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Sensors 2011, 11(5), 4899-4916; doi:10.3390/s110504899

Use of the Electronic Nose as a Screening Tool for the Recognition of Durum Wheat Naturally Contaminated by Deoxynivalenol: A Preliminary Approach

Università Telematica San Raffaele Roma, via di Val Cannuta, 247, 00166, Roma, Italy
Dipartimento di Scienze e Tecnologie Veterinarie per la Sicurezza Alimentare, Facoltà di Medicina Veterinaria, Università degli Studi di Milano, via Celoria, 10, 20133 Milano, Italy
Dipartimento di Prevenzione Veterinaria, Azienda Sanitaria Locale di Sondrio, via Stelvio, 35, 23100, Sondrio, Italy
Author to whom correspondence should be addressed.
Received: 6 April 2011 / Revised: 25 April 2011 / Accepted: 28 April 2011 / Published: 4 May 2011
(This article belongs to the Special Issue Bioinspired Sensor Systems)
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Fungal contamination and the presence of related toxins is a widespread problem. Mycotoxin contamination has prompted many countries to establish appropriate tolerance levels. For instance, with the Commission Regulation (EC) N. 1881/2006, the European Commission fixed the limits for the main mycotoxins (and other contaminants) in food. Although valid analytical methods are being developed for regulatory purposes, a need exists for alternative screening methods that can detect mould and mycotoxin contamination of cereal grains with high sample throughput. In this study, a commercial electronic nose (EN) equipped with metal-oxide-semiconductor (MOS) sensors was used in combination with a trap and the thermal desorption technique, with the adoption of Tenax TA as an adsorbent material to discriminate between durum wheat whole-grain samples naturally contaminated with deoxynivalenol (DON) and non-contaminated samples. Each wheat sample was analysed with the EN at four different desorption temperatures (i.e., 180 °C, 200 °C, 220 °C, and 240 °C) and without a desorption pre-treatment. A 20-sample and a 122-sample dataset were processed by means of principal component analysis (PCA) and classified via classification and regression trees (CART). Results, validated with two different methods, showed that it was possible to classify wheat samples into three clusters based on the DON content proposed by the European legislation: (a) non-contaminated; (b) contaminated below the limit (DON 1,750 μg/kg), with a classification error rate in prediction of 0% (for the 20-sample dataset) and 3.28% (for the 122-sample dataset). View Full-Text
Keywords: electronic nose; screening methods; durum wheat; deoxynivalenol; PCA; CART electronic nose; screening methods; durum wheat; deoxynivalenol; PCA; CART

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Campagnoli, A.; Cheli, F.; Polidori, C.; Zaninelli, M.; Zecca, O.; Savoini, G.; Pinotti, L.; Dell’Orto, V. Use of the Electronic Nose as a Screening Tool for the Recognition of Durum Wheat Naturally Contaminated by Deoxynivalenol: A Preliminary Approach. Sensors 2011, 11, 4899-4916.

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