Title: Analysing dynamics of crop problems by applying text analysis methods on farm advisory data of eSagu^TM

Authors: R. Uday Kiran, P. Krishna Reddy, M. Kumara Swamy, G. Syamasundar Reddy

Addresses: Media Lab Asia Project, ICTs for Agriculture and Rural Development, International Institute of Information Technology (IIIT-H), Gachibowli, Hyderabad, Andhra Pradesh, India. ' Media Lab Asia Project, ICTs for Agriculture and Rural Development, International Institute of Information Technology (IIIT-H), Gachibowli, Hyderabad, Andhra Pradesh, India. ' Media Lab Asia Project, ICTs for Agriculture and Rural Development, International Institute of Information Technology (IIIT-H), Gachibowli, Hyderabad, Andhra Pradesh, India. ' Media Lab Asia Project, ICTs for Agriculture and Rural Development, International Institute of Information Technology (IIIT-H), Gachibowli, Hyderabad, Andhra Pradesh, India

Abstract: By extending information and communication technologies, a personalised agricultural advisory system called eSagu^TM has been developed and operated for 1,051 cotton farms in the state of Andhra Pradesh, India, during 2004-005. In this system, agricultural experts have delivered expert advice to each farm at regular intervals based on the crop photographs and other information. In this paper, we have carried out cluster/textual analysis experiments on 20,000 advice texts and reported the results on the dynamics of crop problems. The cluster analysis of the advices delivered on each day shows that significant number of farms are suffering from distinct crop production problems. The results also indicate that, a cluster of farms which faces the same crop problem during one week faces distinct crop problems during the subsequent weeks. Based on the results, we can conclude that it is necessary to build farm-specific agricultural advisory systems to reduce crop failures and improve crop productivity.

Keywords: ICT; electronic agriculture; e-agriculture; computers in agriculture; agricultural information systems; AISs; crop production dynamics; text analysis; cluster analysis; text mining; agricultural advisory systems; personalised advisory systems; crop failures; crop productivity; cotton farming.

DOI: 10.1504/IJCSE.2010.036825

International Journal of Computational Science and Engineering, 2010 Vol.5 No.2, pp.154 - 164

Published online: 10 Nov 2010 *

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