether theridiids
preferred small over larger prey, and secondly to examine the predatory capacity of large and
small theridiid spiders on DBM larvae.
In a Petri dish trial, small theridiids were equally as likely to select large or small DBM
larvae. Large theridiids were more likely to select small prey, although this difference was
not statistically significant (P > 0.05). Large theridiids were also less likely to make any prey
selection within the experimental period, compared with small spiders. It is possible that
spider size was a reflection of nutritional status or satiation as well as developmental stage. If
the smaller spiders were more nutritionally deprived than the larger spiders, they may have
been less selective when making a prey choice: Haynes and Sisojevic (1966) (pers. obs. in
Provencher & Riechert, 1991) noted that a deprived spider will attack any prey, whereas a
satiated spider is more likely to chose prey that is easily captured.
A second experiment measured the predation rates of large and small theridiids over 24 hours.
Large spiders were found to consume slightly more DBM larvae than smaller theridiids;
however, this difference was not statistically significant (P > 0.05).
It can be concluded that theridiids, the most numerous of the foliage-dwelling spiders, are
capable of attacking late-instar DBM larvae up to five times their body size. Moreover, the
predatory capacity of juveniles (which comprise a large proportion of the spider population)
was almost as great as the adults under laboratory conditions. Although not quantified, DBM
larvae were observed in the webs of theridiid spiders during sampling in brassica crops,
confirming that theridiids prey on these pests in the field as well as the laboratory. Results
therefore indicate that theridiids may make a significant contribution to suppression of
brassica pests such as DBM.
Conclusions
Three spider groups found most commonly during sampling of early season brassica
crops (theridiids, clubionids/miturgids, lycosids) were all able to prey upon key brassica
pests (diamondback moth, cabbage cluster caterpillar and green peach aphids) under
laboratory conditions.
Lycosid spiders exhibited a preference for CCC over DBM, whereas the prey preferences
of the two foliage-dwelling spiders (theridiids and clubionids/miturgids) were less clear
cut. It is likely that the diet of these spiders is highly variable and dependent on prey
availability.
Under laboratory conditions, the spiders were able to consume between 1.1 and 3.3
lepidopteran larvae a day, dependent on spider type, prey size and prey species.
Theridiids consumed the fewest prey items, and clubionids/miturgids the most. However,
the higher relative abundance of theridiids could mean that they have a large impact on
pests.
Theridiids (including juveniles) were found to prey on late instar DBM larvae up to five
times their own body size, and were equally as likely to select large or small prey.
It can be concluded that preliminary laboratory experiments suggest that the three most
commonly-found spider groups are capable of making a substantial contribution to pest
suppression in brassicas.
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Acknowledgements
We thank Dr Mike Furlong (project collaborator, University of Queensland) and Dr Graham
Brodie (Madaline Healey‟s BSc Honours research project supervisor, University of
Melbourne) for their guidance and helpful comments.
References
Carroll, D. (2009) Spiders in San Joaquin Valley vineyards. Pests, biters and IPM agents.
Available from Association of Applied IPM Ecologists web-site:
http://www.aaie.net/IPMinfo/SpidersVineyards.pdf
Gavish-Regev, E., Rotkopf, R. & Lubin, Y. (2009) Consumption of aphids by spiders and the
effect of additional prey: evidence from microcosm experiments. BioControl 54, 341 - 350
Hosseini, R., Schmidt, O. & Keller, M. (2007) A DNA-based approach to study predator-prey
trophic interactions within brassica crops. Final report of project VG04004 Horticulture
Australia Limited, National diamondback moth project: integrating biological, chemical and
area wide management of Brassica pests.
Li, D., Jackson, R.R. & Barrion, A. (1997) Prey preferences of Portia labiata, P. africana and
P. schultzi, araneophagic jumping spiders (Araneae: Salticidae) from the Philippines, Sri
Lanka, Kenya and Uganda. New Zealand Journal of Zoology 24, 333 - 349
Maloney, D., Drummond, F.A. & Alford, R. (2003) Spider predation in agroecosystems: can
spiders effectively control pest populations? Maine Agricultural and Forest Experimental
Station (The University of Maine) Technical Bulletin 190
Marc, P., Canard, A. & Ysnel, F. (1999) Spiders (Araneae) useful for pest limitation and
bioindication. Agriculture, Ecosystems and Environment 74, 229 - 273
Nyffeler, M. (1999) Prey selection of spiders in the field. Journal of Arachnology 27 (1), 317
– 324
Nyffeler, M., Dean, D.A. & Sterling, W.L. (1992) Diets, feeding specialization, and predatory
role of two lynx spiders, Oxyopes salticus and Peucetia viridans (Araneae: Oxyopidae), in a
Texas cotton agroecosystem. Environmental Entomology 21 (6), 1457 - 1465
Nyffeler, M., Sterling, W.L. & Dean, D.A. (1994a) How spiders make a living.
Environmental Entomology 23 (6), 1357 – 1367
Nyffeler, M., Sterling, W.L. & Dean, D.A. (1994b) Insectivorous activities of spiders in
United States field crops. Journal of Applied Entomology 118, 113 - 128
Pearce, S., Hebron, W.M., Raven, R.J., Zalucki, M.P. & Hassan, E. (2004) Spider fauna of
soybean crops in south-east Queensland and their potential as predators of Helicoverpa spp.
(Lepidoptera: Noctuidae). Australian Journal of Entomology 43, 57 - 65
Provencher, L. and Riechert, S.E. (1991) Short-term effects of hunger conditioning on spider
behavior, predation, and gain of weight. Oikos 62 (2) 160 – 166
122
Püntener, W. (1981) Manual for field trials in plant protection. Second edition. Agricultural
Division, Ciba-Geigy Limited
Riechert, S.E. (1999) The hows and whys of successful pest suppression by spiders: insights
from case studies. Journal of Arachnology 27 (1), 387 - 396
Riechert, S.E. & Bishop, L. (1990) Prey control by an assemblage of generalist predators:
spiders in garden test systems. Ecology 71 (4), 1441 – 1450
123
5 BRASSICA ICM TOOLKIT CD - INDUSTRY TRAINING
ACTIVITIES
D.Carey (QLD DEEDI).
Introduction.
The Brassica Integrated Crop Management Toolkit CD (Brassica ICM toolkit CD) was posted
to Brassica industry stakeholders as part of the previous project National Diamondback Moth
project: integrating biological, chemical and area-wide management of brassica pests,
VG04004. The toolkit provides a one stop shop for information on Brassica crop management
and complements valuable existing paper and electronic-based information produced in the
past.
The CD integrates over 355 fact sheets of detailed information and images on crop
management issues, general references and internet links to further sources of information.
The brassica problem solver diagnostic key allows growers to go through a check list
answering short questions about any problem they see in there crop, and then produces a short
list of the possible causes. This self diagnosis can then be compared to reference photos on
the CD and further information on management options can be found in the fact sheets.
Developing a user friendly training manual and training program and delivering it as an
interactive training workshop in each state was undertaken to teach growers how to access
and run the diagnostic tools, generally encourage the use of the toolkit and show growers
how to maximise the valuable information contained in the CD. The Brassica ICM Toolkit
CD was distributed to all Brassica growers in all Australian states. The post out also contained
an explanatory letter and a form to allow growers to register their interest in attending a
Brassica ICM Toolkit training session.
Raising Industry Awareness of the Brassica ICM toolkit CD. Prior to conducting training a number of activities were undertaken to increase industry
awareness and future opportunities to participate in planned training these included
1 An article in the Vegetables Australia magazine. This article highlighted the release of the
Brassica ICM Toolkit to industry. This article also included information about future hands on
training opportunities for industry members and contained project staff contact details. This
article generated a number of requests for further copies of the Brassica ICM Toolkit CD
from the Australian Industry.
2 Australian Vegetable Industry Conference. David Carey (DEEDI) was an invited speaker at
the Researchers Forum of the Australian Vegetable Industry Conference held in Sydney in
2009. David took the opportunity to highlight the many useful aspects of the Brassica ICM
Toolkit at this industry focussed session.
3 Flyers outlining the availability of the Brassica ICM Toolkit were also included with the
mail out of the updated Diamondback Insecticide Resistance Management strategy in late
2009 to all growers nationally. The Brassica ICM Toolkit CD was also highlighted in
Brassica industry newsletters.
Training Manual Design and Content. Prior to conducting workshops a training manual was designed, developed and produced.
Initial development included randomly selecting growers and contacting them directly by
telephone to canvass their thoughts and feedback on the Brassica ICM Toolkit CD that had
been posted to them.
124
These telephone discussions with growers in each state also provided an avenue to discuss
training needs and options as well as giving guidance regarding the most appropriate training
format, and timing of training activities in each state.
Industry Training Manual.
A training manual, was specifically designed for industry users who have limited or no
previous computer experience was produced (Appendix 3.1). This manual provides a step by
step guide to accessing the many functions of the Brassica ICM Toolkit. The Brassica ICM
Toolkit training manual was adapted and used “on screen” as the basis for the user friendly,
hands on interactive training workshops held recently in each state. The manual has been
posted to all users who requested a copy after attending one of the interactive training
sessions. Written feedback from workshop participants indicated that the training manual was
very useful and enhanced the Brassica ICM Toolkit training experience.
Industry Training Sessions.
Several smaller test training sessions were conducted so that the CD manual and training
program could be trialled before conducting the training at the national workshops. These
were held with selected Queensland growers and consultants prior to embarking on the
Australia wide industry training tour. These tests sessions allowed fine tuning of the
equipment and techniques used in the final training program.
