title: A new simplex chemometric approach to identify olive oil blends with potentially high traceability.
abstract: Olive oil blends (OOBs) are complex matrices combining different cultivars at variable proportions. Although qualitative determinations of OOBs have been subjected to several chemometric works, quantitative evaluations of their contents remain poorly developed because of traceability difficulties concerning co-occurring cultivars. Around this question, we recently published an original simplex approach helping to develop predictive models of the proportions of co-occurring cultivars from chemical profiles of resulting blends (Semmar & Artaud, 2015). Beyond predictive model construction and validation, this paper presents an extension based on prediction errors' analysis to statistically define the blends with the highest predictability among all the possible ones that can be made by mixing cultivars at different proportions. This provides an interesting way to identify a priori labeled commercial products with potentially high traceability taking into account the natural chemical variability of different constitutive cultivars.
authors.affiliation: Université de Tunis El Manar, Institut Pasteur de Tunis, Laboratory of Bioinformatics, Biomathematics & Biostatistics (BIMS), Tunis, Tunisia; Aix-Marseille Université, LISA, EA4672, Équipe METICA, 13397 Marseille cedex 20, France. Electronic address: nabilsemmar@yahoo.fr.
authors.forename: N
authors.initials: N
authors.lastname: Semmar
authors.affiliation: Aix-Marseille Université, LISA, EA4672, Équipe METICA, 13397 Marseille cedex 20, France; Biochemistry Laboratory, LR12ES05 'Nutrition-Functional Food & Vascular Health', USCR Mass Spectrometry, Faculty of Medicine, University of Monastir, Tunisia; Institut de l'Olivier, Unité Technologie et Qualité, BP 1087, 3018 Sfax, Tunisia.
authors.forename: S
authors.initials: S
authors.lastname: Laroussi-Mezghani
authors.affiliation: Institut de l'Olivier, Unité Technologie et Qualité, BP 1087, 3018 Sfax, Tunisia.
authors.forename: N
authors.initials: N
authors.lastname: Grati-Kamoun
authors.affiliation: Biochemistry Laboratory, LR12ES05 'Nutrition-Functional Food & Vascular Health', USCR Mass Spectrometry, Faculty of Medicine, University of Monastir, Tunisia.
authors.forename: M
authors.initials: M
authors.lastname: Hammami
authors.affiliation: Aix-Marseille Université, LISA, EA4672, Équipe METICA, 13397 Marseille cedex 20, France.
authors.forename: J
authors.initials: J
authors.lastname: Artaud
mesh_terms: D002849:Chromatography, Gas / Q000379:methods*; D005227:Fatty Acids / Q000032:analysis*; D008962:Models, Theoretical; D000069463:Olive Oil / Q000737:chemistry*
chemical_list: D005227:Fatty Acids; D000069463:Olive Oil
keywords: Blend authentication; Discriminant analysis; Fatty acids; Mixture design; Optimization; Simplex; Traceability; Tunisian olive oils