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Maximizing chitin and chitosan recovery yields from Fusarium verticillioides using a many-factors-at-a-time approach

The extraction of chitin and chitosan presents challenges due to the complexity of the process and the influence of many variables. This study aimed to optimize chitin and chitosan extraction from Fusarium verticillioides by analyzing many additives and processing variables and modeling their yields...

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Published in:International journal of biological macromolecules 2024-12, Vol.282 (Pt 1), p.136708, Article 136708
Main Authors: Arbia, Wassila, Kouider Amar, Mohamed, Adour, Lydia, Amrane, Abdeltif
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Kouider Amar, Mohamed
Adour, Lydia
Amrane, Abdeltif
description The extraction of chitin and chitosan presents challenges due to the complexity of the process and the influence of many variables. This study aimed to optimize chitin and chitosan extraction from Fusarium verticillioides by analyzing many additives and processing variables and modeling their yields using multiple linear regression (MLR) and evolutionary algorithms. FT-IR analysis confirmed the presence of characteristic bands in the extracted samples, and SEM analysis further revealed the microfibrillar appearance of the chitin and the dense, non-porous structure of the chitosan. The Ant Lion Optimizer (ALO) was employed to select significant factors and optimize model parameters. A transformation was applied to capture nonlinear relationships, and the fine-tuned models showed improved predictive power, with p-values of 0.00203 for chitin and 0.00884 for chitosan. Multi-objective optimization (MOO) using the Adaptive Geometry Estimation-based Multi-Objective Evolutionary Algorithm (AGE-MOEA) further identified significant factors for optimal yields, achieving 3 g of Arginine, 100 ml of culture medium volume, 7 to 11 days of incubation time, 0.2 to 1.76 ml of Oligochitin, 1.4 g of FeSO4, 1.5 g of K2HPO4, and 1 g of NaCl. Therefore, the integration of ALO and AGE-MOEA algorithms effectively modeled and optimized chitin and chitosan yields by maximizing biopolymer recovery, enabling significant industrial exploitation. [Display omitted] •Modeled and optimized chitin and chitosan yields from Fusarium verticillioides using many factors simultaneously.•Employed ALO and AGE-MOEA algorithms for single- and multi-objective optimization to maximize chitin and chitosan yields.•Key factors identified for chitin yield included arginine, NH4Cl, oligochitin, and K2HPO4.•Significant contributors to chitosan yield included arginine, NaCl, NH4Cl, oligochitin, FeSO4, K2HPO4, and CaCl2.•WSM, WPM, and NED were utilized as decision-making methods.
doi_str_mv 10.1016/j.ijbiomac.2024.136708
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Multi-objective optimization (MOO) using the Adaptive Geometry Estimation-based Multi-Objective Evolutionary Algorithm (AGE-MOEA) further identified significant factors for optimal yields, achieving 3 g of Arginine, 100 ml of culture medium volume, 7 to 11 days of incubation time, 0.2 to 1.76 ml of Oligochitin, 1.4 g of FeSO4, 1.5 g of K2HPO4, and 1 g of NaCl. Therefore, the integration of ALO and AGE-MOEA algorithms effectively modeled and optimized chitin and chitosan yields by maximizing biopolymer recovery, enabling significant industrial exploitation. 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Multi-objective optimization (MOO) using the Adaptive Geometry Estimation-based Multi-Objective Evolutionary Algorithm (AGE-MOEA) further identified significant factors for optimal yields, achieving 3 g of Arginine, 100 ml of culture medium volume, 7 to 11 days of incubation time, 0.2 to 1.76 ml of Oligochitin, 1.4 g of FeSO4, 1.5 g of K2HPO4, and 1 g of NaCl. Therefore, the integration of ALO and AGE-MOEA algorithms effectively modeled and optimized chitin and chitosan yields by maximizing biopolymer recovery, enabling significant industrial exploitation. 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Multi-objective optimization (MOO) using the Adaptive Geometry Estimation-based Multi-Objective Evolutionary Algorithm (AGE-MOEA) further identified significant factors for optimal yields, achieving 3 g of Arginine, 100 ml of culture medium volume, 7 to 11 days of incubation time, 0.2 to 1.76 ml of Oligochitin, 1.4 g of FeSO4, 1.5 g of K2HPO4, and 1 g of NaCl. Therefore, the integration of ALO and AGE-MOEA algorithms effectively modeled and optimized chitin and chitosan yields by maximizing biopolymer recovery, enabling significant industrial exploitation. 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subjects Algorithms
arginine
biopolymers
Chemical engineering
Chemical Sciences
Chitin
Chitin - chemistry
Chitosan
Chitosan - chemistry
culture media
Evolutionary algorithms
Fusarium
Fusarium verticillioides
geometry
regression analysis
Spectroscopy, Fourier Transform Infrared
title Maximizing chitin and chitosan recovery yields from Fusarium verticillioides using a many-factors-at-a-time approach
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