Neural Networks in Cultivation

Indian farming community is facing multitude of problems. Insect pests are supposed to be a major constraint to the crop productivity. The main problem in addressing the issue of pest management is inadequate knowledge about the factors influencing the pest dynamics. In this paper an effort has been made to compare the efficiency of the prediction systems using the regression modeling, Bayesian analysis and neural network techniques. This was achieved by understanding the pest dynamics of Spodptera Litura on the groundnut crop with the data provided by ICRISAT. The results show that neural network system is the only one giving results with a very high degree of accuracy and is best suited to build a pest prediction system for groundnut crop