| Summary: | "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."
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