A Two-Level Factorial Design for Screening Factors that Influence the Growth of Bacillus sp. Strain ZEID-14 on Acrylamide (Journal of Environmental Bioremediation and Toxicology, 2022)
Acrylamide is often used to strengthen soil structure and usually leachate from this application forms a major source of acrylamide pollution in the environment. The soil matrix means physicochemical methods of removal will be costly if not difficult. Bioremediation using acrylamide-degrading bacteria is an appealing technique. In this investigation, a previously isolated molybdenum-reducing bacterium with the ability to degrade amides was discovered based on critical characteristics contributing to optimal growth on acrylamide utilizing a two-level factorial design. Five independent parameters that influence the growth of the bacterium on acrylamide were evaluated using a two-level factorial design. Among these variables are pH, temperature, incubation period, acrylamide content, and glucose concentration. The two-factor factorial design was successful in identifying significant contributing parameters to the growth of this bacterium on acrylamide, namely acrylamide concentration, pH, and incubation time, which can be further otpimized using RSM in future studies. Using ANOVA, Pareto's chart, perturbation's plot, and other diagnostic plots, the significant contributing factors or parameters were examined. Half-normal, Cook's distance, residual vs runs, leverage versus runs, Box-Cox, DFFITS, and DFBETAS diagnostic plots all supported the two-level factorial result. This work was conducted using acrylamide concentrations well within the known tolerance range of most acrylamide-degrading bacteria. Incubation time is an expected consequence, as longer incubation time permits more growth. The majority of acrylamide-degrading microorganisms thrive under near-neutral circumstances, as indicated by the results of our investigation, which are consistent with previous literature trends.
Keywords: Acrylamide; Bioremediation; Bacillus sp.; Screening; Two-level factorial design