Title :

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

Author(s) :

Gautron, Romain [Auteur]
Agroécologie et Intensification Durables des cultures annuelles [UPR AIDA]
Baudry, Dorian [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Adam, Myriam [Auteur]
Amélioration génétique et adaptation des plantes méditerranéennes et tropicales [UMR AGAP]
Falconnier, Gatien [Auteur]
Agroécologie et Intensification Durables des cultures annuelles [UPR AIDA]
International Maize and Wheat Improvement Center [Zimbabwe] [CIMMYT]
Corbeels, Marc [Auteur]
Agroécologie et Intensification Durables des cultures annuelles [UPR AIDA]
International Institute of Tropical Agriculture [IITA Kenya]

HAL domain(s) :

Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences du Vivant [q-bio]/Sciences agricoles/Agronomie

English abstract : [en]

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 ...
Show more >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.Show less >

Language :

Anglais

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL