Journal article
Muscle Protein Profiles Used for Prediction of Texture of Farmed Salmon (Salmo salar L.)
National Food Institute, Technical University of Denmark1
Research Group for Food Production Engineering, National Food Institute, Technical University of Denmark2
University of Iceland3
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark4
CHO Core, Translational Management, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark5
iLoop, Translational Management, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark6
A soft texture is undesired in Atlantic salmon as it leads to downgrading and reduced yield, yet it is a factor for which the cause is not fully understood. This lack of understanding highlights the need for identifying the cause of the soft texture and developing solutions by which the processing industry can improve the yield.
Changes in muscle protein profiles can occur both pre- and postharvest and constitute an overall characterization of the muscle properties including texture. The aim of this study was to investigate this relationship between specific muscle proteins and the texture of the salmon fillet. Samples for 2D-gel-based proteomics were taken from the fillet above the lateral line at the same position as where the texture had been measured.
The resulting protein profiles were analyzed using multivariate data analysis. Sixteen proteins were found to correlate to the measured texture, showing that it is possible to predict peak force based on a small subset of proteins. Additionally, eight of the 16 proteins were identified by tandem mass spectrometry including serum albumin, dipeptidyl peptidase 3, heat shock protein 70, annexins, and a protein presumed to be a titin fragment.
It is contemplated that the identification of these proteins and their significance for the measured texture will contribute to further understanding of the Atlantic salmon muscle texture.
Language: | English |
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Year: | 2017 |
Pages: | 3413-3421 |
ISSN: | 15205118 and 00218561 |
Types: | Journal article |
DOI: | 10.1021/acs.jafc.6b05588 |
ORCIDs: | Johansson, Gine Ørnholt , Frosch, Stina , Wulff, Tune , Jessen, Flemming and 0000-0001-7577-1190 |
Biological Materials Biology Chemistry Developing solutions Dipeptidyl peptidase Electrophoresis Forecasting Heat shock protein 70 Mass spectrometry Molecular biology Multivariant analysis Multivariate data analysis Muscle Optical Variables Measurements Organic Compounds PLS Prediction model Proteins Salmo salar Spectrometry Statistical Methods Tandem mass spectrometry Textures Two-dimensional electrophoresis (2DE) prediction model proteome tandem mass spectrometry texture two-dimensional electrophoresis (2DE)