This presentation was given by Dr. Sara Stead during a webinar titled, "Addressing complex and critical food integrity issues using the latest analytical technologies," hosted March 18, 2016. Watch on-demand: https://goto.webcasts.com/starthere.jsp?ei=1093628 ABSTRACT: The ability to deliver safe, nutritious and authentic food to the world’s growing population is one of the most important and challenging tasks. To cope with this the supply systems of many commodities have become global in nature and are often very complex with multiple players involved. The potential for contamination of foods due to this complexity has increased considerably. When issues arise the ability to identify the cause of the contamination and origin of the food material implicated is often difficult and sometimes impossible. Of growing concern is the deliberate contamination of foods driven by economic gain. Food fraud has been in existence for many hundreds of years due as global food systems become more complex the opportunities for fraud have greatly increased and the impact these have on consumer health and trust. In 2011 a large study showed that over one third of all fish sold in the US have some sort of fraud associated with it. In Europe in 2013 the red meat supply system was shown to be infiltrated by criminal activity and thus the term food crime emerged. Food testing is one of the key roles of deterring and detecting food fraud. Due to the multiple types of fraud that can be perpetrated the challenges to be able to identify these are enormous and in some cases still impossible. A review of the types of fraud, the challenges to their detection and the potential for a paradigm shift in detection using rapid evaporative ionization mass spectrometry will be given. This webinar will consist of: - 30-minute presentation from Chris Elliot (Professor of Food Safety and Director of the Institute for Global Food Security, Queen’s University Belfast), on food fraud and authenticity issues, and the technology requirements. - 15-minute presentation by Sara Stead (Senior Strategic Collaborations Manager, Food & Environmental, Waters Corporation), on instantaneous determination of food authenticity by rapid evaporative ionisation mass spectrometry. - 15-minute live Q&A session, where you can pose questions to Prof Chris Elliot and Dr Sara Stead.

3. ©2016 Waters Corporation
40
Dr Sara Stead
sara_stead@waters.com
18th March 2016
Rapid Evaporative Ionisation
Mass Spectrometry (REIMS)
for Food & Agri-Tech Applications

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41
Overview
 Real time analysis for food testing
 Food authenticity applications
– Fish & meat speciation
– Botanical origin of honey
– Authenticity of PDO butter
– Phytochemical profiling in herbs
 Agri-tech applications
– Phenotypic profiling
 Summary & future study
 Acknowledgments

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Origins of REIMS
 Rapid Evaporative Ionisation Mass Spectrometry
(REIMS) is an emerging technique that allows rapid
characterisation of biological tissues with no need for
sample preparation
 The inventor, Professor Zoltan Takats of Imperial College,
London, created the iKnife, by connecting an
electrosurgical knife to a mass spectrometer
– Electrosurgical knives use an electrical current to rapidly
heat tissue, cutting through it while minimising blood loss
– In doing so, they vaporise the tissue, creating smoke that is
normally sucked away by extraction systems but is actually a
rich source of biological information that can provide the
surgeon a real-time decision-making tool

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Sample
REIMS Instrument Configuration
iKnife
Hand-held
sampling device(s)
Diathermy
generator
Informatics system
Source
REIMS is an emerging technique that
allows rapid characterisation of biological
tissues and food samples
Xevo G2-XS QTof
& SYNAPT G2 Si
Potential for automation – Tecan system

7. ©2016 Waters Corporation
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How Does it Work?

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45
REIMS for Food Research Workflow
Chemometric Profiling
iKnife
and Xevo
G2-XS QTof
Model
Generation
Different
tissues
Different
species
Different
production
Identification of unknowns
by similarity to database entries

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Direct Analysis for Flexible & Rapid Screening
Sub-sampling
Determination
(5s)
Data analysis
(2s)
Report
Sample to report in seconds
 Point-of-control analysis

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REIMS for Food Security
AGRI-TECHNOLOGY
PROTECTED STATUS

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Oceana Survey Undertaken in 2015
 Only 6% of Northern red
snapper fish collected were
truly red snapper (Lutjanus
campechanus)
 84% of tuna sold in sushi
restaurants was escolar
(health effects)
 Almost 50% of all grocery
stores visited in Boston sold
mislabelled fish
 31% of cod in Boston was
mislabelled

