Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
REVIEW

ASKBILL as a web-based program to enhance sheep well-being and productivity

L. P. Kahn A B D , I. R. Johnson A B , J. B. Rowe A , L. Hogan A and J. Boshoff A C
+ Author Affiliations
- Author Affiliations

A Cooperative Research Centre for Sheep Industry Innovation, Armidale, NSW 2351, Australia.

B School of Environmental and Rural Science, University of New England, NSW 2351, Australia.

C School of Science and Technology, University of New England, NSW 2351, Australia.

D Corresponding author. Email: lkahn3@une.edu.au

Animal Production Science 57(11) 2257-2262 https://doi.org/10.1071/AN17327
Submitted: 15 May 2017  Accepted: 31 July 2017   Published: 30 August 2017

Abstract

ASKBILL is a web-based program that uses farm measurements, climate data and information on genetics to predict pasture growth, animal performance and animal health and climate risks. The program uses several biophysical models, which are customised by user inputs, localised daily weather updates and a dynamical probabilistic 90-day climate forecast to enhance sheep well-being and productivity. This approach can minimise the requirement for manual, auto and remote measurements, thus reducing labour requirements and complexity. In this article, the animal growth model provides an example of a biophysical model used to provide predictions. This is an energy-based model and the model parameterisation is designed to be physiologically meaningful and able to be customised for the genetic merit of the animal using a growth coefficient that calibrates growth of body components and energy requirements. A key feature of the animal growth model is its forecast projections, which are based on an ensemble of simulations. The model can estimate supplementary feeding rates required to achieve target liveweights and body condition scores and stocking rates required to achieve target pasture levels. The model can be customised for a farm and its livestock and is updated daily in response to climate data. This dynamic feature enables it to provide early stage alerts to users when animal production targets are unlikely to be met.

Additional keywords: animal growth, climate, forecast, simulation model.


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