research article statistical optimization of fermentation...

Research ArticleStatistical Optimization of Fermentation ProcessParameters by Taguchi Orthogonal Array Design forImproved Bioethanol Production

Saprativ P Das Debasish Das and Arun Goyal

Department of Biotechnology Indian Institute of Technology Guwahati Guwahati Assam 781 039 India

Correspondence should be addressed to Debasish Das debasishdiitgernetin and Arun Goyal arungoyliitgernetin

Received 31 March 2013 Accepted 10 October 2013 Published 14 January 2014

Academic Editors A Ficarella A W Mohammad B Moreno and C Mortalo

Copyright copy 2014 Saprativ P Das et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

The statistical optimization of different fermentation process parameters in SSF of mixed MAA and organosolv pretreated 1 (wvminus1) wild grass namely recombinant Clostridium thermocellum hydrolytic enzymesrsquo volume (GH5 cellulase GH43 hemicellulase)fermentative microbesrsquo inoculum volume (Saccharomyces cerevisiae Candida shehatae) pH and temperature was accomplishedby Taguchi orthogonal array design The optimized parameters in 100mL of fermentation medium were ( v vminus1) as follows 10recombinant GH5 cellulase (57mgminus1 045mg mLminus1) 20 recombinant GH43 hemicellulase (37U mgminus1 032mg mLminus1) 15 Scerevisiae (39 times 108 cells mLminus1) 025 C shehatae (27 times 107 cells mLminus1) pH 43 and temperature 35∘C pH with p-value 0001 wasfound to be the most significant factor affecting SSF The ethanol titre obtained in Taguchi optimized shake flask SSF was 20 g Lminus1implying a 13-fold increase as compared to ethanol titre of 15 g Lminus1 in unoptimized shake flask SSF A 15-fold gain in ethanol titre(31 g Lminus1) was obtained with the same substrate concentration in lab scale bioreactor on scaling up the shake flask SSF with Taguchioptimized process parameters

1 Introduction

Cost-effective fermentation of lignocellulosic hydrolysate toa value-added product bioethanol necessitates the conspic-uous enhancement in the activities of various hydrolyticenzymes along with efficient mixed sugar utilization byvarious fermentative microbes [1] Simultaneous saccharifi-cation and fermentation (SSF) is a single step combination ofenzymatic hydrolysis of complex polysaccharides with con-current fermentation of derived monosaccharides to ethanol[2] The northeast part of India has a wide abundance oflignocellulosic substrate namely wild grass (Achnatherumhymenoides) rich in cellulose and hemicellulose [3] Ascompared to the commercially employed hydrolytic enzymeof the corresponding Trichoderma system the cellulosomeof the anaerobic thermophilic bacterium Clostridium ther-mocellum exhibits a 50-fold higher specific activity againstcrystalline cellulose [4] The advancement in molecularbiology has familiarized new area of enzyme production intransformed cells with overexpression and their subsequent

use for the breakdown of structural carbohydrates namelycellulose and hemicellulose into simple sugars [3 5]

According to CAZy database glycoside hydrolase family5 (GH5) exhibits activities of chitosanase (EC 321132)cellulase (EC 3214) glucan 1 3-120573-glucosidase (EC 32158)and licheninase (EC 32173) whereas glycoside hydro-lase family 43 displays 120573-xylosidase (EC 32137) 120572-L-arabinofuranosidase (EC 32155) and xylanase (EC 3218)activities A number of available pretreatment techniquesare used for liberating the cellulosic and hemicellulosiccomponents from the lignin moieties and in turn renderingthe accessibility to a better hydrolysis step [6] Saccharomycescerevisiaehas the inherent ability to utilize hexose sugars fromthe breakdown of cellulose considerable product toleranceand resistance tometabolic inhibitions in ethanol production[7] Xylitol dehydrogenase and xylose reductase are theprime enzymes of Candida shehatae that enable it to utilizepentose sugars from hemicellulose degradation for ethanolproduction [8]

Hindawi Publishing CorporationJournal of FuelsVolume 2014 Article ID 419674 11 pageshttpdxdoiorg1011552014419674

2 Journal of Fuels

Temperature pH hydrolytic enzyme volume and fer-mentativemicrobersquos inoculum volume are the process param-eters that play a vital role in lignocellulosic ethanol pro-duction [9] The performance of multiple experiments byanalyzing one variable at a time (OVAT) approach is timeconsuming and laborious for identifying various indepen-dent variables with their effects [10] Statistically basedexperimental designs namely Plackett-Burman design Box-Behnken design and Taguchi orthogonal array designsummarize the collection and sorting of variables to betaken for consideration determine the variable amount andanalyze the variable at different parameters and finally theeffect of variable error Better quality at low cost is themain aim for generation of Taguchi design of experiments(DOE) approaches to maximize robustness of products andprocesses [11] Taguchi experimental design is a fast andconsiderable way of optimization conferring remarkableoutcome in simultaneous study of many factors making itsmark in quality products supplemented with better processperformance and rendering high yield and better stability[12 13] The basic principle involved is the encompassmentof large experimental data as orthogonal (unbiased) array indetermining the effect of various factors which govern thereaction happening ensuing in experimental error reductionwith improved producibility (efficiency) of experimentaloutcome Taguchi design established the importance of sta-tistically aligned experiments in speculating the settings ofproduct (andor processes) on various parameters [14 15]

The current study emphasizes the Taguchi optimizationof different fermentation process parameters such as mixedrecombinant enzymesrsquo volume (GH5 cellulase GH43 hemi-cellulase) mixed culturesrsquo inoculum volume (S cerevisiaeC shehatae) pH and temperature on bioethanol productionfrommixed pretreated wild grass with subsequent validationof the model at shake flask level and scale-up in a bioreactor

2 Materials and Methods

21 Reagents Chemicals and Substrate Carboxy methylcellulose (CMC) and rye arabinoxylan were purchased fromSigmaAldrich (St Louis USA)The analytical grade reagentsand chemicals namely LB medium ampicillin kanamycinsodium acetate glucose yeast extract peptone potassiumdichromate (K

2

Cr2

O7

) sodium carbonate sodium bicar-bonate sodium potassium tartrate sodium sulphate coppersulphate ammonium molybdate sodium arsenate phos-phoric acid and ethanol were purchased from Merck andHimedia Pvt Ltd India Coomassie brilliant blue G-250was purchased from Amresco LLC USA Lignocellulosicsubstrate wild grass (Achnatherum hymenoides) was collectedfrom the campus of Indian Institute of Technology GuwahatiIndia The substrate was washed with water thrice for theremoval of adhered dust particles dried and finally grindedto 1mmmesh size

22 Microorganisms and Culturing Conditions The recombi-nant E coli BL21 (DE3) cells harbouring family 5 glycosidehydrolase (GH5) gene from Clostridium thermocellum were

cloned in an expression vector pET-21a(+) and expressedearlier [16 17] The recombinant GH5 cellulase is availablecommercially at NZY Tech Lda Lisbon Portugal Therecombinant E coli BL21 (DE3) pLysS cells transformed byfamily 43 glycoside hydrolase (GH43) gene from Clostridiumthermocellum and cloned in pET-28a(+) expression vectorwere expressed earlier [3]These cells were cast off as a sourceof recombinant GH43 hemicellulase These E coli BL21 cellswere preserved in LB medium as glycerol stock at minus80∘C inour laboratory at IIT Guwahati

