A MODULAR NEURAL NETWORK APPROACH TO CHEMICAL CONTENT ANALYSIS OF VEGETATION

The state of a plant affects its chlorophyll content, which in turn, affects the way the plant reflects light. Consequently, the characteristics of the reflected light can be used to determine the health of a plant. This raises the possibility of monitoring large areas of vegetation by analyzing the reflectance of the plants in the area. This paper discusses the use of neural networks for analyzing the reflectance of plants. We discuss two approaches: the classical approach and a modular approach and demonstrate that the modular approach has certain advantages for analyzing the reflectance of plants. 1