农业机械学报2024，Vol.55Issue(5)：207-217,11.DOI:10.6041/j.issn.1000-1298.2024.05.019
基于深度学习的小麦抗旱相关根系表型原位测量与分析
In-situ Measurement and Analysis of Drought-related Wheat Root Phenotypic Traits
摘要
Abstract
The identification and selection of drought-tolerant wheat varieties are of great significance for ensuring food security and sustainable agricultural development in China.The root system serves as the primary pathway for water absorption in plants,and the phenotype of the root system is closely related to drought tolerance.In order to obtain root system phenotypic indicators of wheat quickly and accurately,drought stress experiments were conducted by using the soil box method and collected sequential root images at 18 time points.A deep learning-based image processing and analysis workflow was proposed for root image processing.To address the issue of root breakage caused by soil occlusion,a two-stage detection-repair method combining object detection networks and hourglass attention networks was designed to repair the broken root regions.Multi-scale training and adaptive iteration were employed to improve the accuracy and robustness of the repair process.Six phenotypic traits of wheat root systems,including root area,total root length,and root width,were extracted under drought stress and control conditions,and the phenotypic responses of wheat roots to drought stress were analyzed.The results showed that under drought stress,wheat exhibited lower root biomass,deeper rooting depth,and more dispersed root architecture.The drought tolerance index of wheat root systems was calculated,and the drought tolerance of wheat varieties was described and ranked by using principal component analysis.A method of in-situ measurement and analysis of wheat root phenotype was proposed,which can be applied to the study of wheat drought resistance.关键词
小麦/根系表型/原位测量/抗旱性分析/断根修复/深度学习Key words
wheat/root phenotypic traits/in-situ measurement/drought tolerance analysis/root breakage repair/deep learning分类
信息技术与安全科学引用本文复制引用
段凌凤,傅金阳,王新轶,施家伟,李为坤,杨万能..基于深度学习的小麦抗旱相关根系表型原位测量与分析[J].农业机械学报,2024,55(5):207-217,11.基金项目
国家自然科学基金项目(32170411)、国家重点研发计划项目(2021YFD1201500)和湖北洪山实验室开放课题(2021hskf005) （32170411）
