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<p>Accurate assessment of plant height is fundamental in rice breeding and genetic studies, yet manual measurements are labor-intensive and unsuitable for large-scale trials. In this study, unmanned aerial vehicle (UAV) imagery was employed to estimate rice plant height in paddy fields, and the estimates were validated using manual measurements and quantitative trait locus (QTL) analysis. Orthomosaics and digital surface models (DSM) were generated with Pix4D, and UAV-derived plant height showed strong correlations with ground-based measurements. Bland–Altman analysis further confirmed that UAV estimates reliably reflected actual plant height. QTL mapping consistently identified a major locus on chromosome 1 between 188 and 191&#xa0;cM, corresponding to the well-characterized <i>semi-dwarf1 (sd1)</i> gene. A minor QTL was also repeatedly detected on chromosome 8. Together, these findings demonstrate that UAV-based phenotyping provides both precision and reliability, supporting its direct application in genetic studies. Moreover, this work highlights the potential of UAV-enabled high-throughput phenotyping as a valuable tool for accurate trait measurement and genetic analysis in rice and other crops.</p>

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Study on rice plant height estimation using unmanned aerial vehicle (UAV) imagery and validation with QTL analysis

  • 期刊论文

  • 发表日期：

    2025年10月24日

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  • Yunjeong Jeong,
  • Do-hyun Kim,
  • Ji-hyeon Lee,
  • Jeonghwan Seo,
  • Sungyul Chang

摘要

Accurate assessment of plant height is fundamental in rice breeding and genetic studies, yet manual measurements are labor-intensive and unsuitable for large-scale trials. In this study, unmanned aerial vehicle (UAV) imagery was employed to estimate rice plant height in paddy fields, and the estimates were validated using manual measurements and quantitative trait locus (QTL) analysis. Orthomosaics and digital surface models (DSM) were generated with Pix4D, and UAV-derived plant height showed strong correlations with ground-based measurements. Bland–Altman analysis further confirmed that UAV estimates reliably reflected actual plant height. QTL mapping consistently identified a major locus on chromosome 1 between 188 and 191 cM, corresponding to the well-characterized semi-dwarf1 (sd1) gene. A minor QTL was also repeatedly detected on chromosome 8. Together, these findings demonstrate that UAV-based phenotyping provides both precision and reliability, supporting its direct application in genetic studies. Moreover, this work highlights the potential of UAV-enabled high-throughput phenotyping as a valuable tool for accurate trait measurement and genetic analysis in rice and other crops.