Predicting deoxynivalenol in oats under conditions representing Scandinavian production regions

Abstract

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) between 0.84 and 0.88. Regressions of the same indices against DON concentrations in oat samples averaged for 11 × 11 km grids in farmers' fields in Sweden 2012-14 resulted in R 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 1000 μg kg 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 = 0.70 and a standard error of cross-validation (SECV) = 522 μg kg grain for the period 1 April-28 August in the construction of independent variables and R = 0.54 and SECV = 647 μg kg 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.

Modelling the Effects of Weather Conditions on Cereal Grain Contamination with Deoxynivalenol in the Baltic Sea Region

“…The dependent variable was the mean DON content in all oat deliveries to the grain trader Lantmännen from each particular grid. In cross-validated multivariate prediction models for the years 2012-2014, the percentage of correct classifications achieved in that study was around 85% [26]. A somewhat lower percentage of correct classifications (60-70%) was achieved by Xu et al [61] for a model predicting the DON content in wheat using logistic regression.…”

“…According to our studies, high values of either variable at germination, seedling growth/tillering, stem elongation/booting/heading and milk development/dough development/ripening is correlated with increased DON contamination. No correlation was seen between rainy and humid weather at flowering and DON contamination in oat grain, possibly because the flowering period in oats is longer and more difficult to identify than in wheat [26,64]. Rainy weather during the milk and dough development and ripening stages can increase the wetness of host tissue, favouring mycelial growth [26], explaining why high precipitation and RH at these stages can lead to increased DON contamination.…”

“…Field surveys conducted in Northern Europe suggest that the main producer of DON in cereals is F. graminearum, while F. culmorum plays a lesser role [8,17,[20][21][22][23][24][25]. As F. graminearum has become more prevalent, high DON concentrations in spring-sown cereals have also become more frequent and a clear correlation between F. graminearum and DON contamination in grain has been observed [15,17,23,26].…”

“…In a study in Sweden, Persson et al [26] used daily weather data for 11 km × 11 km grids to predict whether DON levels in oats would be below the maximum permissible limit of 1750 µg kg −1 . They calculated 14-day means for five weather variables (air temperature, relative humidity, wind direction, wind speed and cloud cover) and the total amount of precipitation in each 14-day period for the whole cultivation season.…”

“…Although some similarities can be found between countries, there are also region-specific differences. Even though there were attempts to develop models predicting DON contamination in Swedish crops [26,63], no modelling was done for data collected in Poland and Lithuania.…”