Evaluation of extra-virgin olive oils shelf life using an electronic tongue-chemometric approach

Physicochemical quality parameters, olfactory and gustatoryretronasal positive sensations of extra-virgin olive oils vary during storage leading to a decrease in the overall quality. Olive oil quality decline may prevent the compliance of olive oil quality with labeling and significantly reduce shelf life, resulting in important economic losses and negatively condition the consumer confidence. The feasibility of applying an electronic tongue to assess olive oils usual commercial light storage conditions and storage time was evaluated and compared with the discrimination potential of physicochemical or positive olfactory/gustatory sensorial parameters. Linear discriminant models, based on subsets of 58 electronic tongue sensor signals, selected by the meta-heuristic simulated annealing variable selection algorithm, allowed the correct classification of olive oils according to the light exposition conditions and/or storage time (sensitivities and specificities for leave-one-out cross-validation: 8296 %). The predictive performance of the E-tongue approach was further evaluated using an external independent dataset selected using the KennardStone algorithm and, in general, better classification rates (sensitivities and specificities for external dataset: 67100 %) were obtained compared to those achieved using physicochemical or sensorial data. So, the work carried out is a proof-of-principle that the proposed electrochemical device could be a practical and versatile tool for, in a single and fast electrochemical assay, successfully discriminate olive oils with different storage times and/or exposed to different light conditions.The authors acknowledge the financial support from the strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRELCM funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia and under the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).info:eu-repo/semantics/publishedVersio

Olive Oil Characterization and Traceability

Olive oil is characterized by its high quality, health benefits, and high price compared to other edible oils, which results in a permanent problem of adulteration. In that context, the purpose of olive oil authentication is oriented not solely to the detection of possible adulteration but to the genuineness certification of the product with regard to different authenticity issues, such as geographical origin, extraction system, and olive cultivar variety. The most recent authentication issues not only require advanced analytical solutions, but they are also in need of a multivariate mathematical procedure for extracting information from a complex set of chemical data. Thus, this chapter starts by providing a complete description of the main mathematical procedures used in olive oil characterization. The contents include several types of multivariate statistical analyses (cluster analysis, factor analysis, multidimensional scaling, discriminant analysis), expert systems, and artificial neural network. The second half of the chapter is devoted to a critical review of the different authenticity issues, starting with the agronomic and pedoclimatic characteristics that influence olive oil chemical composition. Other authenticity issues are olive ripeness, extraction system, and botanical variety. All these issues determine the distinctive properties of olive oil produced in different geographical zones. Thus, another issue analyzed in this chapter is the geographical identification of olive oils to be implemented in a traceability system. Different geographical zones (Italy, Spain, Greece, and other countries from the Mediterranean basin) are considered in the chemical description of their olive oils. Finally, the last two sections are centered on the authentication of olive oil categories and the detection of other edible oils.Peer reviewe