APSIM-based modeling approach to understand sorghum production environments in Mali
Diancoumba, Madina | Kholova, Jana | Adam, Myriam | Famanta, Mahamoudou | Clerget, Benoît | Traore, Pierre C. S. | Weltzien, Eva | Vacksmann, Michel | Mclean, Greg | Hammer, Graeme L. | van Oosterom, Erik, J. | Vadez, Vincent | Vadez, Vincent | International Crops Research Institute for the Semi-Arid Tropics [Mali] (ICRISAT) ; International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT) ; Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR) | Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF) | International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT) ; Consultative Group on International Agricultural Research [CGIAR] (CGIAR) | Czech University of Life Sciences Prague (CZU) | Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM) | Département Systèmes Biologiques (Cirad-BIOS) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) | Institut Polytechnique Rural de Formation et de Recherche Appliquée (IPR/IFRA) | agCelerant | International Crops Research Institute for the Semi-Arid Tropics [Senegal] (ICRISAT) ; International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT) ; Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR) | University of Wisconsin-Madison | Institut d'Economie Rurale (IER) | Queensland Alliance for Agriculture and Food Innovation (QAAFI) ; The University of Queensland (UQ [All campuses : Brisbane, Dutton Park Gatton, Herston, St Lucia and other locations]) | Diversité, adaptation, développement des plantes (UMR DIADE) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie])-Université de Montpellier (UM) | LMI Adaptation des Plantes et microorganismes associés aux Stress Environnementaux [Dakar] (LAPSE) ; Institut de Recherche pour le Développement (IRD) | Centre d'Etude Regional Pour l'Amelioration de l'Adaptation A la Secheresse (CERAAS) | Institut sénégalais de recherches agricoles [Dakar] (ISRA) | Open access publishing supported by the National Technical Library in Prague. This work was supported by a grant from Australian Centre of International Agricultural Research (ACIAR, CIM-2007-120), a grant from FALL, Feed the Future Innovation Lab for Climate Resilient Sorghum, a grant from Bill and Melinda Gates Foundation, Sorghum Genomic Toolbox, a grant from 2022B0006/provozně ekonomická fakulta česká zemědělská univerzita v praze, and by the additional support from the CGIAR Research Program on Grain Legumes and Dryland Cereals (GLDC).
We thank the APSIM initiative for providing free quality assurance and a structured innovation program for the APSIM modeling software for research and development use (see www.apsim.info for details).
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Показать больше [+] Меньше [-]Английский. Sorghum production system in the semi-arid region of Africa is characterized by low yields which are generally attributed to high rainfall variability, poor soil fertility, and biotic factors. Production constraints must be well understood and quanti- fied to design effective sorghum-system improvements. This study uses the state-of-the-art in silico methods and focuses on characterizing the sorghum production regions in Mali for drought occurrence and its effects on sorghum productivity. For this purpose, we adapted the APSIM-sorghum module to reproduce two cultivated photoperiod-sensitive sorghum types across a latitude of major sorghum production regions in Western Africa. We used the simulation outputs to characterize drought stress scenarios. We identified three main drought scenarios: (i) no-stress; (ii) early pre-flowering drought stress; and (iii) drought stress onset around flowering. The frequency of drought stress scenarios experienced by the two sorghum types across rainfall zones and soil types differed. As expected, the early pre-flowering and flowering drought stress occurred more frequently in isohyets < 600 mm, for the photoperiod-sensitive, late-flowering sorghum type. In isohyets above 600 mm, the frequency of drought stress was very low for both cultivars. We quantified the consequences of these drought scenarios on grain and biomass productivity. The yields of the highly-photoperiod-sensitive sorghum type were quite stable across the higher rainfall zones > 600 mm, but was affected by the drought stress in the lower rainfall zones < 600 mm. Comparatively, the less photoperiod-sensitive cultivar had notable yield gain in the driest regions < 600 mm. The results suggest that, at least for the tested crop types, drought stress might not be the major constraint to sorghum production in isohyets > 600 mm. The findings from this study provide the entry point for further quantitative testing of the Genotype × Environment × Manage- ment options required to optimize sorghum production in Mali.
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