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

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    U19ArtAdnanOptionsInthomDev.pdf (1.216Mb)
    Date
    2019-02-19
    Author
    Adnan, A.A.
    Diels, J.
    Jibrin, J.M.
    Kamara, A.
    Craufurd, Peter Q.
    Shaibu, A.S.
    Mohammed, B.
    Tonnang, Z.E.H.
    Type
    Journal Article
    Metadata
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    Abstract/Description
    Most 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.
    https://dx.doi.org/10.1371/journal.pone.0200118
    Multi standard citation
    Permanent link to this item
    https://hdl.handle.net/20.500.12478/5833
    Non-IITA Authors ORCID
    Alpha Kamarahttps://orcid.org/0000-0002-1844-2574
    Ibrahim Mohammedhttps://orcid.org/0000-0001-5199-5528
    Digital Object Identifier (DOI)
    https://dx.doi.org/10.1371/journal.pone.0200118
    Research Themes
    NATURAL RESOURCE MANAGEMENT; PLANT PRODUCTION & HEALTH
    IITA Subjects
    Maize; Natural Resource Management; Plant Health; Plant Production
    Agrovoc Terms
    Maize; Leaves; Stems; Calibration; Experiments; Agricultural Research
    Regions
    Africa; West Africa
    Countries
    Nigeria
    Journals
    PLOS ONE
    Collections
    • Journal and Journal Articles4835
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