Wu Alex, Song Youhong, van Oosterom Erik J, Hammer Graeme L
Centre for Plant Science, Queensland Alliance for Agriculture and Food Innovation, The University of QueenslandBrisbane, QLD, Australia; ARC Centre of Excellence for Translational Photosynthesis, The University of QueenslandBrisbane, QLD, Australia.
Front Plant Sci. 2016 Oct 13;7:1518. doi: 10.3389/fpls.2016.01518. eCollection 2016.
The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.
大田作物生产力的下一个进步可能需要来自提高作物对资源(如光、水和氮)的利用效率,其中一些方面与作物的整体光合效率密切相关。由于跨尺度连接存在困难,光合作用基因操纵的进展在作物水平上的后果存在不确定性,这使得进展受到困扰。整合生物组织水平并采用基因到表型建模方法的作物生长和发育模拟模型可能是一条前进的道路。能够模拟作物生理属性动态的作物模型已有很长的发展历史。许多作物模型将冠层光合作用(源)作为作物生长的关键驱动因素,而其他模型则从源限制和库限制之间的平衡中推导作物生长。叶片光合作用建模已从通过光响应曲线的经验建模发展到更具机理基础,与光合作用的潜在生化过程有更清晰的联系。连接生化水平和作物水平模型并利用从叶片水平模型到冠层模型的尺度上推发展的跨尺度建模有可能弥合生化水平上的光合操纵与其对作物生产力的影响之间的差距。在这里,我们回顾了这种新兴跨尺度建模框架的方法,并强调了跨建模水平连接的必要性。此外,我们提出了将光合作用生化模型连接到跨尺度建模框架的策略,以支持通过光合操纵来改良作物。