Prediction models of intake and productive performance of non-castrated Nellore cattle finished in the feedlot system under tropical conditions

Moura, Jessika Rodrigues de Figueiredo; Ítavo, Luís Carlos Vinhas; Ítavo, Camila Celeste Brandão Ferreira; Dias, Alexandre Menezes; Difante, Gelson dos Santos; Santos, Geraldo Tadeu dos; Gurgel, Antônio Leandro Chaves; Chay-Canúl, Alfonso Juventino

doi:10.1007/s11250-023-03488-5

Cited by 4 publications

(1 citation statement)

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“…The relationship between animal weight and DMI is well documented, as an animal's requirements increase in response to an increase in BW [43]. This relationship has been reported in various species, such as sheep [18,44,45], beef cattle [20,41,46], and dairy cattle [40]. Previous studies have used BW and/or BW 0.75 or empty body weight to predict DMI, and these variables have been shown to be significant predictors of nutrient intake.…”

Section: Discussionmentioning

confidence: 93%

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

et al. 2023

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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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