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dc.contributor.authorKamara, A.
dc.contributor.authorBebeley, J.F.
dc.contributor.authorAliyu, K.T.
dc.contributor.authorTofa, A.
dc.contributor.authorOmoigui, L.
dc.contributor.authorSolomon, R.
dc.contributor.authorAkinseye, F.M.
dc.date.accessioned2022-11-24T09:42:23Z
dc.date.available2022-11-24T09:42:23Z
dc.date.issued2023-01
dc.identifier.citationKamara, A., Bebeley, J.F., Aliyu, K.T., Tofa, A., Omoigui, L., Solomon, R. & Akinseye, F.M. (2023). Simulating potential yield of rainfed soybean in northeast Nigeria. European Journal of Agronomy, 142, 126683: 1-16.
dc.identifier.issn1161-0301
dc.identifier.urihttps://hdl.handle.net/20.500.12478/7926
dc.description.abstractWe used the CROPGRO-Soybean model to simulate the production potential of rainfed soybean in northeast Nigeria. Data from ten soybean experiments conducted under optimal conditions in 2016–2018 at Kano and Dambatta in the Sudan savanna (SS) agroecological zone were used to determine the cultivar coefficients and calibrate the model for the varieties TGX 1448–2E and TGX1951–3 F. The model was evaluated with data from four phosphorous response trials conducted at Zaria and Doguwa in the northern Guinea savanna (GS) of Nigeria between 2016 and 2018. Results show that the CROPGRO-Soybean model was able to accurately simulate soybean growth and grain yield with low RMSE and high d-index values. Consequently, the model was used to investigate the rainfed yield potential of the two varieties in 24 sites in northeast Nigeria under different sowing windows using 30-year (1985–2014) weather data. The result shows that soybean can be grown in northeast Nigeria, but yield performance is dependent on location, variety and sowing window. The simulated yield was higher in the SS than in the GS agro-ecozone despite the longer growing period in the later. Low yield was simulated for TGX 1448–2E for most of the sites. The yield of TGX1951–3 F was above a threshold of 1500 kg ha−1 in 5 out of 12 sites in the GS and 7 out of 12 sites in the SS, suggesting that this variety is the most suitable for cultivation in northeast Nigeria. Sowing TGX 1951–3 F can be delayed to July 16 at Gwaskara, Nasarawo Demsa and Tawa in the GS and at Briyel, Lakundum, Jara Dali, Kurbo Gayi, and Mathau in the SS with a low-risk of crop failure. The desired yield will be achieved at Chikala and Puba Vidau with a significantly low risk of crop failure for all sowing windows. The results from this study suggest that the CSM-CROPGRO-Soybean model can be a valuable tool in determining the right variety and sowing window for soybean production in targeted agroecological zones in northeast Nigeria.
dc.description.sponsorshipBill & Melinda Gates Foundation
dc.format.extent1-16
dc.language.isoen
dc.subjectSoybeans
dc.subjectSowing
dc.subjectProductivity
dc.subjectNigeria
dc.subjectAgroecology
dc.subjectGrain Legumes
dc.titleSimulating potential yield of rainfed soybean in northeast Nigeria
dc.typeJournal Article
cg.contributor.crpGrain Legumes
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.contributor.affiliationSierra Leone Agricultural Research Institute
cg.contributor.affiliationInternational Crops Research Institute for the Semi-Arid Tropics
cg.contributor.affiliationCentre d′etude regional pour l′amelioration de l′adaptation `a la secheresse, Senegal
cg.coverage.regionAfrica
cg.coverage.regionWest Africa
cg.coverage.countryNigeria
cg.coverage.hubHeadquarters and Western Africa Hub
cg.researchthemePlant Production and Health
cg.identifier.bibtexciteidKAMARA:2023
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectFarming Systems
cg.iitasubjectFood Security
cg.iitasubjectGrain Legumes
cg.iitasubjectPlant Breeding
cg.iitasubjectPlant Health
cg.iitasubjectPlant Production
cg.iitasubjectSoybean
cg.journalEuropean Journal of Agronomy
cg.notesOpen Access Article; Published online: 07 Nov 2022
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://dx.doi.org/10.1016/j.eja.2022.126683
cg.iitaauthor.identifierAlpha Kamara: 0000-0002-1844-2574
cg.iitaauthor.identifierLucky Omoigui: 0000-0001-8473-2775
cg.futureupdate.requiredNo
cg.identifier.issue126683
cg.identifier.volume142


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