Response surface methodology (RSM) was performed in order to determine the optimal mixing conditions of different amounts of egg and sugar for the preparation of soybean pudding. The experiments were designed according to a central composite design by designating whole egg and sugar content as indep...
Response surface methodology (RSM) was performed in order to determine the optimal mixing conditions of different amounts of egg and sugar for the preparation of soybean pudding. The experiments were designed according to a central composite design by designating whole egg and sugar content as independent variables. Meanwhile, sweetness, Commission Internationale de I'Eclairage (CIE) color parameters (L*, a* and b* values), hardness, cohesiveness, springiness, and gumminess were response variables. Overall optimization, conducted by overlaying the contour plots under investigation, was able to determine the optimal range of dependent variables within which the 14 responses were simultaneously optimized. The point chosen as a representative of this optimal region corresponded to 50.00 g of whole egg and 31.66 g of sugar. Under these conditions, the model predicted L* value=80.03, a* value=-5.44, b* value=27.86, sweetness=21.23 ($^{\circ}Brix$), hardness=$25.45{\times}10^5$ (dyne/$cm^2$), cohesiveness=67.90 (%), springiness=46.20 (%), and gumminess=12.71 (g).
Response surface methodology (RSM) was performed in order to determine the optimal mixing conditions of different amounts of egg and sugar for the preparation of soybean pudding. The experiments were designed according to a central composite design by designating whole egg and sugar content as independent variables. Meanwhile, sweetness, Commission Internationale de I'Eclairage (CIE) color parameters (L*, a* and b* values), hardness, cohesiveness, springiness, and gumminess were response variables. Overall optimization, conducted by overlaying the contour plots under investigation, was able to determine the optimal range of dependent variables within which the 14 responses were simultaneously optimized. The point chosen as a representative of this optimal region corresponded to 50.00 g of whole egg and 31.66 g of sugar. Under these conditions, the model predicted L* value=80.03, a* value=-5.44, b* value=27.86, sweetness=21.23 ($^{\circ}Brix$), hardness=$25.45{\times}10^5$ (dyne/$cm^2$), cohesiveness=67.90 (%), springiness=46.20 (%), and gumminess=12.71 (g).
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문제 정의
Despite of previous investigations, research on dessert food using soybean is yet insufficient. Therefore, the goals of this study were to perform a systematic investigation of how different process conditions influence the physicochemical properties of puddings using response surface methodology(RSM), to determine the optimal condition in producing soybean pudding and to provide reliable experimental data for a variety of uses industrially and development of well being snacks which are able to be loved without distinction of age or sex.
제안 방법
Two factors were chosen as independent variables which were the content levels of whole egg and sugar. As dependent variables, sweetness, color parameters (L*-, a*-, and b*- values), texture (hardness, cohesiveness, springiness, gumminess) and sensory evaluation (color, appearance, flavor, texture, taste and overall quality) were selected. The minimum and maximum ranges of egg and sugar were determined to be 50~90 and 12~36 g, respectively from preliminary examinations.
All panelists were presented 10 samples for each treatment respectively. The panelists were asked to evaluated the color, appearance, flavor, texture, taste and overall quality of the soybean pudding by awarding a score ranging from 1 (dislike extremely) to 7 (like extremely).
대상 데이터
A commercial brand of soybean (Nokwon Foodlim Co., Yongin, Gyeonggi, Korea), eggs (Younglim, Yongin, Gyeonggi, Korea), sugar (CJ Corp., Incheon, Korea), vanilla essence (Gold medal Pure Vanilla extract, COMAN, USA) were used for all samples.
데이터처리
The independent and dependent variables were fitted to the second-order model equation and examined for the goodness of fit. Regression analysis and ANOVA were conducted for the model to examine the statistical significance of the model terms. ANOVA of the effect of whole egg and sugar content to produce puddings as linear, quadratic and interaction terms on the response variables are shown in [Table 3].
이론/모형
Sensory evaluation was done according to the seven-point hedonic scale. Processed soybean pudding was evaluated for its sensory quality by 35 graduate student panels at the department of food and nutrition of Sookmyung women’s university.
성능/효과
ANOVA of the effect of whole egg and sugar content to produce puddings as linear, quadratic and interaction terms on the response variables are shown in [Table 3]. The results indicated that the model for CIE L* values, sweetness, hardness and gumminess is highly adequate with their satisfactory levels of R2 (0.85-0.97) and model significance. It has been suggested that the model with R2 greater than 0.
The results indicated that the model for lightness was linear and was highly adequate with the satisfactory levels of R2 (0.85) and model significance (p<0.01), but redness and yellowness results showed low coefficient of determination R2 and the two models were not significant.
The results indicated that the model for sweetness was linear and highly adequate with the satisfactory levels of R2 (0.87) and model significance (p< 0.001).
The software generated two optimum conditions of independent variables namely whole egg and sugar with the predicted values of responses, in the range of whole egg=50.00 g and sugar=31.66 g for achieving the highest values of L*=80.03, a*= −5.44, b*=27.86, sweetness =21.23 (Brix), hardness=25.45×104 (dyne/cm2), cohesiveness =67.90 (%), springiness=46.20 (%), gumminess=12.71 (g), color preference=4.90, appearance preference=4.24, flavor preference=4.55, texture preference=5.10, taste preference= 4.22, overall quality=4.94.
RSM was successfully applied to optimize the soybean pudding. The study showed that both whole egg and sugar content were important factors to affect the physicochemical properties and sensory properties of soybean puddings. Most polynomial models developed by RSM were highly effective to describe the relationships between the studied factors and the responses.
후속연구
The results of soybean application can be easily implemented to estimate the physicochemical properties when the process parameters are known. Nevertheless, further research is needed on RSM optimization with other factors including baking time, temperature and soybean content.
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