The fermentative microbes Saccharomyces cerevisiae(NCIM no 3215) and Candida shehatae (NCIM no 3500)procured from National Chemical Laboratory Pune Indiawere maintained independently at 4∘C on 5mL of Maltextract glucose yeast extract peptone (MGYP) slants contain-ingmalt extract (03 g 100mLminus1) glucose (1 g 100mLminus1) yeastextract (03 g 100mLminus1) and peptone (05 g 100mLminus1) [18]One loopful from these slant cultures was further introducedinto 50mL of glucose yeast extract (GYE) medium in twoseparate 100mL Erlenmeyer flasks containing glucose (1 g100mLminus1) and yeast extract (01 g 100mLminus1) with supple-mentation of KH

2

PO4

(01 g 100mLminus1) (NH4

)2

SO4

(05 g100mLminus1) and MgSO

4

sdot7H2

O (005 g 100mLminus1) They wereincubated at 30∘C and 120 rpm for 48 h prior to inoculationinto fermentation media The aliquots measuring 1mL fromeach of the actively growing cultures of S cerevisiae (39 times108 cellsmLminus1) and C shehatae (27 times 107 cellsmLminus1) were

aseptically inoculated to 100mL fermentation medium Thecell count of the actively growing S cerevisiae andC shehataewas measured using a haemocytometer

23 Production of Recombinant Cellulase (GH5) and Hemi-cellulase (GH43) The recombinant GH5 cellulase produc-tion was initiated by inoculating 50 120583L of the E coli BL21(DE3) culture from glycerol stocks into 5mL of LB mediumcontaining 100 120583gmLminus1 ampicillin with incubation at 37∘Cand 180 rpm for 16 h One percent (v vminus1) of the cultureinoculum was transferred aseptically to 200mL of LBmedium in 500mL flask containing 100120583gmLminus1 ampicillinand was incubated at 37∘C and 180 rpm till the culturereached the midexponential phase (A

600 nm 06) This mid-exponential phase culture was induced with isopropyl-120573-D-thiogalactopyranoside (IPTG) (1mM final concentration)followed by further 8 h incubation for overexpression ofrecombinant protein [16] 50 120583gmLminus1 kanamycin was usedas a selective marker for E coli BL21 (DE3) plysS cellscontaining GH43 hemicellulase [3] Similar production pro-cess was employed for GH43 hemicellulase as followed forGH5 cellulase except that the incubation period was 24∘C180 rpm and 24 h for overexpression of protein after IPTG(1mM final concentration) was added The overexpressed Ecoli cells (GH5 or GH43) collected by centrifugation (4∘C8510 g and 30min) were resuspended in 50mM sodiumphosphate buffer (pH 70) Each of the resuspended cellpellets was subjected to sonication (SONICS Vibra CellNewtown CT USA) in an ice-bath separately for 15minwith further centrifugation (4∘C 19650 g and 30min) The

Journal of Fuels 3

Table 1 Factor (parameter) and levels in Taguchi experimental design for shake flask SSF process employing mixed pretreated 1 (w vminus1)wild grass at 120 rpm

Factorparameter LevelsRecombinant GH5 cellulaselowast (57Umgminus1 045mgmLminus1) 025 05 10 15 20Recombinant GH43 hemicellulaselowast (37Umgminus1 032mgmLminus1) 025 05 10 15 20S cerevisiaelowast (36 times 108 cellsmLminus1) 025 05 10 15 20C shehataelowast (21 times 108 cellsmLminus1) 025 05 10 15 20pH 3 43 50 55 6Temperature (∘C) 26 28 30 33 35lowastThe values of levels in ( v vminus1)

two recombinant enzymes GH5 cellulase and GH43 hemi-cellulase were expressed as soluble proteins The cell freesupernatant obtained was employed as the enzyme source forSSF experiments [16]

24 Mixed Pretreatment Strategy Microwave-assisted alkali(MAA) pretreatment loosens the compact structure of cel-lulose and aids in its hydrolysis to glucose [19] Organosolvpretreatment with the assistance of different organic acidsbenefits in relaxing the complex hemicellulose for its efficienthydrolysis to xylose [20] Owing to the substantial quantitiesof cellulose and hemicellulose in wild grass the lignocellu-losic substrate was subjected to mixed MAA and organosolvpretreatment strategy

25 Microwave-Assisted Alkali (MAA) Pretreatment Onegram (dry powder) of wild grass (A hymenoides) was sus-pended in 8mL of 1 (v vminus1) sodium hydroxide aqueoussolution in a 100mL beaker The beaker was positioned atthe centre of a rotating circular glass plate in a domesticmicrowave oven at 900W for 25min [19] The substrate fil-tered through muslin cloth was further subjected to organo-solv pretreatment

26 Organosolv Pretreatment The microwave-assisted alkali(MAA) pretreated and filtered wild grass was further sub-jected to 20mL of (70 30 v vminus1) ethanol water mixture con-taining 1 (v vminus1) of sulphuric acid hydrochloric acid aceticacid and phosphoric acid (1mL each) at 70∘C for 1 h [20]The substrate was then washed with two ethanolic extracts95 (v vminus1) ethanol at 60∘C for 4 h and 70 (v vminus1) ethanol at30∘C for 1 hThe substrate residuewas further treatedwith 4(v vminus1) hydrogen peroxide at 45∘C for 16 h The final washingwas done with 70 ethanol at 30∘C for 1 h [20] The mixedpretreated substrate was subsequently subjected to enzymatichydrolysis

27 Simultaneous Saccharification and Fermentation (SSF)Process of Mixed Pretreated 1 (w vminus1) Wild Grass atShake Flask Level One percent (w vminus1) of the mixedmicrowave-assisted alkali (MAA) and organosolv pretreatedwild grass (A hymenoides) was autoclaved in 250mLErlenmeyer flask encompassing 100mL working volumeof 20mM sodium acetate buffer (pH 50) supplemented

with (01 w vminus1) each of the yeast extract and peptoneThen 05mL of each crude recombinant cellulase (GH5)(57Umgminus1 045mgmLminus1) and recombinant hemicellulase(GH43) (37Umgminus1 032mgmLminus1) was added as the mixedenzymatic consortium for hydrolysis At the same time05mL of each S cerevisiae (39 times 108 cellsmLminus1) and Cshehatae (27 times 107 cellsmLminus1) inoculum was added forfermentation The flasks were kept at 30∘C and 120 rpm for72 h and the sample was collected at every 6 h intervalThe monitoring of SSF dynamic profile was done with themeasurement of the cell OD (A

600 nm) reducing sugar (g Lminus1)

ethanol concentration (g Lminus1) and specific activity (Umgminus1)

28 Optimization of Process Parameters ofSimultaneous Saccharification and Fermentation (SSF)Involving Mixed Pretreated Wild Grass at ShakeFlask Level by Taguchi Method

281 Statistical Optimization Using Taguchi OrthogonalArray Design Taguchi experimental design matrix a stan-dard orthogonal array L

25

(65

) was used to examine sixfactors namely recombinant GH5 cellulase (57Umgminus1045mgmLminus1) volume (mL) recombinant GH43 hemicellu-lase (37Umgminus1 032mgmLminus1) volume (mL) S cerevisiae(39 times 108 cellsmLminus1) inoculum volume (mL) C shehatae(27 times 107 cellsmLminus1) inoculum volume (mL) pH andtemperature (∘C) in five levels namely Level 1 to Level 5(Table 1) in SSF experiments involving mixed pretreated 1(w vminus1) wild grass at shake flask level The lower and upperlevels of optimized factors were selected on the basis of thesuitable conditions for the active functioning of the recom-binant hydrolytic enzymes and the desired growth of thefermentative microbes for efficient bioethanol productionThe L and the subscript (25) represent the Latin square andthe number of experimental runs respectively The levelsof the factors studied and the layout of the L