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Fish Speciation Study
Phylogentic tree
 Gadidae
– Cod; Haddock; Coley; Whiting & Pollock
 Pangasiidae
– River Cobbler & Basa (Vietnamese Catfish)
 Lophiida
– Monkfish
 Serranidae
– Sea Bass
 Salmo
– Atlantic salmon
 Pleuronectes
– European plaice

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North Atlantic Cod (Gadus morhua)
Gadidae genus
Glycerophospholipids
PAs
PEs
PCs
PIs
EPA
Eicosapentaenoic
acid
DHA
Docosahexaenoic
acid
Arachidonic acid
Hexadecanoic
acid
Fatty acids
Unsaturated&
saturated

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Spot the Differences?
REIMS neg ion +IPA 200 µl/min + leu enk
Cod
Whiting
Monkfish
Leu enk
[M-H]-

15. ©2016 Waters Corporation
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PROTOTYPE Software - PoP Multi-Species Fish Model
Gadidae species
Cod; haddock; whiting;
coley
Atlantic
Salmon
Salmo salar
Sea Bass
Dicentrarchus
labrax
Basa
Pangasius bocourti
Plaice
Pleuronectes platessa
Monkfish
Lophius piscatorius
PCA model LDA model
Real-time recogniser
software - prototype
n=≥3

16. ©2016 Waters Corporation
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Meat Speciation: An Emerging Issue in India
(October 2015)
Bos taurus vs. Bison bonasus

17. ©2016 Waters Corporation
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Polyunsaturated Fatty Acid (PUFA) Content
Ca. x1.6
Arachidonic acid
Ω6
C20H32O2
Eicosapentaenoic acid
Ω3
C20H30O2
Ca. x7
 Good ratio of Ω3:6 acids

18. ©2016 Waters Corporation
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Multi-Species Muscle Tissue – MVA Models
2 biological replicates of each species, 10 technical
replicates per sample.
PCA model
Non-ruminants
Ruminants
Buffalo Bovine
Porcine
Ovine
Gallus
gallus

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PROTOTYPE Real-Time Recogniser Software

20. ©2016 Waters Corporation
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Food Fraud & Authenticity Applications

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REIMS Spectra
Kaempferol
Apigenin
Oleanolic acid /
ursolic acid
Herbs & spices
PDO status Belgian butter
Botanical origin of honey
Essential Ω6 fatty acid
Ω9
Galangin Myricetin
Geographical origin of coffee
Caffeine
Tanzania
Peru
Kenyan
Colombian

22. ©2016 Waters Corporation
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Herbicide Selectivity in Cereals
and Competing Weeds
Collaboration with Prof Rob Edwards
University of Newcastle
School of Agriculture, Food & Rural Development

