Optimization of Tannin Extraction from Areca Nuts (Areca Cateshu Linn) Using Ethanol Solvent
Jakfar1*, Azwar2
1,2Chemical Engineering Department, Faculty of Engineering, University of Syiah Kuala, Banda Aceh, Indonesia
*Corresponding email: jakfar@unsyiah.ac.id
Received: December 14, 2022 Accepted: Januari 14, 2023
Abstract
Areca nut (Areca catesyu Linn) contains chemical compounds that are beneficial to health, namely tannins, alkaloids, fats, essential oils, water, and a little sugar. The tannin content in areca nuts reaches 17%.
Separation of tannins in areca nuts is done by an extraction method using ethanol as a solvent. This research focuses on optimizing the effects of areca nut particle size (40–120 mesh) and ethanol solvent concentration (20–80%) on the tannin yield (%) using Design Expert 13, Response Surface Methodology (RSM), and Central Composite Design (CCD). The results showed that the influence of the two variables and their interactions was very significant. Optimal conditions were obtained with a particle size of 120 mesh, a 50%
ethanol solvent concentration, a 16.7% pectin content, and a desirability of 0.92.
Keywords: areca nut, tannin, extraction, response surface methodology, central composite design
Abstrak
Buah pinang (Areca catesyu Linn) mengandung senyawa kimia yang bermanfaat bagi kesehatan yaitu tanin, alkaloid, lemak, minyak atsiri, air, dan sedikit gula. Kandungan tanin pada buah pinang mencapai 17%.
Pemisahan tanin pada buah pinang dilakukan dengan metode ekstraksi menggunakan pelarut etanol.
Penelitian ini berfokus pada optimalisasi pengaruh ukuran partikel pinang (40–120 mesh) dan konsentrasi pelarut etanol (20–80%) terhadap rendemen tanin (%) menggunakan Design Expert 13, Response Surface Methodology (RSM), dan Central Composite Desain (CCD). Hasil penelitian menunjukkan bahwa pengaruh kedua variabel dan interaksinya sangat signifikan. Kondisi optimal diperoleh dengan ukuran partikel 120 mesh, konsentrasi pelarut etanol 50%, kandungan pektin 16,7%, dan desirabilitas 0,92.
Kata kunci: pinang, tanin, ekstraksi, response surface methodology, central composite design
1. Introduction
Areca nuts, including tropical plants, represent industrial plants that have great economic value for developing countries and grow on the continents of Asia, Africa, and latent America [1]. Traditionally, Areca Nut (AN) is believed to have a number of medicinal properties ranging from anti-worm and astringent to aphrodisiac, digestive improvement, and psychomotor stimulant [3]. Anti-migrant [4]. anti- inflammatory, analgesic, and antioxidant, as well as antiviral [5]. contains flavonoids, is anti-bacterial, prevents hypertension and hyperglycemia, and is bioactive [6]. inhibits free radicals (strong reducing power) [6]. Flavonoids, polyphenols, alkaloids, tannins, terpenes, saponins, and essential oils have been shown to have antimicrobial, antifungal, anti-inflammatory, antiparasitic, antiviral, antitumor and increased activity. Other healthcare professionals, leading to diverse applications in disease management [7].
Dried betel nut is also used as an industrial and pharmaceutical raw material. In industry, areca nut is used as a cosmetic mixture, a candy mixture, as well as a natural dye in fabrics and cotton. Areca nut contains antioxidants and antibacterial substances, so it is widely used in the pharmaceutical field [8]. Its use is as a mixture for the manufacture of medicines, such as dysentery drugs, worm medicine, mouthwash, and others [9]. In addition to its many benefits, areca nut is also dangerous if eaten directly because it contains substances that trigger cancer if the concentration is excessive or accumulates [8].
Besides being used domestically, areca nut is also an export commodity that also increases the country's foreign exchange. The areca nut is exported to many countries. The national export value of this commodity will be $357 million in 2021.Indonesia controls the export of areca nuts globally. In 2021, more than 60 percent of the world's betel nut exports will come from Indonesia. The second-largest betel nut exporting country is a friendly country that is still in Southeast Asia, namely Myanmar. Sri Lanka came in third place. Each country's areca nut export value is US$ 139 million and US$ 46 million, respectively. The main destination country for betel nut exports nationally is Thailand. The value of exports to the white elephant country reached $357 million. More than 50 percent of the areca nut is exported to this neighboring
country. The next largest betel nut export destinations are Iran and India. In 2021, the value is greater than US$ 50 million and less than US$ 40 million [8, 10].
