Author(s)

Sixbert Kajumula Mourice, Cornell Lawrence Rweyemamu, Siza Donald Tumbo, Nyambilila Amuri

Department of Agricultural Engineering and Land Planning, Sokoine University of Agriculture, Morogoro, Tanzania.
Department of Crop Science and Production, Sokoine University of Agriculture, Morogoro, Tanzania.
Department of Soil Science, Sokoine University of Agriculture, Morogoro, Tanzania.

In order to develop basis for tactical or strategic decision making towards agricultural productivity improvement in Tanzania, a new approach in which crop models could be used is required. Crop specific parameters for maize cultivars in Tanzania have not been determined before and consequently; crop modeling approaches to address biophysical resource management challenges has not been effective. The objective of this study was to evaluate DSSAT (v4.5) Cropping System Model (CSM) using four adapted maize cultivars namely Stuka, Staha, TMV1 and Pioneer HB3253 for quantifying model parameters. The results indicate that maize cultivars did not differ significantly in terms of the number of days to anthesis, maturity, or grain weight except final aboveground biomass. Also, there was no difference between variables with respect to growing seasons. The cultivar specific parameters obtained were within the acceptable range of those for a hypothetical maize medium season cultivar (990002) included in the DSSAT 45 CSM. Model evaluation results indicate that using the estimated cultivar coefficients, the model simulated well the effects of varying nitrogen management as indicated by the agreement index (d-statistic) closer to unity. Therefore, it is concluded that model calibration and evaluation was satisfactory within the limits of test conditions, and that the model fitted with cultivar specific parameters can be used in simulation studies for research, farm management or decision making.

CERES-Maize; Crop System Model; Nitrogen; Phenology; Morogoro

Mourice, S. , Rweyemamu, C. , Tumbo, S. and Amuri, N. (2014) Maize Cultivar Specific Parameters for Decision Support System for Agrotechnology Transfer (DSSAT) Application in Tanzania. American Journal of Plant Sciences, 5, 821-833. doi: 10.4236/ajps.2014.56096.