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Rapid quantitative authentication of vegetable blend oil quality by Raman spectroscopy coupled with spectral characteristic intervals selection algorithm

1, 1,Zhi-Ming GUO   

  • Received:2023-06-01 Revised:2023-08-24 Online:2023-09-19 Published:2023-09-19
  • Contact: Zhi-Ming GUO

Abstract: In this study, a method for rapid and quantitative determination of the content of high-value vegetable oil in vegetable blend oils was proposed based on Raman spectroscopy and a spectral characteristic intervals selection algorithm. First, the particle swarm optimization (PSO) algorithm and the grey wolf optimization (GWO) algorithm were combined to develop a hybrid intelligent optimization algorithm, i.e., PSOGWO algorithm. Second, the PSOGWO algorithm and the combined moving window (CMW) strategy were combined to develop a novel spectral characteristic intervals selection algorithm, i.e., PSOGWO-CMW algorithm. Third, the corn oil (CO)-extra virgin olive oil (EVOO) vegetable blend oil was prepared by mixing CO and EVOO with different ratios, and then the Raman spectra of CO-EVOO vegetable blend oil were measured. To investigate the performance of PSOGWO-CMW, the PLSR, PSO-CMW, GWO-CMW, and PSOGWO-CMW models were applied on the Raman spectra of CO-EVOO vegetable blend oil to predict the content of EVOO, and their prediction results were comparatively studied. The results showed that PSOGWO-CMW model possessed superior prediction performance. Finally, the proposed method and the gas chromatography-mass spectrometry method were employed to determine the content of EVOO in real CO-EVOO vegetable blend oils, respectively. The results showed that there was no significant difference between these two methods. In conclusion, the proposed method is rapid and accurate, and it can also be used for rapid and quantitative determination of the content of high-value vegetable oil in other vegetable blend oils.

Key words: Raman spectroscopy, vegetable blend oils, intelligent optimization algorithms, spectral characteristic intervals selection, quantitative authentication

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