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Review
. 2021 Dec 23:12:747142.
doi: 10.3389/fpls.2021.747142. eCollection 2021.

Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects

Affiliations
Review

Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects

Soualihou Soualiou et al. Front Plant Sci. .

Abstract

Functional-structural plant models (FSPMs) have been evolving for over 2 decades and their future development, to some extent, depends on the value of potential applications in crop science. To date, stabilizing crop production by identifying valuable traits for novel cultivars adapted to adverse environments is topical in crop science. Thus, this study will examine how FSPMs are able to address new challenges in crop science for sustainable crop production. FSPMs developed to simulate organogenesis, morphogenesis, and physiological activities under various environments and are amenable to downscale to the tissue, cellular, and molecular level or upscale to the whole plant and ecological level. In a modeling framework with independent and interactive modules, advanced algorithms provide morphophysiological details at various scales. FSPMs are shown to be able to: (i) provide crop ideotypes efficiently for optimizing the resource distribution and use for greater productivity and less disease risk, (ii) guide molecular design breeding via linking molecular basis to plant phenotypes as well as enrich crop models with an additional architectural dimension to assist breeding, and (iii) interact with plant phenotyping for molecular breeding in embracing three-dimensional (3D) architectural traits. This study illustrates that FSPMs have great prospects in speeding up precision breeding for specific environments due to the capacity for guiding and integrating ideotypes, phenotyping, molecular design, and linking molecular basis to target phenotypes. Consequently, the promising great applications of FSPMs in crop science will, in turn, accelerate their evolution and vice versa.

Keywords: assisted molecular breeding; functional-structural plant modeling; genotype to phenotype; plant architecture; plant phenotyping.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The schematic diagram of plant architecture and functional activities on the basis of individual organs for FSPMs downscaled to the cellular function or upscaled to the ecological function via leaf photosynthesis. Leaf photosynthesis can be decoded as a collection of cellular chloroplast photosynthesis per unit that can adopt leaf C3/C4 biochemical models (Farquhar et al., 1980) regulated by molecular network (Wu et al., 2016); while for field level, the estimation of grain yield from leaf photosynthesis is the intercepted light by the canopy as a function of LAI multiplying with LUE and HI. Leaf photosynthesis acts as a nexus in connecting cellular and molecular level to field level modeling. The curve shows net photosynthetic rate as a function of incident irradiance, CO2, H2O, and temperature. From left to right, the upscale from molecular to ecological level or vice versa for downscale from right to left. FSPMs, functional–structural plant models; LAI, leaf area index; LUE, light use efficiency; HI, harvest index.

References

    1. Ababaei B., Chenu K. (2020). Heat shocks increasingly impede grain filling but have little effect on grain setting across the Australian wheat belt. Agric. For. Meteorol. 284:107889. 10.1016/j.agrformet.2019.107889 - DOI
    1. Allen M. T., Prusinkiewicz P., DeJong T. M. (2005). Using L-systems for modeling source-sink interactions, architecture and physiology of growing trees: the L-PEACH model. New Phytol. 166, 869–880. 10.1111/j.1469-8137.2005.01348.x - DOI - PubMed
    1. Altieri M. A., Nicholls C. I. (2017). The adaptation and mitigation potential of traditional agriculture in a changing climate. Clim. Change 140, 33–45. 10.1007/s10584-013-0909-y - DOI
    1. Andrivon D., Giorgetti C., Baranger A., Calonnec A., Sache I. (2012). Defining and designing plant architectural ideotypes to control epidemics? Eur. J. Plant Pathol. 135, 611–617. 10.1007/s10658-012-0126-y - DOI
    1. Barillot R., Chambon C., Andrieu B. (2016). CN-Wheat, a functional–structural model of carbon and nitrogen metabolism in wheat culms after anthesis. I. Model description. Ann. Bot. 118, 997–1013. 10.1093/aob/mcw143 - DOI - PMC - PubMed

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