A model combining agronomic and weather factors to predict occurrence of deoxynivalenol in durum wheat kernels

Autor:	B. Barrier-Guillot, F. Piraux, E. Gourdain
Rok vydání:	2011
Předmět:	Critical factors Public Health Environmental and Occupational Health Biology Toxicology Field survey Tillage Crop chemistry.chemical_compound Food chain Agronomy chemistry European commission Mycotoxin Weather factors Food Science
Zdroj:	World Mycotoxin Journal. 4:129-139
ISSN:	1875-0796 1875-0710
DOI:	10.3920/wmj2009.1190
Popis:	Deoxynivalenol (DON) produced by Fusarium graminearum in durum wheat is a major issue for the French food chain. Since this cereal is exclusively used for human consumption, each batch of grain marketed for first-stage processing must comply with the DON legal limit of 1,750 µg/kg set by the European Commission. As a response to this regulation, we have started a study to identify factors affected the DON content in durum wheat kernels. This study has been made by exploiting data from a field survey started in 2001 in French durum wheat producing regions. Over 700 field samples were harvested and grains were analysed for their DON content. For each field, agronomic parameters and weather conditions during flowering were recorded. The study of these parameters has led to the development of decision-making tools to help farmers manage the risk of DON contamination in the field. The first stage of the work was to identify critical factors involved in DON content, these being the previous crop, the tillage practices and the susceptibility of the wheat variety to Fusarium. The combination of these three factors delimits different crop systems on a DON risk assessment tool which classifies risk categories defined by their risk level expressed as a percentage probability of exceeding the DON legal limit (from 3% to 60%). Nevertheless, the main factors involved in Fusarium infection and DON production are the weather conditions prevailing during wheat flowering. The second stage was to take weather factors into consideration to develop a DON-content predictive model. The main objective of the model is to predict DON content in grain at harvest time according to the crop system and weather for the field. For users, in 85% of cases, the model accurately predicted a DON content below or above the legal limit.
Databáze:	OpenAIRE
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