Home About us MoEF Contact us Sitemap Tamil Website  
About Envis
Whats New
Research on Microbes
Microbiology Experts
Online Submission
Access Statistics

Site Visitors

blog tracking

Journal of Environmental Chemical Engineering
Volume 9 (1), 2021, 105013

Hyper-production optimization of fungal oxidative green enzymes using citrus low-cost byproduct

Débora S.Vilara, Clara D.Fernandesa, Victor R.S.Nascimentoa, Nádia H.Torresb, Manuela S.Leitea,b, Ram Naresh Bharagavac, Muhammad Bilald, Giancarlo R.Salazar-Bandaa,b, Katlin I. Barrios Eguiluza,b, Luiz Fernando Romanholo Ferreiraa,b

Graduate Program in Process Engineering, Tiradentes University (UNIT), Av. Murilo Dantas, 300, Farolândia, Aracaju, Sergipe 49032-490, Brazil.


The use of alternative methods is necessary to improve the production of lignin-modifying enzymes (LMEs) in the biocatalysis scenario. This study demonstrates a new and robust optimization for Lac and MnP enzymes production from Pleurotus sajor-caju induced by pulp wash citrus byproduct. The optimal values determined through response surface methodology (RSM) and artificial neural network coupled to the genetic algorithm (ANN-GA) were agitation rate (180 rpm) and pH (5.5), with a temperature of 28ºC, after 8 days of incubation. The maximum production of Lac and MnP obtained in these conditions using RSM was 307,379.91 IU/L (R2 = 0.9566) and 11,890.20 IU/L (R2 = 0.9932), respectively. However, ANN-GA predicted a maximum production of 204,486.96 IU/L and 36,081.02 UI/L, with R2 of 0.9903. Thus, under optimized conditions, the agroindustrial pulp wash residue emerges as a promising substrate in the production of LMEs, and therefore, its biotechnological viability enables efficient and sustainable production of bioproducts.

Keywords: Lignin-modifying enzymes, Bioprocesses, Optimization, Surface response methodology, Artificial neural network.

Copyright © 2005 ENVIS Centre ! All rights reserved
This site is optimized for 1024 x 768 screen resolution