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通过极性梯度萃取法和化学计量学模式识别对功能性香料进行配方分析。

Formulation analysis of functional fragrance via polar-gradient extraction method and chemometrics pattern recognition.

机构信息

Department of Chemistry and Chemical Engineering, Hunan Institute of Science and Technology, Yueyang, China.

Department of Chemistry and Chemical Engineering, Hunan Institute of Science and Technology, Yueyang, China.

出版信息

Talanta. 2024 Aug 1;275:126121. doi: 10.1016/j.talanta.2024.126121. Epub 2024 Apr 25.

Abstract

In this study, characteristic components of 15 natural flavors was analyzed by the polar-gradient extraction (PGE) technique in combination with GC-MS and chemometrics pattern recognition. The obtained results were utilized for the traceability of 4 functional fragrance formulations. The optimal PGE system consisting of 5 different polar solvents, was developed based on similarity-intermiscibility theory. Four chemometrics pattern recognition models including PCA, HCA, PLS-DA, and OPLS-DA were constructed based on the characteristic component database constituting 15 natural flavors. These models were used to trace 4 functional fragrance formulations. The experimental results obtained were found to be satisfactory and accurate. The combination of PGE technique and chemometric pattern recognition methods provides theoretical guidance for the analysis of characteristic components of natural flavors and the traceability of functional fragrance formulations. This approach can be promoted in various fields such as food, traditional Chinese medicine, and cosmetics.

摘要

本研究采用极性梯度萃取(PGE)技术结合 GC-MS 和化学计量学模式识别分析了 15 种天然香料的特征成分。利用所得结果对 4 种功能性香料配方进行了溯源。基于相似-互溶性理论,开发了由 5 种不同极性溶剂组成的最佳 PGE 体系。基于由 15 种天然香料组成的特征成分数据库,构建了包括 PCA、HCA、PLS-DA 和 OPLS-DA 在内的 4 种化学计量学模式识别模型。这些模型用于追踪 4 种功能性香料配方。实验结果令人满意且准确。PGE 技术与化学计量学模式识别方法的结合为天然香料特征成分分析和功能性香料配方溯源提供了理论指导。这种方法可以在食品、中药和化妆品等各个领域得到推广。

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