A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network
Abstract
:1. Introduction
1.1. Sustainable Waste Management of Shrimp Shells
1.2. Comparison of Chemical, Biochemical and Biological Extraction Techniques of Chitosan
2. Chemical Extraction of Chitosan from Shrimp Shells
2.1. Chemical Demineralization of Shrimp Shells
2.2. Chemical Deproteinization of Demineralized Shells
2.3. Chemical Deacetylation of Chitin
2.4. The Influence of Chemical Extraction Stages on Chitin and Chitosan Yield Percentage
2.5. Characteristics of Chitosan Chemically Obtained from Shrimp Shells
2.5.1. Moisture Content Determination
2.5.2. Solubility of Chitosan
2.5.3. Ash Content Percentage
2.5.4. FT-IR (Fourier Transform Infrared)
2.5.5. Degree of Deacetylation (DD%)
3. Neural Network Modeling (Multilayer Perceptron) of Chitosan Yield
4. Results of Neural Network Modeling (Multilayer Perceptron) of Chitosan Yield
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Thornber, K.; Verner-Jeffreys, D.; Hinchliffe, S.; Rahman, M.M.; Bass, D.; Tyler, C.R. Evaluating antimicrobial resistance in the global shrimp industry. Rev. Aquac. 2019, 12, 966–986. [Google Scholar] [CrossRef] [Green Version]
- Moss, S.M.; Moss, D.R.; Otoshi, C.A.; Arce, S.M. An integrated approach to sustainable shrimp farming. Asian Fish Sci. 2010, 23, 591–605. [Google Scholar] [CrossRef]
- Issue-14-Euroshrimp-Newsletter-European-Shrimp-Production(1). Available online: https://www.euroshrimp.net/14-european-shrimp-production-in-2020/ (accessed on 15 March 2022).
- Valenti, W.; Kimpara, J.M. Measuring Aquaculture Sustainability. World Aquac. 2011, 42, 26–30. [Google Scholar]
- FAO. Environmental Impact Assessment and Monitoring in Aquaculture. 2009. Available online: http://www.fao.org/3/i0970e/i0970e00.pdf (accessed on 17 May 2022).
- FAO. The State of World Fisheries and Aquaculture 2022. Towards Blue Transformation; FAO: Rome, Italy, 2022. [Google Scholar] [CrossRef]
- Nocentini, M.; Panettieri, M.; Barragán, J.M.G.D.C.; Mastrolonardo, G.; Knicker, H. Recycling pyrolyzed organic waste from plant nurseries, rice production and shrimp industry as peat substitute in potting substrates. J. Environ. Manag. 2020, 277, 111436. [Google Scholar] [CrossRef]
- Rashmi, S.H.; Biradar, B.; Maladkar, K.; Kittur, A.A. Extraction of Chitin from Prawn Shell and Preparation of Chitosan. Res. J. Chem. Environ. Sci. 2016, 4, 70–73. Available online: www.aelsindia.com/rjces.htm (accessed on 30 May 2022).
- Chang, C.-C.; Chang, K.-C.; Lin, W.-C.; Wu, M.-H. Carbon footprint analysis in the aquaculture industry: Assessment of an ecological shrimp farm. J. Clean. Prod. 2017, 168, 1101–1107. [Google Scholar] [CrossRef]
- Mathew, G.M.; Sukumaran, R.K.; Sindhu, R.; Binod, P.; Pandey, A. Microbes for the Synthesis of Chitin from Shrimp Shell Wastes. In Application of Microbes in Environmental and Microbial Biotechnology. Environmental and Microbial Biotechnology; Springer: Singapore, 2022; pp. 445–471. [Google Scholar] [CrossRef]
- Riofrio, A.; Alcivar, T.; Baykara, H. Environmental and Economic Viability of Chitosan Production in Guayas-Ecuador: A Robust Investment and Life Cycle Analysis. ACS Omega 2021, 6, 23038–23051. [Google Scholar] [CrossRef]
- Pujari, N.; Pandharipande, S.L. Review on Synthesis, Characterisation and Bioactivity of Chitosan. IJESRT Int. J. Eng. Sci. Res. Technol. 2016, 5, 334. [Google Scholar] [CrossRef]
- Yin, Z.; Hu, D.; Li, X.; Zhong, Y.; Zhu, L. Shell-derived chitosan as a green flocculant to harvest microalgae for biofuel production. Biofuels Bioprod. Biorefining 2021, 15, 637–645. [Google Scholar] [CrossRef]
- Rinaudo, M. Chitin and chitosan: Properties and applications. Prog. Polym. Sci. 2006, 31, 603–632. [Google Scholar] [CrossRef]
- De Alvarenga, E.S. Characterization and Properties of Chitosan. Biotechnol. Biopolym. 2011, 91, 48–53. Available online: www.intechopen.com (accessed on 7 June 2022).
