Triple shot: method development & utilisation of a hyphenated system for the analysis of coffee

BACKGROUND: Coffee is one of the most widely traded commodities worldwide, with a complex supply chain including harvesting, processing, packaging and storage. Quality assessment of coffee is extremely important and is a key determinant of its price and export potential. It is assessed via a combination of sensory parameters including aroma, colour and intensity. However, processing, roasting and grinding can eliminate many such visual indicators. Previous efforts to identify essential contributors of specific aroma components have encountered barriers because of the limitations of the available analytical technology. The use of the thermogravimetric analysis (TGA)–Fourier transform infrared spectroscopy (FTIR)–gas chromatography/mass spectrometry (GC-MS) hyphenated system allows for a multi-faceted approach in the appraisal of evolved volatiles from the coffee bean. The integrated system facilitates the monitoring of the heating process, in real-time via the FTIR element, and at specific time points using GC-MS, which aids in identification of the different volatiles/flavonoids of the coffee sample. RESULTS: A cohesive TGA–FTIR–GC-MS workflow was developed and optimised using a pre-roasted coffee sample as a proof of concept. The system enabled reproducible tracking of mass-loss events during controlled heating, real-time monitoring of evolved gases via FTIR and targeted GC-MS sampling at defined points. Representative classes of coffee volatiles were identified during the thermal programme. The combined analysis illustrates how thermal behaviour, volatile evolution and molecular composition can be correlated within a single framework. CONCLUSION: The present study demonstrates the feasibility and analytical robustness of a hyphenated TGA–FTIR–GC-MS approach for studying coffee volatiles. Although based on a limited sample set, the method provides a foundation for future large-scale studies incorporating statistical modelling, expanded sample diversity and chemometric classification. With further validation, this approach has prospective applications in quality control, authenticity assessment, and process monitoring within the coffee industry.