25

Taguchirsquosorthogonal array are represented in Tables 1 and 2 Each of thetwenty-five simultaneous saccharification and fermentation(SSF) experiments denoted by ldquorunsrdquo was carried out asper the defined values of six different parameters in fivelevels (Table 2) All the SSF experiments were carried out in100mL of fermentation media at 120 rpm for 72 h at varying

4 Journal of Fuels

Table 2 Matrix layout of the L25 Taguchi orthogonal array design

Runexpt no Recombinant GH5cellulaselowast

Recombinant GH43hemicellulaselowast S cerevisiaelowast C shehataelowast pH Temperature

1 025 1 1 1 5 302 05 15 2 025 43 303 1 2 05 15 3 304 15 025 15 05 6 305 2 05 025 2 55 306 025 025 025 025 3 267 05 05 1 15 6 268 1 1 2 05 55 269 15 15 05 2 5 2610 2 2 15 1 43 2611 2 025 2 15 5 2812 15 2 1 025 55 2813 1 15 025 1 6 2814 05 1 15 2 3 2815 025 05 05 05 43 2816 025 15 15 15 55 3317 05 2 025 05 5 3318 1 025 1 2 43 3319 15 05 2 1 3 3320 2 1 05 025 6 3321 025 2 2 2 6 3522 05 025 05 1 55 3523 1 05 15 025 5 3524 15 1 025 15 43 3525 2 15 1 05 3 35lowastThe values of levels in ( v vminus1)

temperatures (Table 1) with sample collection at every 6 hinterval

282 Analysis of the Taguchi Orthogonal Array Experiments(Runs) The MINITAB statistical software package (DesignExpert version 80) was used to determine the outcomesof the fermentation runs The signal-to-noise ratio (119878119873)which is the logarithmic function of desired output servedas objective function for optimization

For each run 119878119873 ratio corresponding to larger-the-better objective function was computed using relation in

119878

119873

= minus10 log10

1

119899

119899

sum

119894=1

1

1199102

119894

(1)

where ldquo119910119894

rdquo is the signal and ldquo119899rdquo is the number of repetitionsin each experiment

The response values in terms of ethanol titre ( v vminus1)and 119878119873 ratios of Taguchi experimental design in 25 runswere analysed to extract independently themain effects of thefactors the analysis of variance technique was then appliedto determine which factors were statistically significant Thecontrolling factors were identified with the magnitude of

the effects qualified and the statistically significant effectsdetermined Accordingly the optimal conditions were deter-mined by combining the levels of factors that had the highestmain effect value The analysis of variance (ANOVA) for theresponses of ethanol production was carried out according tothe factorsrsquo contribution by the Taguchi method The factorsin the experimental design considered to be statisticallysignificant at 95 confidence limit were used to determinethe ratio (119865) and the 119901-value (119901 lt 005)

283 Validation of the Experimental Model The model wasvalidated by performing the SSF trial employing Taguchioptimized fermentation process parameters on mixed pre-treated 1 (w vminus1) wild grass in 100mL of fermentationmedium The best fermentation process parameters com-prised 10mL of recombinant GH5 cellulase (57Umgminus1045mgmLminus1) 20mL of recombinant GH43 hemicellulase(37Umgminus1 032mgmLminus1) 15mL of S cerevisiae (39 times108 cellsmLminus1) 025mL of C shehatae (27 times 107 cellsmLminus1)

pH of 43 and temperature of 35∘C The fermentation wascarried out at 120 rpm for 72 h with 6 h sample collectioninterval The validation of the experimental model wasexecuted by determining the ethanol titre ( v vminus1)

Journal of Fuels 5

284 Scale-Up of Taguchi Optimized Simultaneous Sacchari-fication and Fermentation (SSF) Process Parameters InvolvingMixed Pretreated 1 (w vminus1) Wild Grass at Bioreactor LevelThe Taguchi optimized SSF process parameters involvingmixed pretreated 1 (w vminus1) wild grass were scaled up to 1 Lin a 2 L lab scale fermentor (Applikon model Bio ConsoleADI 1025 Holland) 10 g Lminus1 of mixed MAA and organosolvpretreated wild grass (A hymenoides) was used as substratefor bioreactor SSF experiments 10mL of isolated cruderecombinantGH5 cellulase (57Umgminus1 045mgmLminus1) alongwith 20mL of recombinant GH43 hemicellulase (37Umgminus1032mgmLminus1) was employed for saccharification 15mL of Scerevisiae (39times108 cellsmLminus1) and 25mL of C shehatae (27times 107 cellsmLminus1) were engaged for bioethanol productionThe SSF was carried out at 35∘C pH 43 and agitation of120 rpm For the efficient growth of fermentative microbesan aeration rate of 1 vvm was controlled by a mass flowcontroller to maintain the dissolved oxygen (DO) level ofminimum 40 Growth was observed at 600 nm using UV-visible spectrophotometer (Varian Cary50 Australia) Theonline process parameters namely temperature (∘C) pHand stirring rate (rpm) were noted for every 1min Thedifferent parameters of cell OD (A

600 nm) reducing sugar(g Lminus1) ethanol concentration (g Lminus1) and specific activity(Umgminus1) were surveyed at 6 h fixed interval The addition of1 N HCl and 1N NaOH to maintain the pH at 43 prohibitedthe pH excursions of the organism below the set point

29 Analytical Methods

291 Estimation of Structural Carbohydrate The structuralcarbohydrates like cellulose hemicellulose and lignin ofuntreated and pretreated wild grass were estimated by thestandardized methods of NREL USA [21] 03 g of drypowdered substrate (untreated or pretreated) wasmixed with3mL of H

2

SO4

(27N) and kept at 30∘C for 1 hThen 84mL ofdistilled water was added to lower down the concentrationof H2

SO4

to 15 N Then the sample was autoclaved at 121∘Cfor 1 hThe substrate was cooled to room temperature and thebiomass (untreated or pretreated)was filtered using a vacuumfiltration unitThe residue weighed was lignin (acid insolublelignin) The pH of the collected filtrate was neutralized byaddition of CaCO

3

(1M) Finally the filtrate was assessed forreducing sugar (glucose) and in turn cellulose was calculated(1 g cellulose = 11 g of glucose) The remaining content washemicellulose

292 Recombinant GH5Cellulase GH43Hemicellulase Assayand Protein Content Determination The recombinant GH5cellulase assay was performed by incubating the enzyme(10 120583L) in a 100 120583L reaction mixture with 1 (w vminus1) finalconcentration of CMC in 20mM sodium acetate buffer(pH 43) at 50∘C and 10min The mixture was assessed forthe released reducing sugar [22 23] The released reducingsugar was used to determine the enzyme activity The GH43hemicellulase activity was tested by incubating 10 120583L of therecombinant enzyme in a 100 120583L reaction mixture with 1

(w vminus1) final concentration of rye arabinoxylan in 100mMsodium acetate buffer (pH 54) at 50∘C for 10min Theabsorbance was measured using a UV-visible spectropho-tometer (Perkin Elmer Model lambda-45) at 500 nm againsta blank with D-glucose or L-arabinose as standard Oneunit (U) of cellulase activity is defined as the amount ofenzyme that liberates 1 120583mole of reducing sugar (glucose)per min under the above assay conditions On the otherhand one unit (U) of hemicellulase activity is defined as theamount of enzyme that releases 1 120583mole of reducing sugar(arabinose) per min under the above assay conditions Theconcentration of protein was detected by mixing the enzyme(10 120583L) with distilled water (90120583L) in a total reaction volume(100 120583L) with final addition of 1mL Bradford reagent [24]The reaction mixture was upheld at 25∘C for 20min andOD was determined using a UV-visible spectrophotometer(Perkin ElmerModel lambda-45) at 595 nm A BSA standardcurve was used to determine the protein concentration

