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

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.

Leveraging plant physiological dynamics using physical reservoir computing

“…As such, one could rely on plant models with sufficient details such as functional structural plant models (FSPMs) 58 to investigate suitable reservoir-like plant processes and evaluate sensor technologies in silico . Employing advanced plant models can not only provide information on suitable processes at different organisational levels (and thus also sensing technologies), but also on the timescales 59 as which we can perform reservoir computing.…”

Cropbox: a declarative crop modeling framework

“…supports the instantiation of a new system during runtime to allow dynamic expansion of complex model structure which is an important feature differentiating functional-structural plant models (FSPM) from conventional crop models with a rather static structure [Vos et al, 2010, Soualiou et al, 2021]. We used to build a 3D root structure growth model for switchgrass ( Panicum virgatum ) based on the root growth algorithm described by CRootBox model [Schnepf et al, 2018].…”

“…While the Cropbox modeling framework was primarily designed for developing process-based crop simulation models with a static structure as seen by the examples above, the framework itself does not preclude models with a more dynamic structure which is often demonstrated by functional-structural plant modeling (FSPM) approaches [Vos et al, 2010, Soualiou et al, 2021]. A major difference with such structure-oriented models compared to the conventional crop simulation models is that the former often needs to deal with a sheer amount of structural components that have to be dynamically produced and interconnected for describing a specific aspect of plant growth, which is hardly captured by empirical models relying on a simpler structure approximation.…”

Towards grapevine root architectural models to adapt viticulture to drought

“…To better match rootstocks to target growing areas, it is necessary to combine detailed knowledge of current and future drought stress scenarios with an understanding of root architecture traits that may contribute to drought tolerance ( White et al., 2013 ). In that sense, modeling can assist with explaining observed data, testing hypotheses and integrating drought conditions and plant performance on the scale of individual plants up to crop stands and deepen our understanding of the complex high-dimensional space of G x E x M interactions ( Soualiou et al., 2021 ). Root architecture models can assist in our understanding how roots access and extract soil resources.…”