SciELO - Scientific Electronic Library Online

 
vol.104 issue7-8 author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Article

Indicators

Related links

  • On index processCited by Google
  • On index processSimilars in Google

Share


South African Journal of Science

On-line version ISSN 1996-7489
Print 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.

        · text in English     · English ( pdf )

 

Creative Commons License All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License