OrchardQuant ‐ 3D : combining drone and LiDAR to perform scalable 3D phenotyping for characterising key canopy and floral traits in fruit orchards

作者：Yunpeng Xia, Hanghang Li, Fanhang Zhang, Gang Sun, Kaijie Qi, Robert Jackson, Felipe Grillo Pinheiro, Xiaoman Liu, Yue Mu, Shaoling Zhang, Greg Deakin, E. Charles Whitfield, Shutian Tao, Ji Zhou · 发表于：Plant Biotechnology Journal · 年份：2025 · DOI：10.1111/pbi.70229 · 被引用次数：9 · 研究领域：Remote Sensing and LiDAR Applications、Horticultural and Viticultural Research、Plant Pathogens and Fungal Diseases

Orchard fruits such as pear and apple are important for ensuring global food security and agricultural economy as they not only provide essential nutrients, but also support biodiversity and ecosystem services. Breeders, growers and plant researchers constantly study desirable tree morphological features and floral characteristics to ensure fruit production and quality. Still, traditional orchard phenotyping is often laborious, limited in scale and prone-to-error, resulting in many attempts to develop reliable and scalable toolkits to address this challenge. Here, we present OrchardQuant-3D, an analytic pipeline for automating tree-level analysis of key canopy and floral traits for different types of fruit orchards. We first built a data fusion algorithm to register 3D point clouds collected by both drones (for colour signals) and Light Detection And Ranging (LiDAR, for precise spatial properties), reconstructing high-quality 3D orchard models at different growth stages. Then, we utilised precise global navigation satellite system signals to position trees in orchards with millimetre-level accuracy, enabling tree-level analysis of key canopy (e.g. crown volume and the number or branches) and floral traits (e.g. blossom clusters and volumes) using 3D computer vision, complex graph theory and feature engineering techniques. Equipped with the OrchardQuant-3D pipeline, we successfully measured varietal differences of four pear cultivars from a small pear orchard in Nanjing China,...