发布: 2018年02月20日第8卷第4期 DOI: 10.21769/BioProtoc.2739 浏览次数: 9863
评审: Tie LiuPaweł KrajewskiJason Liang Pin Ng
Abstract
High-throughput phenotyping of plant traits is a powerful tool to further our understanding of plant growth and its underlying physiological, molecular, and genetic determinisms. This protocol describes the methodology of a standard phenotyping experiment in PHENOPSIS automated platform, which was engineered in INRA-LEPSE (https://www6.montpellier.inra.fr/lepse) and custom-made by Optimalog company. The seminal method was published by Granier et al. (2006). The platform is used to explore and test various ecophysiological hypotheses (Tisné et al., 2010; Baerenfaller et al., 2012; Vile et al., 2012; Bac-Molenaar et al., 2015; Rymaszewski et al., 2017). Here, the focus concerns the preparation and management of experiments, as well as measurements of growth-related traits (e.g., projected rosette area, total leaf area and growth rate), water status-related traits (e.g., leaf dry matter content and relative water content), and plant architecture-related traits (e.g., stomatal density and index and lamina/petiole ratio). Briefly, a completely randomized (block) design is set up in the growth chamber. Next, the substrate is prepared, its initial water content is measured and pots are filled. Seeds are sown onto the soil surface and germinated prior to the experiment. After germination, soil watering and image (visible, infra-red, fluorescence) acquisition are planned by the user and performed by the automaton. Destructive measurements may be performed during the experiment. Data extraction from images and estimation of growth-related trait values involves semi-automated procedures and statistical processing.
Keywords: Phenotyping (表型)Background
Phenotyping of plant traits is an important aspect of plant sciences. It can be defined as a set of methodologies used to measure plant traits with certain accuracy and precision at different scales of organization (Fiorani and Schurr, 2013). A renaissance of plant phenotyping was brought by the development of automated phenotyping platforms and the creation of new tools for image analysis (Granier and Vile, 2014). Automated plant phenotyping is useful in many aspects of plant biology, such as ecophysiology (Vile et al., 2012), genetics (Bac-Molenaar et al., 2016), and molecular biology (Baerenfaller et al., 2012). It is then important for the broader readership to understand how these platforms work and what can be achieved. This protocol focuses on one particular installation, namely PHENOPSIS (Granier et al., 2006). PHENOPSIS is a custom-made phenotyping platform (growth chamber, automaton, and computer software), manufactured by Optimalog company and it is especially well-suited for analyses of small plants, such as Arabidopsis thaliana. The platform enables growing up to 504 A. thaliana plants simultaneously. Each plant is grown in a separate pot. Each pot can be automatically weighed and watered to a target value, thus it is feasible to monitor soil water content (SWC) individually and automatically adjust it. This feature of the platform makes it perfect for the application of water deficit treatments. PHENOPSIS automatically takes images of plant rosettes. Images can be of four types: RGB zenithal, RGB lateral, infrared, and fluorescence. In addition, many other non-destructive or destructive measurements are also available with some human involvement, e.g., transpiration, stomatal conductance, phenological stage, individual leaf area, epidermal cell density, extent of endoreduplication, and root weight. Because each of these measurements would require a separate lengthy manual, this protocol focuses on the basic platform operation, as well as measurements of leaf morphology and water status. The video of the platform in action is available online (http://bioweb.supagro.inra.fr/phenopsis/InfoBDD.php).
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版权信息
© 2018 The Authors; exclusive licensee Bio-protocol LLC.
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Readers should cite both the Bio-protocol article and the original research article where this protocol was used:
分类
植物科学 > 植物生理学 > 植物生长
植物科学 > 植物生理学 > 非生物胁迫
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