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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/31056
Title: | Diseases and Pests Identification in Maize – A Multilingual Scenario |
Authors: | Sudeep Marwaha Punam Bedi V.K. Yadav |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR::Indian Agricultural Statistics Research Institute |
Published/ Complete Date: | 2017-04-12 |
Project Code: | Not Available |
Keywords: | detection expert systems maize pests plant diseases plant pests |
Publisher: | Journal of Indian Society of Agricultural Statistics (Special issue on AI) |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | Abstract : Pests and diseases cause major economic losses to the farmers. The estimate loss per annum due to diseases and pests in a country like India touches to billions of Rupees. Most of the time farmers use over dosages of pesticides and fungicides to save their crop and thus cause environmental hazards. The presented expert system is designed to help farmers to identify diseases and insects attacking maize crop which is neither feasible nor practical by conventional system of extension. Traditional expert systems are based on rules and facts whereas the knowledge base of this expert system is built using ontology - the latest knowledge representation technique. OWL is the W3C specifications for building ontologies. It is based on XML and Unicode. Moreover, rule-based knowledge base is not inherently based on Unicode and thus lacks support for internationalization or for regional languages. The system acts as a tool for transferring the site and crop specific knowledge of various domain experts to the farmers. The system is integrated with the Maize Agridaksh. Agridaksh is a tool for developing online expert system of crops. India being a multilingual society with over 16 major languages and most of the farmers across the country understands their local language only. This system is multilingual and at present contains knowledge in English and Hindi languages. |
Description: | Not Available |
ISSN: | 0019-6363 |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Journal of Indian Society of Agricultural Statistics |
NAAS Rating: | 5.51 |
Volume No.: | 67(1) |
Page Number: | 107-120 |
Name of the Division/Regional Station: | Division of Computer Application |
Source, DOI or any other URL: | Not Available |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/31056 |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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Diseases and Pests Identification in Maize – A Multilingual Scenario.pdf | 1.36 MB | Adobe PDF | View/Open |
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