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Bristol Bay supports the world's largest fishery for sockeye salmon which are harvested during an extremely condensed time period as fish return to their natal rivers. Uncertainties in preseason forecasts of run size challenge managers and the fishing community because of limited time to adapt strategies within a season. Preseason forecast errors from 2000 to 2023 were as large as 29%, with a mean absolute % error (MAPE) of 15%. We used autoregressive models including mean size-at-age of returning sockeye salmon, along with other environmental covariates, and weighted these models by the inverse of their MAPE to produce an ensemble in-season model that was subsequently weighted with preseason forecasts. This methodology improved forecasts of run size substantially earlier in the fishing season than currently possible and had an average MAPE of 12% (∼6 million fish), approximately 1 week into the fishing season. This level of error is not met by current in-season methods until approximately 2 weeks later after the season has peaked, and is better than current preseason methods in most years. [ABSTRACT FROM AUTHOR]

Predicting seafood consumption behavior is essential for fishing companies to adjust their production plans and marketing strategies. To achieve accurate predictions, this paper introduces a model for forecasting seafood consumption behavior based on an interpretable machine learning algorithm. Additionally, the Shapley Additive exPlanation (SHAP) model and the Accumulated Local Effects (ALE) plot were integrated to provide a detailed analysis of the factors influencing Shanghai residents' intentions to purchase salmon. In this study, we constructed nine regression prediction models, including ANN, Decision Tree, GBDT, Random Forest, AdaBoost, XGBoost, LightGBM, CatBoost, and NGBoost, to predict the consumers' intentions to purchase salmon and to compare their predictive performance. In addition, Bayesian optimization algorithm is used to optimize the hyperparameters of the optimal regression prediction model to improve the model prediction accuracy. Finally, the SHAP model was used to analyze the key factors and interactions affecting the consumers' willingness to purchase salmon, and the Accumulated Local Effects plot was used to show the specific prediction patterns of different influences on salmon consumption. The results of the study show that salmon farming safety and ease of cooking have significant nonlinear effects on salmon consumption; the BO-CatBoost nonlinear regression prediction model demonstrates superior performance compared to the benchmark model, with the test set exhibiting RMSE, MSE, MAE, R2 and TIC values of 0.155, 0.024, 0.097, 0.902, and 0.313, respectively. This study can provide technical support for suppliers in the salmon value chain and help their decision-making to adjust their corporate production plan and marketing activities [ABSTRACT FROM AUTHOR]

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Background: Vaccination of farmed salmonids has been an integral part of preventing infectious diseases in Norway's aquaculture industry. In Norway, vaccine usage is regulated by the government. There is a need to monitor vaccine usage for both regulatory and research purposes, at local and national scales. The Norwegian Veterinary Prescription Register (VetReg) is a national database that includes all prescriptions of medicines to animals dispensed by pharmacies and all medicines used for food producing animals by veterinarians. This study aimed to evaluate the quality of fish vaccination data reported to VetReg in 2016–2022. We considered the following attributes: completeness, validity, and timeliness. For external validation, we compared the data in VetReg to wholesaler statistics. Results: Pharmacies reported fish vaccines to VetReg in a variety of quantity units, including doses and volumes, which required us to harmonize the data to a single unit. It was not possible to harmonize the quantity units for nine percent of the records, which were mainly bath vaccines reported in doses. We identified specific issues that required manual editing of the units of 1 percent of the records. We validated individual variables such as product codes and location identifiers using external registers. The 'number of animals' variable was inconsistent for 31 percent of the records. The coverage of vaccine data in VetReg ranged from 81 to 113 percent for the ten most sold vaccines in 2020–2022, as compared to wholesales statistics. For the timeliness, we found that 75 percent of the records were submitted within 25 days for all years. Conclusions: Overall, we found that the fish vaccination data in VetReg was of sufficient quality to monitor injectable vaccine usage at hatcheries after 2020. We identified issues at the product level, with bath vaccines, and with single variables (number of animals, weight, and species). We recommend that quality can be improved by reporting all vaccines in volume rather than doses, reporting a single vaccine prescription per report, and including a deadline for pharmacies to report in the legislation. [ABSTRACT FROM AUTHOR]

