[Near infrared determination of dry hay quality in oats]

In the present paper, the analysis of the content of CP, NDF and ADF in the whole dry hay of oats was carried out by using near infrared reflectance spectroscopy (NIRS) technique, and in combination with the partial least square (PLS) regression algorithm the calibration analysis was performed at the same time. The results showed that the calibration models developed by the spectral data pretreatment of the second derivative + Norris smoothing, the multivariate scattering correction + second derivative + Norris smoothing, and the multivariate scattering correction were the best for CP, NDF and ADF with the same spectral regions (9668-4518, 9550-5543, 8943-4042 cm(-1)). All these models yielded coefficients of determination of calibration (r2 cal) for CP and NDF that are both higher than 0.95, and each error lower than 3%, approached the chemical analysis precision. Moreover, the values of (RPD) of CP and NDF were both higher than 3.0. The results of these studies indicate that the contents of CP and NDF can be used to measure various samples in screening and evaluating quality constituents of dry hay in oats. While the effect of ADF modelling was poorer, the coefficients of determination of calibration (r2 cal) and cross validation (r2 CV)for ADF were 0.9120, 0.8553 respectively. The root mean square error of calibration, root mean square error of cross validation, and root mean square error of prediction ( RMSEE, RMSECV and RMSEP) for ADF were 2.33%, 2.62% and 1.91% respectively, and the precision is near the precision of the chemical analysis. The models of ADF can be used to measure various samples in screening and evaluating quality constituents of dry hay of oats also. This study has proved that NIRS technique can be applied to detect the contents of CP, NDF and ADF in the whole dry hay of oats.