This research was conducted on areca nut in Aceh, where the composition of the constituent compounds differs depending on the type of betel nut, the location where it grows, and several other factors such as the age of the betel nut, the climate where it grows, and the height of the soil also vary, because areca nut is bought randomly in several markets in the city of Banda Aceh, Indonesia. The purpose of this study was to study the effect of particle size (mesh) and ethanol solvent concentration (%) on the yield of tannins obtained (%) and focus on optimization using the Design Expert [13], Response Surface Methodology (RSM), and Central Composite Design (CCD) randomly [11].
2. Material and Methods Materials used
The materials used are areca nut, aquadest, concentrated sulfuric acid (Merck), 0.5 M FeCl3, indigocarmin (C16H8N2NO2O8S2), concentrated KMnO4, concentrated oxalic acid (H2C2O.2H2O, and 96%
ethanol).
Fixed variable
The fixed variable used is 30 grams of areca nut, 60oC extraction temperature with the use of ethanol.
And the extraction time is 2 hours, and the ratio of areca nut and ethanol solvent is 1:5.
Variables change
This study varied the particle size of areca nut from 40-120 (mesh), and ethanol concentration 20-80 (%), and the resulting tannin response variable (%). The experimental design followed Design Expert 13, RSM, CCD [12][13]. The experimental design is as in Table 1 and Process Flow in Figure 1 [14][15].
Research Procedure
The betel nut is peeled and the seeds are taken, cleaned and cut into pieces, then dried in an oven for 30 minutes at a temperature of 40-50 oC to remove the free moisture content so that it is easily crushed. The betel nut is then ground in a ball mill for 20 minutes and sieved and separated according to their respective sizes.
Extraction process
Samples were weighed at each size of 30 grams, then put into a 500 ml glass beaker, then 250 ml of ethanol was added, with variations of 20 - 80% according to the experimental design. Then heated with a water bath (water bath) while stirring. The extraction temperature is 60oC, and the extraction time is 2 hours.
The extraction results are then filtered. Then the tannins are dried in an oven at a temperature of 80-85oC for qualitative tests and tannin levels.
Preparation of reagent solutions for analysis
Preparation of indigocarmin solution by dissolving 6 grams of indigocarmin into 500 ml of distilled water and then offering. After being cooled, distilled water was added up to one liter and then filtered [16].
0.1 N. KMnO4 solution
KMnO4 added 3.2 grams then added with distilled water to 1 liter. Simmer for 10-15 minutes, then strain and strain. The solution was kept overnight. Standard KMnO4 solutions need to be standardized before use [16].
Standardization of KMnO4 solution
Weighed 0.63 grams of oxalic acid crystals and dissolved in 100 ml of distilled water, then 25 ml of oxalate solution was taken, added 5 ml of H2SO4 and then seen until the temperature was 70 oC.
Furthermore, in the heat it is titrated with standard KMnO4 solution until the purple color and the permanganate solution does not disappear, and the titration volume is recorded. replicate three times.
Reactions that occur:
2 MnSO4 + 5 H2C2O4 + 3 H2SO4 → 2 MnSO4 + 10 CO2 + K2SO4 + 8 H2O The normality of the standard solution of KMnO4 is calculated using the formula:
𝐾𝑀𝑛𝑂4 = 𝑊(𝑚𝑔)/𝐵𝑀 𝑥 10 𝑥 2 𝑥 25
𝑉 (𝑚𝑙) (1)
Quality test
Tannin filtrate is added from 0.5 M FeCl3 so that the solution will change color to blue-black. Then
Determine the tannin content
The determination of tannin content is carried out in the following way [16]. Weigh 1.5 grams of tannin by putting it into a 100-ml beaker and then adding 50 ml of water. Then heat at a temperature of 40–
60 oC for 30 minutes, then cool. After cooling, the solution was filtered into a 250-ml volumetric flask, and water was added to the mark. The solution was measured in 25 ml, placed in an Erlenmeyer flask, and 20 ml of indigocarmin solution was added. The solution was then titrated with 0.1 N KMnO4 solution, 1 ml of KMnO4 being added at a time until the blue color changed to yellow, and the ocean turned yellow. For example, the titration volume can be 1 ml. The blank is made by taking 20 ml of indigocarmin solution into an Erlenmeyer, adding water, and then titrating it; for example, the titration volume is B ml. Tannin content can be calculated using the following formula:
% 𝑡𝑎𝑛𝑖𝑛 = 𝐹𝑃 (𝐴 − 𝐵 ) 𝑥 𝑁 𝑥 0.00416
𝑠𝑎𝑚𝑝𝑙𝑒 𝑤𝑒𝑖𝑔ℎ𝑡 (2)
Information:
A = tannin titration volume (ml) B = blank titration volume (ml) F = dilution factor
N = normality of KMnO4
1 ml of KMnO4 is equivalent to 0.00416 grams of tannins
Fig. 1. Research process flowchart
Process flowchart
The flow of the tannin making process and optimization is briefly and clearly illustrated in Figure 1 which illustrates the scheme of the tannin making process starting from betel nuts dried in an oven then using a ball mill and then separated to get the appropriate size according to the desired size. control variables were determined through the sieving process, then extraction. using various solvents of ethanol (20-80%) then recording and drying using an oven to obtain tannins and so on, qualitative and quantitative analysis was carried out, namely the yield of tannins (%). The experimental design was carried out according to design experts 13, RSM, CCD as shown in Table 1.
