Tomato Stem and Leaf Segmentation and Phenotype Parameter Extraction Based on Improved Red Billed Blue Magpie Optimization Algorithm

In response to the structural changes of tomato seedlings, traditional image techniques are difficult to accurately quantify key morphological parameters, such as leaf area, internode length, and mutual occlusion between organs. Therefore, this paper proposes a tomato point cloud stem and leaf segme...

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Bibliographic Details
Main Authors:	Lina Zhang, Ziyi Huang, Zhiyin Yang, Bo Yang, Shengpeng Yu, Shuai Zhao, Xingrui Zhang, Xinying Li, Han Yang, Yixing Lin, Helong Yu
Format:	Article
Language:	English
Published:	MDPI AG 2025-01-01
Series:	Agriculture
Subjects:	tomato plants red-billed blue magpie optimization algorithm elite strategy point cloud segmentation convolutional neural network phenotype extraction analysis
Online Access:	https://www.mdpi.com/2077-0472/15/2/180
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Tomato Stem and Leaf Segmentation and Phenotype Parameter Extraction Based on Improved Red Billed Blue Magpie Optimization Algorithm

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