Discrimination of Quality and Geographical Origin of Extra Virgin Olive Oil by S3 Device with Metal Oxides Gas Sensors

Bhandari, Manohar Prasad; Núñez-Carmona, Estefanía; Abbatangelo, Marco; Sberveglieri, Veronica; Duina, Giorgio; Malla, Rajani; Comini, Elisabetta; Sberveglieri, Giorgio

doi:10.3390/proceedings2131061

Cited by 12 publications

(10 citation statements)

References 6 publications

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“…Several approaches based on chemical analysis have been proposed for EVOO traceability [8,9,10,11,12], which are useful to discover some types of macroscopic adulteration, such as the addition of oil from other species. However, they present some limits due to the difficulty in identifying the olive varieties used for oil production.…”

Section: Introductionmentioning

confidence: 99%

A Robust DNA Isolation Protocol from Filtered Commercial Olive Oil for PCR-Based Fingerprinting

Piarulli¹,

Savoia²,

Taranto³

et al. 2019

Foods

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Extra virgin olive oil (EVOO) has elevated commercial value due to its health appeal, desirable characteristics and quantitatively limited production, and thus it has become an object of intentional adulteration. As EVOOs on the market might consist of a blend of olive varieties or sometimes even of a mixture of oils from different botanical species, an array of DNA-fingerprinting methods have been developed to check the varietal composition of the blend. Starting from a comparison between publicly available DNA extraction protocols, we set up a timely, low-cost, reproducible and effective DNA isolation protocol, which allows an adequate amount of DNA to be recovered even from commercial filtered EVOOs. Then, in order to verify the effectiveness of the DNA extraction protocol herein proposed, we applied PCR-based fingerprinting methods starting from the DNA extracted from three EVOO samples of unknown composition. In particular, genomic regions harboring nine simple sequence repeats (SSRs) and eight genotyping-by-sequencing-derived single nucleotide polymorphism (SNP) markers were amplified for authentication and traceability of the three EVOO samples. The whole investigation strategy herein described might favor producers in terms of higher revenues and consumers in terms of price transparency and food safety.

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Section: Introductionmentioning

confidence: 99%

A Robust DNA Isolation Protocol from Filtered Commercial Olive Oil for PCR-Based Fingerprinting

Piarulli¹,

Savoia²,

Taranto³

et al. 2019

Foods

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“…The state-of-the-art of S3 was completely designed, developed, and validated at the SENSOR Lab (University of Brescia, Brescia, Italy) in collaboration with Nano Sensor Systems (NASYS) s.r.l., a spin-off of the University of Brescia, Italy. It has been successfully applied in some selected applications [21,22,23,24,25,26,27]. The S3 system consists of a pneumatic part, an electronic part, an incubated sensor chamber housing an array of eight MOX gas sensors, and an online data acquisition and processing app.…”

Section: Methodsmentioning

confidence: 99%

Multidisciplinary Approach to Characterizing the Fingerprint of Italian EVOO

et al. 2019

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Extra virgin olive oil (EVOO) is characterized by its aroma and other sensory attributes. These are determined by the geographical origin of the oil, extraction process, place of cultivation, soil, tree varieties, and storage conditions. In the present work, an array of metal oxide gas sensors (called S3), in combination with the SPME-GC-MS technique, was applied to the discrimination of different types of olive oil (phase 1) and to the identification of four varieties of Garda PDO extra virgin olive oils coming from west and east shores of Lake Garda (phase 2). The chemical analysis method involving SPME-GC-MS provided a complete volatile component of the extra virgin olive oils that was used to relate to the S3 multisensory responses. Furthermore, principal component analysis (PCA) and k-Nearest Neighbors (k-NN) analysis were carried out on the set of data acquired from the sensor array to determine the best sensors for these tasks and to assess the capability of the system to identify various olive oil samples. k-NN classification rates were found to be 94.3% and 94.7% in the two phases, respectively. These first results are encouraging and show a good capability of the S3 instrument to distinguish different oil samples.

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“…The VOCs analysis technologies have wide application, and volatile components in Zhejiang rosy vinegar were analysed by headspace-solid phase microextraction gas chromatography–mass spectrometry (HS-SPME/GC–MS) [ 3 ], phenolic compounds in the sugarcane vinegar were analyzed by ultra-high pressure liquid chromatography tandem mass spectrometry (UPLC-MS) [ 4 ], aroma extract dilution analysis in the Shanxi vinegars before and after aging were both analyzed by GC-MS and gas chromatography-olfactometry (GC-O) [ 5 ], and the volatomic signature of Tinta Negra wines were analysis by liquid-liquid microextraction combined with gas chromatography–ion trap mass spectrometry (LLME/GC–ITMS) [ 6 ], etc. These methods, however, usually are complicated, time-consuming or costly, thereby necessitating a non-destructive and fast techniques, such as electronic tongue and electronic nose-based [ 7 ], whereby efficient non-destructive techniques are used to simplify the process of distinguishing different samples, although the reliability and accuracy of their results was challenged. Rakow and Suslick [ 8 ] firstly introduced the utilization of sensor array in the olfactory visualization system by exposing VOCs to be detected.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Non-Invasive Testing of Vinegar Storage Time by Olfaction Visualization System and Volatile Organic Compounds Analysis

Hao

Lin

Song

et al. 2021

Foods

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An olfactory visualization system conducts a qualitative or quantitative analysis of volatile organic compounds (VOCs) by utilizing the sensor array made of color sensitive dyes. The reaction chamber is important to the sensor array’s sufficient and even exposure to VOCs. In the current work, a reaction chamber with an arc baffle embedded in the front of the air inlet for drainage effect was designed. The velocity of field and particle distribution of flow field in the reaction chamber was simulated by COMSOL Multiphysics. Through repeated simulation, the chamber achieved optimal result when the baffle curvature was 3.1 and the vertical distance between the baffle front end and the air inlet was 1.6 cm. Under the new reaction chamber, principal component analysis (PCA) and linear discriminant analysis (LDA) were employed to identify vinegar samples with different storage time through analyzing their VOCs. The LDA model achieved optimal performance when 8 principal components (PCs) were used, and the recognition rate was 95% in both training and prediction sets. The new reaction chamber could improve the stability and precision of an olfactory visualization system for VOCs analysis, and achieve the accurate differentiation and rapid discrimination of Zhenjiang vinegar with different storage time.

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Discrimination of Quality and Geographical Origin of Extra Virgin Olive Oil by S3 Device with Metal Oxides Gas Sensors

Cited by 12 publications

References 6 publications

A Robust DNA Isolation Protocol from Filtered Commercial Olive Oil for PCR-Based Fingerprinting

A Robust DNA Isolation Protocol from Filtered Commercial Olive Oil for PCR-Based Fingerprinting

Multidisciplinary Approach to Characterizing the Fingerprint of Italian EVOO

Simulation and Non-Invasive Testing of Vinegar Storage Time by Olfaction Visualization System and Volatile Organic Compounds Analysis

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