- Nazir, G.; Rehman, A.; Park, S.-J. Valorization of shrimp shell biowaste for environmental remediation: Efficient contender for CO2 adsorption and separation. J. Environ. Manag. 2021, 299, 113661. [Google Scholar] [CrossRef]
- Islam, A.; Islam, M.; Zakaria, M.; Paul, S.; Mamun, A. Extraction and Worth Evaluation of Chitosan from Shrimp and Prawn Co-products. Am. J. Food Technol. 2019, 15, 43–48. [Google Scholar] [CrossRef] [Green Version]
- Hossain, S.; Uddin, K. Isolation and Extraction of Chitosan from Shrimp Shells. Int. J. Adv. Res. 2020, 8, 657–664. [Google Scholar] [CrossRef]
- Varlamov, V.P.; Il’Ina, A.V.; Shagdarova, B.T.; Lunkov, A.P.; Mysyakina, I.S. Chitin/Chitosan and Its Derivatives: Fundamental Problems and Practical Approaches. Biochemistry 2020, 85, 154–176. [Google Scholar] [CrossRef]
- Younes, I.; Rinaudo, M. Chitin and Chitosan Preparation from Marine Sources. Structure, Properties and Applications. Mar. Drugs 2015, 13, 1133–1174. [Google Scholar] [CrossRef] [Green Version]
- Shi, W.; Ching, Y.C.; Chuah, C.H. Preparation of aerogel beads and microspheres based on chitosan and cellulose for drug delivery: A review. Int. J. Biol. Macromol. 2021, 170, 751–767. [Google Scholar] [CrossRef]
- Wan, A.; Xu, Q.; Sun, Y.; Li, H. Antioxidant Activity of High Molecular Weight Chitosan and N,O-Quaternized Chitosans. J. Agric. Food Chem. 2013, 61, 6921–6928. [Google Scholar] [CrossRef]
- AlShehri, M.A.; Aziz, A.T.; Trivedi, S.; Panneerselvam, C. Efficacy of chitosan silver nanoparticles from shrimp-shell wastes against major mosquito vectors of public health importance. Green Process. Synth. 2020, 9, 675–684. [Google Scholar] [CrossRef]
- Olivera, S.; Muralidhara, H.B.; Venkatesh, K.; Guna, V.K.; Gopalakrishna, K.; Kumar, Y.K. Potential applications of cellulose and chitosan nanoparticles/composites in wastewater treatment: A review. Carbohydr. Polym. 2016, 153, 600–618. [Google Scholar] [CrossRef]
- Abdul Khalil, H.P.S.; Saurabh, C.K.; Adnan, A.S.; Nurul Fazita, M.R.; Syakir, M.I.; Davoudpour, Y.; Rafatullah, M.; Abdullah, C.K.; Haafiz, M.K.M.; Dungani, R. A review on chitosan-cellulose blends and nanocellulose reinforced chitosan biocomposites: Properties and their applications. Carbohydr. Polym. 2016, 150, 216–226. [Google Scholar] [CrossRef]
- Shi, H.; Liang, N.; Liu, J.; Li, S.; Gong, X.; Yan, P.; Sun, S. AIE-active polymeric micelles based on modified chitosan for bioimaging-guided targeted delivery and controlled release of paclitaxel. Carbohydr. Polym. 2021, 269, 118327. [Google Scholar] [CrossRef]
- Ahmad, S.I.; Ahmad, R.; Khan, M.S.; Kant, R.; Shahid, S.; Gautam, L.; Hasan, G.M.; Hassan, I. Chitin and its derivatives: Structural properties and biomedical applications. Int. J. Biol. Macromol. 2020, 164, 526–539. [Google Scholar] [CrossRef]
- Azuma, K.; Ifuku, S.; Osaki, T.; Okamoto, Y.; Minami, S. Preparation and Biomedical Applications of Chitin and Chitosan Nanofibers. J. Biomed. Nanotechnol. 2014, 10, 2891–2920. [Google Scholar] [CrossRef]
- Latańska, I.; Kolesińska, B.; Draczyński, Z.; Sujka, W. The Use of Chitin and Chitosan in Manufacturing Dressing Materials. Prog. Chem. Appl. Chitin Its Deriv. 2020, XXV, 16–36. [Google Scholar] [CrossRef]
- Khaled, A.M. A Review on Natural Biodegradable Materials: Chitin and Chitosan. Chem. Adv. Mater. 2021, 6, 1–5. Available online: http://issrpublishing.com/cam/ (accessed on 20 June 2022).
