Characterization of 'Olivastro di Bucchianico cv' extra virgin olive oils and its recognition by HS-GC-IMS.

BACKGROUND: Single cultivar 'Olivastro di Bucchianico' extra virgin olive oil is obtained from olives cultivated in a narrow area of the Abruzzo region, Italy. This cultivar is mostly present in the municipality of Bucchianico and in some neighbouring municipalities in the province of Chieti. There is very little research in the literature describing the morphological and chemical characteristics of this cultivar. RESULTS: A morphological characterization of the plant and the fruit was carried out. In addition, we characterized the chemical, physical-chemical and sensory properties of the extra virgin olive oil. The following analyses were conducted: free acidity, peroxide value, ultraviolet spectrophotometric indices, contents in fatty acid ethyl esters, waxes, tocopherols, fatty acids, triglycerides, sterols, alcohols, phenolic substances, volatile compounds and sensory profile. The analysis of the volatile compounds was performed using a headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) instrument connected to a nitrogen generator for carrier/drift gas production. CONCLUSION: The results of the chemical analyses showed good levels of nutraceutical components in the oils, which were found to be organoleptically well balanced with medium values of fruity, bitter and pungent. The HS-GC-IMS method based on the analysis of 15 volatile molecules might be a useful tool for a chemometric discrimination of the varietal origin for the oils under investigation. © 2021 Society of Chemical Industry.

An HS-GC-IMS Method for the Quality Classification of Virgin Olive Oils as Screening Support for the Panel Test.

Sensory evaluation, carried out by panel tests, is essential for quality classification of virgin olive oils (VOOs), but is time consuming and costly when many samples need to be assessed; sensory evaluation could be assisted by the application of screening methods. Rapid instrumental methods based on the analysis of volatile molecules might be considered interesting to assist the panel test through fast pre-classification of samples with a known level of probability, thus increasing the efficiency of quality control. With this objective, a headspace gas chromatography-ion mobility spectrometer (HS-GC-IMS) was used to analyze 198 commercial VOOs (extra virgin, virgin and lampante) by a semi-targeted approach. Different partial least squares-discriminant analysis (PLS-DA) chemometric models were then built by data matrices composed of 15 volatile compounds, which were previously selected as markers: a first approach was proposed to classify samples according to their quality grade and a second based on the presence of sensory defects. The performance (intra-day and inter-day repeatability, linearity) of the method was evaluated. The average percentages of correctly classified samples obtained from the two models were satisfactory, namely 77% (prediction of the quality grades) and 64% (prediction of the presence of three defects) in external validation, thus demonstrating that this easy-to-use screening instrumental approach is promising to support the work carried out by panel tests.