293 Ethanol Content Determination byGas Chromatographyand Dichromate Method The ethanol fraction in fermenta-tion broth was determined by gas chromatography furnishedwith flame ionization detector (GC-FID Varian 450) andPorapak (Hayesep) Q packed column (30m times 20mm id80ndash100mesh Varian) A constant flow rate (55 cm3minminus1)of nitrogen was used as the carrier gas with the oventemperature kept constant at 150∘C for 20min as per Bandaruet al 2006 [25] Both the injector and detector temperatureswere maintained at 170∘C The injection volume used forethanol analysis was 1 120583L

The dichromate method was also employed to detect theethanol content by its conversion to acid following dichro-matic reaction [26]The cell free supernatant of fermentationbroth (1mL) was mixed with 0115M K

2

Cr2

O7

(2mL) withfinal addition of 9mL distilled water The 12mL reactionmixture was kept for 10min in a boiling water bath Finallythe absorbance of the cooled sample was measured againsta blank of potassium dichromate (K

2

Cr2

O7

) as standardusing a UV-visible spectrophotometer (Perkin Elmer Modellambda-45) at 600 nm

The ethanol yield (g of ethanol g of substrateminus1) wasobtained by dividing the maximum ethanol concentration(g Lminus1) attained in SSF experiments with initial cellulose andhemicellulose concentration (g Lminus1) of the pretreated wildgrass (ligninwas not taken into account)When these ethanolyields are compared with the theoretical 051 g ethanolg ofsugar (glucose or xylose) yield since the residual celluloseand hemicellulose contents after fermentation were notdetermined in our SSF studies the amount of cellulose andhemicellulose consumed could not be calculated Similarmethod for calculation of ethanol yield has been reportedearlier [27]

3 Results and Discussion

The improved saccharification of cellulosic and hemicel-lulosic components of lignocellulosic biomass by compe-tent hydrolytic enzymes with simultaneous consumption of

6 Journal of Fuels

Table 3 Comparison of unoptimized and Taguchi optimized SSF combinations with mixed pretreated wild grass

SSF combinationSubstrate concentration( w vminus1) and mode

of SSF

Reducing sugarlowast(g Lminus1)

Ethanol yield(g of ethanol g of

pretreated substrateminus1)

Ethanol titrelowast(g Lminus1)

GH5 + GH43 + S cerevisiae + C shehatae(unoptimized)

1shake flask 170 plusmn 009 0228 150 plusmn 006

GH5 + GH43 + S cerevisiae + C shehatae(Taguchi optimized)



1bioreactor 402 plusmn 003 0472 310 plusmn 007

lowastThe values correspond to the maximum reducing sugar and maximum ethanol at a particular time values are mean plusmn SE (119899 = 3)

monomeric sugars by fermentative microbes is the technoe-conomic viability of an efficient SSF process The structuralcarbohydrates determination of wild grass (A hymenoides)revealed greater amount of cellulose (5009 plusmn 032 wwminus1)followed by hemicellulose (299 plusmn 067 wwminus1) suggestingwild grass as the suitable candidate for SSF based bioethanolproduction The microwave-assisted alkali (MAA) pretreat-ment is reported to increase cellulose hydrolysis [19] and theorganosolv pretreatment is more effective for hemicellulosiccontent breakdown of agroresidues [20] The carbohydratecomposition of wild grass after mixed pretreatment revealedcellulose (4332 plusmn 051 wwminus1) and hemicellulose (2235 plusmn048 wwminus1) In the current study the desired volume ofrecombinant C thermocellum mixed enzymes for the pro-duction of simple sugars and the inoculum volume of mixedfermentative microbes along with other process parametersfor bioethanol production frommixed MAA and organosolvpretreated wild grass were optimized by Taguchi statisticaldesign in shake flask and scaled up in bioreactor

31 Unoptimized Simultaneous Saccharification and Fermen-tation (SSF) Process of Mixed Pretreated 1 (w vminus1)Wild Grassat Shake Flask Level The dynamic profile of SSF involvingunoptimized process parameters for ethanol production frommixed pretreated 1 (w vminus1) wild grass at shake flask level isrepresented in Figure 1 The mixed cultures of S cerevisiaeand C shehatae exhibited negligible lag phase in their growthwith steady increase till 66 h with slight decrease thereafter(Figure 1) The growth-associated ethanol formation beganfrom 12 h of SSF with a gradual increase till 36 h after whicha sharp rise was observed till 54 h (Figure 1) The maximumethanol titre achieved was 150 g Lminus1 (Table 3 Figure 1) witha yield of 0228 (g of ethanol g of substrateminus1) Thereaftera decrease in ethanol production was witnessed The initialphase of the SSF represented an accumulation of availablesugars till 18 hwith a gradual declineThemaximum reducingsugar concentration was 170 g Lminus1 (Figure 1)The activities ofboth the recombinant enzymes decreased with the progressin fermentation The dynamic profile of only recombinantGH5 cellulase has been shown in Figure 1 as wild grasscontains more cellulose Interestingly the microbial growthand ethanol production shared an inverse relationship withenzyme activities and in turn the reducing sugars released

00

04

08

12

16

20

Time (h)0 20 40 60

00

04

08

12

16

20

00

02

04

06

08

Cel

l OD

at600

nm

0

1

2

3

4

5

6

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)

Figure 1 SSF profile of 1 (w vminus1) mixed MAA and organosolvpretreatedwild grass (Achnatherumhymenoides) using unoptimizedfermentation process parameters namely recombinant cellulase(GH5) recombinant hemicellulase (GH43) along with S cerevisiaeC shehatae pH and temperature at shake flask level showing varia-tion of (e) cell OD measured at 600 nm (998771) ethanol concentration(g Lminus1) (998787) reducing sugar (g Lminus1) and (I) specific activity (Umgminus1)of GH5 cellulase with time (h) Similar specific activity profiles wereobtained for recombinant hemicellulase (GH43) (data not shown)

clearly demonstrating the fact of sugar utilization by theorganisms for growth and ethanol formation (Figure 1)

32 Optimization of Process Parameters of SimultaneousSaccharification and Fermentation (SSF) Involving MixedPretreated Wild Grass by Taguchi Method Taguchi experi-mental design is a good positive option for the optimiza-tion of biotechnological processes The fermentation processparameters namely temperature pH hydrolytic enzymevolume and fermentative microbersquos inoculum volume playan important role in lignocellulosic ethanol production [9]In this case the influence of 6 factors on the SSF processwas tested by Taguchi experimental design in 25 runs(Tables 1 and 2) The response values in terms of ethanol titre( v vminus1) and 119878119873 ratios of Taguchi experimental designin 25 runs for the six factors that is recombinant GH5cellulase volume recombinant GH43 hemicellulase volumeS cerevisiae inoculum volumeC shehatae inoculum volumepH and temperature (∘C) chosen for optimization of ethanolproduction by SSF process (Table 4) show the efficiency of

Journal of Fuels 7

Table 4 Response values and 119878119873 ratio of L25 Taguchi orthogonalarray design

Runexpt no Response in terms of ethanoltitre ( v vminus1)lowast 119878119873 ratio

