Preparation of gelatin hydrolysate
Bovine gelatin in powder form (Sigma, USA) as the substrate and trypsin (buffer, 0.1 M Na2HPO4–NaH2PO4; temperature 37°C; pH 8.8) (Sigma, USA) for enzymatic hydrolysis were used in this study. All chemicals used were of analytical grade. For the preparation of a 1% w/v gelatin solution, 1 g of bovine gelatin powder was mixed with 100 mL phosphate buffered saline (pH = 7.4), heated and stirred at 50°C for 2 h. To inactivate any enzymatic activity, gelatin solutions were heated at 95°C for 15 min in a boiling water bath. For pH adjustment, hydrochloric acid (0.1 mol/L, Merck, Germany), sodium hydroxide (0.1 mol/L, Merck, Germany) were used. Gelatin solutions were prepared and incubated at various pH levels, enzyme/substrate ratios (E/S), temperatures and times as determined by RSM optimization and modeling approaches.
Optimization and modeling of enzymatic hydrolysis process by response surface methodology
Response surface methodology was used to model and optimize the hydrolysis conditions of bovine gelatin hydrolysis using trypsin. Optimization of four variables including temperature (X1 = 30, 35, 40, 45 and 50°C), pH level (X2 = 5, 6, 7, 8 and 9), E/S (X3 = 2, 2.5, 3, 3.5 and 4) and time (X4 = 1, 2, 3, 4 and 5 h) for the level of antioxidant activity (Y) was carried out using the Design-Expert software package version 10.0.3.1 (Stat-Ease Inc., Minneapolis, USA). The experimental design is presented in Table 1. Each variable contained five distinct levels. In total, 30 runs were performed, using a central composite rotatable design (CCRD) to scrutinize the impacts of the independent variables. The response function (Y) was associated with the coded variables (X1, X2, X3 and X4) by a second order polynomial equation using the least squares method and the results of experiments were fitted with the following equation:
Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + β11X1X1 + β22X2X2 + β33X3X3 + β44X4X4 + β12X1X2 + β13X1X3 + β14X1X4 + β23X2X3 + β24X2X4 + β34X3X4
where Y represents the level of antioxidant activity response; β0, is the offset term; β1, β2, β3, β4 are the linear effect terms; β11, β22, β33, β44 are the squared effects, β12, β13, β14, β23, β24, β34 are the interaction effects; and X1, X2, X3 and X4 are the variables. Analysis of variance (ANOVA) was regarded to evaluate the significance level (P < 0.05) of polynomial regression model terms for the response value. R2, adjusted and predicted R2 values are determination coefficients analyzed by F-test. Adequacy of the regression model was assessed by calculation of adequate precision (ADP), coefficient of variance (CV), lack of fit and the PRESS values. Fitness of the model was improved by omitting the non-significant (P > 0.05) terms. The model was verified by comparing the response values from experimental design and the predicted responses from the fitted and optimized model.
Antioxidant activity
The antioxidant activity of the hydrolyzed gelatin solutions was measured using DPPH (1, 1-diphenyl-2-picrylhidrazyl) assay. The DPPH method was carried out as previously described by Kedare and Singh (2011) (7). In the presence of antioxidant compounds, DPPH is able to accept a hydrogen atom or an electron from the antioxidant molecules contributing to reduction of DPPH radicals and producing a non-color ethanol solution. A 60 µL aliquot of hydrolyzed gelatin solution (or ethanol as the negative control) was mixed with 60 µL of DPPH solution (60 µM; prepared in ethanol) for 10 s then was transferred into a quartz capillary tube. After 30 min incubation, the scavenging activity of the hydrolyzed gelatin solution on DPPH radicals were evaluated spectrophotometrically and the absorbance of the samples were measured at 517 nm. The antioxidant activity of the samples was calculated by the following formula:
Antioxidant activity (%) = (Ac-As/Ac) × 100
Where Ac and As represent the absorbance values of control and sample, respectively.