Derivatization-based fatty acid profiling as a promising approach for Oviductus Ranae authentication

A derivatization-based fatty acid (FA) analysis method was applied to distinguish Oviductus Ranae (OR) from its counterfeit products. Samples were derivatized with 4-Amino-1-benzylpiperidine and analyzed by UHPLC-Q-TOF MS. A total of 30 OR samples from Rana dybowskii (Chinese name Linwa, LW) and 30 counterfeit samples from Pelophylax nigromaculatus (Chinese name Qingwa, QW) were collected and randomly divided into training and validation sets at a 2:1 ratio. The untargeted analysis of the training set revealed that 56 compounds were significantly different between LW and QW, of which 35 were FAs. Based on the characteristic fragments obtained from LC-MS, 53 FAs were putatively annotated through the GNPS molecular network and in-house database searching. Finally, 11 FAs were selected based on their signal intensities as FA markers for differentiating LW and QW samples. The classification performance of these 11 candidate FA markers for distinguishing LW and QW was preliminarily evaluated using PCA-Class and PLS-DA models. In the limited validation set, LW samples were correctly classified by the PLS-DA model, suggesting the potential of these markers for LW-QW discrimination under the present analytical conditions.