Optimization of saccharification conditions of prebiotic extracted jackfruit seeds

Transcription

1 Paper Code: fb005 TIChE International Conference 0 November 0, 0 at Hatyai, Songkhla THAILAND Optimization of saccharification conditions of prebiotic extracted jackfruit seeds Sininart Chongkhong *, Bancha Lolharat, Abdullateef Doramae, Pakamas Chatpattananondh Department of Chemical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla, 90, Thailand * sininart.c@psu.ac.th Abstract In this work, response surface methodology (RSM) was used to determine the optimum saccharification condition in the hydrolysis steps for the ethanol production from prebiotic extracted jackfruit seeds. Three parameters, which were investigated, were gluco-amylase amount ( %w) temperatures (50 70 C) and time ( min). To apply the quadratic model, the two-level-three-factor array ( ) experiment was explained by using a central composite design (CCD). The determination coefficient, R value, for reducing sugar content in the hydrolyzed product was greater than For this statistical analysis, it showed that the factors effected on the reducing sugar content significantly. Base on response surface, the optimum condition for saccharification process was 0. %w gluco-amylase amount at the 50 C incubation temperature and 60 min. It could provide 5. g/l of the highest amount reducing sugar content in the hydrolyzed product. Keyword: Jackfruit seeds, Glucoamylase, Enzymatic Hydrolysis, Response surface methodology

2 TIChE International Conference 0 November 0, 0 at Hatyai, Songkhla THAILAND. Introduction The commercial utilization of amylase enzyme is the hydrolysis of a starchy biomass as raw material for many industries. On a dry basis, agricultural products that compose mainly of starch, hydrolyzed to glucose, offer a good resource for fermentation processes []. The enzymatic hydrolysis of starchy materials can be used in the liquefaction and saccharification processes conventionally. The components of the prebiotic extracted jackfruit seeds are 5.0% starch, 4.99% crude proteins, 0.5% fat, 0.75% ash and 58.8% moisture []. Ethanol production from the prebiotic extracted jackfruit seeds, a starchy material, can be carried out by using enzymes in pretreatment and hydrolysis processes. The starch can be transformed into fermentable sugar by the liquefaction using alpha-amylase enzyme, and then by the saccharification using gluco-amylase enzyme in the hydrolysis process. After that the sugar is converted into ethanol using yeast in the fermentation process. Likewise, the non-reducing sugars at the tail end of the amylase and amylopectin molecules can be hydrolyzed into the reducing sugars by using the gluco-amylase in the saccharification [ 4]. The several starchy materials were investigated by using the gluco-amylase for the hydrolysis step [5]. The optimum operating condition of enzymatic hydrolysis of cassava waste using the glucoamylase was at ph 4.5, 60 C for 4 hrs [6]. The response surface methodology (RSM) has been increasingly used to optimize the ethanol production process [, 6-7]. RSM has been widely used to evaluate and understand the interactions between different physiological and nutritional parameters. This research is intended to determine the optimum conditions (incubation time, temperature and enzyme concentration) for saccharification process of prebiotic extracted jackfruit seeds by using RSM.. Materials and Methods.. Materials and Microorganisms Prebiotic extracted jackfruit seeds are obtained from SME-OTOP research group, Prince of Songkla University, Thailand. Alpha-amylase (Aspergillus cryzae) and Gluco-amylase (Aspergillus niger) were bought from the Sigma-Aldrich company... Pretreatment The crushed seeds, which were about mm particle size, were boiled at 85 C for 5 min. Then they were cooled down until it reached a room temperature.... Liquefaction process The 5 g of the seeds mixed with 5 ml water were poured in 50 ml screw-capped bottles with 0.7 %w Alpha-amylase. The liquefaction process was carried out at an initial ph 6.0, 80 C for 40 min in the oil both with shaking rate of 00 rpm.... Saccharification process The temperature of the liquefied product was lowered to 60 C. The saccharification process was investigated at C for min with %w glucoamylase by using RSM. The reactions were kept at ph 4.5 with the shaking rate of 00 rpm. The hydrolysates (saccharificated products) were separated by centrifuge at 5,000 rpm for 5 min to obtain the clear liquid product before reducing sugar content analysis... Analytical methods The reducing sugars were assayed in terms of glucose by DNS method using a double beam UV-Vis spectrophotometer (model HP 845) with UV-Visible Chem-Station software []..4. Experimental design and optimization Central composite design (CCD) was used to find the optimum reducing sugar concentrations in the hydrolyzed products. Time (, min), temperature (, C), and gluco-amylase amount (, %w) were chosen as the independent variables (Tables and ). The variables were coded according to Eq. (): i xi, xi i =,,,, k () x j where x i are the dimensionless coded level of variables, i are the actual value, x i are the average of the high and low level values and x are the high value minus the low value of that the variables. The significance of each variable influencing hydrolysis process was determined by Student s t test with 95% confidence levels. Table.. Variables in the experimental design. Variables Coded levels Time (min) Temperature ( C) Gluco-amylase (%w) j fb005-

