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Study on the Volatile Oxidation Compounds and Quantitative Prediction of Oxidation Parameters in Walnut (Carya cathayensis Sarg.) Oil

文献类型： 外文期刊

作者： Mu, Honglei 1 ; Gao, Haiyan 1 ; Chen, Hangjun 1 ; Fang, Xiangjun 1 ; Zhou, Yongjun 1 ; Wu, Weijie 1 ; Han, Qiang 1 ;

作者机构： 1.Zhejiang Acad Agr Sci, Key Lab Postharvest Handling Fruits, Minist Agr,Food Sci Inst, Key Lab Fruits & Vegetables Postharvest & Proc Te, Hangzhou 310021, Zhejiang, Peoples R China

关键词： Carya cathayensis Sarg; oil; oxidation parameters; partial least-squares regression; SPME; GC-MS; volatile oxidation compounds

期刊名称：EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY （ 影响因子：2.679； 五年影响因子：2.627 ）

ISSN： 1438-7697

年卷期： 2019 年 121 卷 6 期

页码：

收录情况： SCI

摘要： Walnut (Carya cathayensis Sarg.) oil contains over 85% unsaturated fatty acids, which are easily oxidized during storage. As a result, a large number of volatile oxidation compounds (VOCs) are formed during oxidation. The qualitative composition of VOCs in walnut oil and quantitative prediction of the oxidation parameters (peroxide value [POV], acid value [AV], and p-anisidine value [p-AnV]) by VOCs are investigated through SPME/GC-MS combined with partial least-squares (PLS) regression analysis. Eighteen VOCs including aldehydes, alcohols, and acids are detected by SPME/GC-MS. According to the comprehensive scores of principal component analysis (PCA), 2-octenal, hexanal, 2-heptenal, 1-octen-3-ol, hexanoic acid, and nonanal are the main products formed during oxidation. Then PLS regression is applied to developing quantitative prediction models of oxidation parameters (POV, AV, and p-AnV) by VOCs. The PLS prediction models have a good performance, with determination coefficients (R-p(2)) of 0.993-0.997 for the prediction sets of the three oxidation parameters.Practical Applications: The quantitative relationship between VOCs and oxidation parameters is developed in this study, which provided a new method for monitoring the quality of walnut oil. The SPME/GC-MS combined with PLSR is a feasible and potential method for simultaneous qualitative and quantitative analysis of oxidation process. This method is proven to have a precise predictive ability and provided a potential application in the quality assessment of other nut products. Volatile oxidation compounds (VOCs) are detected by SPME/GC-MS in oxidized walnut (Carya cathayensis Sarg.) oil. Following this determination, partial least-squares regression (PLSR) is applied to developing quantitative prediction models of oxidation parameters by VOCs.

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