欧亚国际

   WIWAM植物表型成像分析系统由位于先进Ghent大学的VIB研究所、先进的自动化工程公司SMO联合欧洲先进科学家合作研制生产的新型植物表型组学研究平台，可以全自动、高通量、高容量测量分析拟南芥、水稻等植物的三维表型形状及生理状态及其与环境光照、温度、水、营养盐等的关系。

   WIWAM植物表型成像分析系统整合了LED植物智能培养、自动化控制系统、荧光成像测量分析（包括叶绿素、红荧光）、植物红外热成像分析、植物近红外成像分析、植物高光谱分析、自动条码识别管理、RGB真彩3D成像、激光3D成像自动称重与浇灌系统等多项先进技术，以较优化的方式实现大量植物样品——从拟南芥、水稻、玉米到各种其它植物的生理生态与形态结构成像分析，用于高通量植物表型成像分析测量、植物胁迫响应成像分析测量、植物生长分析测量、生态毒理学研究、性状识别及植物生理生态分析研究等。作为先进家将大规模自动化理念和工业级零件和设备整合入植物成像系统的厂家，SMO公司在植物表型成像分析领域处于先进的技术前列，大面积叶绿素荧光成像系统使WIWAM成为植物表型分析与功能成像领域较为先进的仪器设备，植物生长、胁迫响应等测量参数达几百个。先进耐用的工业级部件使系统非常耐用，基本免维护，与同类产品相比，特点突出。目前WIWAM植物表型平台分为WIWAM XY，WIWAM Line以及WIWAM Conveyor 等系列。

   以下文章为Ghent大学Stijn  Dhondt，Nathalie  Wuyts和 Dirk Inze教授联合撰写。

成像技术的进步为植物表型研究提供了革新性的思路，目前是表型系统是性状测量的一种主要工具。本文中我们就3个重要特征来对植物表型系统介绍：高通量、维度以及分辨率。首先全植株表型成像系统是目前研究热点，结合自动化技术的进展，可现状增加通量。组织和细胞水平的表型研究以及所有工具，一般是以低通量运行，常用于获得就空间和时间分辨率而言得到提升的高维度表型数据。传感器技术较新的进展使对植物形态学和生理学相关性状进行研究成为可能。总之，因其是植物表型系统成像过程主要特征，焦点集中于时空分辨率。

   植物表型是结合了多个系统和工具的复合系统。已有人建议将表型组学列入生物新学科，它涉及到在多个组织水准收集高维度表型数据；与全基因组测序一样，研究进展朝向对一个基因组的全部表型进行鉴别。当然此终较目标是理论目标，考量到维度以及通量和分辨率当前和未来的进展，植物表型和表型组学也许可从此获益，我们通常对植物过程以及基因-表型关联关系的理解还非常不全面（Box1）。植物表型从本质而言非常复杂，因其是受多个环境因子影响的多个基因型互作的结果。互作一方面影响了研发项目和以结构性状加以描述植物生长；另外，也影响了以生理性状描述的植物功能。结构和生理性状一起较终决定了以生物量和产量体现的植株性能。不同组织水平或不同类别的表型性状可能在一个特殊环境或多个环境中有巨大相关性（变差）。如果性状较强，可削减表型复杂性（例如，不同测量性状），但是否需要如此则依赖于面对的生物学问题。

所调查的生物问题很多程度上决定了采用哪些感兴趣的表型性状，从而决定了使用何种表型系统和工具。从本质上加以探讨，表型系统本身的测量性状有限，这关系到，植物表型系统究竟是什么。植物表型是在给定环境下与基因型相关的一套结构、生理和性能相关性状。植物表型研究室测定此类性状的定量或定性值。假定表型组理论上包括一个给定基因型的所有可能基因型，植物表型组学可看作是研究多个基因的表型组学。除了提供进行表型研究的工具，植物表型系统通常包括植物在特定环境条件下研究植物生长的方法，植物生长或已经限定和控制或半控制或未控制和测量。植物表型系统的特征决定了其测定基因型数量以及环境条件范围或处理，决定了表型组学研究科持续性。表型系统一般以高通量分辨率以及维度来定义说明。

