Evaluating CERES-Maize Model Using Planting Dates and Nitrogen Fertilizer in Zambia

Charles Bwalya Chisanga, Elijah Phiri, Chizumba Shepande, Henry Sichingabula

Abstract


A field experiment was conducted during the 2013/2014 season to evaluate the performance of CERES-maize model in simulating the effect of date of planting, nitrogen fertilizer and root-zone soil water profile on growth and yield of maize (Zea mays L.) at the Field Research Station of the School of Agricultural Sciences, University of Zambia, Zambia (15°23.6859'S, 28°20.226'E; 1,261 m.a.s.l). The experimental design was a split plot with three replicates, three planting dates (November 24, December 8, and December 22) assigned to main plots and two nitrogen fertilizer rates (112 and 168 kg N ha-1) assigned to sub-plot. Phenological stages and aboveground biomass were used for model evaluation and these were observed at vegetative and reproductive stages. Soil water profiles were monitored using the Diviner 2000 Probe. Planting date significantly affected grain and biomass yield at P < 0.05. The coefficients of variation for grain and biomass yield were below 12% and considered efficient. The Generalized Likelihood Uncertainty Estimation (GLUE) programme was used to estimate the genetic coefficients for the CERES-maize model. The model’s prediction of plant emergence (±1 days), time to anthesis (>= -3 <= ±1 days) and maturity (>= -4 <= 6 days) was good. Simulation of biomass (RMSE = 1135 kg/ha, d = 0.96, EF = 0.86) was reasonably accurate while leaf area index (d = 0.54, EF = -0.65) was simulated with less accuracy due to poor d-stat and forecasting efficiency. The model’s simulation of grain yield was fair (NRMSE = 21.4%) while soil root water availability demonstrated that substantial potential yield may have been lost due to water stress. The results showed that the model can be used to accurately determine optimum planting date, biomass yield and nitrogen fertilizer rates with reasonable accuracy.


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DOI: https://doi.org/10.5539/jas.v7n3p79

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Journal of Agricultural Science   ISSN 1916-9752 (Print)   ISSN 1916-9760 (Online)  E-mail: jas@ccsenet.org

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