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

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.

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Abstract

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.

Item Type:	Conference or Workshop Item (Paper)
Divisions:	UNSPECIFIED
CRP:	UNSPECIFIED
Subjects:	Mandate crops > Chickpea
Depositing User:	Users 6 not found.
Date Deposited:	18 Oct 2011 08:17
Last Modified:	17 May 2018 05:00
URI:	http://oar.icrisat.org/id/eprint/2801
Acknowledgement:	UNSPECIFIED
Links:	Author

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