Training sessions were carried out in the following brassica production locations in the
following states (Table 5.1). These workshops events were kindly promoted locally by state
government research agencies, Vegetables WA, Victorian Vegetable Growers Association,
Tasmanian Farmers and Graziers Association and NSW Farmers Association.
Table 1. Details of training workshops.
Training Date Location State No of
Attendees
Tues July 27th
DEVONPORT TAS 16
Wed July 28th
CRANBOURNE
VIC 10
Thurs July29th
WERRIBEE
VIC 13
Wed Aug 4th
GATTON
QLD 15
Thur Aug 5th
BATHURST
NSW 19
Fri Aug 6th PENRITH
NSW 3
Thurs Aug 12th
LENSWOOD
SA
12
Tues Aug 17th
MANJIMUP
WA 16
Wed Aug 18th
JOONDALUP
WA
8
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The Ausveg, Veginsights weekly newsletter also highlighted the Brassica ICM Toolkit
training and Brassica Researcher Update sessions, prior to their commencement and over the
month that the sessions were conducted.
Training Sessions – A Hands on Process.
A self contained mobile training computer network was hired for the duration of the training
program. This mobile computer network consisted of ten new dedicated training computers
with the Brassica ICM Toolkit preinstalled and ready to run. The chief trainer Mr David
Carey (DEEDI) ran each training session according to a training plan that followed the
structure of the dedicated training manual.
Guided by a visual step by step power point® training presentation based on the training
manual, growers and other participants were guided through a comprehensive overview of the
content of the Brassica ICM Toolkit. This process introduced all aspects of the vast array of
information contained in the CD, including web link access points and a session dedicated to
effective use of the Brassica Problem Solver Diagnostic Key.
Other brassica researchers – involved in the researcher update presentations were also
available to assist participants during these interactive computer training sessions. The
growers less experienced in the use of personnel computers commented at the end of the
session that they felt confident accessing the information contained in the tool after
participating in the “hands on” training sessions.
Confirmation of the Value of One on One Training.
A number of growers stated that they had a copy of the Brassica ICM Toolkit at home in the
office but had not used it prior to attending training. These same growers stated that after the
training session they were impressed with the information contained on the CD and would
definitely use it on their return home.
The practical “hands on” training sessions often included using the problem diagnosis key to
identify a field problem described as being of concern to an attending grower. In Penrith for
example a Cauliflower grower was able to key out a current production problem (boron
deficiency) that was unknown to him but was causing significant economic loss in the field. A
good example of the positive benefits to be gained from information within the CD.
Many positive comments were made by training participants some of these quotes from an
attendee survey are highlighted below.
Training session feed-back from growers;
“it‟s like having an agronomist at home”
“easy to use, great detail, narrows down the problem – no guessing”
„easy to find the problem by following the links”
“much quicker and easier to access specific information”.
“a pertinent and useful resource”
The images and fact sheets on the CD were a highlight to attending growers who could use
the CD to check up on diseases, weeds and insects they had observed in their crops in the
previous weeks.
The feedback also indicated that the Brassica ICM Toolkit proved to be user friendly and
intuitive to growers with limited computer knowledge who attended the hands on training
sessions. The training format allowed growers to gain confidence in using the Brassica ICM
126
Toolkit and many stated they would go home after these sessions and “get it on the job” to
solve on farm issues.
Summary Comments.
A total of 139 growers and industry support personnel participated in the hands on Brassica
CD training.
Growers responded positively to all elements of the Brassica Research Update sessions held
in the major state brassica production regions. The interactive brassica information sessions
complemented the Brassica ICM Toolkit training program. Positive feedback was received
after all presentations and growers and industry personnel were very receptive to the
information supplied. Informative question sessions and interactive discussion among all
participants made these local events a resounding success. Presenters were welcomed warmly
at all events with attendees in each state appreciating the logistical effort of travelling to all
states with a mobile computer network and other presentation equipment.
Thanks to Cate Paull (SARDI) for liaising with state vegetable researchers and representative
bodies to co-ordinate presentation dates and venues. Without this organisation and interstate
co-ordination the Australia wide tour would not have been such a success.
127
6. COMMUNICATION AND TECHNOLOGY TRANSFER
ACTIVITIES.
C.Paull (SARDI) A number of communication tools were used to disseminate information, from the research
undertaken in this project, to the Brassica industry. The major communication tools included
continued production of the Brassica IPM national newsletter and workshops. These
communication tools had already been established and had been identified in previous
projects as the ones most valued by industry stakeholders.
Newsletters
The Brassica IPM national newsletter was developed as part of the project Implementing Pest
Management of Diamondback Moth, VG00055 and was identified by industry as a valuable
communication tool during the National Diamondback Moth project: integrating biological,
chemical and area-wide management of brassica pests, VG04004. Throughout this project
three issues were produced (issues 12, 13 and 14), (Appendix 4.1.I-III)
Thirteen hundred copies of each issue were distributed by post and some additional copies
sent electronically as PDFs, copies of each issue were also made available on the SARDI
website. Each issue covered a range of topics related to IPM and sustainable Brassica
production, information from this and other allied projects. Issue 14 provided an opportunity
to include some of the final results from this project for those of the industry unable to attend
the workshops. In each issue feedback from readers was always invited and contacts were
provided. Through out the project we received several emails in appreciation of the
information.
Work shops
In previous projects workshops were also identified as one of the most popular ways to obtain
information. The aims of the workshops were to update and inform industry about the final
achievements and results of the project.
Planning of workshops began in February 2010. State based research organisations
horticulture organizations were contacted to see if other groups had planned any workshops to
ensure that there were no clashes with other meetings, important times in the production
calendar and if there was any merit in amalgamating meetings to reduce the number of time
growers had to leave their farms to attend extension activities. The project team undertook
and organised nine Brassica Research Update workshops during July and August 2010. These
workshops also incorporated the training sessions which were part of objective 5 the Brassica
CD Toolkit training. Invitation flyers were distributed by state government research agencies
by post, email and advertised over five weeks, using the calendar of events on the Ausveg
web site. Grower organizations, Vegetables WA, Victorian Vegetable Growers Association,
Tasmanian Farmers Graziers Association and NSW Farmers Association were also helpful in
advertising workshops and organising to contact growers.
Workshop Attendance
Date Workshop – Location No of Attendees 27/7/2010 Devonport TAS 16 28/7/2010 Cranbourne VIC 10 29/7/2010 Werribee VIC 13 04/8/2010 Gatton QLD 15 05/8/2010 Bathurst NSW 19 06/8/2010 Penrith NSW 3 12/8/2010 Lenswood SA 12 17/8/2010 Manjimup WA 16 18/8/2010 Edgewater WA 8
Total 112
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Workshop Format
The workshops consisted of three main communication components 1) research presentations,
2) training session and 3) an electronic survey.
1) Presentations: The workshops included four presentations as they related to the individual
objectives of the project and where it was possible they were presented by the researchers
responsible for the research.
There were four core research presentations which related directly to the findings of the
project objectives the were:
Insecticide resistance and the newer pesticide chemistries – Greg Baker
Compost for Brassica vegetable production – Cate Paull
The impact of key predators of DBM – Chris McIntyre, Mike Keller
Using natural enemies to manage early season pests – Lara Senior
In addition in WA and in SA the workshops were extended to include the number of
additional presentations and incorporate research results from other Brassica related projects.
They included:
Developing options for control of Brassica stem canker - Lynette Deland (SARDI).
Optimising fertiliser use in for vegetable production – Alison Beattie (WA DPI).
The affect of uniform-aged Brassica seedlings on marketable yield and harvest –
Helen Ramsey (WA DPI).
We were also able to help collect data for the National vegetable IPM coordinator project,
VG09191.
2) Training
An informative training session to instruct growers on how to use the “Brassica decision
support toolkit CD” and manual was run by David Carey. This training session provided
growers and industry representatives with an opportunity to learn how to access information
and try the various aspects of this interactive CD resource by using individual personal
computers, in a hands on environment. The production distribution and training component of
the Brassica decision tool kit CD is covered in greater detail in section 5 of this report.
3) Electronic Survey
The third component of the workshops was a survey of growers and resellers who attended
the workshops. The aim of the survey was to elicit the current knowledge and attitudes of
industry representatives with respect to current pest management practices and attitudes to
IPM. The survey also included opportunities for feedback. The survey was delivered using the
electronic interactive software Keepad Turning point ®. This system allows respondents to
provide answers and information not only anonymously, but more or less instantaneously.
Surveys have been conducted in previous projects by phone for the project Advancing the
integrated management of diamondback moth (DBM) in Brassica vegetables, VG97014 and
by post for the National Diamondback Moth project: integrating biological, chemical and
area-wide management of brassica pests, VG04004. Both these methods can not only be time
consuming but often result in a limited number of responses.
Respondents said they enjoyed the experience as the got to see the results of the collective
responders more or less instantaneously. Incorporating “other” as a valid response option for
some questions also facilitated a level of interactivity. For example if someone answered
“other” the turning point presenter could stop and try and encourage more information. On a
number of occasions this generated discussion and a number of questions which were able to
be resolved then and there.
129
Workshop Summary:
The combination of the three different communication components helped to generate debate
and discussion as well as many questions, most of which were unique to each workshop. We
received positive feedback about the workshops via the electronic survey, phone, email and in
person. There were also a number of requests for additional information and since then we
have been able to follow up on all of these. There were in total 112 attendees and the numbers
were similar to previous workshops although of the people participating in the survey 30 %
had never been to a workshop previously.
Appreciation was not only evident from survey results but there were a number of positive
verbal responses.