- Seenuvasan, M.; Sarojini, G.; Dineshkumar, M. Recovery of chitosan from natural biotic waste. In Current Developments in Biotechnology and Bioengineering. Resource Recovery from Wastes; Elsevier: Amsterdam, The Netherlands, 2020; pp. 115–133. [Google Scholar] [CrossRef]
- Phat, N.D.T. Chitin and Chitosan Recovered from Shrimp Shell: Structure, Characteristics and Applications. Ph.D. Thesis, Centria University of Applied Sciences, Kokkola, Finland, 2021. [Google Scholar]
- Hamed, I.; Özogul, F.; Regenstein, J.M. Industrial applications of crustacean by-products (chitin, chitosan, and chitooligosaccharides): A review. Trends Food Sci. Technol. 2016, 48, 40–50. [Google Scholar] [CrossRef]
- Jo, G.-H.; Park, R.-D.; Jung, W.-J. Enzymatic Production of Chitin from Crustacean Shell Waste. In Chitin, Chitosan, Oligosaccharides and Their Derivatives; CRC Press: Boca Raton, FL, USA, 2010; pp. 37–45. [Google Scholar] [CrossRef]
- Arbia, W.; Arbia, L.; Adour, L.; Amrane, A. Chitin Extraction from Crustacean Shells Using Biological Methods-A Review. Food Technol. Biotechnol. 2013, 51, 12–25. [Google Scholar]
- Cira, L.A.; Huerta, S.; Hall, G.M.; Shirai, K. Pilot scale lactic acid fermentation of shrimp wastes for chitin recovery. Process Biochem. 2002, 37, 1359–1366. [Google Scholar] [CrossRef]
- Tsigos, I.; Martinou, A.; Kafetzopoulos, D.; Bouriotis, V. Chitin deacetylases: New, versatile tools in biotechnology. Trends Biotechnol. 2000, 18, 305–312. [Google Scholar] [CrossRef]
- Gao, X.-D.; Katsumoto, T.; Onodera, K. Purification and Characterization of Chitin Deacetylase from Absidia coerulea. J. Biochem. 1995, 117, 257–263. [Google Scholar] [CrossRef]
- Tokuyasu, K.; Ohnishi-Kameyama, M.; Hayashi, K. Purification and Characterization of Extracellular Chitin Deacetylase from Colletotrichum lindemuthianum. Biosci. Biotechnol. Biochem. 1996, 60, 1598–1603. Available online: https://academic.oup.com/bbb/article/60/10/1598/5949082 (accessed on 10 July 2022). [CrossRef]
- Al Sagheer, F.; Al-Sughayer, M.; Muslim, S.; Elsabee, M. Extraction and characterization of chitin and chitosan from marine sources in Arabian Gulf. Carbohydr. Polym. 2009, 77, 410–419. [Google Scholar] [CrossRef]
- Dutta, P.K.; Kumar Dutta, P.; Dutta, J.; Tripathi, V.S. Chitin and Chitosan: Chemistry, Properties and Applications. J. Sci. Ind. Res. 2004, 63, 20–31. Available online: https://www.researchgate.net/publication/242294346 (accessed on 12 July 2022).
- No, H.K.; Hur, E.Y. Control of Foam Formation by Antifoam during Demineralization of Crustacean Shell in Preparation of Chitin. J. Agric. Food Chem. 1998, 46, 3844–3846. [Google Scholar] [CrossRef]
- Percot, A.; Viton, C.; Domard, A. Characterization of Shrimp Shell Deproteinization. Biomacromolecules 2003, 4, 1380–1385. [Google Scholar] [CrossRef]
- Pohling, J.; Dave, D.; Liu, Y.; Murphy, W.; Trenholm, S. Two-step demineralization of shrimp (Pandalus Borealis) shells using citric acid: An environmentally friendly, safe and cost-effective alternative to the traditional approach. Green Chem. 2021, 24, 1141–1151. [Google Scholar] [CrossRef]
- Kumar, M.Y.; Ravi, A. Extraction and Characterization of Chitosan from Shrimp Waste for Application in the Feed Industry. Int. J. Sci. Environ. Technol. 2017, 6, 2548–2557. Available online: www.ijset.net (accessed on 13 July 2022).