1 01527 plusmn 005 minus16322 01892 plusmn 004 minus14463 01427 plusmn 009 minus16924 01888 plusmn 002 minus14485 01828 plusmn 007 minus14766 01203 plusmn 008 minus18397 01874 plusmn 006 minus14558 02102 plusmn 001 minus13559 01837 plusmn 003 minus147210 02252 plusmn 006 minus129511 01910 plusmn 005 minus143812 01938 plusmn 007 minus142613 02093 plusmn 008 minus135914 01226 plusmn 008 minus182315 02170 plusmn 004 minus132716 02024 plusmn 005 minus138717 02006 plusmn 003 minus139518 02056 plusmn 002 minus137419 01245 plusmn 001 minus180920 02198 plusmn 008 minus131621 02170 plusmn 009 minus132722 02179 plusmn 007 minus132423 02512 plusmn 003 minus119924 02225 plusmn 002 minus130525 01267 plusmn 005 minus1794lowastThe values correspond to the maximum ethanol at a particular time valuesare mean plusmn SE (119899 = 3)

ethanol production ranging from 0120 ( v vminus1) to 0251 (v vminus1) corresponding to the combined effect of the six factorsin their specific ranges The experimental results suggestthat these factors at optimum level strongly support theproduction of ethanol In run (expt 6) with a combinationof recombinant GH5 cellulase volume (025mL) recombi-nant GH43 hemicellulase volume (025mL) S cerevisiaeinoculum volume (025mL) C shehatae inoculum volume(025mL) pH (3) and temperature (26∘C) an ethanolconcentration of 0120 ( v vminus1) was observed (Table 4Figure 2) A maximum ethanol titre of 0251 ( v vminus1)ethanol was observed in run (expt 23) with a combinationof recombinant GH5 cellulase volume (10mL) recombinantGH43 hemicellulase volume (05mL) S cerevisiae inoculumvolume (150mL) C shehatae inoculum volume (025mL)pH (5) and temperature (30∘C) with the best response andmaximum 119878119873 ratio (minus1199) (Table 4 Figure 2)

The Taguchi optimized fermentation process param-eters are shown in Figure 3 The best process parame-ters in 100mL of fermentation medium comprised 10mLof recombinant GH5 cellulase (57Umgminus1 045mgmLminus1)

030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25

Runexperiment number

Etha

nol t

itre (

v

vminus1)

Figure 2 Comparative results of response in terms of ethanol titre( v vminus1) of Taguchi L

25

orthogonal array of experiments

20mL of recombinant GH43 hemicellulase (37Umgminus1032mgmLminus1) 15mL of S cerevisiae (39 times 108 cellsmLminus1)025mL of C shehatae (27 times 107 cellsmLminus1) pH of 43 andtemperature of 35∘C

The analysis of variance (ANOVA) for the responses ofethanol production was carried out according to the factorsrsquocontribution by the Taguchi method (Table 5) From thecalculated ratios (119865) it can be inferred that the factors con-sidered in the experimental design are statistically significantat 95 confidence limit Table 6 represented the contributionof the selected factors to bioethanol production It can beobserved that on the basis of 119901-value (119901 lt 005) pHwith rank 1 is the most significant of all other factors andshows the highest positive impact on the ethanol productionC shehatae inoculum volume showed the least impact onethanol production among the factors studied with theassigned variance of values Several scientists have reportedthat the transport of chemical products and enzymes acrossthe cell membrane is affected by the pH of the fermentationmedium influencingmany enzymatic reactions [28]The sta-tistical outcomes in our research also confirmed fermentationmedium pH to be an important factor affecting SSF Similarfindings have been reported in the literature [9] C shehataeinoculum volume showed the least impact among the factorsstudied with the assigned variance of values

33 Validation of Taguchi Experimental Model The vali-dation of Taguchi experimental model is represented inTable 7 It was observed that the response (ethanol v vminus1)(0254) as well as 119878119873 ratio (minus1095) for Taguchi optimumvalues was more than the experimental optimum values forethanol production (02512 v vminus1) and 119878119873 ratio (minus1199)(Table 7) This validated the Taguchi optimized SSF processparametersThus there was a 13-fold increase in ethanol titrewith Taguchi optimized SSF process parameters as compared

8 Journal of Fuels

Signal-to-noise larger is better

Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Main effect plots for SN ratios

Figure 3 Main effect plots for 119878119873 ratios with larger-the-better objective function of Taguchi optimized fermentation process parameters

Table 5 Analysis of variance for the responses of ethanol production

Source DF Seq SS Adj SS Adj MS F pRecombinant GH5 cellulase 1 00000660 00000660 00000660 008 0783Recombinant GH43 hemicellulase 1 00000637 00000637 00000637 008 0786S cerevisiae 1 00000000 00000000 00000000 000 0996C shehatae 1 00002732 00002732 00002732 032 0576pH 1 00150152 00150152 00150152 1785 0001Temp 1 00012587 00012587 00012587 150 0237Error 18 00151394 00151394 00008411Total 24 00318162DF degrees of freedom SS sum of squares and MS mean of squares

to unoptimized parameters (Table 3) These experimentssupported the analysis of the main effect of each constituentof the mediumThe Taguchi SSF experiments provided basicinformation for the improvement of the ethanol productionefficiency Finally using the Taguchi optimized fermentationprocess parameters (Table 7) the SSF process was scaled upat bioreactor level

34 Scale-Up of Taguchi Optimized Simultaneous Saccharifi-cation and Fermentation (SSF) Process Parameters InvolvingMixed Pretreated 1 (w vminus1) Wild Grass at Bioreactor LevelIt is a well-established fact that the fermentation dynamics

and in turn the final ethanol titre are significantly affectedby the parameters namely pH and aeration [29] The SSFprocess involving statistically designed Taguchi optimizedfermentation process parameters and mixed pretreated 1(w vminus1) wild grass was finally scaled up in an automatedbioreactor enabling the stringent monitoring of importantprocess parameters (Figure 4)

S cerevisiae and C shehatae remained in a very shortlag phase of initial 6 h and displayed an exponential growthprofile (Figure 4) Until the 66 h the biomass concentrationincreased considerably as the organisms entered the logphase reaching a maximum cell OD (A

600 nm) of 14 andfinally a decline phase was observed thereafter A biphasic

Journal of Fuels 9

Table 6 Rank and significance of various factors

Factorparameter Rank p-valueRecombinant GH5 cellulaselowast(57Umgminus1 045mgmLminus1) 4 0783

Recombinant GH43 hemicellulaselowast(37Umgminus1 032mgmLminus1) 5 0786

S cerevisiaelowast (36 times 108 cellsmLminus1) 3 0996C shehataelowast (21 times 108 cellsmLminus1) 6 0576pH 1 0001Temperature 2 0237119901 lt 005

Table 7 Validation of Taguchi experimental data values

Factorparameter Taguchioptimum

Experimentoptimum

Recombinant GH5 cellulase(57Umgminus1 045mgmLminus1) ( v vminus1) 10 10

Recombinant GH43 hemicellulase(37Umgminus1 032mgmLminus1) ( v vminus1) 20 05

S cerevisiae (36 times 108 cells mLminus1)( v vminus1) 15 15

C shehatae (21 times 108 cells mLminus1)( v vminus1) 025 025

pH 43 50Temperature (∘C) 35 35119878119873 ratio minus1095 minus1199Response experimentalethanol titre ( v vminus1) 02540 02512

Response predicted ( v vminus1)ethanol titre ( v vminus1) 02705 02677

Ethanol titre (g Lminus1) 200 198Ethanol yield(g of ethanol g of substrateminus1) 0200 0198

ethanol formation was recorded The initial phase of ethanolproduction documented a titre of 225 g Lminus1 at 18 h of SSFfollowed by a slight decrease in ethanol synthesis rate till 36 hThe final phase of ethanol kinetics witnessed a maximumethanol concentration of 310 g Lminus1 (Figure 4) with an ethanolyield of 0472 (g of ethanol g of substrateminus1) at 66 h and thena declination in ethanol titre was observed till the end of thefermentation process (Table 3 Figure 4) The reducing sugarconcentration peaked during the initial 18 h of fermentationreaching a maximum concentration of 402 g Lminus1 (Table 3Figure 4) As A hymenoides have more cellulosic contentthe dynamic profile of only recombinant GH5 cellulase hasbeen presented in Figure 4The activities of mixed enzymaticconsortium decreased with the progress of SSF The drop inreducing sugar concentration after 18 h clearly indicated thesugar uptake by the hexose and pentose utilizingmicrobes fortheir growth maintenance and ethanol production