Summary of Survey results:
Of the 112 people who attended the workshops 85 people participated in the survey. The
reasons people gave for not participating included; that they didn‟t want to, or they knew
another person from the same organization and deferred to them and in a number of cases,
people wanted to share the task with a colleague.
A copy of the survey questions and data are provided (Appendix 4.2 and 4.3). A summary of
the results are as follows. Demographically resellers were considered agricultural suppliers
and larger companies. Advisors were considered private scouts and agronomists. Through out
the course of the survey it was clear that there was some confusion in interpreting the
difference between these two demographic groups. Because of this, responses from resellers
and advisors were grouped together for the summary data. Researchers were also omitted.
Demographics:
Over 45 % of the respondents were growers. The remainder were made up of 30% percent of
resellers the remaining 25% were researchers or other industry related such as seedling
suppliers. For 30 % of the respondents it was the first brassica work shop they had attended.
Often resellers and advisers work with more than one grower. In order to get an idea of how
many brassica growers, information from the workshop would extend to, the survey
respondents were asked, how many brassica growers they represented? Two growers
indicated they had influence over 1- 5 growers and one grower influenced more than 10. Nine
resellers were responsible for advising one brassica grower, two resellers advised 1-5
growers, two resellers represented 5-10 and 11 resellers represented 10 or more brassica
growers. These results indicate that the information delivered at the work shops has the
potential to reach twice as many industry representatives than the total number of people that
attended the workshops.
Insect pest priorities and insecticide use:
To identify which pests are a problem in brassica vegetable production attendees were asked
which of the 10 listed pests had they sprayed for in the past 12 months. Resellers were asked
to interpret the question and answer by indicating which pest they had been asked about or
given advice about over the preceding 12 months. The three brassica pests sprayed for most in
the past 12 months were DBM (most), cabbage white and aphids. The response were ranked
exactly the same way not only nationally but regionally and similarly between growers and
resellers.
Respondents were asked to indicate which insecticides were used most often in the previous
12 months for chewing insects such as DBM caterpillars and sucking insects such as aphids.
Success ®
and Entrust ® insecticides for chewing insects were used by 19% of respondents.
The second and third most used, were Proclaim ® (14%) and the newer insecticides Coragen
®
130
and Belt ® (14 %). Confidor
® was most often used by the respondents (23 %) and Chess
® and
Pirimor ® were used by 16 % and 14% of respondents respectively for sucking insects.
Endosulphan and Organophosphates were used the least.
A visual question designed to test general knowledge about insect identification was shown as
part of the survey. The results showed that 88% respondents correctly identified the larvae.
Insecticide Resistance Management:
To determine what extent the integrated resistance management (IRM) “two window”
strategy is used by the industry, a question was asked about how often the strategy was
referred to. The results showed 6 % didn‟t know what it was, further questioning indicated
that these respondents were largely first time growers. Thirty two percent of respondents
never used the IRM strategy. The discussion that followed showed that the respondents who
didn‟t use it wanted clarification on its usefulness. The instantaneous nature of the survey and
having researchers at hand meant that answers and explanations to questions could be given
there and then. Of the 27 % that indicated that they use the IRM strategy regularly 54 % of
these were growers and 17 % were resellers and advisers.
Integrated Pest Management:
After being shown a general definition of IPM respondents were asked to score rate their
practice of IPM. Fifty eight % of all respondents rated their use of IPM high or very high.
Most growers used a combination of regular crop scouting 26%, their own knowledge and
experience 23% and information from insecticide labels 18% to help them make spray
decisions. Resellers and advisors used the same resources similarly. Interestingly the
electronic sampling plan was used by 5 % of respondents none of which were growers and
development calculator for DBM was used even less.
When asked to identify what incentives would encourage further uptake of IPM, in order of
importance 41% of 24% of growers and advisors said increasing the reliability of IPM tactics,
marketing incentives and increased enforcement of minimum residue limits 17% and 15% of
all respondents respectively are things that would encourage greater adoption of IPM.
Survey responses to identify which aspects of IPM they would better like to understand was
divided similarly for all respondents The three main areas identified were ways to improve
numbers of natural enemies 16 % followed by pest and beneficial insect identification 15.91%
and optimal spray techniques nearly 11.93%.
The survey ended with the obligatory question about indicating the usefulness of information
delivered. All but one respondent agreed that the information was useful.
Survey Findings and Key Recommendations:
While not directly comparable a survey was undertaken with Victorian Brassica growers in
1998 as part of the project Advancing the integrated management of diamondback moth in
Brassica vegetables, VG97014 some the questions from this previous project were similar to
the ones above.
Comparing responses from the two surveys the following general statements can be made.
The three most important pests in brassica production still remain DBM, cabbage white
butterfly and aphids.
One of the greatest differences over time is the changes in pesticide use. In 1998
organophosphate (OP) and synthetic pyrethroid (SP) insecticides were widely used. These
have now been largely replaced by the newer chemistries, and OP and SP insecticides are
131
being used far less. Advocacy by the IPM research community for the use of softer
chemistries, that is, ones that have reduced negative effect on natural enemies and the wider
environment, seems to have had resonance in the industry, despite users having to pay a
premium for these products. This represents a major advance in Australian Brassica pest
management practice since the 1990‟s, which perhaps has not been fully appreciated and
promoted, as much as it should be, by industry stakeholders.
Responses of the survey indicate infrequent use of IPM tools such as the DBM calculator and
electronic sampling plan. This could be seen as being in contradiction to the response to the
self-assessment question on the use of IPM, where 58% of survey respondents rated their use
of IPM as high. Interestingly it is these quantitative tools that can help remove the subjectivity
of decision making and can contribute to more effective IPM, but clearly the potential
advantages of quantified pest records has not been sufficiently and convincingly explained to
growers.
The results of the self assessment support that there has been an increase in IPM practice in
Brassica vegetable production since 1998. The industry is still enthusiastic about IPM, and the
respondents in this survey identified opportunities to increase the use of IPM and requested
more information about different aspects of IPM.
The three main incentives that respondents identified as ways to increase IPM / frequency of
use were:
1) Increasing the reliability of IPM
2) Marketing - IPM being recognised and rewarded by market heavy weights
3) Increase frequency of minimum residue testing. This indicates that growers recognise that
this mechanism could be used more effectively to encourage growers to take up IPM. This
might be achieved by helping growers to demonstrate their IPM credentials which could tie in
with marketing incentives. Conversely increasing the frequency of testing or imposing some
penalty on those not complying may have similar results.
The specific IPM information growers that growers are requesting is increasing the reliability
of IPM, enhancing numbers of and identifying natural enemies and optimal spray techniques.
Interestingly these are the areas of critical need identified by Brassica IPM entomologists to
further advance Brassica IPM practice nationally (eg. Baker, presentation on IPM Uptake,
HAL Office, 2008), and closely match with results of other recent Brassica grower surveys in
which spray techniques, followed by crop scouting, IRM and improving beneficial
abundance, were the most sought after for information/skills development.
The indication that industry would like to find ways to increase the reliability of IPM is
aligned with current recommendations in IPM science and where this science is focussing
future research efforts. Inevitably this will also involve identifying ways of enhancing natural
enemies, which is one of the key areas industry wants better information on. Regarding
optimal spray technology, new technologies exist, but they require support in order to be
validated before they can be presented to industry. Until such time there is further research it
is unlikely that there will be any major advances in IPM and these issues along with the
potential of IPM as being integral to sustainable production will remain unrealised and
unresolved.
The results show that survey respondents are united in recognising that a more fundamental
key to advancing IPM uptake, is to provide the superior tools needed (such as better spray
application and natural enemy colonization) through well-focussed research. It is also noted
that the packaging of basic IPM practices for grower access is still necessary.
132
Recommendations - Communication:
It is recommended that a coordinated updated electronic list of contacts for growers, resellers
and industry stakeholders would make the process of distributing information such as the
Brassica IPM newsletter and liaising with industry far more effective and efficient.
Another recommendation from one of the workshops, is that there might be merit in
conducting an annual/biannual brassica research / information day in each state. This could be
an effective and efficient way to truly integrate pest, disease and production information, and
a way of bringing together stakeholders and researchers.
COMMUNICATION OUTPUTS:
Newsletters:
Issues 12, 13 and 14 were produced and published
Workshops:
9 x workshops conducted
Fact sheets:
The following fact sheets were produced and distributed at workshops and or as part of the
newsletter mail outs.
10 steps to IPM – a reminder of key aspects of IPM.
Natural enemies for early season pests in QLD- “What, when and how to look for
them” (Appendix 4.4)
IRM 2009 two window strategy, updated, published and distributed to growers
nationally (Appendix 4.5).
Media:
21 October 2009 Cauliflowers and Compost - South Australian Grower
Web Sites:
Newsletters and information such as the IRM two window strategy 2009 version were
uploaded and updated regularly on the SARDI and VIC DPI web site.
Conferences:
Dr Lara Senior ( DEEDI) and Mr Christopher McIntrye (Adelaide University) will travel to
Kasetsart University, Kamphaeng Saen campus, Nakhon Pathom, Thailand, to present some
of the research results, from the project, at “The sixth international workshop on management
of the diamondback moth and other crucifer insect pests” from 21st to 25th March 2011.
Feedback:
With all of the communication components we invited feedback and through out the project
we received enquires in person, by phone and email all of which were promptly followed up.
Acknowledgements:
These communication activities and workshops would not have been as successful or
supported to the extent that they were had it not been for the generous help of a number of
people, especially individuals from state government research agencies and state based
horticultural organisations. In many cases these individuals freely gave up their time and
resources to help organise and provide ways of contacting growers and organising resources
for the workshops. The project team gratefully acknowledges these people.
