The architecture of apple trees plays a pivotal role in shaping their growth and fruit-bearing potential,forming the foundation for precision apple management.Traditionally,2D imaging technologies were employed to del...The architecture of apple trees plays a pivotal role in shaping their growth and fruit-bearing potential,forming the foundation for precision apple management.Traditionally,2D imaging technologies were employed to delineate the architectural traits of apple trees,but their accuracy was hampered by occlusion and perspective ambiguities.This study aimed to surmount these constraints by devising a 3D geometry-based processing pipeline for apple tree structure segmentation and architectural trait characterization,utilizing point clouds collected by a terrestrial laser scanner(TLS).The pipeline consisted of four modules:(a)data preprocessing module,(b)tree instance segmentation module,(c)tree structure segmentation module,and(d)architectural trait extraction module.The developed pipeline was used to analyze 84 trees of two representative apple cultivars,characterizing architectural traits such as tree height,trunk diameter,branch count,branch diameter,and branch angle.Experimental results indicated that the established pipeline attained an R^(2)of 0.92 and 0.83,and a mean absolute error(MAE)of 6.1cm and 4.71mm for tree height and trunk diameter at the tree level,respectively.Additionally,at the branch level,it achieved an R^(2)of 0.77 and 0.69,and a MAE of 6.86 mm and 7.48°for branch diameter and angle,respectively.The accurate measurement of these architectural traits can enable precision management in high-density apple orchards and bolster phenotyping endeavors in breeding programs.Moreover,bottlenecks of 3D tree characterization in general were comprehensively analyzed to reveal future development.展开更多
基金supported by the USDA NIFA Hatch project(accession no.1025032)USDA NIFA Specialty Crop Research Initiative(award no.2020-51181-32197)+4 种基金the McIntire-Stennis award(accession 1027551)from the United States Department of Agriculture Institute of Food and AgricultureCornell Institute of Digital Agriculture Research Innovation FundBeijing Municipal Natural Science Foundation(grant no.1232019)National Natural Science Foundation of China(grant no.12101606)Renmin University of China Research Fund Program for Young Scholars.
文摘The architecture of apple trees plays a pivotal role in shaping their growth and fruit-bearing potential,forming the foundation for precision apple management.Traditionally,2D imaging technologies were employed to delineate the architectural traits of apple trees,but their accuracy was hampered by occlusion and perspective ambiguities.This study aimed to surmount these constraints by devising a 3D geometry-based processing pipeline for apple tree structure segmentation and architectural trait characterization,utilizing point clouds collected by a terrestrial laser scanner(TLS).The pipeline consisted of four modules:(a)data preprocessing module,(b)tree instance segmentation module,(c)tree structure segmentation module,and(d)architectural trait extraction module.The developed pipeline was used to analyze 84 trees of two representative apple cultivars,characterizing architectural traits such as tree height,trunk diameter,branch count,branch diameter,and branch angle.Experimental results indicated that the established pipeline attained an R^(2)of 0.92 and 0.83,and a mean absolute error(MAE)of 6.1cm and 4.71mm for tree height and trunk diameter at the tree level,respectively.Additionally,at the branch level,it achieved an R^(2)of 0.77 and 0.69,and a MAE of 6.86 mm and 7.48°for branch diameter and angle,respectively.The accurate measurement of these architectural traits can enable precision management in high-density apple orchards and bolster phenotyping endeavors in breeding programs.Moreover,bottlenecks of 3D tree characterization in general were comprehensively analyzed to reveal future development.
