کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1163186 1490931 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging
ترجمه فارسی عنوان
متابولومیک گوشت اگزودا: پتانسیل آن برای ارزیابی گوشت گاو و پیری
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
چکیده انگلیسی


• NMR spectra from beef samples and their exudates are very strongly correlated.
• 23 metabolites not reported in previous NMR meat studies have been identified.
• Meat exudate NMR spectra allow monitoring of biochemical changes related to aging.
• PCA of exudate NMR spectra classified meat samples by their storage time.
• The aging of a meat sample can be predicted by PLS analysis of its exudate.

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.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Analytica Chimica Acta - Volume 901, 11 December 2015, Pages 1–11
نویسندگان
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