1. Artificial Neural Networks and Response Surface Methodology Approach for Optimization of an Eco-Friendly and Detergent-Stable Lipase Production from Actinomadura Keratinilytica Strain Cpt29.
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Semache, Noura, Benamia, Fatiha, Kerouaz, Bilal, Belhaj, Inès, Bounour, Selma, Belghith, Hafedh, Gargouri, Ali, Ladjama, Ali, and Djeghaba, Zeineddine
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RESPONSE surfaces (Statistics) , *LIPASES , *ARTIFICIAL neural networks , *LAUNDRY detergents - 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 °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. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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