Diversity of photosynthesis-related and high-throughput phenotyping traits in indica rice

Abstract

Manual phenotyping of photosynthesis-related traits in rice is labor-intensive and limits the scale and temporal resolution of genetic analysis under field conditions. Here, we integrated unmanned aerial vehicle (UAV)-based high-throughput phenotyping (HTP) with genome-wide association studies (GWAS) to dissect the diversity and genetic architecture of photosynthesis-related traits in a large indica rice diversity panel (>300 accessions) evaluated across three dry seasons. A total of 45 traits, including UAV-derived NDVI, canopy height, and canopy temperature, together with leaf gas-exchange, stomatal, anatomical, and agronomic traits, were quantified. UAV-derived traits captured temporal growth and senescence dynamics and showed strong and consistent correlations with leaf photosynthetic rate, stomatal conductance, flowering time, biomass, and grain yield. GWAS identified multiple QTLs for photosynthetic and HTP traits, including a cross-year stable transpiration-rate QTL (qTRMMOL-2-2) and a photosynthetic-rate QTL (qPHOTO-1-2). Haplotype analyses revealed that the wall-associated receptor-like kinase gene OsWAK6 and the potassium transporter gene OsHAK1 were strongly associated with variation in photosynthetic rate and transpiration, respectively. Several elite accessions with consistently high photosynthetic performance carried superior haplotypes at multiple qPHOTO loci, suggesting their potential value for breeding. Together, our results demonstrate that UAV-based HTP provides reliable field-scale proxies for physiological performance, and that integrating HTP with GWAS can enable the identification of genetic targets for improving photosynthesis, water use, and yield potential in rice. • Forty-five traits, including HTP, photosynthesis, and leaf morphology, were measured across three dry seasons in diverse Indica rice. • GWAS identified genes linked to photosynthesis and stomatal density, aiding in breeding resilient, high-yield rice. • UAV-based HTP data effectively tracked plant growth and senescence, correlating with photosynthetic rate. • GWAS co-localization revealed shared QTLs, suggesting multi-trait regulation by common genes.

Plant phenotyping relevance

UAVベースのHTPによる植物形質取得と生理性能の推定が研究の中心であり、45形質を大規模・反復的に測定し、信頼性や他の生理形質との相関も評価している。

Code and data availability

The paper reports UAV-based high-throughput phenotyping, gas-exchange, stomatal, and GWAS analyses of an indica rice panel, but provides no public deposit of phenotype datasets, drone imagery, or analysis code. The only availability statement is 'Data will be made available on request.' Supplementary data is referenced

No evidence-backed public reproduction asset is currently recorded.