Volatile profile analysis of pasta using HS-SPME/GC–MS and chemometric modelling for process and quality marker identification

Dried pasta is a staple in global cuisine and its production process is crucial to the quality of the final product, especially the drying phase. Depending on whether Low-Temperature, Long time drying (LT-Lt) or High/Very High Temperature – Short time drying (HT-St/VHT-St) is used, the organoleptic and nutritional properties of the pasta, its shelf life and overall quality can vary significantly. The flavour profile of pasta acts as a “fingerprint”, with specific volatile compounds acting as markers that reveal its production history, and the heat treatment applied. This study aimed to identify innovative processes and quality markers for pasta, using its flavour as a key indicator. To achieve this goal, 100 samples of spaghetti from five different brands were analyzed using Headspace Solid-Phase Microextraction / Gas Chromatography–Mass Spectrometry (HS-SPME/GC–MS). The collected data underwent qualitative evaluation followed by processing with chemometric classification models, Partial Least Squares - Discriminant Analysis (PLS-DA) and Soft Independent Modelling of Class Analogy (SIMCA). Despite some challenges, these models successfully characterized samples based on their flavour profiles. More importantly, they identified novel indicators that can distinguish pasta from different brands and innovative process markers that differentiate slow-dried pasta from high-temperature-dried pasta. Among the most significant markers identified were furfural, 2-furanmethanol, maltol, hexanal, 2-pentylfuran, 1-hexanol, nonanal, nonanoic acid, and acetic acid.