Journal
WORLD MYCOTOXIN JOURNAL
Volume 1, Issue 4, Pages 449-456Publisher
WAGENINGEN ACADEMIC PUBLISHERS
DOI: 10.3920/WMJ2008.x043
Keywords
aflatoxin B-1; predictive system; logistic regression; geographic pattern; maize management
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Funding
- Ministry of Agriculture and Forestry Policy
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The aim of this study was to develop a prototype simple predictive system for aflatoxin B-1 contamination in maize based on meteorological data. A database was developed with meteorological data and aflatoxin B-1 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 B-1 contamination running a logistic regression. Relevant differences were found between years both for meteorology and aflatoxin B-1 contamination. North Italy is not arid and conditions for Aspergillus flavus development and aflatoxin B-1 contamination of maize do not commonly occur. Nevertheless, arid areas were found in some years, and favourable conditions for aflatoxin B-1 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 B-1 contamination in maize with 64% correct predictions and 23% overestimates. Underestimates were 13%, but only half of these were contaminated with aflatoxin B-1 above 5 mu g/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.
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