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Published on: January 14, 2020
Valorization of fishery industry waste: Chitosan extraction and its application in the industry
Maricarmen Iñiguez-Moreno1,2, Berenice Santiesteban-Romero1,2, Elda M Melchor-Martínez1,2
1Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey 64849, Mexico.
Abstract:
Waste from the fishing industry is disposed of in soils and oceans, causing environmental damage. However, it is also a source of valuable compounds such as chitin. Although chitin is the second most abundant polymer in nature, its use in industry is limited due to the lack of standardized and scalable extraction methods and its poor solubility. The deacetylation process increases its potential applications by enabling the recovery of chitosan, which is soluble in dilute acidic solutions. Chitosan is a polymer of great importance due to its biocompatible and bioactive properties, which include antimicrobial and antioxidant capabilities. Chitin extraction and its deacetylation to obtain chitosan are typically performed using chemical processes that involve large amounts of strongly acidic and alkaline solutions. To reduce the environmental impact of this process, extraction methods based on biotechnological tools, such as fermentation and chitin deacetylase, as well as emerging technologies, have been proposed. These extraction methods have demonstrated the potential to reduce or even avoid using strong solvents and shorten extraction time, thereby reducing costs. Nevertheless, it is important to address existing gaps in this area, such as the requirements for large-scale implementation and the determination of the stoichiometric ratios for each process. This review highlights the use of biotechnological tools and emerging technologies for chitin extraction and chitosan production. These approaches truly minimize environmental impact, reduce the use of strong solvents, and shorten extraction time. They are a reliable alternative to fishery waste valorization, lowering costs; however, addressing the critical gaps for their large-scale implementation remains challenging.
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