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Black-Grass vs. Rye Grass Spectral Comparison
(50 to 1200 m/z 6-8 combined scans)
Rye grass
B-G Pel
B-G Roth
B-G Oxford
B-G Nots
Black-grass grouped vs. Rye grass
EZInfo OPLS-DA scores & S-plot
-1.0
-0.9
-0.8
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
-0.14 -0.13 -0.12 -0.11 -0.10 -0.09 -0.08 -0.07 -0.06 -0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.20 0.21 0.22
p(corr)[1](Correlation)
p[1] (Loadings)
S-Plot(Blackgrass=-1,Lollium=1)
140.0263
90.0115
277.2171
165.0455190.0430 115.0312
166.0423
165.0222
741.4758
139.0313
117.0221
216.0587217.0469
99.9280
164.0275
192.0537141.0447
113.0162
193.0453
255.2326
191.0415
78.9608
837.4927
743.4941
89.0162
815.5041
191.0613
279.2326
141.0257
116.0273
167.0376
142.0379
189.0476
742.4819
143.0295
243.0625
240.0606
114.0118
167.0597
242.0682
278.2199
555.2222
215.0628
168.0474
267.0647
169.0422
268.0652
219.0560
218.0432
118.0312
220.0463241.0607
144.0446
218.0665
163.0323
505.2589
194.0420
214.0450
816.5106
244.0529
745.5052
266.0738
838.4946
170.0281
1169.7676
809.4982
195.0502
1170.7704
554.2578
242.0409
1171.7755
573.5311
245.0553
744.4981
269.0692
239.0650
293.0754
199.8563
861.7405
265.0702
145.0321
1147.7844
833.5289
264.0620
839.4948
140.0519
833.7086
270.0652
114.0359
292.0795
294.0695
395.3933601.5605
206.0688
840.6590
291.0720
819.5257
817.5112
831.5120
290.0772
189.0230
135.0443
196.0452
188.0293
1148.7867
180.0564
301.2278
138.0355
1172.7795
283.2641
317.0824
268.0890
537.2213
116.0503
545.4991
231.0683
168.0217
91.0147
195.0222
230.0694
719.4830
695.4716
256.2358
232.0608
423.4233
179.0543
156.0516
820.5289
129.0382
539.2049
257.0787
157.0513
862.7454
318.0788
295.0697
221.0507
205.0623246.0644207.0610119.0275
593.3974
746.5073
316.0869
213.0503
935.5658
574.5342
256.0841
697.4842
451.4525
1183.7466
1185.7577
121.0294
553.2010
836.5219
130.0399
319.0802
834.5370
204.0579
349.2758
511.1992
164.0516
615.2411
181.0549
281.2465
1184.7494
280.2354
229.0659
281.0806
834.7144
100.9284
523.2013
255.0738233.0434 283.0815
256.0594
493.1918506.2539
271.0566
1149.7875
527.1964
1114.7670
153.0357
763.4579
232.0847
116.9309
282.0823
180.0357
1173.7845
510.2015
112.0180
793.5181
889.7736
841.6608
842.6729
571.2109
203.0529
154.0434
233.0701
832.5140
494.1957
939.5429
131.0367
197.0286
247.0491
155.0549
190.0186
721.4974
343.0887
499.1964
254.0732
146.0259
1125.7343
88.0201
479.4843
258.0741
289.0826
182.0591183.0560
208.0551
306.0845
764.5134
982.5695
538.2233
341.0883
602.5622
128.0380
507.5155
1127.7435
927.5060
923.5465
1126.7379
280.0776
479.1825
999.5588
259.0824
508.2025
344.0854
320.0786
390.3002
342.0869271.0906
805.6771
234.0668
521.1984
480.1862
177.0352
1186.7628
305.0892
307.0834
171.0426
470.1903
134.0441
209.0619
321.0783
714.5068
1161.7667
275.2002
90.0361
747.5107
279.0792
971.5456
315.0858
86.0048
296.0437
178.0541
522.1994
936.5671
765.4983
339.3279
187.0355
308.0932
766.5297
571.4155
465.1740
253.0728
821.5335
345.0795
171.0229
351.1502
524.2039
835.5342
367.0932
953.5483
155.0360
863.5513
173.0254
330.0849
152.0394
134.0361
818.5092
696.4726
159.0453
535.2074
331.0911
890.7746
222.0601
934.5486332.0920
1029.7576
552.2083
296.0862
309.0531
339.2009
453.1693
340.0913
322.0610
645.5845
314.0816
1162.7695
133.0388
170.0606
325.1864
228.0655
272.0394
192.0204
567.2099
1187.7735
147.0445
543.2086
200.8561
132.0477
559.2517
329.0886
759.4156
