Li Ning, Min Shun-geng, Qin Fang-li, Zhang Ming-xiang, Ye Sheng-feng
Department of Applied Chemistry, China Agricultural University, Beijing 100094, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2004 Jan;24(1):45-9.
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 0.9930 and 0.9752 respectively, and the relative standard deviation (RSD) is 0.76% and 1.3% respectively. The correlation coefficient r of validation set is 0.9473 and 0.8695 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.
近红外漫反射光谱法是一种快速技术，能够提供完整大豆样品的成分信息。我们已将该技术与偏最小二乘法（PLS）回归相结合，以对大豆样品中的蛋白质和脂肪含量进行定量测定。在校准集中，蛋白质和脂肪的近红外模型测定系数R2分别为0.9930和0.9752，相对标准偏差（RSD）分别为0.76%和1.3%。验证集的相关系数r分别为0.9473和0.8695。该近红外模型用于预测264个大豆样品中的蛋白质和脂肪含量，采用R误差评估分析结果的偏差。蛋白质和脂肪预测的最小RSD分别为0.04%和2.46%，蛋白质和脂肪预测的最大RSD分别为2.45%和4.25%。这些结果在作物育种的早期筛选中具有重要意义。