133
APPENDICES Appendix 1
LIST OF MORPHOSPECIES
Funcn Reference Number Order Division/Family
Larva /
Adult
D/ fun 1 Diptera Mycetophilidae l
D 2 Diptera Sciaridae a
D 3 Diptera Chironomidae a
P 4 Nematoda a
Bacterial/D 5 Nematoda a
P 6 Coleoptera Carabidae l
O 7 Coleoptera Scarabaeidae a
D 8 Diptera Cecidomiidae l
P 9 Tricladida a
P/O 10 Coleoptera Staphylinidae a
P/O 11 Coleoptera Staphylinidae a
P/O 12 Coleoptera Staphylinidae a
P/O 13 Coleoptera Staphylinidae l
D 14 Diptera Drosophilidae a
D 15 Diptera Scatopsidae l
D 16 Diptera Otitidae l
P/O 17 Coleoptera Staphlynidae l
D 18 Diptera Sphaeroceridae a
D 19 Diptera Sphaeroceridae a
O 20 Coleoptera Tenebrionidae a
O 21 Coleoptera Curculionoidea a
D 22 Diptera Trichoceridae l
D 23 Diptera Otitidae l
D 24 Diptera Anthomyiidae l
P 25 Coleoptera Staphylinidae a
P 26 Araneae Linyphiidae a
D fung 27 Diptera Mycetophilidae l
inc 28 Diptera Muscidae l
P 29 Coleoptera Staphylinidae a
D 30 Acarina Carpoglyphidae a
D 31 Annelida Oligochaeta a
inc 32 Acarina a
inc 33 Acarina a
pest 34 Mollusca a
D 35 Acarina Orabatid a
P 36 Acarina Bdellid a
134
D 37 Diptera Tipulidae l
P 38 Coleoptera Staphlynidae a
inc 39 Acarina a
O 40 Coleoptera a
P 41 Neuroptera Hemerobyiidae a
P 42 Chilopoda a
pest 43 Hemiptera Orsillinae a
P 44 Thysanoptera a
P 45 Coleoptera Aleocharinae a
D 46 Diptera Sphaeroceridae a
P/O 47 Hymenoptera Formicidae a
P 48 Araneae Linyphiidae a
O 49 Acarina a
O 50 Acarina a
D 51 Collembola a
D 52 Diptera Psychodidae a
D 53 Diptera Psychodidae l
P/O 54 Hymenoptera Formicidae a
D 55 Acarina Oribatid a
D/fung 56 Diptera Mycetophilidae l
O 57 Coleoptera a
P 58 Coleoptera Carabidae a
S/D 59 Coleoptera Tenebrionidae l
O 60 Acarina a
P 61 Coleoptera Carabidae a
P/O 62 Hymenoptera Formicidae a
inc 63 Diptera Cyclorrahapha l
O 64 Hemiptera Cydnidae a
inc 65 Diptera Cylclorrhapha l
P 66 Thysanoptera Haplothrips l
P 67 Neuroptera l
O 68 Lepidoptera l
D 69 Acarina Orabatid a
P 70 Araneae Theridiidae a
pest 71 Mollusca a
inc 72 Coleoptera l
D 73 Diptera Cylclorrhapha l
D 74 Diptera Cylclorrhapha l
inc 75 Acarina a
O 76 Coleoptera Cucujoidea l
inc 77 Coleoptera
P 78 Chilopoda a
135
pest 79 Mollusca a
D 80 Isopoda
D 81 Diptera Psychodidae l
D 82 Coleoptera Ptilidae
O 83 Lepidoptera l
pest 84 Hemiptera Aphididae l
O 85 Coleoptera a
P 86 Hymenoptera a
P 87 Coleoptera Carabidae
inc 88 Hymenoptera Trichogrammatidae a
P 89 Coleoptera Staphylinidae a
P 90 Coleoptera Staphylinidae a
inc 91 Diptera Cylclorrhapha l
pest /O 92 Coleoptera Elateridae l
D/fung 93 Diptera Mycetophilidae l
inc 94 Diptera l
P 95 Hymenoptera a
inc 96 Eggs? l
inc 97 Acarina Oribatid a
P/O/pest 98 Dermaptera a
D/fung 99 Diptera Mycetophilidae l
D 100 Diptera Sciomyzoidea a
pest 101 Thysanoptera a
inc 102 Coleoptera a
D 103 Diptera Drosophilidae a
O 104 Lepidoptera p
D 105 Hemiptera Dipscoridae a
P 106 Coleoptera Coccinellidae a
D 107 Psocoptera a
O 108 Coleoptera Elateridae a
O 109 Lepidoptera p
O 110 Coleoptera Curculionoidea l
D 111 Coleoptera Tenebrionidae l
pest 112 Mollusca a
D 113 Coleoptera Scarabaeidae l
inc 114 Acarina a
pest 115 Diptera Muscoidea l
O 116 Diptera Chloropoidea a
D 117 Psocoptera a
D 118 Coleoptera Byrrhoidea l
inc 119 Coleoptera a
O 120 Diptera Muscoidea l
136
inc 121 Hemiptera l
P 122 Hymenoptera a
O 123 Thysanoptera l
P 124 Coleoptera Carabidae a
inc 125 Lepidoptera p
inc 126 Diptera Cyclorrhapha l
D 127 Diptera Drosophilidae a
P 128 Coleoptera Staphylinidae a
inc 129 Coleoptera l
D/fung 130 Coleoptera Lathridiidae l
inc 131 Coleoptera l
inc 132 Coleoptera l
inc 133 Coleoptera l
P 134 Hymenoptera a
P 135 Hymenoptera aPOD 136 Diptera Cecidomyiidae l
P 137 Diptera Therevidae? l
inc 138 Coleoptera a
D 139 Diptera Phoridae a
D 140 Coleoptera Hydrophilidae a
pest 141 Diptera a
inc 142 Coleoptera a
inc 143 Acarina a
P 144 Coleoptera Staphylinidae l
P 145 Coleoptera Carabidae a
pest 146 Acarina Penthaleidae a
D= Detritivore
P=Predator
O=Omnivore
pest = pest
inc= inconclusive
fung= fungivore
bacteria= bacterial feeder
137
Appendix 2.1 (I) – Identifying natural enemies of early season brassica pests in
unsprayed plantings at Gatton Research Station: photographs of trial sites
Photo no 1: Replicate block number 4, Gatton Research Station (Lockyer Valley), 24
th April 2009
Photo no 2: Replicate block number 3, Gatton Research Station (Lockyer Valley), 24
th April 2009
138
Appendix 2.1 (II) - weather data
0
5
10
15
20
25
30
35
40
26/2
/09
12/3
/09
26/3
/09
9/4/
09
23/4
/09
7/5/
09
Date
Tem
pera
ture
(°C
)
0
10
20
30
40
50
60
Rain
(m
m)
rain
max tempmin temp
Source: Gatton Research Station weather station
139
Appendix 2.1 (III) – pest species data
Pests logged during the trial period
Common name Scientific name
Lepidoptera
Cabbage cluster caterpillar Crocidolomia pavonana
Cluster caterpillar Spodoptera litura
Heliothis Helicoverpa sp.
Cabbage white butterfly Pieris rapae
Centre grub Hellula hydralis
Diamondback moth Plutella xylostella
Loopers Chrysodeixis sp.
Sucking pests
Aphids Predominantly Myzus persicae;
a few Brevicoryne brassicae
Silverleaf whitefly Bemisia tabaci
Thrips Thysanoptera, various species
Leafhoppers/jassids Cicadellidae, various species
Green vegetable bugs Nezara viridula
Rutherglen bugs Nysius vinitor
Soil pests
Black field earwig Nala lividipes
Crickets Primarily Teleogryllus commodus
Wireworms Elateridae
False wireworms Tenebrionidae
Minor pests (found infrequently)
Flea beetles Chrysomelidae, various species
Weevils Curculionoidea, various species
Grasshoppers/locusts Orthoptera
Cutworms Agrotis sp.
140
Pest data - results of visual inspections of plants
Data points at 20/4/09 and 5/5/09 represent results of destructive sampling; remaining dates
represent results of plants sampled in situ.
Bt applied 25th March and 1
st April.
Lepidoptera
0
2
4
6
8
10
12
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Nu
mb
er
of
larv
ae
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa sp.
Number of lepidopteran larvae logged from broccoli (mean per plant)
0
2
4
6
8
10
12
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Nu
mb
er
of
larv
ae
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa sp.
Number of lepidopteran larvae logged from cabbage (mean per plant)
141
0
2
4
6
8
10
12
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Nu
mb
er
of
larv
ae
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa sp.
Number of lepidopteran larvae logged from cauliflower (mean per plant)
0
2
4
6
8
10
12
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Nu
mb
er
of
larv
ae
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa sp.
