Food fraud has become a major concern in recent years. Fruit juice is commonly adulterated with cheaper alternatives. High resolution MS in combination with 'omics data analysis approaches can identify markers of adulteration.

1. ©2015 Waters Corporation 1
Investigating Fruit Juice Authenticity using
MS and ‘Omics approaches

2. ©2015 Waters Corporation 2
Presentation overview
 Project Background
 Workflow
 Results
o UV
o MS
 Sample Comparison
o Visual inspection
o Software interpretation
 Why are they different?
o Are there any marker compounds?
o Can we ID marker compounds?
 Ion mobility for discovery of natural compounds

3. ©2015 Waters Corporation 3
Project background
 Activities in food fraud and authenticity has increased in
importance over the last decade
– Estimated to cost $10-$15 billion per year
 Fruit juices (orange and apple juice) were in the top 7 foods
reported from 1980 to 2010 as the most common targets for
adulteration
 Food & beverage products are adulterated in many different ways:
– Be harmful to health
– Misleading to the consumer
o …includes unacceptable enhancement, dilution and/or substitution with
less expensive ingredients, failure to declare contamination and
inaccurate or misleading labelling of a product or ingredient
 Reported cases of adulterated fruit juices have been economically
driven, e.g. inclusion of high fructose corn syrup, other fruit juices…

4. ©2015 Waters Corporation 4
Workflow Overview
How did we perform the analysis?

5. ©2015 Waters Corporation 5
Results:
PDA & MS (exact mass) Data
Time
2.00 3.00 4.00 5.00 6.00 7.00
%
1
2.00 3.00 4.00 5.00 6.00 7.00
%
3
2.00 3.00 4.00 5.00 6.00 7.00
AU
0.0
2.5e-2
5.0e-2
PA_24_2_010 4: Diode Array
269
Range: 7.395e-2
4.81
1.30
4.29
1.75 2.53
3.99
5.66
PA_24_2_010 1: TOF MS ES-
BPI
2.09e4
2.85
1.33
1.83
5.24
4.44
3.91
5.68
PA_24_2_010 2: TOF MS ES-
BPI
9.19e3
5.04
1.33
5.68
MS –
product ions
MS –
precursor ions
PDA

6. ©2015 Waters Corporation 6
Sample Comparison
Visual inspection – Study Samples:
Time
1.00 2.00 3.00 4.00 5.00 6.00 7.00
AU
0.0
5.0e-2
1.00 2.00 3.00 4.00 5.00 6.00 7.00
AU
0.0
5.0e-2
1.00 2.00 3.00 4.00 5.00 6.00 7.00
AU
0.0
5.0e-2
1.29 4.80
4.56
2.73
1.73 3.27
5.61
1.30
4.80
4.55
2.70 3.26
5.61
4.81
1.30
4.44
2.71 3.27
5.65

7. ©2015 Waters Corporation 7
-600
-500
-400
-300
-200
-100
0
100
200
300
400
500
600
-1200 -1000 -800 -600 -400 -200 0 200 400 600 800 1000 1200
t[2]
t[1]
Scores Comp[1] vs. Comp[2] colored by Sample Group
S10
S11
S12
S12
S12
S12
S12
S12
S12
S12
S11
S11S11
S11S11
S11
S11
S11
S10
S10
S10
S10S10
S10
S10
S10S10
EZinf o 2 - Negativ e_Pineapple_no_QC_3_samples (M8: PCA-X) - 2011-02-28 20:50:30 (UTC-5)
Sample Comparison
Software inspection – Study Samples

8. ©2015 Waters Corporation 8
Sample Comparison
Software inspection – Study & Supermarket samples
Supermarket
samples
Study
samples

9. ©2015 Waters Corporation 9
Identify Markers for Observed Differences
OPLS-DA Model: 207 / 316 & 102

10. ©2015 Waters Corporation 10
Identify Markers for Observed Differences
S-Plot: 207 / 316 & 102
-1.0
-0.8
-0.6
-0.4
-0.2
-0.0
0.2
0.4
0.6
0.8
1.0
-0.2 -0.1 -0.0
p(corr)[1]P(Correlation)
w*[1]P (Covariance)
S-Plot (S10 = -1, S11_S12 = 1)
EZinf o 2 - Negativ e_Pineapple_S10_VS11S12 (M6: OPLS-DA) - 2011-03-11 09:49:12 (UTC-5)
Rt 5.03-
m/z 649.2495
Rt 5.55-m/z
579.1712
Rt 5.67-m/z
609.1616
Rt 5.10-m/z
711.2862

