title: [Study on the application for near-infrared spectroscopy quantitative analysis and selecting optimum wavelength by the MAXR regression procedure].
abstract: This paper introduces the principle and method with which the model about the quantitative analysis of Fourier transformation near infrared (NIR) spectroscopy by MAXR regression procedure can be established. In this way, the authors have selected the wave length information by Matlab language design programming in order to establish the quantitative analysis models with near infrared spectroscopy. Taking sixty-six wheat samples as experiment materials, quantitative analysis models to determine protein content are established with thirty-three samples. The relative coefficient are 0.977 1 and 0.976 5 respectively and the standard error are 0.335 and 0.340 between the predication result of the two models which include respectively two or three wave length information and Kjeldahl's value for the protein content of the another thirty-three wheat samples. When selecting the wave length information, the MAXR regression procedure can establish the optimum regression models which contain 1 or 2...or k wavelength information respectively. MAXR regression procedure is a useful method when selecting the optimum wavelength information because of its shorter computation time, and the method not only can carefully select the essential wavelength information to establish NIR spectroscopy quantitative analysis models of resisting multicollinearity information disturbance, but also to establish the work for selecting optimum wavelength information which can direct to design the special NIR analysis instrument for analyzing specific component in the special samples.
authors.affiliation: College of Science, China Agricultural University, Beijing 100094, China.
authors.forename: Lu-da
authors.initials: LD
authors.lastname: Zhang
authors.forename: Li-li
authors.initials: LL
authors.lastname: Zhao
authors.forename: Long-lian
authors.initials: LL
authors.lastname: Zhao
authors.forename: Jun-hui
authors.initials: JH
authors.lastname: Li
authors.forename: Yan-lu
authors.initials: YL
authors.lastname: Yan
mesh_terms: D000465:Algorithms; D015233:Models, Statistical; D010940:Plant Proteins / Q000032:analysis*; D012044:Regression Analysis; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D014908:Triticum / Q000378:metabolism*
chemical_list: D010940:Plant Proteins