Number of lepidopteran larvae logged from Chinese cabbage (mean per plant)
142
Sucking pests
Sucking pests were assessed on a crude scale based on relative severity of infestation: 0 =
absent; 1 = low; 2 = medium; 3 = high
0
0.5
1
1.5
2
2.5
3
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Ap
hid
in
festa
tio
n
Broccoli
Cabbage
Cauliflower
Chinese cabbage
Relative severity of aphid infestation in four brassica types
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Wh
itefl
y s
cale
in
festa
tio
n
Broccoli
Cabbage
Cauliflower
Chinese cabbage
Relative severity of whitely (scales) infestation in four brassica types
143
0
0.2
0.4
0.6
0.8
1
1.2
1.4
3/3/09 10/3/09 17/3/09 24/3/09 31/3/09 7/4/09 14/4/09 21/4/09 28/4/09 5/5/09
Date
Th
rip
s i
nfe
sta
tio
nBroccoli
Cabbage
Cauliflower
Chinese cabbage
Relative severity of thrips infestation in four brassica types
144
Appendix 2.1 (IV) – beneficial fauna logged during the trial period
Beneficial fauna Notes
Spiders * Including: Lycosidae, Theridiidae, Clubionidae; Salticidae,
Oxyopidae, Araneidae, Tetragnathidae, Thomisidae, plus unidentified
soil-dwelling and foliage-dwelling spiders
Ladybirds Transverse, Coccinella transversalis
Variable, Coelophora inaequalis
Three-banded, Harmonia octomaculata
Minute two-spotted, Diomus notescens
Common spotted, Harmonia conformis
White collared ladybird, Hippodamia variegata
Brown lacewings Hemerobiidae, not identified to genus
Hoverflies Syrphidae, not identified to species
Predatory bugs Including: brokenbacked bugs, Taylorilygus pallidulus; brown
smudge bugs, Deraeocoris signatus; assassin bugs, Reduviidae; pirate
bugs, Orius sp.; big eyed bugs, not identified to species
Ants Not identified to species
Other Soldier beetles, Chauliognathus pulchellus
Native earwigs, Labidura truncata
Carabid beetles, not identified to species, low numbers only
Centipedes, not identified to species, low numbers only
Parasitoids
Cotesia sp. (parasitising cabbage white larvae)
Pteromalus puparum (parasitising cabbage white pupae)
Tachnid flies, not identified to species (parasitising cabbage white
larvae)
Diadegma semiclausum (parasitising DBM larvae)
Litomastix sp. (parasitising looper larva)
Microplitis sp. (parasitising cabbage cluster larva)
Aphid parasitoids, not identified to species
Whitefly parasitoids: Eretmocerus sp., Encarsia sp.
* Samples of theridiids, clubionids/miturgids and lycosids were sent to the Queensland
Museum (Brisbane) for verification of identification, identified as follows:
Wolf spiders: Artoria sp. (not 100% certain)
Tangle-web spiders: Cryptachaea veruculata (formerly Achaearanea)
Sac / night-stalking spiders: Cheiracanthium gilvum (now in the Miturgidae, formerly
Clubionidae) and Clubiona sp. (Clubionidae)
145
Appendix 2.2 (I) – Identifying natural enemies of early season brassica pests in
commercial plantings in the Lockyer Valley: photographs of trial sites
Photo no 1: Farm 1, Mt Whitestone (Lockyer Valley), broccoli crop, 16
th February 2010
Photo no 2: Farm 1, Mt Whitestone (Lockyer Valley), cauliflower crop, 16
th February 2010
146
Photo no 3:Farm 2, Grantham (Lockyer Valley), cabbage crop (unsprayed area in
foreground, sprayed area in background), 22nd
February 2010
147
Photo no 4:Farm 3, Glenore Grove (Lockyer Valley), sprayed broccoli crop, 17
th March
2010
Photo no 5: Farm 3, Glenore Grove (Lockyer Valley), unsprayed mixed brassicas, 17
th
March 2010
148
Photo no 6: Pitfall trap and yellow sticky trap, placed in cabbage crop at farm 2 (Grantham,
Lockyer Valley), 22nd
February 2010
Photo no 7: Pitfall trap, placed in cabbage crop at Gatton Research Station, 13
th May 2009
149
Appendix 2.2 (II) – weather data
0
5
10
15
20
25
30
35
40
10/2
/10
24/2
/10
10/3
/10
24/3
/10
7/4/
10
Date
Tem
pera
ture
(°C
)
0
10
20
30
40
50
60
Rain
(m
m)
Rain
Max TempMin Temp
Source: Gatton Research Station weather station (a distance of from ca 5 km to 20 km from
trial areas)
150
Appendix 2.2 (III) – pest species data
Pests logged during the trial period
Common name Scientific name
Lepidoptera
Cabbage cluster caterpillar Crocidolomia pavonana
Cluster caterpillar Spodoptera litura
Heliothis Helicoverpa sp.
Cabbage white butterfly Pieris rapae
Centre grub Hellula hydralis
Diamondback moth Plutella xylostella
Loopers Chrysodeixis sp.
Sucking pests
Aphids Myzus persicae
Silverleaf whitefly Bemisia tabaci
Thrips Thysanoptera, various species
Leafhoppers/jassids Cicadellidae, various species
Rutherglen bugs Nysius vinitor
Soil pests
Black field earwig Nala lividipes
Crickets Primarily Teleogryllus commodus
Wireworms Elateridae
False wireworms Tenebrionidae
Minor pests (found infrequently)
Flea beetles Chrysomelidae, various species
Weevils Curculionoidea, various species
151
Lepidopteran pests: results of visual inspections of plants
0
0.5
1
1.5
2
2.5
3
15/02/10 22/02/10 01/03/10 08/03/10 15/03/10 22/03/10 29/03/10 05/04/10 12/04/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa spp
Number of lepidopteran larvae logged from plants in farm 1 broccoli (mean per plant, n = 30)
0
0.5
1
1.5
2
2.5
3
15/02/10 22/02/10 01/03/10 08/03/10 15/03/10 22/03/10 29/03/10 05/04/10 12/04/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa spp
Number of lepidopteran larvae logged from plants in farm 1 cauliflower (mean per plant, n =
30)
152
0
0.5
1
1.5
2
2.5
3
15/02/10 22/02/10 01/03/10 08/03/10 15/03/10 22/03/10 29/03/10 05/04/10 12/04/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa spp
Number of lepidopteran larvae logged from plants in farm 2 unsprayed cabbage (mean per
plant, n = 30)
0
0.5
1
1.5
2
2.5
3
15/02/10 22/02/10 01/03/10 08/03/10 15/03/10 22/03/10 29/03/10 05/04/10 12/04/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa spp
Number of lepidopteran larvae logged from plants in farm 2 sprayed cabbage (mean per plant,
n = 30)
153
0
0.5
1
1.5
2
2.5
3
15/02/10 22/02/10 01/03/10 08/03/10 15/03/10 22/03/10 29/03/10 05/04/10 12/04/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa spp
Number of lepidopteran larvae logged from plants in farm 3 unsprayed mixed brassicas (mean
per plant, n = 30)
0
0.5
1
1.5
2
2.5
3
15/02/10 22/02/10 01/03/10 08/03/10 15/03/10 22/03/10 29/03/10 05/04/10 12/04/10
Date
Nu
mb
er
of
larv
ae p
er
pla
nt
P. rapae
P. xylostella
H. hydralis
C. pavonana
S. litura
Helicoverpa spp
Number of lepidopteran larvae logged from plants in farm 3 sprayed broccoli (mean per plant,
n = 30)
154
Sucking pests: results of visual inspections of plants
0
10
20
30
40
50
60
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
insects
per
pla
nt
Whitefly adults
Whitefly scales
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from plants in farm 1 broccoli (mean per plant, n = 30)
0
10
20
30
40
50
60
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
insects
per
pla
nt
Whitefly adults
Whitefly scales
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from plants in farm 1 cauliflower (mean per plant, n = 30)
155
0
1
2
3
4
5
6
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
insects
per
pla
nt
Whitefly adults
Whitefly scales
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from plants in farm 2 unsprayed cabbage (mean per plant, n
= 30)
0
1
2
3
4
5
6
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
insects
per
pla
nt
Whitefly adults
Whitefly scales
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from plants in farm 2 sprayed cabbage (mean per plant, n =
30)
156
0
2
4
6
8
10
12
14
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
insects
per
pla
nt
Whitefly adults
Whitefly scales
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from plants in farm 3 unsprayed mixed brassicas (mean per
plant, n = 30)
0
2
4
6
8
10
12
14
15/2/10 22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date
Nu
mb
er
insects
per
pla
nt
Whitefly adults
Whitefly scales
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from plants in farm 3 sprayed broccoli (mean per plant, n =
30)
157
Sucking pests: results of sticky trapping
0
50
100
150
200
250
300
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
insects
per
trap
Whitefly
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from sticky traps in farm 1 broccoli (mean per trap, n = 5)
0
50
100
150
200
250
300
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
insects
per
trap
Whitefly
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from sticky traps in farm 1 cauliflower (mean per trap, n = 5)
Peak leaf-hopper trap catch was 559 in broccoli and 1568 in cauliflower.
158
0
20
40
60
80
100
120
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
insects
per
trap
Whitefly
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from sticky traps in farm 2 unsprayed cabbage (mean per
trap, n = 5)
0
20
40
60
80
100
120
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
insects
per
trap
Whitefly
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from sticky traps in farm 2 sprayed cabbage (mean per trap,
n = 5)
159
0
20
40
60
80
100
120
140
160
180
200
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
insects
per
trap
Whitefly
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from sticky traps in farm 3 unsprayed mixed brassicas (mean
per trap, n = 5)
0
20
40
60
80
100
120
140
160
180
200
22/2/10 1/3/10 8/3/10 15/3/10 22/3/10 29/3/10 5/4/10 12/4/10
Date collected
Nu
mb
er
insects
per
trap
Whitefly
Aphids
Thrips
Leafhoppers
Number of sucking pests logged from sticky traps in farm 3 sprayed broccoli (mean per trap,
n = 5)
160
Appendix 2.2 (IV) – Evaluation of the predatory behaviour of some spiders
commonly found in early season brassica crops: photographs of experimental
set-up
Beneficial fauna logged during the trial period
Common name Scientific name
Spiders
Wolf spider Lycosidae
Tangle-web spider Theridiidae
Sac / night-stalking spider Clubionidae/Miturgidae
Jumping spider Salticidae
Lynx spider Oxyopidae
Flower/crab spider Thomisidae
Orb web spider Araneidae
Long-jawed spider Tetragnathidae
Various unidentified soil-dwelling & foliage-dwelling spiders
Ladybirds
Transverse ladybird Coccinella transversalis
Variable ladybird Coelophora inaequalis
Three-banded ladybird Harmonia octomaculata
Minute two-spotted ladybird Diomus notescens
Common spotted ladybird Harmonia conformis
White collared ladybird Hippodamia variegata
Mite-eating ladybird Stethorus spp
Brown lacewings Hemerobiidae
Hoverflies Syrphidae
Predatory bugs
Brokenbacked bug Taylorilygus pallidulus
Big eyed bug Geocoris lubra
Pirate bug Orius spp.
