Quantitative Analysis of Nutrition Composition in Native Grasses by Near-Infrared Reflectance Spectroscopy

doi:10.11924/j.issn.1000-6850.casb14120188

Abstract

Abstract: In order to evaluate the potential of using near infrared reflectance spectroscopy (NIRS) in analyzing the nutrition composition of native grasses quantitatively, content of CP, NDF and EE in 210 native grass samples were tested by modified partial least square (MPLS) regression. The results showed that cross validation determination coefficients (1-VR) of CP and NDF were 0.9886 and 0.9554, standard errors of cross validation (SECV) were 0.4393 and 1.7169, and ratios of standard deviation of reference analysis data to SECV (RPDCV) were 9.3355 and 4.7194, respectively. With low value of 1-VR (0.668) and SECV (0.6264), the model of EE needed to be further optimized. This study preliminarily established model of CP, NDF and EE in native Kobresia in Henan County, and provided basic data for establishing database of native grasses in different areas in Qinghai Province.

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