The aim of this study was to develop a prototype simple predictive system for aflatoxin B1 contamination in maize
based on meteorological data. A database was developed with meteorological data and aflatoxin B1 contamination
level of maize samples collected over a five-year period. All data were georeferenced. An aridity index was computed
to summarise meteorological conditions and was used to estimate the probability of aflatoxin B1 contamination
running a logistic regression. Relevant differences were found between years both for meteorology and aflatoxin
B1 contamination. North Italy is not arid and conditions for Aspergillus flavus development and aflatoxin B1
contamination of maize do not commonly occur. Nevertheless, arid areas were found in some years, and favourable
conditions for aflatoxin B1 production were confirmed by maize kernels surveys. The aridity index is a good indicator
to summarise meteorological conditions being significantly correlated to maize kernels contamination at harvest.
The logistic regression gave acceptable warning on aflatoxin B1 contamination in maize with 64% correct predictions
and 23% overestimates. Underestimates were 13%, but only half of these were contaminated with aflatoxin B1 above
5 μg/kg, the European legislative limit for maize to be subjected to sorting or other physical treatment before human
consumption or to be used as an ingredient in foodstuffs as well as for complete feedingstuffs for dairy animals.
First indications with this simple predictive system are available before mid-July with conclusive information in
early September, which is a good time to plan maize management pre- and post-harvest.
- aflatoxin B1
- geographic pattern
- logistic regression
- maize management
- predictive system