# Collagen-Based Bioactive Bromelain Hydrolysate from Salt-Cured Cod Skin
## 3 Results
### Hydrolysis Optimisation  
When we saw that BR was a good candidate to apply in the production of collagen hydrolyses, we proceeded to design a process that had to be optimised. For this, we carry out an experimental design as described in the methodology. Figure 1: Degree of hydrolysis (DH). DH is expressed in percentage as a function of hydrolysis time expressed in hours. BR: bromelain; CHC: collagenase; Control: without enzyme. Figure 2: SDS-PAGE: Calfskin type I collagen (lane 1), collagen purified from cod skin by acid methodology (lane 2); molecular weight marker (lane 3); initial time of the hydrolysis with bromelain (lane 4), collagenase (lane 5) and control (lane 6); hydrolysis at 30 min with bromelain (lane 7), with collagenase (lane 8) and control (lane 9). Molecular weight in kDa. Supplementary Materials shows all the data acquired for the design and the complete multifactorial analysis for the 15 randomised treatments. The finally adjusted models explained the variability in a good way, as shown by their determination coefficients (R\({}^{2}\) in Figure 3). Figure 3 shows the standardised effects for the coefficients of the factors of the recalculated models (criterion explained in the methodology). We observed that temperature was a significant factor for the three responses considered. For protein extraction, increasing the temperature increased the response and an important maximising curvature effect. On the other hand, for bioactivities, the increase in temperature had a negative effect. The pH effect was significant both for the protein content and antioxidant activity but not for the antihypertensive activity. For protein extraction, increasing the pH increased the extractive capacity. On the contrary, in antioxidant activity, when the pH increased, the bioactivity decreased. In the case of the time factor, it was not significant for any of the responses analysed. However, its interaction with temperature was significant in the case of antihypertensive activity; its interaction with pH was considered in the case of the protein extraction (improved R\({}^{2}_{\text{adj}}\)). In a first step, each response was optimised, obtaining different conditions according to the response to maximise (Figure 4a-c; Table 2). [PERSON]'s total desirability model was applied to carry out general optimisation. Thus, the condition that would allow for the achievement of a good joint maximisation of the responses was reached (Table 3). In the optimal global conditions, the antioxidant activity value (ORAC) is 514 umol Trolox Equivalent/g protein) and the iACE value corresponds to an IC\({}_{50}\) of 59 \(\upmu\)g protein/mL. From the optimal levels, the validation of the models was carried out, but with a slight modification, instead of 29.8 \({}^{\circ}\)C, 30.0 \({}^{\circ}\)C was applied, and the predictions were re-entered with these values. Table 3 shows the predicted values for these validation conditions and the observed values for an experiment done in a single execution (for this reason, it does not present any deviation). From the hypothesis test, we did not find significant differences for a confidence level of 5%. Therefore, the models are valid. Besides, by producing the hydrolysate in this condition, a yield of 44% was achieved. Furthermore, it should be mentioned that, for the hydrolysate produced for the validation, the iACE showed an IC\({}_{50}\) of 166 \(\upmu\)g protein/mL. This value corresponds to a significant antihypertensive potential [23; 26]. Figure 3: Analysis of the effects of the Box–Behnken factorial design. Pareto charts with standardised effects of three experimental factors, in decreasing order of importance (in absolute value) for the three responses: protein concentration (**a**); ORAC (**b**); and iACE (**c**). The vertical blue lines represent the threshold of significance (\(p=0.05\)) for 32 degrees of freedom. Figure 4: Response surface models. Each response is based on two experimental factors keeping the third factor at its central level.