Assassin bug Reduviidae
Brown smudge bug Deraeocoris signatus
Apple dimpling bug Campylomma liebknechti
Predatory shield bug Pentatomidae
Predatory beetles
Rove beetle Staphylinidae
Ground beetle Carabidae (including Bombardier beetles)
Soldier beetle Chauliognathus pulchellus
Ants Formicidae (variety of species)
Common brown earwig Labidura truncata
Centipede Chilopoda
Parasitoids
Moth egg parasitoids Trichogramma sp.; Telenomus sp.
Diamondback moth parasitoids Diadegma sp.; Diadromus sp.
Moth larva parasitoids Microplitis sp.; Cotesia sp.; Litomastix sp.
Tachnid fly Trichopoda sp.
Whitefly parasitoids Eretmocerus sp.; Encarsia sp.
Aphid parasitoids Aphidius sp.
161
Foliage-dwelling predators: results of visual inspections of plants
Numbers of some foliage-dwelling predators appear to be linked to aphid populations;
therefore these data are included for comparison.
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
15-Feb 22-Feb 5-Mar 8-Mar 15-Mar 22-Mar 29-Mar 9-Apr 12-Apr
No
. p
red
ato
rs p
er
pla
nt
0
10
20
30
40
50
60
70
80
90
No
. ap
hid
s p
er
pla
nt
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Foliage spiders
Aphids
Number of predators logged from plants in farm 1 broccoli (mean per plant, n = 30)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
15-Feb 22-Feb 5-Mar 8-Mar 15-Mar 22-Mar 29-Mar 9-Apr 12-Apr
No
. p
red
ato
rs p
er
pla
nt
0
10
20
30
40
50
60
70
80
90N
o.
ap
hid
s p
er
pla
nt
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Foliage spiders
Aphids
Number of predators logged from plants in farm 1 cauliflower (mean per plant, n = 30)
162
0.0
0.1
0.2
0.3
0.4
0.5
22-Feb 5-Mar 8-Mar 15-Mar 22-Mar 29-Mar 9-Apr 12-Apr
No
. p
red
ato
rs p
er
pla
nt
0
0.05
0.1
0.15
0.2
0.25
No
. ap
hid
s p
er
pla
nt
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Foliage spiders
Aphids
Number of predators logged from plants in farm 2 unsprayed cabbage (mean per plant, n =
30)
0.0
0.1
0.2
0.3
0.4
0.5
22-Feb 5-Mar 8-Mar 15-Mar 22-Mar 29-Mar 9-Apr 12-Apr
No
. p
red
ato
rs p
er
pla
nt
0
0.05
0.1
0.15
0.2
0.25
No
. ap
hid
s p
er
pla
nt
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Foliage spiders
Aphids
Number of predators logged from plants in farm 2 sprayed cabbage (mean per plant, n = 30)
163
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
5-Mar 8-Mar 15-Mar 22-Mar 29-Mar 9-Apr 12-Apr
No
. p
red
ato
rs p
er
pla
nt
0
2
4
6
8
10
12
14
16
18
20
No
. ap
hid
s p
er
pla
nt
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Foliage spiders
Aphids
Number of predators logged from plants in farm 3 unsprayed mixed brassicas (mean per
plant, n = 30)
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
5-Mar 8-Mar 15-Mar 22-Mar 29-Mar 9-Apr 12-Apr
No
. p
red
ato
rs p
er
pla
nt
0
2
4
6
8
10
12
14
16
18
20
No
. ap
hid
s p
er
pla
nt
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Foliage spiders
Aphids
Number of predators logged from plants in farm 3 sprayed broccoli (mean per plant, n = 30)
164
Foliage-dwelling predators: results of sticky trapping
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date trap collected
Ben
efi
cia
ls p
er
trap
Predatory beetles
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders
Number of predators caught on sticky traps in farm 1 broccoli (mean per trap, n = 5)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date trap collected
Ben
efi
cia
ls p
er
trap
Predatory beetles
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders
Number of predators caught on sticky traps in farm 1 cauliflower (mean per trap, n = 5)
165
0
1
2
3
4
5
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date trap collected
Ben
efi
cia
ls p
er
trap
Predatory beetles
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders
N/A
Number of predators caught on sticky traps in farm 2 unsprayed cabbage (mean per trap, n =
5)
0
1
2
3
4
5
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date trap collected
Ben
efi
cia
ls p
er
trap
Predatory beetles
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders
N/A
Number of predators caught on sticky traps in farm 2 sprayed cabbage (mean per trap, n = 5)
166
0
1
2
3
4
5
6
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date trap collected
Ben
efi
cia
ls p
er
trap
Predatory beetles
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders
N/A - not set up
Number of predators caught on sticky traps in farm 3 unsprayed mixed brassicas (mean per
trap, n = 5)
0
1
2
3
4
5
6
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date trap collected
Ben
efi
cals
per
trap
Predatory beetles
Predatory bugs
Hoverflies
Lacewings
Ladybirds
Spiders
N/A - not set up
Number of predators caught on sticky traps in farm 3 sprayed broccoli (mean per trap, n = 5)
167
Ground-dwelling predators: results of pitfall trapping
0
1
2
3
4
5
6
26th
Feb
5th
Mar
8th
Mar
12th
Mar
15th
Mar
19th
Mar
22nd
Mar
26th
Mar
29th
Mar
6th
Apr
9th
Apr
12th
Apr
Collection date
Nu
mb
er
ben
efi
cia
ls p
er
trap
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
Number of ground-dwelling predators caught in pitfall traps in farm 1 broccoli (mean per
trap, n = 5)
0
1
2
3
4
5
6
26th
Feb
5th
Mar
8th
Mar
12th
Mar
15th
Mar
19th
Mar
22nd
Mar
26th
Mar
29th
Mar
6th
Apr
9th
Apr
12th
Apr
Collection date
Nu
mb
er
ben
efi
cia
ls p
er
trap
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
Number of ground-dwelling predators caught in pitfall traps in farm 1 cauliflower (mean per
trap, n = 5)
NB Although traps were collected from the farm 1 sites on 22nd
February, the majority were
full of mud and therefore these data are not included.
168
0
1
2
3
4
5
6
26th
Feb
5th
Mar
8th
Mar
12th
Mar
15th
Mar
19th
Mar
22nd
Mar
26th
Mar
29th
Mar
6th
Apr
9th
Apr
12th
AprCollection date
Nu
mb
er
ben
efi
cia
ls p
er
trap
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
Number of ground-dwelling predators caught in pitfall traps in farm 2 unsprayed cabbage
(mean per trap, n = 5)
0
1
2
3
4
5
6
26th
Feb
5th
Mar
8th
Mar
12th
Mar
15th
Mar
19th
Mar
22nd
Mar
26th
Mar
29th
Mar
6th
Apr
9th
Apr
12th
AprCollection date
Nu
mb
er
ben
efi
cia
ls p
er
trap
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
Number of ground-dwelling predators caught in pitfall traps in farm 2 sprayed cabbage (mean
per trap, n = 5)
169
0
1
2
3
4
5
6
26th
Feb
5th
Mar
8th
Mar
12th
Mar
15th
Mar
19th
Mar
22nd
Mar
26th
Mar
29th
Mar
6th
Apr
9th
Apr
12th
AprCollection date
Nu
mb
er
ben
efi
cia
ls p
er
trap
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
N/A - not set up
Number of ground-dwelling predators caught in pitfall traps in farm 3 unsprayed mixed
brassicas (mean per trap, n = 5)
0
1
2
3
4
5
6
26th
Feb
5th
Mar
8th
Mar
12th
Mar
15th
Mar
19th
Mar
22nd
Mar
26th
Mar
29th
Mar
6th
Apr
9th
Apr
12th
AprCollection date
Nu
mb
er
ben
efi
cia
ls p
er
trap
Rove beetles
Ground beetles
Native earwigs
Lycosid spiders
N/A - not set up
Number of ground-dwelling predators caught in pitfall traps in farm 3 sprayed broccoli (mean
per trap, n = 5)
170
Parasitoids: results of sticky trapping
0
5
10
15
20
25
30
35
40
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Other parasitoidAphidiusTrichopoda
EncarsiaEretmocerusLitomastixCotesiaDiadromusDiadegma
MicroplitisTelenomusTrichogramma
Number of parasitoids caught on sticky traps in farm 1 broccoli (mean per trap, n = 5)
0
5
10
15
20
25
30
35
40
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Other parasitoid
Aphidius
TrichopodaEncarsia
Eretmocerus
Litomastix
Cotesia
Diadromus
DiadegmaMicroplitis
Telenomus
Trichogramma
Number of parasitoids caught on sticky traps in farm 1 cauliflower (mean per trap, n = 5)
171
0
5
10
15
20
25
30
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Other parasitoid
Aphidius
Trichopoda
Encarsia
Eretmocerus
Litomastix
Cotesia
Diadromus
Diadegma
Microplitis
Telenomus
Trichogramma
N/A
Number of parasitoids caught on sticky traps in farm 2 unsprayed cabbage (mean per trap, n =
5)
0
5
10
15
20
25
30
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Other parasitoid
Aphidius
TrichopodaEncarsia
Eretmocerus
Litomastix
Cotesia
Diadromus
DiadegmaMicroplitis
Telenomus
Trichogramma
N/A
Number of parasitoids caught on sticky traps in farm 2 sprayed cabbage (mean per trap, n = 5)
172
0
2
4
6
8
10
12
14
16
18
20
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Other parasitoidAphidiusTrichopodaEncarsiaEretmocerusLitomastixCotesiaDiadromusDiadegmaMicroplitisTelenomusTrichogramma
N/A - not set up
Number of parasitoids caught on sticky traps in farm 3 unsprayed mixed brassicas (mean per
trap, n = 5)
0
2
4
6
8
10
12
14
16
18
20
22-F
eb
26-F
eb
5-M
ar
9-M
ar
12-M
ar
15-M
ar
19-M
ar
22-M
ar
26-M
ar
29-M
ar
6-A
pr
9-A
pr
12-A
pr
Date collected
Nu
mb
er
para
sit
oid
s p
er
trap
Other parasitoidAphidiusTrichopodaEncarsiaEretmocerusLitomastixCotesiaDiadromusDiadegmaMicroplitisTelenomusTrichogramma
N/A - not set up
Number of parasitoids caught on sticky traps in farm 3 sprayed broccoli (mean per trap, n = 5)
173
Appendix 2.3 – weather data
0
5
10
15
20
25
30
35
25/3
/10
8/4/
10
22/4
/10
6/5/
10
20/5
/10
3/6/
10
Date
Tem
pera
ture
(°C
)
0
10
20
30
40
50
60
Rain
(m
m)
Rain
Max TempMin Temp
Source: Gatton Research Station weather station
174
Appendix 2.4
Experimental set-up type 1 – Petri dish
Experimental set-up type 2 – enclosed broccoli seedling
175
Lycosid spider observed on broccoli seedling during experiment 2, Selection of prey species
(enclosed seedling method) part 1, 7th September 2010.
