Predicción del valor nutricional de sorgo para forraje mediante espectroscopia de reflectancia en el infrarrojo cercano (NIRS) y ecuaciones empíricas

In the present work it is studied the predictive ability of NIRS for the estimation of chemical composition (n=171) and organic matter digestibility (n=71) of whole plants forage sorghum and morphological components, being developed empirical equations based on chemical parameters to estimate the organic matter digestibility (OMD) values and compared the predictive ability of empirical models vs. NIRS equations. The predictive ability of NIRS models for estimating the OMD and chemical composition showed high reliability, according to the coefficient of determination in external validation (r²≥0.90), whilst the ratio of the standard deviation of the original data to standard error of external validation (RPD) values were higher than 3.0 for all parameters studied. Applying NIRS models to the prediction of OMD of whole plants and morphological components of forage sorghum led to the reduction in the standard error of external validation, in comparison of the best empirical model based on the chemical composition of samples (from ±3.9 to ±1.9%). It is concluded that the NIRS equations developed in the present work are valuable tools for the fast and accurate assessment of the nutritive value of the whole plant and components of forage sorghum.