Abstract

ESPASANDIN, A. C.; LARRACHARTE CARDOSO, A.  and  PEREZ, N.. Guided classification measurement of body condition in beef cows. Agrocienc. Urug. [online]. 2023, vol.27, e1165.  Epub Dec 01, 2023. ISSN 2730-5066.  https://doi.org/10.31285/agro.27.1165.

The use of predictive techniques based on image acquisition at field level is presented to improve livestock production. With this, the farmer can plan the management of the herd and the need for supplemental feeding. The use of the Body Condition Score (BCS) measured by visual assessment has been proposed as a method of subjective evaluation of the nutritional status of cattle. Studies show that a good BCS at calving allows increases in the order of 10 to 15% in the following pregnancy rate of the herd. This increase has a significant impact on farm productivity. Although the benefits of the visual assessment scale are recognized, the percentage of breeders using this tool is still low, the main reason being the lack of trained raters to record the BCS. The objective of this study was to develop a practical, repetitive, and non-invasive method to evaluate BCS through a guided grading process using images taken in the field. The results show that the BCS determination method proposed in this paper is presented as a simple and economical tool to evaluate BCS, so that it can be accepted by the breeder for its simplicity and benefits. Additionally, it can serve as a tutorial for the acquisition of experience in calibrating BCS in breeding cows.

Keywords : body condition score; digital imaging; beef cattle; information technology.

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