摘要
将移动窗口偏最小二乘（moving window partial least squares,MWPLS）法应用于羊肉中挥发性盐基氮（total volatile basic nitrogen,TVB-N）含量的近红外定量分析模型的构建中,通过改变MWPLS的窗口宽度,优选与羊肉中TVB-N含量高度相关的光谱区域。模型评价及验证结果显示,移动窗口宽度为160个波长点时优选得到的光谱区域（1 325～1 484 nm）所构建的定量分析模型最佳,其预测相关系数、预测标准偏差、主因子数和预测偏差比率分别为0.856 84、0.564 29 mg/100 g、5和2.9,这说明MWPLS可以有效地筛选羊肉中TVB-N的近红外光谱信息区间,提高定量分析模型的预测能力,并降低数据的处理量（数据点由800个减少为160个）。
Moving window pa rtial least squares（MWPLS） is a method of regional optimization, which is most frequently used for selecting spectral region including large information related to the components to be determined in the samples. In this study, MWPLS was used to select the appropriate frequency range for setting up a partial least squares（PLS） model for quanti tative analysis of the total volatile basic nitrogen（TVB-N） in mutton. The near infrared reflectance（NIR） spectra were processed by MWPLS and different spectral regions relevant to TVB-N content in meat were selected by chan ging the window width of MWPLS. T he evaluation and validation results showed that the optimal region for setting up a best PLS model was the original spectrum between 1 325 nm and 1 484 nm. and the corresponding correlation coefficie nt of prediction（Rp）, standard error of prediction（SEP）, rank and residual prediction deviation（RPD） were 0.856 84, 0.564 29 mg/100 g, 5 and 2.9, separately, suggesting that MWPLS is a valid method to select the spectral feature that reduces spectral data（from 800 reduce to 160） and enhances the prediction ability of the quantitative analysis model of TVB-N in mutton.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2015年第20期218-221,共4页
Food Science
基金
"十二五"农村领域国家科技计划课题(2012BAD28B01)
