Biovalorization of the raw agro-industrial waste rice husk through directed production of xylanase byThermomyces lanuginosusstrain A3-1 DSM 105773: a statistical sequential model

The current work addresses a statistically optimized, economic, and efficient approach for the professional valorization of the massively accumulated non-efficiently utilized, raw agro-industrial waste rice husk (RH).Thermomyces lanuginosusstrain A3-1 DSM 105773, a locally isolated strain, was employed for directed production of xylanase, an industrially important enzyme upon growing on RH-based medium. A three-step empirical sequential, statistical approach-one variable at a time (OVAT), Plackett-Burman design (PBD), and Box-Behnken design (BBD)-was employed to optimize the xylanase production through liquid-state fermentation of rice husk. Incubation temperature (50 degrees C) and ammonium sulfate concentration as an inorganic nitrogen source were the most appropriate parameters triggering the production of xylanase, deduced from OVAT. The three key determinants RH concentration, initial pH of the production medium, and incubation time did exhibit significant influences (P <= 0.001) on the production of xylanase, deduced from PBD. By the end of the optimization process, the optimal levels of RH, initial pH of the production medium, and incubation time were 3.8% (w/v), 4.5, and 8 days, respectively, with an agitation speed of 120 rpm to achieve a maximal xylanase level of 0.8344 U/mL with a fivefold enhancement deduced from the estimated ridge of the canonical path. Present data would reinforce the scaling up of xylanase production using the present powerful and reproducible approach for the simultaneous and proficient valorization of RH and production of xylanase for further exploitation in food, pharmaceutical, and textile industries.

Automated summary

This work presents a statistically optimized and efficient approach for the valorization of rice husk waste through directed production of xylanase using a locally isolated strain. By employing a three-step statistical method, the study determined the optimal conditions for xylanase production, enhancing the enzyme yield and providing insights for scaling up production. The results could facilitate the simultaneous valorization of rice husk waste and production of xylanase for various industries.