Options for calibrating ceres-maize genotype specific parameters under data-scarce environments

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dc.creatorAdnan, A.A.
dc.creatorDiels, J.
dc.creatorJibrin, J.M.
dc.creatorKamara, A.
dc.creatorCraufurd, Peter Q.
dc.creatorShaibu, A.S.
dc.creatorMohammed, I.B.
dc.creatorTonnang, Henri E.Z.
dc.date2019-02-19
dc.date2019-05-22T10:13:55Z
dc.date2019-05-22T10:13:55Z
dc.date.accessioned2026-06-27T15:52:50Z
dc.descriptionMost crop simulation models require the use of Genotype Specific Parameters (GSPs) which provide the Genotype component of G×E×M interactions. Estimation of GSPs is the most difficult aspect of most modelling exercises because it requires expensive and time-consuming field experiments. GSPs could also be estimated using multi-year and multi locational data from breeder evaluation experiments. This research was set up with the following objectives: i) to determine GSPs of 10 newly released maize varieties for the Nigerian Savannas using data from both calibration experiments and by using existing data from breeder varietal evaluation trials; ii) to compare the accuracy of the GSPs generated using experimental and breeder data; and iii) to evaluate CERES-Maize model to simulate grain and tissue nitrogen contents. For experimental evaluation, 8 different experiments were conducted during the rainy and dry seasons of 2016 across the Nigerian Savanna. Breeder evaluation data were also collected for 2 years and 7 locations. The calibrated GSPs were evaluated using data from a 4-year experiment conducted under varying nitrogen rates (0, 60 and 120kg N ha-1). For the model calibration using experimental data, calculated model efficiency (EF) values ranged between 0.88–0.94 and coefficient of determination (d-index) between 0.93–0.98. Calibration of time-series data produced nRMSE below 7% while all prediction deviations were below 10% of the mean. For breeder experiments, EF (0.58–0.88) and d-index (0.56–0.86) ranges were lower. Prediction deviations were below 17% of the means for all measured variables. Model evaluation using both experimental and breeder trials resulted in good agreement (low RMSE, high EF and d-index values) between observed and simulated grain yields, and tissue and grain nitrogen contents. It is concluded that higher calibration accuracy of CERES-Maize model is achieved from detailed experiments. If unavailable, data from breeder experimental trials collected from many locations and planting dates can be used with lower but acceptable accuracy.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/101339
dc.identifier.urihttp://hdl.handle.net/123456789/116221
dc.languageen
dc.publisherPublic Library of Science
dc.rightsOpen Access
dc.sourceAdnan, A.A., Diels, J., Jibrin, J.M., Kamara, A., Craufurd, P., Shaibu, A.S., ... & Tonnang, Z.E.H. (2019). Options for calibrating ceres-maize genotype specific parameters under data-scarce environments. PLOS ONE, 14(2), 1-20.
dc.subjectmaize
dc.subjectleaves
dc.subjectstems
dc.subjectcalibration
dc.subjectexperiments
dc.subjectagricultural research
dc.titleOptions for calibrating ceres-maize genotype specific parameters under data-scarce environments
dc.typeJournal Article

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Instituto Internacional de Agricultura Tropical (IITA)