South African Journal of Science
On-line version ISSN 1996-7489
Print version ISSN 0038-2353
COTTON YIELD IS ONE OF THE INDICATORS for describing agricultural efficiency from different resource management methods in the cotton-growing industry. Selected cotton-growing cost factors were used to design an artificial neural network model to predict cotton yield in Kenya. This neural network model was able to predict cotton yield with a satisfactory performance error of 0.204 kg/ha and a regression correlation coefficient between network output and actual yield of 0.945.