Modeling Embedded Optimization Strategy for the Formulation of Bacterial Lipase-Based Biodetergent

Abstract

Lipase-based detergent formulations are a viable substitute for chemical detergents that pose health and environmental hazards to customers and society. In this study, the efficacy of Staphylococcus arlettae JPBW-1 lipase as an additive in laundry detergent was assessed for oil removal through modeling and optimization using a response-surface-methodologyintegrated genetic algorithm. A three-level five-factorial central composite design was used to evaluate the interactive effects on oil removal percentage from cotton fabric of process conditions, namely, detergent concentration, lipase concentration, buffer pH, washing temperature, and washing time. The input space of the validated response surface methodology (RSM) model (R 2 value of 97.7%) was utilized for genetic algorithm (GA) optimization. An optimum value of 79.6% oil removal was achieved with the GA-predicted process variables of 0.69% detergent, 47.37 U of lipase, buffer pH of 7.2, and washing temperature of 37.18°C in 26.11 min, which was 27% more than the oil removal without lipase. Hence, lipase from S. arlettae JPBW-1 can be effectively used as an additive in laundry detergent for oil removal from soiled fabric and introduces a new lipase into the biobased detergent industry.

Realm of Thermoalkaline Lipases in Bioprocess Commodities

“…TA lipases are very stable at high temperature and alkaline environment which is the optimum condition required for maximal cleaning process. Most of them are also compatible with detergents components and resistant to inhibition [ 22 , 24 , 25 , 50 ]. TA lipases are also available in their natural free form, soluble, and readily incorporated in liquid-based detergent [ 35 , 83 ].…”

“…On the contrary, TA lipase from Bacillus stearothermophilus showed its stability and compatibility with commercial detergents [ 26 ]. BSK-L lipase was very stable when formulated in detergent and its components such as oxidising agents and surfactants, hence, help to improve detergent effectiveness and washing performance in removing oil stains [ 22 ]. In dishwashing experiment, T1 lipase was proven to be stable in most nonionic surfactants and a mixture of sodium carbonate (Na 2 CO 3 ) and glycine (Gly) [ 52 , 53 ].…”

Bioprocessing of wheat bran for the production of lignocellulolytic enzyme cocktail byCotylidia pannosaunder submerged conditions

“…Response surface methodology (RSM) is a well-practiced one for creation of a process model in the form of a non-linear regression equation by considering the effect of individual, square and interaction terms of process variables on the ouput. [16][17][18] Moreover, the response optimizer function of RSM will be helpful for predicting the process variables for getting optimum output. A white rot fungus Cotilydia pannosa reported in our recent work, possessing cellulase and xylanase activities along with the laccase activity.…”

Enhancing the Production of Therapeutic Enzyme Arginase from Lactobacillus acidophilus Using Response Surface Methodology

“…The predictive ability of developed models and results of CCD were further confirmed through statistical significance tests and ANOVA [27,34,35]. Significance test results for arginase activity are tabulated in Table 3 and ANOVA test results are tabulated in Table 4.…”

“…The model F-value of 7.26 implies that the model is significant [34,37]. In this case, the variables that seemed to have a significant effect ("Prob>F" is less than 0.0500) were an individual effect of arginine, interaction effect of yeast extract, and pH and squared effects of arginine and pH.…”