[An applied study on Fourier transform near-infrared whole spectroscopy regression analysis].
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 0.979 9 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.
College of Science, China Agricultural University, Beijing 100094, China.
Lu-Da
LD
Zhang
Tao
T
Wang
Li-Ming
LM
Yang
Li-Li
LL
Zhao
Long-Lian
LL
Zhao
Jun-Hui
JH
Li
Yan-Lu
YL
Yan
D010940:Plant Proteins / Q000032:analysis; D012044:Regression Analysis; D017550:Spectroscopy, Fourier Transform Infrared / Q000379:methods*; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D014908:Triticum / Q000737:chemistry
D010940:Plant Proteins