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Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models

Yasin, M. (författare)
Sugarcane Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan
Ahmad, A. (författare)
Asian Disaster Preparedness Centre (ADPC), Islamabad, Pakistan
Khaliq, T. (författare)
Agro-Climatology Lab, Department of Agronomy, University of Agriculture, Faisalabad, Pakistan
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Habib-ur-Rahman, M. (författare)
Institute of Crop Science and Resource Conservation (INRES), University Bonn, Bonn, 53115, Germany
Niaz, S. (författare)
Sugarcane Research Institute, Ayub Agricultural Research Institute, Faisalabad, Pakistan
Gaiser, T. (författare)
Institute of Crop Science and Resource Conservation (INRES), University Bonn, Bonn, 53115, Germany
Ghafoor, I. (författare)
Department of Agronomy, MNS-University of Agriculture Multan, Multan, 60650, Pakistan
Hassan, H. S. (författare)
Sera Processing Lab, National Institute of Health, Islamabad, Pakistan
Qasim, Muhammad (författare)
Jönköping University,IHH, Nationalekonomi, Finansiering och Statistik
Hoogenboom, G. (författare)
Institute for Sustainable Food Systems, University of Florida, 184 Rogers Hall, Gainesville, 32611, FL, United State
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 (creator_code:org_t)
2021-10-27
2022
Engelska.
Ingår i: Environmental Science and Pollution Research. - : Springer. - 0944-1344 .- 1614-7499. ; 29, s. 18967-18988
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • 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.

Ämnesord

LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske -- Jordbruksvetenskap (hsv//swe)
AGRICULTURAL SCIENCES  -- Agriculture, Forestry and Fisheries -- Agricultural Science (hsv//eng)

Nyckelord

Adaptation
CERES-Maize
CSM-IXIM
APSIM-Maize
Phenology
Climate variability
LAI
Maize hybrids
Sowing time
Sustainable maize production
TDM
Yield

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