Horticulture Plant Disease Prediction by using Graph Database

Author(s):

Shinkita Negi, Suchi Juyal

Published in:

HCTL Open International Journal of Technology Innovations and Research (IJTIR), e-ISSN: 2321-1814

Published on:

31-July-2014

Volume:

Volume 10, July 2014, ISBN:978-1-62951-619-6.

Copyright Information:

© 2014 by the Authors; Licensed by HCTL Open, India.

License Information:

This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License.

Abstract

Horticulture plant pathology is an important part among the various disciplines of horticulture. Plant pathology is diagnosis, management, prediction for plant disease which can help enhance yield and quality of horticultural crops. Plant disease Prediction System provides interface with user for detecting the disease in the plants.There are mainly three types of plant diseases such as Fungal, Bacteria and Virus Plant Disease. We focused here on the fungal diseases classification and prediction Model. We propose an approach for plant disease prediction model for the horticulture plants. To implement this we used the Graph database for the purpose of Integration of the Horticultural Plants database and then classify the data into classes of Fungal Disease. All the data has been represented and traversal by using the graph database, Neo4j.


Keywords

Plant Disease Prediction, Graph Database, Horticulture.

Cite this Article

Shinkita Negi, Suchi Juyal, Horticulture Plant Disease Prediction by using Graph Database, HCTL Open International Journal of Technology Innovations and Research, Volume 10, July 2014, ISSN: 2321-1814, ISBN: 978-1-62951-619-6.

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