A Mathematical Model to Investigate Iron Allocation in Plants

This presentation discusses the development of a mathematical model to study the mobilization of nutrients in plants – specifically iron. The development of the model involved the combined use of biological principles and the theory of ordinary differential equations. The model merges both biological and mathematical principles to construct a nutrient allocation model that can accurately reproduce experimental data. At each step of the model development process, we will discuss how the principles from both fields worked together to resolve the problems we faced while building a model that produces biologically meaningful results. We demonstrate that the model can be used as a virtual laboratory to study the plant’s response to changes in iron availability in the soil. The quantitative results from the simulations give insights into how to design future lab experiments (predictive biology). The motivation for building the model is the hope that further understanding of the uptake and storage of iron in plants will allow biologists to engineer plants – through precision breeding and gene editing- that can better respond to changes in soil nutrient concentrations.