Literature DB >> 26619315

Rapid prediction of ochratoxin A-producing strains of Penicillium on dry-cured meat by MOS-based electronic nose.

Vincenzo Lippolis1, Massimo Ferrara2, Salvatore Cervellieri3, Anna Damascelli4, Filomena Epifani5, Michelangelo Pascale6, Giancarlo Perrone7.   

Abstract

The availability of rapid diagnostic methods for monitoring ochratoxigenic species during the seasoning processes for dry-cured meats is crucial and constitutes a key stage in order to prevent the risk of ochratoxin A (OTA) contamination. A rapid, easy-to-perform and non-invasive method using an electronic nose (e-nose) based on metal oxide semiconductors (MOS) was developed to discriminate dry-cured meat samples in two classes based on the fungal contamination: class P (samples contaminated by OTA-producing Penicillium strains) and class NP (samples contaminated by OTA non-producing Penicillium strains). Two OTA-producing strains of Penicillium nordicum and two OTA non-producing strains of Penicillium nalgiovense and Penicillium salamii, were tested. The feasibility of this approach was initially evaluated by e-nose analysis of 480 samples of both Yeast extract sucrose (YES) and meat-based agar media inoculated with the tested Penicillium strains and incubated up to 14 days. The high recognition percentages (higher than 82%) obtained by Discriminant Function Analysis (DFA), either in calibration and cross-validation (leave-more-out approach), for both YES and meat-based samples demonstrated the validity of the used approach. The e-nose method was subsequently developed and validated for the analysis of dry-cured meat samples. A total of 240 e-nose analyses were carried out using inoculated sausages, seasoned by a laboratory-scale process and sampled at 5, 7, 10 and 14 days. DFA provided calibration models that permitted discrimination of dry-cured meat samples after only 5 days of seasoning with mean recognition percentages in calibration and cross-validation of 98 and 88%, respectively. A further validation of the developed e-nose method was performed using 60 dry-cured meat samples produced by an industrial-scale seasoning process showing a total recognition percentage of 73%. The pattern of volatile compounds of dry-cured meat samples was identified and characterized by a developed HS-SPME/GC-MS method. Seven volatile compounds (2-methyl-1-butanol, octane, 1R-α-pinene, d-limonene, undecane, tetradecanal, 9-(Z)-octadecenoic acid methyl ester) allowed discrimination between dry-cured meat samples of classes P and NP. These results demonstrate that MOS-based electronic nose can be a useful tool for a rapid screening in preventing OTA contamination in the cured meat supply chain.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Dry-cured meat; Electronic nose; Metal oxide sensors; Penicillium nordicum; Rapid method

Mesh:

Substances:

Year:  2015        PMID: 26619315     DOI: 10.1016/j.ijfoodmicro.2015.11.011

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  5 in total

Review 1.  Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges.

Authors:  Huaying Zhou; Dehan Luo; Hamid GholamHosseini; Zhong Li; Jiafeng He
Journal:  Sensors (Basel)       Date:  2017-05-09       Impact factor: 3.576

2.  Predicting the growth situation of Pseudomonas aeruginosa on agar plates and meat stuffs using gas sensors.

Authors:  Xinzhe Gu; Ye Sun; Kang Tu; Qingli Dong; Leiqing Pan
Journal:  Sci Rep       Date:  2016-12-12       Impact factor: 4.379

3.  Chemometric Analysis of the Volatile Compounds Generated by Aspergillus carbonarius Strains Isolated from Grapes and Dried Vine Fruits.

Authors:  Zhan Cheng; Menghua Li; Philip J Marriott; Xiaoxu Zhang; Shiping Wang; Jiangui Li; Liyan Ma
Journal:  Toxins (Basel)       Date:  2018-02-06       Impact factor: 4.546

4.  Detection of bitterness and astringency of green tea with different taste by electronic nose and tongue.

Authors:  Guangyu Zou; Yanzhong Xiao; Miaosen Wang; Hongmei Zhang
Journal:  PLoS One       Date:  2018-12-31       Impact factor: 3.240

Review 5.  The Existing Methods and Novel Approaches in Mycotoxins' Detection.

Authors:  Edyta Janik; Marcin Niemcewicz; Marcin Podogrocki; Michal Ceremuga; Leslaw Gorniak; Maksymilian Stela; Michal Bijak
Journal:  Molecules       Date:  2021-06-29       Impact factor: 4.411

  5 in total

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