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

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

Journal Name: Current Bioinformatics

Volume 11 , Issue 5 , 2016

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Abstract:

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.

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Article Details

VOLUME: 11
ISSUE: 5
Year: 2016
Page: [515 - 522]
Pages: 8
DOI: 10.2174/1574893611666160617094329
Price: $58

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