A Weather Data-Based System for Predicting Mycotoxin Contamination in Cereals

Certain weather conditions can lead to increased mycotoxin levels during grain harvest. This, in turn, can result in elevated levels in feed or food products, which is why a contaminated harvest may only be partially usable or require specific treatment before being used for production. Early countermeasures are essential to prevent high pollutant levels, and it is crucial to assess the contamination at the time of harvest based on the current situation. By combining weather data with data from experimental grain cultivation or other mycotoxin measurement results, mathematical models can be developed to estimate mycotoxin contamination early. This aims to enable grain producers to respond promptly to the conditions and potentially reduce contamination in the grain through appropriate countermeasures. An example of such a countermeasure could be an earlier harvest. Additionally, it will be analyzed whether it is possible to make predictions for new cultivation sites where no historical measurement data on mycotoxin contamination is available.