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Review
. 2016 Feb;5(1):18-25.
doi: 10.1002/fes3.74. Epub 2016 Jan 4.

Genetics-based dynamic systems model of canopy photosynthesis: the key to improve light and resource use efficiencies for crops

Qingfeng Song  1 , Chengcai Chu  2 , Martin A J Parry  3 , Xin-Guang Zhu  1
Affiliations
Review

Genetics-based dynamic systems model of canopy photosynthesis: the key to improve light and resource use efficiencies for crops

Qingfeng Song et al. Food Energy Secur. 2016 Feb.

Abstract

Improving canopy photosynthetic light use efficiency instead of leaf photosynthesis holds great potential to catalyze the next "green revolution". However, leaves in a canopy experience different biochemical limitations due to the heterogeneities of microclimates and also physiological parameters. Mechanistic dynamic systems models of canopy photosynthesis are now available which can be used to design the optimal canopy architectural and physiological parameters to maximize CO 2 uptake. Rapid development of modern crop genetics research now makes it possible to link such canopy models with genetic variations of crops to develop genetics-based dynamic systems models of canopy photosynthesis. Such models can guide marker-assisted breeding or genomic selection or engineering of crops to enhance light and nitrogen use efficiencies for different regions under future climate change scenarios.

Keywords: Canopy photosynthesis; design crop systems; genetics‐based model of canopy photosynthesis; heterogeneity; microclimates.

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Figures

Figure 1
Figure 1
The impacts of varying growth location and growth direction on canopy photosynthetic rates. The simulation was conducted for a rice canopy based on methods for 3D canopy reconstruction (Song et al. 2013). (A) The impacts of varying the growth latitudes on the diurnal canopy photosynthetic rates; (B) The impacts of varying the leaf area index (LAI) and also the growth direction on the diurnal canopy photosynthesis. NS (North‐south direction); EW (East‐west direction).
Figure 2
Figure 2
The parameters required for developing an idea type of a particular crop. (A) The general structure of the model. The model will incorporate both the detailed description of the canopy architectural parameters and also the detailed description of the photosynthetic processes. Functions relating genomic variations to variations of parameters will be used in the model so that the model can predict the consequences of different genetic variations on photosynthetic properties. (B) The procedure to establish the function to linking genetic variations to parameters used in the genetics‐based dynamic systems model of canopy photosynthesis.
Figure 3
Figure 3
The routine for identifying the key parameters controlling the canopy photosynthetic light or nitrogen use efficiencies of a crop. P1,elite, P2,elite, … … P1,common, P2,common are parameters for the elite or common cultivars. The V1,elite or V1,common are the predicted value of a particular phenotype. Synthetic cultivar is a hypothetical cultivar in which the value of parameter 1 from common cultivar (P1,common) is used to replace the parameter value of the elite cultivar (P1,elite).
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References

    1. Carmo‐Silva, E. , Scales J. C., Madgwick P. J., and Parry M. A. J.. 2015. Optimizing Rubisco and its regulation for greater resource use efficiency. Plant Cell Environ. 38:1817–32. - PubMed
    1. Cellier, P. , and Olioso A.. 1993. A simple system for automated long‐term Bowen ratio measurement. Agric. For. Meteorol. 66:81–92.
    1. Chu, C. 2015. A new era for crop improvement – From model‐guided rationale design to practical engineering. Mol. Plant. 8:1299–1301. - PubMed
    1. Donald, C. M. 1968. The breeding of crop ideotypes. Euphytica 17:385–403.
    1. Driever, S. M. , Lawson T., Andralojc P. J., Raines C. A., and Parry M. A. J.. 2014. Natural variation in photosynthetic capacity, growth and yield in 64 field grown wheat genotypes. J. Exp. Bot. doi:10.1093/jxb/eru253. - DOI - PMC - PubMed