Integrating Portable GC and QEPAS Detection: Method Translation Strategies for VOC-Based Food Monitoring

The analysis of Volatile Organic Compounds (VOCs) plays an important role in evaluating food quality, safety, and authenticity. VOC profiles serve as informative markers reflecting a wide range of influencing factors, including plant genotype and phenotype, environmental and harvest conditions, post-harvest treatments, storage, and processing methods. Within the framework of a European project aimed at developing a compact, low-cost, and user-friendly system for at-line and on-site quality monitoring (https://www.evoque-project.eu/), this work focuses on two applications: the VOC-based evaluation of raw hazelnut quality during storage and the VOC fingerprinting of roasted coffee for geographic origin discrimination. The system under development integrates portable Gas Chromatography with photonic technologies, such as Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) detector, long-wavelength Quantum Cascade Lasers, and Mid-Infrared Metasurfaces. This combination is designed to enable sensitive and selective VOC detection in complex food matrices, supporting fast, reliable, and environmentally sustainable analyses directly in the field or close to the production line. However, this ambitious integration brings with it several technical constraints, such as the use of nitrogen as carrier gas, high flow rates, a limited maximum operating temperature, and a restricted data acquisition rate. This work aims to adapt the analytical method to these constraints starting from classic chromatographic conditions. Various column geometries were tested to identify optimal configurations: a 0.53 mm column operated at 10 mL/min and a 0.32 mm column at 5 mL/min. The first configuration met key requirements, showing analyte elution below 120 °C, good linearity and sensitivity, and more than 40 data points per peak. The reduced-diameter column provided additional improvements in sensitivity and chromatographic efficiency. These results mark an essential step toward converting a high-information, high-separation platform into a high-throughput, miniaturized tool for real-time quality assessment, in line with the principles of Green Analytical Chemistry.