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

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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.

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Data availability

The majority of the datasets are available in the article and supplementary material. Other datasets are available upon request from the corresponding author.

Code availability

On request, the corresponding author will provide the R code for the analyses.

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Acknowledgements

We are very grateful to Dr. Alex. C. Ruane (NASA, New York, USA) for supplying us with study area downscaled scenarios of RCP8.5.

Funding

This research was funded by Taif University Researchers Supporting Project number (TURSP-2020/110), Taif University, Saudi Arabia. The authors would like to extend their sincere appreciation to the Deanship of Scientific Research at King Saud University for its funding of this research through the Research Group project no. RGP-275.

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Authors and Affiliations

  1. Soil and Water Department, Faculty of Agriculture, Tanta University, Tanta, Egypt

    Marwa G. M. Ali, Mahmoud M. Ibrahim, Ahmed A El Baroudy & Mohamed S. Shokr

  2. Soils, Water and Environment Research Institute, Agricultural Research Center, Giza, Egypt

    Marwa G. M. Ali & Ahmed M. S. Kheir

  3. Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences, 90183, Umeå, Sweden

    Mukhtar Ahmed

  4. Department of Agronomy, PMAS Arid Agriculture University Rawalpindi, Rawalpindi, 46300, Pakistan

    Mukhtar Ahmed

  5. Department of Biology, College of Science, Taif University, P.O.Box 11099, Taif, 21944, Saudi Arabia

    Esmat F. Ali & Ali Majrashi

  6. Geography Department, King Saud University, Riyadh, Saudi Arabia

    Ali A. Aldosari

  7. International Center for Biosaline Agriculture, Directorate of Programs, Dubai, 14660, United Arab Emirates

    Ahmed M. S. Kheir

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  4. Ahmed A El Baroudy
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  5. Esmat F. Ali
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  6. Mohamed S. Shokr
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  7. Ali A. Aldosari
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  8. Ali Majrashi
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  9. Ahmed M. S. Kheir
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Contributions

Marwa Ali: writing – original draft, methodology, software, formal analysis, visualization. Mukhtar Ahmed: formal analysis, writing – review and editing. Mahmoud Ibrahim: conceptualization, methodology, resources, writing – review and editing. Ahmed El Baroudy: resources, writing – review and editing. Esmat Ali: resources, funding acquisition, writing – review and editing. Mohamed Shokr: methodology, resources. Ali Aldosari: funding acquisition, writing – review and editing. Ali Majrashi: funding acquisition, writing – review and editing. Ahmed Kheir: supervision, methodology, resources, writing – review and editing.

Corresponding author

Correspondence to Ahmed M. S. Kheir.

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The authors declare no competing interests.

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Ali, M.G.M., Ahmed, M., Ibrahim, M.M. et al. Optimizing sowing window, cultivar choice, and plant density to boost maize yield under RCP8.5 climate scenario of CMIP5. Int J Biometeorol 66, 971–985 (2022). https://doi.org/10.1007/s00484-022-02253-x

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

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