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Current Bioinformatics


ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

Research Article

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

Author(s): Sebastien Alameda, Jean-Pierre Mano, Carole Bernon and Sebastien Mella

Volume 11, Issue 5, 2016

Page: [515 - 522] Pages: 8

DOI: 10.2174/1574893611666160617094329

Price: $65


Background: 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.

Objective: In this paper, we show that a cooperative, adaptive Multi-Agent System can overcome the drawbacks of such algorithms.

Method: The system resolves the problem in an iterative way by a cooperation between the constraints, modelled as agents.

Results: Results show that the Agent-Based Model gives results comparable to other approaches, without having to preprocess or reconcile data.

Conclusion: This collective and self-adaptive search of a solution functions like a heuristic to efficiently explore the solution space and is therefore able to consider both genetic and environmental data.

Keywords: Adaptation, environmental data, genomics, multi-agent systems, phenotypic prediction.

Graphical Abstract

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