# Beyond the network of plants volatile organic compounds

## TL;DR

This study analyzes volatile organic compounds emitted by 109 plant species to classify them using complex network theory, revealing ecological relationships and adaptive strategies through chemical profiles.

## Contribution

It introduces a novel application of complex network analysis and community detection algorithms to classify plant species based on VOC emissions.

## Key findings

- VOCs vary widely across species and are linked to ecological strategies.
- Network analysis can classify plants by chemical emission profiles.
- Complex network methodology uncovers plant-environment relationships.

## Abstract

Plants emission of volatile organic compounds (VOCs) is involved in a wide class of ecological functions, as VOCs play a crucial role in plants interactions with biotic and abiotic factors. Accordingly, they vary widely across species and underpin differences in ecological strategy. In this paper, VOCs spontaneously emitted by 109 plant species (belonging to 56 different families) have been qualitatively and quantitatively analysed in order to classify plants species. By using bipartite networks methodology, based on recent advancements in Complex Network Theory, and through the application of complementary classical and advanced community detection algorithms, the possibility to classify species according to chemical classes such as terpenes and sulfur compounds is suggested. This indicates complex network analysis as an advantageous methodology to uncover plants relationships also related to the way they react to the environment where they evolve and adapt.