Optimizing alpha-amylase from Bacillus amyloliquefaciens on bread waste for effective industrial wastewater treatment and textile desizing through response surface methodology
Abd-Elhalim, Basma T.; Gamal , Rawia F.; Salwa M. El-sayed; Abu-Hussien, Samah H;
Abstract
Food waste is a major issue, with one-third of food wasted yearly. This study aimed to produce sustainably the industrial enzyme alpha-amylase using discarded bread waste. Brown (BBW) and white bread waste (WBW) were tested as growth substrates using solid-state and submerged fermentation. The biosynthesized α- amylase is applied to treat starch-heavy industrial wastewater and for textile desizing. Bacillus amyloliquificiens showed the highest starch hydrolysis and enzyme activity on solid and liquid media. α-amylase production by B. amyloliquificiens was optimized via a one-factor-at-a-time evaluation of production parameters. Optimal production occurred by submerged fermentation of BBW inoculated with 2% B. amyloliquificiens at 37 °C and 200rpm for 24 h, reaching 695.2 U/mL α- amylase. The crude enzyme was immobilized on calcium alginate beads with 96.6% efficiency and kept 88.5% activity after 20 reuses, enhancing stability. A Box-Behnken design (BOX) assessed variable interactions. Response surface methodology (RSM) generated a quadratic model and analysis of variance (ANOVA analysis) fitting experimental starch hydrolysis data. Optimal conditions were pH 9, 45 °C, 70% starch, and 27.5 U/mL enzyme incubated for 15 min of contact time, with a high R2 of 0.83. ANOVA confirmed the enzyme's alkaliphilic and thermophilic nature. Using enzyme concentrations ranging from 10.9 to 695.1 U/mL, the enzyme desized textiles in 15 min at pH 9.0 and 45 °C with 96.3% efficiency. Overall, the optimized α- amylase from bread waste has industrial potential for sustainable starch processing.
Other data
Title | Optimizing alpha-amylase from Bacillus amyloliquefaciens on bread waste for effective industrial wastewater treatment and textile desizing through response surface methodology | Authors | Abd-Elhalim, Basma T. ; Gamal , Rawia F. ; Salwa M. El-sayed ; Abu-Hussien, Samah H | Issue Date | 6-Nov-2023 | Journal | Scientific Reports | ISSN | 2045-2322 | DOI | 10.1038/s41598-023-46384-6 | PubMed ID | 37932353 | Scopus ID | 2-s2.0-85175826002 |
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