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    South African Journal of Science

    On-line version ISSN 1996-7489Print version ISSN 0038-2353

    Abstract

    MWASIAGI, Josphat Igadwa; HUANG, Xiu Bao  and  WANG, Xin Hou. Prediction of cotton yield in Kenya. S. Afr. j. sci. [online]. 2008, vol.104, n.7-8, pp.249-250. ISSN 1996-7489.

    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.

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