Prediction of forage quality of maize stover by near infrared spectroscopy

In order to reliably, conveniently and rapidly analyze and evaluate forage quality of maize stover, the samples of maize stover from different varieties and treatments of density, nitrogenous fertilizer and water were used to establish near infrared reflectance spectroscopy (NIRS) calibration models of in vitro dry matter digestion (IVDMD), acid detergent fiber (ADF), neutral detergent fiber (NDF) and water soluble carbohydrate (WSC) of maize stover with near infrared reflectance spectroscopy (NIRS) technique, partial least square regression (PLS) and data pretreatment of 1st derivative+mean center+Multiple scatter correction. The results showed that determination coefficients of calibration (R2cal) about those models were 0.9906, 0.9870, 0.9931 and 0.9802 and those of cross validation (R2cv) and validation (R2val) were 0.9593(0.9549), 0.9413(0.9353), 0.9678(0.9519) and 0.9342(0.9191) for IVDMD, ADF, NDF and WSC, respectively. Standard error of calibration, cross validation and prediction (SEC, SECV and SEP) ranged from 0.935 to 1.904. All values of relative percent differences (RPD) were greater than three. It demonstrated that these calibration models could be used to rapidly and accurately predict forage quality of maize stover and screen various samples in maize breeding.