A ready-to-use portable VIS–NIR spectroscopy device to assess superior EVOO quality

Abstract

Extra virgin olive oil (EVOO) represents one of the first-choice products made in Italy for its high quality and use in the Mediterranean diet. The aim of this study was to evaluate the effectiveness of a portable VIS–NIR open source spectroscopic system coupled with an artificial intelligence model and compared to panel tests for the determination of EVOOs quality. The quality of 203 oil samples was determined through panel tests and spectrophotometric analysis with a VIS–NIR instrument (740–1070 nm). The spectral data were processed through an artificial intelligence algorithm. On the base of the Sensory Evaluation, the oil samples were divided into two classes: “Superior” and “Standard” quality, respectively. The artificial neural network (ANN) model with an external test showed a correct classification percentage of 99%. Both tested methods MANOVA and ANN showed that the most important spectral wavelengths for quality determination reside in the range 890–980 nm. These wavelengths are closely related to the quality of the fruit being ground. As a result, a clear and explicit link between the fruit quality status and the quality of the obtained EVOO emerges. The combined use of panel testing and VIS–NIR spectroscopy could be a useful tool for determining the quality of EVOO and, in a reverse-engineer perspective, the open-source VIS–NIR device allows to predict the EVOO quality given the average fruit quality status in the field.