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OA北大核心CSTPCD

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.