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Research article - Peer-reviewed, 2022

Optimizing sowing window, cultivar choice, and plant density to boost maize yield under RCP8.5 climate scenario of CMIP5

Ali, Marwa G. M.; Ahmed, Mukhtar; Ibrahim, Mahmoud M.; El Baroudy, Ahmed A.; Ali, Esmat F.; Shokr, Mohamed S.; Aldosari, Ali A.; Majrashi, Ali; Kheir, Ahmed M. S.

Abstract

The impacts of climate change and possible adaptations to food security are a global concern and need greater focus in arid and semi-arid regions. It includes scenario of Coupled Model Intercomparison Phase 5 (CMIP-RCP8.5). For this purpose, two DSSAT maize models (CSM-CERES and CSM-IXIM) were calibrated and tested with two different maize cultivars namely Single Cross 10 (SC10) and Three Way Cross 324 (TW24) using a dataset of three growing seasons in Nile Delta. SC10 is a long-growing cultivar that is resistant to abiotic stresses, whereas TW24 is short and sensitive to such harsh conditions. The calibrated models were then employed to predict maize yield in baseline (1981-2010) and under future time slices (2030s, 2050s, and 2080s) using three Global Climate Models (GCMs) under CMIP5-RCP8.5 scenario. In addition, the use of various adaptation options as shifting planting date, increasing sowing density, and genotypes was included in crop models. Simulation analysis showed that, averaged over three GCMs and two crop models, the yield of late maturity cultivar (SC10) decreased by 4.1, 17.2, and 55.9% for the three time slices of 2030s, 2050s, and 2080s, respectively, compared to baseline yield (1981-2010). Such reduction increased with early maturity cultivar (TW24), recording 12.4, 40.6, and 71.3% for near (2030s), mid (2050s), and late century (2080s) respectively relative to baseline yield. The most suitable adaptation options included choosing a stress-resistant genotype, changing the planting date to plus or minus 30 days from baseline planting date, and raising the sowing density to 9 m(-2) plants. These insights could minimize the potential reduction of climate change-induced yields by 39% by late century.

Keywords

DSSAT models; Climate change; Impacts; Adaptation; Uncertainty; Food security

Published in

International Journal of Biometeorology
2022, Volume: 66, number: 5, pages: 971-985
Publisher: SPRINGER

      SLU Authors

    • Ahmed, Mukhtar

      • Arid Agriculture University
      • Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences

    Sustainable Development Goals

    SDG13 Climate action
    SDG2 Zero hunger

    UKÄ Subject classification

    Agricultural Science

    Publication Identifiers

    DOI: https://doi.org/10.1007/s00484-022-02253-x

    Permanent link to this page (URI)

    https://res.slu.se/id/publ/116284