Tomé Filipa, Jansseune Karel, Saey Bernadette, Grundy Jack, Vandenbroucke Korneel, Hannah Matthew A, Redestig Henning
Bayer CropScience NV, Technologiepark 38, 9052 Ghent, Belgium.
Max Planck Institute for Plant Breeding Research, 50829 Cologne, Germany.
Plant Methods. 2017 Mar 15;13:13. doi: 10.1186/s13007-017-0163-9. eCollection 2017.
Growth is an important parameter to consider when studying the impact of treatments or mutations on plant physiology. Leaf area and growth rates can be estimated efficiently from images of plants, but the experiment setup, image analysis, and statistical evaluation can be laborious, often requiring substantial manual effort and programming skills.
Here we present , a non-destructive and high-throughput phenotyping protocol for the measurement of total rosette area of seedlings grown in plates in sterile conditions. We demonstrate that our protocol can be used to accurately detect growth differences among different genotypes and in response to light regimes and osmotic stress. rosettR is implemented as a package for the statistical computing software R and provides easy to use functions to design an experiment, analyze the images, and generate reports on quality control as well as a final comparison across genotypes and applied treatments. Experiment procedures are included as part of the package documentation.
Using rosettR it is straight-forward to perform accurate, reproducible measurements of rosette area and relative growth rate with high-throughput using inexpensive equipment. Suitable applications include screening mutant populations for growth phenotypes visible at early growth stages and profiling different genotypes in a wide variety of treatments.
在研究处理方法或突变对植物生理学的影响时,生长是一个需要考虑的重要参数。叶面积和生长速率可以从植物图像中有效地估算出来,但实验设置、图像分析和统计评估可能很费力,通常需要大量的人工操作和编程技能。
在此,我们提出了一种用于测量无菌条件下平板培养的幼苗总莲座叶面积的非破坏性高通量表型分析方案。我们证明,我们的方案可用于准确检测不同基因型之间以及对光照条件和渗透胁迫的生长差异。rosettR作为统计计算软件R的一个包来实现,提供了易于使用的函数来设计实验、分析图像、生成质量控制报告以及对基因型和应用处理进行最终比较。实验步骤包含在包文档中。
使用rosettR,可以使用廉价设备以高通量方式对莲座叶面积和相对生长速率进行准确、可重复的测量。合适的应用包括筛选突变群体以寻找早期生长阶段可见的生长表型,以及在各种处理中分析不同基因型。