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Monitoring resistance to phosphine in the lesser grain borer, Rhyzopertha dominica, in Australia: A national analysis of trends, storage types and geography in relation to resistance detections

Collins, Patrick J. and Falk, Matthew G. and Nayak, Manoj K. and Emery, Robert N. and Holloway, Joanne C. (2017) Monitoring resistance to phosphine in the lesser grain borer, Rhyzopertha dominica, in Australia: A national analysis of trends, storage types and geography in relation to resistance detections. Journal of Stored Products Research, 70 . pp. 25-36. ISSN 0022-474X

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Article Link(s): http://dx.doi.org/10.1016/j.jspr.2016.10.006

Publisher URL: http://www.sciencedirect.com/science/article/pii/S0022474X1630282X

Abstract

Data on incidence of resistance to phosphine over the last 20 years and factors associated with insect sample collection are stored in the Australian Grain Insect Resistance Database. The database was analysed using descriptive statistics, linear trend analysis and Bayesian hurdle modelling to gain insights into factors contributing to the development of strong resistance in Rhyzopertha dominica. Descriptive statistics indicated that strong resistance was significantly more common in central storages, particularly bunker storages, than on farms. Strong resistance in R. dominica was also associated with wheat, barley and sorghum but there was no significant link to any grain protectant or storage treatment chemical, other than phosphine. Highest frequency of strong resistance was found in northern New South Wales and no detections were made in Western Australia. In eastern Australia, trend analysis indicated that strong resistance detections increased steadily from the first detection in 1997 to about 8% of samples containing resistant insects in 2014. Weak resistance was detected in about 10% of samples in eastern Australia in the early 1990s but this increased rapidly to 40–50% by 1990, at the same time that industry use of phosphine greatly increased, and then to about 80% in 1995. Strong resistance was first detected in this species when weak resistance was diagnosed in close to 80% of population samples. The Bayesian hurdle model identified bunkers, silos and unsealed storages as being associated with development of strong resistance and sheds with a lower frequency. This model also identified an accelerated increase in resistance frequency of strong resistance from 2011 to present. The information gained from this analysis is being used to inform current and future management of resistance to phosphine.

Item Type:Article
Business groups:Crop and Food Science
Keywords:Phosphine resistance Insects Bayesian Monitoring Survey
Subjects:Science > Entomology
Plant culture > Field crops > Grain. Cereals
Plant pests and diseases
Deposited On:18 Jan 2017 23:44
Last Modified:18 Jan 2017 23:44

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