Yu Liyao, Fujiwara Kazuhiro, Matsuda Ryo
Department of Biological and Environmental Engineering, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan.
Front Plant Sci. 2022 Feb 8;12:809046. doi: 10.3389/fpls.2021.809046. eCollection 2021.
Leaves acclimate to day-to-day fluctuating levels of photosynthetic photon flux density (PPFD) by adjusting their morphological and physiological parameters. Accurate estimation of these parameters under day-to-day fluctuating PPFD conditions benefits crop growth modeling and light environment management in greenhouses, although it remains challenging. We quantified the relationships between day-to-day PPFD changes over 6 days and light acclimation parameters for cucumber seedling leaves, including leaf mass per area (LMA), chlorophyll (Chl) / ratio, maximum net photosynthetic rate ( ), maximum rate of ribulose-1,5-bisphosphate (RuBP) carboxylase/oxygenase ( ), and maximum rate of electron transport ( ). The last two parameters reflect the capacity of the photosynthetic partial reactions. We built linear regression models of these parameters based on average or time-weighted averages of daily PPFDs. For time-weighted averages of daily PPFDs, the influence of daily PPFD was given a specific weight. We employed three types of functions to calculate this weight, including linear, quadratic, and sigmoid derivative types. We then determined the trend of weights that estimated each parameter most accurately. Moreover, we introduced saturating functions to calibrate the average or time-weighted averages of daily PPFDs, considering that light acclimation parameters are usually saturated under high PPFDs. We found that time-weighted average PPFDs, in which recent PPFD levels had larger weights than earlier levels, better estimated LMA than average PPFDs. This suggests that recent PPFDs contribute more to LMA than earlier PPFDs. Except for the Chl / ratio, the average PPFDs estimated , , and with acceptable accuracy. In contrast, time-weighted averages of daily PPFDs did not improve the estimation accuracy of these four parameters, possibly due to their low response rates and plasticity. Calibrating functions generally improved estimation of Chl / ratio, , and because of their saturating tendencies under high PPFDs. Our findings provide a reasonable approach to quantifying the extent to which the leaves acclimate to day-to-day fluctuating PPFDs, especially the extent of LMA.
叶片通过调整其形态和生理参数来适应光合光子通量密度(PPFD)的每日波动水平。在每日波动的PPFD条件下准确估计这些参数有利于作物生长建模和温室光环境管理,尽管这仍然具有挑战性。我们量化了6天内黄瓜幼苗叶片的每日PPFD变化与光适应参数之间的关系,这些参数包括单位面积叶质量(LMA)、叶绿素(Chl)/比、最大净光合速率( )、核酮糖-1,5-二磷酸羧化酶/加氧酶(RuBP羧化酶/加氧酶)的最大速率( )以及最大电子传递速率( )。最后两个参数反映了光合部分反应的能力。我们基于每日PPFD的平均值或时间加权平均值建立了这些参数的线性回归模型。对于每日PPFD的时间加权平均值,赋予了每日PPFD特定的权重。我们采用了三种类型的函数来计算这个权重,包括线性、二次和S形导数类型。然后我们确定了最准确估计每个参数的权重趋势。此外,考虑到光适应参数在高PPFD下通常会饱和,我们引入了饱和函数来校准每日PPFD的平均值或时间加权平均值。我们发现,近期PPFD水平权重比早期水平更大的时间加权平均PPFD比平均PPFD能更好地估计LMA。这表明近期PPFD对LMA的贡献比早期PPFD更大。除了Chl/比,平均PPFD以可接受的准确度估计了 、 和 。相比之下,每日PPFD的时间加权平均值并没有提高这四个参数的估计准确度,可能是由于它们的低响应率和可塑性。校准函数由于其在高PPFD下的饱和趋势,通常提高了对Chl/比、 和 的估计。我们的研究结果提供了一种合理的方法来量化叶片适应每日波动的PPFD的程度,特别是LMA的程度。