A STATISTICAL AND MICROBIAL STUDY: ROSE FLOWER WASTE INTO BIOETHANOL

The utilization of beet molasses as a novel carbon source for cephalosporin C production by Acremonium chrysogenum: Optimization of process parameters through statistical experimental designs

Optimization of bioethanol production from glycerol by Escherichia coli SS1

Response surface optimization of bioethanol production from third generation feedstock - Eucheuma cottonii

The sustainability of any symbolic development is hinged on renewable energy like bioethanol. This study investigated the applicability of corn steep liquor (CSL) as both carbon and nitrogen sources in bioethanol production using Saccharomyces cerevisiae. The CSL used was characterized to ascertain its physical and chemical properties. The CSL was first applied in place of yeast extract in the inoculum medium and later applied in the fermentation medium, acting as both carbon and nitrogen sources. Box-Behnken design was used to develop the optimal variables (time, substrate concentration (CSL ratio), and pH) affecting the fermentation process. From the results, the analyzed CSL sample contained a total carbon-to-n for bioethanol production using the Box-Behnken design are CSL of 17.70 (v/v), time of 22.8 h, and pH of 5 with a corresponding bioethanol amount of 17.70 (v/v), time of 22.8 h, and pH of 5 with corresponding bioethanol amount of 9.49 g/L and reducing sugar of 1.59 g/L. This study shows that CSL could serve a dual purpose as a carbon and nitrogen source in microbial fermentation process, thereby reducing the overall cost of setting up a bioethanol production plant.

Optimization of solid-state medium for the production of inulinase by Aspergillus ficuum JNSP5-06 using response surface methodology

Optimization of solid-state medium for the production of inulinase by Kluyveromyces S120 using response surface methodology

The present study explores the potential of Rosa indica flower waste as a renewable feedstock for bioethanol production. The bioethanol fermentation process was carried out using Saccharomyces cerevisiae. Both chemically pretreated and untreated rose flower waste hydrolysates were employed as primary carbon sources under submerged fermentation conditions. Process optimization was conducted using the One-Variable-at-a-Time (OVAT) approach to enhance bioethanol yield. The maximum bioethanol concentration of 28.2 g/L was achieved under optimal conditions: 6 g% substrate concentration, 1.5 g% of fructose supplementation, 0.5 mL % corn steep liquor as a nitrogen source, 4 mL % inoculum size, pH 5.5, temperature of 30 °C and an incubation period of 3 days. These results indicate that the optimized fermentation process significantly improves bioethanol production from rose flower waste, highlighting its potential as a sustainable biofuel source.

Bioethanol production has seen an increasing trend in research recently, with a focus on increasing its economic viability. The aim of this study is to develop a low-cost fermentation medium with a minimum of redundant nutritional supplements, thereby minimizing the costs associated with nutritional supplements and seed production. Corn steep liquor (CSL) in glucose fermentation by Saccharomyces Type 1 (ST1) strain and Anchor Instant Yeast (AIY), which are low-cost media, is used as a replacement for yeast extract (YE). The fermentation process parameters were optimized using artificial neural networks (ANN) and the response surface method (RSM). The study shows that for CSL, maximum average ethanol concentrations of 41.92 and 45.16 g/L, representing 82% and 88% of the theoretical yield, were obtained after 36 h of fermentation in a shake flask for ST1 and AIY, respectively. For YE, ethanol concentrations equivalent to 86% and 88% of theoretical yield were obtained with ST1 and AIY, respectively after 48 h. Although ANN better predicted the responses compared to RSM, optimum conditions were better predicted by RSM. This study shows that corn steep liquor is an inexpensive potential nutrient that may have significant cost implications for commercial ethanol production.

Statistical experimental designs and response surface methodology were employed to optimize the concentrations of agroindustrial residues as soybean oil (SORR) from refinery, and corn steep liquor (CSL) from corn industry, for tensio-active agent produced by Candida sphaerica UCP 0995. Three 22 full factorial design were applied sequentially to investigate the effects of the concentrations and interactions of soybean oil refinery residue and corn steep liquor on the surface tension of free-cell culture broth for 144 h. Two 22 central composite designs and response surface methodology were adopted to derive a statistical model to measure the effect of SORR and CSL on the surface tension of the free-cell culture broth for 144 h. The regression equation obtained from the experimental data using a central composite design was solved, and by analyzing the response surface contour plots, the optimal concentrations of the constituents of the medium were determined: 8.63% v/v (≅9% v/v) of SORR and 8.80% v/v (≅9% v/v) CSL. The minimum surface tension predicted and experimentally confirmed was 25.25 mN/m. The new biosurfactant, denominated Lunasan, recovered 95% of motor oil adsorbed in a sand sample, thus showing great potential for use in bioremediation processes, especially in the petroleum industry.

