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

Published online by Cambridge University Press:  25 September 2012

D. Elmouttie ,
N.E.B. Hammond  and
G. Hamilton
D. Elmouttie
Affiliation:
Cooperative Research Centre for National Plant Biosecurity, LPO Box 5012, Bruce, ACT 2617, Australia Earth, Environmental and Biological Sciences, Science and Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia
N.E.B. Hammond
Affiliation:
Cooperative Research Centre for National Plant Biosecurity, LPO Box 5012, Bruce, ACT 2617, Australia School of Veterinary and Biomedical Sciences, Murdoch University, South Street, Murdoch, WA, 6150, Australia Department of Agriculture and Food, Locked Bag 4, Bentley Delivery Centre, WA, 6983, Australia
G. Hamilton*
Affiliation:
Cooperative Research Centre for National Plant Biosecurity, LPO Box 5012, Bruce, ACT 2617, Australia Earth, Environmental and Biological Sciences, Science and Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia
*
*Author for correspondence Fax: + 61 7 3138 1535 E-mail: [email protected]
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Abstract

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.

Keywords

grainssamplingsurveillancedetectionpestsIPMsurveys
Type
Research Paper
Information
Bulletin of Entomological Research , Volume 103 , Issue 2 , April 2013 , pp. 140 - 147
Copyright
Copyright © Cambridge University Press 2012

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