您好，欢迎访问新疆农业科学院 机构知识库！
新疆农业科学院机构知识库

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

UAV-Based High-Throughput Phenotyping to Segment Individual Apple Tree Row Based on Geometrical Features of Poles and Colored Point Cloud

文献类型： 外文期刊

作者： Mao, Wulan 1 ; Murengami, Bryan 1 ; Jiang, Hanhui 1 ; Li, Rui 1 ; He, Long 3 ; Fu, Longsheng 1 ;

作者机构： 1.Northwest A&F Univ, Coll Mech & Elect Engn, Yangling, Shaanxi, Peoples R China

2.Xinjiang Acad Agr Sci, Inst Agr Mechanizat, Urumqi, Xinjiang, Peoples R China

3.Penn State Univ, Dept Agr & Biol Engn, University Pk, PA USA

4.Minist Agr & Rural Affairs, Key Lab Agr Internet Things, Yangling, Shaanxi, Peoples R China

关键词： Apple trees; Detection; Point cloud; RGB-colored; Segmentation.

期刊名称：JOURNAL OF THE ASABE （ 影响因子：1.0； 五年影响因子：1.0 ）

ISSN： 2769-3295

年卷期： 2024 年 67 卷 5 期

页码：

收录情况： SCI

摘要： . High-throughput phenotyping (HTP) of fruit trees is important for providing crop geometrical information to evaluate their high yield genotypes. Unmanned aerial vehicle (UAV) is suitable for HTP by obtaining remote sensing data of large modern apple orchards, where each tree row needs to be segmented before segmenting a single tree. This study aims to develop a method for segmenting each row without noise (ERWON) of apple trees based on integrating RGB values and three-dimensional coordinates by UAV. A robust, real-time, RGB-colored, and LiDAR-inertial-visual tightly-coupled state estimation network was used to form a dense map of the orchard, which provided datasets of colored point clouds. Supporting poles were removed from the point clouds based on the consistent number of half upper parts and lower parts. Random sampling and an effective local feature aggregator were trained to segment ERWON after pole segmentation. Results showed that a precision of 0.971, a recall of 0.984, and an intersection-over-union of 0.817 for ERWON segmentation were achieved. This method proposed a potential solution for addressing the challenge of accurately and efficiently segmenting ERWON in large orchards. It is expected to be helpful for obtaining general parameters, such as geometric, morphological, and textural characteristics, as well as more specific parameters relevant to a particular phenotyping task.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：新疆农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台