Predictive models for assessing the risk of Fusarium pseudograminearum mycotoxin contamination in post-harvest wheat with multi-parameter integrated sensors

Reliable prediction of the risk of mycotoxin contamination in post-harvest wheat will aid in improvement of the quality and safety. To establish the relationship between Fusarium pseudograminearum mycotoxins and CO(2) production, changes in their respective concentrations were monitored for the artificial contamination of wheat under different values of water activities (0.84 a(w), 0.92 a(w), and 0.97 a(w)) and temperatures (20 ℃, 25 ℃, and 30 ℃). Water activity played a significant role in all these processes. CO(2) concentration together with moisture content and temperature were used as the main parameters to establish DON and ZEN contamination prediction models. The prediction accuracy for DON was 98.15 % (R(2) = 0.990) and 90.74 % for ZEN (R(2) = 0.982). These models were combined with T/RH/MC/CO(2) multi-parameter integrated sensors to form an early warning system, which offers a great prospect to minimise the risk of DON/ZEN contamination in post-harvest wheat.