## 4 Conclusions  
The best conditions for the enzymatic treatment were dependent on both the enzymes and the raw material. For whole fish, Neutrase led to the best yield, and the 70-min extraction time was better than 35 min. Neutrase also led to a smaller total volatile content than the other two enzymes; however, treatment with Alcalase gave the smallest TOTOX values. In contrast, extraction with Protamex resulted in the most oxidized oils. For by-products, Protamex with a 70-min extraction time led to the highest yield. Both hydrolysis times with Protamex resulted in oils with lower total volatile contents compared to treatment with Alcalase, and the longer extraction time with Neutrase. The PCA models show distinctive differences in the oils extracted with different enzymes. Neutrase and Protamex extractions showed a negative correlation with volatile oxidation products in the PCA model. Further research is needed to optimize the enzyme-assisted oil extraction process to improve the yield and quality of crude oils. Figure 3: Principal component analysis (PCA) of volatile compounds that were most influential in PCAs with all identified volatiles, total volatile and aldehyde peak areas, EPA, DHA and PUFA contents, and AVs and PVs. Both raw materials were analyzed together and marked to the figures as bb (by-products) and wbh (whole Baltic herring). The enzymes are marked as their initials: A for Alcalase, N for Neutrase and P for Protamex. The figures are (**a**) scores plot and (**b**) correlation loadings of principal components PC1 and PC2. The data was normalized (auto normalization) and centered (mean centering). **Author Contributions:** Conceptualization, E.A., A.M.-V., A.D. and B.Y. ; methodology, E.A., A.M.-V. and B.Y. ; formal analysis, E.A., A.M.-V. and A.D.; investigation, E.A. and A.M.-V., resources, B.Y. ; writing--original draft preparation, E.A., A.M.-V. and A.D.; writing--review and editing, E-A., A.M.-V., A.D. and B.Y. ; visualization, E.A. ; supervision, A.M.-V., A.D. and B.Y. ; project administration, B.Y. ; funding acquisition, B.Y. All authors have read and agreed to the published version of the manuscript. **Funding:** This work was funded by the Finnish Culture Foundation (the Project \"Green technologies for the extraction of high-quality oil for human consumption\", grant number 28.01.2019) and by the Finnish Operational Programme of the European Maritime and Fisheries Fund (the Project \"Blue Welfare Network-Blue Products\", Project no. 3338. [PERSON] acknowledges support from the MICIU (Spain) through the Juan de la Cierva-Formacion program (FJC2018-035486-I). **Data Availability Statement:** Not applicable. **Acknowledgments:** The authors would like to acknowledge our colleague in Project \"Blue Welfare Network-Blue Products\" [PERSON] for her constructive comments on this study. **Conflicts of Interest:** The authors declare no conflict of interest. Figure 11: Principal component analysis (PCA) of volatile data from enzymatically extracted oils from whole Baltic herring. The samples are A: Alcalase (blue), N: Neutrase (red) and P: Protarex (green). The samples are also marked according to their extraction times of 35 or 70 min. (**a**) Scores plot of Principal Components (PC) 1 and 2; (**b**) correlation loadings of PC1 and PC2; (**c**) scores plot of PC1 and PC3 and (**d**) correlation loadings of PC1 and PC3. The numbered volatiles are (1) acetaldehyde, (2) 2-propanal, (3) propanal, (4) butanalo  
Figure A2: Cont. Figure 13: Principal component analysis (PCA) of volatile data from enzymatically extracted oils from by-products of Baltic herring. The samples are A: Alcalase (blue), N: Neutrase (red) and P: Protamex (green). The samples are also marked according to their extraction times 35 or 70 min. (**a**) Scores plot of Principal Components (PC) 1 and 2; (**b**) correlation loadings of PC1 and PC2; (**c**) scores plot of PC1 and PC3 and (**d**) correlation loadings of PC1 and PC3.