Feed conversion ratio (FCR) and performance group estimation based on predicted feed intake for the optimisation of beef production
Davison, C. and Michie, C. and Tachtatzis, C. and Andonovic, I. and Bowen, J. M. and Duthie, C-A. (2023) Feed conversion ratio (FCR) and performance group estimation based on predicted feed intake for the optimisation of beef production. Sensors. ISSN 1424-8220 (In Press)
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Abstract
This paper reports on the use of estimates of individual animal feed intake (made using time spent feeding measurements) to predict the feed conversion ratio (FCR), a measure of the amount of feed consumed to produce 1 kg of body mass, for an individual animal. Reported research to date has evaluated the ability of statistical methods to predict daily feed intake based on measurements of time spent feeding measured using electronic feeding systems. The study collated data of the time spent eating for 80 beef animals over a 56-day period as the basis for the prediction of feed intake. A Support Vector Regression (SVR) model was trained to predict feed intake and the performance of the approach was quantified. Here feed intake predictions are used to estimate individual FCR and use this information to categorise animals into three groups based on the estimated Feed Conversion Ratio value. Results provide evidence of the feasibility of utilising the 'time spent eating' data to estimate feed intake and in turn Feed Conversion Ratio (FCR), the latter providing insight that guide farmer decisions on the optimisation of production costs.
ORCID iDs
Davison, C.


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Item type: Article ID code: 85430 Dates: DateEvent4 May 2023Published4 May 2023AcceptedKeywords: feed intake estimation, feed conversion ratio, beef production, precision livestock farming, machine learning, Electrical Engineering. Electronics Nuclear Engineering, Biochemistry, Atomic and Molecular Physics, and Optics, Analytical Chemistry, Electrical and Electronic Engineering Subjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > Measurement Science and Enabling TechnologiesDepositing user: Pure Administrator Date deposited: 10 May 2023 09:52 Last modified: 10 May 2023 09:52 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/85430