Development of a statistical model to detect quality and storage conditions of Atlantic salmon.

The ever-increasing demand for fish as a food, has led to the development of new handling and packaging technologies resulting in premium quality fish products. In order to avoid frauds reaching the market, fish quality assurance methods need to be developed. In this study, two statistical models of biochemical processes that occur in Atlantic salmon during two weeks of storage at 0 and 4 °C were developed. These models were further used to detect salmon quality and its storage conditions. The biochemical processes were monitored using Nuclear Magnetic Resonance (NMR) spectroscopy and principal component analysis (PCA). The Soft Independent Modeling of Class Analogy (SIMCA) approach was applied to develop and evaluate the models. The fraud detection potential of the models was tested using samples of various quality and storage parameters. It was shown that the developed models are able to discriminate quality, time and temperature of stored Atlantic salmon.

Quality changes of salmon by-products during storage: Assessment and quantification by NMR.

Safe utilization of fish by-products is an important task due to increasing fish consumption. It can provide new valuable food/feed and will increase the economical profit and sustainability of the fishery industry. NMR spectroscopy is a reliable tool able to monitor qualitative and quantitative changes in by-products. In this work the trichloroacetic acid extracts of salmon backbones, heads and viscera stored at industrially relevant temperatures (4 and 10°C) were studied using NMR. Twenty-five metabolites were detected and the possibility of salmon by-products utilization as a source of anserine, phosphocreatine and taurine was discussed. Statistical data elaboration allowed determining the main processes occurring during by-products storage: formation of trimethylamine and biogenic amines, proteolysis and different types of fermentations. By-products freshness was evaluated using a multi-parameter approach: the trimethylamine and biogenic amines concentration changes were compared with Ki and H-values and safe temperatures and times for storage of salmon by-products were proposed.