NMR Analysis in Food Science

Dr. Dave Russell

NMR Applications Scientist

Agilent Technologies

“I know what I like… and I like what I know.” Dr. J. Josephs, Sr.

Courtesy: Lydia Park

NMR as a Structure Elucidation Tool

Empirical Formula C27H35N9O5S2

Aildenafil core

It started with a phone call from Flora Labs…

NMR as a Structure Elucidation Tool

MS/MS

Proton and Carbon

HSQC

COSY

HMBC

NOESY

15N CIGAR

It started with a phone call from Flora Labs…

NMR as a Structure Elucidation Tool It started with a phone call from Flora Labs…

MS/MS

Proton and Carbon

HSQC

COSY

HMBC

NOESY

15N CIGAR

qNMR – Accuracy and Precision, made simple

R² = 0.9996

0.050

0.500

5.000

50.000

0.050 0.500 5.000 50.000

Actu

al

Co

ncen

trati

on

, m

M

Experimental Concentration, mM

Accuracy 98.47%

%SD 0.74%

No reference standards required. (Complete unknowns are just fine, thanks.)

Overview - CRAFT analysis of NMR data

• Introduction to the problems of frequency-based

analyses in Food Science

• Comparison of CRAFT to standard techniques

• Real-world applications Soy bean supplements – quality control

Tea – authenticity

Smelt – origin

Quantitation in frequency domain This is easy when the spectra are simple

100x

Zinfandel Wine

Real data are never “simple” Complex overlapped spectra are the rule for food science samples

The “Standard” NMR Analysis Workflow

Manual processing. Manual data reduction. Manual everything!

FT & phase correct

The NMR workflow for data analysis

is primarily based on manual

processing and interpretation of each

individual spectrum.

This is a slow, tedious, and error-

prone process.

Time vs. Frequency domain: the good and the bad

x y presentation of frequency vs. “intensity”

• peak height = f(amplitude, linewidth, phase)

• integral = f(amplitude, linewidth, phase)

Baseline issues • A few corrupted data points in the fid

translate to several corrupted data points in

frequency axis

• Broad features obscure the true baseline

Time vs. Frequency domain: the good and the bad

Sum of multiple sinusoids

Each sinusoid represented by independent

NMR properties • Frequency

• Amplitude

• Decay rate

• Phase

x y presentation of frequency vs. “intensity”

• peak height = f(amplitude, linewidth, phase)

• integral = f(amplitude, linewidth, phase)

Baseline issues • A few corrupted data points in the fid

translate to several corrupted data points in

frequency axis

• Broad features obscure the true baseline

CRAFT workflow

Define R

OI

“Fingerprint” chemical

shift for chemicals of

interest

Relative

amplitudes

(components)

Statistical

Analysis

Cluster of

FIDs

Array of spectra

Alignment table

Krishnamurthy, K., Mag. Reson. Chem., 2013

doi: 10.1002/mrc.4022

Overview - CRAFT analysis of NMR data

• Introduction to the problems of frequency-based

analyses in Food Science

• Comparison of CRAFT to standard techniques

• Real-world applications Soy bean supplements – quality control

Tea – authenticity

Smelt – origin

CRAFT Analysis of Fermentation Broth SA Bradley, TA Smitka, DJ Russell and K Krishnamurthy. Current Metabolomics, submitted

1H NMR Spectrum of

Fermentation Broth

CRAFT Results – Comfort Zone Total CRAFT’ing time: 3.5 minutes

Models

Residual

Reconstructed

Experimental

Fingerprints for component extraction

SA Bradley, TA Smitka, DJ Russell and K Krishnamurthy. Current Metabolomics, submitted

CRAFT Results: Comparison

CRAFT Results: Comparison

Overview - CRAFT analysis of NMR data

• Introduction to the problems of frequency-based

analyses in Food Science

• Comparison of CRAFT to standard techniques

• Real-world applications Soy bean supplements – quality control

Tea – authenticity

Smelt – origin

CRAFT applications Food sciences – soy dietary supplement analysis

Over-the-counter soy dietary

supplements

3 different soy supplements

15 (replicate) capsules from

each group

Extracted, filtered, 1H NMR

collected

Soy Extract - Aromatics Isoflavone peaks of interest

Soy Extract - Aromatics Isoflavone peaks of interest

Soy Extract – Analyte Table Isoflavone peaks of interest

CRAFT example Soy extract analysis

3 groups; 15 samples/each; ~2 min/spectrum CRAFT’ing time

CRAFT example Soy extract analysis

3 groups; 15 samples/each; ~2 min/spectrum CRAFT’ing time

CRAFT example Soy extract analysis

3 groups; 10 samples/each; 30 sec/spectrum CRAFT’ing time

Overview - CRAFT analysis of NMR data

• Introduction to the problems of frequency-based

analyses in Food Science

• Comparison of CRAFT to standard techniques

• Real-world applications Soy bean supplements – quality control

Tea – authenticity

Smelt – origin

Analysis of Tea - Method

Which country did this tea come from?

Eleven teas of known origin

• 1 g samples

• boiled for 5 minutes in 5 mL D2O

• centrifuged

• transferred to NMR tubes

5 replicates of each type of tea

• 55 samples, total

Tea Analysis Stack plot – D2O samples

Spectra

recorded for

one set of 5

replicates; tea

extracted with

hot D2O.

