Indonesia has significant potential to develop the halal industry due to its majority Muslim population, which constitutes 87.2% of the total population, creating a high demand for halal-compliant products. One major concern in this context is the adulteration of processed meat products, such as sausages, with non-halal meat types. This study aimed to develop a meat type authentication method relevant for halal sausage products by utilizing a lipidomics approach based on ultra-high-performance liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) combined with chemometric analysis, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA).

Three types of sausages were prepared using beef, pork, and dog meat, including their binary and ternary combinations. Lipids were extracted using a modified Bligh and Dyer method, followed by filtration and dilution prior to UHPLC-HRMS analysis. Untargeted lipidomics was performed to identify variations in lipid profiles across different meat sources.

The results indicated that lipid categories such as glycerophospholipids exhibited distinct patterns among the sausage types and have the potential to serve as crucial biomarkers for meat type in halal authentication, detecting non-halal meat adulteration. PCA successfully visualized clustering among sausage groups, while PLS-DA identified 15 potential lipid markers in each ionization mode. In pork sausages, PG(16:0/18:2) and PE(6:0/14:1)+H were identified, aligning with previous findings and considered key indicators of non-halal meat presence. In dog meat sausages, notable lipid markers included PC(18:0p/17:1)+H, PC(13:0/21:2)+H, PE(8:0p/11:0)+H, PS(6:0/14:0)+H, PS(10:0/10:0)+H, and PS(8:0e/13:0)+H.

These findings demonstrate that untargeted lipidomics, combined with chemometric analysis, provides a promising approach for authenticating meat types in processed products, thereby supporting halal assurance and protecting consumers from non-halal meat adulteration.