Predicting deoxynivalenol in oats under conditions representing Scandinavian production regions

Deoxynivalenol (DON) in cereals, produced by Fusarium fungi, cause poisoning in humans and animals. Fusarium infections in cereals are favoured by humid conditions. Host species are susceptible mainly during the anthesis stage. Infections are also positively correlated with a regional history of Fusarium infections, frequent cereal production and non-tillage field management practices. Here, previously developed process-based models based on relative air humidity, rain and temperature conditions, Fusarium sporulation, host phenology and mycelium growth in host tissue were adapted and tested on oats. Model outputs were used to calculate risk indices. Statistical multivariate models, where independent variables were constructed from weather data, were also developed. Regressions of the risk indices obtained against DON concentrations in field experiments on oats in Sweden and Norway 2012-14 had coefficient of determination values (R-2) between 0.84 and 0.88. Regressions of the same indices against DON concentrations in oat samples averaged for 11x11km grids in farmers' fields in Sweden 2012-14 resulted in R-2 values between 0.27 and 0.41 for randomly selected grids and between 0.31 and 0.62 for grids with average DON concentration above 1000gkg(-1) grain in the previous year. When data from all three years were evaluated together, a cross-validated statistical partial least squares model resulted in R-2=0.70 and a standard error of cross-validation (SECV)=522gkg(-1) grain for the period 1 April-28 August in the construction of independent variables and R-2=0.54 and SECV=647gkg(-1) grain for 1 April-23 June. Factors that were not accounted for in this study probably explain large parts of the variation in DON among samples and make further model development necessary before these models can be used practically. DON prediction in oats could potentially be improved by combining weather-based risk index outputs with agronomic factors.