176
Appendix 3.1
177
Appendix 4.1 (I)
178
Appendix 4.1 (II)
179
Appendix 4.1 (III)
180
Appendix 4.2
Brassica Research Update 2010 – Survey Questions
1) Who are you….?
• Brassica grower
• Researcher
• Reseller
• Advisor
• Other
2) How many growers do you represent ?
• Yourself
• 1 – 5
• 5 – 10
• 10 or more
•
3) Have you been to any of previous brassica research updates or workshops?
• Yes
• No
4) Please identify the pests that you have had to spray for, in the past 12 months
• Diamondback moth
• Cabbage white butterfly
• Aphids
• Thrips
• Cutworm
• Helicoverpa
• Cabbage centre grub
• Looper caterpillar
• Earwigs
• Other
5) Which of the following insecticides for chewing insects have you used in the past 12 months?
• Pyrethroids
• Success®, Entrust
®
• Proclaim®
• Regent®
• OPs - Organophosphates
• Bt
• Avatar®
181
• Coragen®, Belt
®
• Other
6) Which of the following insecticides for sucking insects have you used in the past 12 months? • Pirimor
®
• Chess ®
• Confidor ®
• endosulphan
• OPs Organophosphates
• Pyrethroids
• Other
7) What am I ?
• A good bug – a natural enemy
• A bad bug –pest
8) How often do you use this …?
• Every month or so
• Once a year
• What is it ?
• Never
Statement: Integrated Pest Management IPM includes ….
a mixture of pest and disease control methods used together
• moving away from relying on chemicals as the only control method
• monitoring for pests and natural enemies regularly before and after spraying fine tuning
chemical sprays, choosing the right chemical, applying the correct rate at the right time with
calibrated spray equipment.
• reducing the need to spray
9) Based on the above statements how would you rate your level of practise of IPM?
• Low
• Quite low
• Medium
• High
• Very high
10) What tools and resources do you use when you are deciding what and when to spray?
• Pesticide toxicity chart
• Your own knowledge and experience
• Electronic scouting tool
• Information on insecticide labels
• Regular crop scouting
• Record and review pest numbers regularly
• Pest development calculator
• Other growers
• Agronomists resellers
• Other
182
11) What would encourage you to use IPM more often ?
• Marketing incentives
• National quality standard - audited process
• Increasing the reliability of IPM
• Increased enforcement of minimum residue levels
• More time
• More information
• Other
12) Which IPM topics you would like to understand better?
• How IPM works
• DBM control in relation with other pest and disease control using IPM
• Crop monitoring
• Pest and beneficial insect identification
• Insecticide resistance management
• Improving natural enemy numbers
• Using products of low toxicity to beneficials
• Optimal spraying techniques
• Accessing an IPM consultant
• Other
13) Are there any other issues you would like to raise?
14) Was the information from this meeting was helpful?
• Strongly Agree
• Agree
• Neutral
• Disagree
• Strongly Disagree
Thank you
183
Appendix 4.3
Results from 2010 surveyQuesti
on 1 Growers
Resear
chers ResellersAdvisorsOther
No 39.00 5.00 13.00 12.00 19.00
% 45.88 5.88 15.29 14.12 22.35
Questi
on 2 How many growers do you represent?
Yourse
lf
1 - 5
grower
s 5 - 10
10 or
more Total
Grower 34.00 3.00 0.00 1.00 36.00
Researcher0.00 0.00 0.00 0.00 0.00
Reseller 5.00 1.00 1.00 7.00 14.00
Adviisor 4.00 0.00 1.00 4.00 9.00
Reseller plus advisor 9.00 1.00 2.00 11.00
Other 0.00 0.00 0.00 0.00 0.00
Total
Questi
on 3 Have you attended a previous Brassica Work shop?
yes no
Grower 22.00 12.00 34.00 0.65 0.35
Researcher3.00 2.00 5.00 0.60 0.40
Reseller 9.00 4.00 13.00 0.69 0.31
Adviisor 7.00 5.00 12.00 0.58 0.42
Reseller plus advisor 16.00 9.00 25.00 0.64
Other 9.00 10.00 19.00 0.47 0.53
Total 66.00 42.00 108.00 0.61
Questi
on 4 Insect pests sprayed for in the last 12 months
DBM
cabbag
e white Aphids Thrips
Cutwor
m
Helico
verpa
Cabba
ge
centre
grub
Looper
caterpi
llar
Earwig
s Other Total
Grower 32.00 30.00 23.00 9.00 11.00 11.00 7.00 6.00 0.00 4.00 133.00
% 24.06 22.56 17.29 6.77 8.27 8.27 5.26 4.51 0.00 3.01
Researcher3.00 1.00 2.00 1.00 0.00 1.00 1.00 0.00 0.00 1.00 10.00
% 30.00 10.00 20.00 10.00 0.00 10.00 10.00 0.00 0.00 10.00
Reseller 12.00 8.00 10.00 6.00 6.00 6.00 3.00 2.00 5.00 0.00 58.00
% 20.69 13.79 17.24 10.34 10.34 10.34 5.17 3.45 8.62 0.00
Adviisor 7.00 7.00 5.00 5.00 4.00 1.00 2.00 3.00 1.00 1.00 36.00
% 19.44 19.44 13.89 13.89 11.11 2.78 5.56 8.33 2.78 2.78
Reseller plus advisor 19.00 15.00 15.00 11.00 10.00 7.00 5.00 5.00 6.00 1.00 94.00
% 20.21 15.96 15.96 11.70 10.64 7.45 5.32 5.32 6.38 1.06
Other 13.00 7.00 6.00 4.00 4.00 3.00 3.00 3.00 4.00 5.00 52.00
% 25.00 13.46 11.54 7.69 7.69 5.77 5.77 5.77 7.69 9.62
Total 67.00 53.00 46.00 25.00 25.00 22.00 16.00 14.00 10.00 11.00
% 23.18 18.34 15.92 8.65 8.65 7.61 5.54 4.84 3.46 3.81
More
than
one
answer
184
Questi
on 5 Insecticides for chewing insects.
