Analysis of Furan and Alkyl Furans in Food Commodities Using Headspace-SPME Arrow Coupled to GC-MS

Furan and alkyl furans are formed in foods when compounds, such as carbohydrates, ascorbic acid, and derivatives, as well as some lipids, are thermally degraded during roasting, frying, or baking. The International Agency for Research of Cancer (IARC) classified furan as a possible carcinogenic compound, raising general concern about the possible health risks associated with the occurrence of furans and alkyl furans in food. Previous research on the analysis of these volatile organic compounds reported static headspace (HS) and solid-phase microextraction (SPME) in combination with GC-MS are both beneficial techniques. The use of SPME for the analysis of these highly volatile analytes has demonstrated improved method sensitivity and higher signal-to-noise for some of the alkyl furans; however, the fragility of traditional SPME fibers is a concern. In this work, we developed a HS-SPME-GC-MS method for the analysis of furans and alkyl furans in baby formula and coffee using a SPME Arrow. The SPME Arrow geometry and design offer improved mechanical durability, enhanced method sensitivity, and robustness. Different experimental conditions, such as coating chemistry, incubation temperature, and extraction time, were evaluated. Two calibration ranges are covered, both a low concentration range from 1.25 to 150 µg/kg, and a high concentration calibration range from 25 to 8000 µg/kg. For the analysis of highly concentrated samples, different conditions of split (1:100), extraction time (1 min), and sodium chloride solution (30%) (5 mL) were selected. The method was evaluated in matrices spiked at two concentration levels: 5 and 50 µg/kg for baby formula, and 1000 and 4000 µg/kg for coffee. Satisfactory results in terms of linearity, accuracy, and precision were obtained for the majority of experiments. Accuracy values above 111% in coffee samples could be due to sample handling and requires future experimental work to understand this bias.