Combining chromatography and chemometrics for the characterization and authentication of fats and oils from triacylglycerol compositional data鈥擜 review

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• 作者：Juan M. Bosque-Sendra^a  ; [Author Vitae] ; Luis Cuadros-Rodr&iacute ; guez^a ; ^{lcuadros@ugr.es}  ; [Author Vitae] ; Cristina Ruiz-Samblá ; s^a  ; [Author Vitae] ; A. Paulina de la Mata^b  ; [Author Vitae]
• 关键词：ANN ; artificial neural network ; ANOVA ; analysis of variance ; APCI ; atmospheric-pressure chemical ionization ; CAD ; charged aerosol detector ; CART ; classification and regression tree ; CB ; cocoa butter ; CBE ; cocoa butter equivalent ; CDA ; canonical discrimina
• 刊名：Analytica Chimica Acta
• 出版年：2012
• 期刊代码：2_00032670
• 类别：ch
• 出版时间：29 April, 2012
• 卷：724
• 期：Complete
• 页码：1-11
• 文件大小：656 K

摘要

The characterization and authentication of fats and oils is a subject of great importance for market and health aspects. Identification and quantification of triacylglycerols in fats and oils can be excellent tools for detecting changes in their composition due to the mixtures of these products. Most of the triacylglycerol species present in either fats or oils could be analyzed and identified by chromatographic methods. However, the natural variability of these samples and the possible presence of adulterants require the application of chemometric pattern recognition methods to facilitate the interpretation of the obtained data. In view of the growing interest in this topic, this paper reviews the literature of the application of exploratory and unsupervised/supervised chemometric methods on chromatographic data, using triacylglycerol composition for the characterization and authentication of several foodstuffs such as olive oil, vegetable oils, animal fats, fish oils, milk and dairy products, cocoa and coffee.