Abstract：Near-infrared diffusion reflectance spectroscopy is a fast technique that can provide component information about intact soybean samples. We have combined this technique with partial least-squares (PLS) regression to perform a quantitative determination of protein and fat contents in soybean samples. In calibration set, the NIR model determination coefficient R2 of protein and fat is 0.993 0 and 0.975 2 respectively, and the relative standard deviation (RSD) is 0.76% and 1.3% respectively. The correlation coefficient r of validation set is 0.947 3 and 0.869 5 respectively. This NIR model is used to predict the contents of protein and fat in 264 soybean samples, using R-error to assess the deviation of analysis results. The minimum RSD of prediction of protein and fat is 0.04% and 2.46% respectively, and the maximum RSD of prediction of protein and fat is 2.45% and 4.25% respectively. These results are of great importance in early screening of crop breeding.
李 宁，闵顺耕*，覃方丽，张明祥，叶升锋 . 近红外光谱法非破坏性测定黄豆籽粒中蛋白质、脂肪含量 [J]. 光谱学与光谱分析, 2004, 24(01): 45-49.
LI Ning, MIN Shun-geng, QIN Fang-li, ZHANG Ming-xiang, YE Sheng-feng . Nondestructive Analysis of Protein and Fat in Whole-kernel Soybean by NIR . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2004, 24(01): 45-49.
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