Evaluation of a multisensorial system for a rapid preliminary screening of the olive oil chemical compounds in an industrial process

Abstract

In this study, a sensory system, named BIONOTE, based on gas and liquid analyses was used to analyse the headspace of olive oil samples obtained at the end of the extraction process for a preliminary screening of the volatile and phenolic compounds. Olive oil samples were obtained using different olive paste conditioning systems, including microwave and megasound machines at different processing time. The same olives batch was used for the entire test. BIONOTE showed the ability to discriminate between 64 virgin olive oils originated from different technologies or by using different process parameters, as demonstrated by the partial least square discriminant analysis (PLS-DA) models calculated. The percentage of correct classification in different conditions are in a range from 92.19% to 100%. In addition, the research shown that the multisensorial system can provide a preliminary estimation of some volatile and phenolic compounds concentrations detected by laboratory analysis. Data analysis has been performed using multivariate data analysis techniques: PLS-DA cross validation via leave one out criterion. Future perspectives are to further develop BIONOTE in order to increase the number of detected chemical compounds and finally to include the mathematical models obtained in the BIONOTE microcontroller for a rapid chemical characterization of olive oil in the mill.