Calibrating the STICS soil-crop model to explore the impact of agroforestry parklands on millet growth

Sow Sidy, Senghor Yolande, Sadio Khardiatou, Vezy Rémi, Roupsard Olivier, Affholder François, N’Diénor Moussa, Clermont-Dauphin Cathy, Gaglo Koudjo Espoir, Ba Seydina, Tounkara Adama, Balde Alpha Bocar, Agbohessou Yélognissè Frédi, Seghieri Josiane, Sall Saidou Nourou, Couedel Antoine, Leroux Louise, Jourdan Christophe, Sanogo Diaite Diaminatou, Falconnier Gatien. 2024. Calibrating the STICS soil-crop model to explore the impact of agroforestry parklands on millet growth. Field Crops Research, 306:109206, 15 p.

Résumé : Context: Agroforestry systems provide critical benefits for food security and climate change mitigation. Yet, they are complex and heteregoneous sytems hard to optimize. The use of process-based crop models provides an opportunity to understand better the interactions between soil, crop, tree and climate and explore the impact of agroforestry on crop growth, for contrasting crop management. Objective: The objectives of this study were to i) calibrate the soil-crop STICS model for pearl millet (Pennisetum glaucum) in order to simulate millet potential growth and impact of water and nitrogen limitations on millet growth in open fields and ii) explore the impacts of the parkland tree Faidherbia albida on millet performance for contrasting N fertilizer inputs. Methods: We gathered a comprehensive database of 28 agronomically contrasting situations, ranging from near-potential growth to drought- and N-stress, either on-station or in a farmer's home- or bush-fields. Parameters governing relevant plant and soil processes for grain yield were calibrated in a stepwise procedure. The calibrated model was used to explore the impact on millet growth of the widely reported benefits of Faidherbia albida, namely a minimum reduction in radiation thanks to the peculiar reverse phenology of this tree, improvement of soil water content at the beginning of the growing season and of organic nitrogen in the topsoil. Results: Model simulations with the calibration dataset were reasonably accurate for aboveground biomass and grain yield. Normalized Root Mean Square Errors (nRMSE) for these variables were 29% and 26%, respectively; model efficiency (EF) was 0.58 for both. The nRMSE ranged from 33% to 53% for Soil Water Content (SWC), plant N uptake, grain number, and leaf-area index (LAI). Model accuracy was lower with the evaluation dataset. In the virtual experiment, millet yield decreased with incoming solar radiation, but only at levels of shading (e.g. below 80% of the radiation obtained with full sun) that do not occur under Faidherbia. The decline was greater when millet was fertilized. Increasing the initial soil water content did not affect simulated millet growth. Simulated millet aboveground biomass and grain yield increased with higher organic nitrogen contents of the topsoil, by 80% when millet was not fertilizer, but only by 25% when millet was fertilized. Implications: This study provides the first set of comprehensively calibrated parameters for applying STICS to pearl millet in open cropland. A virtual experiment with historical climate suggests that the benefits of Faidherbia decrease if farmers intensify crop production by adding more mineral N fertilizer. Hence, precise fertilizer management is recommended in Faidherbia parklands. These results illustrate the benefits of process-based crop modelling for better understanding the functioning of agroforestry systems.

Mots-clés Agrovoc : modèle de simulation, Cenchrus americanus, agroforesterie, changement climatique, croissance de la plante, rendement des cultures, agroécologie, engrais azoté, millet, Faidherbia albida, modélisation des cultures, modèle mathématique

Mots-clés libres : Crop model, Sustainable intensification, Calibration, Validation, Senegal

Classification Agris : U10 - Informatique, mathématiques et statistiques
F62 - Physiologie végétale - Croissance et développement
F08 - Systèmes et modes de culture

Agences de financement européennes : European Commission

Agences de financement hors UE : Agropolis Fondation, Institut de Recherche pour le Développement

Programme de financement européen : H2020

Projets sur financement : (EU) Development Smart Innovation through Research in Agriculture, (EU) A long term EU-Africa research and innovation partnership on food and nutrition security and sustainable agriculture, (EU) Synergistic use and protection of natural resources for rural livelihoods through systematic integration of crops, shrubs and livestock in the Sahel

Auteurs et affiliations

• Sow Sidy, CIRAD-PERSYST-UMR Eco&Sols (FRA)
• Senghor Yolande, CIRAD-PERSYST-UPR AIDA (FRA)
• Sadio Khardiatou, ISRA (SEN)
• Vezy Rémi, CIRAD-BIOS-UMR AMAP (FRA) ORCID: 0000-0002-0808-1461
• Roupsard Olivier, CIRAD-PERSYST-UMR Eco&Sols (SEN)
• Affholder François, CIRAD-PERSYST-UPR AIDA (MOZ) ORCID: 0000-0002-3919-4805
• N’Diénor Moussa, ISRA (SEN)
• Clermont-Dauphin Cathy, IRD (FRA)
• Gaglo Koudjo Espoir, CIRAD-PERSYST-UMR Eco&Sols (FRA)
• Ba Seydina, ISRA (SEN)
• Tounkara Adama, Université Iba Der Thiam de Thiès (SEN)
• Balde Alpha Bocar, ISRA (SEN)
• Agbohessou Yélognissè Frédi, CIRAD-PERSYST-UMR Eco&Sols (FRA)
• Seghieri Josiane, IRD (FRA)
• Sall Saidou Nourou, Université Gaston Berger (SEN)
• Couedel Antoine, CIRAD-PERSYST-UPR AIDA (FRA)
• Leroux Louise, CIRAD-PERSYST-UPR AIDA (KEN) ORCID: 0000-0002-7631-2399
• Jourdan Christophe, CIRAD-PERSYST-UMR Eco&Sols (FRA) ORCID: 0000-0001-9857-3269
• Sanogo Diaite Diaminatou, ISRA (SEN)
• Falconnier Gatien, CIRAD-PERSYST-UPR AIDA (ZWE) ORCID: 0000-0003-3291-650X - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/607652/)

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