The complex volatile profiles of plant and food products can provide a wealth of information – but conventional 1D GC–MS systems are rarely up to the analytical challenge.

We talk to researchers at the University of Reading, who have migrated to an automated GCxGC–TOF MS system that’s allowing them to achieve much better confidence in non-target screening, while also streamlining sample prep.

Understanding the volatiles emitted from crop plants and food products can provide valuable insights into their response to different growing conditions, especially factors such as climate change and agricultural pests. Analysing these volatiles is often done using GC–MS, but conventional 1D systems usually struggle to separate all the analytes in complex profiles, meaning that the confidence attached to the spectra of individual peaks is low.

It was exactly that problem that was faced by researchers at the University of Reading’s Chemical Analysis Facility back in 2021 who needed to gain more detailed information on the volatile constituents of various natural products that they were studying.

“We needed a system that could go beyond our standard GC–MS capabilities”, said Dr Luke Bell, Lecturer in Temperate Horticulture, who at the time was focused on understanding the volatile profiles of kale, honey and wine. And that, he says, was when they reached out to SepSolve to provide some answers.

Download the case study