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Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models
Sugarcane Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan.
Asian Disaster Preparedness Centre (ADPC), Islamabad, Pakistan.
Agro-Climatology Lab, Department of Agronomy, University of Agriculture, Faisalabad, Pakistan.
Institute of Crop Science and Resource Conservation (INRES), University Bonn, Bonn, 53115, Germany.
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2022 (English)In: Environmental Science and Pollution Research, ISSN 0944-1344, E-ISSN 1614-7499, Vol. 29, p. 18967-18988Article in journal (Refereed) Published
Abstract [en]

Future climate scenarios are predicting considerable threats to sustainable maize production in arid and semi-arid regions. These adverse impacts can be minimized by adopting modern agricultural tools to assess and develop successful adaptation practices. A multi-model approach (climate and crop) was used to assess the impacts and uncertainties of climate change on maize crop. An extensive field study was conducted to explore the temporal thermal variations on maize hybrids grown at farmer’s fields for ten sowing dates during two consecutive growing years. Data about phenology, morphology, biomass development, and yield were recorded by adopting standard procedures and protocols. The CSM-CERES, APSIM, and CSM-IXIM-Maize models were calibrated and evaluated. Five GCMs among 29 were selected based on classification into different groups and uncertainty to predict climatic changes in the future. The results predicted that there would be a rise in temperature (1.57–3.29 °C) during the maize growing season in five General Circulation Models (GCMs) by using RCP 8.5 scenarios for the mid-century (2040–2069) as compared with the baseline (1980–2015). The CERES-Maize and APSIM-Maize model showed lower root mean square error values (2.78 and 5.41), higher d-index (0.85 and 0.87) along reliable R2 (0.89 and 0.89), respectively for days to anthesis and maturity, while the CSM-IXIM-Maize model performed well for growth parameters (leaf area index, total dry matter) and yield with reasonably good statistical indices. The CSM-IXIM-Maize model performed well for all hybrids during both years whereas climate models, NorESM1-M and IPSL-CM5A-MR, showed less uncertain results for climate change impacts. Maize models along GCMs predicted a reduction in yield (8–55%) than baseline. Maize crop may face a high yield decline that could be overcome by modifying the sowing dates and fertilizer (fertigation) and heat and drought-tolerant hybrids.

Place, publisher, year, edition, pages
Springer, 2022. Vol. 29, p. 18967-18988
Keywords [en]
Adaptation, CERES-Maize, CSM-IXIM, APSIM-Maize, Phenology, Climate variability, LAI, Maize hybrids, Sowing time, Sustainable maize production, TDM, Yield
National Category
Agricultural Science
Identifiers
URN: urn:nbn:se:hj:diva-55067DOI: 10.1007/s11356-021-17050-zISI: 000712505900013PubMedID: 34705205Scopus ID: 2-s2.0-85117905092Local ID: HOA;intsam;776665OAI: oai:DiVA.org:hj-55067DiVA, id: diva2:1611422
Available from: 2021-11-15 Created: 2021-11-15 Last updated: 2022-04-07Bibliographically approved

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Qasim, Muhammad

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