Artificial Life of Soybean Plant Growth Modeling Using Intelligence Approaches

Atris Suyantohadi (1Agricultural Technology Faculty, University of Gadjah Mada (UGM), Sosioyustisia, Bulaksumur, Yogyakarta, Indonesia 2Electrical Engineering Department, Industrial Technology Faculty, Institute Technology Sepuluh November (ITS), Surabaya, Indonesia)
Mochamad Hariadi (2Electrical Engineering Department, Industrial Technology Faculty, Institute Technology Sepuluh November (ITS), Surabaya, Indonesia)
Mauridhi Hery Purnomo (2Electrical Engineering Department, Industrial Technology Faculty, Institute Technology Sepuluh November (ITS), Surabaya, Indonesia)

Journal of Mathematical and Fundamental Sciences
Vol. 42 No. 1 (2010)

The natural process on plant growth system has a complex system and it has could be developed on characteristic studied using intelligent approaches conducting with artificial life system. The approaches on examining the natural process on soybean (Glycine Max L.Merr) plant growth have been analyzed and synthesized in these research through modeling using Artificial Neural Network (ANN) and Lindenmayer System (L-System) methods. Research aimed to design and to visualize plant growth modeling on the soybean varieties which these could help for studying botany of plant based on fertilizer compositions on plant growth with Nitrogen (N), Phosphor (P) and Potassium (K). The soybean plant growth has been analyzed based on the treatments of plant fertilizer compositions in the experimental research to develop plant growth modeling. By using N, P, K fertilizer compositions, its capable result on the highest production 2.074 tons/hectares. Using these models, the simulation on artificial life for describing identification and visualization on the characteristic of soybean plant growth could be demonstrated and applied.