The controlled parameters of pH and aeration rate sig-nificantly affected the growth and ethanol concentration Athreshold dissolved oxygen (DO) level of minimum 40 was

Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)

Figure 4 SSF profile of 1 (w vminus1) mixed MAA and organosolvpretreated wild grass (Achnatherum hymenoides) using statisti-cally designed Taguchi optimized fermentation process parametersnamely recombinant cellulase (GH5) recombinant hemicellulase(GH43) along with S cerevisiae C shehatae pH and temperatureat bioreactor level showing variation of (e) cell OD measuredat 600 nm (998771) ethanol concentration (g Lminus1) (998787) reducing sugar(g Lminus1) and (I) specific activity (Umgminus1) of GH5 cellulase with time(h) Similar specific activity profiles were obtained for recombinanthemicellulase (GH43) (data not shown)

maintained by 1 vvm aeration rate for the efficient growth ofbioethanol producers and in turn a good product yield Theethanol titre obtained in Taguchi optimized shake flask SSFwas 20 g Lminus1 (Table 3) implying a 13-fold rise as compared toethanol titre of 15 g Lminus1 (Table 3) in unoptimized shake flaskSSF A 15-fold upsurge in ethanol titre (31 g Lminus1) (Table 3)was obtained in lab scale bioreactor on scaling up the shakeflask SSF (20 g Lminus1) (Table 3) with Taguchi optimized SSFprocess parameters The dynamic profiles of various offlinemeasurements from various SSF batch runs established acomplex interplay between the rates of saccharification bythe mixed recombinant enzymes utilization of sugar bybioethanol producers and finally the formation of ethanolThe reducing sugar profile was inversely proportional to therate of ethanol formation The repressed enzyme activitiesin the later stages of fermentation might be attributed tosugar accumulation in the broth A depleted reducing sugarconcentration was observed without any further upturnin ethanol titre during the late log phase indicating thesugars utilization only for maintenance and endurance of thefermentative microbes

The ethanol titre values obtained in our research arecomparable with the findings reported in the literatureAn ethanol titre of 21 g Lminus1 has been reported from 1(w vminus1) mango leaves with recombinant GH43 hemicellulasefrom C thermocellum and C shehatae [3] The cocultureof C thermosaccharolyticum HG8 and Thermoanaerobacterethanolicus ATCC 31937 provided an ethanol concentration(22 g Lminus1) from 1 (w vminus1) of banana waste [30] The recom-binant cellulase from Clostridium thermocellum offered anethanol titre of 14 g Lminus1 from 1 (w vminus1) Jamun (Syzygiumcumini) leafy biomass [31] A SSF process from 6 (wwminus1)solka floc employing commercial cellulase andKluyveromyces

10 Journal of Fuels

marxianus contributed to an ethanol yield of 0337 (g gminus1)[27] An ethanol titre of 1 g Lminus1 from 1 (w vminus1) wheat strawusing crude unprocessed Trichoderma reesei cellulase hasbeen reported [32]

4 Conclusions

This study reported for the first time the statistical opti-mization and validation of different fermentation processparameters for bioethanol production frommixed MAA andorganosolv pretreated 1 (w vminus1) wild grass using Taguchiorthogonal array design namely mixed recombinant Cthermocellum hydrolytic enzymesrsquo volume along with mixedfermentative microbesrsquo inoculum volume pH and temper-ature The model was successfully validated at shake flasklevel with pH as the most significant factor Finally theoptimized process parameters were scaled up at bioreactorlevel with a gain of significant ethanol titre In essence thestatistical optimization of fermentation process parametersinvolving recombinant enzymes can transform the weed Ahymenoides into the fuel of tomorrow bioethanol

Conflict of Interests

The authors clearly state that they do not have any possibleconflict of interests with the mentioned commercial identi-ties

Acknowledgments

Mr Saprativ P Das is supported by PhD fellowship from theIndian Institute of Technology Guwahati throughMinistry ofHuman Resource and Development (MHRD) Governmentof India New Delhi India The research work in part issupported by a project Grant (BT23NETBP2010) fromDepartment of Biotechnology (DBT) Ministry of Scienceand Technology New Delhi India to Arun Goyal

References

[1] Y Sun and J Cheng ldquoHydrolysis of lignocellulosic materials forethanol production a reviewrdquo Bioresource Technology vol 83no 1 pp 1ndash11 2002

[2] M Ballesteros J M Oliva M J Negro P Manzanares and IBallesteros ldquoEthanol from lignocellulosic materials by a simul-taneous saccharification and fermentation process (SFS) withKluyveromyces marxianus CECT 10875rdquo Process Biochemistryvol 39 no 12 pp 1843ndash1848 2004

[3] S P Das R Ravindran S Ahmed et al ldquoBioethanol productioninvolving recombinant C thermocellum hydrolytic hemicel-lulase and fermentative microbesrdquo Applied Biochemistry andBiotechnology vol 167 pp 1475ndash1488 2012

[4] A L Demain M Newcomb and J H D Wu ldquoCellulaseclostridia and ethanolrdquo Microbiology and Molecular BiologyReviews vol 69 no 1 pp 124ndash154 2005

[5] N Adlakha R Rajagopal S Kumar V S Reddy and S SYazdani ldquoSynthesis and characterization of chimeric proteinsbased on cellulase and xylanase from an insect gut bacteriumrdquo

Applied and Environmental Microbiology vol 77 no 14 pp4859ndash4866 2011

[6] P Kumar D M Barrett M J Delwiche and P Stroeve ldquoMeth-ods for pretreatment of lignocellulosic biomass for efficienthydrolysis and biofuel productionrdquo Industrial and EngineeringChemistry Research vol 48 no 8 pp 3713ndash3729 2009

[7] K Grohmann E A Baldwin and B S Buslig ldquoProductionof ethanol from enzymatically hydrolyzed orange peel bythe yeast Saccharomyces cerevisiaerdquo Applied Biochemistry andBiotechnology vol 45-46 no 1 pp 315ndash327 1994

[8] A K Chandel R K Kapoor A Singh andR C Kuhad ldquoDetox-ification of sugarcane bagasse hydrolysate improves ethanolproduction by Candida shehatae NCIM 3501rdquo BioresourceTechnology vol 98 no 10 pp 1947ndash1950 2007

[9] M Latifian Z Hamidi-Esfahani and M Barzegar ldquoEvalu-ation of culture conditions for cellulase production by twoTrichoderma reesei mutants under solid-state fermentationconditionsrdquo Bioresource Technology vol 98 no 18 pp 3634ndash3637 2007

[10] K S Vishwanatha A G A Rao and S A Singh ldquoAcid proteaseproduction by solid-state fermentation using Aspergillus oryzaeMTCC 5341 optimization of process parametersrdquo Journal ofIndustrialMicrobiology andBiotechnology vol 37 no 2 pp 129ndash138 2010

[11] J AntonyMKaye andA Frangou ldquoA strategicmethodology tothe use of advanced statistical quality improvement techniquesrdquoTQMMagazine vol 10 no 3 pp 169ndash176 1998

[12] D H Stamatis TQM Engineering Handbook Marcel DekkerNew York NY USA 1977

[13] G Taguchi Introduction to Quality Engineering UNI-PUBKraus International White Plains NY USA 1986

