The goal of this work was to determine the accuracy and utility of the Cornell Net Carbohydrate and Protein System (CNCPS) model to predict milk production from diets based on pasture and forage supplements. Data were obtained from studies in which pasture was complemented with contrasting silages including maize, pasture, sulla, lotus and forage mixtures, comprising 30-40% of dry matter intake (DMI). Twelve diets were used in this evaluation. DMI, live weight (LW), days in milk, and diet composition were determined during the trials and used as inputs in the model. Across all diets, a significant (P<0.01) relationship existed between predicted and actual values for DMI (r2=0.63), milk yield (r2=0.64) and LW change (r2=0.57) but there were still large unexplained sources of variation and the slopes of the regression lines were significantly (P<0.01) different than 1. No significant mean bias was observed for any of the variables, but the slope of residual differences against predicted values was significantly different from zero (P<0.01 for milk yield and LW change; P<0.06 for DMI). The results indicate a satisfactory prediction of milk production when cows are neither gaining nor losing weight, but that a systematic bias exists probably because of the CNCPS model’s failure to account for nutrient partitioning.
Proceedings of the New Zealand Society of Animal Production, Volume 63, Queenstown, 91-95, 2003
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