11. ©2015 Waters Corporation 11
Identify Markers for Observed Differences
Trend Plot for the markers in all samples
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
S12
S12
S12
S12
S12
S12
S12
S12
S11
S11
S11
S11
S11
S11
S11
S11
S10
S10
S10
S10
S10
S10
S10
S10
QC
QC
QC
QC
QC
QC
QC
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
Sample Group
Variables
EZinf o 2 - Negativ e_Pineapple_w_QC (M6: PCA-X) - 2011-03-11 10:35:34 (UTC-5)

12. ©2015 Waters Corporation 12
Why are there differences?

13. ©2015 Waters Corporation 13
Why are there differences?
Marker ID – using R.T, MS and UV

14. ©2015 Waters Corporation 14
Time
1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 5.50 6.00 6.50 7.00 7.50
%
0
100
1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 5.50 6.00 6.50 7.00 7.50
%
0
100
1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 5.50 6.00 6.50 7.00 7.50
%
0
100
PA_24_2_063a 1: TOF MS ES-
609.182 0.0030Da
8.09e3
PA_24_2_062a 1: TOF MS ES-
609.182 0.0030Da
8.09e3
5.66
PA_24_2_061a 1: TOF MS ES-
609.182 0.0030Da
8.09e3
Why are there differences?
Marker ID – using R.T, MS and UV

15. ©2015 Waters Corporation 15
Why are there differences?
Marker ID – using R.T, MS and UV
m/z
50 100 150 200 250 300 350 400 450 500 550 600 650
%
0
100
301.0706
609.1822

16. ©2015 Waters Corporation 16
Why are there differences?
Marker ID – using R.T, MS and UV
m/z
50 100 150 200 250 300 350 400 450 500 550 600 650
%
0
100
301.0706
609.1822

17. ©2015 Waters Corporation 17
nm
260 280 300 320 340
AU
0.0
5.0e-3
1.0e-2
1.5e-2
2.0e-2
2.5e-2
nm
260 280 300 320 340
AU
0.0
5.0e-3
1.0e-2
1.5e-2
2.0e-2
2.5e-2
Time
3.00 4.00 5.00 6.00 7.00
AU
0.0
1.0e-2
2.0e-2
3.0e-2
4.0e-2
5.0e-2
3.00 4.00 5.00 6.00 7.00
AU
0.0
1.0e-2
2.0e-2
3.0e-2
4.0e-2
5.0e-2
PA_24_2_096a 4: Diode Array
283
Range: 2.583e-2
5.66
PA_24_2_071a 4: Diode Array
283
Range: 5.559e-2
4.83
4.31
2.73
3.993.33
5.03
5.66
Confirm marker Identification
Marker ID – using R.T, MS and UV

18. ©2015 Waters Corporation 18
Confirm marker Identification
Marker ID – using R.T, MS and UV
Time
1.00 2.00 3.00 4.00 5.00 6.00 7.00
%
0
100
1.00 2.00 3.00 4.00 5.00 6.00 7.00
%
0
100
PA_24_2_098a 2: TOF MSMS ES-
609.182 0.0050Da
1.96e3
5.67
PA_24_2_093a 2: TOF MSMS ES-
609.182 0.0050Da
3.57e3
5.67
m/z
100 200 300 400 500 600
%
0
100
m/z
100 200 300 400 500 600
%
0
100
301.0707
609.1819
301.0706
609.1821

19. ©2015 Waters Corporation 19
Hesperidin Sources

20. ©2015 Waters Corporation 20
Identifying other markers highlighted....

