Beijing Laboratory for Food Quality and Safety, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.
ASEAN Key Laboratory of Comprehensive Exploitation and Utilization of Aquatic Germplasm Resources, Guangxi Academy of Fishery Sciences, Nanning, China.
Compr Rev Food Sci Food Saf. 2024 Nov;23(6):e70039. doi: 10.1111/1541-4337.70039.
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.
由于不同部位的鱼具有独特的营养成分和风味，因此鱼片产品深受消费者喜爱。然而，由于工作环境恶劣、工作量大且季节性强，鱼片切割面临劳动力短缺的问题。因此，需要一些自动、高效和大规模的切割技术来克服这些挑战。随着工业 4.0 的发展，物联网、人工智能、大数据和区块链技术逐渐应用于切割过程中，在数字化生产监控和提高产品安全性方面发挥着关键作用。本综述重点介绍了主要的鱼片切割方案，并深入探讨了先进的自动切割技术，展示了最新的技术进步以及它们如何推动鱼片切割的革新。此外，还讨论了基于物联网的鱼片切割过程中的生产监控架构。鱼片切割涉及多种方案，这些方案针对每种鱼片切割的具体特点进行定制。切割过程包括去头和去尾、去骨、去皮、修剪和骨检查。通过集成传感器、机器视觉、深度学习和先进的切割工具，这些技术正在将鱼片切割从手动操作转变为自动化过程。这种转变对该行业具有重要的实际意义，可提高效率、保持产品质量的一致性，并增强安全性，最终为鱼片切割自动化提供了现代化的制造方法，这也是工业 4.0 的背景下的一项重要发展。
