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估算光合诱导过程中气孔和生化限制因素。

Estimating stomatal and biochemical limitations during photosynthetic induction.

机构信息

ARC Centre of Excellence in Translational Photosynthesis, Division of Plant Science, Research School of Biology, Australian National University, Canberra, ACT 2601, Australia.

出版信息

Plant Cell Environ. 2019 Dec;42(12):3227-3240. doi: 10.1111/pce.13622. Epub 2019 Aug 16.

Abstract

Understanding stomatal and biochemical components that limit photosynthesis under different conditions is important for both the targeted improvement of photosynthesis and the elucidation of how stomata and biochemistry affect plant performance in an ecological context. Limitation analyses have not yet been extensively applied to conditions of photosynthetic induction after an increase in irradiance. Moreover, few studies have systematically assessed how well various limitation analyses actually work. Here we build on two general ways of estimating limitations, one that sequentially removes the effect of a limitation (elimination) and one that uses a tangent plane approximation (differential), by including the ternary effect and boundary layer conductance so that they are consistent with gas exchange data. We apply them to the analysis of temporal and time-integrated limitations during photosynthetic induction, calculating limitations either independent of the time course (one-step) or make use of the entire time course (stepwise). We show that the stepwise differential method is the best method to use when time steps are small enough. We further show that the differential method predicts limitations near exact when the internal CO concentration stays constant. This last insight has important implications for the general use of limitation analyses beyond photosynthetic induction.

摘要

理解不同条件下限制光合作用的气孔和生化因素对于有针对性地提高光合作用以及阐明气孔和生化因素如何影响植物在生态背景下的性能都很重要。限制分析尚未广泛应用于辐照度增加后光合作用诱导的条件下。此外,很少有研究系统地评估各种限制分析实际上的工作效果如何。在这里,我们通过包括三元效应和边界层导度,使它们与气体交换数据一致,基于两种估算限制的常用方法(依次消除限制的效果(消除法)和使用切平面逼近(微分法))构建。我们将它们应用于光合作用诱导过程中时间和时间积分限制的分析,要么独立于时间过程(一步法)计算限制,要么利用整个时间过程(逐步法)计算限制。我们表明,当时间步长足够小时,逐步微分法是最好的方法。我们进一步表明,当内部 CO2 浓度保持不变时,微分法可以近乎精确地预测限制。这最后一点对于限制分析在光合作用诱导之外的一般应用具有重要意义。

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