Graefe Jan, Yu Wenjuan, Körner Oliver
Leibniz-Institute of Vegetable and Ornamental Crops (IGZ), Next-Generation Horticultural Systems, Grossbeeren, Germany.
Department of Functional Genome and Gene Safety, Chinese Academy of Agricultural Sciences, Beijing, China.
Front Plant Sci. 2022 Jun 22;13:889709. doi: 10.3389/fpls.2022.889709. eCollection 2022.
Mechanistic models of canopy photosynthesis usually upscale leaf photosynthesis to crop level. A detailed prediction of canopy microclimate with accurate leaf morphological and physiological model parameters is the pre-requisite for accurate predictions. It is well established that certain leaf model parameters ( , ) of the frequently adopted Farquhar and Caemmerer photosynthesis model change with leaf age and light interception history. Previous approaches to predict and focused primarily on light interception, either by cumulative intercepted photosynthetic photon flux density (PPFD) or by closely related proxy variables such as leaf nitrogen content per leaf area. However, for plants with monopodial growth, such as vertically grown tomatoes or cucumber crops, in greenhouse production, there is a strong relationship between leaf age and light interception, complicating the experimental and mathematical separation of both effects. We propose a modeling framework that separates age and light intensity-related acclimation effects in a crop stand: Improved approximation of intra-leaf light absorption profiles with cumulative chlorophyll content () is the basis, while parameters are estimated Gaussian process regression from total , carotenoid content (), and leaf mass per area (). The model approximates light absorption profiles within a leaf and links them to leaf capacity profiles of photosynthetic electron transport. Published datasets for and were used to parameterize the relationship between light and capacity profiles and to set the curvature parameter of electron transport rate described by a non-rectangular hyperbola on . Using the modified capacity and light absorption profile functions, the new model was then able to predict light acclimation in a 2-month period of a fully grown tomato crop. An age-dependent lower limit of the electron transport capacity per unit was essential in order to capture the decline of and over time and space of the investigated tomato crop. We detected that current leaf photosynthetic capacity in tomato is highly affected by intercepted light-sum of 3-5 previous days.
冠层光合作用的机理模型通常将叶片光合作用扩展到作物水平。利用准确的叶片形态和生理模型参数对冠层微气候进行详细预测是准确预测的前提条件。众所周知，常用的Farquhar和Caemmerer光合作用模型的某些叶片模型参数（ ， ）会随着叶片年龄和光截获历史而变化。以前预测 和 的方法主要集中在光截获上，要么通过累积截获的光合光子通量密度（PPFD），要么通过密切相关的替代变量，如单位叶面积的叶片氮含量。然而，对于具有单轴生长的植物，如温室生产中垂直生长的番茄或黄瓜作物，叶片年龄和光截获之间存在很强的关系，这使得对这两种效应进行实验和数学分离变得复杂。我们提出了一个建模框架，该框架在作物冠层中分离与年龄和光强相关的适应效应：以累积叶绿素含量（ ）对叶内光吸收剖面进行改进近似是基础，而参数则通过高斯过程回归从总 、类胡萝卜素含量（ ）和单位面积叶质量中估计。该模型近似叶内的光吸收剖面，并将它们与光合电子传递的叶片能力剖面联系起来。已发表的关于 和 的数据集用于参数化光和能力剖面之间的关系，并设置由非矩形双曲线描述的电子传递速率的曲率参数。使用修改后的能力和光吸收剖面函数，新模型随后能够预测完全成熟的番茄作物在两个月期间的光适应。为了捕捉所研究的番茄作物在时间和空间上 和 的下降，单位 电子传递能力的年龄依赖性下限至关重要。我们发现，番茄当前的叶片光合能力受前3-5天截获光量总和的影响很大。
