Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi
"This database links plot-level agronomic management with high-resolution thermal and multispectral drone observations to quantify nitrogen use efficiency (NUE) and water use efficiency (WUE) in rice during the Kharif 2025 season at the Paniyara site near Varanasi. Agronomic records include crop est...
| Main Authors: | , , , , , , |
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| Format: | Conjunto de datos |
| Language: | Inglés |
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International Rice Research Institute
2025
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/179375 |
| _version_ | 1855534491236302848 |
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| author | Peramaiyan, Panneerselvam Kumar, Sunil Srivastava, Amit Dugesar, Vikas Dastidar, Payel Ghosh Srivastava, Swati Murugesan, Deiveegan |
| author_browse | Dastidar, Payel Ghosh Dugesar, Vikas Kumar, Sunil Murugesan, Deiveegan Peramaiyan, Panneerselvam Srivastava, Amit Srivastava, Swati |
| author_facet | Peramaiyan, Panneerselvam Kumar, Sunil Srivastava, Amit Dugesar, Vikas Dastidar, Payel Ghosh Srivastava, Swati Murugesan, Deiveegan |
| author_sort | Peramaiyan, Panneerselvam |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | "This database links plot-level agronomic management with high-resolution thermal and multispectral drone observations to quantify nitrogen use efficiency (NUE) and water use efficiency (WUE) in rice during the Kharif 2025 season at the Paniyara site near Varanasi. Agronomic records include crop establishment method (vattar DSR and PTR), variety, fertilizer recommendation pathways, split nutrient applications, irrigation events, machinery use, and weed and pest management. Ground observations cover tiller density, plant height, panicle length, test weight, and grain yield.
Thermal UAV data provide canopy temperature and derived stress indicators linked to irrigation timing and soil moisture dynamics, while multispectral imagery (including visible and NIR bands) enables computation of vegetation indices for crop vigor and nitrogen status. The synchronized acquisition allows direct association of spectral–thermal signals with management practices and yield outcomes. What this really means is that the dataset supports field-scale diagnosis of N and water stress, benchmarking of NUE and WUE across management regimes, and development of data-driven advisories and models for precision rice management under eastern Indo Gangetic conditions.
The extensive data intends to support the development of AI enabled agro-advisory system using baseline and near real time data." |
| format | Conjunto de datos |
| id | CGSpace179375 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | International Rice Research Institute |
| publisherStr | International Rice Research Institute |
| record_format | dspace |
| spelling | CGSpace1793752026-01-05T06:57:58Z Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi Peramaiyan, Panneerselvam Kumar, Sunil Srivastava, Amit Dugesar, Vikas Dastidar, Payel Ghosh Srivastava, Swati Murugesan, Deiveegan databases agronomic practices cropping systems thermal analysis technology adoption climate-smart agriculture sustainable agriculture "This database links plot-level agronomic management with high-resolution thermal and multispectral drone observations to quantify nitrogen use efficiency (NUE) and water use efficiency (WUE) in rice during the Kharif 2025 season at the Paniyara site near Varanasi. Agronomic records include crop establishment method (vattar DSR and PTR), variety, fertilizer recommendation pathways, split nutrient applications, irrigation events, machinery use, and weed and pest management. Ground observations cover tiller density, plant height, panicle length, test weight, and grain yield. Thermal UAV data provide canopy temperature and derived stress indicators linked to irrigation timing and soil moisture dynamics, while multispectral imagery (including visible and NIR bands) enables computation of vegetation indices for crop vigor and nitrogen status. The synchronized acquisition allows direct association of spectral–thermal signals with management practices and yield outcomes. What this really means is that the dataset supports field-scale diagnosis of N and water stress, benchmarking of NUE and WUE across management regimes, and development of data-driven advisories and models for precision rice management under eastern Indo Gangetic conditions. The extensive data intends to support the development of AI enabled agro-advisory system using baseline and near real time data." 2025 2026-01-05T06:57:57Z 2026-01-05T06:57:57Z Dataset https://hdl.handle.net/10568/179375 en Limited Access International Rice Research Institute Peramaiyan, Panneerselvam, Sunil Kumar, Amit Srivastava, Vikas Dugesar, Payel Ghosh Dastidar, Swati Srivastava, Deiveegan Murugesan (2025). Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi. International Rice Research Institute. |
| spellingShingle | databases agronomic practices cropping systems thermal analysis technology adoption climate-smart agriculture sustainable agriculture Peramaiyan, Panneerselvam Kumar, Sunil Srivastava, Amit Dugesar, Vikas Dastidar, Payel Ghosh Srivastava, Swati Murugesan, Deiveegan Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi |
| title | Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi |
| title_full | Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi |
| title_fullStr | Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi |
| title_full_unstemmed | Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi |
| title_short | Integrated Agronomic Management and Thermal–Multispectral UAV–Based Database of Direct-Seeded and Transplanted Rice in Paniyara, Varanasi |
| title_sort | integrated agronomic management and thermal multispectral uav based database of direct seeded and transplanted rice in paniyara varanasi |
| topic | databases agronomic practices cropping systems thermal analysis technology adoption climate-smart agriculture sustainable agriculture |
| url | https://hdl.handle.net/10568/179375 |
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