Semache_2021_Acta.Chim.Slov_68_575

Reference

Title : Artificial Neural Networks and Response Surface Methodology Approach for Optimization of an Eco-Friendly and Detergent-Stable Lipase Production from Actinomadura Keratinilytica Strain Cpt29 - Semache_2021_Acta.Chim.Slov_68_575
Author(s) : Semache N , Benamia F , Kerouaz B , Belhaj IS , Bounour S , Belghith H , Gargouri A , Ladjama A , Djeghaba Z
Ref : Acta Chim Slov , 68 :575 , 2021
Abstract :

This work mainly focused on the production of an efficient, economical, and eco-friendly lipase (AKL29) from Actinomadura keratinilytica strain Cpt29 isolated from poultry compost in north east of Algeria, for use in detergent industries. AKL29 shows a significant lipase activity (45 U/mL) towards hydrolyzed triacylglycerols, indicating that it is a true lipase. For maximum lipase production the modeling and optimization of potential culture parameters such as incubation temperature, cultivation time, and Tween 80 (v/v) were built using RSM and ANN approaches. The results show that both the two models provided good quality predictions, yet the ANN showed a clear superiority over RSM for both data fitting and estimation capabilities. A 4.1-fold increase in lipase production was recorded under the following optimal condition: incubation temperature (37.9 degreesC), cultivation time (111 h), and Tween 80 (3.27%, v/v). Furthermore, the partially purified lipase showed good stability, high compatibility, and significant wash performance with various commercial laundry detergents, making this novel lipase a promising potential candidate for detergent industries.

PubMedSearch : Semache_2021_Acta.Chim.Slov_68_575
PubMedID: 34897543

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Citations formats

Semache N, Benamia F, Kerouaz B, Belhaj IS, Bounour S, Belghith H, Gargouri A, Ladjama A, Djeghaba Z (2021)
Artificial Neural Networks and Response Surface Methodology Approach for Optimization of an Eco-Friendly and Detergent-Stable Lipase Production from Actinomadura Keratinilytica Strain Cpt29
Acta Chim Slov 68 :575

Semache N, Benamia F, Kerouaz B, Belhaj IS, Bounour S, Belghith H, Gargouri A, Ladjama A, Djeghaba Z (2021)
Acta Chim Slov 68 :575