Stewart Postharvest Review

An international journal for reviews in postharvest biology and technology

© 2011 Stewart Postharvest Solutions (UK) Ltd.                                                                                                  

Online ISSN:1945-9656

www.stewartpostharvest.com                                        

                                                                                                                                                                                                                                      Online ISSN:1945-9656

www.stewartpostharvest.com  © 2005 Stewart Postharvest Solutions (UK) Ltd.

 All Rights Reserved 1

 

Insect distributions and sampling protocols for stored commodities

 

 

 

Grant Hamilton1,2* and David Elmouttie1,2

1Cooperative Research Centre for National Plant Biosecurity, Bruce, Australia

2Discipline of Biogeosciences, Queensland University of Technology, Brisbane, Queensland, Australia

 

 

 

Abstract

Purpose of review: This review provides an overview on the importance of characterising and considering insect distribution information for designing stored commodity sampling protocols.

Findings: Sampling protocols are influenced by a number of factors including government regulations, management practices, new technology and current perceptions of the status of insect pest damage. The spatial distribution of insects in stored commodities influences the efficiency of sampling protocols; these can vary in response to season, treatment and other factors. It is important to use sampling designs based on robust statistics suitable for the purpose.

Future research: The development of sampling protocols based on flexible, robust statistics allows for accuracy across a range of spatial distributions. Additionally, power can be added to sampling protocols through the integration of external information such as treatment history and climate. Bayesian analysis provides a coherent and well understood means to achieve this.

 

Keywords: statistical model; grains; pests; detection; abundance estimation; statistical distribution

 

*Correspondence to: Grant Hamilton, Discipline of Biogeosciences, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, Australia, 4001. Phone: + 61 7 3138 1325 ; Fax: + 61 7 3138 1535; email: g.hamilton@qut.edu.au

 

Stewart Postharvest Review 2011, 3:2

Published online 01 December 2011

doi: 10.2212/spr.2011.3.2