13 OPTIMIZATION OF TOFU WHEY CONCENTRATION IN COCONUT MILK NATA
DE SKIM
Nuriyya Saleh*, Simon Bambang Widjanarko
Department of Food Science and Biotechnology, Faculty of Agricultural Technology, Universitas Brawijaya
Veteran street, Malang 65145 East Java Indonesia
*Corresponding Author, Email: [email protected] ABSTRACT
One of the uses of coconut milk scheme is for the production of Nata De Skim Santan using Acetobacter xylinum bacteria and the addition of tofu whey substrate. This study aims to determine the effect of whey concentration on the characteristics of nata de coconut milk and the right optimum whey concentration on making nata de coconut milk. The independent variable used X1= Whey concentration with a lower limit of 0% (-1) and an upper limit of 50%
(+1). The responses observed were yield (Y1), nata thickness (Y2), and moisture content (Y3).
The results showed that the use of whey concentration had an influence on the characteristics of nata de coconut milk with Fvalue for the yield model, thickness model, moisture content model, and whey was 17.94, 24.83, 14.72, and 14.72. The optimum concentration of whey that is right for making nata de coconut milk was 49.07% with a desirability value of 0.89, the optimum yield was 29.71%, the optimum thickness was 1.13 cm, and the optimum moisture content was 89.7%.
Keywords: Acetobacter xylinum, Coconut milk skim, Nata de coconut milk, Whey tofu
INTRODUCTION
Nata is a food product that is processed through fermentation with the help of Acetobacter xylinum bacteria. Nata is generally clear white in color with a chewy texture and jelly-like shape. The chewy texture of nata is caused by the presence of fiber components formed by Acetobacter xylinum, where in the production of nata, Acetobacter xylinum bacteria have a role in cellulose production (Bäckdahl et al., 2006). Generally, the raw material for nata production uses coconut water as a medium, but nata can also be produced from various substrates that are carbon sources (simple carbohydrates), nitrogen sources (organic or inorganic) and minerals (Setiaji et al., 2010). One material that has the potential to be used as a nata substrate is skim coconut milk.
Skimmed coconut milk is a by-product (waste) of the coconut oil production process.
Skimmed coconut milk is obtained through the wet process of making coconut oil. Generally, the coconut milk skim will be discarded because it does not produce oil and will cause environmental pollution. Skim coconut milk that is not utilized actually still contains several components of water-soluble coconut fruit including proteins, carbohydrates, minerals and others (Setiaji, Setyopratiwi, & Cahyandaru, 2010). Processing skim coconut milk into nata products can add value to the coconut processing process and reduce the waste produced.
Previously, research was conducted by Setiaji, et al (2010) on the use of skim coconut milk and coconut water as raw materials for making nata de coco. In the study, researchers wanted to know the effect of coconut water mixing concentration and sucrose concentration on coconut milk skim as a nata de coco substrate. Variations in the addition of coconut water concentration used were 0%, 15%, 35%, 50% and sucrose of 0.5%, 1%, 1.5% and 2%. The results of the experiment showed that the higher the concentration of sugar, the more Based on this research, it can be seen that the use of skim coconut milk in making nata still requires
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other additional ingredients to support the growth of bacteria that have not been fulfilled in skim coconut milk. One of the ingredients that can be used is tofu whey.The tofu industry in Indonesia is commonly found with different production quantities and sizes. Similar to every industry, the tofu industry also produces quite a lot of liquid waste in the process. Tofu waste in the form of whey should be utilized to help reduce environmental pollution. Whey can be utilized as a nata product because it still contains organic materials such as protein, fat, and carbohydrates (Sutiyanti et al., 2003). The use of tofu whey has the potential to be used in making nata de skim coconut milk. Therefore, research is needed to determine the right concentration of tofu whey for making nata de skim coconut milk.
Response Surface Methodology (RSM) is a statistical and mathematical technique, used to solve problems with procedures, formulas, or a mixture of both. RSM is useful in setting the right conditions for procedures used in the food business, such as drying (Nainggolan &
Amwar, 2023). Response Surface Methodology (RSM) is used for situations where a number of independent variables impact the response variable, aiming to maximize the response. The goal of this strategy is to find the ideal response value with a statistically assisted experimental design (Malingkas et al., 2021).
METHODOLOGY Materials
The materials used in this study include coconut milk, Tofu whey obtained from Bandung Raos 3 Tofu Factory, Bogor. Acetobacter xyilinum bacterial starter was obtained from Bagasari, Bekasi. sucrose, coconut water, Ammonium Sulfate from PT Trias Nathomi Chemindo, and Acetic Acid.
Tools
The tools that will be used in this research are plastic containers, measuring cups, erlenmeyers, measuring pipettes, bulp, test tubes, vectors, gas stoves, analytical scales (Denver Instrument M-310), and pH meters (Trans Instrument Senz).
