Intelligent Cutting in Fish Processing: Efficient, High-quality, and Safe Production of Fish Products

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Publicado en:Food and Bioprocess Technology vol. 17, no. 4 (Apr 2024), p. 828
Autor principal: Fu, Jiaying
Otros Autores: He, Yingchao, Cheng, Fang
Publicado:
Springer Nature B.V.
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Acceso en línea:Citation/Abstract
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024 7 |a 10.1007/s11947-023-03163-5  |2 doi 
035 |a 2969195063 
045 2 |b d20240401  |b d20240430 
100 1 |a Fu, Jiaying  |u Zhejiang University, College of Biosystems Engineering and Food Science, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
245 1 |a Intelligent Cutting in Fish Processing: Efficient, High-quality, and Safe Production of Fish Products 
260 |b Springer Nature B.V.  |c Apr 2024 
513 |a Journal Article 
520 3 |a Fish processing is an indispensable part of fish food production. It mainly involves de-heading, gutting, filleting, skinning, trimming, and slicing, with the cutting operations holding a critical role. Unfortunately, inefficiency, low quality, and poor safety are the primary problems facing the fish processing industry today, dramatically hindering the automation and intelligence of fish processing. Consequently, it is vital to develop intelligent cutting in current fish processing in an efficient, high-quality, and safe manner. This review summarizes the main cutting techniques for fish processing. The critical techniques to achieve intelligent cutting in fish processing from imaging, image processing, and modeling dimensions are outlined, with their applications in practical fish processing. Fish characteristics, cutting mechanisms, and cutting process control are emphasized. In addition, Industry 4.0 technologies, especially the Internet of Things (IoT), big data analytics, and digital twins (DT), are emphasized. Finally, challenges and future work are highlighted, which will serve as references for subsequent researchers and enterprises engaged in this field to promote the automation and intelligence of fish processing production, ultimately realizing the high-efficiency, high-quality, and safe production of fish food products. 
653 |a Food 
653 |a Intelligence 
653 |a Internet of Things 
653 |a Process control 
653 |a Automation 
653 |a Process controls 
653 |a Fish feeds 
653 |a Industry 4.0 
653 |a Digital twins 
653 |a Industrial applications 
653 |a Food production 
653 |a Cuttings 
653 |a Image processing 
653 |a Processing industry 
653 |a Filleting 
653 |a Fish 
653 |a Fishery products 
653 |a Cutting 
653 |a Artificial intelligence 
653 |a Neural networks 
653 |a Economic 
700 1 |a He, Yingchao  |u Zhejiang University, College of Biosystems Engineering and Food Science, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
700 1 |a Cheng, Fang  |u Zhejiang University, College of Biosystems Engineering and Food Science, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X); Zhejiang University, Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X) 
773 0 |t Food and Bioprocess Technology  |g vol. 17, no. 4 (Apr 2024), p. 828 
786 0 |d ProQuest  |t Agriculture Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2969195063/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/2969195063/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch