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Data-centric Approach for Farming Support System in Semiarid Area of India
Authors: Seishi Ninomiya,
Identifier: CSBE21708
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Published in: CSBE-SCGAB Technical Conferences » 5th CIGR and AGM Quebec City 2021 » World Congress on Computers in Agriculture and Natural Resources
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Description: The 21st century agriculture requires achieving high productivity while realizing its sustainability and solving the complex issues particularly in fragile and large semi-arid tracts, which is 80 per cent of total arable area of India. The unstable crop production is attributed to biotic and abiotic pressures and lack of proper cultivars, lack of knowledge of farmers, etc. A bilateral research project entitled ?Data Science-based Farming Support System for Sustainable Crop Production under Climatic Change? has been conducted under the support of Japan Science Technology Agency (JST) and Department of Science and Technology, India (DST). The project aims to establish a joint laboratory for solving the agricultural issues particularly in semiarid area of India, maximally utilizing data science including artificial intelligence such as machine learning. This paper will report the current status of the 5 year project. The project is composed of 6 working packages; namely, WP1: Development of IoT/field sensors and field monitoring drone systems, WP2: Interoperable data management with standardized APIs, WP3: Data analytics with AI/Deep learning and image analysis, WP4: Optimal maize crop management with efficient water use, WP5: Efficient transfer of customized and personalized knowledge to farmers and WP6: High-throughput breeding system for aerobic rice. They are mutually collaborating in an interdisciplinary manner. The first stage of the project will last for 5 years until March 2022.
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Date: 2021-06-11
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Conference name: 5th CIGR International Conference and CSBE-SCGAB AGM 2021, Quebec City,QC, 11-14 May 2021.
Session name: World Congress on Computers in Agriculture and Natural Resources (WCCA 1)
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Type: Text.Abstract
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Publication type: Presentation
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Language 1: en
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Rights: Canadian Society for Bioengineering
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DOI:
Description: The 21st century agriculture requires achieving high productivity while realizing its sustainability and solving the complex issues particularly in fragile and large semi-arid tracts, which is 80 per cent of total arable area of India. The unstable crop production is attributed to biotic and abiotic pressures and lack of proper cultivars, lack of knowledge of farmers, etc. A bilateral research project entitled ?Data Science-based Farming Support System for Sustainable Crop Production under Climatic Change? has been conducted under the support of Japan Science Technology Agency (JST) and Department of Science and Technology, India (DST). The project aims to establish a joint laboratory for solving the agricultural issues particularly in semiarid area of India, maximally utilizing data science including artificial intelligence such as machine learning. This paper will report the current status of the 5 year project. The project is composed of 6 working packages; namely, WP1: Development of IoT/field sensors and field monitoring drone systems, WP2: Interoperable data management with standardized APIs, WP3: Data analytics with AI/Deep learning and image analysis, WP4: Optimal maize crop management with efficient water use, WP5: Efficient transfer of customized and personalized knowledge to farmers and WP6: High-throughput breeding system for aerobic rice. They are mutually collaborating in an interdisciplinary manner. The first stage of the project will last for 5 years until March 2022.
Keywords:
Résumé:
Mots-clés:
Citation:
Volume:
Issue:
Pages -
Contributor:
Date: 2021-06-11
Technical field:
Conference name: 5th CIGR International Conference and CSBE-SCGAB AGM 2021, Quebec City,QC, 11-14 May 2021.
Session name: World Congress on Computers in Agriculture and Natural Resources (WCCA 1)
Other information:
Type: Text.Abstract
Format:
Publication type: Presentation
Source:
Relation:
Coverage:
Language 1: en
Language 2:
Rights: Canadian Society for Bioengineering
Notes:
Other files:
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