Research Design
This study was conducted using Response Surface Methodology (RSM) Randomized Optimal design using Design Expert 10 (DX10) software. The independent variable used was X1 = whey concentration with 0% lower limit (-1) and 50% upper limit (+1).
The observed responses were yield (Y1), nata thickness (Y2), and water content (Y3). Optimal Randomized Design on the manufacture of nata de coconut milk can be seen in Table 1 and 2
Table 1. Independent Variables and Levels in Randomized Optimal Design Independent
Variable
Level
-1 -0.660 -0.320 0 +0.240 +0.490 +0.740 +1 Whey
Concentration (%)(X)
0 8.5 17 25 31 37.25 43.5 50
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Table 2. Randomized Optimal DesignStd Run Space Type
Factor Respons
X Y1 Rendemen (%b/v)
Y2 Thickness (cm)
Y3 Moisture Content (%)
1 9 Edge 0.00 2 12 Center 0.00 3 6 Vertex 0.00 4 11 Edge 8.50 5 2 Vertex 17.00 6 3 Vertex 25.00 7 5 Center 25.00 8 10 Edge 25.00 9 7 Vertex 31.00 10 13 Vertex 37.25 11 1 Center 43.50 12 4 Edge 50.00 13 8 edge 50.00 Research Stages
Nata Making
The process of making Nata in this study refers to the research conducted by Setiaji, et al (2010). The first thing to do is to mix skim coconut milk and whey using 13 treatment variations that have been designed in DX10 software which will be used as a substrate. Then the substrate is heated to boiling, with added sugar as much as 5%, Ammonium Sulfate as much as 0.5%, and Acetic Acid. The addition of Acetic Acid is done until the pH of the media reaches between 4-5 for optimum growth of starter bacteria. Then the solution was poured into a tray in a hot state and immediately covered with tied paper. The solution was left to cool for one night, then inoculated with 10% (v/v) Acetobacter xylinum starter. Fermentation was carried out for 7 days. The resulting nata sheets were cleaned from mucus by boiling for 15 minutes to kill the bacteria and then tested.
Yield, (AOAC, 1979)
Nata yield was measured using the gravimetric method and expressed in weight per volume of liquid medium used.
Thickness Measurement
Measurements were taken with a caliper and the thickness values obtained were an average of the measurements from five different places.
Water Content Analysis (AOAC, 1995)
Analysis of water content is done by gravimetric method. The principle of this method is based on the evaporation of water in the nata by heating, then weighed until the weight is constant. The weight reduction that occurs is the water content contained in the nata.
Metods
This study was conducted using Response Surface Methodology (RSM) Randomized Optimal design using Design Expert 10 (DX10) software. The independent variable used was X1 = Whey concentration with 0% lower limit (-1) and 50% upper limit (+1). The observed responses were yield (Y1), nata thickness (Y2), and moisture content (Y3).
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Prosedur AnalisisData analysis was conducted using DX10 software with Randomized Optimal design including model selection, analysis of variance, model equation, response surface curve and optimal concentration.
RESULTS AND DISCUSSION 1. Response Variable Value
Data analysis was conducted using DX10 software with Randomized Optimal design including model selection, analysis of variance, model equation, response surface curve and optimal concentration.
Tabel 3. Value of Variable Respons
Std Run Space Type
Faktor Respon
X Whey
Y1
Rendemen (%b/v)
Y2
Ketebalan (cm) Y3
Kadar Air (%)
1 9 Edge 0.00 9.50 0.00 84.30
2 12 Center 0.00 15.50 0.00 82.70
3 6 Vertex 0.00 18.00 0.00 79.40
4 11 Edge 8.50 24.50 0.78 87.00
5 2 Vertex 17.00 25.50 0.86 85.50
6 3 Vertex 25.00 27.50 1.24 87.60
7 5 Center 25.00 30.00 1.46 85.90
8 10 Edge 25.00 31.00 0.84 80.90
9 7 Vertex 31.00 25.00 1.10 89.00
10 13 Vertex 37.25 23.50 0.78 89.50
11 1 Center 43.50 29.00 1.14 89.20
12 4 Edge 50.00 30.00 1.14 89.00
13 8 edge 50.00 30.50 1.18 89.70
The measurement results of whey addition in Table 3 to the total yield response values produced were around 9.5-31%. The highest yield value was 31% in treatment 8 with 25%
whey addition. And the lowest yield value was 9.5% in treatment 1 with 0% whey addition. This indicates that the higher the addition of whey, the higher the yield value. According to Aulia et al. (2020), the longer the fermentation duration, the higher the yield value. The increase in yield is influenced by the thickness of the nata. The amount of yield produced is directly proportional to the thickness of the nata. The thicker the cellulose layer of nata, the higher the yield.
