Definition of the optimal conditions for the convective hot air drying process
For the design studied (Table 4), after eliminating the parameters with non-significant effects, the ANOVA test applied shows the significance of the regression and of the lack-of-fit with a 95% confidence level by using F test. Table 4 also presents the coded models proposed to represent gel strength, moisture, and water activity in the fish skin gelatin.
The analysis of variance (Table 4) shows that the model fitted to gel strength was significant and predictive at 95% confidence level30. For a regression to be significant not only statistically but also useful for predictions, the F value calculated for the regression must be, at least, four to five times greater than the F value tabulated. In the present study, the F calculated was 23.02 times greater than F tabulated. The lack-of-fit was not significant at the same confidence level, thus the model and response surface were generated. The coefficient of determination (R2) indicates that the model explained 98% of the total variation of the data observed. The model fitted to moisture (Table 4) was significant and predictive at 95% confidence level. The lack-of-fit was not significant, allowing the model explains 96% of the data variation.
The water activity (Table 4) showed the fitted model was significant and predictive, explaining 97% of the data variation. The lack-of-fit was not significant at 95% confidence level.
Figure 1 shows the response surfaces and level curves generated by the models proposed, which consider the mean points of time and temperature and gelatin drying regarding to the responses of gel strength, moisture, and water activity.
Response surface and level curve for gel strength (A), moisture (B), and water activity (C) relating time and temperature of convective drying of gelatin.
Figure 1A shows the region with the highest gel strength found at the highest temperatures. This behavior can also be observed in the analysis of the coefficients model (Table 4), where linear temperature (X2) was the parameter with greatest influence. The estimated effect indicates how much each factor impacts the responses studied31 (Higher values means greater the influence). A positive effect indicates that, by going from a minimum value to a maximum value of the variable, the response increases, whereas a negative effect indicates the opposite. Thus, temperature had a positive effect on the response, i.e., when going from the lowest temperature (− 1) to the highest (+ 1), gel strength increases. However, for the same dependent variable (gel strength), linear and quadratic drying time (X1 and X12) had significant negative effects (Table 4), i.e., increases in these parameters decreases gel strength and makes the gelatin less rigid, hence the best condition is found in the region with the shortest time.
Interpreting the model, response surface plots, and level curves shows that the greatest gel strength is obtained by using higher temperature and shorter time during drying. Depending on the target application of the gelatin, this protein can be used with high or low gel strength. Gelatins with gel strength of 260 g on average is more appropriate for applications in food32. On the other hand, gelatin with high gel strength can be used as a biopolymer to produce biodegradable films, which makes them more rigid and, consequently, have better mechanical properties.
This gelatin can be considered a multi-purpose hydrocolloid that can be used as an ingredient in confectionery products, desserts, dairy products, savory dishes, soft and hard capsules, tablets, cosmetics, sports and nutritional beverages, dietary supplements, photography, microcapsules, and many other applications33.
Concerning moisture percentage and water activity (Fig. 1B,C, respectively), it can be seen that the parameters of linear (X2) and quadratic (X22) temperature have a desirable negative effect (Table 4), i.e., an increase in this factor leads to lower responses. The lowest water contents are found in the highest temperature range (45–59.1 °C). Drying at higher temperatures leads to higher water evaporation rates from the food product due to the efficiency of the heat and mass transfer process34. However, the quadratic time variable (X12) had a significant positive effect on water activity. On the other hand, the water activity of the dried gelatins ranged from 0.165 to 0.376, which indicates very little water availability for chemical reactions and microbial growth.
Simultaneous optimization of the convective drying process
The optimal drying process conditions were estimated based on the experimental data proposed by the RSM and by the simultaneous optimization technique called desirability function. From those results, optimal values were established for the input variables of time and temperature to obtain desirable values for the responses of gel strength, moisture, and water activity.
In the desirability function plot (Fig. 2), the red vertical dashed lines indicate the maximum overall desirability conditions. Therefore, the optimal point found by assessing the results was 1, which corresponds to approximately 100% reliability and shows the optimal conditions of the factors being studied are time of 12.35 h and temperature of 59.14 °C (level + α). Under such conditions, a product with the most desirable values of gel strength (517.5 g), moisture (5.79%), and water activity (0.114) should be produced.
