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Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach.

Yi XiaoJennifer SloanChristopher HepworthMarc Fradera-SolerAndrew MathersRachel ThorleyAlice L BaillieHannah JonesTiangen ChangXingyuan ChenNazmin YaaparColin P OsborneCraig J SturrockSacha J MooneyAndrew J FlemingXin-Guang Zhu
Published in: The New phytologist (2022)
Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO 2 . We developed a 3D reaction-diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO 2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf-level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO 2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis.
Keyphrases
  • high resolution
  • machine learning
  • mass spectrometry
  • deep learning