Improving sorghum productivity under changing climatic conditions: A modelling approach

cg.contactF.Akinseye@cgiar.orgen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerFederal University of Technologyen_US
cg.contributor.crpCRP on Climate Change, Agriculture and Food Security - CCAFSen_US
cg.contributor.crpCRP on Grain Legumes and Dryland Cereals - GLDCen_US
cg.contributor.funderInternational Institute of Tropical Agriculture - IITAen_US
cg.contributor.projectAgricultural Transformation Agenda Support Program-Phase 1 (ATASP-1) - Nigeria - Sorghumen_US
cg.contributor.project-lead-instituteInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.coverage.countryINen_US
cg.coverage.countryMLen_US
cg.coverage.countryNGen_US
cg.coverage.countrySNen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.regionWestern Africaen_US
cg.creator.idWhitbread, Anthony: 0000-0003-4840-7670en_US
cg.date.embargo-end-dateTimelessen_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.fcr.2019.107685en_US
cg.isijournalISI journalen_US
cg.issn0378-4290en_US
cg.issue246en_US
cg.journalField Crops Researchen_US
cg.subject.actionAreaResilient agrifood systemsen_US
cg.subject.agrovocsorghumen_US
dc.contributorAjeigbe, Hakeemen_US
dc.contributorTraore, Pierre C. Sibiryen_US
dc.contributorAgele, Samuelen_US
dc.contributorBirhanu, Zemadimen_US
dc.contributorWhitbread, Anthonyen_US
dc.creatorAkinseye, Folorunsoen_US
dc.date.accessioned2020-02-11T05:16:48Z
dc.date.available2020-02-11T05:16:48Z
dc.description.abstractClimate variability and change will have far reaching consequences for smallholder farmers in sub-Saharan Africa, the majority of whom depend on agriculture for their livelihoods. Crop modelling can help inform the improvement of agricultural productivity under future climate. This study applies the Agricultural Production Systems sIMulator (APSIM) to assessing the impacts of projected climate change on two (early and medium maturing) sorghum varieties under different management practices. Results show high model accuracy with excellent agreement between simulated and observed values for crop phenology and leaf number per plant. The prediction of grain yield and total biomass of an early maturing variety was fair RMSEn (22.9 and 23.1%), while that of the medium maturing was highly accurate RMSEn (14.9 and 11.9%). Sensitivity analysis performed by changing the calibrated variables of key plant traits in the model, showed higher significant yield change by+or - 10 % changed in radiation use efficiency, (RUE), coefficient extinction (Coeff_ext) and Phyllocron (Phyllo) for early maturing variety while +or - 10 % changed in phyllochron and RUE showed a significant yield change for the medium maturing variety. Under climate change scenerios using RCP 8.5, the simulated yield for the early–maturing variety revealed high inter-annual variability and potential yield loss of 3.3% at Bamako and 1% at Kano in the near-future (2010–2039) compared to baseline (1980–2009). The midcentury (2040–2069) projected yield decline by 4.8% at Bamako and 6.2% at Kano compared to baseline (1980–2009). On the contrary, the medium maturing variety indicated significantly yield gain with high yielding potential in both climate regimes compared to the baseline period (1980–2009). The simulated grain yield increased by 7.2% at Bamako and 4.6% at Kano, in the near-future (2010–2039) while in the mid-century (2040–2069) projected yield increase of 12.3% and 2% at Bamako and Kano compared to baseline (1980–2009). Adaptation strategies under climate change for varying sowing dates in the near-future (2010–2039, indicated that June sowing had a higher positive yield gained over July and August sowing for early maturing variety; July sowing simulated positive gained by 5 -11% over June and August sowing for medium maturing variety in both locations. Similarly, under the mid-century (2040–2069), among the sowing dates and in both locations, June sowing indicates lowest negative yield change over July and August sowing for early maturing variety. However, for medium maturing variety, July sowing had the highest yield gain of 16% over June and August sowing at Bamako and June highest positive yield gained of 11.4% over July and August at Kano. Our study has, therefore, demonstrated the capacity of APSIM model as a tool for testing management, plant traits practices and adoption of improved variety for enhancing the adaptive capacity of smallholder farmers under climate change in the Sudanian zone of West Africa. This approach offers a promising option to design more resilient and productive farming systems for West Africa using the diverse sorghum germplasm available in the region.en_US
dc.formatTXTen_US
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationFolorunso Akinseye, Hakeem Ajeigbe, Pierre C. Sibiry Traore, Samuel Agele, Zemadim Birhanu, Anthony Whitbread. (1/2/2020). Improving sorghum productivity under changing climatic conditions: A modelling approach. (246), pp. 1-11.en_US
dc.identifier.statusTimeless limited accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/10695
dc.languageenen_US
dc.publisherElsevier (12 months)en_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceField Crops Research;(2020) Pagination 1,11en_US
dc.subjectapsimen_US
dc.subjectclimate scenariosen_US
dc.subjectwater-limited environment simulated yield potentialen_US
dc.subjectSorghumen_US
dc.titleImproving sorghum productivity under changing climatic conditions: A modelling approachen_US
dc.typeJournal Articleen_US
dcterms.available2020-02-01en_US
dcterms.extent1-11en_US
mel.impact-factor3.868en_US
mel.project.openhttps://mel.cgiar.org/projects/81en_US

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