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田间玉米根系三维结构的测定与可视化

Quantification and Visualization of Three-dimensional Root System Architecture of Field-grown Maize

【作者】 吴劼

【导师】 郭焱;

【作者基本信息】 中国农业大学 , 土地利用与信息技术, 2014, 博士

【摘要】 根系结构指各个根段的拓扑连接和几何形态,它对植物吸收水分和养分有着重要的作用。根系结构在品种间以及同一品种间的不同基因型有着很大的差异。根系会随着土壤环境的改变而改变其结构,具有很强的可塑性。根特征的数量性状点位(QTLs)与植株生产力的QTLs在位置上具有一定的交叉,说明了根系结构决定了植株的生产力。根结构的这些特性说明了其在作物栽培和育种研究中的重要意义。但是由于根系生长在不透明的土壤中,其观察和测定都比较困难,阻碍对根系结构的深入了解,限制了根系结构模型的参数化,同时阻碍了其在作物栽培、育种上的应用。为了解决这一问题,开发了一整套用于测定田间成熟玉米根系结构的方法。对于轴根结构,采用三维数字化仪在田间原位测定一定土体范围内(80cm长,60cm宽,45cm深)的相邻玉米植株轴根的三维生长轨迹,同时结合图像处理方法获取相应轴根上的直径变化。对于节根的侧根结构,我们开发了一套集成的方法:采用自行设计和制造的整根取样系统获取相对完整的玉米整株根系;结合商用图像处理软件WinRHIZO Pro和自行开发的Excel VBA数据处理程序提取每条节根的侧根拓扑结构和几何形态数据。整根取样系统包括一个由两个半圆柱铁框构成的取样框(50cm直径和55cm深),一个电动夯框机(2.2m高、1.1m长和1m宽),一个吊框架(宽1.2m,高2m)和一套洗根系统。该整套测定方法用于测定两个品种玉米(郑单958和先玉335)的根系结构。为实现根系结构重建,我们开发了一个viRoot软件。该软件采用C++语言编写,应用Boost库,SQLite关系型数据库和可视化图形库(Visualisation Toolkit)。采用Para View软件执行可视化。viRoot用于重建轴根三维结构,侧根二维结构以及将侧根匹配到轴根构建根系三维结构。通过对轴根结构的分析,发现相邻两个品种玉米植株在行内与行间的不等距离以及由其造成的根系占有的土壤体积的不同不会对轴根的生长轨迹造成影响。不同品种玉米的不同节根轮次轴根的初始角度和在表土层中的水平扩展量有着很大的差异,但根角度的分布模式差异较小。两个品种玉米的轴根的直径沿轴根下降的趋势随节根轮次的增高而增强;同时,两个品种的同一轮次的轴根的直径下降程度相同。5cm轴根根段角度与其根段直径有着线性相关。这些结果为参数化根系结构模型的轴根部分提供有价值的信息。通过对节根侧根结构的分析得出二级以及更高级别侧根占30cm长节根的总侧根长和总数量的大部分,其占总侧根数量的比例可达85%。不同级别的侧根的长度变异很大,其长度的概率密度分布服从对数正态分布。侧根单元指一级侧根及其上面的更高级别侧根,侧根单元的级别由其最高分枝级别决定。二级及更高级别侧根单元占总侧根长和总数量的绝大部分,其占总侧根长度可达90%。个别侧根单元的分枝能力极强,单条侧根单元最多可达总侧根长的18%。大部分总侧根长和总数量分布在轴根的基部的5cm长分枝段,比例可达90%。以上结果表明,采用三维数字化仪结合图像处理的方法能够精确测定玉米轴根三维空间结构;采用整根取样系统结合图像处理方法能够获取详细的节根的侧根拓扑结构和几何形态数据。将上述两种方法集成能够获得独一无二的关于田间玉米根系结构,能够为参数化根系结构模型提供完整的数据。此外,也能为目前正广泛开展的根结构特征的室内筛选研究与其田间表达的定量关系研究提供有效的数据。

【Abstract】 Root system architecture (RSA), the topology and geometry of root segments, plays a key role in supporting shoot growth and in plant water and nutrients uptake. RSA has large variation among species and gemontypes in the same species. Roots have strong plasticity which can changes their architecture with the variation of soil environment, In several instances, RSA determines the productivity (such as yield, water use and nutrient capture) as the overlap of QTLs for root traits and those for productivity. Hence, understanding the root architecture has significant meaning on advancing the cultivation and plant breeding processing. However, due to the opacity of soil, it is difficult to observing and measuring root system, and thus impeding our thorough understanding on root architecture, limiting the parameterization of root architectural model, and hindering its application on plant breeding.To address these, we developed a suit of method on the quantification of the root architecture of mature field-grown maize. For measuring axile root architecture, we used a three-dimensional(3D) digitizer to measure the3D trajectory of axile root in situ in the field, in parallel with an image processing method for measurement of diameter along the same roots. For measuring the topology and geometry of single nodal roots, we developed an integrated method includes a custom-made whole-root sampling system for extracting intact root systems of individual maize plants, a combination of proprietary software WinRHIZO Pro and a novel Excel VBA program used for collecting individual RSA information. The whole-root sampling system includes a sampling cylinder (50cm diameter and55cm deep), an electric hammer module (2.2m high,1.1m long,1m wide), a lifting module (1.2m wide,2m high) and root washing system. The whole-root sampling system was applied on measurement of root architecture of two maize cultivars (Zhangdan958and Xianyu335). To reconstructe the root architecture, we developed a viRoot software. The software was written using C++language and used Boost library, SQLite relational database and Visualisation Toolkit library. Visualisation was executed using ParaView software. viRoot was used for reconstruction of3D axile root architecture and2D nodal root architecture, and for matching lateral roots on axile roots to construct a whole3D root architecture.Our calculations provide evidence that neither unequal spacing nor unequal soil volumes play a role in determining root trajectory of field-grown maize of both cultivars. The two cultivars had different initial angles from the vertical and horizontal root spread, and presented slightly different patterns of root angle distribution. Root diameter decreased sharply along an axile root arising from the higher whorls. The reorientation of an axile root downwards was related to its angle and diameter. Second-and higher order laterals are found to contribute substantially to total lateral root number and length of a30cm long axile root of nodal root, up to85%in total number of lateral roots. The length of laterals of distinct orders varies significantly. A log-normal distribution is suit to describe the probability density of lateral root length for distinct order. Lateral root unit (LRU) indicates a first-order laterals and higher-order laterals derived from it. LRU rank was determined by highest branching order of LRU. Second-and higher rank LRU occupied most of total lateral root length and number, up to90%in total lateral root length. Abundant higher order laterals can arise from a single first-order lateral and one lateral root unit can occupy up to18%of total lateral root length of one nodal root. Most total lateral root length and number distributes in the proximal5cm long axile branching zone.Combination of3D digitizer and image processing is suitable for accurate determination of the3D architecture of axile roots of mature maize plants under field conditions. Integration of root sampling system and image processing is suitable for measurement of topological and geometrical structure of nodal roots of field-grown maize. Based on above two methods, a unique estimation on root architecture of maize could be obtained, which should serve as a valuable resource for the parameterisation of root architecture models and as a benchmark for evaluating other less demanding, field sampling methods and for testing whether the screened root architecture based on laboratory method also express the same under field conditions.

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