Chitosan, one of the most interesting and intriguing biopolymer, can be extracted from different marine waste. The present paper focuses on the chitosan extraction procedure from Macropipus holsatus crab waste. Because the deacetylation degree is the most important characteristic of chitosan, the influence of specific operating parameters during deacetylation treatment was analyzed by statistical analysis and mathematical modelling using artificial neural networks (ANN). The ANN simulation put into evidence the manner that the deacetylation degree is influenced by the considered operating conditions and enabled the identification of optimal operating conditions in order to obtain a chitosan with a relatively high deacetylation degree. The obtained chitosan was characterized by various methods, including physical-chemical analysis, structure identification and crystallinity index. The main effects as well as the interaction effects for some physical-chemical properties were studied to establish if and how the chitosan properties are affected by the extraction procedure.
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