[Research on predicting the qualities of stem of alfalfa hay by near infrared reflectance spectroscopy].
The present research was attempted to predict the qualities of stem of alfalfa (Medicago sativa L. ) without separation from the whole plant by near infrared reflectance spectroscopy and discussed the feasibility of using the near infrared reflectance spectra information of the whole object to predict the qualities of a certain part. Sixty six whole alfalfa hay samples of separated stems from leaves were collected and they were distinguishing by years, cultivars, cuts and growing periods. There were 138 calibration samples and 60 validation samplers. Fourier transform-near infrared reflectance spectroscopy (FT-NIRS) and partial least square (PLS) were used to set up the calibration models of stem's crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), crude ash (CA) and in vitro digestible dry matter (IVDDM) contents. All models showed great calibration and prediction performances except the one of stem's NDF content. The correlation coefficients of cross-validation (rCV) were between 0.8523 and 0.9007, the root mean square errors of cross-validation (RMSECV) were between 0.72% and 3.96% and the correlation coefficients of NIRS values and chemical values (r) were between 0.9255 and 0.9512. However, rCV, RMSECV and r of the model of stem's NDF content were 0.8214, 3.70% and 0.9020, respectively. It wasn't exact enough and would be used for rough predicting only. All of the results showed that near infrared reflectance spectra information of whole alfalfa hay could be used to predict some components of its stem exactly. It was the maiden attempt of using near infrared reflectance spectra information of the whole objects to evaluated the qualities of a certain part.
Qi
Xiao
X
Institute of Grassland Science, China Agricultural University, Beijing Major Laboratory, Beijing 100094, China. tq07mms@sina.com
Han
Jian-guo
JG
Nie
Zhi-dong
ZD
Liu
Fu-yuan
FY
Zhang
Ze-hong
ZH
Li
Man-li
ML