FT-IR and Raman spectroscopy data fusion with chemometrics for simultaneous determination of chemical quality indices of edible oils during thermal oxidation
文献类型： 外文期刊
作者： Liu, Huan 1 ; Chen, Yi 3 ; Shi, Ce 1 ; Yang, Xinting 1 ; Han, Donghai 2 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
2.China Agr Univ, Coll Food Sci & Nutr Engn, Beijing 100083, Peoples R China
3.Beijing Technol & Business Univ, Beijing Key Lab Big Data Technol Food Safety, Beijing 100048, Peoples R China
4.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China
5.Natl Engn Lab Agriprod Qual Traceabil, Beijing 100097, Peoples R China
关键词： Data fusion strategy; Feature variables extraction; SPA-PLS; Quality indices; Edible oils
期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：4.952； 五年影响因子：5.383 ）
ISSN： 0023-6438
年卷期： 2020 年 119 卷
页码：
收录情况： SCI
摘要： A rapid, non-destructive and robust method for measuring peroxide values (PVs) and acid values (AVs) of common edible oils (soybean, rapeseed, sunflower and peanut) simultaneously under various thermal oxidation was explored by FT-IR and Raman spectroscopy data fusion strategy. Uninformative variable elimination (UVE) and successive projections algorithm (SPA) methods were used for feature variables extraction, quantitative models for prediction of chemical quality indices were established using partial least squares regression (PLSR) algorithm. The bands associated with vibration of C = O and C = C stretching were highly correlated with PVs and AVs, data fusion of the two spectra showed the best modeling results when variables identified by SPA were used. For modeling of PVs, the resulting R-c(2) and R-p(2) were 0.964 and 0.939, RMSEC and RMSEP were 0.060 and 0.080. For modeling of AVs, the resulting R-c(2) and R-p(2) were 0.955 and 0.919, RMSEC and RMSEP were 0.025 and 0.027.
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