Guided classification measurement of body condition in beef cows

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 p...

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Main Authors: Ana Carolina Espasandin, Andrea Gimena Larracharte Cardoso, Nicolás Pérez López
Format: Article
Language:English
Published: Universidad de la República, Facultad de Agronomía 2023-08-01
Series:Agrociencia Uruguay
Subjects:
Online Access:https://doi.org/10.31285/AGRO.27.1165
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author Ana Carolina Espasandin
Andrea Gimena Larracharte Cardoso
Nicolás Pérez López
author_facet Ana Carolina Espasandin
Andrea Gimena Larracharte Cardoso
Nicolás Pérez López
author_sort Ana Carolina Espasandin
collection DOAJ
description 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.
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spelling doaj.art-96d42ee7ca364a4087b24c18e8d2afb12023-09-02T13:23:17ZengUniversidad de la República, Facultad de AgronomíaAgrociencia Uruguay2730-50662023-08-0127e116510.31285/AGRO.27.1165Guided classification measurement of body condition in beef cowsAna Carolina Espasandin0https://orcid.org/0000-0003-2233-4290Andrea Gimena Larracharte Cardoso1https://orcid.org/0000-0002-3934-1078Nicolás Pérez López2https://orcid.org/0000-0002-8043-5383Universidad de la República, Facultad de Agronomía, Montevideo, UruguayUniversidad de la República, Facultad de Agronomía, Montevideo, UruguayUniversidad de la República, Facultad de Ingeniería, Montevideo, UruguayThe 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.https://doi.org/10.31285/AGRO.27.1165body condition scoredigital imagingbeef cattleinformation technology
spellingShingle Ana Carolina Espasandin
Andrea Gimena Larracharte Cardoso
Nicolás Pérez López
Guided classification measurement of body condition in beef cows
Agrociencia Uruguay
body condition score
digital imaging
beef cattle
information technology
title Guided classification measurement of body condition in beef cows
title_full Guided classification measurement of body condition in beef cows
title_fullStr Guided classification measurement of body condition in beef cows
title_full_unstemmed Guided classification measurement of body condition in beef cows
title_short Guided classification measurement of body condition in beef cows
title_sort guided classification measurement of body condition in beef cows
topic body condition score
digital imaging
beef cattle
information technology
url https://doi.org/10.31285/AGRO.27.1165
work_keys_str_mv AT anacarolinaespasandin guidedclassificationmeasurementofbodyconditioninbeefcows
AT andreagimenalarrachartecardoso guidedclassificationmeasurementofbodyconditioninbeefcows
AT nicolasperezlopez guidedclassificationmeasurementofbodyconditioninbeefcows