Evaluation of N submodel of CERES-maize under Egyptian desert soil conditions of North Sinai [electronic resource].

Includes references.

Maize (Zea mays L.) is one of the most important cereal crop cultivated in Egypt. A new research techniques and technology transfer are needed to provide with more efficient use of resources and alternative systems for increasing productivity and prediction of yield. The Decision Support System for Agro technology transfer (DSSAT V 4.5) that includes N sub model of CERES-Maize was evaluated under Egyptian desert condition of North Sinai. The study area located at El Maghara Research Station of Desert Research Center at North Sinai - Egypt (30 34 N°, 33 19 E°). Maize (Zea mays) was sown in summer, growing season of year 2001. The experimental treatments were eight levels of N (0, 60, 100, 140, 175,215,250,290 kg N ha⁻¹ ) as nitric acid (15.6% N) applied through drip irrigation system. The input data to' the model included daily weather data, site information, soil characteristics for each layer, soil initial conditions and fertilizer management, crop and irrigation management. The evaluation of the N sub model was conducted on maize grains and straw yield as a validation parameter. The results of the study indicated that the regression coefficient (R²) for grains and straw are between field and predicted results 0.61 and 0.77, respectively. The average ,of the simulated maize grains yield for all treatments was 117% of the measured yield. The average of the simulated corn straw yield for all treatments was 89.1 % of the measured yield. The N sub model of CERES-Maize provided acceptable rage or prediction for grains and straw yield of maize under different rates of N application. The predicted results of the treatments followed the same trend as the observed ones. The model call be used to predict grains and straw yield of maize after calibration and evaluation of the experimental data for the field tested. Further research is needed to evaluate the ability of the N model to predict maize grain and straw yield under different conditions of soils, cultivar and weather. The decision support tool can be used for evaluation of predicted maize yield based on local weather and soil conditions and management practices. The proposed decision support tool will provide decision makers with an additional option to integrate local weather and soil conditions in their management decision making which will be transferred and delivered to farmers. This weather. soil and crops-based decision support system should lead to an enhanced production of maize and provide information for future agricultural planning that will lead to an improvement of the food security in Egypt.

Summary in Arabic.

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