Increasing the activity of Acetobacter xylinum bacteria and providing the right nutrients will produce denser cellulose resulting in higher and thicker yields (Aini & Nur, 2019).
2. Response Surface Analysis
Table 4 shows the results of finding the three responses based on the observations from the regression equation. Based on the coefficient of determination (R2) Table, the higher the coefficient of determination, the more variables can be explained by a set of independent variables at the same time.
The responses of yield (Y1), nata thickness (Y2), and moisture content (Y3) can be seen in the following equation:
Y1 = 27.83 – 3.54 A – 5.48 A2 + 11.63 A3 Y2 = 1.10 – 0.083 A – 0.52 A2 + 0,67 A3 Y3 = 86.27 + 3.56 A
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Table 4. Response Surface MethodologyResponse Equation R2 F-
Value
P-Value (p<0,05)
Lack of fit
(p<0,05) Rendemen 27.83 – 3.54 A – 5.48 A2 + 11.63 A3 0.8567 17.94 0.0004 0.82 Ketebalan 1.10 – 0.083 A – 0.52 A2 + 0.67 A3 0.8922 24.73 0.0001 0.80
Kadar Air 86.27 + 3.56 A 0.5723 14.72 0.0028 0.53
Note: A = Whey
Based on Table 4, the R2 value for yield is close to 1.0, which is 0.8567, indicating that 0.8567 of the yield response variable is influenced by the addition of Whey. The f-value for yield is 17.94 and is significant because there is only a 0.0004 chance an f-value is likely to cause interference. Similarly, the p-value of 0.0004 is significant because Prob > F is less than 0.05. The lack of fit value obtained for Yield is greater than 0.05 which is 0.82.
Figure 1 Normal Plot of Residual Yield Respond
The R2 value for thickness is close to 1.0 at 0.8922 which indicates that 0.892 of the thickness response variable is affected by the addition of whey. The F-value for thickness is 24.73 and is significant because there is only a 0.0001 chance that an f-value is likely to cause a disturbance. Similarly, the p-value of 0.0001 is significant because Prob > F is less than 0.05.
The lack of fit value obtained for thickness is greater than 0.05 which is 0.80.
Figure. 2 Normal Plot of Residual Thickness respond
The R2 value for moisture content is 0.5723 which indicates that 0.5723 of the response variable moisture content is affected by the addition of Whey. The Fvalue for moisture content
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is 14.72 and is significant because there is only a 0.2008 chance that an f-value is likely to cause interference. Similarly, the p-value of 0.0028 is significant because Prob > F is less than 0.05. The lack of fit value obtained for water content is greater than 0.05 which is 0.53.Figure 3. Normal Plot Of Residual Water Content Respond
Yield, thickness, and moisture content are not significant based on the Lack of Fit results because the p value is greater than 0.05. This indicates that the lack of fit is not significant due to the suitability of the response data with the model. In accordance with the research of Sitompul et al. (2020), this shows that the lack of fit condition is not significant if the p value is> 0.05, so the model can be said to be acceptable because it shows the suitability of the data response with the model used in this study.
3. Yield Response Analysis
According to the observations made, the amount of Acetobacter xylinum bacterial starter, sucrose, Ammonium Sulfate, and acetic acid added in making nata de skim coconut milk affects the yield produced. The addition of whey affects the yield because the availability of nutrients in the media solution has a considerable influence on the development of Acetoacter xylinum starter. The results of the Analysis of Variance (ANOVA) of yield can be seen in Table 5.
Tabel 5. ANOVA Model Respon of Yield
Source F - Value P - Value
Model 17.94 0.0004
A-Whey 0.76 0.4066
A2 8.65 0.0164
A3 6.68 0.0294
Error
Lack of Fit 0.82 0.5628
The ANOVA analysis showed the results of the cubic model. And the addition of whey affects the yield of nata de skim coconut milk where the f-value is greater than the p-value with a 95% probability level. The f-value for the yield model is 17.94 and the f-value for Whey is 0.76. Similarly, the p-value of 0.0004 is significant because Prob > F is less than 0.05. The lack of fit value obtained for the pendemen response is greater than 0.05, namely 0.82, so the model can be said to be acceptable because there is a fit of the yield response data with the model.
