02249nas a2200241 4500008004100000022001400041245010900055210006900164260009900233300001400332490000700346520131600353653001801669653002401687653003301711653002101744100002401765700002801789700002201817700002101839700002101860856012601881 2008 eng d a0960-852400aUse of response surface optimization for the production of biosurfactant from rhodococcus spp. MTCC 25740 aUse of response surface optimization for the production of biosu aTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLANDbELSEVIER SCI LTDcNOV a7875-78800 v993 a

The production of biosurfactant from Rhodococcus spp. MTCC 2574 was effectively enhanced by response surface methodology (RSM). Rhodococcus spp. MTCC 2574 was selected through screening of seven different Rhodococcus strains. The preliminary screening experiments (one-factor at a time) suggested that carbon source: mannitol, nitrogen source: yeast extract and meat peptone and inducer: n-hexadecane are the critical medium components. The concentrations of these four media components were optimized by using central composite rotatable design (CCRD) of RSM. The adequately high R-2 value (0.947) and F score 19.11 indicated the statistical significance of the model. The optimum medium composition for biosurfactant production was found to contain mannitol (1.6 g/L), yeast extract (6.92 g/L), meat peptone (19.65 g/L), n-hexadecane (63.8 g/L). The crude biosurfactant was obtained from methyl tert-butyl ether extraction. The yield of biosurfactant before and after optimization was 3.2 g/L of and 10.9 g/L, respectively. Thus, RSM has increased the yield of biosurfactant to 3.4-fold. The crude biosurfactant decreased the surface tension of water from 72 mN/m to 30.8 mN/m (at 120 mg L-1) and achieved a critical, micelle concentration (CMC) value of 120 mg L-1. (C) 2008 Published by Elsevier Ltd.

10aBiosurfactant10aMedium optimization10aResponse surface methodology10aRhodococcus spp.1 aMutalik, Snehal, R.1 aVaidya, Bhalchandra, K.1 aJoshi, Renuka, M.1 aDesai, Kiran, M.1 aNene, Sanjay, N. uhttps://library.ncl.res.in/content/use-response-surface-optimization-production-biosurfactant-rhodococcus-spp-mtcc-2574-002362nas a2200277 4500008004100000022001400041245014500055210006900200260008000269300001200349490000700361520130400368653003001672653001801702653002201720653002301742653003301765653001601798100002101814700002801835700002101863700002201884700002101906700002601927856013101953 2009 eng d a1367-543500aMedia optimization for biosurfactant production by rhodococcus erythropolis MTCC 2794: artificial intelligence versus a statistical approach0 aMedia optimization for biosurfactant production by rhodococcus e aTIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANYbSPRINGER HEIDELBERGcMAY a747-7560 v363 a

This paper entails a comprehensive study on production of a biosurfactant from Rhodococcus erythropolis MTCC 2794. Two optimization techniques-(1) artificial neural network (ANN) coupled with genetic algorithm (GA) and (2) response surface methodology (RSM)-were used for media optimization in order to enhance the biosurfactant yield by Rhodococcus erythropolis MTCC 2794. ANN and RSM models were developed, incorporating the quantity of four medium components (sucrose, yeast extract, meat peptone, and toluene) as independent input variables and biosurfactant yield [calculated in terms of percent emulsification index (% EI24)] as output variable. ANN-GA and RSM were compared for their predictive and generalization ability using a separate data set of 16 experiments, for which the average quadratic errors were similar to 3 and similar to 6%, respectively. ANN-GA was found to be more accurate and consistent in predicting optimized conditions and maximum yield than RSM. For the ANN-GA model, the values of correlation coefficient and average quadratic error were similar to 0.99 and similar to 3%, respectively. It was also shown that ANN-based models could be used accurately for sensitivity analysis. ANN-GA-optimized media gave about a 3.5-fold enhancement in biosurfactant yield.

