Quality and chemical profiles of monovarietal north Moroccan olive oils from “Picholine Marocaine” cultivar: Registration database development and geographical discrimination

• Published in: Food chemistry Vol. 179; pp. 127 - 136
• Main Authors: Bajoub, Aadil, Hurtado-Fernández, Elena, Ajal, El Amine, Fernández-Gutiérrez, Alberto, Carrasco-Pancorbo, Alegría, Ouazzani, Noureddine
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15-07-2015
• Subjects: Databases, Factual; Discriminant Analysis; Fatty Acids - analysis; Geographical origin; Geography; Morocco; Olive Oil; Physicochemical quality parameters; Picholine Marocaine; Plant Oils - analysis; Purity criteria; Sterols - analysis; Triglycerides - analysis; Triterpenes - analysis; Virgin olive oil; Morocco; Physicochemical quality parameters; Picholine Marocaine; Geographical origin; Virgin olive oil; Purity criteria
• ISSN: 0308-8146; 1873-7072
• DOI: 10.1016/j.foodchem.2015.01.101

•First comprehensive characterisation of monovarietal north Moroccan olive oils.•Geo-location of olive growing areas with some peculiarities with GIS (ArcGIS).•Multivariate statistical analysis for geographical discrimination of samples.
Current knowledge of the quality and composition of Moroccan olive oil is still incomplete and no consistent database compiling its properties is available. This study was carried out to achieve a comprehensive characterisation of north Moroccan olive oils. Thus, 279 olive samples of “Picholine Marocaine” cultivar grown in 7 Moroccan regions were collected, and oils extracted over two consecutive crop seasons (2011 and 2012) and analysed (considering physicochemical quality parameters and purity criteria). Results indicated that all the studied samples showed values fulfilling the established limits set by the International Olive Council (IOC) standards, with the exception of 32 samples that had a linolenic acid content higher than 1%, which is the maximum value fixed by the IOC regulation. Furthermore, the usefulness of the evaluated parameters for tracing the geographical origin of the studied samples was tested by using canonical discriminant analysis. A good rate of correct classification and prediction was achieved.