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A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network
There are two viable options to produce shrimp shells as by-product waste, either within the shrimp production phases or when the shrimp are peeled before cooking by the end user. This waste is considered a double-edged sword, as it is possible to be either a source of environmental pollution, throu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9693855/ https://www.ncbi.nlm.nih.gov/pubmed/36354998 http://dx.doi.org/10.3390/md20110675 |
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author | Hosney, Ahmed Ullah, Sana Barčauskaitė, Karolina |
author_facet | Hosney, Ahmed Ullah, Sana Barčauskaitė, Karolina |
author_sort | Hosney, Ahmed |
collection | PubMed |
description | There are two viable options to produce shrimp shells as by-product waste, either within the shrimp production phases or when the shrimp are peeled before cooking by the end user. This waste is considered a double-edged sword, as it is possible to be either a source of environmental pollution, through dumping and burning, or a promising source from which to produce chitosan as a biodegradable, biocompatible biopolymer which has a variety of agricultural, industrial, and biomedical applications. Chitosan is a deacetylated form of chitin that can be chemically recovered from shrimp shells through the three sequential stages of demineralization, deproteinization, and deacetylation. The main aim of this review paper is to summarize the recent literature on the chemical extraction of chitosan from shrimp shells and to represent the physicochemical properties of chitosan extracted from shrimp shells in different articles, such as chitosan yield, moisture content, solubility, ash content, and degree of deacetylation. Another aim is to analyze the influence of the main predictors of the chemical extraction stages (demineralization, deproteinization, and deacetylation) on the chitosan yield percentage by using a multilayer perceptron artificial neural network. This study showed that the deacetylation alkali concentration is the most crucial parameter, followed by the concentrations of acid and alkali of demineralization and deproteinization, respectively. The current review was conducted to be used in prospective studies for optimizing the chemical extraction of chitosan from shrimp wastes. |
format | Online Article Text |
id | pubmed-9693855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96938552022-11-26 A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network Hosney, Ahmed Ullah, Sana Barčauskaitė, Karolina Mar Drugs Review There are two viable options to produce shrimp shells as by-product waste, either within the shrimp production phases or when the shrimp are peeled before cooking by the end user. This waste is considered a double-edged sword, as it is possible to be either a source of environmental pollution, through dumping and burning, or a promising source from which to produce chitosan as a biodegradable, biocompatible biopolymer which has a variety of agricultural, industrial, and biomedical applications. Chitosan is a deacetylated form of chitin that can be chemically recovered from shrimp shells through the three sequential stages of demineralization, deproteinization, and deacetylation. The main aim of this review paper is to summarize the recent literature on the chemical extraction of chitosan from shrimp shells and to represent the physicochemical properties of chitosan extracted from shrimp shells in different articles, such as chitosan yield, moisture content, solubility, ash content, and degree of deacetylation. Another aim is to analyze the influence of the main predictors of the chemical extraction stages (demineralization, deproteinization, and deacetylation) on the chitosan yield percentage by using a multilayer perceptron artificial neural network. This study showed that the deacetylation alkali concentration is the most crucial parameter, followed by the concentrations of acid and alkali of demineralization and deproteinization, respectively. The current review was conducted to be used in prospective studies for optimizing the chemical extraction of chitosan from shrimp wastes. MDPI 2022-10-28 /pmc/articles/PMC9693855/ /pubmed/36354998 http://dx.doi.org/10.3390/md20110675 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Hosney, Ahmed Ullah, Sana Barčauskaitė, Karolina A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network |
title | A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network |
title_full | A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network |
title_fullStr | A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network |
title_full_unstemmed | A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network |
title_short | A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network |
title_sort | review of the chemical extraction of chitosan from shrimp wastes and prediction of factors affecting chitosan yield by using an artificial neural network |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9693855/ https://www.ncbi.nlm.nih.gov/pubmed/36354998 http://dx.doi.org/10.3390/md20110675 |
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