Indian Journal of Experimental Biology Vol. 51, November 2013, pp. 935-943 Statistical media and process optimization for biotransformation of rice bran to using Pediococcus acidilactici Baljinder Kaur* & Debkumar Chakraborty Department of Biotechnology, Punjabi University, Patiala 147 002, India Received 7 December 2012; revised 9 March 2013 An isolate of P. acidilactici capable of producing from rice bran was isolated from a milk product. Response Surface Methodology was employed for statistical media and process optimization for production of bio. Statistical medium optimization was done in two steps involving Placket Burman Design and Central Composite Response Designs. The RSM optimized production medium consisted of 15% (w/v) rice bran, 0.5% (w/v) peptone, 0.1% (w/v) ammonium nitrate, 0.005% (w/v) ferulic acid, 0.005% (w/v) magnesium sulphate, and 0.1% (v/v) tween-80, ph 5.6, at a temperature of 37 C under shaking conditions at 180 rpm. 1.269 g/l was obtained within 24 h of incubation in optimized culture medium. This is the first report indicating such a high yield obtained during biotransformation of ferulic acid to using a Pediococcal isolate. Keywords: Pediococcus acidilactici, RSM, Rice bran, Statistical optimization, Vanillin Vanillin (4-hydroxy-3-methoxybenzaldehyde) is one of the most extensively used flavour compound in food industry. It has several applications in chemical and pharmaceutical industry also 1. Natural is obtained from vanilla beans but, it is very expensive as it has very limited availability. Annual world consumption of is more than 12,000 tons, which is mostly fulfilled by synthetic 2. However, according to European legislation chemically synthesized is not safe for human consumption 3. So, alternative routes of producing bio are urgently required which are safe to use and cheap to process. Common agricultural waste residues such as cereal bran, rice bran, sugar beet pulp, and wheat straw are rich sources of ferulic acid (FA), which is an important precursor of microbially synthesized and can be exploited as raw material for transformation to by microorganisms 4-6. Other substrates involving phenolic stibenes 7, lignin 8, isoeugenol 9, eugenol 10, vanillic acid 11, aromatic amino acids 12, biomass slurry fuel 13, rice bran oil 14 and coconut husk 15 were also investigated and implemented as precursor for production using microbial transformation. *Correspondent author Telephone: +91 175 3046262 Fax. +91 175 3046262, E-mail: baljinderbt@hotmail.com As an important subject in the statistical design of experiments, Response Surface Methodology is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize the response by using a sequence of designed experiments which was introduced by Box and Wilson in 1951. It is used for designing, formulating, developing, and analyzing new scientific studies and products. RSM finds its applications in improving and analyzing biological, clinical, food and industrial processes 16. In statistics, RSM explores the relationships between several explanatory variables and one or more response variables. This study aims to produce from rice bran using Pediococcus acidilactici isolate BD16. It was employed for statistical optimization of medium components for production of bio. Statistical medium optimization was done in two steps involving Placket Burman Design and Central Composite Response Designs. Materials and Methods Microorganism and culture conditions P. acidilactici isolate BD16 was revived in MRS broth under shaking conditions at 37 C and 180 rpm. After two sub-culturing, 1% inoculum was transferred into 250 ml flasks containing 50 ml of MRS medium and then cultivated overnight. All batch bioconversions
