An applied study on Fourier transform near-infrared whole Spectroscopy regression analysis

被引:0
|
作者
Zhang, LD [1 ]
Wang, T
Yang, LM
Zhao, LL
Zhao, LL
Li, JH
Yan, YL
机构
[1] China Agr Univ, Coll Sci, Beijing 100094, Peoples R China
[2] China Agr Univ, Coll Informat, Beijing 100094, Peoples R China
关键词
chemometrics; near-infrared; Moore-Penrose matrix; regression analysis;
D O I
暂无
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
In the present paper, 66 wheat samples were used as experimental materials, 33 of them were used for building the quantitative analysis model of protein content, and the rest composed the prediction set. Using Moore-Penrose matrix, we estimated directly the regression coefficients of the regression analysis model with Fourier transform near-infrared (FTNIR) whole spectroscopy. The samples of prediction set were analyzed, and the correlation coefficient is 0.9799 between the prediction values of the near-infrared model and the standard chemical ones by Kjeldahl's method, and the average relative error is 1.76 %. Using Moore-Penrose matrix, we can not only get the near-infrared spectroscopy analysis model's regression coefficients, but also know their contribution at every wavelength point. Consequently we can understand and explain the physical and chemical significance of the FTNIR whole spectroscopy regression model.
引用
收藏
页码:1959 / 1962
页数:4
相关论文
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