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http://dx.doi.org/10.5333/KGFS.2014.34.3.214

Studies on 5 Protein Fractions Prediction of Forage Legume Mixture by NIRS  

Lee, Hyo-Won (Department of Agriculture, Korea National Open University)
Jang, Sungkwon (Department of Agriculture, Korea National Open University)
Lee, Hyo-Jin (Department of Landscape Architecture, Sungkyunkwan University)
Park, Hyung-Soo (National Institute of Animal Science, RDA)
Publication Information
Journal of The Korean Society of Grassland and Forage Science / v.34, no.3, 2014 , pp. 214-218 More about this Journal
Abstract
This study was conducted to assess the feasibility of near-infrared reflectance spectroscopy (NIRS) as a rapid and reliable method for the estimation of crude protein (CP) fractions in forage legume mixtures (sudangrass and pea mixture, and kidney bean and potato mixture). A total of 178 samples were collected and their spectral reflectance obtained in the range of 400~2,500 nm. Of these, 50 samples were selected for calibration and validation, and 35 samples were used for calibration of the data set, and the modified partial least square regression (MPLSR) analysis was performed. The correlation coefficient ($r^2$) and the standard error of cross-validation (SECV) of the calibration models in the CP fractions, A, B1, B2, B3, and C, were 0.94 (1.05), 0.92 (0.74), 0.96 (0.95), 0.91 (0.42), and 0.83 (0.38), respectively. Fifteen samples were used for equation validation, and the $r^2$ and the standard error of prediction (SEP) were 0.87 (1.45), 0.91 (0.49), 0.94 (1.13), 0.36 (0.96), and 0.74 (0.67), respectively. This study showed that NIRS could be an effective tool for the rapid and precise estimation of CP fractions in forage legume mixtures.
Keywords
Five crude protein fractions; Forage; Legume; MPLSR; NIRS;
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