936 INDIAN J EXP BIOL, NOVEMBER 2013 were performed in 50 ml of bioconversion medium composed of different concentration of rice bran, ferulic acid, peptone and ammonium nitrate at 37 C under shaking at 180 rpm for 24 h. Vanillin estimation using TBA reagent Biotransformation media (2 ml) was centrifuged at 8000 rpm for 5 min to remove bran partials. Cell free supernatant (500 µl) was diluted with 500 µl of 70 mm phosphate buffer (ph 7). It was acidified with 5 ml of 24% HCl and 2 ml of 1% thiobarbituric acid. It was heated at 55 C in a water bath for 10 min and kept at room temperature for 20 min. Absorbance was read at 434 nm using spectrophotometer model UV-VIS spectrophotometer (Thermoscientific Genesis 1 model U10) 17. Vanillin estimation using HPLC and ESI Cultured media was centrifuged to remove bran partials. Supernatant was acidified to ph 2 using 6 N HCl. Phenolic compounds were extracted thrice with equal volume of ethyl acetate. Vanillin and other phenolics were estimated by HPLC 18. Phenolics were also detected by UV scans from 220 to 380 nm using a UV detector and by ESI in the mass range from 100 to 300. Ferulic acid,, vanillic acid, 4-ethyl phenol and vanillyl alcohol were used as standards. Preliminary screening of response variables using Placket-Burman design The Plackett-Burman design was applied for preliminary screening of process variables viz. ammonium nitrate, ferulic acid, magnesium sulphate, manganese sulphate, peptone, di-potassium hydrogen phosphate, rice bran, sodium acetate, yeast extract, ph and temperature for their significance in production. The effects of 11 variables were considered in 12 experimental Table 1 Plackett Burman design matrix sets (Table 1). The results were analyzed using design expert 8.0.7.1 software and analysis of variance (ANOVA). Confirmatory experiments were done in triplicates and by taking mean of all the three responses. Values of production were expressed in g/l of the medium. The PB model equation is summarized in Eq. 1 as, Amount of = 155.30 + 114.73 A + 65.71 B + 67.48 C + (-75.63) E... 1 where, A-rice bran, B-ferulic acid, C-peptone and E-magnesium sulphate. Media optimization using CCRD design A set of 30 experimental designs were generated in CCRD to point out the relationships existing between the response functions and the process variables as well as to determine the conditions of these variables able to optimize the bioconversion process. The four studied factors (rice bran, ferulic acid, peptone, ammonium nitrate) with one studied response (amount of produced in g/l) were entered into the design in Design Expert software, which generated a screening set with a total of 30 experimental designs. Different concentrations of rice bran, ferulic acid, peptone and ammonium nitrate concentration were selected as the independent variables and were varied in the range of 50-150 g/l, 0.05-1.5 g/l, 5-15 g/l and 1-3 g/l respectively (Table 2). Magnesium sulphate (0.05 g/l) was added as constant factor in each CCRD run. Central points were added to estimate experimental error as well as to investigate the suitability of the proposed model. The choice of these parameters was based on the knowledge that ferulic acid is a key factor influencing Run RB FA P SA MS KHP AN YE MAS ph Temp. Actual value Predicted value ( C) 1 100 1 0 0 0 2 0 5 0.05 4 40 0.327 0.344 2 100 0 10 5 0 2 2 5 0 4 30 0.365 0.347 3 0 0 0 0 0 0 0 0 0 4 30 0 0 4 0 0 10 0 0.1 2 0 5 0.05 7 30 0.037 0 5 100 1 0 5 0.1 2 0 0 0 7 30 0.173 0.193 6 100 0 10 5 0.1 0 0 0 0.05 4 40 0.019 0.196 7 0 1 10 5 0 0 0 5 0 7 40 0.063 0.249 8 0 1 0 5 0.1 0 2 5 0.05 4 30 0 0 9 0 0 0 5 0 2 2 0 0.05 7 40 0.006 0 10 100 1 10 0 0 0 2 0 0.05 7 30 0.625 0.479 11 0 1 10 0 0.1 2 2 0 0 4 40 0.128 0.098 12 100 0 0 0 0.1 0 2 5 0 7 40 0 0.061 RB: rice Bran; FA: ferulic acid; P: peptone; SA: sodium acetate; MS: magnesium sulfate; KHP: potassium dihydrogen phosphate; AN: ammonium nitrate; YE: yeast extract and MAS: manganous sulphate
