Computational Models Growth & Development

The model bean? Computational modelling of Coffea growth

The model can reproduce the measured data, and so opens up avenues for applying this original procedure to other experimental data.

Computational models are being increasingly used in all areas of life sciences to mimic and probe the processes undertaken by living organisms. Plant science is no exception to this, and computational modelling techniques are now widely used to study plant growth and development. Why, people may ask, should we use computational models when we can work with actual plants instead? Well if got right, computational models can go through a variety of scenarios much more rapidly and less labour intensively than we ever could using actual plants. By developing them to match experimental data, computational models could be an extremely powerful way of modelling plant responses to certain scenarios. For example, we might want to know how a slow-growing commercially-important plant responds to certain conditions in the field. A well-informed computational model could give an indication of this far quicker than an experimental set up. In their recent paper in Annals of Botany Véronique Letort and colleagues develop a computational model to simulate the growth of Coffea trees, the source of that little-known (*coughs*) beverage coffee.

The authors produce a type of model known as a Functional-Structural Plant growth Model (FSPM), which can be used to computationally model the growth of plants, and apply it to young Coffea trees. One of the key features of this model is that it incorporates internal trophic pressure into its growth simulations. This is to say, it accounts for the assumption that a new organ such as a branch being developed by the plant must be able to be met by available resources. The central result of this is that the model developed by Letort and colleagues was able to simulate the growth patterns of young Coffea trees in an overall realistic manner compared to the properties of real trees measured by the authors.

Coffea canephora tree (left, J.M.Garg/Wikimedia Commons), simulated Coffea trees (middle, Letort et al., 2020). Coffea canephora berries, the precursors to coffee beans (right, Jeevan Jose/Wikimedia Commons)

While the inclusion of trophic pressure into this model and the accurate results it produces are exciting, the authors concede that it does not definitively prove that plant internal trophic pressure is a parameter that definitely should be included in computational plant growth models. The results are strong for some parameters. For example, the probability of branching happening in the early stages of Coffea tree growth correlates well with simulated trophic pressure. In contrast, the probability of plant organ initiation was less well correlated with the simulated trophic pressure. The authors also point out that trophic competition is likely not something that can be directly measured in plants and that work is needed to arrive at an accepted way of estimating it experimentally to validate models like the one they create.

However, the more models that are created like the one presented here and compared to real data, the better we will get at producing them for various plant species. This also helps to build up to, as the authors point out, increasingly complex mimicking of the various challenges and environmental conditions that real plants encounter in these models. The more realistic these models get, the more we might be able to use them to understand how plants grow and to possibly answer complex, slow-to-investigate questions.

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