| 光谱学与光谱分析 |
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| Nondestructive Analysis of Protein and Fat in Whole-kernel Soybean by NIR |
| LI Ning, MIN Shun-geng, QIN Fang-li, ZHANG Ming-xiang, YE Sheng-feng |
| Department of Applied Chemistry, China Agricultural University, Beijing 100094, China |
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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.
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Received: 2002-06-06
Accepted: 2003-01-16
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Corresponding Authors:
MIN Shun-geng
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| Cite this article: |
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LI Ning,MIN Shun-geng,QIN Fang-li, et al. Nondestructive Analysis of Protein and Fat in Whole-kernel Soybean by NIR [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2004, 24(01): 45-49.
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| URL: |
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http://www.gpxygpfx.com/EN/Y2004/V24/I01/45 |
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