Desirability profiles for oven time and temperature in gelatin drying for the convective drying process.
Determining the process variables of the combined drying
The estimated contrast, t coefficient, and statistical significance (p) of each factor of combined gelatin drying in relation to the responses of gel strength, moisture, and water activity obtained after the fish gelatin production process are seen in Table 5. These values were determined through pure error and the factors in bold indicate the variable had significant difference in relation to the responses with 95% confidence (p < 0.05).
The gel strength results (Table 5) show an influence of infrared temperature, oven temperature, and oven time, with significant negative contrasts (p < 0.05). Oven temperature was the factor with the greatest contrast (X2 = − 71.14), with the assays with the highest values producing the least rigid gelatins (Bloom = 179.2–209 g). According to35, the Bloom values of commercial gelatins are classified as low (< 150 g), medium (150–200 g), and high (> 220 g). Therefore, the results show the gelatins have good gelling properties in the range of 179.2–452.3 g.
An analysis of moisture (Table 5) shows that variables X1 (oven time) and X2 (temperature) had significant negative contrasts when considering pure error. Thus, an increase in these two factors leads to a decrease in water content, which improves gelatin stability. However, the only variable that had significant contrast for water activity was X3 (infrared temperature), which confirms the data behavior.
Variable X4 (infrared time) showed no significant contrast on the responses studied (Table 5), thus the infrared drying time was fixed at 2 h taking into account the reduction in process time and cost.
Defining the optimal conditions of the combined drying process
According to the fractional design, the variables that influenced (p < 0.05) gel strength, moisture, and water activity were oven time, oven temperature, and infrared temperature. Therefore, a full factorial design with three factors was carried out to study the influence of the significant independent variables X1 (oven time), X2 (oven temperature) and X3 (infrared temperature) on those responses. Table 6 shows the analysis of variance, model, F test, and R2 of the combined process.
The analysis of variance showed that the models fitted to all responses had significant (Fcal > Ftab) and predictive regression with non-significant lack-of-fit (Table 6). The R2 values of the variables studied indicate the models properly described the process behavior and explained 96.9, 90.6, and 96.3% of the variation in experimental data of gel strength, moisture, and water activity, respectively.
Gel strength had significance, with a negative effect, on all factors when the model coefficients and the estimated effect of each independent variable were assessed since an increase in these parameters led to lower gel strength (Table 6, Fig. 3A). The highest drying temperatures caused protein degradation and produced protein fragments with reduced gelling capacity. Worked with different drying temperatures to produce gelatin from sea bass (Lates calcarifer) skin and also associated decreases in gel strength with the formation of small protein fragments36.
Response surface for gel strength (A), moisture (B), and water activity (C) relating oven time and temperature and infrared temperature of the combined drying of gelatin process.
For moisture and water activity (Table 6), oven time and temperature had a significant negative effect. Meanwhile, the X32 (quadratic infrared temperature) had a positive effect with the increase in water activity.
Figure 3B shows that the region with the lowest water content is found in the region with the highest oven time and temperature. The same behavior was observed for water activity, with the central region having the lowest levels, which confirms the efficiency of the heat and mass transfer process since drying at higher temperatures increase the water evaporation rate from the food.
Simultaneous optimization of the combined drying process
Figure 4 presents the desirability function plot applied to the data found in the 23 CCRD for gelatin drying using the combined method.
Desirability profiles for infrared temperature and oven temperature and time for the combined drying process.
The red vertical dashed lines indicate the maximum overall desirability conditions with the optimal conditions for gelatin drying being X1 = 3.51 h, X2 = 70 °C, and X3 = 70 °C. Under such conditions, a product with the most desirable values of gel strength (304.88 g), moisture (8.86%), and water activity (0.20) should be produced. These results match those found when observing the response surface plots (Fig. 3).