KAUR & CHAKRABORTY: BIOTRANSFORMATION OF RICE BRAN 937 Run Rice Bran Ferulic acid Table 2 CCRD design matrix Peptone Ammonium nitrate Actual value Predicted value 1 100 0 10 2 0.708 0.723 2 0 0 0 0 0.017 0 3 0 0.05 5 1 0 0.033 4 50 0.05 5 3 0.242 0.336 5 150 0.05 5 1 1.126 1.269 6 0 0.10 10 2 0.110 0.084 7 50 0.15 5 1 0.277 0.411 8 100 0 0 0 0.652 0.617 9 100 0 0 2 0.674 0.573 10 0 0 10 1 0.084 0.05 11 0 0.10 0 1 0.054 0.002 12 50 0.05 5 1 0.376 0.367 13 100 0.10 0 0 0.613 0.529 14 50 0.05 0 1 0.302 0.429 15 100 0.10 0 2 0.581 0.531 16 50 0.05 5 1 0.376 0.318 17 100 0.10 0 2 0.605 0.504 18 100 0.10 10 0 0.611 0.569 19 0 0.10 10 0 0.139 0.121 20 50 0.05 15 1 0.367 0.419 21 0 0.10 0 0 0.109 0.034 22 50 0.05 5 1 0.376 0.392 23 50 0.05 5 1 0.376 0.392 24 50 0.05 5 1 0.376 0.392 25 0 0 0 2 0.018 0 26 100 0 10 0 0.660 0.594 27 50 0 5 1 0.289 0.333 28 50 0.05 5 0 0.248 0.333 29 0 0 10 0 0.058 0.048 30 50 0.05 5 1 0.376 0.392 most biotechnological production process and rice bran is a huge source of ferulic acid. ANOVA was used to evaluate the statistical significance of the model genertaed. The Statistica software Design Expert software (trial version 8.0.7.1, Stat-Ease, Minneapolis, MN) was employed for media optimization analysis. The model of each response was expressed in terms of coded variables and without taking into account the statistically insignificant terms. Confirmatory experiments were done in triplicates and amount of production was expressed in g/l by taking mean of all three results. The behaviour of the CCRD system is expressed by the following equation: Amount of = 375.63 + 282.18 A + (-3.06) B + 16.14 C + (-1.61) D + (-32.44) AB + (-7.91) AC + 5.51 AD + (-2.61) BC + (-13.69) BD +6.49 CD + 46.44 A 2 + 23.26 B 2 + (-10.34) C 2 + (-32.64) D 2 2 where, A=rice bran, B=ferulic acid, C=peptone and D= ammonium nitrate. Results Preliminary screening of response variable using Placket Burman design Plackett-Burman design was implemented to optimize the liquid medium components in submerged fermentation. Plackett- Burman design not only help to reduce the number of components in the medium selecting the more significant contributions to 11 compounds established by the design but also ensured a better production, making the process interesting for industrial production. In the present study, results obtained from PB design run 1, 2 and 10 indicated that rice bran (RB, 100 g/l), feluric acid (FA, 1 g/l) potassium dihydrogen phosphate (KHP, 2 g/l), ammonium nitrate (AN, 2 g/l) yeast extract (YE, 5 g/l) and manganous sulphate (MAS, 0.05 g/l) are required for biosynthesis using Pediococcus acidilactici isolate BD16 at 30 C. Pediococcus acidilactici isolate BD16 yielded 0.625 g/l in the run 10 that contained rice bran (100 g/l), peptone (10 g/l), AN (2 g/l), FA (1 g/l) and
938 INDIAN J EXP BIOL, NOVEMBER 2013 manganous sulphate (0.05 g/l); at ph 7 and 30 C and the actual vs. predicted responses are shown in Table 1. Four variables including rice bran, ferulic acid, peptone and magnesium sulphate out of 11 factors studied influenced production that are indicated in PB experimental model equation no. 1. Independent experiments with ferulic acid and peptone show their positive affect on production that is why, they were carried forward for CCRD assay. A fixed concentration of magnesium sulphate (0.05 g/l) and tween-80 (1g /L) were added in each and every run of CCRD design (Table 2). It can be interpreted from the PB design that the increasing rice bran concentration positively influences production and maximum production is observed only if biotransformation media contains rice bran. Further, scientific literature has suggested that ferulic acid acts as an inducer of biosynthetic genes; therefore its presence increases production in rice bran containing biotransforming media. Variance of regression was analyzed which demonstrates that this model is significant whicn can be conclude from R-squared (0.817), adequate precision (7.740) and very low probability value (0.01). "Prob > F" less than 0.05 indicates that the model terms are significant. In this case rice bran and magnesium sulphate are significant model terms (Table 3). The regression was also checked by the coefficient of determination R 2 whose value is 0.8170. A ratio greater than 4 is desirable. The ratio of 7.740 indicates an adequate signal. This model can be used to navigate the design space. The final