21. ©2015 Waters Corporation 21
Identify Markers for Observed
Differences
Trend Plot for the markers in all samples
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
S12
S12
S12
S12
S12
S12
S12
S12
S11
S11
S11
S11
S11
S11
S11
S11
S10
S10
S10
S10
S10
S10
S10
S10
QC
QC
QC
QC
QC
QC
QC
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
Sample Group
Variables
EZinf o 2 - Negativ e_Pineapple_w_QC (M6: PCA-X) - 2011-03-11 10:35:34 (UTC-5)

22. ©2015 Waters Corporation 22
Time
2.00 3.00 4.00 5.00 6.00 7.00
%
0
100
2.00 3.00 4.00 5.00 6.00 7.00
%
0
100
2.00 3.00 4.00 5.00 6.00 7.00
%
0
100
PA_24_2_070a 1: TOF MS ES-
579.171 0.0030Da
4.12e3
PA_24_2_071a 1: TOF MS ES-
579.171 0.0030Da
4.12e3
5.54
PA_24_2_072a 1: TOF MS ES-
579.171 0.0030Da
4.12e3
Identify Markers for Observed
Differences
Potential Compound ID’ed as Naringen

23. ©2015 Waters Corporation 23
Time
2.00 4.00 6.00
%
0
100
2.00 4.00 6.00
AU
0.0
1.0e-2
2.0e-2
PA_24_2_097a 4: Diode Array
280
Range: 3.084e-2
5.57
PA_24_2_097a 1: TOF MS ES-
579.171 0.0030Da
1.73e4
5.59
Identify Markers for Observed Differences
Potential Compound ID’ed as Naringen
Same elemental
composition
C27H31O14
Time
2.00 4.00 6.00
%
0
100
2.00 4.00 6.00
AU
0.0
2.0e-2
4.0e-2
6.0e-2
PA_24_2_062a 4: Diode Array
280
Range: 6.675e-2
1.31
4.80
4.28
2.70
3.95
3.31
5.64
PA_24_2_062a 1: TOF MS ES-
579.171 0.0030Da
8.08e3
5.54

24. ©2015 Waters Corporation 24
Identify Markers for Observed Differences
Potential Compound – Naringen ”like”
m/z
100 200 300 400 500 600
%
0
100
m/z
100 200 300 400 500 600
%
0
100
579.1720
271.0604
151.0029
459.1152
271.0603
151.0029 579.1714
Naringin like
component
nm
260 280 300 320 340
AU
0.0
5.0e-3
1.0e-2
1.5e-2
nm
260 280 300 320 340
AU
0.0
5.0e-3
1.0e-2
1.5e-2
nm
260 280 300 320 340
AU
0.0
5.0e-3
1.0e-2
1.5e-2
nm
260 280 300 320 340
AU
0.0
5.0e-3
1.0e-2
1.5e-2
JA-11S2-102

25. ©2015 Waters Corporation 25
C27H32O14
MW:580.54

26. ©2015 Waters Corporation 26
Identify Markers for Observed Differences
Trend Plot for the markers in all samples
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
S12
S12
S12
S12
S12
S12
S12
S12
S11
S11
S11
S11
S11
S11
S11
S11
S10
S10
S10
S10
S10
S10
S10
S10
QC
QC
QC
QC
QC
QC
QC
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
Sample Group
Variables
EZinf o 2 - Negativ e_Pineapple_w_QC (M6: PCA-X) - 2011-03-11 10:35:34 (UTC-5)

27. ©2015 Waters Corporation 27
Identify Markers for Observed Differences
Trend Plot for the markers in all samples
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
11000
12000
13000
14000
S12
S12
S12
S12
S12
S12
S12
S12
S11
S11
S11
S11
S11
S11
S11
S11
S10
S10
S10
S10
S10
S10
S10
S10
QC
QC
QC
QC
QC
QC
QC
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
LWOPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
KnPAJ
Sample Group
Variables
EZinf o 2 - Negativ e_Pineapple_w_QC (M6: PCA-X) - 2011-03-11 10:35:34 (UTC-5)
Rt 5.10 min, m/z 711.2862
Nomilinic acid 17-beta-D-glucopyranoside
(NAG)
Rt 5.03 min, m/z 649.2495
Limonin 17-beta-D-glucopyranoside (LG)

28. ©2015 Waters Corporation 28
Conclusions

29. ©2015 Waters Corporation 29
Conclusions
 Using the data processing tools we were able to identify the
presence of citrus components in JA-11S2-102.
 Flavone-O-glycosides
– Hesperidin
– Naringin “like” compound possibly narirutin
 Tentative identification of two citrus limonoids (no standards
available)
– Limonin 17-beta-D-glucopyranoside (LG)
– Nomilinic acid 17-beta-D-glucopyranoside (NAG)