- Rasweefali, M.; Sabu, S.; Azad, K.M.; Rahman, M.R.; Sunooj, K.; Sasidharan, A.; Anoop, K. Influence of deproteinization and demineralization process sequences on the physicochemical and structural characteristics of chitin isolated from Deep-sea mud shrimp (Solenocera hextii). Adv. Biomark. Sci. Technol. 2022, 4, 12–27. [Google Scholar] [CrossRef]
- Hajji, S.; Younes, I.; Ghorbel-Bellaaj, O.; Hajji, R.; Rinaudo, M.; Nasri, M.; Jellouli, K. Structural differences between chitin and chitosan extracted from three different marine sources. Int. J. Biol. Macromol. 2014, 65, 298–306. [Google Scholar] [CrossRef]
- AIT, B.M.; Chairi, H.; Laglaoui, A.; Arakrak, A.; Zantar, S.; Bakkali, M.; Hassani, M. Optimization and characterization of gelatin and chitosan extracted from fish and shrimp waste. E3S Web Conf. 2018, 37, 02006. [Google Scholar] [CrossRef] [Green Version]
- Hossain, M.; Iqbal, A. Production and characterization of chitosan from shrimp waste. J. Bangladesh Agric. Univ. 2014, 12, 153–160. [Google Scholar] [CrossRef] [Green Version]
- Patria, A. Production and Characterization of Chitosan from Shrimp Shells Waste. AACL Bioflux 2013, 6, 339–344. Available online: http://www.bioflux.com.ro/aacl (accessed on 15 July 2022).
- Naznin, R. Extraction of chitin and chitosan from shrimp (Metapenaeus monoceros) shell by chemical method. Pak. J. Biol. Sci. 2005, 8, 1051–1054. [Google Scholar]
- Khanafari, A.; Marandi, R.; Sanatei, S. Recovery of Chitin and Chitosan from Shrimp Waste by Chemical and Microbial Methods. Iran. J. Environ. Health. Sci. Eng. 2008, 5, 19–24. Available online: www.SID.ir (accessed on 17 July 2022).
- Santos, V.P.; Maia, P.; Alencar, N.D.S.; Farias, L.; Andrade, R.F.S.; Souza, D.; Ribaux, D.R.; Franco, L.D.O.; Campos-Takaki, G.M. Recovery of chitin and chitosan from shrimp waste with microwave technique and versatile application. Arq. Inst. Biol. 2019, 86, 1–5. [Google Scholar] [CrossRef]
- Abdel-Rahman, R.M.; Hrdina, R.; Abdel-Mohsen, A.; Fouda, M.M.; Soliman, A.; Mohamed, F.; Mohsin, K.; Pinto, T.D. Chitin and chitosan from Brazilian Atlantic Coast: Isolation, characterization and antibacterial activity. Int. J. Biol. Macromol. 2015, 80, 107–120. [Google Scholar] [CrossRef]
- Elgannoudi, E.S.M. Some Aspects of Physico-Chemical Properties of Chitosan in Solutions and Films. Master’s Thesis, University of Malaya, Kuala Lumpur, Malaysia, 2009. [Google Scholar]
- Zargar, V.; Asghari, M.; Dashti, A. A Review on Chitin and Chitosan Polymers: Structure, Chemistry, Solubility, Derivatives, and Applications. ChemBioEng Rev. 2015, 2, 204–226. [Google Scholar] [CrossRef]
- Souza, V.G.L.; Fernando, A.L.; Pires, J.R.A.; Rodrigues, P.F.; Lopes, A.A.S.; Fernandes, F.M.B. Physical properties of chitosan films incorporated with natural antioxidants. Ind. Crop. Prod. 2017, 107, 565–572. [Google Scholar] [CrossRef]
- Gzyra-Jagieła, K.; Pęczek, B.; Wiśniewska-Wrona, M.; Gutowska, N. Physicochemical properties of chitosan and its degradation products. In Chitin and Chitosan: Properties and Applications; Wiley Publishing: Hoboken, NJ, USA, 2019; pp. 61–80. [Google Scholar]
- Cheng, J.; Zhu, H.; Huang, J.; Zhao, J.; Yan, B.; Ma, S.; Zhang, H.; Fan, D. The physicochemical properties of chitosan prepared by microwave heating. Food Sci. Nutr. 2020, 8, 1987–1994. [Google Scholar] [CrossRef] [Green Version]
- Silvestre, J.; Delattre, C.; Michaud, P.; de Baynast, H. Optimization of Chitosan Properties with the Aim of a Water Resistant Adhesive Development. Polymers 2021, 13, 4031. [Google Scholar] [CrossRef] [PubMed]
- Blake, G.R.; Hartge, K.H. Bulk Density. In Methods of Soil Analysis: Part 1; ASA/SSSA: Madison, WI, USA, 1986; pp. 363–375. [Google Scholar]
