PhotoGEA: An R Package for Closer Fitting of Photosynthetic Gas Exchange Data With Non-Gaussian Confidence Interval Estimation.

IF 6 1区 生物学 Q1 PLANT SCIENCES
Edward B Lochocki, Coralie E Salesse-Smith, Justin M McGrath
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引用次数: 0

Abstract

Fitting mechanistic models, such as the Farquhar-von-Caemmerer-Berry model, to experimentally measured photosynthetic CO2 response curves (A-Ci curves) is a widely used technique for estimating the values of key leaf biochemical parameters and determining limitations to photosynthesis in vivo. Here, we present PhotoGEA, an R package with tools for C3 A-Ci, C3 Variable J and C4 A-Ci curve fitting. In contrast to existing software, these automated tools use derivative-free optimizers to ensure close fits and they calculate non-Gaussian confidence intervals to indicate which parameter values are most reliable. Results from PhotoGEA's C3 A-Ci curve fitting tool are compared against other available tools, where it is found to achieve the closest fits and most reasonable parameter estimates across a range of curves with different characteristics. PhotoGEA's C3 Variable J and C4 A-Ci fitting tools are also presented, demonstrating how they can provide insights into mesophyll conductance and the processes limiting C4 photosynthesis at high CO2 concentrations. PhotoGEA enables users to develop data analysis pipelines for efficiently reading, processing, fitting and analysing photosynthetic gas exchange measurements. It includes extensive documentation and example scripts to help new users become proficient as quickly as possible.

photoga:一个用非高斯置信区间估计更接近地拟合光合气体交换数据的R包。
拟合机制模型(如Farquhar-von-Caemmerer-Berry模型)与实验测量的光合CO2响应曲线(a - ci曲线)是一种广泛使用的技术,用于估计关键叶片生化参数的值和确定体内光合作用的局限性。在这里,我们提出了photoga,一个带有C3 A-Ci, C3变量J和C4 A-Ci曲线拟合工具的R包。与现有的软件相比,这些自动化工具使用无导数优化器来确保紧密配合,并且它们计算非高斯置信区间来指示哪些参数值是最可靠的。photoga的C3 a - ci曲线拟合工具的结果与其他可用工具进行了比较,发现它可以在一系列具有不同特征的曲线中实现最接近的拟合和最合理的参数估计。photoga的C3变量J和C4 A-Ci拟合工具也被介绍,展示了它们如何能够深入了解叶肉电导和在高浓度二氧化碳下限制C4光合作用的过程。photoga使用户能够开发数据分析管道,以有效地读取,处理,拟合和分析光合气体交换测量值。它包括大量的文档和示例脚本,以帮助新用户尽快精通。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Plant, Cell & Environment
Plant, Cell & Environment 生物-植物科学
CiteScore
13.30
自引率
4.10%
发文量
253
审稿时长
1.8 months
期刊介绍: Plant, Cell & Environment is a premier plant science journal, offering valuable insights into plant responses to their environment. Committed to publishing high-quality theoretical and experimental research, the journal covers a broad spectrum of factors, spanning from molecular to community levels. Researchers exploring various aspects of plant biology, physiology, and ecology contribute to the journal's comprehensive understanding of plant-environment interactions.
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