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

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

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)

Sucrose without water suppression

Sucrose with water suppression

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. 2011. 49, 734–739

Performance of the 8-fold suppression: methanol

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

Peak to peak variations

Bucketing

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

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 10.1007/s00723-011-0309-2

Applications: quantification of ethyl carbamate in spirits

PLS models for ethyl carbamate (10 - 6.0 ppm) n Reference range, mg/L RMSE, mg/L R2 Calibration set 1 146 0 - 9.0 0.15 0.96 Calibration set 2 119 0.13 0.98 Validation set 43 0 - 5.0 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 989174, 5 pages doi:10.5402/2012/989174

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

Classification methods Percent of inaccurate classifications PLS-DA SIMCA

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) 0.1-7.3 0.82 Protein, (g/100 ml) 0.1-3.7 0.35 0.93 Fat, (g/100 ml) 0.1-4.2 0.19 Saturates, (g/100 ml) 0.1-2.8 0.95 Fibre, (g/100 ml) 0.0-1.6 0.21 0.47

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

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): 6877-6881.

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

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

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.  

Thanks for your attention!!! Contact: yul-monakhova@mail.ru

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