基于高通量根系表型测定平台的干旱胁迫下不同基因型小麦根系性状的研究

Increasing water scarcity, caused by global climate change and increasing competition for available water resources, is a major constraint for crop production and global food security. Consequently, there is an urgent need to breed more drought-tolerant crops to meet future demands of the growing world population. Roots are a multifunctional organ system through which plants obtain most of their water and nutrients required for growth and development. Breeding drought-tolerant cultivars through trait-based selection or ideotype breeding has a crucial role in ensuring national food security. Dynamic phenotyping the root growth and development in response to drought condition, is a prerequisite for breeding drought-tolerant cultivars. However, due to the opaque of the soil, it is extreme difficult to observe and analyse root system under natural conditions. To address these issues, high through-put, automated root imaging platforms, based on two types of new cultivation container, will be designed and constructed. Open-source root analysing software will be adopted and home-made software will be developed to extract multi-scale root architectural traits, respectively, according to the characteristic of different cultivating containers. The reliability and usability of these platforms for root traits phenotyping will be estimated. Based on these root phenotyping platforms, the key phenotypic traits can be chosen as breeding criteria and root ideotype can be quantified, by examining the root traits variation between wheat genotypes with contrasting drought-tolerant under different watering conditions.

由于全球气候变化和水资源的竞争利用，日益严峻的水资源匮乏已成为粮食生产和全球粮食安全的主要制约因素之一。因此，迫切需要培育耐旱作物品种以满足日益增长的未来世界人口的粮食需求。根系是一个多功能器官，决定着作物对水分养分的吸收能力。通过改良根系结构性状来培育抗旱品种对满足我国未来粮食需求具有重要意义。动态观测根系结构对干旱胁迫的响应以深入了解根系性状的功能特性是培育抗旱品种的前提。但土壤的不透明性导致对根系的观察和测定都十分困难。本项目拟自主设计并构建基于两种透明栽培容器的模块化、高通量、自动化根系表型实时成像平台。根据不同栽培容器的特点，采用已有的根系分析软件结合自主开发的软件来提取根系结构性状。通过测试实验验证平台测定结果的可靠性。应用构建的根表型测定平台定量化具有不同抗旱敏感性的小麦在不同水分处理下的根结构特征，确定可用来指导抗旱品种筛选的优势根特征参数，提出耐旱的理想根构型。

通过改良根系性状来培育新品种可有效提高作物产量和养分资源利用效率。但由于根系生长介质的不透明性，导致对作物根系的观测十分困难，亟需系统的、规模化的根系表型实时监测技术来加速对根系性状和功能的研究。本项目结合非标机械自动化设计、运动控制、成像通讯、物联网通讯、软件工程等关键技术，开发高通量、自动化、实时多种类型的根系表型快速监测平台。研发了2套扁根盒自动化成像设备和扁根盒并行灌溉设备，实现对扁根盒的自动化装载和扁根盒正反面的自动化成像，实现对单个栽培框的两排扁根盒的并行精准灌溉。创制了全新的根系栽培容器，提出以高外筒、低封口内筒组合的栽培容器模式，相较于单筒式栽培容器，极大地降低了栽培容器的土壤重量，迫使更多的根系与内筒和外筒紧贴，可获得更完整的根系成像图像。创制了国际上首个圆根盒成像设备，同时包括圆根盒自动化拆堆垛机、自动化组装机、自动化土壤填充设备，实现了从组装、拆堆垛和成像的一体化作业。开发了配套的圆根盒成像作业管理软件系统，实现了设备操作与实验操作的自动化与作业记录。初步开发了基于深度学习的根系图像分析软件。该智能监测平台显著地提高了根系表型信息系统性收集的效率，极大地降低了人力成本和经济成本，创新性地实现标准化、规模化、系统化、自动化、智能化的表型监测。该根系表型设备将会填补国内根系表型研究领域中研究技术和研究设备的空白，切实解决遗传育种研究和基础植物科学研究领域科研人员的需求。