- Goosen, M.F.A. Applications of Chitin and Chitosan; CRC Press: Boca Raton, FL, USA, 2020. [Google Scholar] [CrossRef]
- Sreelekshmi, R.S.; Alex, L.; Jose, J.J. Shelf-Life Specific Moisture Variation in Chitosan of Genus Fenneropenaeus Distributed along Arabian Sea, India. BioRxiv 2022, 2–8. [Google Scholar] [CrossRef]
- Rosa, G.S.; Moraes, M.A.; Pinto, L.A. Moisture sorption properties of chitosan. LWT 2010, 43, 415–420. [Google Scholar] [CrossRef]
- Bonilla, F.; Chouljenko, A.; Lin, A.; Young, B.M.; Goribidanur, T.S.; Blake, J.C.; Bechtel, P.J.; Sathivel, S. Chitosan and water-soluble chitosan effects on refrigerated catfish fillet quality. Food Biosci. 2019, 31, 100426. [Google Scholar] [CrossRef]
- Sogias, I.A.; Khutoryanskiy, V.V.; Williams, A.C. Exploring the Factors Affecting the Solubility of Chitosan in Water. Macromol. Chem. Phys. 2009, 211, 426–433. [Google Scholar] [CrossRef]
- Aldila, H.; Asmar; Fabiani, V.A.; Dalimunthe, D.Y.; Irwanto, R. The effect of deproteinization temperature and NaOH concentration on deacetylation step in optimizing extraction of chitosan from shrimp shells waste. IOP Conf. Ser. Earth Environ. Sci. 2020, 599, 012003. [Google Scholar] [CrossRef]
- Suneeta, K.; Rath, P.; Sri, H.K.A. Chitosan from shrimp shell (Crangon crangon) and fish scales (Labeorohita): Extraction and characterization. Afr. J. Biotechnol. 2016, 15, 1258–1268. [Google Scholar] [CrossRef] [Green Version]
- Qin, C.; Li, H.; Xiao, Q.; Liu, Y.; Zhu, J.; Du, Y. Water-solubility of chitosan and its antimicrobial activity. Carbohydr. Polym. 2006, 63, 367–374. [Google Scholar] [CrossRef]
- Kaimudin, M.; Radiena, M. The Effect of Time Deacetylation to Characterize Chitosan from Waste Shrimp. In Proceedings of the Pattimura Proceeding: The 3rd International Seminar of Basic Science, Ambon, Indonesia, 6 April 2017. [Google Scholar]
- Moosa, A.; Ridha, A.M.; Moosa, A.A.; Kadhim, A. Use of Biocomposite Adsorbents for the Removal of Methylene Blue Dye from Aqueous Solution An Open Forum for Expert Opinions and Discussion View project Multidisciplinary Research View project Use of Biocomposite Adsorbents for the Removal of Methylene Blue Dye from Aqueous Solution. Am. J. Mater. Sci. 2016, 6, 135–146. [Google Scholar] [CrossRef]
- Wenling, C.; Duohui, J.; Jiamou, L.; Yandao, G.; Nanming, Z.; Xiufang, Z. Effects of the Degree of Deacetylation on the Physicochemical Properties and Schwann Cell Affinity of Chitosan Films. J. Biomater. Appl. 2005, 20, 157–177. [Google Scholar] [CrossRef]
- Harish Prashanth, K.v.; Kittur, F.S.; Tharanathan, R.N. Solid state structure of chitosan prepared under different N-deacetylating conditions. Carbohydr Polym. 2001, 50, 27–33. Available online: www.elsevier.com/locate/carbpol (accessed on 25 July 2022). [CrossRef]
- Freier, T.; Koh, H.S.; Kazazian, K.; Shoichet, M.S. Controlling cell adhesion and degradation of chitosan films by N-acetylation. Biomaterials 2005, 26, 5872–5878. [Google Scholar] [CrossRef] [PubMed]
- Jaworska, M.; Sakurai, K.; Gaudon, P.; Guibal, E. Influence of chitosan characteristics on polymer properties. I: Crystallographic properties. Polym. Int. 2003, 52, 198–205. [Google Scholar] [CrossRef]
- Rasweefali, M.; Sabu, S.; Sunooj, K.; Sasidharan, A.; Xavier, K.M. Consequences of chemical deacetylation on physicochemical, structural and functional characteristics of chitosan extracted from deep-sea mud shrimp. Carbohydr. Polym. Technol. Appl. 2021, 2, 100032. [Google Scholar] [CrossRef]
