An improved simulation model to predict pre-harvest aflatoxin risk in maize

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cg.contributor.affiliationQueensland Department of Agriculture and Fisheriesen
cg.contributor.affiliationKenya Agricultural and Livestock Research Organizationen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.identifier.doihttps://doi.org/10.1016/j.fcr.2015.03.024en
cg.issn0378-4290en
cg.journalField Crops Researchen
cg.subject.ilriAFLATOXINSen
cg.subject.ilriCROPSen
cg.subject.ilriDROUGHTen
cg.volume178en
dc.contributor.authorChauhan, Y.en
dc.contributor.authorTatnell, J.en
dc.contributor.authorKrosch, S.en
dc.contributor.authorKaranja, J.en
dc.contributor.authorGnonlonfin, G.J.B.en
dc.contributor.authorWanjuki, I.en
dc.contributor.authorWainaina, J.en
dc.contributor.authorHarvey, Jagger J.W.en
dc.date.accessioned2015-04-29T04:39:15Zen
dc.date.available2015-04-29T04:39:15Zen
dc.identifier.urihttps://hdl.handle.net/10568/65235
dc.titleAn improved simulation model to predict pre-harvest aflatoxin risk in maizeen
dcterms.abstractAflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationChauhan , Y., Tatnell, J., Krosch, S., Karanja, J., Gnonlonfin, B., Wanjuki, I., Wainaina, J. and Harvey, J. 2015. An improved simulation model to predict pre-harvest aflatoxin risk in maize. Field Crops Research 178:91-99.en
dcterms.extentp. 91-99en
dcterms.issued2015-07
dcterms.languageen
dcterms.licenseCC-BY-NC-ND-4.0
dcterms.publisherElsevieren
dcterms.subjectdroughten
dcterms.typeJournal Article

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