PLANTAIN TREE GROWTH (MUSA SP., AAB CULTIVAR HORN 1) MODELING USING THE ARTIFICIAL NEURAL NETWORKS METHOD

Abstract

The plantain tree growth is made up of a number of growth parameters such as leaves number (Ln), leaf length (Ll), leaf width (Lw), pseudo-stem height (Hp), width at 10 cm above the ground (W10), pseudo-stem width at middle (Wm) and its width at top (Wt). A study of these growth parameters was carried out in the area of Azaguié (Côte d'Ivoire). The results show that plantain tree growth depends on growth parameters evolution. For this purpose, mathematical models were developed to predict the growth using an artificial neural network. Satisfactory results were obtained since all the determination coefficients were higher than 0.97. These coefficients are approximately 1, and it points out the ability of the artificial neural network to map suitably the experimental data.