title: Identification of olive oil sensory defects by multivariate analysis of mid infrared spectra.
abstract: Mid-infrared (MIR) spectra (4000-600 cm(-1)) of olive oils were analyzed using chemometric methods to identify the four main sensorial defects, musty, winey, fusty and rancid, previously evaluated by an expert sensory panel. Classification models were developed using partial least squares discriminant analysis (PLS-DA) to distinguish between extra-virgin olive oils (defect absent) and lower quality olive oils (defect present). The most important spectral ranges responsible for the discrimination were identified. PLS-DA models were able to discriminate between defective and high quality oils with predictive abilities around 87% for the musty defect and around 77% for winey, fusty and rancid defects. This methodology advances instrumental determination of results previously only achievable with a human test panel.
authors.affiliation: Instrumental Sensometry Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain.
authors.forename: Eva
authors.initials: E
authors.lastname: Borràs
authors.affiliation: Instrumental Sensometry Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain.
authors.forename: Montserrat
authors.initials: M
authors.lastname: Mestres
authors.affiliation: Instrumental Sensometry Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain.
authors.forename: Laura
authors.initials: L
authors.lastname: Aceña
authors.affiliation: Instrumental Sensometry Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain. Electronic address: olga.busto@urv.cat.
authors.forename: Olga
authors.initials: O
authors.lastname: Busto
authors.affiliation: Chemometrics, Qualimetrics and Nanosensors Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain.
authors.forename: Joan
authors.initials: J
authors.lastname: Ferré
authors.affiliation: Chemometrics, Qualimetrics and Nanosensors Group, Department of Analytical Chemistry and Organic Chemistry, Universitat Rovira i Virgili, Campus Sescelades, 43007 Tarragona, Spain.
authors.forename: Ricard
authors.initials: R
authors.lastname: Boqué
authors.affiliation: Official Taste Panel of Virgin Olive Oil in Catalonia, Reus, Spain.
authors.forename: Angels
authors.initials: A
authors.lastname: Calvo
mesh_terms: D016002:Discriminant Analysis; D006801:Humans; D016018:Least-Squares Analysis; D015999:Multivariate Analysis; D000069463:Olive Oil / Q000737:chemistry*; D010938:Plant Oils / Q000737:chemistry; D011786:Quality Control; D013055:Spectrophotometry, Infrared / Q000379:methods*; D013649:Taste
chemical_list: D000069463:Olive Oil; D010938:Plant Oils
keywords: Classification; Mid-infrared spectroscopy; Multivariate analysis; Partial least squares discriminant analysis (PLS-DA); Sensory analysis; Virgin olive oil