response function to predict the amount of production in terms of actual factors is given below. Amount of = -16.99 + 0.045 A + 26.286 B + 0.269 C + (-30.253) E... 3 where, A=rice bran, B=ferulic acid, C=peptone and E=magnesium sulphate. Optimization of production using CCRD design The bioconversion process was further optimized by studying individual effects and interactions including rice bran, ferulic acid, peptone and ammonium nitrate as response variables and constant factors like magnesium sulphate, and tween-80 in the design. FA and peptone was taken along with rice bran as FA and peptone do affect production as indicated in run 10. Especially, FA acts as an inducer of FAE (ferulic acid esterase) activity that facilitates hydrolysis and release of FA from esterified FA from highly cross-linked rice bran matrix and ammonium nitrate acts as nitrogen source and therefore incorporated as variable factors in CCRD design. Both are key factors according to PB run 1, 2 and 10, as their presence enhanced synthesis in 2 out of three best PB runs. Bioconversion assays were performed with Pediococcus acidilactici BD16 isolate in shake flask conditions. Considering production as a response, the model predicted 1.126 g/l of in run 5 (Table 2). Predicted runs were validated experimentally using optimized media consisting of rice bran (150 g/l), ammonium nitrate (1 g/l), ferulic acid (0.05 g/l), peptone (5 g/l), magnesium sulphate (0.05 g/l), and tween-80 (1 g/l) (ph 5.6) at 37 C and 180 rpm after 24 h of incubation and 1.269 g/l was obtained (Table 2). It was observed that the actual and predicted values for both the responses were very close to each other. Finally, using the Design Expert software imposing different criteria three-dimensional response surface curves were plotted to study the interaction between the four factors selected and to determine the optimum concentration of each for maximum production (Fig. 1). Table 4 represents ANOVA analysis of CCRD response variables, the design matrix collected by tests planned according to the 30 experiments. Increasing rice bran concentration, production enhanced significantly and this factor Table 3 Anova analysis of important factors of Placket- Burman Design S.No Variables C SS MS CI (low) CI (high) F value P value Significance 1 (A) Rice Bran 114.73 1.580E+005 1.580E+005 44.27 185.20 14.83 0.0063 Significant 2 (B) Ferulic acid 65.71 51820.22 51820.22-4.75 136.18 4.86 0.0632 3 (C) Peptone 67.48 54641.26 54641.26-2.98 137.94 5.13 0.0579 4 (E) Magnesium sulphate -75.63 68646.33 68646.33-146.1-5.17 6.44 0.0388 Significant C=Coefficient SS = sum of squares, MS= mean square, CI =Confidence interval
KAUR & CHAKRABORTY: BIOTRANSFORMATION OF RICE BRAN 939 Fig. 1 Response contour plots obtained in CCRD design showing interaction between various response factors.
940 INDIAN J EXP BIOL, NOVEMBER 2013 Source Sum of Squares CE df Mean Square Table 4 ANOVA analysis of CCRD response variables SE 95% CI Low 95% CI High Value Prob > F Model 2.062E+006 375.63 14 1.473E+005 < 0.0001 Intercept 375.63 38.02 294.60 456.67 A-RB 1.911E+006 282.18 1 1.911E+006 19.01 241.66 322.69 220.34 < 0.0001 B-FA 224.48-3.06 1 224.48 19.01-43.58 37.46 0.026 0.8743 C-P 6253.28 16.14 1 6253.28 19.01-24.38 56.66 0.72 0.4092 D-AN 62.08-1.61 1 62.08 19.01-42.13 38.91 7.158E-003 0.9337 AB 16835.06-32.44 1 16835.06 23.28-82.06 17.19 1.94 0.1838 AC 1001.72-7.91 1 1001.72 23.28-57.54 41.71 0.12 0.7387 AD 486.20 5.51 1 486.20 23.28-44.11 55.14 0.056 0.8160 BC 109.20-2.61 1 109.20 23.28-52.24 47.01 0.013 0.9121 BD 2997.56-13.69 1 2997.56 23.28-63.31 35.94 0.35 0.5653 CD 673.40 6.49 1 673.40 23.28-43.14 56.11 0.078 0.7843 A2 59142.80 46.44 1 59142.80 17.78 8.53 84.34 6.82 0.0196 B2 14845.46-23.26 1 14845.46 17.78-61.17 14.64 1.71 0.2105 C2 2932.31-10.34 1 2932.31 17.78-48.24 27.56 0.34 0.5696 D2 29220.82-32.64 1 29220.82 17.78-70.54 5.26 3.37 0.0863 Residual 1.301E+005 15 8672.62 Lack of Fit 1.256E+005 10 12557.57 13.91 0.0048 Pure error 4513.63 5 902.73 Cor Total 2.192E+006 29 Coefficient