Prediction of quality of total mixed ration for dairy cows by near infrared reflectance spectroscopy and empirical equations

Abstract

This study aimed to evaluate the predictive ability of NIRS for the estimation of the chemical composition and organic matter digestibility (OMD) of total mixed rations (TMR) for dairy cows. Moreover, herein, empirical equations based on chemical parameters were developed for calculating the OMD. Samples were collected from Galician dairy farms and were scanned in duplicate a Foss NIRSystem 6500 monochromator (1100-2500 nm). The predictive ability of NIRS models was evaluated according to the coefficient of determination in external validation ($r$2). High $r$2 (equal to or higher than 0.90) was shown in predicting chemical composition, however, the estimation of OMD was acceptable ($r$2 = 0.83). The ability of the NIRS models for estimating the chemical composition was considered excellent, with the ratio performance deviation of external validation ($RPD$) higher than 3.0, allowing for quantitative predictions. The estimation of the OMD value by NIRS was considered acceptable ($RPD$ = 2.5), and led to reduction in the standard error of external validation, in comparison of the best empirical model based on the chemical composition of samples (from ± 2.06% to ± 1.89%). Therefore, this study demonstrated that the NIRS is an effective technology for the rapid and precise nutritional evaluation of TMR in Galicia.

Keywords

• total mixed ration
• digestibility
• chemical composition
• nirs
• empirical models