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
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Antonio Leandro Chaves Gurgel: Campus Professora Cinobelina Elvas, Federal University of Piauí, Bom Jesus 64900-000, Piauí, Brazil
Geraldo Tadeu dos Santos: Department of Animal Science, State University of Maringá, Maringá 87020-900, Paraná, Brazil
Luís Carlos Vinhas Ítavo: College of Veterinary Medicine and Animal Science, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Mato Grosso do Sul, Brazil
Camila Celeste Brandão Ferreira Ítavo: College of Veterinary Medicine and Animal Science, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Mato Grosso do Sul, Brazil
Gelson dos Santos Difante: College of Veterinary Medicine and Animal Science, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Mato Grosso do Sul, Brazil
Alexandre Menezes Dias: College of Veterinary Medicine and Animal Science, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Mato Grosso do Sul, Brazil
Vanessa Zirondi Longhini: College of Veterinary Medicine and Animal Science, Federal University of Mato Grosso do Sul, Campo Grande 79070-900, Mato Grosso do Sul, Brazil
Tairon Pannunzio Dias-Silva: Campus Professora Cinobelina Elvas, Federal University of Piauí, Bom Jesus 64900-000, Piauí, Brazil
Marcos Jácome de Araújo: Campus Professora Cinobelina Elvas, Federal University of Piauí, Bom Jesus 64900-000, Piauí, Brazil
João Virgínio Emerenciano Neto: Academic Unit Specialized in Agricultural Sciences, Federal University of Rio Grande do Norte, Macaíba 59280-000, Rio Grande do Norte, Brazil
Patrick Bezerra Fernandes: Goiás Federal Institute, Campus Rio Verde, Rio Verde 75901-970, Goiás, Brazil
Alfonso Juventino Chay-Canul: División Académica de Ciencias Agropecuarias, Universidad Juárez Autónoma de Tabasco, Villahermosa 86298, Tabasco, México

Agriculture, 2023, vol. 13, issue 7, 1-11

Abstract: 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 (r 2 ) 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 (r 2 = 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 (r 2 = 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.

Keywords: fat; intake; milk composition; milk yield; milk urea nitrogen; protein (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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