Expected to improve yield rates by 50% resulting in 12.5% increase in profits.
Blue Star Foods to Enhance Soft Shell Crab Shedding Operations with Artificial Intelligence and UV Light Technology
(UNITED STATES, 7/17/2024)
Blue Star Foods Corp., an integrated Environmental, Social, and Governance (ESG) sustainable seafood company with a focus on Recirculatory Aquaculture Systems (RAS), that its looking to improve its soft-shell crab operations by introducing cutting-edge technology that combines Artificial Intelligence (AI) with Ultraviolet (UV) light technology to revolutionize the industry’s standard molting crab identification process.
The Atlantic blue crab, scientifically known as Callinectes sapidus, goes through a molting process where it sheds its old shell to form a new one. Identifying the precise moment when crabs are in the molting stage (busters) and harvesting them before they grow a new shell (soft crabs) is crucial for the soft-shell crab industry, as soft-shell crabs are high value seafood staple. The current traditional method of manual inspection for identifying molting crabs is not only time-consuming but also prone to errors, resulting in the company's view in high mortality rates and operational inefficiencies.
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An ongoing pilot study is conducted to gather and analyze key performance indicators in the traditional manual method versus the AI-UV system across all shifts. |
Challenges & Solution
The high labor costs in the soft-shell crab shedding industry are primarily attributed to visually & manually identifying molting crabs (busters) from non-molting ones (peelers). By implementing an AI system combined with UV light technology, the identification process can be automated, significantly reducing labor hours and costs, enhancing operational efficiency, and decreasing mortality rates.
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The traditional inpection method is time-consuming and also prone to errors. |
Blue Star's pilot facility operates 24/7 with three shifts. First shift from 6 am to 2 pm, Second shift from 2 pm to 10 pm, Third shift (night shift) from 10 pm to 6 am. Observations indicate that during the night shift, crabs molt at a higher rate. Production peaks during this time, with a 30% increase in molting crabs compared to the first and second shifts. Workers during the night shift are more likely to be tired or distracted, making it more difficult for them to accurately identify busters.
This increases the likelihood of errors and missed busters, which negatively impact the yield and overall efficiency, resulting in lower survival rate when comparing with the other 2 shifts. In this traditional industry method, the correlation between increase molting and mortality rate, shown an exponential growth curve. However; in AI-UV light, we predict the correlation to be a logistical growth curve. As molting rate increases, a mortality rate stabilized over time as the AI system maps its processes.
The integration of AI with UV light technology is expected to accurately and efficiently identify molting crabs, leading to reduced labor hours, operational costs, and mortality rates.
By harnessing the power of AI and UV light technology, this innovative approach aims to automate the identification process by training the system to recognize the specific physiological changes in crabs during molting. UV light will enhance the identification process by highlighting these changes, enabling AI algorithms to differentiate between busters and peelers accurately.
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The groundbreaking initiative represents a significant step forward in transforming the soft-shell crab shedding process. |
Operational Analysis and Expected Benefits
The implementation of AI and UV light technology is forecasted to result in a reduction in labor costs (currently 15% of Blue Star Food’s soft-shell crab revenues), increased operational efficiency, and improve the current yield rates by 50%, resulting in potential increase profits of approximately 12.5% or $9 per dozen [(*) based on the company's 2024 season average selling prices] of live soft-shell crabs.
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Atlantic blue crab. |
The AI system can operate continuously without fatigue, ensuring prompt and accurate identification of molting crabs, thereby enhancing overall operational efficiency.
Furthermore, the technology will aid in identifying the optimal removal time for soft-shell crabs post-molting, maximizing their quality and market value while increasing the company's average biennial 75% survival rates and operational profitability.
Pilot Study
An ongoing pilot study is conducted to gather and analyze key performance indicators in the traditional manual method versus the AI-UV system across all shifts, focusing on those KPI’s such as accuracy, labor hours, mortality rates, and its costs.
Using AI Software to create a vision system that monitors crab tanks under UV light, identifying molting crabs based on fluorescence changes. Its graphical interface simplifies the process of setting up and adjusting the vision system as needed, crucial for accurately monitoring crab molting processes.
This groundbreaking initiative represents a significant step forward in transforming the soft-shell crab shedding process, paving the way for increased operational survival rate efficiently, reduced labor costs, hence improved profitability.
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Blue Star has been proudly processing, packaging and selling pasteurized Blue Crab meat since 1995 with products sold in the U.K., Europe, U.S.A., Mexico, Canada, The Caribbean and Asia. |
About Blue Star Foods Corp.
Blue Star Foods Corp. an integrated Environmental, Social, and Governance (ESG) sustainable seafood company with a focus on Recirculatory Aquaculture Systems (RAS) that processes, packages and sells high-value seafood products. The Company believes it utilizes best-in-class technology, in both resource sustainability management and traceability, and ecological packaging. The Company also owns and operates the oldest continuously operating Recirculating Aquaculture System (RAS) full grow-out salmon farm in North America. The company is based in Miami, Florida.
Source: Blue Star Foods
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3000 NW 109th Ave
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Miami
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Florida (33172)
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