304.0902
963.9555
263.0691
895.5434
308.0512
546.5031
812.5025
323.0755
928.5057
595.4112299.0494
720.4831
924.5485
309.1066
369.0903
466.1751
929.5025
1145.7617
361.1777
227.0571
155.0808
455.1726
396.3949
519.2065
220.0835
368.0918
977.5713
582.2216
1128.7421
869.4794
517.4678
93.0349
954.5319
357.0876
983.5672
130.0170
355.1006
391.2237
767.5241
680.6206
594.4002
505.1964
617.5527
413.2085
185.0665
949.5535
366.1005
880.5358346.0701
935.9283
297.1042
202.0548
698.4850
513.1827
333.0729
963.5594
92.0263
235.0678
397.1399
995.5513
158.0589
535.5463
806.5247
675.3567
297.0489
761.4208
356.0963
375.1952
921.5250
184.0468
1174.7899
717.4561
1104.7437
333.1133
863.7473
840.4870
483.2678
1129.7440
97.9335
387.1967
585.2164
383.1176
334.0639
806.6815
383.3529
393.1039
876.6168
284.0925
297.0779
222.0233
424.2853
119.0486
520.2085
738.4976
794.5208
365.0938
177.0546
925.5469
536.2122
715.5010
597.2156
454.1688
629.5896
91.0307
595.2075
152.9958
487.2402
471.1823
273.0879
1000.5560
311.1696
362.1768
272.0840
712.5001
978.5731
197.0660
310.0673
370.0874
507.2627
1175.8158
424.4255452.4554
285.0908
158.0335
260.0821
155.0118
835.7145
223.0551
878.6303
814.6333
613.5543
491.1776
109.0303
415.2190
173.0617
210.0585
285.0394
616.2455
161.0601
358.0800
249.0542
1030.7599
964.5654
843.6725
371.0899
876.5425
1146.7695
739.4558
392.1043
381.0982
1150.7916
528.1971
964.9639
760.4111
1008.0158
201.0541
303.0878
309.0703
630.2345
379.1128
940.5409
181.0963
922.5329
101.9269
974.7161
278.0866
848.5229
979.5653
1027.7450
161.0240
577.2661
678.6026
394.1029
353.0995
936.9360
643.5715
380.1014
381.3366
611.2240
1129.0284
572.2117
335.0821
298.0882172.0424
405.2047
615.5484
984.0194
1163.7616
1104.0270
713.4889
671.4595
311.0738
853.4854
144.0202
657.5788
456.1846
641.5835
354.0966395.1038
955.5296
587.5335
966.5490
626.2206
850.5415
871.4804
598.2299
816.0143
508.5154
596.2097
1061.6688
960.0241
1009.0187
480.4886407.1135
910.5355
248.0783
441.1630
419.1153
877.5419
382.1028
337.1805
1092.7682
967.5453
577.4370
199.0818
359.0810
492.1864
211.0795
1128.0242
391.1047
1116.7652
888.0191
443.1177
1076.68631101.6946
1025.5946
985.0237
353.1390
351.2037
185.0363
881.5267
545.1675
529.1878
1105.0264
808.5375
212.1010
1080.0206
1188.7752
842.4172
347.0782
328.0995
991.9899
822.5432
238.0653
1177.0292
1056.0196
336.0916
1152.0261
941.4851
385.1576
996.5468
599.5438
286.0954
912.0200
736.4886
477.1631
723.4610
373.1792
682.6372
297.1571
424.2554
1153.0318
1077.6817
417.1167
1032.0182
575.5372
1081.0276
457.1728
646.5837
406.1163
1057.0244
768.5507
439.1567
186.0611
350.2724
105.0342
840.0166
877.6174
178.0315
444.2226
489.4342
669.4536
274.0896335.1721
127.0392
904.6364
1105.7352531.4575
105.9764
226.1188
257.1262
587.2073
864.0153
260.0298
323.1720
197.8611
186.1232
475.4315
1063.6717
401.2098
313.1020
120.0131
358.1301
275.1127
1189.7851
236.0714
389.2100
261.0734
657.3444
889.0225
555.4441
248.1204
329.1619
943.4821
529.5383
722.4929
363.1866
549.4320
813.4838784.5423
180.10461131.7491
1005.6043
478.1732
222.1208
950.5652
346.1323
559.5014
463.1775
360.1053
337.1090
325.1095
334.1160
109.0398
903.6501
421.1211
707.2238
859.7265
378.1661
643.2196
1049.6629
416.1204
322.1176
287.0734
359.1322
913.0189
1176.0280
961.0253
1007.5990
300.1208
113.0397
187.0761 792.0152
461.1220
1033.0226
418.1203
198.0538
372.1041
1117.7697
896.5378
339.1185
339.0914
817.0204
451.1673
361.1149
603.5618
436.3959
288.0770
