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番茄植株生长过程中茎叶表型的无损分割与提取

王亚鑫 吕洋成 王文琦 刘琦 杨杰 任桂鸿 张吴平 李富忠

中国农业科技导报2025,Vol.27Issue(7):90-100,11.
中国农业科技导报2025,Vol.27Issue(7):90-100,11.DOI:10.13304/j.nykjdb.2024.0080

番茄植株生长过程中茎叶表型的无损分割与提取

Nondestructive Segmentation and Extraction of Stem and Leaf Phenotypes During Tomato Plant Growth

王亚鑫 1吕洋成 1王文琦 1刘琦 1杨杰 1任桂鸿 1张吴平 1李富忠1

作者信息

  • 1. 山西农业大学软件学院,山西 太谷 030801
  • 折叠

摘要

Abstract

Aiming at the current problem that it is difficult to extract the phenotypic parameters of tomato plants without any loss,the stem and leaf segmentation and phenotypic extraction method of tomato plants based on 3D reconstruction was proposed.Firstly,the multi-view image sequences of tomato plants were collected to construct a 3D model of the plant,and a combination of multiple filtering algorithms was used to complete the pre-processing.The skeleton of the pre-processed point cloud was extracted using the Laplace-based skeleton extraction algorithm,and the segmentation of the stem and leaves was completed based on the skeleton of the plant,and the segmentation of the single leaves was completed using the method based on the clustering of hyperbolomers.6 phenotypic parameters including the height of the plant,the thickness of the stem,the angle of the inclination of the leaf,the length of the leaf,the width of the leaf,and the area of the leaf were also extracted.The results showed that the average accuracy,average recall and average F1 score of stem and leaf segmentation were 0.88,0.80 and 0.84,respectively,and the segmentation indexes were better than the other 4 segmentation algorithms.The coefficients of determination between the calculated and measured values of plant height,stem thickness,leaf inclination,leaf length,leaf width and leaf area were 0.97,0.84,0.88,0.94,0.92 and 0.93,respectively,and the root mean square errors were 2.17 cm,0.346 cm,5.65°,3.18 cm,2.99 cm and 8.79 cm2.The measured values of the proposed method had a strong correlation with the calculated values,which provided technical support for high-throughput phenotypic parameter extraction in tomato plants.

关键词

番茄/三维重建/茎叶分割/表型提取

Key words

tomato/three-dimensional reconstruction/stem and leaf segmentation/phenotype extraction

分类

农业科技

引用本文复制引用

王亚鑫,吕洋成,王文琦,刘琦,杨杰,任桂鸿,张吴平,李富忠..番茄植株生长过程中茎叶表型的无损分割与提取[J].中国农业科技导报,2025,27(7):90-100,11.

基金项目

山西省重点研发计划项目(202202140601021) (202202140601021)

山西省科技厅基础研究项目(202103021224123). (202103021224123)

中国农业科技导报

OA北大核心

1008-0864

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