The aim of this study was to develop a chilled, texture-modified salmon product for dysphagia patients, enriched with dairy and fish hydrolysate proteins. The challenge was to create a product with appealing sensory qualities and texture that meets level 5 (minced & moist) of the IDDSI framework. Atlantic salmon (Salmo salar) was heat-treated (95 °C/15 min), blended, and reconstructed by adding texture modifiers, casein and whey protein, and enzymatically derived fish hydrolysate. The products were packaged in oxygen-free plastic trays, heat-treated to a core temperature of 95 °C for 15 min, chilled and stored at 4 °C for 29 days and analyzed for microbiology, instrumental texture, and sensory properties. The texture analyses showed that products with fish protein hydrolysate were softer than those only with casein and whey protein, a result also confirmed by the IDDSI fork pressure test. Quantitative descriptive analysis of salmon products revealed significant differences (p < 0.05) in sensory attributes within flavour (fish flavour), and texture (softness and adhesiveness) but there was no significant change in bitterness. The shelf-life study at 4 °C showed good microbiological quality of the product, and safety after 29 days with appealing sensory and textural properties, i.e., a product at IDDSI level 5 for age care facilities and commercial production was obtained. [ABSTRACT FROM AUTHOR]

Salmon is popular among consumers because of its rich nutrition and tender taste, but it is easy to be contaminated by microorganisms during processing and storage, resulting in nutrient loss and tissue structure destruction. In this study, curcumin was used as photosensitizer to preserve salmon by Photodynamic technology (PDT) . The bacteriostatic efficiency of curcumin-mediated photodynamics was investigated by detecting the proliferation of microorganisms in salmon treated with PDT, and the mechanism of PDT to guarantee the quality of salmon was preliminatively explored from the perspective of color difference, endogenous enzyme activity, tissue slices and water migration. The results showed that 150 μmol/L curcumin combined with light treatment for 1 h could effectively kill 1. 6 log10CFU/g microorganisms in salmon. In addition, curcumin-mediated PDT significantly inhibited the activity of ATPase and lipase in salmon, delayed the degradation of free amino acids and free fatty acids, thus guaranteeing the structural integrity and moisture content of salmon, and extended its shelf life by 2 d. This study can provide data and theoretical support for the photodynamic technology to guarantee the quality of salmon, and promote its practical application in the field of food preservation. [ABSTRACT FROM AUTHOR]

Predicting seafood consumption behavior is essential for fishing companies to adjust their production plans and marketing strategies. To achieve accurate predictions, this paper introduces a model for forecasting seafood consumption behavior based on an interpretable machine learning algorithm. Additionally, the Shapley Additive exPlanation (SHAP) model and the Accumulated Local Effects (ALE) plot were integrated to provide a detailed analysis of the factors influencing Shanghai residents’ intentions to purchase salmon. In this study, we constructed nine regression prediction models, including ANN, Decision Tree, GBDT, Random Forest, AdaBoost, XGBoost, LightGBM, CatBoost, and NGBoost, to predict the consumers’ intentions to purchase salmon and to compare their predictive performance. In addition, Bayesian optimization algorithm is used to optimize the hyperparameters of the optimal regression prediction model to improve the model prediction accuracy. Finally, the SHAP model was used to analyze the key factors and interactions affecting the consumers’ willingness to purchase salmon, and the Accumulated Local Effects plot was used to show the specific prediction patterns of different influences on salmon consumption. The results of the study show that salmon farming safety and ease of cooking have significant nonlinear effects on salmon consumption; the BO-CatBoost nonlinear regression prediction model demonstrates superior performance compared to the benchmark model, with the test set exhibiting RMSE, MSE, MAE, R2 and TIC values of 0.155, 0.024, 0.097, 0.902, and 0.313, respectively. This study can provide technical support for suppliers in the salmon value chain and help their decision-making to adjust their corporate production plan and marketing activities

The aim of this study was to develop a chilled, texture-modified salmon product for dysphagia patients, enriched with dairy and fish hydrolysate proteins. The challenge was to create a product with appealing sensory qualities and texture that meets level 5 (minced & moist) of the IDDSI framework. Atlantic salmon (Salmo salar) was heat-treated (95 °C/15 min), blended, and reconstructed by adding texture modifiers, casein and whey protein, and enzymatically derived fish hydrolysate. The products were packaged in oxygen-free plastic trays, heat-treated to a core temperature of 95 °C for 15 min, chilled and stored at 4 °C for 29 days and analyzed for microbiology, instrumental texture, and sensory properties. The texture analyses showed that products with fish protein hydrolysate were softer than those only with casein and whey protein, a result also confirmed by the IDDSI fork pressure test. Quantitative descriptive analysis of salmon products revealed significant differences (p < 0.05) in sensory attributes within flavour (fish flavour), and texture (softness and adhesiveness) but there was no significant change in bitterness. The shelf-life study at 4 °C showed good microbiological quality of the product, and safety after 29 days with appealing sensory and textural properties, i.e., a product at IDDSI level 5 for age care facilities and commercial production was obtained.