Replacing Fishmeal and Fish Oil with Complex Protein and Canola Oil: Effect on Organoleptic and Nutritional Quality of Triploid Rainbow Trout (Oncorhynchus mykiss).

A twelve-week feeding experiment was undertaken to explore the impact of substituting dietary fish meal (FM) and fish oil (FO) with complex protein (CP) and canola oil (CO) in the diet of triploid rainbow trout on the quality of their fillets. The control diet (F100) contained FM (60%) and FO (18.6%) as the main protein and lipid sources. Based on this, 50% and 100% of FM and FO were substituted by CP and CO and they were named as F50 and F0, respectively. The results showed that there were no significant differences in the specific growth rates, condition factors, gutted yields, fillet yields and yellowness values as the substitution levels increased (p > 0.05). The F50 treatment obtained the highest values of fillet springiness and chewiness, improved the umami and bitter taste of the fillets by increasing the contents of inosine-5'-monophosphate and histidine, and increased lipid, protein, C18: 1n-9 and C18: 2n-6 contents (p < 0.05). The F0 treatment obtained the highest values of fillet hardness and pH, attenuated the sweet taste of the fillets by decreasing the content of glycine, and decreased the contents of EPA and DHA (p < 0.05). Both F50 and F0 treatments could increase the redness value, decrease the lightness and hue values of fillets, and increase the odor intensity, resulting in the typical fillet odors of green, fatty, orange and fishy (p < 0.05). In general, 50% and 100% of FM and FO substitution did not affect the growth of trout, but it did affect quality. Compared to the F100 treatment, the fillet quality of the F0 treatment was similar to the F50 treatment and could improve the appearance and odor intensity of the fillets. However, the difference was that the F50 treatment increased the springiness, umami, bitterness and lipid nutritional value of the fillets, but the F0 treatment increased the hardness, decreased the sweetness, and decreased the lipid, EPA and DHA contents of the fillets.

A new paradigm for smart packaging: A dual-channel freshness monitoring platform based on aerogels of sodium alginate-anthocyanin complex with high colorimetric sensitivity and stability.

Global seafood consumption is estimated at 156 million tons annually, with an economic loss of >25 billion euros annually due to marine fish spoilage. In contrast to traditional smart packaging which can only roughly estimate food freshness, an intelligent platform integrating machine learning and smart aerogel can accurately predict remaining shelf life in food products, reducing economic losses and food waste. In this study, we prepared aerogels based on anthocyanin complexes that exhibited excellent environmental responsiveness, high porosity, high color-rendering properties, high biocompatibility, high stability, and irreversibility. The aerogel showed excellent indication properties for rainbow trout and proved suitable for fish storage environments. Among the four machine learning models, the radial basis function neural network and backpropagation network optimized by genetic algorithm demonstrated excellent monitoring performance. Also, the two-channel dataset provided more comprehensive information and superior descriptive capability. The three-layer structure of the monitoring platform provided a new paradigm for intelligent and sophisticated food packaging. The results of the study might be of great significance to the food industry and sustainable development.

Development of machine learning-based shelf-life prediction models for multiple marine fish species and construction of a real-time prediction platform.

At least 10 million tons of seafood products are spoiled or damaged during transportation or storage every year worldwide. Monitoring the freshness of seafood in real time has become especially important. In this study, four machine learning algorithms were used for the first time to develop a multi-objective model that can simultaneously predict the shelf-life of five marine fish species at multiple storage temperatures using 14 features such as species, temperature, total viable count, K-value, total volatile basic­nitrogen, sensory and E-nose-GC-Ms/Ms. as inputs. Among them, the radial basis function model performed the best, and the absolute errors of all test samples were <0.5. With the optimal model as the base layer, a real-time prediction platform was developed to meet the needs of practical applications. This study successfully realized multi-objective real-time prediction with accurate prediction results, providing scientific basis and technical support for food safety and quality.

Preparation of multifunctional hydrogels based on co-pigment-polysaccharide complexes and establishment of a machine learning monitoring platform.

Economic loss due to fish spoilage exceeds 25 billion euros every year. Accurate and real-time monitoring of the freshness of fish can effectively cut down economic loss and food wastage. In this study, a dual-functional hydrogel based on sodium alginate-co-pigment complex with volatile antibacterial and intelligent indication was prepared and characterized. The characterization results indicated that the sodium alginate-co-pigment complex successfully improved the stability and color development ability of blueberry anthocyanins and bilberry anthocyanins at different temperatures and pH. The double cross-linking network inside the hydrogel conferred it with excellent mechanical properties. During rainbow trout storage, the hydrogel indicated a color difference of 73.55 on the last day and successfully extended the shelf-life of rainbow trout by 2 days (4 °C). Additionally, four dual-channel monitoring models were constructed using machine learning. The validation error of the genetic algorithm back propagation model (GA-BP) was only 5.6e-3, indicating that GA-BP can accurately monitor the freshness of rainbow trout. The rainbow trout real-time monitoring platform built based on GA-BP model can monitor the freshness of rainbow trout in real time through the images uploaded by users. The results of this study have broad applicability in the food industry, environmental conservation, and economic sustainability.

Radish residue carbon dots-based novel starch/chitosan film with high antioxidant, biocompatibility, and antibacterial activities for salmon fillets' active packaging.

The corruption of refrigerated marine fish results in global economic losses exceeding 25 billion euros annually. However, conventional preservatives present challenges, including singular functionality, potential toxicity, and high cost. In response, we developed multifunctional, safe, cost-effective, and environmentally friendly carbon dots derived from radish residues (R-CDs) by using the one-pot hydrothermal method. The surface of R-CDs is enriched with hydroxyl groups, conferring broad-spectrum antioxidant and antibacterial characteristics. R-CDs exhibited a notable 72.92 % inhibition rate on lipid peroxidation, surpassing the effectiveness of vitamin C (46 %). Additionally, R-CDs demonstrated impressive scavenging rates of 93.8 % for 2,2-diphenyl-1-picrylhydrazyl free radicals and 99.36 % for 2,2-azino-bis-3-ethylbenzothiazoline-6-sulphonic acid-free radicals. In combating spoilage bacteria such as Aeromonas sobria and Hafnia alvei, R-CDs disrupted cell structures and influenced intracellular substance content. Importantly, co-cultivation with R-CDs showed no significant cytotoxicity. Further incorporating R-CDs into films using starch and chitosan (S/CS/R-CDs films) for efficient and convenient use in salmon fillets preservation. S/CS/R-CDs films effectively inhibited the growth of spoilage bacteria, lipid oxidation, and protein decomposition in salmon fillets, thereby extending shelf life by 4 days. This combination of antioxidant and antibacterial properties in R-CDs, along with the functional films, presents a promising approach for enhancing salmon fillet preservation.