- Abdou, E.S.; Nagy, K.S.; Elsabee, M.Z. Extraction and characterization of chitin and chitosan from local sources. Bioresour. Technol. 2008, 99, 1359–1367. [Google Scholar] [CrossRef] [PubMed]
- Cavalcanti, F.M.; Kozonoe, C.E.; Pacheco, K.A.; Alves, R.M.D.B. Application of Artificial Neural Networks to Chemical and Process Engineering. In Deep Learning Applications; IntechOpen: London, UK, 2021. [Google Scholar] [CrossRef]
- Panerati, J.; Schnellmann, M.; Patience, C.; Beltrame, G.; Patience, G.S. Experimental methods in chemical engineering: Artificial neural networks–ANNs. Can. J. Chem. Eng. 2019, 97, 2372–2382. [Google Scholar] [CrossRef]
- Lavine, B.; Blank, T. Feed-Forward Neural Networks; Elsevier: Amsterdam, The Netherlands, 2009; pp. 571–586. [Google Scholar] [CrossRef]
- Gudivada, V.N. Natural Language Core Tasks and Applications. In Handbook of Statistics; Elsevier B.V.: Amsterdam, The Netherlands, 2018; Volume 38, pp. 403–428. [Google Scholar] [CrossRef]
- Al-Saif, A.M.; Abdel-Sattar, M.; Aboukarima, A.M.; Eshra, D.H. Application of a multilayer perceptron artificial neural network for identification of peach cultivars based on physical characteristics. PeerJ 2021, 9, e11529. [Google Scholar] [CrossRef]
- Zacharis, N.Z. Predicting Student Academic Performance in Blended Learning Using Artificial Neural Networks. Int. J. Artif. Intell. Appl. 2016, 7, 17–29. [Google Scholar] [CrossRef]
- Ghosh, M.; Srivastava, S.; Raigar, R.K.; Mishra, H.N. Multilayer perceptron neural networking for prediction of quality attributes of spray-dried vegetable oil powder. Soft Comput. 2019, 24, 9821–9833. [Google Scholar] [CrossRef]
- Salehuddin, N.F.; Omar, M.B.; Ibrahim, R.; Bingi, K. A Neural Network-Based Model for Predicting Saybolt Color of Petroleum Products. Sensors 2022, 22, 2796. [Google Scholar] [CrossRef]
- Velasco, L.C.P.; Serquiña, R.P.; Zamad, M.S.A.A.; Juanico, B.F.; Lomocso, J.C. Week-ahead Rainfall Forecasting Using Multilayer Perceptron Neural Network. Procedia Comput. Sci. 2019, 161, 386–397. [Google Scholar] [CrossRef]
- Zulkifli, F.; Abdullah, S.; Suriani, M.J.; Kamaludin, M.I.A.; Nik, W.B.W. Multilayer Perceptron Model for the prediction of corrosion rate of Aluminium Alloy 5083 in seawater via different training algorithms. IOP Conf. Ser. Earth Environ. Sci. 2021, 646, 012058. [Google Scholar] [CrossRef]
- Amor, N.; Noman, M.T.; Petru, M.; Mahmood, A.; Ismail, A. Neural network-crow search model for the prediction of functional properties of nano TiO2 coated cotton composites. Sci. Rep. 2021, 11, 1–13. [Google Scholar] [CrossRef] [PubMed]
- Bologna, G. A Simple Convolutional Neural Network with Rule Extraction. Appl. Sci. 2019, 9, 2411. [Google Scholar] [CrossRef] [Green Version]
- Tabatabaei, G. Applications of Multi-Layer Perceptron Artificial Neural Networks for Polymerization of Expandable Polystyrene by Multi-Stage Dosing Initiator. Iran. J. Chem. Chem. Eng. 2022, 41, 890–901. [Google Scholar]
- Tümer, A.E. Artificial Neural Network Modeling of The Removal of Cr (VI) on by Polymeric Calix[6]arene in aqueous solutions. Int. J. Eng. Res. Dev. 2020, 12, 13–20. [Google Scholar] [CrossRef]
Demineralization Acid Concentration (%) | Deproteinization Alkali Concentration (%) | Chitin Yield % | Deacetylation Alkali Concentration (%) | Deacetylation Temperature (°C) | Chitosan Yield % |
---|---|---|---|---|---|
10 | 1.5 | 30.6 | 50 | 60–70 | 30.00 |
10 | 3 | 29.1 | 50 | 60–70 | 28.00 |
10 | 6 | 28.7 | 50 | 60–70 | 27.00 |
10 | 8 | 27.7 | 50 | 60–70 | 25.20 |
20 | 1.5 | 28 | 50 | 60–70 | 27.80 |
20 | 3 | 27.7 | 50 | 60–70 | 27.50 |
20 | 6 | 26.4 | 50 | 60–70 | 25.80 |
20 | 8 | 24.9 | 50 | 60–70 | 24.30 |
30 | 1.5 | 24.4 | 50 | 60–70 | 24.10 |
30 | 3 | 24 | 50 | 60–70 | 23.80 |