212.1395
627.5718
325.2255
513.3007
563.1564
324.1060
429.1438
143.0602211.0459
681.6216
252.0752
580.2245
787.4365
449.1756
472.2560
458.2333
405.1165
430.1264
404.1180
891.7797
262.1424
95.0203
415.1419
907.8908
829.7492
1102.6966
1001.5657
414.2048
409.1156
390.1071
992.9976
463.2314
445.1202
586.2180
720.0138
384.1000
865.0185
515.1799
797.4761
364.0969
1130.7423
841.0183919.5413
224.1065
533.2041
509.3084237.0665
388.1917433.1470
358.1740
209.1241
968.5170
571.5123
631.2458
312.0895
812.6135
885.8056
737.4302
486.2015
610.2351
1006.5871
327.1186
566.2113
453.2367
1021.5873
172.0879
352.1521
326.1718
376.1946
655.5710
1003.6396
302.1319
544.2009
231.1225
699.4913
422.2393
147.0111
534.2169
359.1688
399.1920
398.1491
875.5116
1073.6596
787.5007
789.5062
579.2587
258.0297
865.5635
178.0966
997.5427
799.4347
408.1001
141.0671
565.2118
262.0926
600.2308
431.1249
693.4409
625.2238
403.1293
98.0043
861.5444890.5095
204.1051
437.1725775.4112
431.1900
373.1305
355.3198196.0976
731.3592
773.4037
1028.7470514.1693
444.1353
199.0420
1015.5624
529.2651
1019.6235
406.2073
210.1220
848.6200
614.5565
411.1637
213.1022
377.2055
442.1662
427.1665
501.1862
748.5024
976.7251
106.0404
348.1091
993.5616
105.0224
364.1958
465.2444
831.6978
411.3810
392.1980
447.1331
635.3838
198.0305
275.0798
467.2536
913.8408
192.1084
183.1050
396.0984
473.1403
440.1536
873.4682
1062.6651
517.1728
589.5261
386.1463
201.8539
194.1229
238.1188
207.1104
991.5809
212.0594
464.1793
428.1708
911.5094
374.1481
813.5368
729.3762
857.7775
495.2886
283.1425
486.2666
774.3735
1059.6627
780.5173
525.3496
573.2068
948.5331
260.1294312.1671
371.1714
446.1364
860.5493226.0647
152.0676
676.3465
975.7116
1130.0258
536.5522
430.2003
851.5357
1020.0218
980.5620
774.4096
493.2667
146.0603
609.2011
769.5379
793.0167
641.2360
269.1252
873.5703
378.1136362.1304
1041.5820
726.5051
448.1786
354.1711
309.1548
186.0960
388.1317
942.4849
533.4684
1010.0171
338.1774
259.1430
1154.0310
721.0149
380.1917
618.5555
434.1273
389.1118
439.2265
503.4686
1035.6243
446.1877
154.0831
941.8797
1057.6240
331.1661
399.1458
403.1945
1033.6467
642.2377
387.1298
459.1785
548.2840
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EZInfo controlled byProgenesis QI3 - Black grass vs lollium.usp (M9:OPLS-DA) - 2015-12-11 17:15:17 (UTC+0)

24. ©2016 Waters Corporation
61
Summary & Future Prospects
 REIMS for food authenticity?
– Direct analysis technique results possible in seconds
o New ionisation technique
– Simplicity of operation & potential for automation
– Point-of-control analysis… bringing the analysis to the sample
o RTR software commercialisation June 2016
 Chemometric profiling
– Holistic profiling of the sample for QC
– Detection of the “unexpected” for authenticity
o Potential to identify & verify unique product markers
 Liquid sampling REIMS
– Alcoholic beverages; fruit juices; milk & edible oils
 Implementation of ion mobility into the workflow to enhance power to differentiate sample
types & model generation (CCS)

25. ©2016 Waters Corporation
62
Acknowledgements
 Prof Zoltan Takats (Imperial College, London)
 Dr Simon Hird, Dr Jonathan Williams, Dr Emrys Jones, Dr Julia Balog,
Dr Steve Pringle, Dr Mike Morris, Dr Jackson Pope (Waters, Manchester
and Budapest)
 Prof Chris Elliott, Dr Olivier Chevallier, Connor Black (Queens
University, Belfast)
 Prof Rob Edwards, Dr Melissa Brazier-Hicks, Dr Catherine Tetard-Jones
More Fish!