A large indica rice diversity panel (>300 accessions) was evaluated across three dry seasons. The dataset includes 45 traits derived from unmanned aerial vehicle (UAV) phenotyping, leaf gas-exchange measurements, stomatal and anatomical traits, and agronomic traits. It was created by Hsiang-Chun Lin and hosted on the IRRI Dataverse, with a last update recorded in May 2026.
Use Cases
- Perform genome-wide association studies (GWAS) based on UAV-derived NDVI, canopy height, and canopy temperature traits.
- Analyze temporal growth and senescence dynamics based on UAV-derived trait measurements.
- Identify elite breeding accessions based on haplotype analyses of photosynthetic rate and transpiration QTLs.
- Study correlations between UAV proxies and physiological performance metrics like leaf photosynthetic rate and stomatal conductance.
Strengths
- Includes >300 rice accessions, providing a large genetic diversity panel.
- Quantifies 45 traits across multiple categories, including UAV-derived, physiological, and agronomic measurements.
- Data collection spanned three dry seasons, allowing for cross-year stability analysis.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- IRRI Dataverse
- Collection Method
- Integrated unmanned aerial vehicle (UAV)-based high-throughput phenotyping (HTP) with genome-wide association studies (GWAS).
- Time Range
- Three dry seasons
- Freshness
- Last updated 2026-05-05 04:43:14; freshness should be verified.