of determination (R 2 )=0.9407 SS = sum of squares, DF = degrees of freedom and MS = mean square Source Sum of squares Degree of freedom Table 5 Model summary Mean square F-value P-value Prob>F Mean vs Total 3.883E+006 1 3.883E+006 Linear vs Mean 1.917E+006 4 4.794E+005 43.62 < 0.0001 2FI vs Linear 22103.16 6 3683.86 0.28 0.9408 Quadratic vs 2FI 1.226E+005 4 30644.01 3.53 0.0319 Suggested Cubic vs Quadratic 26173.92 8 3271.74 0.22 0.9751 Aliased Residual 1.039E+005 7 14845.06 Total 6.076E+006 30 2.025E+005 found to be as the most important contributor of production (Fig. 1a). Quadratic effect of rice bran is significant at P <0.0001. FA shows its effect as inducer at 0.05 g/l concentration in the presence of rice bran and enhances production. Peptone and ammonium nitrate did not significantly affect production as compared to rice bran and ferulic acid (Fig. 1b-e) as it was hypothesized earlier. However, collaborative effect of ammonium nitrate and ferulic acid was observed in production (Fig. 1d). On the basis of model summary, quadratic model was selected as best fit model as compared to other models. ANOVA for production indicated the P=0.0319, implies the model to be significant (Table 5). Values of "Prob > F" less than 0.05 and high R 2 (0.9407) explaining 94.07% of the variability in the response indicate that this regression is statistically significant. The "Lack of Fit" is significant at P-value of 0.0048 (Table 4). "Adeq precision" measures the signal to noise ratio and it should be greater than 4. Ratio of 17.140 indicates an adequate signal and can be used to navigate the design space. Final equation in terms of actual factors was amount = +17.525 + (+0.089) A + (36.883) B + (0.163) C + (1.307) D + (-5.190E-003) AB + (1.266E- 005) AC + (4.410E-005) AD + (-4.180E-003) BC + (-0.109) BD + (+5.190E-004) CD + (7.429E-006) A 2 + (-3.722)B 2 + (-1.654E-004)C 2 + (-0.013)D 2 4 where, A = rice bran, B = ferulic acid, C = peptone and D = ammonium nitrate.
KAUR & CHAKRABORTY: BIOTRANSFORMATION OF RICE BRAN 941 Fig. 2 HPLC chromatogram of extracted (a) and ESI spectrum of extracted and other phenolic metabolites from biotransformation media (b). Vanillin estimation using HPLC and ESI Vanillin was extracted from cultured media after 16 h of incubation using optimized media components supplemented with magnesium sulphate (0.5 g/l) and tween-80 (1 g/l) and 1.269 g/l was recovered and its confirmation was done using HPLC and ESI mass. Pure as well as extracted from optimized medium gave peaks at retention time of 4min as observed in Fig. 2. Further, ESI spectrum confirmed the existence of (with a molecular weight of 153.18 Da) from culture filtrate of the optimized rice bran containing medium. Discussion The present study deals with rice bran to bioconversion process using a LAB isolate Pediococcus acidilactici BD16. A set of batch bioconversion tests were carried out on aqueous rice bran solutions according to a 30 experimental designs selecting the ferulic acid, rice bran, ammonium nitrate and peptone as independent variables. The experimental data was analyzed by RSM, using a quadratic model for predicting the optimal point and significant factors were evaluated and analyzed using one way ANOVA. Under these conditions the model predicted a maximum production 1.269 g/l. Final, optimized production media consisted of 15% (w/v) rice bran, 0.5% (w/v) peptone, 0.1% (w/v) ammonium nitrate, 0.005% (w/v) ferulic acid, 0.005% (w/v) magnesium sulphate and 0.1% (v/v) tween-80, ph 5.6, at 37 C under shaking conditions at 120 rpm. 1.264 g/l was recovered from 16 h old optimized culture medium. The biotechnological production of is a topic of high interest, as demonstrated by the number of reviews published before 1,19,20. In the present study, production was explored using Pediococcal isolate, as an alternative to Actinomyces, Gram-negative strains like Pseudomonas sp. and recombinant E. coli. The maximum
