3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis

Abstract

Canopy photosynthesis is the sum of photosynthesis of all above-ground photosynthetic tissues. Quantitative roles of nonfoliar tissues in canopy photosynthesis remain elusive due to methodology limitations. Here, we develop the first complete canopy photosynthesis model incorporating all above-ground photosynthetic tissues and validate this model on wheat with state-of-the-art gas exchange measurement facilities. The new model precisely predicts wheat canopy gas exchange rates at different growth stages, weather conditions, and canopy architectural perturbations. Using the model, we systematically study (1) the contribution of both foliar and nonfoliar tissues to wheat canopy photosynthesis and (2) the responses of wheat canopy photosynthesis to plant physiological and architectural changes. We found that (1) at tillering, heading, and milking stages, nonfoliar tissues can contribute ~4, ~32, and ~50% of daily gross canopy photosynthesis (Acgross; ~2, ~15, and ~-13% of daily net canopy photosynthesis, Acnet) and absorb ~6, ~42, and ~60% of total light, respectively; (2) under favorable condition, increasing spike photosynthetic activity, rather than enlarging spike size or awn size, can enhance canopy photosynthesis; (3) covariation in tissue respiratory rate and photosynthetic rate may be a major factor responsible for less than expected increase in daily Acnet; and (4) in general, erect leaves, lower spike position, shorter plant height, and proper plant densities can benefit daily Acnet. Overall, the model, together with the facilities for quantifying plant architecture and tissue gas exchange, provides an integrated platform to study canopy photosynthesis and support rational design of photosynthetically efficient wheat crops.

A ‘wiring diagram’ for sink strength traits impacting wheat yield potential

“…In the pre-heading stage, tillering and stem extension create a highly dynamic leaf canopy architecture. Such variability can be accounted for within canopy photosynthesis models (of varying complexity) combined with empirical validation (Baldocchi and Amthor, 2001;Hirose, 2005;Zhu et al, 2012;Burgess et al, 2019;Chang et al, 2022). In modelling and empirical architecture, studies of the contribution of lower leaves indicate that it is probably below potential.…”

Modelling plants across scales of biological organisation for guiding crop improvement

“…In the aboveground canopy, modelling of environmental factors other than light in such detail remains to be seen. Validating 3D model outputs by measuring the photosynthetic rates of every photosynthetic organ is not feasible; a common practice is to test predicted whole-canopy CO 2 uptake rates against canopy-scale gasexchange chamber measurement (Song et al 2016;Chang et al 2022).…”

“…Combining molecular pathway models with a detailed canopy upscaling approach presents a means for highly detailed canopy modelling that can explicitly simulate the effects of photosynthetic bioengineering on canopy CO 2 uptake rates. Model parameterisation and perhaps simulation runtime can be challenging, and in some circumstances model simplification was made by switching to biochemical and empirical models of leaf photosynthesis (Song et al 2017;Chang et al 2022). While the capacity to simulate the entire crop cycle is theoretically sound, the requirement to predict 3D canopy architecture (including time-series plant architectural, leaf morphological, and physiological attributes, and parameterisation of all photosynthetic model parameters) and canopy micro-environment remain major barriers.…”

“…descriptions of plant/canopy morphology and architecture, Current method for reliably quantify time series canopy then adapt molecular pathway models to each part of the architectures is to rely on experimental measurements throughsimulated plant, resulting in a large number of input para-out the growth (e.g. Chang et al 2022). Both spatial and meters that are needed to simulate all model mechanisms and temporal parameterisation requirements of bottom-up processes under each specific set of environmental conditions.…”

Balancing grain yield trade-offs in ‘Miracle-Wheat’

“…They can broadly be classified as source and sink strength related, which jointly determine a particular genotype’s assimilate production and reallocation potential. Typically, green tissues of the plant – both foliar (leaves) and non-foliar (peduncle, spikes) are the photosynthesising organs that act as ‘source’ for resource generation (Chang et al , 2022; Molero and Reynolds, 2020). In the pre-anthesis phase, assimilates are partitioned to both vegetative biomass establishment and developing spikes – that determine the overall yield potential (Fischer, 2011; Slafer, 2003).…”