平滑、导数、基线校正对近红外光谱PLS定量分析的影响研究

Influence of Smooth, 1st Derivative and Baseline Correction on the Near-Infrared Spectrum Analysis with PLS

基于偏最小二乘法 ,利用平滑、导数、基线校正预处理手段 ,对近红外光谱进行了定量分析 ,比较了分析结果 ,给出了不同预处理方法的PRESS值和RMSEC的值 ,比较并选取了最佳预处理方法。在平滑预处理方法中 ,比较了不同平滑点数对预测的影响 ,确定了最佳平滑点数 ,通过采用PLS回归分析 ,与原始光谱数据回归比较 ,结果令人满意。

This paper studied the influence of using pre-procession such as smooth, 1st derivative and baseline correction on the analysis of near-infrared spectrum. Comparing the analysis results by the pre-procession methods, and using PLS arithmetic, the best pre-procession was determined. In smooth pre-procession method, the best smooth points were proposed for regression using PLS. The analysis result is satisfactory.