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 securityPublished in
International Journal of Biometeorology2022, volume: 66, number: 5, pages: 971-985
Publisher: SPRINGER
Authors' information
Ali, Marwa G. M.
Agricultural Research Center - Egypt
Ali, Marwa G. M.
Tanta University
Arid Agriculture University
Swedish University of Agricultural Sciences, Department of Agricultural Research for Northern Sweden
Ibrahim, Mahmoud M.
Egyptian Knowledge Bank (EKB)
El Baroudy, Ahmed A.
Tanta University
Ali, Esmat F.
Taif University
Shokr, Mohamed S.
Egyptian Knowledge Bank (EKB)
Aldosari, Ali A.
King Saud University
Majrashi, Ali
Taif University
Kheir, Ahmed M. S.
Egyptian Knowledge Bank (EKB)
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
URI (permanent link to this page)
https://res.slu.se/id/publ/116284