Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/95093
Type: Thesis
Title: Meta-barcoding for assessment of risks posed by genetically modified crops to farmland arthropods.
Author: Akankunda, Trace
Issue Date: 2015
School/Discipline: School of Agriculture, Food and Wine
Abstract: The rate of adoption of genetically modified (GM) crops continues to grow at unprecedented rates 19 years after their first commercialisation. As global coverage of GM crops increases, concerns about their potential effects on the environment and specifically agro-ecosystem health intensify. To address these concerns, researchers have called for increased monitoring of agro-ecosystems to detect unforeseen adverse effects of GM crops. To date, only Europe has a statutory requirement for developers of GM products to conduct post market environmental monitoring (PMEM) in order to assess potential risks associated with their products. This might be due to lack of robust and cost effective methods for conducting PMEM. Here we propose the use of a modified meta-barcoding pipeline on an Illumina MiSeq platform as a comprehensive and cost effective approach for conducting PMEM on farmland arthropod communities. We test the method’s capacity to generate baseline data on a selection of indicator arthropod groups following guidelines issued by the European Food Safety Authority (EFSA). We use arthropod communities of coffee plantations in the south and south-western regions of Uganda as an exemplar for the approach. We modify the sample preparation steps of the meta-barcoding pipeline to reduce sequencing cost and successfully adapt the MiSeq Reporter program to classify arthropods using COI sequence reads produced by the MiSeq. We compile baseline data on the diversity and distribution s of six generalist predators, two parasitoids, two pollinators, four common pests and three herbivores of the coffee crop system using incidence counts. We demonstrate the method’s capacity to monitor arthropod communities at the genus and species level and discuss the application of the baseline data collected for GM risk assessment.
Advisor: Keller, Michael Anthony
Dissertation Note: Thesis (M.Bio.(PB)) -- University of Adelaide, Masters of Biotechnology (Plant Biotechnology), School of Agriculture, Food and Wine, 2015
Keywords: coursework; genetically modified crops (GM); farmland arthropods; GM risk assessment; Meta-barcoding
Provenance: [Masters of Biotechnology (Plant Biotechnology)] by coursework
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