Literature DB >> 33676677

Application of a lab-made electronic nose for extra virgin olive oils commercial classification according to the perceived fruitiness intensity.

Guilherme G Teixeira1, Luís G Dias2, Nuno Rodrigues1, Ítala M G Marx3, Ana C A Veloso4, José A Pereira1, António M Peres5.   

Abstract

An electronic nose, comprising nine metal oxide sensors, has been built aiming to classify olive oils according to the fruity intensity commercial grade (ripely fruity or light, medium and intense greenly fruity), following the European regulated complementary terminology. The lab-made sensor device was capable to differentiate standard aqueous solutions (acetic acid, cis-3-hexenyl, cis-3-hexen-1-ol, hexanal, 1-hexenol and nonanal) that mimicked positive sensations (e.g., fatty, floral, fruit, grass, green and green leaves attributes) and negative attributes (e.g., sour and vinegary defects), as well as to semi-quantitatively classify them according to the concentration ranges (0.05-2.25 mg/kg). For that, unsupervised (principal component analysis) and supervised (linear discriminant analysis: sensitivity of 92% for leave-one-out cross validation) classification multivariate models were established based on nine or six gas sensors, respectively. It was also showed that the built E-nose allowed differentiating/discriminating (sensitivity of 81% for leave-one-out cross validation) extra virgin olive oils according to the perceived intensity of fruitiness as ripely fruity, light, medium or intense greenly fruity. In conclusion, the gas sensor device could be used as a practical preliminary non-destructive tool for guaranteeing the correctness of olive oil fruitiness intensity labelling.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Electronic nose; Fruity intensity commercial grade; Linear discriminant analysis; Metal oxide sensors; Olive oil; Simulated annealing algorithm

Year:  2021        PMID: 33676677     DOI: 10.1016/j.talanta.2021.122122

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  2 in total

Review 1.  Progress of Research on the Application of Nanoelectronic Smelling in the Field of Food.

Authors:  Junjiang Sha; Chong Xu; Ke Xu
Journal:  Micromachines (Basel)       Date:  2022-05-18       Impact factor: 3.523

2.  Prediction of Fruity Aroma Intensity and Defect Presence in Virgin Olive Oil Using an Electronic Nose.

Authors:  Pablo Cano Marchal; Chiara Sanmartin; Silvia Satorres Martínez; Juan Gómez Ortega; Fabio Mencarelli; Javier Gámez García
Journal:  Sensors (Basel)       Date:  2021-03-25       Impact factor: 3.576

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.