食品科学2024，Vol.45Issue(6)：244-253,10.DOI:10.7506/spkx1002-6630-20230531-291
拉曼光谱结合光谱特征区间筛选算法快速定量鉴别植物调和油品质
Rapid Quantitative Authentication of Blended Vegetable Oil Quality by Raman Spectroscopy Coupled with a Selection Algorithm of Spectral Characteristic Intervals
摘要
Abstract
In this study,a method for the rapid quantitative determination of the content of high-value vegetable oil in blended edible vegetable oils(BEVO)was proposed based on Raman spectroscopy and a selection algorithm of spectral characteristic intervals.First,the particle swarm optimization(PSO)and grey wolf optimization(GWO)algorithms were combined to develop a hybrid intelligent optimization algorithm called PSOGWO.Second,the PSOGWO algorithm and the combined moving window(CMW)strategy were combined to develop a novel spectral characteristic interval selection algorithm named PSOGWO-CMW.Third,blends of corn oil(CO)and extra virgin olive oil(EVOO)at different ratios were prepared,and then their Raman spectra were acquired.Using the Raman spectra as input variables,partial least squares regression(PLSR),PSO-CMW,GWO-CMW,and PSOGWO-CMW models were developed to predict the content of EVOO,and their performance was comparatively studied.The results showed that the PSOGWO-CMW model had the best prediction performance.The results of the proposed method for the content of EVOO in CO-EVOO blends were not significantly different from those of gas chromatography-mass spectrometry.In conclusion,this method is rapid and accurate,and can be used for rapid and quantitative determination of the content of high-value vegetable oil in BEVO.关键词
拉曼光谱/植物调和油/智能优化算法/光谱特征区间筛选/定量鉴别Key words
Raman spectroscopy/blended edible vegetable oils/intelligent optimization algorithms/spectral characteristic intervals selection/quantitative authentication分类
轻工纺织引用本文复制引用
吴升德,姜鑫,李爱琴,郭志明,朱家骥..拉曼光谱结合光谱特征区间筛选算法快速定量鉴别植物调和油品质[J].食品科学,2024,45(6):244-253,10.基金项目
国家自然科学基金青年科学基金项目(32102075) （32102075）
江苏省市场监督管理局科技计划项目(KJ2022050) （KJ2022050）
江苏省高等学校基础科学(自然科学)面上项目(21KJD550002) （自然科学）
