Department of Botany and Biodiversity Research Centre, The University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.
New Phytol. 2024 Feb;241(3):1361-1372. doi: 10.1111/nph.19405. Epub 2023 Nov 20.
We present the Fast Assimilation-Temperature Response (FAsTeR) method, a new method for measuring plant assimilation-temperature (AT) response that reduces measurement time and increases data density compared with conventional methods. The FAsTeR method subjects plant leaves to a linearly increasing temperature ramp while taking rapid, nonequilibrium measurements of gas exchange variables. Two postprocessing steps are employed to correct measured assimilation rates for nonequilibrium effects and sensor calibration drift. Results obtained with the new method are compared with those from two conventional stepwise methods. Our new method accurately reproduces results obtained from conventional methods, reduces measurement time by a factor of c. 3.3 (from c. 90 to 27 min), and increases data density by a factor of c. 55 (from c. 10 to c. 550 observations). Simulation results demonstrate that increased data density substantially improves confidence in parameter estimates and drastically reduces the influence of noise. By improving measurement speed and data density, the FAsTeR method enables users to ask fundamentally new kinds of ecological and physiological questions, expediting data collection in short-field campaigns, and improving the representativeness of data across species in the literature.
我们提出了快速同化-温度响应（Fast Assimilation-Temperature Response，简称 FAsTeR）方法，这是一种测量植物同化-温度（AT）响应的新方法，与传统方法相比，它可以减少测量时间并增加数据密度。FAsTeR 方法使植物叶片经历线性递增的温度斜坡，同时对气体交换变量进行快速、非平衡测量。采用两个后处理步骤来校正测量同化率的非平衡效应和传感器校准漂移。新方法得到的结果与两种传统逐步方法的结果进行了比较。我们的新方法准确地再现了传统方法的结果，将测量时间缩短了约 1/3.3（从约 90 分钟缩短至 27 分钟），并将数据密度提高了约 55 倍（从约 10 个增加至约 550 个观测值）。模拟结果表明，增加数据密度可以大大提高参数估计的置信度，并显著降低噪声的影响。通过提高测量速度和数据密度，FAsTeR 方法使用户能够提出全新的生态和生理问题，加速短期野外实验的数据收集，并提高文献中不同物种数据的代表性。
