摘要
利用近红外光谱对非均匀样品进行分析时,所得样品光谱中包含由光散射导致的干扰信息,通常需要借助多元散射校正算法(multiple scattering correction,MSC)对光谱进行预处理。由于不同波段光谱中所包含的散射信息、噪声水平、基线漂移程度等存在差异,利用MSC方法对光谱进行预处理时,基于不同波段的光谱数据会得到不同的校正结果,进而影响所得定标模型的可靠性。以60个全麦粉样品为研究对象,确定定标区间后,对包含定标区间的不同波段的原始光谱分别进行MSC处理,并利用固定区间内的光谱数据结合偏最小二乘回归(partial least square regression,PLSR)方法建立分析样品中蛋白质含量的定标模型,研究了MSC光谱预处理波段对定标模型的影响,并对MSC光谱预处理波段进行了优化,使定标模型的相关系数由0.96提高到0.98,交互验证均方根误差(root mean squares error of cross validation,RMSECV)由0.37%降低到0.32%。结果表明:利用MSC方法对样品光谱预处理时,光谱预处理波段会影响多元散射校正对光谱中非化学吸收信息的校正能力,确定合适的预处理波段是获得可靠分析结果的一个前提条件。
In the present paper,60 whole wheat flour samples were prepared and corresponding NIR spectra were collected.After the determinations of calibration range,several spectral sub-regions containing calibration range and prepared for the correction using multiple scattering correction(MSC)were obtained in the whole spectral region firstly,and MSC correction based on different spectral sub-region followed subsequently.Corresponding spectral data were obtained from the fixed calibration range of the spectra corrected based on different regions.Several partial least squares regression(PLSR)calibration models for analyzing protein content of whole wheat flour were established based on corresponding spectral data,and according to the performance about the calibration coefficient and the root mean square error of cross validation(RMSEV)of every calibration,the effects of MSC pretreatment spectral region on PLSR calibration results were investigated and the pretreatment spectral regions were optimized by comparing the performance of more calibration models.For the optimized calibration,the calibration coefficient and the RMSECV improved compared with the calibration established based on the spectral data corrected using MSC in the fixed region of calibration.The correlation coefficient can be raised from 0.96 to 0.98 and RMSECV can be decreased from 0.37% to0.32%.The results show that the capability of MSC on correcting the spectral interference information of non-chemical absorption can be influenced by preprocessing spectral regions,the performance of calibration model can be improved by optimizing the MSC pretreatment spectral region,and the appropriate pretreatment spectral region is prerequisite to obtain the best calibration results while using MSC for near-infrared spectra analysis.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2014年第9期2387-2390,共4页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(61078038)
国家(863计划)项目(2012AA022602)
河南工业大学高层次人才基金项目(2012BS050)资助
关键词
多元散射校正
预处理波段
偏最小二乘回归
近红外光谱分析
Multiplicative scatter correction
Preprocessing regions
Partial least square regression
Near infrared spectroscopy
