A mechanistic model towards ecological inclusion for a better plant growth understanding

Plants growth is a complex and delicate balance among different factors involving environmental and physiological conditions. In this context, we propose a mechanistic model that considers the main internal processes of plant growth and reproduces a wide range of plant behaviors observed experimentally. In particular, we describe the model plant of Arabidopsis thaliana in a realistic environment with a day-and-night cycle, which considers different inputs as light, water, phosphorus, nitrogen, starch and sucrose. In addition, we propose a new function that describes the affinity between the plant and a specific nutrient, and a novel feedback signal to model how plants have the remarkable capacity to distribute resources among their organs. The result is an efficient tool applicable in ecological and agricultural studies, which can estimate several parameters, simulate several soil conditions and analyze how limiting or toxic resources can affect the plant development. We improve our understanding of plant adaptive strategies, reproducing results in line with experiments.