Arid
DOI10.1007/s00484-022-02253-x
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.
通讯作者Kheir, AMS (corresponding author),Agr Res Ctr, Soils Water & Environm Res Inst, Giza, Egypt.
来源期刊INTERNATIONAL JOURNAL OF BIOMETEOROLOGY
ISSN0020-7128
EISSN1432-1254
出版年2022-02
英文摘要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.
英文关键词DSSAT models Climate change Impacts Adaptation Uncertainty Food security
类型Article ; Early Access
语种英语
收录类别SCI-E
WOS记录号WOS:000754137900001
WOS关键词CHANGE IMPACTS ; CERES-MAIZE ; KERNEL SET ; LEAF-AREA ; MODEL ; HEAT ; ADAPTATION ; STRESS ; DATE ; QUANTIFICATION
WOS类目Biophysics ; Environmental Sciences ; Meteorology & Atmospheric Sciences ; Physiology
WOS研究方向Biophysics ; Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences ; Physiology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/377300
作者单位[Ali, Marwa G. M.; Ibrahim, Mahmoud M.; El Baroudy, Ahmed A.; Shokr, Mohamed S.] Tanta Univ, Fac Agr, Soil & Water Dept, Tanta, Egypt; [Ali, Marwa G. M.; Kheir, Ahmed M. S.] Agr Res Ctr, Soils Water & Environm Res Inst, Giza, Egypt; [Ahmed, Mukhtar] Swedish Univ Agr Sci, Dept Agr Res Northern Sweden, S-90183 Umea, Sweden; [Ahmed, Mukhtar] PMAS Arid Agr Univ Rawalpindi, Dept Agron, Rawalpindi 46300, Pakistan; [Ali, Esmat F.; Majrashi, Ali] Taif Univ, Coll Sci, Dept Biol, POB 11099, At Taif 21944, Saudi Arabia; [Aldosari, Ali A.] King Saud Univ, Geog Dept, Riyadh, Saudi Arabia; [Kheir, Ahmed M. S.] Int Ctr Biosaline Agr, Directorate Programs, Dubai 14660, U Arab Emirates
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Ali, Marwa G. M.,Ahmed, Mukhtar,Ibrahim, Mahmoud M.,et al. Optimizing sowing window, cultivar choice, and plant density to boost maize yield under RCP8.5 climate scenario of CMIP5[J],2022.
APA Ali, Marwa G. M..,Ahmed, Mukhtar.,Ibrahim, Mahmoud M..,El Baroudy, Ahmed A..,Ali, Esmat F..,...&Kheir, Ahmed M. S..(2022).Optimizing sowing window, cultivar choice, and plant density to boost maize yield under RCP8.5 climate scenario of CMIP5.INTERNATIONAL JOURNAL OF BIOMETEOROLOGY.
MLA Ali, Marwa G. M.,et al."Optimizing sowing window, cultivar choice, and plant density to boost maize yield under RCP8.5 climate scenario of CMIP5".INTERNATIONAL JOURNAL OF BIOMETEOROLOGY (2022).
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