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

Horton, B. J., Evans, D. L., James, P. J. and Campbell, N. J. (2009) Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing. Animal Production Science, 49 1: 48-55.


Author Horton, B. J.
Evans, D. L.
James, P. J.
Campbell, N. J.
Title Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing
Journal name Animal Production Science   Check publisher's open access policy
ISSN 1836-5787
1836-5787
Publication date 2009
Sub-type Article (original research)
DOI 10.1071/EA07179
Volume 49
Issue 1
Start page 48
End page 55
Total pages 8
Place of publication Collingwood, Vic., Australia
Publisher CSIRO Publishing
Language eng
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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
 
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