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Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing

Citation

Horton, BJ and Evans, DL and James, PJ and Campbell, NJ, Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing, Animal Production Science, 49, (1) pp. 48-55. ISSN 1836-5787 (2009) [Refereed Article]

DOI: doi:10.1071/EA07179

Abstract

This paper describes the development of a model, based on Bayesian networks, to estimate the likelihood that sheep flocks are infested with lice at shearing and to assist farm managers or advisers to assess whether or not to apply a lousicide treatment. The risk of lice comes from three main sources: (i) lice may have been present at the previous shearing and not eradicated; (ii) lice may have been introduced with purchased sheep; and (iii) lice may have entered with strays. A Bayesian network is used to assess the probability of each of these events independently and combine them for an overall assessment. Rubbing is a common indicator of lice but there are other causes too. If rubbing has been observed, an additional Bayesian network is used to assess the probability that lice are the cause. The presence or absence of rubbing and its possible cause are combined with these networks to improve the overall risk assessment. © CSIRO 2009.

Item Details

Item Type:Refereed Article
Research Division:Agricultural and Veterinary Sciences
Research Group:Animal Production
Research Field:Animal Protection (Pests and Pathogens)
Objective Division:Animal Production and Animal Primary Products
Objective Group:Livestock Raising
Objective Field:Sheep - Wool
UTAS Author:Horton, BJ (Dr Brian Horton)
ID Code:69687
Year Published:2009
Web of Science® Times Cited:9
Deposited By:Agricultural Science
Deposited On:2011-05-13
Last Modified:2011-09-20
Downloads:0

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