This work demonstrated a method combining reversed-phase high-performance liquid chromatography (RP-HPLC) with chemometrics analysis to identify the authenticity of Ranae Oviductus. The fingerprint chromatograms of the Ranae Oviductus protein were established through an Agilent Zorbax 300SB-C8 column and diode array detection at 215 nm, using 0.085% TFA (v/v) in acetonitrile (A) and 0.1% TFA in ultrapure water (B) as mobile phase. The similarity was in the range of 0.779–0.980. The fingerprint chromatogram of Ranae Oviductus showed a significant difference with counterfeit products. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) successfully identified Ranae Oviductus from the samples. These results indicated that the method established in this work was reliable.

Oviductus Ranae is a nutritional product for both medicine and food. Its quality is uneven due to multiple factors. An efficient method was established to evaluate the quality of Oviductus Ranae using fingerprint techniques and chemometric methods based on the analysis of polyunsaturated fatty acids (PUFAs) in petroleum ether extract by high performance liquid chromatography (HPLC). During this process, 27 batches of Oviductus Ranae were analyzed by HPLC and two types of chromatographic fingerprints were established. The fingerprint that was obtained by matching six known peaks was used for the quantification of six PUFAs. Another fingerprint was obtained by matching sixteen peaks with a peak area ratio greater than 0.5% and it was used to classify the different qualities of Oviductus Ranae by further combining three different chemometric models. The 27 batches of Oviductus Ranae were divided into four categories, which was consistent with the analysis results of six PUFAs contents. The two high-quality samples with significantly higher contents were classified into one category, and samples with medium contents were divided into two categories, including eight and thirteen samples, respectively. The four inferior samples with lower contents were classified into one category. The results indicated that the newly developed method has potential application prospects for the quality evaluation of Oviductus Ranae.

Rana chensinensis ovum oil (RCOO) is an emerging source of unsaturated fatty acids (UFAs), but it is lacking in green and efficient extraction methods. In this work, using the response surface strategy, we developed a green and efficient CO2 supercritical fluid extraction (CO2-SFE) technology for RCOO. The response surface methodology (RSM), based on the Box–Behnken Design (BBD), was used to investigate the influence of four independent factors (pressure, flow, temperature, and time) on the yield of RCOO in the CO2-SFE process, and UPLC-ESI-Q-TOP-MS and HPLC were used to identify and analyze the principal UFA components of RCOO. According to the BBD response surface model, the optimal CO2-SFE condition of RCOO was pressure 29 MPa, flow 82 L/h, temperature 50 °C, and time 132 min, and the corresponding predicted optimal yield was 13.61%. The actual optimal yield obtained from the model verification was 13.29 ± 0.37%, and the average error with the predicted value was 0.38 ± 0.27%. The six principal UFAs identified in RCOO included eicosapentaenoic acid (EPA), α-linolenic acid (ALA), docosahexaenoic acid (DHA), arachidonic acid (ARA), linoleic acid (LA), and oleic acid (OA), which were important biologically active ingredients in RCOO. Pearson correlation analysis showed that the yield of these UFAs was closely related to the yield of RCOO (the correlation coefficients were greater than 0.9). Therefore, under optimal conditions, the yield of RCOO and principal UFAs always reached the optimal value at the same time. Based on the above results, this work realized the optimization of CO2-SFE green extraction process and the confirmation of principal bioactive ingredients of the extract, which laid a foundation for the green production of RCOO.

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This work studied the influences of environmental factors on the quality features of Oviductus Ranae.