Year: 2013 | Month: June | volume 6 | Issue 2
Forecasting of Productivity and Pod Damage by Helicoverpa armigera using Artificial Neural Network Model in Pigeonpea (Cajanus cajan)
Abstract: <div>Pigeonpea (<i>Cajanus cajan</i>) 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</div><div>this pest and productivity of Pigeonpea during 2012-13 were obtained as 26.29% and 1137.40 kg/ha, respectively. The performance of the model was assessed by values of the mean squared error, and the model was found suitable for the problem under study.</div>
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