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Inicio  /  Agriculture  /  Vol: 13 Par: 7 (2023)  /  Artículo
ARTÍCULO
TITULO

Mathematical Models to Predict Dry Matter Intake and Milk Production by Dairy Cows Managed under Tropical Conditions

Antonio Leandro Chaves Gurgel    
Geraldo Tadeu dos Santos    
Luís Carlos Vinhas Ítavo    
Camila Celeste Brandão Ferreira Ítavo    
Gelson dos Santos Difante    
Alexandre Menezes Dias    
Vanessa Zirondi Longhini    
Tairon Pannunzio Dias-Silva    
Marcos Jácome de Araújo    
João Virgínio Emerenciano Neto    
Patrick Bezerra Fernandes and Alfonso Juventino Chay-Canul    

Resumen

This study aimed to create an equation to predict dry matter intake (DMI) and milk production and N-ureic in the milk of dairy cows managed in tropical conditions in Brazil. We used 113 observations from three experiments using lactating Jersey, Girolando, and Holstein cows. The goodness of fit of the developed equations was evaluated using the coefficients of determination (r2) and root mean square error (RMSE). There was a positive correlation between body weight and milk yield (MY) of r = 0.73. The equation considered DMI to be the most important variable to estimate the MY (r2 = 0.65). Four equations were adjusted to estimate the DMI, where, by a stepwise procedure, the first variable included in the equation was the neutral detergent fibre intake, which explained 92% of the DMI of the cows. However, when the variables BW, MY, and milk fat were included in the equation, there was a reduction of 0.06 in RMSE and an increase in precision (r2 = 0.94). The nutrient intake, milk production, and characteristics prediction equations present satisfactory precision and accuracy for dairy cows managed in tropical conditions in Brazil.

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