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Towards an efficient and risk aware strategy for guiding farmers in identifying best crop management

Abstract : Identification of best performing fertilizer practices among a set of contrasting practices with field trials is challenging as crop losses are costly for farmers. To identify best management practices, an "intuitive strategy" would be to set multi-year field trials with equal proportion of each practice to test. Our objective was to provide an identification strategy using a bandit algorithm that was better at minimizing farmers' losses occurring during the identification, compared with the "intuitive strategy". We used a modification of the Decision Support Systems for Agro-Technological Transfer (DSSAT) crop model to mimic field trial responses, with a case-study in Southern Mali. We compared fertilizer practices using a risk-aware measure, the Conditional Value-at-Risk (CVaR), and a novel agronomic metric, the Yield Excess (YE). YE accounts for both grain yield and agronomic nitrogen use efficiency. The bandit-algorithm performed better than the intuitive strategy: it increased, in most cases, farmers' protection against worst outcomes. This study is a methodological step which opens up new horizons for risk-aware ensemble identification of the performance of contrasting crop management practices in real conditions.
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Pré-publication, Document de travail
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http://hal.cirad.fr/cirad-03806634
Contributeur : Romain Gautron Connectez-vous pour contacter le contributeur
Soumis le : vendredi 7 octobre 2022 - 19:54:03
Dernière modification le : mardi 6 décembre 2022 - 12:42:13

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  • HAL Id : cirad-03806634, version 1
  • ARXIV : 2210.04537

Citation

Romain Gautron, Dorian Baudry, Myriam Adam, Gatien N Falconnier, Marc Corbeels. Towards an efficient and risk aware strategy for guiding farmers in identifying best crop management. 2022. ⟨cirad-03806634⟩

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