Forage intake is the most important factor for beef cattle raised on pasture, as it is the basis of the diet. Thus, knowing the variables that affect this parameter can help supplementation programs. Thus, a meta-analytic study was conducted to develop and evaluate models for the prediction of pasture dry matter intake (DMIpasture) by beef cattle in tropical conditions. Eight hundred four individual observations of DMIpasture were used, taken from 23 studies through analysis of mixed models, including the study as a random effect. To evaluate the accuracy and precision of the new models proposed as well as for the models of Azevedo et al. (2016) and Minson and McDonald (1987), an independent databank with 87 means from treatments of 21 experiments (n = 888 animals) was used. Three prediction models were adjusted: model I (animal information), model II (animal information + supplement), and model III (animal information + supplement + pasture). The proposed models presented similarity for the average square root of the prediction error. The inclusion of the predictive variables for supplementation (supplement dry matter intake - DMIsupplement - % of the body weight and crude protein intake through supplement) with the variables for the animal (BW0.75 and average daily gain) and of the pasture (% of crude protein) in model III improved accuracy and precision and provided higher determination and correlation coefficients, and agreement than the other proposed models. Similarly, it was found to be more accurate and precise than the equations of Azevêdo et al. (2016) and Minson and McDonald (1987), which presented lower precision. The DMIpasture for beef cattle in tropical conditions is more accurate and precise when the information for the animal, supplement, and pasture is included.
Keywords: Meta-analysis; Modeling; Supplementation; Tropical pasture.
© 2021. The Author(s), under exclusive licence to Springer Nature B.V.