C.J.H. Booij

Modeling Deoxynivalenol Contamination of Wheat in Northwestern Europe for Climate Change Assessments

Climate change will affect mycotoxin contamination of feed and food. Mathematical models for predicting mycotoxin concentrations in cereal grains are useful for estimating the impact of climate change on these toxins. The objective of the current study was to construct a descriptive model to estimate climate change impacts on deoxynivalenol (DON) contamination of mature wheat grown in northwestern Europe. Observational data from 717 wheat fields in Norway, Sweden, Finland, and The Netherlands were analyzed, including the DON concentrations in mature wheat, agronomical practices, and local weather. Multiple regression analyses were conducted, and the best set of explanatory variables, mainly including weather factors, was selected. The final model included the following variables: flowering date, length of time between flowering and harvest, wheat resistance to Fusarium infection, and several climatic variables related to relative humidity, temperature, and rainfall during critical stages of wheat cultivation. The model accounted for 50 % of the variance, which was sufficient to make this model useful for estimating the trends of climate change on DON contamination of wheat in northwestern Europe. Application of the model in possible climate change scenarios is illustrated.

Occurrence of Fusarium Head Blight species and Fusarium mycotoxins in winter wheat in the Netherlands in 2009

Most recent information on the occurrence of Fusarium Head Blight species and related mycotoxins in wheat grown in the Netherlands dates from 2001. This aim of this study was to investigate the incidence and levels of Fusarium Head Blight species and Fusarium mycotoxins, as well as their possible relationships, in winter wheat cultivated in the Netherlands in 2009. Samples were collected from individual fields of 88 commercial wheat growers. Samples were collected at harvest from 86 fields, and 2 weeks before the expected harvest date from 21 fields. In all, 128 samples, the levels of each of seven Fusarium Head Blight species and of 12 related mycotoxins were quantified. The results showed that F. graminearum was the most frequently observed species at harvest, followed by F. avenaceum and M. nivale. In the pre-harvest samples, only F. graminearum and M. nivale were relevant. The highest incidence and concentrations of mycotoxins were found for deoxynivalenol, followed by zearalenone and beauvericin, both pre-harvest and at harvest. Other toxins frequently found – for the first time in the Netherlands – included T-2 toxin, HT-2 toxin, and moniliformin. The levels of deoxynivalenol were positively related to F. graminearum levels, as well as to zearalenone levels. Other relationships could not be established. The current approach taken in collecting wheat samples and quantifying the presence of Fusarium Head Blight species and related mycotoxins is an efficient method to obtain insight into the occurrence of these species and toxins in wheat grown under natural environmental conditions. It is recommended that this survey be repeated for several years to establish inter-annual variability in both species composition and mycotoxin occurrence.

Modelling mycotoxin formation by Fusarium graminearum in maize in The Netherlands

The predominant species in maize in temperate climates is Fusarium graminearum, which produces the mycotoxins deoxynivalenol and zearalenone. Projected climate change is expected to affect Fusarium incidence and thus the occurrence of these mycotoxins. Predictive models may be helpful in determining trends in the levels of these mycotoxins with expected changing climatic conditions. The aim of this study was to develop a model describing fungal infection and subsequent growth as well as the formation of deoxynivalenol and zearalenone in maize in The Netherlands. For this purpose, a published Italian model was used as a starting point. This model is a mixed empiric–mechanistic model that describes fungal infection during silking (based on wind speed and rainfall) and subsequent germination, growth and toxin formation (depending on temperature and water availability). Model input uses weather parameters and crop management factors, such as maize hybrid, sowing date, flowering period and harvest date. Model parameter values were obtained by fitting these parameters to deoxynivalenol and zearalenone measurements in Dutch maize, using national mycotoxin data from the years 2002–2007. The results showed that the adapted model is capable of describing the trend in average deoxynivalenol and zearalenone levels over these years. Validation with external data is needed to verify model outcomes. It is expected that the current model can be used to estimate the effect of projected climate change on trends in deoxynivalenol and zearalenone levels in the coming years.

Expert Study to Select Indicators of the Occurrence of Emerging Mycotoxin Hazards

This article describes a Delphi-based expert judgment study aimed at the selection of indicators to identify the occurrence of emerging mycotoxin hazards related to Fusarium spp. in wheat supply chains. A panel of 29 experts from 12 European countries followed a holistic approach to evaluate the most important indicators for different chain stages (growth, transport and storage, and processing) and their relative importance. After three e-mailing rounds, the experts reached consensus on the most important indicators for each of the three stages: wheat growth, transport and storage, and processing. For wheat growth, these indicators include: relative humidity/rainfall, crop rotation, temperature, tillage practice, water activity of the kernels, and crop variety/cultivar. For the transport and storage stage, they include water activity in the kernels, relative humidity, ventilation, temperature, storage capacity, and logistics. For wheat processing, indicators include quality data, fraction of the cereal used, water activity in the kernels, quality management and traceability systems, and carryover of contamination. The indicators selected in this study can be used in an identification system for the occurrence of emerging mycotoxin hazards in wheat supply chains. Such a system can be used by risk managers within governmental (related) organizations and/or the food and feed industry in order to react proactively to the occurrence of these emerging mycotoxins.