4. Thickness Response Analysis
According to the observations made, the amount of Acetobacter xylinum bacterial starter, sucrose, ammonium sulphate, and acetic acid added in the preparation of Nata de skim
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coconut milk affects the thickness produced. The addition of whey affects the thickness because the availability of nutrients in the media solution has a considerable influence on the development of Acetoacter xylinum starter. The results of Analysis of Variance (ANOVA) of thickness response can be seen in Table 5.Tabel 5. ANOVA Model Respon of Thickness
Source F-Value P-Value
Model 24.83 0.0001
A-Whey 0.095 0.7647
A2 17.70 0.0023
A3 5.01 0.0520
Error
Lack of Fit 0.80 0.5731
The ANOVA analysis results show the cubic model. And the addition of whey affects the thickness of nata de skim coconut milk where the f-value is greater than the p-value with a 95% probability level. The f-value for the thickness model is 24.83. Similarly, the p-value is 0.0004, which is significant because Prob > F is less than 0.05. The lack of fit value obtained for the thickness response is greater than 0.05, namely 0.80, so the model can be said to be acceptable because there is a match between the thickness response data and the model.
5. Moisture Content Response Analysis
According to the observations made, the amount of Acetobacter xyilinum bacterial starter, sucrose, ammonium sulfate, and acetic acid added in the preparation of nata de skim coconut milk affects the water content produced. The addition of whey affects the water content because the availability of nutrients in the media solution has a considerable influence on the development of Acetoacter xylinum starter. The results of the Analysis of Variance (ANOVA) of the moisture content response can be seen in Table 6.
Tabel 6. ANOVA Model Respon of Water Content
Source F-Value P-Value
Model 14.72 0.0028
A-Whey 14.72 0.0028
Error
Lack of Fit 0.53 0.7713
The ANOVA analysis showed the results of a linear model. And the addition of whey affects the water content of nata de skim coconut milk where the f-value is greater than the p- value with a 95% probability level. The f-value for the water content model is 14.72 and the f- value for Whey is 14.72. Similarly, the p-value of 0.0028 is significant because Prob > F is less than 0.05. The lack of fit value obtained for yield is greater than 0.05, namely 0.53, so the model can be said to be acceptable because there is a match between the water content response data and the model.
6. Optimization Analysis of Whey Addition on the Response of Yield, Thickness, and Moisture Content
The optimization process uses the help of the design expert application, the process is carried out to obtain a response that is in accordance with the desirability. Optimization is done after obtaining a mathematical model of the response, the purpose of optimization is to minimize the required effort or operation and maximize the desired results (Nurmiah et al., 2013; Sitompul et al., 2020). Desirability value is the optimization target value that can be obtained. It ranges from 0 to 1 (Wahyudi, 2012; Surahman, Cahyadi & Stania, 2019) Based on
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the results of the yield, thickness, and water content tests, the longer the fermentation time, the higher the % yield, thickness, and water content of nata de skim coconut milk. This is related to the microbial growth curve. The 7-day fermentation time is the exponential phase.Microbes multiply in this phase to create ideal products (Ramayanti & Giasmara, 2017;
Sulistiyana, 2020).
Tabel 7. Solution of Process Optimation Prediction
Variabel Respons Desirability
Whey Yield Thickness Water Content
(%) (%) (cm) (%)
49.066 29.714 1.135 89.700 0.892
The optimum concentration of whey that is appropriate for making coconut milk nata de skim is 49.07% with the optimization response to the yield of coconut milk nata de skim shown in Table 6. The ideal coconut milk nata de skim yield value is 29.71%. RSM can achieve the maximum result of y = 29.71 with a composite desirability value of d = 0.89 by using the optimal solution. The optimum concentration of whey that is appropriate for the manufacture of nata de skim coconut milk is 49.066% with the optimum thickness level in nata de skim coconut milk is 1.135 cm. According to SNI 01-4317-1996, the optimal number is 1-1.5 cm. Then the optimum value is appropriate. RSM can give the maximum thickness y = 1.135 with the composite desirability value d = 0.89 using the best solution. The optimum concentration of whey that is appropriate for making coconut milk nata de skim is 49.066% with the optimum water content in coconut milk nata de skim is 89.7%. The optimum figure is in accordance with the Puslitbang water content standard for nata which is ≥ 80%. The best RSM solution can provide a maximum yield of y = 89.7 with a composite desirability value of d = 0.89. Because the desirability value is close to 1, it means that the nata de skim coconut milk formula can achieve the optimal formula according to the desired response variable.
CONCLUSION
The use of whey concentration influences the characteristics of nata de skim coconut milk with f-value for the yield model is 17.94 and f-value for Whey 0.76. Likewise, the p-value is 0.0004, so it is declared significant because Prob> F is less than 0.05. F-value for thickness model is 24.83 and p-value is 0.0004. The f-value for the moisture content model is 14.72 and the f-value for Whey 14.72. Similarly, the p-value is 0.0028, which is significant because Prob
> F is less than 0.05. The optimum concentration of whey that is appropriate for the manufacture of coconut milk nata de skim 49.066% with a desirability value of 0.892, the optimum yield level in coconut milk nata de skim 29.7139%, the optimum thickness level in coconut milk nata de skim 1.13453 cm, and the optimum water content in coconut milk nata de skim 89.7%.
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