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Optimizing alpha-amylase from Bacillus amyloliquefaciens on bread waste for effective industrial wastewater treatment and textile desizing through response surface methodology

Article scientifique 2023 Anglais

Résumé

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 amyloliquefaciens showed the highest starch hydrolysis and enzyme activity on solid and liquid media. α-amylase production by B. amyloliquefaciens 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. amyloliquefaciens 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 R 2 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.

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Abd-Elhalim, B., Gamal, R., El-Sayed, S., Abu-Hussien, S. (2023). Optimizing alpha-amylase from Bacillus amyloliquefaciens on bread waste for effective industrial wastewater treatment and textile desizing through response surface methodology. https://doi.org/10.1038/s41598-023-46384-6

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