An Agent-Based Model to Associate Genomic and Environmental Data for Phenotypic Prediction in Plants

Abstract

One of the means to increase in-field crop yields is the use of software tools to predict future yield values using past in-field trials and plant genetics. The traditional, statistics-based approaches lack environmental data integration and are very sensitive to missing and/or noisy data. In this paper, we show that a cooperative, adaptive Multi-Agent System can overcome the drawbacks of such algorithms. The system resolves the problem in an iterative way by a cooperation between the constraints, modelled as agents. Results show that the Agent-Based Model gives results comparable to other approaches, without having to preprocess data.