30 | 6 | 22.6 | 50 | 60–70 | 21.76 |
30 | 8 | 21.8 | 50 | 60–70 | 20.50 |
40 | 1.5 | 23.8 | 50 | 60–70 | 22.80 |
40 | 3 | 22.6 | 50 | 60–70 | 22.20 |
40 | 6 | 21.1 | 50 | 60–70 | 20.60 |
40 | 8 | 20.2 | 50 | 60–70 | 19.50 |
50 | 1.5 | 22.1 | 50 | 60–70 | 20.90 |
50 | 3 | 20.7 | 50 | 60–70 | 19.50 |
50 | 6 | 19.4 | 50 | 60–70 | 17.80 |
50 | 8 | 18.2 | 50 | 60–70 | 15.40 |
Crude Shells Sample | Moisture Content (%) | Reference |
---|---|---|
Penaeus monodon | 4.3 | [8] |
Penaeus indicus | 3.9 | [8] |
Penaeus merguiensis | 4.05 | [8] |
Shrimp shell waste | 4 | [18] |
Shrimp shell waste | 4.36 | [18] |
Shrimp shell waste | 5.02 | [18] |
Shrimp shell waste | 6 | [18] |
Shrimp shell waste | 5.79 | [18] |
Shrimp shell waste | 6.49 | [18] |
Shrimp shell waste | 5.52 | [18] |
Shrimp shell waste | 5.21 | [18] |
Shrimp waste | 8.71 | [48] |
Penaeus monodon | 1.28 | [17] |
Penaeus monodon | 1.27 | [17] |
Penaeus monodon | 1.25 | [17] |
Penaeus monodon | 1.26 | [17] |
Shrimp shell waste | 8.25 | [49] |
Shrimp shell waste | 7.69 | [49] |
Shrimp shell waste | 8.32 | [49] |
Shrimp shell waste | 7.96 | [49] |
Metapenaeus monoceros | 8.01 | [51] |
Metapenaeus monoceros | 7.53 | [51] |
Metapenaeus monoceros | 7.44 | [51] |
Metapenaeus monoceros | 7.31 | [51] |
Metapenaeus monoceros | 6.62 | [51] |
Vibration Modes | |||||||
---|---|---|---|---|---|---|---|
Reference | NH2, OH in Pyranose Ring (cm−1) | -NH Stretching (cm−1) | Symmetric (CH3) and Asymmetric (CH2) Stretching (cm−1) | Amide I Amide II ** and Amide III *** Bands (cm−1) | CH2 Bending and CH3 Deformation (cm−1) | CO Stretching (cm−1) | Ring Stretching (cm−1) |
[8] | 3438 | --- | 2924 | 1421 *** | --- | 1075 | 896 |
[18] | 3452.58 | --- | 2924.01 | 1622.21 1550 ** | 1446 | 1078 | 875 |
[68] | 3398 | 3262 | --- | 1658 | --- | --- | 876 |
[45] | 3846 | 3295 | 2878 | 1646 1537 ** | 1403 | 1018 | --- |
[69] | 3450.65 | 2852.72 | 2924.09 | 1629.85 | --- | --- | --- |
[70] | 3411 | 3425 | 2919 | 1651 1321 *** | 1418 | 1078 | 899 |
[71] | 3425 | 2881 | 2921-2879 | 1647.19 1559 ** | --- | --- | --- |
Shell Origin | DD (%) | Extraction Condition Minutes | Reference |
---|---|---|---|
Shrimp shell waste | 39.10 | 2% HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 40.00 | 2% HCl for DM, 4% NaOH for DP, and 60% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 41.00 | 3% HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 42.00 | 3% HCl for DM, 4% NaOH for DP, and 60% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 61.00 | 4% HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 70.00 | 4% HCl for DM, 4% NaOH for DP, and 60% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 58.00 | 5% HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, at DT 65 °C | [18] |
Shrimp shell waste | 67.00 | 5% HCl for DM, 4% NaOH for DP, and 60% NaOH for DA, at DT 65 °C | [18] |
Penaeus monodon | 45.50 | (2%, 3%, 4% ) HCl for DM, 4% NaOH for DP, and 30% NaOH for DA, at DT 65 °C | [49] |
Penaeus monodon | 61.24 | (2%, 3%, 4% ) HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, at DT 65 °C | [49] |
Penaeus monodon | 79.57 | (2%, 3%, 4% ) HCl for DM, 4% NaOH for DP, and 50% NaOH for DA, at DT 65 °C | [49] |
Penaeus monodon | 81.24 | (2%, 3%, 4% ) HCl for DM, 4% NaOH for DP, and 60% NaOH for DA, at DT 65 °C | [49] |
Shrimp shell waste | 76.26 | 6% HCl for DM, 3.5% NaOH for DP, and 50% NaOH for DA, at DT 70 °C | [50] |
Shrimp shell waste | 81.37 | 6% HCl for DM, 3.5% NaOH for DP, and 50% NaOH for DA, at DT 80 °C | [50] |
Shrimp shell waste | 81.25 | 6% HCl for DM, 3.5% NaOH for DP, and 50% NaOH for DA, at DT 90 °C | [50] |
