Objective
Deoxynivalenol (DON) is a fungal toxin particularly associated with cereals. Contamination by DON is of concern for crops grown in areas whose climates favour mould formation, notably, North America and northern Europe. Discrepancies of 2 orders of magnitude in the results of laboratories monitoring DON have been recorded in recent international studies. The project set out to improve the reliability of the methods and to provide blank and contaminated maize and wheat reference materials (RM).
Four intercomparisons of methods have been made to reduce the major sources of errors. A pair of wheat and a pair of maize reference materials have been prepared. They consist of naturally contaminated samples having low levels close to the recommended (voluntary) action limits, and samples having low levels to provide a means of checking analytical background and recovery efficiency. Certification measurements were made by 8 laboratories using a variety of extraction and clean up procedures with high performance liquid chromatography (HPLC) as the final step. The certified values of DON (mg/kg) were as follows:
RM number 377: maize flour low level < 0.05;
RM number 378: maize flour high level = 0.43 (+/-0.04);
RM number 379: wheat flour high level = 0.67 (+/-0.02);
RM number 396: wheat flour low level < 0.05.
DON is a fungal toxin particularly associated with cereals. In extreme cases, DON in mouldy grain has caused serious human illness. The presence of DON in grain may lead to feed-refusal by farm animals.
Contamination by DON is of concern for crops grown in areas whose climates favour mould formation, notably, north-America and northern Europe. Discrepancies of two orders of magnitude in the results of laboratories have been recorded in recent international studies. The objective of the project was to improve the reliability of the methods and to provide blank and contaminated maize and wheat RMs.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Topic(s)
Data not availableCall for proposal
Data not availableFunding Scheme
CSC - Cost-sharing contractsCoordinator
NR4 7UQ Norwich
United Kingdom