COFFEE ROASTING AND AROMA FORMATION: AN INVESTIGATION USING GCxGC-TOFMS AND CHEMOMETRICS

Coffee is one of the most consumed beverages worldwide, with its global market generating approximately US$ 36 billion in exports in 2021. Brazil remains the top exporter of coffee beans. The overall appeal of coffee is heavily influenced by its organoleptic characteristics, particularly its aroma, which is partially developed during the roasting process through reactions such as Maillard and caramelization. Intrinsic factors such as the coffee species, variety, and origin, as well as operational roasting parameters like temperature ramp profile and duration, play a significant role in coffee aroma development. These parameters can be manipulated to create new coffee aroma profiles by roasting the same beans with different temperature programs. Monitoring these parameters is essential for achieving consistent desired aroma and taste, both on an industrial and homemade scale, ensuring a constant level of quality. Therefore, this study aimed to explore the roasting scenario and monitored the evolution of volatile and semi-volatile compounds (VOCs and SVOCs) during the roasting process of coffee beans. While several studies have investigated the physical and chemical aspects of coffee beans during roasting using conventional gas chromatography (1D-GC), the qualitative and quantitative analysis can be hindered due to peak overlap in complex samples. In this regard, comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS) is a valuable tool for studying the coffee matrix. The enhanced peak capacity of GC×GC, combined with MS-based sample characterization, provides suitable tools for VOC profiling in coffee beans. However, despite the potential of GC×GC-MS in investigating aspects related to coffee roasting, its application in this area remains limited. To address this gap, we employed tubes containing sorbent phase to capture VOCs and SVOCs during the coffee roasting process. These compounds were then subsequently desorbed in a thermal desorber, separated, and identified using comprehensive two-dimensional gas chromatography coupled with a time-of-flight mass spectrometer (GC×GC-TOFMS). The coffee samples consisted of five different subgroups from the same coffee species (Coffea arabica) and were roasted using a lab-made coffee roaster modified from an electric popcorn maker. Principal component analysis (PCA) was able to extract roast-oriented information through pixel-based pattern recognition from the GC×GC-TOFMS data. Finally, template matching assisted in identifying target molecules that significantly varied during the roasting process.