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Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging
Authors:David Castejón  Juan Manuel García-Segura  Rosa Escudero  Antonio Herrera  María Isabel Cambero
Institution:1. Centro de Asistencia a la Investigación de Resonancia Magnética Nuclear y de Espín Electrónico, Universidad Complutense de Madrid, 28040 Madrid, Spain;2. Departamento de Bioquímica y Biología Molecular I, Facultad de Químicas, Universidad Complutense de Madrid, 28040 Madrid, Spain;3. Departamento de Nutrición, Bromatología y Tecnología de los Alimentos, Facultad de Veterinaria. Universidad Complutense de Madrid, 28040 Madrid, Spain;4. Departamento de Química Orgánica, Facultad de Químicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
Abstract:In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by 1H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.
Keywords:Beef  Exudate  Nuclear magnetic resonance spectroscopy  Metabolomics  Principal component analysis  Partial least squares
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