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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, NJ
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.

History

Publication title

Animal Production Science

Volume

49

Pagination

48-55

ISSN

1836-5787

Department/School

Tasmanian Institute of Agriculture (TIA)

Publisher

CSIRO Publishing

Place of publication

Australia

Repository Status

  • Restricted

Socio-economic Objectives

Sheep for wool

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