首页> 美国卫生研究院文献>Plant Methods >LEAF-E: a tool to analyze grass leaf growth using function fitting
【2h】

LEAF-E: a tool to analyze grass leaf growth using function fitting

机译:LEAF-E:使用函数拟合分析草叶生长的工具

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

In grasses, leaf growth is often monitored to gain insights in growth processes, biomass accumulation, regrowth after cutting, etc. To study the growth dynamics of the grass leaf, its length is measured at regular time intervals to derive the leaf elongation rate (LER) profile over time. From the LER profile, parameters such as maximal LER and leaf elongation duration (LED), which are essential for detecting inter-genotype growth differences and/or quantifying plant growth responses to changing environmental conditions, can be determined. As growth is influenced by the circadian clock and, especially in grasses, changes in environmental conditions such as temperature and evaporative demand, the LER profiles show considerable experimental variation and thus often do not follow a smooth curve. Hence it is difficult to quantify the duration and timing of growth. For these reasons, the measured data points should be fitted using a suitable mathematical function, such as the beta sigmoid function for leaf elongation.In the context of high-throughput phenotyping, we implemented the fitting of leaf growth measurements into a user-friendly Microsoft Excel-based macro, a tool called LEAF-E. LEAF-E allows to perform non-linear regression modeling of leaf length measurements suitable for robust and automated extraction of leaf growth parameters such as LER and LED from large datasets. LEAF-E is particularly useful to quantify the timing of leaf growth, which forms an important added value for detecting differences in leaf growth development. We illustrate the broad application range of LEAF-E using published and unpublished data sets of maize, Miscanthus spp. and Brachypodium distachyon, generated in independent experiments and for different purposes. In addition, we show that LEAF-E could also be used to fit datasets of other growth-related processes that follow the sigmoidal profile, such as cell length measurements along the leaf axis.Given its user-friendliness, ability to quantify duration and timing of leaf growth and broad application range, LEAF-E is a tool that could be routinely used to study growth processes following the sigmoidal profile.Electronic supplementary materialThe online version of this article (doi:10.1186/1746-4811-10-37) contains supplementary material, which is available to authorized users.
机译:在草丛中,通常会监测叶片的生长情况,以了解生长过程,生物量积累,割草后的再生长等。为研究草叶的生长动力学,定期测量其长度以得出叶片的伸长率(LER) )的个人资料。根据LER谱,可以确定诸如最大LER和叶片伸长持续时间(LED)之类的参数,这些参数对于检测基因型间的生长差异和/或量化植物对变化的环境条件的生长响应至关重要。由于生长受到昼夜节律的影响,尤其是在草丛中,环境条件(如温度和蒸发需求)的变化会影响其生长,因此LER曲线显示出相当大的实验变化,因此通常不遵循平滑曲线。因此,难以量化生长的持续时间和时间。由于这些原因,应该使用合适的数学函数拟合测量的数据点,例如用于叶伸长的β乙状结肠功能。在高通量表型的背景下,我们将叶生长测量值拟合到用户友好的Microsoft中基于Excel的宏,称为LEAF-E的工具。 LEAF-E允许对叶长测量值执行非线性回归建模,该模型适合从大型数据集中强大而自动地提取叶长参数(例如LER和LED)。 LEAF-E对量化叶片生长的时机特别有用,它为检测叶片生长发育的差异形成了重要的附加值。我们使用已发表和未发表的玉米(Miscanthus spp)数据集说明了LEAF-E的广泛应用范围。和短枝曲霉(Brachypodium distachyon),是通过独立实验和不同目的生成的。此外,我们表明LEAF-E还可以用于拟合遵循S形曲线的其他与生长相关的过程的数据集,例如沿叶轴的细胞长度测量。鉴于其用户友好性,量化持续时间和时间的能力关于叶的生长和广泛的应用范围,LEAF-E是一种可常规用于研究按照S形曲线进行生长过程的工具。电子补充材料本文的在线版本(doi:10.1186 / 1746-4811-10-37)包含补充材料,授权用户可以使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号