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.

In this study, the chemical composition of different tissues of Rana temporaria chensinensis David derived from the same individual was analyzed by comparative approach. First, pre-column derivatization combined with high performance liquid chromatography (HPLC) was established to determine the content of 1-methyl hydantoin in samples, which used S1–S5 samples. The results indicated that 1-methyl hydantoin was determined in Oviductus Ranae (OR), Rana chensinensis ovum (RCO), Rana chensinensis meat (RCM), and Rana chensinensis skin (RCS), except for Rana chensinensis bone (RCB). Moreover, the content of it in RCS was the highest. In addition, the contents of six polyunsaturated fatty acids (PUFAs) in different tissues of Rana chensinensis were measured by HPLC, including eicosapentaenoic acid (EPA), α-linolenic acid (ALA), docosahexaenoic acid (DHA), arachidonic acid (ARA), linoleic acid (LA) and oleic acid (OA). The results indicated that OR, RCO, RCM, RCS, and RCB all contained the above six PUFAs. With the aid of chemometrics methods, the results of principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) combined with the sequencing results of the total PUFAs content of each sample, showed that different tissues of Rana chensinensis could be divided into four categories, and the RCO sample was divided into one category because of the highest PUFAs content, which was a good source of PUFA. For comparison, OR and other tissue from the perspective of PUFAs, we also established OPLS-DA models of them. It could be found that the RCM was the most similar to the OR in the diversity and content of PUFAs. This study provided a theoretical basis for the further development and utilization of RCO, RCM, RCS, and RCB as by-products of OR.