Pyrethr
oids
Succes
s®,
Entrust
®
Proclai
m®
Regent
®
OPs -
Organ
ophos
phates
Bt
Secure
®
Avatar
®
Corage
n®,
Belt® Other Total
Grower 14 30 18 10 9 15 17 23 5 141.00
% 9.93 21.28 12.77 7.09 6.38 10.64 12.06 16.31 3.55
Researcher0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 na
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Reseller 5.00 10.00 10.00 7.00 4.00 9.00 7.00 9.00 2.00 63.00
% 7.94 15.87 15.87 11.11 6.35 14.29 11.11 14.29 3.17
Adviisor 1.00 4.00 4.00 3.00 1.00 5.00 3.00 5.00 2.00 28.00
% 3.57 14.29 14.29 10.71 3.57 17.86 10.71 17.86 7.14
Reseller plus advisor 6.00 14.00 14.00 10.00 5.00 14.00 10.00 14.00 4.00 91.00
% 6.59 15.38 15.38 10.99 5.49 15.38 10.99 15.38 4.40
Other 7.00 8.00 6.00 5.00 4.00 5.00 0.00 1.00 3.00 39.00
% 17.95 20.51 15.38 12.82 10.26 12.82 0.00 2.56 7.69
Total 27.00 52.00 38.00 25.00 18.00 34.00 27.00 38.00 12.00
% 9.96 19.19 14.02 9.23 6.64 12.55 9.96 14.02 4.43
Questi
on 6 Insecticides for sucking insects
Pirimo
r®
Chess
®
Confid
or ®
endos
ulphan
OPs
Organ
ophos
phates
Pyrethr
oids Other Total
Grower 20.00 9.00 12.00 1.00 3.00 5.00 8.00 58.00
% 34.48 15.52 20.69 1.72 5.17 8.62 13.79
Researcher0.00 0.00 0.00 0.00 0.00 0.00 0.00 na
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Reseller 10.00 8.00 9.00 0.00 5.00 4.00 2.00 38.00
% 26.32 21.05 23.68 0.00 13.16 10.53 5.26
Adviisor 6.00 3.00 4.00 0.00 1.00 0.00 0.00 14.00
% 42.86 21.43 28.57 0.00 7.14 0.00 0.00
Reseller plus advisor 16.00 11.00 13.00 0.00 6.00 4.00 2.00 52.00
% 30.77 21.15 25.00 0.00 11.54 7.69 3.85 100.00
Other 7.00 3.00 7.00 2.00 1.00 4.00 3.00 27.00
% 25.93 11.11 25.93 7.41 3.70 14.81 11.11
Total 43.00 23.00 32.00 3.00 10.00 13.00 13.00
% 14.88 16.79 23.36 1.59 7.30 9.49 6.88
Questi
on 7 Insect ID
Grower 29.00 7.00 36.00
%
Researcher5.00 0.00 5.00
%
Reseller 11.00 0.00 11.00
%
Adviisor 9.00 1.00 10.00
Reseller plus advisor 20.00 1.00 21.00 21.00
% 95.24 4.76
Other 16.00 1.00 17.00
Total 70.00 9.00 79.00 79.00
% 88.61 11.39
More
than
one
answer
More
than
one
answer
185
Questi
on 8 How often do you use/ refer to the IRM strategy chart
Every
month
or so
Once a
year
What is
it ? Never Total
Grower 18.00 5.00 2.00 8.00 33.00
% 54.55 15.15 6.06 24.24
Researcher0.00 0.00 0.00 0.00 0.00
% 0.00 0.00 0.00 0.00
Reseller 3.00 5.00 0.00 5.00 13.00
% 23.08 38.46 0.00 38.46
Adviisor 1.00 4.00 2.00 3.00 10.00
% 10.00 40.00 20.00 30.00
Reseller plus advisor 4.00 9.00 2.00 8.00 23.00
% 17.39 39.13 8.70 34.78
Other 4.00 4.00 1.00 8.00 17.00
% 23.53 23.53 5.88 47.06
Total 26.00 18.00 5.00 24.00
% 27.08 24.66 6.85 32.88
Questi
on 9 Practise of IPM
Low
Quite
low
Mediu
m High
Very
high Total
Grower 1.00 2.00 13.00 16.00 4.00 36.00
% 2.78 5.56 36.11 44.44 11.11
Researcher0.00 0.00 0.00 0.00 0.00 0.00
% 0.00 0.00 0.00 0.00 0.00
Reseller 1.00 0.00 2.00 7.00 3.00 13.00
% 7.69 0.00 15.38 53.85 23.08
Adviisor 0.00 0.00 3.00 9.00 0.00 12.00
% 0.00 0.00 25.00 75.00 0.00
Reseller plus advisor 1.00 0.00 5.00 16.00 3.00 25.00
% 4.00 0.00 20.00 64.00 12.00
Other 2.00 1.00 6.00 3.00 2.00 14.00
% 14.29 7.14 42.86 21.43 14.29
Total 4.00 3.00 24.00 35.00 9.00
% 5.33 4.00 32.00 46.67 12.00
Questi
on 10
What
tools
or info
do you
use
before
sprayin
g
Pestici
de
toxicity
chart
Your
own
knowle
dge
and
experie
nce
Electro
nic
scouti
ng tool
Inform
ation
on
insecti
cide
labels
Regula
r crop
scouti
ng
Record
and
review
pest
numbe
rs
regular
ly
Pest
develo
pment
calcula
tor
Other
grower
s
Agrono
mists
reselle
rs Other Total
Grower 11.00 26.00 0.00 21.00 29.00 6.00 1.00 6.00 10.00 1.00 111.00
% 9.91 23.42 0.00 18.92 26.13 5.41 0.90 5.41 9.01 0.90
Researcher0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Reseller 26.24 53.42 32.00 86.59 67.13 11.41 1.90 11.41 19.01 1.90 111.00
% 23.64 48.13 28.83 78.01 60.47 10.28 1.71 10.28 17.13 1.71
Adviisor 4.00 7.00 0.00 8.00 5.00 3.00 0.00 0.00 4.00 0.00 31.00
% 12.90 22.58 0.00 25.81 16.13 9.68 0.00 0.00 12.90 0.00
Reseller plus advisor 30.24 60.42 32.00 94.59 72.13 14.41 1.90 11.41 23.01 1.90 142.00
% 21.30 42.55 22.54 66.61 50.79 10.14 1.34 8.03 16.20 1.34
Other 2.00 10.00 0.00 8.00 12.00 6.00 0.00 1.00 2.00 1.00 42.00
% 4.76 23.81 0.00 19.05 28.57 14.29 0.00 2.38 4.76 2.38
Total 43.24 96.42 32.00 123.59 113.13 26.41 2.90 18.41 35.01 3.90
% 8.74 19.48 6.46 24.97 22.85 5.33 0.59 3.72 7.07 0.79
More
than
one
answer
186
What
would
encour
age
you to
use
IPM
more
often
Marketi
ng
incentiv
es
Nationa
l quality
standar
d -
audited
process
Increasi
ng the
reliabilit
y of
IPM
Increas
ed
enforce
ment of
minimu
m
residue
levels
More
time
More
informa
tion other Total
Questi
on 11 Grower 9.00 8.00 25.00 7.00 8.00 4.00 0.00 61.00
% 14.75 13.11 40.98 11.48 13.11 6.56 0.00
Researcher0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Reseller 5.00 4.00 5.00 7.00 4.00 4.00 0.00 29.00
%
Adviisor 3.00 1.00 6.00 2.00 1.00 2.00 1.00 16.00
%
Reseller plus advisor 8.00 5.00 11.00 9.00 5.00 6.00 1.00 45.00
% 17.78 11.11 24.44 20.00 11.11 13.33 2.22
Other 8.00 5.00 9.00 6.00 3.00 3.00 2.00 36.00
% 22.22 13.89 25.00 16.67 8.33 8.33 5.56
Total 25.00 18.00 45.00 22.00 16.00 13.00 3.00
% 17.61 12.68 31.69 15.49 11.27 9.15 2.11
What
would
you like
to
better
underst
and re
IPM
How
IPM
works
DBM
control
in
relation
with
other
pest
and
Crop
monitor
ing
Pest
and
benefici
al
insect
identific
ation
Insectic
ide
resistan
ce
manag
ement
Improvi
ng
natural
enemy
number
s
Using
product
s of low
toxicity
to
benefici
als
Optimal
sprayin
g
techniq
ues
Accessi
ng an
IPM
consult
ant Other Total
Questi
on 12 Grower 1.00 11.00 10.00 11.00 10.00 16.00 8.00 11.00 1.00 0.00 79.00
% 1.27 13.92 12.66 13.92 12.66 20.25 10.13 13.92 1.27 0.00
Researcher0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
% 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Reseller 0.00 4.00 3.00 5.00 2.00 4.00 4.00 6.00 2.00 0.00 30.00
% 0.00 13.33 10.00 16.67 6.67 13.33 13.33 20.00 6.67 0.00
Adviisor 1.00 4.00 4.00 5.00 3.00 5.00 2.00 2.00 1.00 0.00 27.00
% 3.70 14.81 14.81 18.52 11.11 18.52 7.41 7.41 3.70 0.00
Reseller plus advisor 1.00 8.00 7.00 10.00 5.00 9.00 6.00 8.00 3.00 0.00 57.00
% 1.75 14.04 12.28 17.54 8.77 15.79 10.53 14.04 5.26 0.00
Other 4.00 5.00 4.00 7.00 4.00 4.00 5.00 2.00 3.00 2.00 40.00
% 10.00 12.50 10.00 17.50 10.00 10.00 12.50 5.00 7.50
Total 6.00 24.00 21.00 28.00 19.00 29.00 19.00 21.00 7.00 2.00
% 3.41 13.64 11.93 15.91 10.80 16.48 10.80 11.93 3.98
More
than
one
answer
More
than
one
answer
187
Questi
on 13
Was
info
from
meetin
g
Strongl
y Agree Agree Neutral
Disagre
e
Strongl
y
Disagre
e Total
Grower 12.00 22.00 1.00 0.00 0.00 35.00
% 34.29 62.86 2.86 0.00 0.00
Researcher
%
Reseller 0.00 13.00 0.00 0.00 0.00 13.00
% 0.00 100.00 0.00 0.00 0.00
Adviisor 2.00 6.00 1.00 0.00 1.00 10.00
% 20.00 60.00 10.00 0.00 10.00
Reseller plus advisor 2.00 19.00 1.00 0.00 1.00 23.00
% 8.70 82.61 4.35 0.00 4.35
Other 4.00 11.00 1.00 0.00 1.00 17.00
% 23.53 64.71 5.88 0.00 5.88
Total 18.00 52.00 3.00 0.00 2.00
% 24.00 69.33 4.00 0.00 2.67
188
Appendix 4.4
189
Appendix 4.5