Physical, chemical, technological and functional properties of gelatins obtained by using optimized conditions
The results of physical, chemical, technological, and functional characterization of the gelatins obtained by using optimized conditions, are presented in Table 7. The gelatin obtained by the convective hot air process had lower water content (p < 0.05) compared to the combined process, due to the long drying time (12.35 h) the convective process requires. These results are similar to those reported for lyophilized fish skin (7.51%)20.
According to the standard methods to test edible gelatin and the regulation for industrial and sanitary inspection of products of animal origin37, moisture and ash contents must be lower than 15% and 2%, respectively. Thus, the results found are within the limits set by the legislation (Table 7).
The gelatin obtained by either method used in this study has a high protein content of about ~ 90%, which is above the 88% previously reported38. It is noteworthy that the high protein content represents the amount of partially hydrolysate collagen in the gelatins, which can be considered excellent raw materials to produce new products.
The lipid content found in this study was 1.87% (p ≥ 0.05), which is considered low and desirable for fish skin gelatins. Fish skin contains lipids with high degree of unsaturation and the products of lipid oxidation mainly contribute to the fish odor in the final product39. The gelatins obtained had low characteristic fish odor, which shows their viability since such odors may limit their applications, particularly as food ingredients.
The highest gel strength value was obtained by convective drying (507.33 g) and the lowest, by combined drying (298 g). However, both products can be used in different applications. Gel strength is one of the most important functional properties of gelatin. Fish gelatin typically has lower gel strength than gelatin from mammals (0–200 g), which was not observed in this study32.
The results indicated that gel strength was influenced by drying temperature since the highest result for dry gelatin was 59.14 °C (Table 7), that is, the higher the temperature, the lower the gelatin bloom. Indicating that higher temperatures produce protein fragments with less gelling capacity.
The results indicated that gel strength was influenced by drying temperature since the highest value was 59.14 °C (Table 7), which means, to higher temperatures, the gelatin bloom is lower. Thus, higher temperatures produce protein fragments with less gelling capacity. Short protein chains are less able to form a junction zone during gelatin drying process, which difficult the growing of nucleation sites and generates a less strong network with more fragile gel40. Despite the reduction, the gel strength of the gelatin obtained from the combined drying process is within the values considered like satisfactory (298 g) when compared to commercial gelatin.
Studies have reported that increasing the drying temperature of fish skin gelatin reduced the gel strength41. The gel strength values were related to intrinsic characteristics such as molecular weight distribution, protein chain length, interactions among amino acids, and α/β chain ratio in the gelatin, as well as the location of amino acids in the peptide chain42,43.
The melting point of the gelatin obtained by the convective process differed (p < 0.05) from the sample dried using the combined method. This property is impacted by many factors, such as the distribution of mean molecular weight, concentration, time and temperature of gel maturation, extraction conditions, and the proline and hydroxyproline ratios and extraction in the original collagen molecule in the material44. The highest result was the one found (Table 7) for convective drying, which was higher than the values previously reported45. Gelatins with higher melting point provide better mouth feel.
The functional properties (foaming and emulsion activity index) were lower (p < 0.05) for the gelatin obtained through the convective drying process (Table 7). It is likely that exposure to drying had an undesirable influence on these properties. However, the results were higher than those previously reported for emulsifying activity (16.23–31.46 m2/g)46 and then those observed for foaming (0.35%)47.
Overall, these properties are positively correlated with the molecular weight of the peptides since larger and longer peptides may more effectively stabilize the protein in the interface48. Emulsion stability and foaming allow for multifunctional gelatin and are widely explored properties by the confectionery industry in products such as marshmallows and chewing gums. It can also be used as emulsifier in aerated dairy desserts such as mousses, yoghurts, curds, and ice creams, which are three-phase systems formed by air, oil, and water49.
Color is an important parameter that may determine the application of gelatin. The sample obtained by combined drying for 3.51 h had lighter color (L*) and lower color variation (ΔE) (p < 0.05) compared with the gelatin dried by convection for 12.35 h. These results indicate that the drying conditions and different processes impacted the color of the gelatins extracted from acoupa weakfish (Cynoscion acoupa) skin.
