Research on Intelligent Development and Processing Technology of Crab Industry
Abstract
1. Introduction
2. Main Economic Crab Species
2.1. Asia
2.2. North America
2.3. Europe
2.4. South America
3. Research Status of Crab Processing Technology
3.1. Processing Technology of Live Crab
3.1.1. Harvesting and Temporary Rearing Technology
3.1.2. Depuration Technology
3.1.3. Sorting and Packaging Transportation Technology
3.2. Processing Technology of Dead Crab
3.2.1. Crab Meat Extraction Technology
3.2.2. Frozen Preservation and Packaging Technology
3.2.3. Deep Processing Technology
4. Intelligent Equipment
4.1. Sensor Technology
4.2. Intelligent Technique
4.3. Internet of Things and Big Data Analysis Technology
| The Role and Effectiveness of IoT Technology | Related References | |
|---|---|---|
| Breeding and processing | Real-time environmental monitoring, intelligent feeding, improved survival rate, full link traceability | [69,81] |
| Transport and circulation | Vitality monitoring, intelligent early warning, reducing loss and improving economic benefits | [71,84] |
| Quality traceability and supervision | Information transparency, enhance brand trust | [81,84] |
4.4. Artificial Intelligence Technology
5. The Future Development Direction
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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| Scientific Name | Optimal Salinity | Water Temperature | Main Sources of Acquisition |
|---|---|---|---|
| Eriocheir sinensis | / | 23–30 °C | Aquaculture |
| Portunus pelagicus | 30 ppt | 30 °C | Wild capture |
| Portunus trituberculatus | 20–30 ppt | 18–26 °C | Aquaculture |
| Scylla serrata | 20–30 ppt | 25–32 °C | Wild capture |
| Callinectes sapidus | 18–25 ppt | 23–28 °C | Wild capture |
| Cancer magister | 25–32 ppt | 10–15 °C | Wild capture |
| Paralithodes camtschaticus | 25–30 ppt | 3–10 °C | Wild capture |
| Paralithodes platypus | 25–33 ppt | 1–9 °C | Wild capture |
| Chionoecetes opilio | 20–30 ppt | −1–4 °C | Wild capture |
| Chionoecetes bairdi | / | 4–9 °C | Wild capture |
| Cancer paguris | 33–34 ppt | 9–15 °C | Wild capture |
| Lithodes santolla | 33–34 ppt | 5–10 °C | Wild capture |
| Depuration Method | Principle | Advantages | Disadvantages |
|---|---|---|---|
| High-pressure water washing [33,34] | High-speed water flow is generated by high-pressure water pump, and the dirt and impurities on the surface of the object are stripped by impact force. | 1. high depuration efficiency, can quickly remove stubborn stains (such as oil stains, sediment, paint layer); 2. Low cost, no need for chemical agents; 3. Simple operation, wide application range. | 1. May damage the fragile surface; 2. Large water consumption; 3. Depuration of the hidden positions such as gaps and blind holes is not thorough. |
| Ozone water treatment [35,36] | Using the strong oxidation of ozone decomposition of organic matter, bacteria and viruses, at the same time, through water erosion to achieve depuration. | 1. Can remove bacteria, viruses, pesticide residues, etc. 2. No chemical residues, environmental protection and safety; 3. It can complete depuration and disinfection at the same time; 4. The effect of odor removal is significant; | 1. Depuration efficiency is lower than the physical impact; 2. Professional equipment is needed to generate ozone, and the initial investment is high; 3. The ability to remove stubborn stains (such as dry sediment) is weak; 4. Improper control of ozone concentration may corrode metals. |
| Ultrasonic depuration [37,38,39] | Through the cavitation effect of ultrasonic waves in the liquid, the dirt on the surface of the object and in the gap is stripped. | 1. It can deeply clean the hidden positions such as gaps, blind holes, and micropores; 2. It can be combined with chemical depuration agent to enhance the effect; 3. High degree of automation, suitable for batch processing. | 1. High equipment costs; 2. The depuration effect of large-sized or irregularly shaped objects is limited; 3. Chemical waste liquid may be produced when depuration agent is needed; 4. High noise. |
| Model | Identification Type | Result | Reference |
|---|---|---|---|
| GA-BPNN | Sex, fatness, weight, and shell color | Achieve efficient and accurate classification and sorting of crabs. | [43] |
| GAM + YOLOv7 | Sex | Accurately performing the classification task of Chinese mitten crabs in low-light environments. | [44] |
| CNN | Sex | The proposed method achieved 98.90% classified accuracy. | [6] |
| GMNet-YOLOv4 | Sex | Effectively detects and classifies Chinese mitten crabs based on sex. | [45] |
| R-CNN + Grad-CAM | Shelf life | The recognition rate of the olfactory recognition system is as high as 96.67%. | [46] |
| Improved YOLOv3 | Molt | The precision of the improved model in clean water reaches 100% | [47] |
| Main Sensor Types | Critical Role | Related References | |
|---|---|---|---|
| Breeding | Water quality, video, heavy metals | Improve survival rate and ensure environmental safety | [68,69,70] |
| Processing | Machine vision, image recognition | Automatic grading, precise processing | [6,42,43,44,45] |
| Transport | Multi-source environmental sensor | Vigor monitoring, reduce loss | [71] |
| Main Technology/Equipment | Main Achievements | |
|---|---|---|
| Automatic feeding | Automatic feeding machine, GPS navigation | Feed evenly, save manpower |
| Machining control | Sensor + fuzzy logic, robot segmentation | Improve product quality and processing efficiency |
| Environmental maintenance | Automatic water grass combing machine | Optimize the growth environment and reduce damage |
| Transportation and remote management | Closed-loop system | Easy to scale, quality assurance |
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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Qu, Z.; Tian, C.; Che, X.; Xu, Z.; Chen, J.; He, X. Research on Intelligent Development and Processing Technology of Crab Industry. Fishes 2025, 10, 639. https://doi.org/10.3390/fishes10120639
Qu Z, Tian C, Che X, Xu Z, Chen J, He X. Research on Intelligent Development and Processing Technology of Crab Industry. Fishes. 2025; 10(12):639. https://doi.org/10.3390/fishes10120639
Chicago/Turabian StyleQu, Zhi, Changfeng Tian, Xuan Che, Zhijing Xu, Jun Chen, and Xiyu He. 2025. "Research on Intelligent Development and Processing Technology of Crab Industry" Fishes 10, no. 12: 639. https://doi.org/10.3390/fishes10120639
APA StyleQu, Z., Tian, C., Che, X., Xu, Z., Chen, J., & He, X. (2025). Research on Intelligent Development and Processing Technology of Crab Industry. Fishes, 10(12), 639. https://doi.org/10.3390/fishes10120639

