Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 10/13/2003
Publication Date: 10/13/2003
Citation: Xian, H., Bridges, S.M., Hodges, J.E., Williams, W.P., Windham, G.L. 2003. Using genetic algorithms to derive environmental indices correlated with aflatoxin levels [abstract]. Multicrop Aflatoxin and Fumonisin Elimination and Fungal Genomics Workshop Proceedings. p. 66.
Technical Abstract: Infection by Aspergillus flavus and the resulting production of aflatoxin are major problems in maize in the southern US and other warm climates. Some cultivars of maize are more resistant to Aspergillus infection than others. Environmental conditions affect infection rates, but the relationship appears to be quite complex. It is not clear which environmental factors (i.e., temperature, rainfall, etc.) are most important, how these factors should be combined (minimum, maximum, average), nor which time periods are most critical. The goal of the present work is to develop a method for deriving an environmental index that correlates with aflatoxin levels in maize and that can be used to study the differences in responses of resistant and susceptible varieties. In our approach, we use a genetic algorithm to evolve the specification of an environmental index. An index specification is represented as a population of randomly initialized artificial chromosomes. The correlation of the index specified by each chromosome and aflatoxin levels is used to evaluate the "fitness" of each chromosome. More fit chromosomes have a higher probability of being selected for the next generation. Mutation and crossover operations are applied at each generation. Experiments using this approach have been conducted with field data for two susceptible and two resistant lines. The results show that, for all of the four pedigrees, air temperature, rainfall, and pan evaporation are the most important environmental factors affecting aflatoxin levels.