Body weight prediction in lambs

small sheep farmers in northern Argentina do not have scales and know the characteristics of the Santa Ines breed. With the objective to estimate equations for prediction body weight (BW) of lambs with different ages and from different genetics groups, were determinated biometric measures: thoraci...

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Autores principales: Flores Quintana, Carolina Isabel, Yáñez, Enrique Alejandro, Fernández, Juan Alfredo
Formato: Documento de conferencia
Lenguaje:Inglés
Publicado: Sociedade Brasileira de Zootecnia 2020
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Acceso en línea:http://repositorio.unne.edu.ar/handle/123456789/9167
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Sumario:small sheep farmers in northern Argentina do not have scales and know the characteristics of the Santa Ines breed. With the objective to estimate equations for prediction body weight (BW) of lambs with different ages and from different genetics groups, were determinated biometric measures: thoracic perimeter, anterior height, rump height and body length. Was recorded 581 BW and biometric data, making Pearson correlation analysis, simple regression and linear regression, calculating the BW with each body measurements and combined four, three and two biometric variables. The analysis was performed with total data and discriminated against by genetic group: wool animals, without wool and absorbent cross with Santa Inês: F1, F2 and F3. The four biometric measurements correlate with BW. In equation with four variables, rump height is the variable that least contributes to regression coefficient, and verified that the adjustment to remove body length only decreased by 1%. The combination of thoracic perimeter and anterior height has a setting of 90% in the total data, the biggest adjustment for genetic analysis group and has the highest proportion in the regression coefficient. In wool animals thoracic perimeter has lower anterior height setting, not so in the rest of the genetic groups, demonstrating the influence of wool in determining. Thoracic perimeter had the highest accuracy and easy execution for estimating body weight.