MAXR回归法在近红外光谱定量分析及最优波长选择中的应用研究

介绍了运用MAXR回归法建立傅里叶变换近红外光谱定量分析模型的原理和方法。以此方法，由Matlab语言设计程序，进行近红外光谱定量分析建模的波长信息选择。并以小麦样品为实验材料，建立了蛋白质含量的近红外光谱定量分析模型，其中优选出2个和3个波长点处光谱信息建立的多元回归模型的预测结果与凯氏定氮法分析结果相关系数分别为0.977 1和0.976 5，标准差分别为0.335和0.340。MAXR回归法在进行波长信息，选择时可建立分别包含1，2，…，k个波长点信息的最优回归模型，且计算量适中，因此是一种实用的选择“最优”波长信息的回归方法。该方法不仅可少而精选择波长信息，建立抗共线性信息干扰的光谱定量分析模型，而且对于特定样品、特定待分析组分，选择最优波长信息建模分析的工作，可指导专用近红外分析仪器的设计。

Study on the Application for Near-Infrared Spectroscopy Quantitative Analysis and Selecting Optimum Wavelength by the MAXR Regression Procedure

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.