[14] D M Byrne and S Taguchi ldquoThe Taguchi approach to param-eter designrdquo Quality Progress vol 20 no 12 pp 19ndash26 1987

[15] D De Oliveira and T L M Alves ldquoA kinetic study of lipase-catalyzed alcoholysis of palm kernel oilrdquo Applied Biochemistryand Biotechnology A vol 84ndash86 pp 59ndash68 2000

[16] E J Taylor A Goyal C I P D Guerreiro et al ldquoHow family 26glycoside hydrolases orchestrate catalysis on different polysac-charides structure and activity of a Clostridium thermocellumlichenase CtLic26Ardquo The Journal of Biological Chemistry vol280 no 38 pp 32761ndash32767 2005

[17] S Bharali R K Purama A Majumder C M G A Fontesand A Goyal ldquoMolecular cloning and biochemical propertiesof family 5 glycoside hydrolase of bi-functional cellulase fromClostridium thermocellumrdquo Indian Journal of Microbiology vol45 no 4 pp 317ndash321 2005

[18] L J Wickerman Taxonomy of Yeasts US Department ofAgriculture Technical Bulletin Washington DC USA 1951

[19] S Zhu Y Wu Z Yu et al ldquoProduction of ethanol frommicrowave-assisted alkali pretreated wheat strawrdquo Process Bio-chemistry vol 41 no 4 pp 869ndash873 2006

[20] A Geng F Xin and J-Y Ip ldquoEthanol production fromhorticultural waste treated by a modified organosolv methodrdquoBioresource Technology vol 104 no 7 pp 715ndash721 2012

[21] A Sluiter B Hames R Ruiz et al ldquoDetermination of structuralcarbohydrates and lignin in substratesrdquo Tech Rep NRELTP-510 Laboratory Analytical Procedure (LAP) Boulder ColoUSA 2008

[22] N Nelson ldquoA photometric adaptation of the Somogyi methodfor the determination of glucoserdquo The Journal of BiologicalChemistry vol 153 pp 375ndash380 1944

Journal of Fuels 11

[23] M Somogyi ldquoDetermination of blood sugarrdquo The Journal ofBiological Chemistry vol 160 pp 69ndash73 1945

[24] M M Bradford ldquoA rapid and sensitive method for the quanti-tation of microgram quantities of protein utilizing the principleof protein dye bindingrdquoAnalytical Biochemistry vol 72 no 1-2pp 248ndash254 1976

[25] V V R Bandaru S R Somalanka D R Mendu N RMadicherla and A Chityala ldquoOptimization of fermentationconditions for the production of ethanol from sago starch by co-immobilized amyloglucosidase and cells of Zymomonas mobilisusing response surface methodologyrdquo Enzyme and MicrobialTechnology vol 38 no 1-2 pp 209ndash214 2006

[26] H-B Seo H-J Kim O-K Lee J-H Ha H-Y Lee and K-H Jung ldquoMeasurement of ethanol concentration using solventextraction and dichromate oxidation and its application tobioethanol production processrdquo Journal of Industrial Microbi-ology and Biotechnology vol 36 no 2 pp 285ndash292 2009

[27] Z Kadar Z Szengyel and K Reczey ldquoSimultaneous saccha-rification and fermentation (SSF) of industrial wastes for theproduction of ethanolrdquo Industrial Crops and Products vol 20no 1 pp 103ndash110 2004

[28] Y Liang Z Feng J Yesuf and J W Blackburn ldquoOptimizationof growth medium and enzyme assay conditions for crudecellulases produced by a novel thermophilic and cellulolyticbacteriumAnoxybacillus sprdquoApplied Biochemistry andBiotech-nology vol 160 no 6 pp 1841ndash1852 2010

[29] S SanchezV Bravo E Castro A JMoya and FCamacho ldquoTheinfluence of pH and aeration rate on the fermentation of D-xylose byCandida shehataerdquo Enzyme andMicrobial Technologyvol 21 no 5 pp 355ndash360 1997

[30] Y Harish Kumar Reddy M Srijana D Madhusudhan Reddyand R Gopal ldquoCoculture fermentation of banana agro-waste toethanol by cellulolytic thermophilic Clostridium thermocellumCT2rdquo African Journal of Biotechnology vol 9 no 13 pp 1926ndash1934 2010

[31] R Mutreja D Das D Goyal and A Goyal ldquoBioconversion ofagricultural waste to ethanol by SSF using recombinant cellulasefrom Clostridium thermocellumrdquo Enzyme Research vol 2011Article ID 340279 6 pages 2011

[32] M Lever G Ho and R Cord-Ruwisch ldquoEthanol from lig-nocellulose using crude unprocessed cellulase from solid-statefermentationrdquo Bioresource Technology vol 101 no 18 pp 7094ndash7098 2010

TribologyAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

FuelsJournal of


Journal ofPetroleum Engineering


Industrial EngineeringJournal of


Power ElectronicsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in

CombustionJournal of


Journal of


Renewable Energy

Submit your manuscripts athttpwwwhindawicom


StructuresJournal of


RotatingMachinery


EnergyJournal of


Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal ofPhotoenergy


Nuclear InstallationsScience and Technology of


Solar EnergyJournal of


Wind EnergyJournal of


Nuclear EnergyInternational Journal of


High Energy PhysicsAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

2 Journal of Fuels

Temperature pH hydrolytic enzyme volume and fer-mentativemicrobersquos inoculum volume are the process param-eters that play a vital role in lignocellulosic ethanol pro-duction [9] The performance of multiple experiments byanalyzing one variable at a time (OVAT) approach is timeconsuming and laborious for identifying various indepen-dent variables with their effects [10] Statistically basedexperimental designs namely Plackett-Burman design Box-Behnken design and Taguchi orthogonal array designsummarize the collection and sorting of variables to betaken for consideration determine the variable amount andanalyze the variable at different parameters and finally theeffect of variable error Better quality at low cost is themain aim for generation of Taguchi design of experiments(DOE) approaches to maximize robustness of products andprocesses [11] Taguchi experimental design is a fast andconsiderable way of optimization conferring remarkableoutcome in simultaneous study of many factors making itsmark in quality products supplemented with better processperformance and rendering high yield and better stability[12 13] The basic principle involved is the encompassmentof large experimental data as orthogonal (unbiased) array indetermining the effect of various factors which govern thereaction happening ensuing in experimental error reductionwith improved producibility (efficiency) of experimentaloutcome Taguchi design established the importance of sta-tistically aligned experiments in speculating the settings ofproduct (andor processes) on various parameters [14 15]

The current study emphasizes the Taguchi optimizationof different fermentation process parameters such as mixedrecombinant enzymesrsquo volume (GH5 cellulase GH43 hemi-cellulase) mixed culturesrsquo inoculum volume (S cerevisiaeC shehatae) pH and temperature on bioethanol productionfrommixed pretreated wild grass with subsequent validationof the model at shake flask level and scale-up in a bioreactor

2 Materials and Methods

21 Reagents Chemicals and Substrate Carboxy methylcellulose (CMC) and rye arabinoxylan were purchased fromSigmaAldrich (St Louis USA)The analytical grade reagentsand chemicals namely LB medium ampicillin kanamycinsodium acetate glucose yeast extract peptone potassiumdichromate (K

2

Cr2

O7

) sodium carbonate sodium bicar-bonate sodium potassium tartrate sodium sulphate coppersulphate ammonium molybdate sodium arsenate phos-phoric acid and ethanol were purchased from Merck andHimedia Pvt Ltd India Coomassie brilliant blue G-250was purchased from Amresco LLC USA Lignocellulosicsubstrate wild grass (Achnatherum hymenoides) was collectedfrom the campus of Indian Institute of Technology GuwahatiIndia The substrate was washed with water thrice for theremoval of adhered dust particles dried and finally grindedto 1mmmesh size

