The aim of this study was to identify a set of feeding behaviour and activity related variables that could potentially detect a shortage of available feed for the individual cow on pasture. A group of lactating cows was offered 100% of their intake capacity as herbage allowance throughout a 10-week experimental period, while another group was offered 60% of their intake allowance, either for a two week or six week period in springtime. Each cow was equipped with an automated noseband sensor. The data were analysed by using a binomial generalized lineal model (GLM). The GLM was examined for the classification of full or restricted herbage allowance as a function of a previously identified set of characteristics. The model was further refined by including additional characteristics, which achieved higher prediction performance. For the combined data, the refined model achieved 77% accuracy, 75% sensitivity, 78% specificity and F-score 0.76 towards a decision support system for grass utilisation in pasture based milk production.
Modelling restricted feeding conditions on cows’ feeding behaviour on pasture-based milk production systems to develop a Decision Support System / A. Shafiullah, J. Werner, E. Kennedy, L. Leso, B. O’ Brien, C. Umstätter. - ELETTRONICO. - (2019), pp. 152-158. (Intervento presentato al convegno Precision Livestock Farming ’19).
Modelling restricted feeding conditions on cows’ feeding behaviour on pasture-based milk production systems to develop a Decision Support System
L. LesoInvestigation
;
2019
Abstract
The aim of this study was to identify a set of feeding behaviour and activity related variables that could potentially detect a shortage of available feed for the individual cow on pasture. A group of lactating cows was offered 100% of their intake capacity as herbage allowance throughout a 10-week experimental period, while another group was offered 60% of their intake allowance, either for a two week or six week period in springtime. Each cow was equipped with an automated noseband sensor. The data were analysed by using a binomial generalized lineal model (GLM). The GLM was examined for the classification of full or restricted herbage allowance as a function of a previously identified set of characteristics. The model was further refined by including additional characteristics, which achieved higher prediction performance. For the combined data, the refined model achieved 77% accuracy, 75% sensitivity, 78% specificity and F-score 0.76 towards a decision support system for grass utilisation in pasture based milk production.File | Dimensione | Formato | |
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ECPLF19_Modelling restricted feeding conditions on cows' feeding behaviour on pasture.pdf
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