Evaluation of theGrazeIn model of grass dry‐matter intake and milk production prediction for dairy cows in temperate grass‐based production systems. 1–Sward characteristics and grazing management factors

Abstract

AbstractThis study evaluated the prediction accuracy of grass dry‐matter intake (GDMI) and milk yield predicted by the modelGrazeIn using a database representing 522 grazing herds. TheGrazeIn input variables under consideration were fill value (FV), grass energy content [UnitéFourragèreLait (UFL)], grass protein value [true protein absorbable in the small intestine when rumen fermen energy is limiting microbial protein synthesis in the rumen (PDIE)], pre‐grazing herbage mass (PGHM), daily herbage allowance (DHA) and concentrate supplementation. GrazeIn was evaluated using the relative prediction error (RPE). The mean actualGDMIand milk yields of grazing herds in the database ranged from 9·9–22·0 kgDMper cow d−1and 8·9–41·8 kg per cow d−1, respectively. The accuracy of predictions for the total database estimated byRPEwas 12·2 and 12·8% forGDMIand milk yield, respectively. The mean bias (predicted minus actual) forGDMIwas −0·3 kgDMper cow d−1and for milk yield was +0·9 kg per cow d−1. GrazeIn predictedGDMIwith a level of error <13·4%RPEfor spring, summer and autumn. GrazeIn predicted milk yield in autumn (RPE = 17·6%) with a larger error in comparison with spring (RPE = 10·4%) and summer (RPE = 11·0%). Future studies should focus on the adaptation ofGrazeIn to correct and improve the prediction of milk yield in autumn.