近红外漫反射光谱中散射对化学定量分析模型的影响

Progress in the Study of Impact of Scattering on Stability of Quantitative Analysis Model Using Near Infrared Spectroscopy Technology and Correction Methods

结合国内外研究发展现状,分析了近红外光谱分析与检测技术中影响模型稳健性及预测模型精度的原因,特别是散射的影响。阐述了近红外光与样品组织之间的相互作用机理,及近红外光谱法定量分析模型中散射对漫反射光的影响,总结了光学方法中光学特性参数(散射系数、吸收系数)的主要检测技术的研究进展。探讨了近红外光谱检测与分析技术为基础的定量模型中为改善、增强模型稳健性所用的方法及效果,如中心化、附加散射校正(MSC)等预处理算法;偏最小二乘法(PLS)、主成分回归方法(PCA)等不同的多元校正方法。采用现有的数据预处理方法,可以改善散射对模型的稳健性的影响,但要在浓度范围较大、样品物理状态复杂的情况下消除散射引起的模型预测误差仍需要探索新的方法。

Near infrared spectroscopy technology for inner quality detection and analysis is a rapid and accurate technique. The factors affecting the stability of quantitative analysis models based on NIRS especially the influence of scattering, were investigated. The methods of determination of the parameters of optical properties of sample （scattering coefficient and absorption coefficient） and the interaction between light and sample were summarized. The progress in pretreatment methods to improve the model＇s stability, such as transformation of standard normal variate （SNV） and multiplication scatter correction （MSC） ; as well as the multivariate calibration model techniques, such as partial least square （PLS） and primary component analysis regression （PCA）, were also described. The model with scatter correction pretreatrnents and different regression methods were compared to establish a better regression equation by near Infrared reflectance spectroscopy （NIRS）. Although pretreatment methods could improve the robustness of model for influence of scattering, new techniques should be employed to eliminate the error of predication under scattering condition when samples are complicated in physical states and are in the large range of concentration.