Amrita Ranjan

Publications (11) View all

• Article: Development of Semi-defined Rice Straw Based Medium for Butanol Production and Its Kinetic Study

  Amrita Ranjan, Rahul Mayank, V.S. Moholkar
  3biotech. 11/2012;
• Article: Process Optimization for Butanol Production from Developed Rice Straw Hydrolysate using Clostridium acetobutylicum MTCC 481 Strain

  Amrita Ranjan, Rahul Mayank, VS Moholkar
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  ABSTRACT: In this study, an attempt is made to optimize the effect of various physical and cultural parameters on butanol production by microbial strain C. acetobutylicum MTCC 481 by employing L18 orthogonal array design of experiments. A set of five parameters, viz. temperature, pH, inoculum size, inoculum age and agitation have been studied. Utilizing a pre-optimized RSH medium, the clostridial strain produced maximum amount of butanol at optimum conditions of temperature 37°C, pH 4.0 ± 0.5, inoculum size 5% (v/v), inoculum age 18 h, and agitation 150 rpm. Among these parameters, pH, temperature, and agitation were found to be the most significant factors affecting solvent production. The optimized physical and cultural parameters were further verified at shake flask and bioreactor scale (2 L and 5 L bioreactor). Experiments using 2 L and 5 L bioreactor under the optimized process condition showed nearly complete utilization of soluble sugars with the production of 15.84 g L-1 of total solvents with 12.17 g L-1 of butanol in 2 L bioreactor, and 16.91 g L-1 of total solvents with 12.22 g L-1 of butanol in a 5 L of bioreactor, respectively. The experimental data was further validated by fitting it to a kinetic model reported in literature to determine the kinetic parameters of the fermentation process.
  Biomass conversion and biorefinery. 11/2012;
• Article: Mathematical models of ABE fermentation: review and analysis.

  Rahul Mayank, Amrita Ranjan, Vijayanand S Moholkar
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  ABSTRACT: Among different liquid biofuels that have emerged in the recent past, biobutanol produced via fermentation processes is of special interest due to very similar properties to that of gasoline. For an effective design, scale-up, and optimization of the acetone-butanol-ethanol (ABE) fermentation process, it is necessary to have insight into the micro- and macro-mechanisms of the process. The mathematical models for ABE fermentation are efficient tools for this purpose, which have evolved from simple stoichiometric fermentation equations in the 1980s to the recent sophisticated and elaborate kinetic models based on metabolic pathways. In this article, we have reviewed the literature published in the area of mathematical modeling of the ABE fermentation. We have tried to present an analysis of these models in terms of their potency in describing the overall physiology of the process, design features, mode of operation along with comparison and validation with experimental results. In addition, we have also highlighted important facets of these models such as metabolic pathways, basic kinetics of different metabolites, biomass growth, inhibition modeling and other additional features such as cell retention and immobilized cultures. Our review also covers the mathematical modeling of the downstream processing of ABE fermentation, i.e. recovery and purification of solvents through flash distillation, liquid-liquid extraction, and pervaporation. We believe that this review will be a useful source of information and analysis on mathematical models for ABE fermentation for both the appropriate scientific and engineering communities.
  Critical Reviews in Biotechnology 10/2012; · 6.47 Impact Factor
• Article: Feasibility of Rice Straw as Alternate Substrate for Biobutanol Production

  Amrita Ranjan, Swati khanna, vs Moholkar
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  ABSTRACT: Biobutanol has recently emerged as a potential alternate liquid fuel for gasoline and diesel. In this work, we have studied clostridial fermentation of stress assisted-acid hydrolyzed rice straw that exhibited a typical trend of acidogenesis followed by solventogenesis. Acid hydrolysis of 5% (w/v) mixture of rice straw in water with simultaneous application of shearing stress resulted in release of 3.9% (w/v) total sugar out of which 3.1% (w/v) was reducing sugar. Glucose formed major fraction (75%) of the reducing sugar (or 2.3% w/v total sugar). Thus, essentially, 5% (w/v) of rice straw solution released nearly 46% (w/w) (i.e. 23 gL-1 glucose for 50 gL-1 rice straw solution) glucose. Anaerobic fermentation of rice straw hydrolyzate using Clostridium acetobutylicum NCIM 2337 resulted in production of 6.24 gL-1 of acetone, 13.5 g L-1 of butanol and only 0.82 gL-1 of ethanol. The net consumption of substrates was as follows: glucose 12.86 gL-1 (i.e. ~ 55%), total reducing sugar 18.32gL-1 (~ 57%) and total sugar 24.5gL-1 (~ 61%). Thus, higher solvents yield and significant sugar utilization makes rice straw a potential feedstock for biofuels production.
  Applied Energy 01/2012; · 5.11 Impact Factor
• Article: Mathematical Models of ABE Fermentation: Review and Analysis

  Rahul Mayank, Amrita Ranjan, VS Moholkar
  [show abstract] [hide abstract]
  ABSTRACT: Among different liquid biofuels that have emerged in recent past, biobutanol produced via fermentation process is of special interest due to very similar properties as that of gasoline. For an effective design, scale-up, and optimization of the ABE fermentation process, it is necessary to have an insight into the micro- and macro-mechanism of the process. The mathematical models for ABE fermentation are efficient tools for this purpose, which have evolved from simple stoichiometric fermentation equations in the 1980s to the recent sophisticated and elaborate kinetic models based on metabolic pathway. In this paper, we have reviewed the literature published in the area of mathematical modeling of the ABE fermentation. We have tried to present an analysis of these models in terms of their potency in describing the overall physiology of the process, design features, mode of operation along with comparison and validation with experimental results. In addition, we have also highlighted important facets of these models such as metabolic pathway, basic kinetics of different metabolites, biomass growth, and inhibition modeling and other additional features such as cell retention and immobilized cultures. Our review also covers the mathematical modeling of the downstream processing of ABE fermentation, i.e. recovery and purification of solvents through flash distillation, liquid-liquid extraction, and pervaporation. We believe that this review will be useful source of information and analysis on mathematical models for ABE fermentation for both scientific and engineering community in this area.
  Critical Reviews in Biotechnology 01/2012; · 6.47 Impact Factor