Forecasting of Productivity and Pod Damage by Helicoverpa armigera using Artificial Neural Network Model in Pigeonpea (Cajanus cajan)

摘要

Pigeonpea (Cajanus cajan) is one of the most important food legume, making it an ideal supplement to traditional cereals, which are generally protein-deficient. So, due to its high nutritional value and enormous losses caused by insect pests, it is very important to forecast the damage caused by major insect-pests and the yield of this crop. In this paper, Artificial Neural Network (ANN) model was developed to forecast productivity (Kg/ha) and percent pod damage by a key insect pest Helicoverpa armigera of long duration pigeonpea in North East Plain Zone (NEPZ) of India. The forecasted values of percent pod damage by this pest and productivity of Pigeonpea during 2012-13 were obtained as 26.29% and 1137.40 kg/ha, respectively. The performance of themodel was assessed by values of the mean squared error, and the model was found suitable for the problem under study.