数字农科院2.0

Multiple adulteration detection of olive oils by Raman spectroscopy

文献类型： 外文期刊

作者： 李雪;王督;喻理;马飞;汪雪芳;张良晓;李培武

关键词： Olive oil Raman spectroscopy D-optimal mixture design Partial least squares-discriminant analysis

期刊名称： Oil Crop Science

ISSN： 2096-2428

年卷期： 2025 年

页码：

收录情况： CSCD（2025-2026年度） ; ; 农林核心（2024版）

摘要： The increasing prevalence of multiple adulteration in olive oil, which undermines product authenticity and market integrity, necessitates the development of advanced detection methods. In this study, a portable Raman spectrometer was employed to address this issue, with adulterant mixtures designed using a D-optimal mixture approach to ensure representative blending. The results showed that principal component analysis (PCA) was unable to distinguish between authentic and adulterated samples, whereas partial least squares-discriminant analysis (PLS-DA) successfully differentiated the two groups. These findings demonstrate the technical feasibility of combining Raman spectroscopy with PLS-DA for detecting complex olive oil adulteration, offering a promising basis for portable, rapid authentication tools to counter increasingly sophisticated fraud in the edible oil industry.

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