3 Predicted Values (g/l) TIChE International Conference 0 November 0, 0 at Hatyai, Songkhla THAILAND Table.. The central composite design matrix employed for three independent variables (Actual values are given in Table ). Run no. x x x Reducing sugar concentration (Y, g/l) in the hydrolyzed product was a desirable output. To obtain optimum conditions, 7 experiments in Table were studied. A mathematic model for predicting the output yields by ANOVA, Eq. (), was created from the roles of parameters, their interactions and statistical analysis. Y 0 () Where Y is the predicted response;,, are the independent variables; b 0 is the offset term; b, b, b are the linear effects; b, b, b are the square effects; and b, b, b are the cross effects of the interaction terms. A correction of the polynomial model Eq. () can be verified with the determination coefficient (R ) and the F-test for the statistical significance.. Results and Discussion.. Response surface analysis for optimization of three factors The trials and results for central composite design are shown in Table. The response surface and contour curves were obtained by using Eq. (): Y () Table.. Experimental and predicted yields for reducing sugar Run no. Experimental Reducing sugar (g/l) Predictive Fig. shows a satisfactory correlation between experimental values and predictive values. As can be seen from the figure, the predicted data of the response from the empirical model agreed well with the observed ones in the range of the operating variables R = Experimental Values (g/l) Fig.. Parity plot for the distribution of experimental vs. predicted values of reducing sugar. The results from using Eq. () showed a high determination coefficient, R = 0.96, which implied that the model was a good fit with the experiments. It gave 96.% predicting efficiency. The adjusted R value corrects the R value for the sample size and for the number of terms. A high value of adjusted determination coefficient (adjusted R = 0.9) advocates for a high significance of the model. fb005-

4 TIChE International Conference 0 November 0, 0 at Hatyai, Songkhla THAILAND As illustrated in Tables 4 and 5, a P value of 0.05 for any factor in analysis of variance (ANOVA) indicates a significant effect of the corresponding factors on the response. The model F value of 0.50 and values of probability > F indicated that the model terms are significant Table.4. Coefficients, t-statistics and significance probability of the model. Term Coefficient Value Standard error t-value P-value Constant b Time b Temperature b Gluco-amylase b Time x time b Temperature x temperature b Gluco-amylase x gluco-amylase b Time x temperature b Temperature x gluco-amylase b Time x gluco-amylase b Table.5. ANOVA for the full quadratic model. Source of variation Sum of squares (SS) Degrees of freedom (DF) Mean squares (MS) F-value Probe > F Regression Residual LOF Error Pure Error Interactions among the factors Fig.. Response surface of temperature vs. time (the enzymatic hydrolysis of prebiotic extracted jackfruit seeds with 0.% glucoamylase). Effects of temperatures and time on the reducing sugar amount (hydrolysis yield) are shown in Fig.. The reducing sugar content was decreased with temperature ranging from 50 to 70 C as the content was increased with the increasing in time from 40 to 480 min. Fig.. Response surface of temperature vs. glucoamylase amount (the enzymatic hydrolysis for 60 min) The amount of gluco-amylase use in the process was varied from 0.05 to 0. %w for 40 to 480 min. It found that the highest reducing sugar content could be obtained at the centre point of this factors (0. %w gluco-amylase and 60 min). fb005-4

5 TIChE International Conference 0 November 0, 0 at Hatyai, Songkhla THAILAND Fig. 4. Response surface of temperatures vs. gluco-amylase amount (the enzymatic hydrolysis at 60 C) Fig. 4 shows the effects of temperatures and amylase amount on reducing sugar content at 60 C. The formation of sugar content was reduced when temperature was raised while the sugar content was increased with amylase amount from 0.05 to 0. %w. Further increase of amylase amount did not significantly increase the amount of reducing sugar. 4. Conclusions suitability for the hydrolysis of wheat starch. Process Biochem. 9 (00) [] G.L. Miller, Use of dinitrosalicyclic acid reagent for determination of reducing sugar, Anal. Chem. (959) [] B. Lolharat, S. Chongkhong, P. Chetpattananondh, Optimization of saccharification condition for the ethanol production from prebiotic extracted jackfruit seed. The 5 th PSU-UNS International Conference on Engineering and Technology (ICET), Prince of Songkla University, Faculty of Engineering, Phuket, May - (0). [4] H. Anto, U.B. Trivedi and K.C. Patel, Glucoamylase production by solid-state fermentation using rice flake manufacturing waste products as substrate, Bioresource Technol. 97 (0) (006) [5] Q. Wang,. Wang,. Wang, H. Ma, Glucoamylase production from food waste by Aspergillus niger under submerged fermentation. Process Biochem. 4 (008) [6] S. O'Brien, Y.-J. Wang, Susceptibility of annealed starches to hydrolysis by [alpha]-amylase and glucoamylase. Carbohyd. Polym. 7 (008) [7] S. Teerapatr, K. Lerdluk and S. La-aied, Approach of Cassava Waste Pretreatments for Fuel Ethanol Production in Thailand, Chulalongkorn J. Sci. Res. (006). [8] I.-L. Shih, C.-Y. Kuo, F.-C. Hsieh, S.-S. Kao, C. Hsieh, Use of surface response methodology to optimize culture conditions for iturin A production by Bacillus subtilis in solid-state fermentation, Journal of the Chinese Institute of Chemical Engineers 9 (008) [9] G.L. Miller, Use of dinitrosalicyclic acid reagent for determination of reducing sugar, Anal. Chem. (959) The response surface methodology (RSM) was successfully used to determine the optimum conditions for the hydrolysis of the prebiotic extracted jackfruit seeds. The saccharification process could increase the significantly reducing sugar concentration before operating in the next fermentation step for ethanol production. A quadratic model, established in terms of hydrolysis: temperature, time and gluco-amylase amount, was proved usefully to predict the yield of saccharification process. The recommended for hydrolysis condition was 0.% enzyme concentration at 50 C for 60 min. It provided 5. g/l reducing sugar content. 5. Acknowledgements The authors gratefully acknowledge the financial support from the Graduate School of Prince of Songkla University, DoE (Discipline of Excellent chemical engineering) and NRCT 0. References [] S.K. Soni, A. Kaur, J.K. Gupta, A solid state fermentation based bacterial [alpha]-amylase and fungal glucoamylase system and its fb005-5