Artificial Neural Networks and Response Surface Methodology approach for optimization of an eco-friendly and detergent-stable lipase production from Actinomadura keratinilytica strain Cpt29
| Autor: | Noura Semache, Fatiha Benamia, Bilal Kerouaz, Inès Belhaj, Selma Bounour, Hafedh Belghith, Ali Gargouri, Ali Ladjama, Zeineddine Djeghaba |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Acta Chimica Slovenica, Vol 68, Iss 3, Pp 575-586 (2021) |
| Druh dokumentu: | article |
| ISSN: | 1318-0207 1580-3155 |
| DOI: | 10.17344/acsi.2020.6401 |
| Popis: | 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 °C), 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. |
| Databáze: | Directory of Open Access Journals |
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