Table 1. Design and analysis of experiments for optimization of Tannin Extraction
Factor 1 Factor 2 Variable Response
Run A:X1 (Mesh) B:X2 (%) Y (%)
Mesh % %
1 120 50 16.7
2 40 20 5.7
3 40 50 15.7
4 40 80 16
5 200 50 18
6 200 20 7
7 120 50 16.7
8 120 80 17.3
9 120 50 16.7
10 120 50 16.7
11 200 80 20
12 120 50 16.7
13 120 20 6.7
Experimental design studies the effect of individual variables and interactions using multi-regression polynomial models.
𝑌 = 𝛽𝑜 + ∑𝑘𝑖=1𝛽𝑜𝑥𝑖 ∑𝑘𝑖=1𝛽𝑜 𝑥𝑖2 + ∑𝑘𝑖=1∑𝑘𝑗=1𝛽𝑜𝑥𝑖𝑥𝑗 + 𝜀 (3)
Where Y is predicted response, xi, xj,…,xk are the input variables affecting the response Y, xi2, xj2,…xk2 are the square effects, xixj, xixk and xjxk are the interaction effects, βo is intercept term, βii (i=
1,2,...,k) is the square effect, βij (i=1,2,…k; j= 1,2,…,k is the interaction effect and ε is random error.
3. Results and Discussion
Central Composite Design
The Central Composite method was analyzed and the results of the analysis of variance (ANOVA) from regression coefficient are presented in Table 2.
Table 2. Analysis of variance (ANOVA) for Response Surface Quadratic Model
Source Sum of Squares df Mean Square F-value p-value
Model 272.20 5 54.44 932.27 < 0.0001
A-Average Size of Areca Seed Particles (Mesh) 9.63 1 9.63 164.85 < 0.0001 B-Ethanol Solvent Concentration (%) 191.53 1 191.53 3279.99 < 0.0001
AB 1.82 1 1.82 31.21 0.0008
A² 0.0725 1 0.0725 1.24 0.3018
B² 60.70 1 60.70 1039.43 < 0.0001
Residual 0.4088 7 0.0584
Analysis of variance (ANOVA) response (tannin yield, %) indicate that effect of individual factors, interaction factor for degree of confidence ≥ 95 %. The RSM model is selected quadratic model, R2 = 0.98, and the model is very significant.
Fitting model
Analysis of variance (ANOVA) were employed to evaluate the effect of individual factors, interaction factors, and multiple regression analysis in Design Expert 13, CCD in the RSM was used. The model equation which are used to predict the optimum degree of tannin yield were determined by multiple regression analysis using following equation.
Based on the eq (4) it showed that the factor of each variables (X1= Size of Areca Seed Particles (mesh), X2 = Ethanol Solvent Concentration (%), X1X2 = interaction of X1 and X2 is the effect of the interaction of these two variables have a positive effect on the tannin yield, the positive value represents an effect of optimization.
Table 3. Fit Summary of Tannin Yield Model
Source Sequential p-value Adjusted R² Predicted R²
Linear 0.0012 0.6855 0.4820
2FI 0.6390 0.6595 -0.0043
Quadratic < 0.0001 0.9974 0.9847 Suggested
Cubic < 0.0001 1.0000 0.9998 Aliased
Table 3 summarizes the suitability value of the tannin yield model obtained in equation (4), namely the effect of areca seed particle size and ethanol solvent concentration and their interaction quadratic with a p-value <0.0001, adjusted R2 = 0.997 and predicted R2 = 0.985, the correlation value is very high and shows very accurate predictions.
