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Di Duan,Yong Huang,Ying Zou,Bingju He,Ruihui Tang,Liuxia Yang,Zecao Zhang,Shucai Su,Guoping Wang,Deyi Zhang,Chunhui Zhou,Jing Li,Maocheng Deng 한국식품과학회 2021 Food Science and Biotechnology Vol.30 No.10
Analytical method which combines electronictongue technique and chemometrics analysis is developedto discriminate oil types and predict oil quality. All thestudied Camellia oil samples from pressing, n-hexaneextraction and supercritical CO2 extraction (SCCE), weresuccessfully identified by principal component analysis(PCA) and hierarchical cluster analysis (HCA). Furthermore,multi factor linear regression model (MLRM) wasestablished to predict oil quality, which are indicated byacid value (AV) and peroxide value (POV). The practicalpotential of e-tongue for the discrimination and assessmentof Camellia oils has shown promising application in thecharacterization of Camellia oils in the oil qualityevaluation.