β-Glucosidase from novel bacteria Zobellella denitrificans VIT SB117 was isolated, and to increase the production of the enzyme, various growth parameters of the bacteria were optimized. Plackett–Burman design and response surface methodology helped determine the most significant parameters (fructose, temperature, and culture volume) resulting in a 10-fold increase in enzyme activity. The enzyme was purified and kinetics study for free and immobilized enzyme revealed Km of 4.76 mM and 8.39 mM, Kcat of 255.02 s−1 and 114.02 s−1, and Vmax of 4.33 mg/s and 1.25 mg/s, respectively. Enzyme characterization determined optimum substrate concentration and incubation time as 3.5 mM and 10 min respectively for the free enzyme, and 4 mM and 20 min respectively for the immobilized enzyme for maximum activity. pH 5, 45 °C incubation temperature and addition of Mg2+ and Mn2+ ions exhibited similar stimulatory effects on free and immobilized enzyme activities while Hg2+ ions showed strong inhibitory effects. The immobilized enzyme had negligible loss of activity after a month’s storage at 2–4 °C in acetate buffer and ~ 27.76% residual activity after 17 continuous cycles. These optimized parameters were employed for bioethanol production from lignocellulosic wastes. A total cellulose recovery of 52.77% was achieved after pretreatment. Release of ~ 57 mg/g substrate reducing sugars was achieved by enzymatic hydrolysis using immobilized cellulase enzyme complex that produced ~ 5.46 mg/ml bioethanol after 144 h of fermentation using yeast.

The research focuses on the synthesis of syngas from lignocellulosic biomass via co-gasification, employing response surface methodology. In addition, the study aims to optimize syngas fermentation efficiency for bioethanol production, utilizing two species of microorganisms – Saccharomyces cerevisiae and Clostridium butyricum – within an integrated biorefinery framework. The raw syngas was generated through the co-gasification of empty fruit bunches and charcoal mixtures (75:25). The optimal ratio of these components was determined via central composite design. The individual performances of S. cerevisiae and C. butyricum, as well as their co-fermentation, were thoroughly investigated, considering parameters such as colony forming units (CFU), pH, total organic carbon (TOC), and syngas flow rate. Morphological features of microorganisms during syngas fermentation were characterized using field emission scanning electron microscopy analysis. The results indicated that the highest bioethanol concentration, reaching 31.20 mmol, was achieved through co-fermentation as opposed to single-inoculum fermentation. Furthermore, a significant increase (3.08%) in bioethanol productivity was observed when the syngas flow rate was elevated from 50 to 1000 mL/min. Therefore, microbial co-fermentation emerges as a promising strategy to enhance bioethanol production from syngas derived from lignocellulosic biomass. Highlights Parametric optimization for co-gasification using response surface methodology Syngas was co-fermented using Saccharomyces cerevisiae and Clostridium butyricum Effects of syngas (CFU, pH, and TOC) were investigated during co-fermentation Bioethanol production increased 3.08% when syngas flowrate increased from (50 to 1000 mL/min)

Optimization of β-carotene production from agro-industrial by-products by Serratia marcescens ATCC 27117 using Plackett–Burman design and central composite design

Experimental optimization of thermochemical pretreatment of sal (Shorea robusta) sawdust by Central Composite Design study for bioethanol production by co-fermentation using Saccharomyces cerevisiae (MTCC-36) and Pichia stipitis (NCIM-3498)

Response surface methodology was applied to identify and optimize the medium composition for the cis-epoxysuccinate hydrolase production in recombinantEscherichia coli. Plackett-Burman design was used in the first step to evaluate the effects of 8 variables on the enzyme activity. CaCl2, corn steep liquor and lactose were screened as significant factors and their concentrations were further optimized using response surface methodology based on 23 full factorial rotatable central composite design. The optimum predicted medium for maximum expression of recombinant cis-epoxysuccinate hydrolase was found to comprise: 17.1 g/l Na2HPO4·12H2O, 2.0 g/l KH2PO4, 0.5 g/l NaCl, 1.0 g/l NH4Cl, 0.0111 g/l CaCl2 and 0.5 g/l MgSO4·7H2O, 17.18 ml/l corn steep liquor and 9.74 g/l lactose, with a predicted enzyme activity of 35490 U/g biomass, which was very close to the experimental activity of 36318 U/g biomass resulting in 1.7-fold increment after optimization.   Key words: Medium, optimization, response surface methodology, cis-epoxysuccinate hydrolase, Escherichia coli.

In view of the large number of microparameters of the flat-joint model (FJM) and the inefficiency of the calibration process, this paper uses the Plackett-Burman (PB) design, response surface methodology (RSM), and optimization techniques to calibrate the FJM3D. The values of each lower and upper bound in the PB design are selected based on the relationship between 10 microparameters and the UCS, BTS, UCS/BTS, elastic modulus E, Poisson’s ratio υ, Hoek-Brown strength parameter mi, average coordination number (CN), and crack initiation stress σci. Then, the PB design is used in the sensitivity analysis to screen out the three most influential factors for each response for the central composite design (CCD). The three microparameters most influencing E are the effective modulus Empb, the ratio of the normal to shear stiffness KnKs, and the installation gap ratio Gapr; the three microparameters most influencing υ are KnKs, the mean bond cohesion strength Coh, and Empb; the three microparameters most influencing UCS are Coh, Gapr, and the mean bond tensile strength Mbts; and the three microparameters most influencing BTS are Mbts, KnKs, and the residual friction angle Rfa. CCD analysis reveals that there are interaction effects between the FJM3D microparameters and the real effect of each microparameter differs at different levels of other microparameters. The linear and nonlinear equations obtained by fitting the PB design and the CCD design are applied as constraints to the optimization problem, and the problem of obtaining the best set of FJM3D microparameters is solved. The optimal sets were successfully matched for a variety of rock types from both the FJM3D simulations and experiments, and Lac du Bonnet granite was used as an example to compare the strength, deformation characteristics, and rock failure modes. This method can be used as a new way to quickly calibrate the microparameters of the FJM3D.