942 INDIAN J EXP BIOL, NOVEMBER 2013 Table 6 Comparison of yields obtained from different substrates Strain Substrate Yield Time/Comments References 1. Aspergillus niger I-1472 and Pycnoporus cinnabarinus concentrations i.e. 11.5 g/l using Amycolatopsis sp. strain HR167, 13.9 g/l using S. setonii ATCC 39116; > 10 g/l using Streptomyces setonii have been reported 3,21-23. Faveri et al 24 used recombinant E. coli JM109pBB1 for synthesis and the biotransformation process was optimized using RSM with biomass and ferulic acid content as response variables. 1.1 g/l was obtained from 1.52 g/l ferulic acid within 48 h of biotransformation using recombinant E. coli 25. Long biotransformation time, costlier substrate and genetically unstable recombinant strain made these processes very uncertain. Using Pseudomonas putida, >10 g/l of from the fermentative media 26. In the strains of Pseudomonas and E. coli, a decrease in bioconversion rate was observed as incubation proceeded. This may be due to the toxicity of or may be due to the transformation of into undesired products such as vanillyl alcohol or vanillic acid as reported previously 27. Considering the applied experimental conditions in the present study, 1.269 g/l was produced in biotransforming media which contained 0.257 mm of ferulic acid (0.05 g/l) as an inducer. Use of less amount of ferulic acid made the process cheaper as pure ferulic acid is very costly. Lower tendency of this strain to reduce to its corresponding alcohol also resulted in increased accumulation in the broth, which was observed after 16 h of incubation. This productivity is the highest reported so far in the literature for a lactic acid bacterial isolate. Results obtained in this study were compared with earlier reports on production from different cheap agro wastes and FA (Table 6). Most of the studies used fungal consortia and required long 834 mg/l FA (hydrolyzed sugar beet pulp) 253 mg/l 192 h 29 2. A. niger I-1472 and Pycnoporus cinnabarinus FA (hydrolyzed maize bran) 767 mg/l 168-192 h 30 MUCL 39533 3. A. niger CGMCC0774; P. cinnabarinus FA (hydrolyzed rice bran oil) 2.8g/L 72 h 31 CGMCC1115 4. Lactobacillus brevis, L. hilgardii, L. plantarum, FA Vanillin - 28 Pediococcus damnosus and Oenococcus oeni (in traces) 5. Phanerochaete chrysosporium Green coconut husk 52.5 µg/g 24 h 15 6. Aspergillus niger and P. chrysosporium FA (hydrolyzed paddy straw) 0.085g/L 288 h 32 7. Pediococcus acidilactici Rice bran containing 0.257 mm FA 1.27g/L 16 h This Work bioconversion time for production of bio. Earlier report on biotransformations mediated through lactic acid bacteria, indicates very low level synthesis and accumulation of 28. Although, the amount of produced in present study is not comparable to that obtained using actinomycetes, it is significant. Moreover, P. acidilactici is easy to cultivate than actinomycetes and the stability of produced by P. acidilactici is comparatively high with respect to the same product obtained from recombinant Gram-negative bacteria that clearly indicates the high potential of the bio production system proposed in this study. The present one is the first report that indicates very high amount of synthesis and its accumulation by a lactic acid bacterial isolate P. acidilactici BD16 that can be exploited in the food industry for in situ biosynthesis. Of course, the separate studies on scale up of the process are suggested. Acknowledgement Thanks are due to UGC, New Delhi, for financial assistance to BK and meritorious BSR fellowship to DC. References 1 Priefert H, Rabenhorst J & Steinbuchel A, Biotechnological production of, Appl. Microbiol Biotechnol, 56 (2001) 296. 2 Li The & Rosazza J P N, Biocatalytic synthesis of, Appl Environ Microbiol, 66 (2000) 684. 3 Muheim A & Lerch K, Towards a high-yield bioconversion of ferulic acid to, Appl Microbiol Biotechnol, 51 (1999) 456. 4 Ishii T, Structure and functions of feruloylated polysaccharides, Plant Sci, 127 (1997) 111. 5 Bonnin E, Grange H, Lesage-Meessen L, Asther M & Thibault J F, Enzymic release of cellobiose from sugar beet
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