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Detection and quantification of ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose
Olligon AB, Uppsala, Sweden.
ODAL R&D, SE-531 87 Lidköping, Sweden.
Melacure Therapeutics AB, Uppsala Science Park, Uppsala, Sweden.
Department of Microbiology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
2002 (English)In: International Journal of Food Microbiology, ISSN 0168-1605, E-ISSN 1879-3460, Vol. 72, no 3, 203-214 p.Article in journal (Refereed) Published
Abstract [en]

Mycotoxin contamination of cereal grains can be detected and quantified using complex extraction procedures and analytical techniques. Normally, the grain odour, i.e. the presence of non-grain volatile metabolites, is used for quality classification of grain. We have investigated the possibility of using fungal volatile metabolites as indicators of mycotoxins in grain. Ten barley samples with normal odour, and 30 with some kind of off-odour were selected from Swedish granaries. The samples were evaluated with regard to moisture content, fungal contamination, ergosterol content, and levels of ochratoxin A (OA) and deoxynivalenol (DON). Volatile compounds were also analysed using both an electronic nose and gas chromatography combined with mass spectrometry (GC-MS). Samples with normal odour had no detectable ochratoxin A and average DON contents of 16 mug kg(-1) (range 0-80), while samples with off-odour had average OA contents of 76 mug kg(-1) (range 0-934) and DON contents of 69 mug kg(-1) (range 0-857). Data were evaluated by multivariate data analysis using projection methods such as principal component analysis (PCA) and partial least squares (PLS). The results show that it was possible to classify the OA level as below or above the maximum limit of 5 mug kg(-1) cereal grain established by the Swedish National Food Administration, and that the DON level could be estimated using PLS. Samples with OA levels below 5 mug kg(-1) had higher concentration of aldehydes (nonanal, 2-hexenal) and alcohols (1-penten-3-ol, 1-octanol). Samples with OA levels above 5 mug kg(-1) had higher concentrations of ketones (2-hexanone, 3-octanone). The GC-MS system predicted OA concentrations with a higher accuracy than the electronic nose, since the GC-MS misclassified only 3 of 37 samples and the electronic nose 7 of 37 samples. No correlation was found between odour and OA level, as samples with pronounced or strong off-odours had OA levels both below and above 5 mug kg(-1). We were able to predict DON levels in the naturally contaminated barley samples using the volatile compounds detected and quantified by either GC-MS or the electronic nose. Pentane, methylpyrazine, 3-pentanone, 3-octene-2-ol and isooctylacetate showed a positive correlation with DON, while ethylhexanol, pentadecane, toluene, 1-octanol, 1-nonanol, and 1-heptanol showed a negative correlation with DON. The root mean square error of estimation values for prediction of DON based on GC-MS and electronic nose data were 16 and 25 mug kg(-1) respectively.

Place, publisher, year, edition, pages
Elsevier, 2002. Vol. 72, no 3, 203-214 p.
Keyword [en]
ochratoxin A/DON prediction, fungal volatile compounds, mould, fungi, PCA, PLS, asymmetric data
National Category
Food Science Microbiology
Identifiers
URN: urn:nbn:se:oru:diva-52363DOI: 10.1016/S0168-1605(01)00685-7ISI: 000173701300002PubMedID: 11845819Scopus ID: 2-s2.0-0037022350OAI: oai:DiVA.org:oru-52363DiVA: diva2:971922
Available from: 2016-09-19 Created: 2016-09-19 Last updated: 2016-09-19Bibliographically approved

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CiteExportLink to record
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