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Development of a model based on Bayesian networks to estimate the probability of sheep lice presence at shearing
journal contribution
posted on 2023-05-17, 06:08 authored by Brian HortonBrian Horton, Evans, DL, James, PJ, Campbell, NJThis 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.
History
Publication title
Animal Production ScienceVolume
49Pagination
48-55ISSN
1836-5787Department/School
Tasmanian Institute of Agriculture (TIA)Publisher
CSIRO PublishingPlace of publication
AustraliaRepository Status
- Restricted
Socio-economic Objectives
Sheep for woolUsage metrics
Keywords
Licence
Exports
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