A Reinforcement Learning approach to study climbing plant behaviour.

A plant's structure is the result of constant adaptation and evolution to the surrounding environment. From this perspective, our goal is to investigate the mass and radius distribution of a particular plant organ, namely the searcher shoot, by providing a Reinforcement Learning (RL) environment, that we call Searcher-Shoot, which considers the mechanics due to the mass of the shoot and leaves. We uphold the hypothesis that plants maximize their length, avoiding a maximal stress threshold. To do this, we explore whether the mass distribution along the stem is efficient, formulating a Markov Decision Process. By exploiting this strategy, we are able to mimic and thus study the plant's behavior, finding that shoots decrease their diameters smoothly, resulting in an efficient distribution of the mass. The strong accordance between our results and the experimental data allows us to remark on the strength of our approach in the analysis of biological systems traits.

A 2D model to study how secondary growth affects the self-supporting behaviour of climbing plants.

Climbing plants exhibit specialized shoots, called "searchers", to cross spaces and alternate between spatially discontinuous supports in their natural habitats. To achieve this task, searcher shoots combine both primary and secondary growth processes of their stems in order to support, orientate and explore their extensional growth into the environment. Currently, there is an increasing interest in developing models to describe plant growth and posture. However, the interactions between the sensing activity (e.g. photo-, gravi-, proprioceptive sensing) and the elastic responses are not yet fully understood. Here, we aim to model the extension and rigidification of searcher shoots. Our model defines variations in the radius (and consequently in mass distribution) along the shoot based on experimental data collected in natural habitats of two climbing species: Trachelospermum jasminoides (Lindl.) Lem. and Condylocarpon guianense Desf.. Using this framework, we predicted the sensory aspect of a plant, that is, the plant's response to external stimuli, and the plant's proprioception, that is, the plant's "self-awareness". The results suggest that the inclusion of the secondary growth in a model is fundamental to predict the postural development and self-supporting growth phase of shoots in climbing plants.