A practical workflow to facilitate analysis of the emission dynamics of non-target BVOCs in terrestrial ecosystems by PTR-TOF-MS

Mathias Fontez ^1,2,3* Joris Huguenin ^4,5,6 Frédéric JULLIEN ^1,2,3 Sandrine Moja ^1,2,3 Magali Proffit ^4,5,6 Florence Nicole ^1,2,3

• ¹ Université Jean Monnet, Saint-Étienne, Rhône-Alpes, France
• ² LBVpam UMR 5079, Saint-Etienne, France
• ³ CNRS, Saint-Etienne, France
• ⁴ UMR5175 Centre d'Ecologie Fonctionnelle et Evolutive (CEFE), Montpellier, Languedoc-Roussillon, France
• ⁵ Université de Montpellier, Montpellier, Languedoc-Roussillon, France
• ⁶ CNRS, Montpellier, France

Proton Transfer Reaction Time-of-Flight Mass Spectrometry (PTR-TOF-MS) provides highresolution, real-time tracking of volatile organic compounds (VOCs), yet its analytical workflows for complex mixtures are often underexplored. This study presents a flexible data analysis workflow tailored for PTR-TOF-MS, designed to manage datasets with multiple replicates and experimental factors efficiently. Using lavender plants (Lavandula angustifolia Mill. var. diva) in a controlled greenhouse environment, we analyzed BVOC emissions over a 24-hour cycle. The workflow integrates data importation and optimization via the provoc R package, utilizing Multivariate Curve Resolution (MCR) to decompose spectra into biologically meaningful components and Redundancy Analysis (RDA) to assess component relevance. For this specific model experiment, we determined that normalization using the RUVr method and using and setting the MCR on a number of five components gave the most accurate results. However, this configuration is optimized for the current dataset; other experimental designs may require different normalization methods or numbers of components to achieve optimal results. The workflow enables effective differentiation of VOC emission patterns depending on experimental factors as well as an effective normalization method selection. It provides a systematic approach to PTR-TOF-MS data interpretation, adaptable to various experimental designs and scientific questions, making it valuable for studying complex VOC mixtures in chemical ecology and metabolomics. This method supports long-term, non-destructive sampling while delivering precise VOC profiling.