| Title: | Rapid prediction of deoxynivalenol contamination in wheat bran by MOS-based electronic nose and characterization of the relevant pattern of volatile compounds |
| Author(s): | Lippolis V; Cervellieri S; Damascelli A; Pascale M; Di Gioia A; Longobardi F; De Girolamo A; |
| Address: | "Institute of Sciences of Food Production (ISPA), CNR-National Research Council of Italy, Bari, Italy. Dipartimento di Chimica, Universita di Bari 'Aldo Moro', Bari, Italy" |
| ISSN/ISBN: | 1097-0010 (Electronic) 0022-5142 (Linking) |
| 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 microg 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. (c) 2018 Society of Chemical Industry" |
| Keywords: | Dietary Fiber/*analysis Electronic Nose/*statistics & numerical data Food Analysis/instrumentation/*methods Food Contamination/*analysis Gas Chromatography-Mass Spectrometry Mycotoxins/*analysis Trichothecenes/*analysis Volatile Organic Compounds/*analysi; |
| Notes: | "MedlineLippolis, Vincenzo Cervellieri, Salvatore Damascelli, Anna Pascale, Michelangelo Di Gioia, Annalisa Longobardi, Francesco De Girolamo, Annalisa eng Evaluation Study England 2018/03/27 J Sci Food Agric. 2018 Oct; 98(13):4955-4962. doi: 10.1002/jsfa.9028. Epub 2018 May 13" |
