A deep learning-integrated phenotyping pipeline for vascular bundle phenotypes and its application in evaluating sap flow in the maize stem

作     者：Jianjun Du Ying Zhang Xianju Lu Minggang Zhang Jinglu Wang Shengjin Liao Xinyu Guo Chunjiang Zhao Jianjun Du;Ying Zhang;Xianju Lu;Minggang Zhang;Jinglu Wang;Shengjin Liao;Xinyu Guo;Chunjiang Zhao

作者机构：Beijing Key Lab of Digital PlantResearch Center of Information TechnologyBeijing Academy of Agriculture and Forestry SciencesBeijing 100097China 

出 版 物：《The Crop Journal》 (作物学报（英文版）)

年 卷 期：2022年第10卷第5期

页      面：1424-1434页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 080203[工学-机械设计及理论] 09[农学] 0901[农学-作物学] 0835[工学-软件工程] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Construction of Collaborative Innovation Center of Beijing Academy of Agriculture and Forestry Science (KJCX201917) Beijing Academy of Agriculture and Forestry Sciences Grants (QNJJ202124) the National Natural Science Foundation of China (31801254 and U21A20205) Beijing Natural Science Foundation (5202018) 

主　　题：Deep learning Maize stem Phenotyping Semantic segmentation Vascular bundle 

摘      要：Plant vascular bundles are responsible for water and material transportation, and their quantitative and functional evaluation is desirable in plant research. At the single-plant level, the number, size, and distribution of vascular bundles vary widely, posing a challenge to automatically and accurately identifying and quantifying them. In this study, a deep learning-integrated phenotyping pipeline was developed to robustly and accurately detect vascular bundles in Computed Tomography(CT) images of stem internodes. Two semantic indicators were used to evaluate and identify a suitable feature extraction network for semantic segmentation models. The epidermis thickness of maize stem was evaluated for the first time and adjacent vascular bundles were improved using an adaptive watershed-based approach. The counting accuracy(R^(2)) of vascular bundles was 0.997 for all types of stem internodes, and the measured accuracy of size traits was over 0.98. Combining sap flow experiments, multiscale traits of vascular bundles were evaluated at the single-plant level, which provided an insight into the water use efficiency of the maize plant.