Shrimp shell waste | 84.87 | 6% HCl for DM, 3.5% NaOH for DP, and 50% NaOH for DA, at DT 100 °C | [50] |
Litopenaeus vannamei | 81.00 | DM with 2% HCl for shrimp shells with 16 mesh size, then DP under 4% NaOH, and 45% NaOH for DA, at 600 watts in the microwave for 15 min | [53] |
Litopenaeus vannamei | 72.00 | DM with 2% HCl for shrimp shells with 32 mesh size, then DP under 4% NaOH, and 45% NaOH for DA, at 600 watts in the microwave for 15 min | [53] |
Litopenaeus vannamei | 78.00 | DM with 2% HCl for shrimp shells with 60 mesh size, then DP under 4% NaOH, and 45% NaOH for DA, at 600 watts in the microwave for 15 min | [53] |
Litopenaeus vannamei | 81.00 | DM with 2% HCl for shrimp shells with 16 mesh size, then DP with 4% NaOH, and 45% NaOH for DA at 600 watts in the microwave for six pulses of 5 min | [53] |
Litopenaeus vannamei | 92.00 | DM with 2% HCl for shrimp shells with 32 mesh size, then DP with 4% NaOH, and 45% NaOH for DA at 600 watts in the microwave for six pulses of 5 min | [53] |
Litopenaeus vannamei | 89.00 | DM with 2% HCl for shrimp shells with 60 mesh size, then DP with 4% NaOH, and 45% NaOH for DA at 600 watts in the microwave for six pulses of 5 min | [53] |
Pink shrimp shells | 97.00 | 3% HCl for DM, 4% NaOH for DP, heating at 2-atmospheric pressure in the autoclave for 1 h and then steeping in 40% NaOH for DA for 4 days | [77] |
Brown shrimp shells | 92.00 | 3% HCl for DM, 4% NaOH for DP, heating at 2-atmospheric pressure in the autoclave for 1 h and then steeping in 40% NaOH for DA for 4 days | [77] |
Pink shrimp shells | 94.00 | 3% HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, and then autoclaved at 2-atmospheric pressure for 3 h | [77] |
Brown shrimp shells | 90.00 | 3% HCl for DM, 4% NaOH for DP, and 40% NaOH for DA, and then autoclaved at 2-atmospheric pressure for 3 h | [77] |
Network Information | |||
---|---|---|---|
Input Layer | Factors | 1 | Demineralization acid concentration |
2 | Demineralization temperature | ||
3 | Demineralization time | ||
4 | Deproteinization acid concentration | ||
5 | Deproteinization temperature | ||
6 | Deproteinization time | ||
7 | Deacetylation alkali concentration | ||
8 | Deacetylation temperature | ||
9 | Deacetylation time | ||
Number of Units | 84 | ||
Hidden Layer(s) | Number of Hidden Layers | 1 | |
Number of Units in Hidden Layer | 13 | ||
Activation Function | Hyperbolic tangent | ||
Output Layer | Dependent Variables | 1 | Chitosan yield |
Number of Units | 2 | ||
Activation Function | SoftMax | ||
Error Function | Cross-entropy |
Model Summary | ||
---|---|---|
Training | Cross Entropy Error | 0.54 |
Percent Incorrect Predictions | 1.7% | |
Stopping Rule Used | 1 consecutive step with no decrease in errors | |
Training Time | 0:00:00.05 | |
Testing | Cross Entropy Error | 0.975 |
Percent Incorrect Predictions | 3.1% |
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Hosney, A.; Ullah, S.; Barčauskaitė, K. A Review of the Chemical Extraction of Chitosan from Shrimp Wastes and Prediction of Factors Affecting Chitosan Yield by Using an Artificial Neural Network. Mar. Drugs 2022, 20, 675. https://doi.org/10.3390/md20110675
Hosney A, Ullah S, Barčauskaitė K. 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. 2022; 20(11):675. https://doi.org/10.3390/md20110675
Chicago/Turabian StyleHosney, Ahmed, Sana Ullah, and Karolina Barčauskaitė. 2022. "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 20, no. 11: 675. https://doi.org/10.3390/md20110675
APA StyleHosney, A., Ullah, S., & Barčauskaitė, K. (2022). 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, 20(11), 675. https://doi.org/10.3390/md20110675