Improved deinking and biobleaching efficiency of enzyme consortium from Thermomyces lanuginosus VAPS25 using genetic Algorithm-Artificial neural network based tools.

The present study reports the combined enzymatic production efficiency of thermophilic fungus Thermomyces lanuginosus VAPS25 using a combinatory artificial intelligence-based tool, resulting in 2.7 IU/ml, 5.2 IU/ml, and 18.85 U/ml activity of endoglucanase, amylase, and lipase, respectively with good thermostability at 90 °C (pH 8-10). Interestingly, the metal ions viz. Cu2+ and Mg2+ increased the endoglucanase activity to 5 folds, i.e.,5.6 IU/ml compared to control. Further, the amylase and lipase activity was also enhanced by Fe2+ and Co2+ to 5.4 IU/ml and 19.57 U/ml, respectively. Additionally, the deinking efficiency was improved by 68.9%, 42.7%, and 52.8% by endoglucanase, amylase, and lipase, respectively, while the consortium increased the deinking efficiency to 72.7%. The bio-bleached paper strength parameters such as burst index, breaking length, tear index, and tensile index of sheets were significantly improved by 1.38%, 13.54%, 7.54%, and 20.88%, respectively. These enzymes at an industrial scale would help develop an economical paper recycling process.