Table 4. Response Tannin Yield (%)
Source Sum of Squares df Mean Square F-value p-value
Mean vs Total 2774.00 1 2774.00
Linear vs Mean 201.16 2 100.58 14.08 0.0012
2FI vs Linear 1.82 1 1.82 0.2356 0.6390
Quadratic vs 2FI 69.22 2 34.61 592.66 < 0.0001 Suggested
Cubic vs Quadratic 0.4083 2 0.2042 2368.33 < 0.0001 Aliased
Residual 0.0004 5 0.0001
Total 3046.61 13 234.35
Table 4 shows the response value of the tannin yield model and the model proposed by the RSM CCD, namely quadratic regression with an F-value of 592.66 and a p-value <0.0001, this value is very accurate according to Table 3 and equation (4).
(a) (b)
Fig. 2. (a) Relationship correlation between externally studentized and normal
% probability for Tannin produced (b) Correlation between actual and predicted data for tannin obtained
Figure 2 (a) Showing the Relationship between External Students and Normal % Probability of the tannins produced are purchased at the time of purchase (4) namely the effect of areca seed particle size and ethanol solvent concentration and their quadratic interaction with p-value < 0.0001, Adjusted R2 = 0.997 and Predicted R2 = 0.985, the correlation value is very high and the prediction is very accurate. Percentage of Normal and Externally Educated The probability is zero. Figure 2 (b) Correlation between the actual value of the research results and the predicted value in equation (4) with a correlation value of R2 = 0.997.
This shows that the deviation is very small and the prediction is very accurate.
Fig. 3. Contour response surface plots of average size of areca seed particles (mesh) and ethanol solvent concentration(%) on tannin yield (%) and desirability
Figure 3 shows the contour response surface plot of the average size of areca nut particles (mesh) and ethanol solvent concentration (%) at the optimization value of 17% tannin yield and 0.92 desirability obtained on sales (4), namely the effect of areca nut particle size and concentration ethanol interaction and its interactions quadratic with a p-value <0.0001, adjusted R2 = 0.99 and Predicted R2 = 0.99, the correlation value is very high.
Fig. 4: 3D response surface plots of average size of areca seed particles (mesh) and ethanol solvent concentration(%) on tannin yield (%) and desirability
Figure 4 depicts a 3D response surface plot of the average size of areca seed particles (mesh) and ethanol solvent concentration (%) at a tannin yield (%) of 17% and a desire of 0.92 obtained at the time of purchase (4), namely the effect of areca seed particle size and concentration of ethanol solvent and its interactions squared with a p-value <0.0001, adjusted R2 = 0.99 and Predicted R2 = 0.99, the correlation values are very high and the deviations are very small.
Fig. 5. Corelation deviation from reference point plots of average size of areca seed particles (mesh) and ethanol solvent concentration (%) on tannin yield (%) and desirability
Figure 5 shows deviations from reference points and desirability plots. The desirability value is 0.92 according to equation (4), namely the effect of areca seed particle size and the concentration of ethanol solvent, and their interaction is quadratic with a p-value <0.0001, adjusted R2 = 0.99, and predicted R2 = 0.99, making the correlation value very high and the deviation very small (zero). The results showed that the effect of areca seed particle size, ethanol dissolution concentration, and their interaction on the tannin yield obtained was very significant. The correlation between the actual and predicted values shows a value very close to a 99% correlation, and the prediction deviation is close to zero. The optimization value of the RSM CCD test results from the study of all independent variables and response variables showed a desirability value of 0.92. This value is very accurate because the combined value of all the variables involved and the error have been calculated (p-value < 0.5).
4. Conclusion
The areca nut is a type of industrial plant that grows on the continents of Asia, Africa, and America.
This plant has significant economic value for developing countries. Areca nut has numerous health benefits, including aphrodisiac, digestive aid, anti-worm, astringent, anti-migrant, antiviral, analgesic, anti- inflammatory, and antioxidant properties. Areca nuts are also able to lower blood pressure and glucose levels, inhibit free radicals, and are bioactive. The purpose of this study was to study the effect of particle size (mesh) and ethanol solvent concentration (%) on the yield of tannins obtained (%) with different compositions of the constituent compounds, such as location of growth, age of the areca nut, climate where it grows, and height from the surface of the sea. The results showed that the influence of the two variables and their interactions was very significant. The correlation value between the actual and predicted values reached 99% (R2 = 0.99, p-value <0.0001). Optimal conditions were obtained for particle size of 120 mesh, 50% ethanol solvent concentration, 17% tannin content, and 0.92 desirability.
5. Abbreviations
% Percentage
A, X1 Average Size of Areca Seed Particles (Mesh) B, X2 Ethanol Solvent Concentration (%)
X1X2 Interaction variable Y Variable Response Df Degree of freedom
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