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Title: MODELLING THE COMPONENTS OF LIVESTOCK STRESS FOR PRECISION ANIMAL MANAGEMENT

Author
item Brown-Brandl, Tami
item JONES, D - UNIV NEBRASKA, LINCOLN
item GAUGHAN, J - UNIV QUEENSLAND, AUSTRALI

Submitted to: American Society of Agri Engineers Special Meetings and Conferences Papers
Publication Type: Other
Publication Acceptance Date: 6/16/2006
Publication Date: 7/9/2006
Citation: Brown Brandl, T.M., Jones, D.D., Gaughan, J.B. 2006. Modelling the components of livestock stress for precision animal management. American Society of Agri Engineers Special Meetings and Conferences Papers. Paper No. 064204

Interpretive Summary: Animal stress originates from a combination of three areas: weather, the animal itself, and the physical surroundings (pen). A model is under development to predict the animal stress level based on these three factors. This paper details the development of just one of the factors—the animal's own characteristics. The paper provides details on the type of model chosen, the development of the model, and the initial testing of animal's characteristics as part of predicted response.

Technical Abstract: An individual animal’s stress level is the summation of stresses from three areas: the environment, animal, and management. A model is being developed to summarize components of each of these three areas to determine the overall stress on the animal. The purpose of the model will be three-fold. First, the animal component will be used to identify animals at high risk for suffering from heat stress. This would allow producers to sort these animals and provide them with extra care. Second, the model could be used to monitor weather events to indicate extreme weather, so precautions could be taken. Third, producers could investigate different management strategies and impacts on stress. All three components could be used in conjunction to investigate management strategies under different weather events on animals with different risk factors. This paper documents the first component of the model—animal susceptibility. The details provided explain the type of model, method of integrating a prediction of ambiguity associated with each prediction made, and an initial validation of the animal susceptibility model.