Limits...
Authentication of beef versus horse meat using 60 MHz 1H NMR spectroscopy.

Jakes W, Gerdova A, Defernez M, Watson AD, McCallum C, Limer E, Colquhoun IJ, Williamson DC, Kemsley EK - Food Chem (2014)

Bottom Line: Principal component analysis gave a two-dimensional "authentic" beef region (p=0.001) against which further spectra could be compared.The outcomes indicated that storing samples by freezing does not adversely affect the analysis.We conclude that 60 MHz (1)H NMR represents a feasible high-throughput approach for screening raw meat.

View Article: PubMed Central - PubMed

Affiliation: Analytical Sciences Unit, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK.

Show MeSH
First versus second principal component scores plots for (a) Lab 1 Training Set data, and (b) Lab 2 Training Set data (black disks = beef, open triangles = horse). (c) and (d) Corresponding loadings plots (black trace), together with the covariance of each dataset with the group membership (grey trace) and peaks picked from the loadings in the CH3 region.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4308633&req=5

f0020: First versus second principal component scores plots for (a) Lab 1 Training Set data, and (b) Lab 2 Training Set data (black disks = beef, open triangles = horse). (c) and (d) Corresponding loadings plots (black trace), together with the covariance of each dataset with the group membership (grey trace) and peaks picked from the loadings in the CH3 region.

Mentions: PCA was applied to datasets of normalised intensities obtained by concatenating the olefinic (NB: truncated at 5.39 ppm to exclude the carbon satellite region), bis-allylic and terminal CH3 regions of Fig. 2, treating each Lab’s Training data separately. The first two PC scores are plotted against one another in Fig. 4(a) and (b), with symbols coded according to species. In both cases, the first dimension contains most of the relevant information relating to the difference between the two species. Furthermore, regions of the loading corresponding to the olefinic and bis-allylic peaks are positively associated with horse samples (Fig. 4(c) and (d)); this is as expected, given the performance of the Naïve Bayes classification using just these integrated peak areas reported above. The loadings in the terminal CH3 region show considerable detail, including peaks at 1.08 ppm, 0.96 ppm and 0.84 ppm that tally with those in Fig. 3 and are associated with increasing C18:3 content, and peaks at 1.00 ppm and 0.67 ppm linked to cholesterol.


Authentication of beef versus horse meat using 60 MHz 1H NMR spectroscopy.

Jakes W, Gerdova A, Defernez M, Watson AD, McCallum C, Limer E, Colquhoun IJ, Williamson DC, Kemsley EK - Food Chem (2014)

First versus second principal component scores plots for (a) Lab 1 Training Set data, and (b) Lab 2 Training Set data (black disks = beef, open triangles = horse). (c) and (d) Corresponding loadings plots (black trace), together with the covariance of each dataset with the group membership (grey trace) and peaks picked from the loadings in the CH3 region.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4308633&req=5

f0020: First versus second principal component scores plots for (a) Lab 1 Training Set data, and (b) Lab 2 Training Set data (black disks = beef, open triangles = horse). (c) and (d) Corresponding loadings plots (black trace), together with the covariance of each dataset with the group membership (grey trace) and peaks picked from the loadings in the CH3 region.
Mentions: PCA was applied to datasets of normalised intensities obtained by concatenating the olefinic (NB: truncated at 5.39 ppm to exclude the carbon satellite region), bis-allylic and terminal CH3 regions of Fig. 2, treating each Lab’s Training data separately. The first two PC scores are plotted against one another in Fig. 4(a) and (b), with symbols coded according to species. In both cases, the first dimension contains most of the relevant information relating to the difference between the two species. Furthermore, regions of the loading corresponding to the olefinic and bis-allylic peaks are positively associated with horse samples (Fig. 4(c) and (d)); this is as expected, given the performance of the Naïve Bayes classification using just these integrated peak areas reported above. The loadings in the terminal CH3 region show considerable detail, including peaks at 1.08 ppm, 0.96 ppm and 0.84 ppm that tally with those in Fig. 3 and are associated with increasing C18:3 content, and peaks at 1.00 ppm and 0.67 ppm linked to cholesterol.

Bottom Line: Principal component analysis gave a two-dimensional "authentic" beef region (p=0.001) against which further spectra could be compared.The outcomes indicated that storing samples by freezing does not adversely affect the analysis.We conclude that 60 MHz (1)H NMR represents a feasible high-throughput approach for screening raw meat.

View Article: PubMed Central - PubMed

Affiliation: Analytical Sciences Unit, Institute of Food Research, Norwich Research Park, Norwich NR4 7UA, UK.

Show MeSH