A doctoral dissertation at the College of Agriculture, University of Basra, investigated predicting the yield of yellow corn using artificial neural networks, taking into account varying levels of nitrogen and potassium fertilization and irrigation water salinity.
The dissertation, presented by researcher Zahraa Wahih Shalash, aimed to study the efficiency of artificial neural networks in predicting yellow corn yield compared to other statistical programs. The thesis included the use of silty clay soil for cultivating yellow corn and a study of the effect of irrigation water salinity levels, potassium fertilization levels, and their interaction on some crop growth characteristics using DesignExpert software and artificial neural networks.
The study recommended using DesignExpert software to predict yellow corn growth parameters, as well as using artificial neural networks to increase the accuracy of these predictions.
Media and Government Communication Division / College of Agriculture
