# Optimization of Valorization of Chicken MDCM to Produce Soluble Protein and Collagen Peptides
## 3 Results and Discussion  
### MDCM Protein Hydrolysate Production  
The volume and protein concentrations of the produced protein fraction were collected, and the protein yield was calculated to establish the statistical model between processingfactors and the response. The model was fitted with multiple linear regression, and ANOVA was performed. The resulting regression coefficients for MDCM meat hydrolyzed with ERM 1 were as follows: \(R^{2}\) = 0.888; Q\({}^{2}\) = 0.451. ANOVA showed that the model was statistically significant (\(p\) = 0.001), and no lack of fit was observed (\(p\) = 0.166). Similarly, in the second set of experiments when both ERM 1 and ERM 2 were used in the hydrolys process, these values were \(R^{2}\) = 0.687 and Q\({}^{2}\) = 0.615. ANOVA showed that the model was statistically significant (\(p\) = 0.001), and no lack of fit was observed (\(p\) = 0.620) in this case. The results indicated that there was a difference in the dominant factors in the ERM 1 and ERM 1 + 2 treatments. Hydromodule and the enzyme-substrate ratio as main factors played a significant role in protein recovery with the single ERM 1 enzyme hydrolyses, while the hydrolysis time did not play significant role. The interaction terms were also investigated, and hydrolysis time, the hydromodule, and the enzyme-substrate ratio, therefore, played an important role in the model. Furthermore, the second orders of the hydromodule and the enzyme-to-substrate ratio were also significant in the modeling. On the basis of the results, the second-order polynomial equation to describe the model is as follows:  
\[\mathrm{Y}=8.766\mathrm{X_{1}}-27.90\mathrm{X_{2}}+22.34\mathrm{X_{3}}+23.41 \mathrm{X_{2}}^{2}-39.29\mathrm{X_{3}}^{2}+15.99\mathrm{X_{1}}\mathrm{X_{2}}- 15.95\mathrm{X_{2}}\mathrm{X_{3}},\]  
where \(\mathrm{Y(\%)}\) is protein recovery, \(\mathrm{X_{1}}\) = time, \(\mathrm{X_{2}}\) = hydromodule (L/kg), and \(\mathrm{X_{3}}\) = E:S ratio. In the optimization function, a hydrolysis time of 4 h, an E:S ratio of 0.4325%, and a hydromodule of 1 L/kg were selected. In these conditions, protein recovery was shown to be above 114.03 g/kg protein stock (yield of approximately 90%) with ERM 1. The model was shown to be simpler in the case of hydrolyses with both ERM 1 and ERM 2, in which case only the major terms, the time of the hydrolyses, the hydromodule, and the enzyme-substrate ratio, played a significant role in the protein recovery, although the model fitting showed lower \(R^{2}\) and Q\({}^{2}\) values than those described above. The second-order polynomial equation based on the results to describe the model is as follows:  
\[\mathrm{Y}=21.66\mathrm{X_{1}}-35.62\mathrm{X_{2}}+21.66\mathrm{X_{3}}.\]  
In the optimization function, a hydrolysis time of 4 h, an E:S ratio 0.2709% for both enzymes, and a hydromodule of 1 L/kg were selected. In these conditions, the protein concentration was above 118.03 g/kg protein stock (yield of approximately 90%) with ERM 1 + 2 enzymes. The longer enzymatic treatment (72 h) of MDCM was found also more favorable to achieve higher hydrolysate yield (6.2-6.8%); correspondingly, the total gelatin recovery was also significantly influenced by the extraction temperature and time with close to a final recovery yield of 46%. [PERSON] et al. (20), on the other hand, determine that the optimal combination of different proteases might be a good way toward more profitable processing with an increase in yield of 15% in poultry byproduct valorization, making the process even more profitable. The model was verified by repeating the experiments twice within the optimal process parameters, and similar results were found for the protein concentration and recovery values. Table 3 shows the proximate composition of fractions produced in optimal conditions after 4 h of hydrolysis with one enzyme and the combination of enzymes using the optimal process conditions. [PERSON] et al.