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Shellfish

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Cooperation of lactic acid bacteria regulated by the AI-2/LuxS system involve in the biopreservation of refrigerated shrimp.

Food research international (Ottawa, Ont.)
Litopenaeus vannamei is an extremely perishable food because of rapid microbial growth and chemical degradation after harvesting. Biopreservation is a food preservation technology based on the addition of "positive" bacteria to kill or prevent the gr...

Predicting fish kills and toxic blooms in an intensive mariculture site in the Philippines using a machine learning model.

The Science of the total environment
Harmful algal blooms (HABs) that produce toxins and those that lead to fish kills are global problems that appear to be increasing in frequency and expanding in area. One way to help mitigate their impacts on people's health and livelihoods is to dev...

Deep learning-based ensemble modeling of Vibrio parahaemolyticus concentration in marine environment.

Environmental monitoring and assessment
Vibrio parahaemolyticus (V.p) is a marine pathogenic bacterium that poses a high risk to human health and shellfish industry, yet an effective regional-scale nowcasting model for managing the risk remains lacking. This study presents the first region...

Detection of paralytic shellfish toxins by near-infrared spectroscopy based on a near-Bayesian SVM classifier with unequal misclassification costs.

Journal of the science of food and agriculture
BACKGROUND: Paralytic shellfish poisoning caused by human consumption of shellfish fed on toxic algae is a public health hazard. It is essential to implement shellfish monitoring programs to minimize the possibility of shellfish contaminated by paral...

Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions.

Food research international (Ottawa, Ont.)
Vibrio parahaemolyticus and Vibrio vulnificus are bacteria with a significant public health impact. Identifying factors impacting their presence and concentrations in food sources could enable the identification of significant risk factors and preven...

Detection of mussels contaminated with cadmium by near-infrared reflectance spectroscopy based on RELS-TSVM.

Journal of food science
Eating mussels contaminated with cadmium (Cd) can seriously harm health. In this study, a non-destructive and rapid detection method for Cd-contaminated mussels based on near-infrared reflectance spectroscopy was studied. The spectral data of Cd-cont...

Machine learning models to predict the bioaccessibility of parent and substituted polycyclic aromatic hydrocarbons (PAHs) in food: Impact on accurate health risk assessment.

Journal of hazardous materials
Food intake is the primary pathway for polycyclic aromatic hydrocarbons (PAHs) to enter the human body. Once ingested, PAHs tend to accumulate, posing health risks. To accurately assess the risk of PAHs from food, concentrations of 10 parent PAHs (PP...

Quantitative analysis and visualization of chemical compositions during shrimp flesh deterioration using hyperspectral imaging: A comparative study of machine learning and deep learning models.

Food chemistry
The current work explores hyperspectral imaging (HSI) to quantitatively identify changes in TVB-N and K value during shrimp flesh deterioration. The work developed low-level data fusion (LLF) and predictive models using both machine learning methods ...

Applying deep learning algorithms for non-invasive estimation of carotenoid content in the foot muscle of Pacific abalone with different colors.

Food chemistry
Carotenoids are vital pigments influencing both the coloration and health of aquatic organisms, particularly in species such as the Pacific abalone (Haliotis discus hannai). In this study, we identified the major carotenoids in abalone foot muscle us...