Literature DB >> 29577312

Rapid prediction of deoxynivalenol contamination in wheat bran by MOS-based electronic nose and characterization of the relevant pattern of volatile compounds.

Vincenzo Lippolis1, Salvatore Cervellieri1, Anna Damascelli1, Michelangelo Pascale1, Annalisa Di Gioia1,2, Francesco Longobardi2, Annalisa De Girolamo1.   

Abstract

BACKGROUND: Deoxynivalenol (DON) is a mycotoxin, mainly produced by Fusarium sp., most frequently occurring in cereals and cereal-based products. Wheat bran refers to the outer layers of the kernel, which has a high risk of damage due to chemical hazards, including mycotoxins. Rapid methods for DON detection in wheat bran are required.
RESULTS: A rapid screening method using an electronic nose (e-nose), based on metal oxide semiconductor sensors, has been developed to distinguish wheat bran samples with different levels of DON contamination. A total of 470 naturally contaminated wheat bran samples were analyzed by e-nose analysis. Wheat bran samples were divided in two contamination classes: class A ([DON] ≤ 400 µg kg-1 , 225 samples) and class B ([DON] > 400 µg kg-1 , 245 samples). Discriminant function analysis (DFA) classified wheat bran samples with good mean recognizability in terms of both calibration (92%) and validation (89%). A pattern of 17 volatile compounds of wheat bran samples that were associated (positively or negatively) with DON content was also characterized by HS-SPME/GC-MS.
CONCLUSIONS: These results indicate that the e-nose method could be a useful tool for high-throughput screening of DON-contaminated wheat bran samples for their classification as acceptable / rejectable at contamination levels close to the EU maximum limit for DON, reducing the number of samples to be analyzed with a confirmatory method.
© 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Entities:  

Keywords:  deoxynivalenol; discriminant function analysis; electronic nose; metal oxide sensors; volatile compounds; wheat bran

Mesh:

Substances:

Year:  2018        PMID: 29577312     DOI: 10.1002/jsfa.9028

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  6 in total

Review 1.  Application of electronic nose as a non-invasive technique for odor fingerprinting and detection of bacterial foodborne pathogens: a review.

Authors:  Ernest Bonah; Xingyi Huang; Joshua Harrington Aheto; Richard Osae
Journal:  J Food Sci Technol       Date:  2019-11-05       Impact factor: 2.701

2.  Volatile Organic Compounds Emitted by Aspergillus flavus Strains Producing or Not Aflatoxin B1.

Authors:  Laurie Josselin; Caroline De Clerck; Marthe De Boevre; Antonio Moretti; M Haïssam Jijakli; Hélène Soyeurt; Marie-Laure Fauconnier
Journal:  Toxins (Basel)       Date:  2021-10-06       Impact factor: 4.546

3.  Rapid, Sensitive On-Site Detection of Deoxynivalenol in Cereals Using Portable and Reusable Evanescent Wave Optofluidic Immunosensor.

Authors:  Yanping Liu; Yuyang Chen; Wenjuan Xu; Dan Song; Xiangzhi Han; Feng Long
Journal:  Int J Environ Res Public Health       Date:  2022-03-22       Impact factor: 3.390

4.  Electronic Nose for the Rapid Detection of Deoxynivalenol in Wheat Using Classification and Regression Trees.

Authors:  Marco Camardo Leggieri; Marco Mazzoni; Terenzio Bertuzzi; Maurizio Moschini; Aldo Prandini; Paola Battilani
Journal:  Toxins (Basel)       Date:  2022-09-03       Impact factor: 5.075

5.  Enhancing the Discrimination Ability of a Gas Sensor Array Based on a Novel Feature Selection and Fusion Framework.

Authors:  Changjian Deng; Kun Lv; Debo Shi; Bo Yang; Song Yu; Zhiyi He; Jia Yan
Journal:  Sensors (Basel)       Date:  2018-06-12       Impact factor: 3.576

Review 6.  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

  6 in total

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