Green ultrasound-assisted extraction and GC-MS for the identification of intentionally and non-intentionally added substances in bio-based food contact materials

Abstract

The use of bioplastics as food contact materials (FCMs) is rapidly expanding as a sustainable alternative to conventional plastics, with polylactic acid (PLA) being among the most widely used biopolymer. The complex nature of bioplastics makes extraction and detection of intentionally and non-intentionally added substances (IAS and NIAS) particularly challenging, requiring the development of efficient and environmentally sustainable analytical procedures. In this study, a green analytical approach based on ultrasound-assisted extraction followed by GC–MS was developed for the untargeted analysis of GC-amenable IAS and NIAS from commercial biobased FCMs. For the first time in this context, Analytical Quality by Design principles were applied to optimize the extraction process. A screening design was applied to identify the significant critical method parameters, namely, solvent type, extraction and sonication time. A comparative assessment of conventional and green solvents was performed. Cyclopentyl methyl ether showed the highest extraction efficiency, while reducing the extraction time. The method operable design region ranged from 8:30 h to 10:50 h for extraction time and 10–25 min for sonication time. As a proof of concept, the optimized procedure was applied to bioplastic commercial items, leading to the detection of 39 volatile compounds belonging to different chemical classes. Multivariate data analysis allowed for a correct classification of samples according to their composition, demonstrating the method suitability for quality control purposes. Finally, AGREE, BAGI, and CHEMS-1 metrics were used to assess the greenness and applicability of the developed method, demonstrating a good alignment with the principles of green analytical chemistry