Cell to whole-plant phenotyping: The best is yet to come

 Trends in Plant Science

Stijn  Dhondt1,2*, Nathalie  Wuyts1,2*, and Dirk Inze´ 1,2

1 Department  of Plant Systems Biology,  VIB, Technologiepark 927, 9052 Gent, Belgium

2 Department  of Plant Biotechnology and Bioinformatics, Ghent University, Technologiepark 927, 9052 Gent, Belgium

Imaging and image processing have revolutionized plant phenotyping and are now  a major  tool  for phenotypic trait  measurement. Here we review  plant  phenotyping systems  by examining three  important characteristics: throughput,  dimensionality, and  resolution.  First, whole-plant phenotyping systems  are highlighted to- gether with advances in automation that enable signifi- cant throughput increases. Organ and cellular  level phenotyping and its  tools,  often  operating at a lower throughput, are then  discussed  as a means  to  obtain high-dimensional phenotypic data  at  elevated  spatial and temporal resolution. The significance of recent developments in sensor  technologies that  give  access to plant  morphology and physiology-related traits  is shown.  Overall, attention is focused on spatial and tem- poral resolution because these are crucial aspects of imaging procedures  in plant  phenotyping systems.

Plant phenotyping is a complex  matter involving a plethora of systems and tools

‘Phenomics’   has   been   proposed as  a  novel  discipline in biology  and   involves the  gathering  of  high-dimensional phenotypic data at multiple levels  of organization, to prog- ress  towards the full characterization of the complete set of phenotypes of a genome, in analogy with whole  genome sequencing [1]. This  ultimate aim  will of course remain hypothetical; however, current  and   future developments in plant phenotyping and  phenomics may  benefit from the consideration of dimensionality, together with  throughput and resolution, because our comprehension of plant process- es in general, and  the  genotype–phenotype relationship in particular, is far from  complete (Box 1). Plant phenotypes are inherently complex  because they result from the inter- action of genotypes with  a multitude of environmental factors. This  interaction  influences on  the one  hand the developmental program and  growth of plants, which  can be described by means of structural traits, and, on the other hand, plant functioning, described by means of physiological traits (Figure 1). Both the structural and physiological traits eventually determine plant performance in  terms of bio- mass and yield. Phenotypic traits at different organizational levels  or in different categories may show high correlations (dependent variation) in one particular or in multiple envir- onments. If  robust, these may  reduce the complexity of phenotyping (i.e., the number of different traits to be mea- sured), but whether this is wanted depends on the biological question [2].

The biological  question under investigation largely determines the  phenotypic traits  of interest and   conse- quently the  phenotyping system and  tools.  It may  be exploratory in nature, meaning that the  number of traits is limited by the  phenotyping system itself  and  to what isPlant phenotyping A plant phenotype is the set of structural, physiological, and performance-related  traits  of  a  genotype   in  a  given  environment. Plant phenotyping is the act of determining the quantitative or qualitative values of these traits. Given that a phenome  consists in principle – of the set of all possible  phenotypes of a given genotype, plant phenomics could be considered  as the study of phenomes  of multiple genotypes.  Besides providing the tools to perform phenotyp- ing itself,  plant  phenotyping systems usually  comprise  the means to grow  plants in certain environments, which  are either defined  and controlled, or semi-controlled, or uncontrolled and measured. The characteristics  of  the  phenotyping system  determine its  capacity  in terms  of the number  of  genotypes  and the range  of  environmental conditions  or  treatments   and,  thus,  its  suitability  for  phenomics. Phenotyping  systems  can  be  described  by  means  of  throughput,resolution, and dimensionality