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根系时间细粒度表型分析研究——改进的YoloV8seg应用于原位根时间表型的细粒度分析

Research on Fine-Grained Phenotypic Analysis of Temporal Root Systems - Improved YoloV8seg Applied for Fine-Grained Analysis of In Situ Root Temporal Phenotypes.

作者信息

Yu Qiushi, Zhang Meng, Wang Liuli, Liu Xingyun, Zhu Lingxiao, Liu Liantao, Wang Nan

机构信息

State Key Laboratory of North China Crop Improvement and Regulation, College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding, 071000, China.

State Key Laboratory of North China Crop Improvement and Regulation, College of Agronomy, Hebei Agricultural University, Baoding, 071000, China.

出版信息

Adv Sci (Weinh). 2025 Feb;12(5):e2408144. doi: 10.1002/advs.202408144. Epub 2024 Dec 12.

Abstract

Root systems are crucial organs for crops to absorb water and nutrients. Conducting phenotypic analysis on roots is of great importance. To date, methods for root system phenotypic analysis have predominantly focused on semantic segmentation, integrating phenotypic extraction software to achieve comprehensive root phenotype analysis. This study demonstrates the feasibility of instance segmentation tasks on in situ root system images. An improved YoloV8n-seg network tailored for detecting elongated roots is proposed, which outperforms the original YoloV8seg in all network performance metrics. Additionally, the post-processing method introduced reduces root identification errors, ensuring a one-to-one correspondence between each root system and its detection box. The experiment yields phenotypic parameters for fine-grained roots, such as fine-grained root length, diameter, and curvature. Compared to traditional parameters like total root length and average root diameter, these detailed phenotypic analyses enable more precise phenotyping and facilitate accurate artificial intervention during crop cultivation.

摘要

根系是作物吸收水分和养分的关键器官。对根系进行表型分析非常重要。迄今为止,根系表型分析方法主要集中在语义分割上,集成表型提取软件以实现全面的根系表型分析。本研究证明了对原位根系图像进行实例分割任务的可行性。提出了一种针对检测细长根系而改进的YoloV8n-seg网络,在所有网络性能指标上均优于原始的YoloV8seg。此外,引入的后处理方法减少了根系识别错误,确保每个根系与其检测框之间一一对应。实验得出了细根的表型参数,如细根长度、直径和曲率。与总根长和平均根径等传统参数相比,这些详细的表型分析能够实现更精确的表型鉴定,并有助于在作物种植过程中进行准确的人工干预。

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