Berlioz Benoit, Cordella Christophe, Cavalli Jean-François, Lizzani-Cuvelier Louisette, Loiseau André-Michel, Fernandez Xavier
LCMBA, UMR CNRS 6001, Université de Nice-Sophia Antipolis, Parc Valrose, F-06108 Nice Cedex 2, France.
J Agric Food Chem. 2006 Dec 27;54(26):10092-101. doi: 10.1021/jf061796+.
Headspace solid-phase microextraction (HS-SPME) -gas chromatography using flame ionization detection and multivariate analysis were applied to the study of the specificity of protected designation of origin (PDO) virgin olive oils produced in a southern French region (Alpes-Maritimes) based on their volatile compounds. A total of 35 PDO olive oils from Nice, 6 commercial oils, and 12 other French PDO olive oils were analyzed. Recorded data were subjected to principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). The method developed here was able to perfectly distinguish different qualities of olive oils. Representative samples from each class obtained by chemometric treatment were analyzed by HS-SPME and GC-MS. PCA and SIMCA of chromatographic data were related to sensory analysis and led to a better understanding of the chemical features and observed sensory effects of olive oils.
采用顶空固相微萃取(HS-SPME)-气相色谱法(配备火焰离子化检测器)并结合多变量分析,对法国南部地区(滨海阿尔卑斯省)生产的受保护原产地名称(PDO)初榨橄榄油基于其挥发性化合物的特异性展开研究。共分析了来自尼斯的35种PDO橄榄油、6种市售橄榄油以及12种其他法国PDO橄榄油。记录的数据进行主成分分析(PCA)和类软独立建模(SIMCA)。此处开发的方法能够完美区分不同品质的橄榄油。通过化学计量处理从每个类别中获得的代表性样品采用HS-SPME和GC-MS进行分析。色谱数据的PCA和SIMCA与感官分析相关联,有助于更好地理解橄榄油的化学特征和观察到的感官效果。