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...

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Main Authors: Ahmed Hosney, Sana Ullah, Karolina Barčauskaitė
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Marine Drugs
Subjects:
Online Access:https://www.mdpi.com/1660-3397/20/11/675
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author Ahmed Hosney
Sana Ullah
Karolina Barčauskaitė
author_facet Ahmed Hosney
Sana Ullah
Karolina Barčauskaitė
author_sort Ahmed Hosney
collection DOAJ
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.
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spelling doaj.art-0fb5ac2ab3174d2f91c79fbd053230b82023-11-24T05:34:16ZengMDPI AGMarine Drugs1660-33972022-10-01201167510.3390/md20110675A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural NetworkAhmed Hosney0Sana Ullah1Karolina Barčauskaitė2Lithuanian Research Centre for Agriculture and Forestry, Instituto Av. 1, Akademija, 58344 Kedainiai, LithuaniaLithuanian Research Centre for Agriculture and Forestry, Instituto Av. 1, Akademija, 58344 Kedainiai, LithuaniaLithuanian Research Centre for Agriculture and Forestry, Instituto Av. 1, Akademija, 58344 Kedainiai, LithuaniaThere 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.https://www.mdpi.com/1660-3397/20/11/675shrimp shellschitosanchemical extractionneural networks
spellingShingle Ahmed Hosney
Sana Ullah
Karolina Barčauskaitė
A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network
Marine Drugs
shrimp shells
chitosan
chemical extraction
neural networks
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 shrimp shells
chitosan
chemical extraction
neural networks
url https://www.mdpi.com/1660-3397/20/11/675
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