VolatileAI joins UniNe during SSP measurement campaign

The University of Neuchâtel (UniNe) welcomed Urte Puodziunaite from VolatileAI, who develops data processing pipelines for the Sensor System Prototype (SSP), including machine learning models for analysing volatile compound data.

Urte joined the UniNe team during the ongoing measurement campaign to gain a deeper understanding of sampling dynamics and to help implement a standardized naming system for samples across all SSP campaigns. Her visit also provided valuable hands-on support during the measurements of maize plants in meshed cages, ensuring smooth data collection and contributing to the refinement of SSP methodologies.

In the photos:

• The UniNe team with Urte from VolatileAI — from left to right: Ted Turlings, Christèle Borgeaud, Marine Mamin, Carla Arce, Amandine André, and Urte Puodziunaite.
• A meshed cage of maize plants, with both healthy and FAW-infested individuals being sampled.
• A particularly photogenic fall armyworm (FAW) larva, captured after 24 hours of feeding.

This collaboration further strengthens the partnership between UniNe and VolatileAI within the PURPEST project, advancing the development of innovative diagnostic tools for plant health monitoring.