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Discrimination of Camellia seed oils processed by different extraction methods based on electronic tongue technology
  • +8
  • Di Duan,
  • Bingju He,
  • Ruihui Tang,
  • Liuxia Yang,
  • Zecao Zhang,
  • Shucai Su,
  • Guoping Wang,
  • Deyi Zhang,
  • Chunhui Zhou,
  • Jing Li,
  • Maocheng Deng
Di Duan
Guangdong Industry Technical College
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Bingju He
Guangdong Industry Technical College
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Ruihui Tang
Guangdong Industry Technical College
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Liuxia Yang
Guangdong Industry Technical College
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Zecao Zhang
Guangdong Industry Technical College
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Shucai Su
Guangdong Industry Technical College
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Guoping Wang
Guangdong Fanlong Agricultural Technology Development Co., Ltd
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Deyi Zhang
Guangdong Fanlong Agricultural Technology Development Co., Ltd
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Chunhui Zhou
Guangdong Industry Technical College
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Jing Li
Guangdong Industry Technical College
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Maocheng Deng
Guangdong Industry Technical College
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Abstract

Analytical methods involving electronic tongue technique combined with chemometrics analysis was proposed to discriminate oil variety and predict oil quality parameters. All the studied Camellia oil samples from pressing, n-hexane extraction and scCO2 extraction, were successfully discriminated by principal component analysis (PCA) and hierarchical cluster analysis (HCA). Furthermore, Multi Factor Linear Regression Model (MLRM) was established allowing predictive capacity of oil quality indicators, such as acid value (AV) and peroxide value (POV). The practical potential of e-tongue for the discrimination and assessment of Camellia oils has shown promising application in the characterization of Camellia oils in the oil quality evaluation.