Solvent-Dependent GC–MS Fingerprinting of Lipophilic Constituents in Syzygium polyanthum Leaves: A Baseline Study for Future Greener Extraction Optimization

Syzygium polyanthum (Wight) Walp., commonly known as Indonesian bay leaf or Daun salam, is widely used as a culinary and traditional botanical resource. However, region-specific information on its lipophilic constituents remains limited, and the sustainability implications of solvent-dependent phytochemical profiling are rarely addressed. This study characterized the GC–MS-detectable volatile lipophilic constituents of a selected nonpolar fraction of S. polyanthum leaves collected from Paniki Bawah, Mapanget District, Manado, Indonesia, using GC–MS, while evaluating solvent-related limitations for future greener extraction strategies. Dried leaf powder was macerated with 96% ethanol, followed by liquid–liquid partitioning with n-hexane and ethyl acetate. The n-hexane fraction was separated by silica gel column chromatography, and a TLC-selected fraction was analyzed by GC–MS. Compound annotation was supported by NIST 17 library matching, retention-index comparison using a C8–C40 n-alkane series, diagnostic ion evaluation, solvent blank analysis, and triplicate injections. Ethanolic extraction of 900 g dried powder yielded 87.0 g crude extract (9.67%). The n-hexane, ethyl acetate, and aqueous fractions yielded 5.98%, 21.15%, and 72.87%, respectively. GC–MS analysis tentatively annotated 11 compounds representing 94.44% of the total normalized peak area. The major constituents were palmitic acid, phytol, squalene, and neophytadiene. All annotations showed match scores of 90–98%, ΔRI values of 4–8 units, and RSD values of 1.86–3.27%. Although ethanol use, sunlight drying, solvent recovery, and recirculating chiller-assisted evaporation partially aligned with green chemistry principles, the use of n-hexane and chloroform means that the workflow should not be described as fully green. This study provides a baseline GC–MS fingerprint to support future greener extraction optimization.