AIMC Topic: Seafood

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An analytical and machine learning approach for total mercury and methylmercury determination in squid: enhancing food safety testing and traceability monitoring systems.

Food chemistry
This study presents the first assessment of total mercury (THg) and methylmercury (MeHg) in squids (Todarodes sagittatus, L.), providing insights into contamination levels and their correlation with the geographical origin. A method based on acidic e...

Gilthead sea bream gut bacteriome as a valuable tool for seafood provenance analysis.

Applied and environmental microbiology
The increasing demand for high-quality seafood underscores the significant challenges posed by rampant seafood fraud. This study aimed to identify regional capture biomarkers by using the gut bacteriome of specimens through state-of-the-art long-rea...

AI verification for spirulina's antimicrobial power in total coliform and Staphylococcus aureus isolated from tilapia fillet.

Scientific reports
Seafood products, including fresh tilapia fillets, are highly susceptible to rapid quality deterioration due to microbial contamination, posing a significant concern for food safety and public health. This study investigated, both experimentally and ...

Frontier research on the risk of spoilage microorganisms in refrigerated marine fish: From regional to global perspectives.

International journal of food microbiology
Microbial spoilage is creating safety risks and significant wastage of refrigerated marine fish. Spoilage microorganisms possess distinct physiological adaptations that enable them to contribute to the spoilage of refrigerated marine fish, thereby co...

Deep learning algorithm-assisted non-destructive detection of TBARS values of salmon flesh using multi-modal molecular spectra fusion.

Food chemistry
This study presents a deep learning framework for the non-destructive assessment of lipid oxidation in salmon flesh, quantified by thiobarbituric acid reactive substances (TBARS), under diverse storage conditions (-20, 0, 4, 20 °C, and dynamic temper...

Automated seafood freshness detection and preservation analysis using machine learning and paper-based pH sensors.

Scientific reports
Seafood, including fish, prawns and various marine products, is a critical component of global nutrition due to its high protein content, essential fatty acids, vitamins and minerals. Traditional methods for assessing seafood freshness such as sensor...

Comparative analysis of autofluorescence spectra in a filet of three fish species during chilled storage for raw consumption.

Food chemistry
Recent advances in fish freshness evaluation rely on a combination of optical imaging and artificial intelligence due to their applicability to non-invasive and non-destructive measurements. Using trout salmon, red sea bream, and Japanese amberjack, ...

Direct detection and differentiation of the Vibrio harveyi clade using MALDI-TOF MS integrated with artificial intelligence for effective outbreak management.

Food chemistry
Accurate identification of Vibrio harveyi clade species is critical for seafood safety and the control of aquaculture diseases. However, existing methods demonstrate limited classification performance. This study presents an artificial intelligence-a...

Quality enhancement of batter-coated oysters via low temperature vacuum frying technique and machine learning-based prediction models for shelf life and quality dynamics.

Food chemistry
As a widely consumed prepared food, the preservation of nutrient retention and sensory quality in batter fried oysters is a significant concern. Deep frying, air frying, and vacuum frying (VF) were used to prepare battered fried oysters. Guar gum (GG...

A FPGA based recurrent neural networks-based impedance spectroscopy system for detection of YAKE in tuna.

Scientific reports
This paper evaluates the use of impedance spectroscopy combined with artificial intelligence. Both technologies have been widely used in food classification and it is proposed a way to improve classifications using recurrent neural networks that trea...