22 Microorganisms and Culturing Conditions The recombi-nant E coli BL21 (DE3) cells harbouring family 5 glycosidehydrolase (GH5) gene from Clostridium thermocellum were

cloned in an expression vector pET-21a(+) and expressedearlier [16 17] The recombinant GH5 cellulase is availablecommercially at NZY Tech Lda Lisbon Portugal Therecombinant E coli BL21 (DE3) pLysS cells transformed byfamily 43 glycoside hydrolase (GH43) gene from Clostridiumthermocellum and cloned in pET-28a(+) expression vectorwere expressed earlier [3]These cells were cast off as a sourceof recombinant GH43 hemicellulase These E coli BL21 cellswere preserved in LB medium as glycerol stock at minus80∘C inour laboratory at IIT Guwahati

The fermentative microbes Saccharomyces cerevisiae(NCIM no 3215) and Candida shehatae (NCIM no 3500)procured from National Chemical Laboratory Pune Indiawere maintained independently at 4∘C on 5mL of Maltextract glucose yeast extract peptone (MGYP) slants contain-ingmalt extract (03 g 100mLminus1) glucose (1 g 100mLminus1) yeastextract (03 g 100mLminus1) and peptone (05 g 100mLminus1) [18]One loopful from these slant cultures was further introducedinto 50mL of glucose yeast extract (GYE) medium in twoseparate 100mL Erlenmeyer flasks containing glucose (1 g100mLminus1) and yeast extract (01 g 100mLminus1) with supple-mentation of KH

2

PO4

(01 g 100mLminus1) (NH4

)2

SO4

(05 g100mLminus1) and MgSO

4

sdot7H2

O (005 g 100mLminus1) They wereincubated at 30∘C and 120 rpm for 48 h prior to inoculationinto fermentation media The aliquots measuring 1mL fromeach of the actively growing cultures of S cerevisiae (39 times108 cellsmLminus1) and C shehatae (27 times 107 cellsmLminus1) were

aseptically inoculated to 100mL fermentation medium Thecell count of the actively growing S cerevisiae andC shehataewas measured using a haemocytometer

23 Production of Recombinant Cellulase (GH5) and Hemi-cellulase (GH43) The recombinant GH5 cellulase produc-tion was initiated by inoculating 50 120583L of the E coli BL21(DE3) culture from glycerol stocks into 5mL of LB mediumcontaining 100 120583gmLminus1 ampicillin with incubation at 37∘Cand 180 rpm for 16 h One percent (v vminus1) of the cultureinoculum was transferred aseptically to 200mL of LBmedium in 500mL flask containing 100120583gmLminus1 ampicillinand was incubated at 37∘C and 180 rpm till the culturereached the midexponential phase (A

600 nm 06) This mid-exponential phase culture was induced with isopropyl-120573-D-thiogalactopyranoside (IPTG) (1mM final concentration)followed by further 8 h incubation for overexpression ofrecombinant protein [16] 50 120583gmLminus1 kanamycin was usedas a selective marker for E coli BL21 (DE3) plysS cellscontaining GH43 hemicellulase [3] Similar production pro-cess was employed for GH43 hemicellulase as followed forGH5 cellulase except that the incubation period was 24∘C180 rpm and 24 h for overexpression of protein after IPTG(1mM final concentration) was added The overexpressed Ecoli cells (GH5 or GH43) collected by centrifugation (4∘C8510 g and 30min) were resuspended in 50mM sodiumphosphate buffer (pH 70) Each of the resuspended cellpellets was subjected to sonication (SONICS Vibra CellNewtown CT USA) in an ice-bath separately for 15minwith further centrifugation (4∘C 19650 g and 30min) The

Journal of Fuels 3













25

(65


25


4 Journal of Fuels








119878

119873

= minus10 log10

1

119899

119899

sum

119894=1

1

1199102

119894

(1)







Journal of Fuels 5





2

SO4


SO4


3






2

Cr2

O7


2

Cr2

O7





6 Journal of Fuels



of SSF














00

04

08

12

16

20

Time (h)0 20 40 60

00

04

08

12

16

20

00

02

04

06

08

Cel

l OD

at600

nm

0

1

2

3

4

5

6

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




Journal of Fuels 7






030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25


Etha

nol t

itre (

v

vminus1)


25





8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















Journal of Fuels 3













25

(65


25


4 Journal of Fuels








119878

119873

= minus10 log10

1

119899

119899

sum

119894=1

1

1199102

119894

(1)







Journal of Fuels 5





2

SO4


SO4


3






2

Cr2

O7


2

Cr2

O7





6 Journal of Fuels



of SSF














00

04

08

12

16

20

Time (h)0 20 40 60

00

04

08

12

16

20

00

02

04

06

08

Cel

l OD

at600

nm

0

1

2

3

4

5

6

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




Journal of Fuels 7






030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25


Etha

nol t

itre (

v

vminus1)


25





8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















4 Journal of Fuels








119878

119873

= minus10 log10

1

119899

119899

sum

119894=1

1

1199102

119894

(1)







Journal of Fuels 5





2

SO4


SO4


3






2

Cr2

O7


2

Cr2

O7





6 Journal of Fuels



of SSF














00

04

08

12

16

20

Time (h)0 20 40 60

00

04

08

12

16

20

00

02

04

06

08

Cel

l OD

at600

nm

0

1

2

3

4

5

6

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




Journal of Fuels 7






030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25


Etha

nol t

itre (

v

vminus1)


25





8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















Journal of Fuels 5





2

SO4


SO4


3






2

Cr2

O7


2

Cr2

O7





6 Journal of Fuels



of SSF














00

04

08

12

16

20

Time (h)0 20 40 60

00

04

08

12

16

20

00

02

04

06

08

Cel

l OD

at600

nm

0

1

2

3

4

5

6

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




Journal of Fuels 7






030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25


Etha

nol t

itre (

v

vminus1)


25





8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















6 Journal of Fuels



of SSF














00

04

08

12

16

20

Time (h)0 20 40 60

00

04

08

12

16

20

00

02

04

06

08

Cel

l OD

at600

nm

0

1

2

3

4

5

6

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




Journal of Fuels 7






030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25


Etha

nol t

itre (

v

vminus1)


25





8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















Journal of Fuels 7






030

025

020

015

010

005

000

1 3 5 7 9 11 13 15 17 19 21 23 25


Etha

nol t

itre (

v

vminus1)


25





8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















8 Journal of Fuels


Data means

C shehatae

S cerevisiae

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

minus14

minus15

minus16

minus17

minus18

GH5 cellulase

025 050 100 150 200

pH

30 43 50 55 60

Temperature

26 28 30 33 35

GH43 hemicellulase

025 050 100 150 200 025 050 100 150 200

025 050 100 150 200

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

sM

ean

ofSN

ratio

s

Mea

n of

SN

ratio

s

Mea

n of

SN

ratio

s










Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















Journal of Fuels 9







Experimentoptimum










Time (h)0 20 40 60

00

04

08

12

16

00

05

10

15

20

25

30

35

00

15

30

45

0

1

2

3

4

5

6

Cel

l OD

at600

nm

Etha

nol c

once

ntra

tion

(g Lminus1)

Redu

cing

suga

r (g L

minus1)

GH5

cellu

lase

activ

ity (U

mgminus

1)




10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















10 Journal of Fuels


4 Conclusions




Acknowledgments


References
























Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















Journal of Fuels 11















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of





















FuelsJournal of







Advances in



Journal of


Renewable Energy





RotatingMachinery


EnergyJournal of

















research article statistical optimization of fermentation...

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