10aArtificial neural network10aBiosurfactant10aGenetic algorithm10aMedia optimization10aResponse surface methodology10aRhodococcus1 aPal, Moumita, P.1 aVaidya, Bhalchandra, K.1 aDesai, Kiran, M.1 aJoshi, Renuka, M.1 aNene, Sanjay, N.1 aKulkarni, Bhaskar, D. uhttps://library.ncl.res.in/content/media-optimization-biosurfactant-production-rhodococcus-erythropolis-mtcc-2794-artificial-001982nas a2200241 4500008004100000022001400041245016500055210006900220260009900289300001400388490000800402520103100410653001801441653001201459653001801471653002601489653002501515100001801540700001801558700002101576700001401597856012901611 2010 eng d a0960-852400aBiocatalytic approach for the utilization of hemicellulose for ethanol production from agricultural residue using thermostable xylanase and thermotolerant yeast0 aBiocatalytic approach for the utilization of hemicellulose for e aTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLANDbELSEVIER SCI LTDcJUL a5366-53730 v1013 a

A hydrolysis of 62% and 50% for OSX (Oat spelt xylan) and WBH (Wheat bran hemicellulose) were obtained in 36 h and 48 h using Accellerase(TM) 1000 at 50 degrees C wherein thermostable xylanase from alkalothermophilic Thermomonospora sp. yielded 67% (OSX) in 3 h and 58% (WBH) in 24 h at 60 degrees C, favouring a reduction in process time and enzyme dosage. The rate of hydrolysis with thermostable xylanase was increased by 20% with the addition of nonionic surfactant tween 80 or biosurfactant sophorolipid. The simultaneous saccharification and fermentation (SSF) of OSX and WBH using thermostable xylanase and D. hansenii in batch cultures produced 9.1 g/L and 9.5 g/L of ethanol, respectively and had a shorter overall process time than the separate hydrolysis and fermentation (SHF). The immobilized yeast cells in Ca-alginate matrix produced ethanol with a yield of 0.46 g/g from hemicellulosic hydrolysates and were reused six times with 100% fermentation efficiency. (C) 2010 Elsevier Ltd. All rights reserved.

10aBiosurfactant10aEthanol10aHemicellulose10aThermostable xylanase10aThermotolerant yeast1 aMenon, Vishnu1 aPrakash, Gyan1 aPrabhune, Asmita1 aRao, Mala uhttps://library.ncl.res.in/content/biocatalytic-approach-utilization-hemicellulose-ethanol-production-agricultural-residue-002364nas a2200289 4500008004100000022001400041245012000055210006900175260000800244300000600252490000700258520141400265653001801679653001101697653001601708653001901724653002101743100001601764700003101780700002901811700001901840700002301859700002101882700002201903700001801925856013101943 2021 eng d a0025-323500aRhamonolipids produced by Pseudomonas aeruginosa promotes methane hydrates formation in fixed bed silica gel medium0 aRhamonolipids produced by Pseudomonas aeruginosa promotes methan cMAR a50 v423 a

Natural gas hydrates are seen as an alternative future energy source. They have also been valued for their carbon dioxide capturing capability, gas separation, desalination, natural gas storage and transportation. Developing economical and viable gas hydrate based technology is one of the most promising research areas of present decade. Successful commercialization of gas hydrate based technology is often curtailed due to slow formation rate. The present study evaluates biosurfactant as a kinetic promoter of methane hydrates formation in a fixed bed C type silica gel medium. Biosurfactant was produced by growing Pseudomonas aeruginosa strain A11 in glycerol supplemented mineral salt medium. Biosurfactant characterization with FTIR, NMR and MALDI-TOF spectroscopy reveled it to be a glycolipids type biosurfactant namely rhamnolipids. Saturating C type silica gel with of 100 ppm rhamnolipids solution enhanced the rate of methane hydrates formation by reducing the induction time. Mole of methane consumed and percentage of water to hydrate conversion was observed to be more in 1000 ppm rhamnolipids saturated C type silica gel as compared to quiescent water system and water saturated silica gel system. Overall results suggest that rhamonolipids produced by strain A11 in combination with silica gel can be utilized as environmentally safe kinetic promoter for methane hydrate formation.

10aBiosurfactant10aEnergy10aGlycolipids10aInduction time10aKinetic promoter1 aArora, Amit1 aCameotra, Swaranjit, Singh1 aBalomajumder, Chandrajit1 aKumar, Rajnish1 aSingh, Anil, Kumar1 aSanthakumari, B.1 aKumar, Pushpendra1 aLaik, Sukumar uhttps://library.ncl.res.in/content/rhamonolipids-produced-pseudomonas-aeruginosa-promotes-methane-hydrates-formation-fixed-bed