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.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2022 The Author(s).)