Modelling climatic risks of aflatoxin contamination in maize
Y. S. Chauhan A B , G. C. Wright A and N. C. Rachaputi AA Queensland Department of Primary Industries and Fisheries, Delivery, Plant Science, PO Box 23, Kingaroy, Qld 4610, Australia.
B Corresponding author. Email: yash.chauhan@dpi.qld.gov.au
Australian Journal of Experimental Agriculture 48(3) 358-366 https://doi.org/10.1071/EA06101
Submitted: 15 March 2006 Accepted: 29 June 2007 Published: 4 February 2008
Abstract
Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM’s maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.
Additional keywords: Zea mays L.
Acknowledgements
The authors are thankful to Barry Blaney and Lisa Bricknell for providing data for validating the model. We thank the Grains Research and Development Corporation for funding support to conduct this study.
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