A review of current statistical methodologies for in storage sampling and surveillance in the grains industry

Elmouttie, David, Hammond, Nicole Elana, & Hamilton, Grant S. (2013) A review of current statistical methodologies for in storage sampling and surveillance in the grains industry. Bulletin of Entomological Research, 103(02), pp. 140-147.

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Effective, statistically robust sampling and surveillance strategies form an integral component of large agricultural industries such as the grains industry. Intensive in-storage sampling is essential for pest detection, Integrated Pest Management (IPM), to determine grain quality and to satisfy importing nation’s biosecurity concerns, while surveillance over broad geographic regions ensures that biosecurity risks can be excluded, monitored, eradicated or contained within an area. In the grains industry, a number of qualitative and quantitative methodologies for surveillance and in-storage sampling have been considered. Primarily, research has focussed on developing statistical methodologies for in storage sampling strategies concentrating on detection of pest insects within a grain bulk, however, the need for effective and statistically defensible surveillance strategies has also been recognised. Interestingly, although surveillance and in storage sampling have typically been considered independently, many techniques and concepts are common between the two fields of research. This review aims to consider the development of statistically based in storage sampling and surveillance strategies and to identify methods that may be useful for both surveillance and in storage sampling. We discuss the utility of new quantitative and qualitative approaches, such as Bayesian statistics, fault trees and more traditional probabilistic methods and show how these methods may be used in both surveillance and in storage sampling systems.

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ID Code: 53160
Item Type: Journal Article
Refereed: Yes
Keywords: Grains, Sampling, Surveillance, Detection, Pests, IPM, Surveys
DOI: 10.1017/S0007485312000624
ISSN: 0007-4853
Divisions: Current > Schools > School of Earth, Environmental & Biological Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Cambridge University Press
Deposited On: 16 Aug 2012 23:44
Last Modified: 18 Oct 2013 08:22

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