Comparison of the Amounts of Volatile Compounds in French Protected Designation of Origin Virgin Olive Oils

• Published in: Journal of agricultural and food chemistry Vol. 54; no. 26; pp. 10092 - 10101
• Main Authors: Berlioz, Benoit, Cordella, Christophe, Cavalli, Jean-François, Lizzani-Cuvelier, Louisette, Loiseau, André-Michel, Fernandez, Xavier
• Format: Journal Article
• Language: English
• Published: Washington, DC American Chemical Society 27-12-2006
• Subjects: Biological and medical sciences; Chromatography, Gas - methods; Fat industries; Food and Nutrition; food chemistry; Food engineering; Food industries; France; Fundamental and applied biological sciences. Psychology; gas chromatography; Gas Chromatography-Mass Spectrometry; headspace analysis; headspace solid phase microextraction; Humans; Life Sciences; mass spectrometry; microextraction; Odorants - analysis; Olea; Olive Oil; Plant Oils - chemistry; Plant Oils - classification; principal component analysis; protected designation of origin; Smell; soft independent modeling of class analogy; solid phase extraction; Taste; volatile organic compounds; Volatilization; France; Volatile compound; soft independent modeling of class analogy; Vegetable oil; Olive oil; Headspace solid-phase microextraction; Edible oil; Modeling; Virgin oil; Solid phase microextraction; GC-MS; French; Classification; Headspace; PDO; Protected Designation of Origin; GC-FID; Principal component analysis; headspace solid-phase microextraction; olive oil; classification; principal component analysis
• ISSN: 0021-8561; 1520-5118
• 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. Keywords: Headspace solid-phase microextraction; GC-FID; GC-MS; principal component analysis; soft independent modeling of class analogy; classification; olive oil; PDO