Field assessment of a BCS measuring device at timed AI in crossbread dairy cows of Amazonian smallholders.

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Author(s): PFEIFER, L. F. M.; BARBOSA, I. P.; PIONTE, P.; SIQUEIRA, L. G. B.

Summary: This study aimed to evaluate the efficiency of a body condition score (BCS) assessment device (BCAD) to identify cows with an adequate BCS and, presumably, a higher fertility when subjected to timed artificial insemination (TAI). We evaluated cows at smallholder dairy farms in the state of Rondonia, Brazil. Crossbred dairy cows (n = 141) were subjected to a TAI protocol and classified according to the BCAD scale as low BCS (red; n = 55) or adequate BCS (green; n = 86). The outcome pregnancy per artificial insemination (P/AI) was analyzed by logistic regression. Cows classified as green by the BCAD had a significantly greater P/AI (41 of 86; 47.7%) than cows classified as red (15 of 55; 27.3%; P = 0.01). In conclusion, the BCS assessment device was an effective tool to detect cows more likely to become pregnant due to their adequate BCS and, consequently, better fertility in TAI. Este estudo investigou a eficiência de um dispositivo avaliador de ECC (escore de condição corporal) (DAEC) para identificar vacas com ECC adequado e, presumivelmente, com fertilidade mais alta quando submetidas a protocolos de inseminação artificial em tempo-fixo (IATF). Conduzimos o estudo em pequenas propriedades leiteiras no estado de Rondônia, Brasil. Vacas leiteiras mestiças (n = 141) foram submetidas a um protocolo de IATF e classificadas de acordo com a escala do DAEC em vacas com ECC baixo (vermelho; n = 55) ou ECC adequado (verde; n = 86). A prenhez por inseminação artificial (P/IA) foi analisada por regressão logística. Vacas classificadas como verde no DAEC apresentaram P/IA significativamente mais alto (41 de 86; 47,7%) que vacas classificadas como vermelho (15 de 55; 27,3%; P = 0,01). Conclui-se que o dispositivo avaliador de ECC é uma ferramenta eficiente para detectar vacas com adequado ECC e com consequente maior fertilidade na IATF.

Publication year: 2023

Types of publication: Journal article

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