Volatile fingerprinting of allspice (Pimenta dioica L.) leaf essential oil by GC-MS, E-Nose and NMR

The study explores the Allspice (Pimenta dioica L.) leaf essential oil (AEO), employing green techniques to enhance yield and chemical composition, thereby broadening its applicability in food, pharmaceutical, flavoring, and cosmetic industries. Enzyme-assisted methods, particularly cellulase and viscozyme, significantly increased the AEO yield (2.8 +/- 0.5% and 3.28 +/- 0.25%) while maintaining its physical properties. The chemical composition of AEO was analyzed using gas chromatography-mass spectrometry (GC-MS), fourier transform infrared spectroscopy (FTIR), and nuclear magnetic resonance (NMR), including 1H, 13C, and 2D NMR techniques like HSQC and HMBC. Antioxidant activity was determined using the ABTS assay, while aroma profiling was conducted using an electronic nose (E-Nose) combined with principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). Enzyme pretreatment boosted total phenols by 26% as well as antioxidant activity (87.2 +/- 0.75 to 90.83 +/- 0.75 mg TE/ml) through complex enzyme interactions, indicating improved bioactivity. Eugenol (74.43%), beta-myrcene (10.75%), p-chavicol (5.00%), and limonene (2.67%), are major compounds identified by GC-MS. ATR-FTIR confirmed aromatic ethers, carboxylic acids, alkanes, alkenes, and alkynes in 750-2900 nm. NMR spectroscopy differentiated beta-pinene and beta-myrcene (both C10H16 isomers), while providing detail insight into eugenol, p-chavicol, beta-myrcene, and caryophyllene. Aroma profiling using an E-Nose revealed distinct volatile compound patterns, visualized using PCA and SIMCA. This study insights into the aroma, flavor, and chemical composition of Allspice leaves, highlighting its potential for diverse industrial applications and promoting green extraction process.