Scientific Results

Rapid diagnosis of Enterobacteriaceae in vegetable soups by a metal oxide sensor based electronic nose

Year: 2015

Authors: Gobbi E., Falasconi M., Zambotti G., Sberveglieri V., Pulvirenti A., Sberveglieri G.

Autors Affiliation: Univ Brescia, Dept Mol & Translat Med, Viale Europa 11, I-25123 Brescia, Italy;‎ Univ Brescia, Dept Informat Engn, I-25123 Brescia, Italy;‎ CNR INO, SENSOR Lab, I-25123 Brescia, Italy;‎ Univ Modena & Reggio Emilia, Dept Life Sci Padiglione Besta, I-42122 Reggio Emilia, Italy;‎ Univ Brescia, AgriFood Lab, I-25123 Brescia, Italy

Abstract: A rapid protocol for the early diagnosis of microbial contamination of commercial food products by Electronic Nose is presented. Mixed vegetable soup samples are artificially contaminated by Enterobacter hormaechei and Escherichia coli and a large dataset of 584 samples, over two experimental campaigns, was analyzed by the electronic nose EOS507C based on a four metal oxide sensors array. Diagnosis of the contamination is obtained after 21 h and 18 h from the inoculation of E. hormaechei and E. coli respectively. EOS detection thresholds at 24h were as little as 8 cells/100 ml for E. hormaechei and 3 cells/100 ml for E. coli. The achieved LDA classification performance of contaminated samples was 98%. Also a significant correlation between the sensors responses and the inocula concentrations was obtained. Good long-term repeatability and reliability was demonstrated by comparing the results of the two experimental campaigns spanning for 14 months. The EOS resulted to fulfill all the main requirements of an ideal industrial screening system: specificity, sensitivity, early diagnosis, operational simplicity, reproducibility and cost effectiveness. (C) 2014 Elsevier B.V. All rights reserved.

Journal/Review: SENSORS AND ACTUATORS B-CHEMICAL

Volume: 207      Pages from: 1104  to: 1113

KeyWords: Electronic nose; Metal oxide sensors; Food spoilage; Enterobacter hormaechei; Escherichia coli; Vegetable soups
DOI: 10.1016/j.snb.2014.10.051

Citations: 42
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2021-10-24
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