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Understanding Helicoverpa armigera pest population dynamics related to chickpea crop using neural networks

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Relation http://oar.icrisat.org/2801/
 
Title Understanding Helicoverpa armigera pest population dynamics related to chickpea crop using neural networks
 
Creator Gupta, Rajat
Narayana, B V L
Reddy, P K
Ranga Rao, G V
Gowda, C L L
Reddy, Y V R
Murthy, G R
 
Subject Chickpea
 
Description Insect pests are a major cause of crop loss globally. Pest management will be effective and efficient if we can predict the occurrence of peak activities of a given pest. Research efforts are going on to understand the pest dynamics by applying analytical and other techniques on pest surveillance data sets. We make an effort to understand pest population dynamics using neural networks by analyzing pest surveillance data set of Helicoverpa armigera or Pod borer on chickpea (Cicer arietinum L.) crop. The results show that neural network method successfully predicts the pest attack incidences for one week in advance.
 
Date 2003
 
Type Conference or Workshop Item
PeerReviewed
 
Format application/pdf
 
Language en
 
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Identifier http://oar.icrisat.org/2801/1/UnderstandingHelicoverpaArmigeraPestPopulationDynamicsRelated.pdf
Gupta, Rajat and Narayana, B V L and Reddy, P K and Ranga Rao, G V and Gowda, C L L and Reddy, Y V R and Murthy, G R (2003) Understanding Helicoverpa armigera pest population dynamics related to chickpea crop using neural networks. In: Third IEEE international conference on data mining, 19-22 Nov 2003, Melbourne, Florida.