Qing Li, Huawei Ma, Weiqing Min, Yang Wang, Ran Zhao, Yongjie Zhou, Yuqing Tan, Yongkang Luo, Hui Hong
{"title":"Recent advances in fish cutting: From cutting schemes to automatic technologies and internet of things innovations","authors":"Qing Li, Huawei Ma, Weiqing Min, Yang Wang, Ran Zhao, Yongjie Zhou, Yuqing Tan, Yongkang Luo, Hui Hong","doi":"10.1111/1541-4337.70039","DOIUrl":null,"url":null,"abstract":"<p>Fish-cutting products are widely loved by consumers due to the unique nutrient composition and flavor in different cuts. However, fish-cutting faces the issue of labor shortage due to the harsh working environment, huge workload, and seasonal work. Hence, some automatic, efficient, and large-scale cutting technologies are needed to overcome these challenges. Accompanied by the development of Industry 4.0, the Internet of Things (IoT), artificial intelligence, big data, and blockchain technologies are progressively applied in the cutting process, which plays pivotal roles in digital production monitoring and product safety enhancement. This review focuses on the main fish-cutting schemes and delves into advanced automatic cutting techniques, showing the latest technological advancements and how they are revolutionizing fish cutting. Additionally, the production monitoring architecture based on IoT in the fish-cutting process is discussed. Fish cutting involves a variety of schemes tailored to the specific characteristics of each fish cut. The cutting process includes deheading and tail removal, filleting, boning, skinning, trimming, and bone inspection. By incorporating sensors, machine vision, deep learning, and advanced cutting tools, these technologies are transforming fish cutting from a manual to an automated process. This transformation has significant practical implications for the industry, offering improved efficiency, consistent product quality, and enhanced safety, ultimately providing a modernized manufacturing approach to fish-cutting automation within the context of Industry 4.0.</p>","PeriodicalId":155,"journal":{"name":"Comprehensive Reviews in Food Science and Food Safety","volume":null,"pages":null},"PeriodicalIF":12.0000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Comprehensive Reviews in Food Science and Food Safety","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1541-4337.70039","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Fish-cutting products are widely loved by consumers due to the unique nutrient composition and flavor in different cuts. However, fish-cutting faces the issue of labor shortage due to the harsh working environment, huge workload, and seasonal work. Hence, some automatic, efficient, and large-scale cutting technologies are needed to overcome these challenges. Accompanied by the development of Industry 4.0, the Internet of Things (IoT), artificial intelligence, big data, and blockchain technologies are progressively applied in the cutting process, which plays pivotal roles in digital production monitoring and product safety enhancement. This review focuses on the main fish-cutting schemes and delves into advanced automatic cutting techniques, showing the latest technological advancements and how they are revolutionizing fish cutting. Additionally, the production monitoring architecture based on IoT in the fish-cutting process is discussed. Fish cutting involves a variety of schemes tailored to the specific characteristics of each fish cut. The cutting process includes deheading and tail removal, filleting, boning, skinning, trimming, and bone inspection. By incorporating sensors, machine vision, deep learning, and advanced cutting tools, these technologies are transforming fish cutting from a manual to an automated process. This transformation has significant practical implications for the industry, offering improved efficiency, consistent product quality, and enhanced safety, ultimately providing a modernized manufacturing approach to fish-cutting automation within the context of Industry 4.0.
期刊介绍:
Comprehensive Reviews in Food Science and Food Safety (CRFSFS) is an online peer-reviewed journal established in 2002. It aims to provide scientists with unique and comprehensive reviews covering various aspects of food science and technology.
CRFSFS publishes in-depth reviews addressing the chemical, microbiological, physical, sensory, and nutritional properties of foods, as well as food processing, engineering, analytical methods, and packaging. Manuscripts should contribute new insights and recommendations to the scientific knowledge on the topic. The journal prioritizes recent developments and encourages critical assessment of experimental design and interpretation of results.
Topics related to food safety, such as preventive controls, ingredient contaminants, storage, food authenticity, and adulteration, are considered. Reviews on food hazards must demonstrate validity and reliability in real food systems, not just in model systems. Additionally, reviews on nutritional properties should provide a realistic perspective on how foods influence health, considering processing and storage effects on bioactivity.
The journal also accepts reviews on consumer behavior, risk assessment, food regulations, and post-harvest physiology. Authors are encouraged to consult the Editor in Chief before submission to ensure topic suitability. Systematic reviews and meta-analyses on analytical and sensory methods, quality control, and food safety approaches are welcomed, with authors advised to follow IFIS Good review practice guidelines.