-0.25

-0.15

-0.05

0.05

0.15

0.25

0.35

0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16

China (black)

Everything else…

Tea Analysis PCA plot – D2O samples

Analysis of Tea - Method

Reset, rethink, and try again.

Eleven teas of known origin

• 1 g samples

• extracted w/ 5 mL solvent

• centrifuged

• transferred to NMR tubes

DMSO extraction, 3 replicates of each type

• 33 samples, total, then duplicate spectra

Tea Analysis Stack plot – DMSO samples – CRAFT reconstructions

Example of

CRAFT

results for

DSMO

extracts

Residual

CRAFT

Experimental

Tea Analysis Stack plot – DMSO samples – CRAFT reconstructions

Spectra

recorded for

DSMO

extracts;

3x samples

per variety of

tea, 2x

spectra per

sample tube,

CRAFTed

What is a Fingerprint?

• Often generated

from a standard

sample

• Can be extracted

from a CRAFTed

mixture

• Really, it’s just a

line list and

segment width

• Need not contain

every resonance in

a molecule!

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1 6 11 16 21 26 31 36 41 46 51 56 61

0

0.1

0.2

0.3

0.4

0.5

0.6

1 6 11 16 21 26 31 36 41 46 51 56 61

0

1

2

3

4

5

6

1 5 9 13172125293337414549535761

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1 6 11 16 21 26 31 36 41 46 51 56 61

0

1

2

3

4

5

6

7

8

9

1 5 9 13172125293337414549535761

Tea Analysis DMSO samples – CRAFTed concentrations

Epigallocatechin Gallate Theobromine

Glucose Caffeine

0

0.5

1

1.5

2

2.5

1 6 11 16 21 26 31 36 41 46 51 56 61

Epicatechin

Gallocatechin

Tea Analysis Caffeine reproducibility study

PCA plot – DMSO samples - Targeted

-2.3

-1.8

-1.3

-0.8

-0.3

0.2

0.7

1.2

1.7

1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5

China (black)

Rwanda

(black)

India (black)

Maybe better

than the hot

D2O extractions,

but still not

suitable for

sample class

prediction.

Tea Analysis Caffeine reproducibility study

PCA plot – DMSO samples - Targeted

-2.3

-1.8

-1.3

-0.8

-0.3

0.2

0.7

1.2

1.7

1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5

China (black)

Rwanda

(black)

India (black)

Green Teas

Maybe better

than the hot

D2O extractions,

but still not

suitable for

sample class

prediction.

Tea Analysis Caffeine reproducibility study

Selecting untargeted resonances

-8

-6

-4

-2

0

2

4

-9 -4 1 6 11

India

Rwanda

Japan China (black)

Tea Analysis Untargeted PCA – 56 peaks

“blended”

China (green)

PCA 1

PCA 3

Tea Analysis Untargeted PCA – 56 peaks

China (green)

China (black)

Japan

India

Rwanda

blended

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

-0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3

China (black)

India (black)

Rwanda (black)

Japan (green)

China

(blended)

Tea Analysis Untargeted PCA – every point

China (green)

PCA 1

PCA 2

Overview - CRAFT analysis of NMR data

• Introduction to the problems of frequency-based

analyses in Food Science

• Comparison of CRAFT to standard techniques

• Real-world applications Soy bean supplements – quality control

Tea – authenticity

Smelt – origin

CRAFT Fish (Agentina Sphyraena) perchloric acid extraction

Dr. Flaminia Cesare Marincola, U. Cagliari, IT

CRAFT Fish (Agentina Sphyraena) – 49 samples

Dr. Flaminia Cesare Marincola, U. Cagliari, IT

Spring

Winter

Fall – Different depth

Fall

CRAFT Fish (Agentina Sphyraena) – 32 ROIs

Sample courtesy of Dr. Flaminia Cesare Marincola, U. Cagliari, IT

Spring

Winter

Fall – Different depth

Fall

CRAFT Fish (Agentina Sphyraena) – PCA with 89 segments

Sample courtesy of Dr. Flaminia Cesare Marincola, U. Cagliari, IT

Spring

Winter

Fall – Different depth

Fall

NMR is Food Science Conclusions

• Time-domain analysis rapidly yields accurate and precise

results on even the most complex spectra.

• NMR analysis can be used to build high-fidelity sample class

prediction models for complex samples such as dietary

supplements and food science studies.

• You still can’t cheat physics.

Acknowledgements

Scott Bradley (Eli Lilly)

Andreas Kaerner (Eli Lilly)

Jonus Buser (Eli Lilly)

Allen Kline (ex Eli Lilly)

Ross Johnson (Eli Lilly)

Juel DeHoniesto (Eli Lilly)

Scott Baggett (Acorn)

Joe Ackerman (WashU, St. Louis)

Larry Bretthorst (WashU, St. Louis)

Krish Krishnamurthy

Frank Delaglio

Dan Iverson

He Liu

Mauro Cremonini

Dimitris Argyropoulos

Heiko Schill

Ron Crouch

Agilent