近红外光谱分析中建模光谱宽度的选择

Selection of spectral width for prediction modeling in near-infrared spectroscopy analysis

为选择生化样品近红外光谱分析中最优的建模光谱宽度,结合样品特征波长与光谱学原理开展研究.收集348份血清样品,以血清中胆固醇、甘油三酯为例进行分析.根据光谱学原理及2 mm厚度血清的光谱吸光度,选择一级倍频区域作为分析波段,考察该区域内不同宽度光谱范围的模型效果.优选出胆固醇与甘油三酯的最优光谱宽度分别为70 nm和100 nm,并建立相应分析模型,分析的预测标准差和相对预测误差分别是0.17 mmol/L,3.0%和0.14 mmol/L,10.3%,效果不弱于他人建立模型的最好结果,使用的光谱范围更窄.

In order to select optimal spectral width for biomedical components analysis by near-infrared（NIR） spectroscopy,starting with the characteristic wavelengths of the samples,a modeling procedure based on spectroscopy principles is presented.348 human serum samples are collected.Cholesterol and triglyceride in human sera are analyzed as an example.According to spectroscopy principles and absorbance of 2 mm-thick sera,first overtone region is selected for analysis.Models with different spectral width are compared.For cholesterol and triglyceride models,optimal spectral width is 70nm and 100nm respectively.Root mean square error of prediction（RMSEP） and mean percent error of prediction（MPEP） are 0.17 mmol/L,3.0% and 0.14mmol/L,10.3%,respectively.The performance is comparable with the best works of other groups while the spectral width is narrower.