# Comparing Proton Transfer Reaction (PTR) and Adduct Ionization Mechanism (AIM) for the Study of Volatile Organic Compounds

## TL;DR

This paper compares two mass spectrometry techniques for detecting plant VOCs, finding that the newer AIM-MS detects a broader range of compounds than PTR-MS.

## Contribution

The study introduces AIM-MS as a novel method for real-time VOC monitoring in plants with broader detection capabilities.

## Key findings

- AIM-MS detected more distinct signals than PTR-MS in pea plants.
- AIM-MS signals were mainly from lipids and amino acids, while PTR-MS signals were from phenolics.
- AIM-MS shows potential for real-time plant health and stress monitoring.

## Abstract

Volatile organic compounds (VOCs) play a central role in plant communication and ecology, acting as a chemical language that mediates interactions with other organisms and responses to environmental stimuli. Analyzing changes in the plant volatilome enables the effective differentiation between biotic and abiotic stresses. Consequently, monitoring VOC emissions offers valuable insights into plant signaling pathways and health status. These insights position this approach as a promising strategy for improving crop protection. Direct infusion (DI) online analytical techniques, such as proton transfer reaction mass spectrometry (PTR-MS) and adduct ionization mechanism mass spectrometry (AIM-MS), have been developed to detect and characterize VOCs in real time. Here, we evaluated the suitability of PTR-MS and AIM-MS for monitoring VOC emissions in pea plants (Pisum sativum L.). Comparative analysis revealed that AIM-MS, a recently developed technology, detected a higher number of distinct signals than PTR-MS. Annotation of detected and significant AIM-MS signals indicated a predominance toward those that were putative lipids-derived and amino acids-derived, whereas PTR-MS signals were primarily associated with putative phenolic compounds. These findings suggest that the newly developed AIM reactor offers a broader detection range and may enhance our ability to monitor plant VOC emissions. Consequently, AIM-MS emerges as a promising tool for the real-time assessment of pea plant health and stress responses. Further efforts are needed to improve the portability of DI-MS techniques and to integrate them with GC-MS techniques. Overall, these efforts will allow this technology to be exploited for plant protection in compromised environments.