1. NMR AND CHEMOMETRICS: A POWERFUL COMBINATION FOR FOOD ANALYSIS
Eighth Winter Symposium on Chemometrics 2012
NMR AND CHEMOMETRICS: A POWERFUL COMBINATION FOR FOOD ANALYSIS
Yulia B. Monakhova, Hartmut Schäfer, Eberhard Humpfer, Manfred Spraul, Thomas Kuballa, Dirk W. Lachenmeier
Baden-Württemberg
Chemische und Veterinäruntersuchungsämter
Bruker Biospin GmbH, Germany
State University, Saratov, Russia

2. NMR for chemometric applications in food analysis
1. The high spectral information of NMR provides ideal conditions for non-targeted analysis and the opportunity for chemometric discrimination
2. Modern NMR has reached sensitivity down to ppm-range
3. High throughput (minimal sample preparation, fast spectra aquasition and processing) is extremely efficient when dealing with a high number of samples to be analyzed using multivariate methods

3. Sample preparation and reference compound pH adjustment
Addition of proper solvent
and reference compound
pH adjustment
(soft drinks, wine)
Additional
steps
Solvent extraction
(pine nuts)
Hydrolysis/fat extraction
(fish, cheese, meat)

4. Sucrose without water suppression

5. Sucrose with water suppression

6. Alcohol: Eightfold suppression
Y. B. Monakhova, H. Schäfer, E. Humpfer, M. Spraul, T. Kuballa, D.W. Lachenmeier. Application of automated eightfold suppression of water and ethanol signals in 1H NMR to provide sensitivity for analyzing alcoholic beverages. Magnetic resonance in chemistry , 734–739

7. Performance of the 8-fold suppression: methanol

8. Data preparation for chemometrics
Fourier
transformation (FT)
Baseline and phase correction
and referencing

9. Peak to peak variations

10. Bucketing

11. Chemometric methods data reduction: PCA - Principal Component Analysis
classification:
SIMCA – Soft Independent Modeling of Class Analogy;
PLS-DA – Partial Least Squares - Discriminant Analysis;
LDA - Linear Discriminant Analysis;
SVM - Support Vector Machine
- quantitative analysis:
PLS - Partial Least Squares;
PCR – Principal Component Regression
- resolution of overlaped signals:
MCR – Multivariate Curve Resolution
ICA – Independent Component Analysis
PC3
PC2
PC1

12. Applications: unrecorded alcohol
                                   
Y. B. Monakhova, T. Kuballa, D. W. Lachenmeier. (2012) Nontargeted NMR Analysis to Rapidly Detect Hazardous Substances in Alcoholic Beverages. Applied Magnetic Resonance, DOI /s

13. Applications: quantification of ethyl carbamate in spirits

14. PLS models for ethyl carbamate (10 - 6.0 ppm)n
Reference range, mg/L
RMSE,
mg/L R2
Calibration set 1
146
0.15
0.96
Calibration set 2
119
0.13
0.98
Validation set 43
0.14
0.89
Y. B. Monakhova, T. Kuballa, D.W. Lachenmeier (2012) Rapid quantification of ethyl carbamate in spirits using NMR
spectroscopy and chemometrics. ISRN Analytical Chemistry, Volume 2012, Article ID , 5 pages
doi: /2012/989174

15. Applications: milk
Y. B. Monakhova, T. Kuballa, J. Leitz, C. Andlauer, D.W. Lachenmeier (2012) NMR Screening of milk, lactose-free milk and milk substitutes based on soy and grains to validate nutrition labeling. Dairy Science and Technology (92):109–120

16. Classification methods
Percent of inaccurate classifications
PLS-DA
SIMCA

17. PLS correlation between labeling parameters and NMR spectra
Reference
range
NMR
(ppm)
Validation
RMSE R2
Energy, (kJ/100 mg)
79-296
3-0 17
0.86
Carbohydrate, (g/100ml)
0.2-11
6-3
0.48
0.96
Sugars, (g/100 ml)
0.82
Protein, (g/100 ml)
0.35
0.93
Fat, (g/100 ml)
0.19
Saturates, (g/100 ml)
0.95
Fibre, (g/100 ml)
0.21
0.47

18. Applications: Pine nuts (Pinus Pinea)
The first case of adverse effects of pine nut consumption has been reported in 2001 in Belgium. Later it is called „Pine Nut Syndrome“ (PNS)
PNS is characterized as a bitter, metallic taste disturbance, developing 1-3 days after consumption and lasting for days or weeks.
A mechanism or specific cause has yet to be identified

19. 1H NMR - Origin Auf der rechten Seite: kein PNS !
H. Kobler, Y. B. Monakhova, T. Kuballa, C. Tschiersch, J. Vancutsem, G. Thielert, A. Mohring, D. W. Lachenmeier (2011) Nuclear magnetic resonance spectroscopy and chemometrics to identify pine nuts that cause taste disturbance. Journal of agricultural and food chemistry. 59 (13):

20. Applications: Cola beverages
P. Maes, Y. B. Monakhova, T. Kuballa, H. Reusch, D. W. Lachenmeier. Qualitative and quantitative control of carbonated cola beverages
using 1H NMR Spectroscopy (2012) Journal of agricultural and food chemistry, accepted

21. Resolution of of overlaped signals
MILCA - Mutual Information Least
Dependent Component Analysis

22. Conclusions
NMR and chemometrics represents a robust method for checking the food authenticity (geographical origin, the species of plant and animal, labeling validation, etc.)
NMR spectroscopy combined with chemometric methods can be successfully used for quantification of substances whose resonances overlap with signals of other compounds
NMR spectroscopy and chemometrics is judged as suitable for the rapid routine analysis of food and the application range will be extended to further matrices in the future.  

23. Thanks for your attention!!!
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24. PLS correlation between data of reference analysis and NMR spectra
Parameter
Reference range
PLS
factors
NMR range
(ppm)
Calibration
Test set validation
RMSE R2
Methanol, g/hL pa
0-1552 4
6-3
47.0
0.99
52.9
0.98
Acetaldehyde,
g/hL pa
0-91 7
3-0
4.28
0.91
9.40
0.61
Sum of higher alcohols,
g/hL pa a
0-1416 5
37.9
45.6
0.97
Propanol, g/hL pa a
0-1202 6
31.5
38.5
0.95
Isobutanol, g/hL pa a
0-179
7.59
0.96
9.01
Amyl alcohol, g/hL pa a
0-398
21.03
32.0
2-phenyl alcohol, g/hL pa
0-28
10-6
1.27
0.94
1.64
0.90
Methyl acetate, g/hL pa
0-24
1.18
0.93
1.76
0.85
Ethyl acetate, g/hL pa
0-753
15.98
30.4
Ethyl caprylate, g/hL pa a
0-3.9
6-0
0.55
0.66
0.72
0.45
Ethyl benzoate, g/hL pa
0-2.9
0.40
0.75
0.49
0.64
Benzaldehyde, g/hL pa
0-6.9
0.33
0.70
0.83
a overlapped signal, not possible to quantify with integration