Post on 21-Jun-2018
FE
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NT Authenticity Testing of Food
- State of Play and Future Challenges -
Carsten Fauhl-Hassek
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 2
WHO AM I ?WHERE AM I
FROM ?
Authenticity Testing
Authentication: confirmation of all requirements regarding the legal product description
or the detection of the fraudulent statements, particularly in view of:
(i) the substitution by cheaper but similar ingredients,
(ii) extension of food using adulterant (e.g. water, starch including exogenous material)
or blending and/or undeclared processes (e.g. irradiation, extraction)
(iii) the origin, e.g. geographic, species or method of production.
Esslinger, S., Riedl, J., Fauhl-Hassek, C., Food Research International, 60, 189-204 (2014)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 3
Authenticity of food
Authenticity
Labelling
GeographicalOrigin
Identity (Composition)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 4
Authenticity of food
Motivation
Food
QualityFood Fraud I 1 Gain: Economic
Food
Safety
Food Fraud II
Food Defense
Harm:
Public Health, Economic or Terror
Unintentional Intentional
Action1 Includes the subcategory of economically motivated adulteration
and food counterfeiting
Journal of Food Science, 76(9), 157-163 (2011) Spink, J. and Moyer, D.C.
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 5
Codex Alimentarius: „Traceability/product tracing:
the ability to follow the movement of a food through specified stage(s) of production, processing and distribution.“
(Regulation (EC) No 178/2002 § 3 p 15)
Traceability systems trace and track “food packaging”
Definition: Traceability
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 6
1. Analysis of composition• Classical analysis, wet chemistry, chromatography, spectroscopy,• Detection of non-natural food constitutes
2. Analysis of stable isotopes• (D/H, 13C/12C, 18O/16O, 15N/14N)
3. Enantioselective analysis
4. Molecular biological methods
5. Non-targeted analysis (analysis of composition)• Spectroscopy, spectrometry
Analytical methods for authentication
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 7
P = 0,95
α = 0,025α = 0,025
± Student Factor x σ
Authenticity range
Authentic or unsuspicious samples
Analytical methods for authentication
Classical approachReference Data (bases)
e.g. German RSK system Fruit Juices(Standard Values and Ranges of certain analytical characteristics)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 8
• Glycerol 4,8-14 g/l
• Methods: wet chemistry, GC, HPLC, NMR
Water
Wine
Alc.Acid
Addition of glycerol to wine
Composition1) Composition
Cyclic Diglycerols (Dioxan, Dioxepan)
O HO
CH3
OH
3-Methoxy-propandiol
O
O
OH
HO
O
O
OH
HO
OO
OH
OH
OO
OH
OH
O
O
HOHO
Fauhl C, Wittkowski R, Lofthouse J, Hird S, Brereton P, Versini G, Lees M, Guillou C (2004), Journal of AOAC International 87: 1179-1188
• in 1997: 140 of 850 samples were
“positive” (16 %)
• in 1999: 3 of 150 samples were “positive”O
O
HO
HO
• By-products in technical glycerin (exogenous wine substances)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 9
Stable Isotope Ratios “Fingerprint”
Stable isotopes2) Stable isotopes
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 10
δ 18O-value of wine
water (‰ vs VSMOW)-1,0
+7,5
+8,5
+3,5
-0,5 - + 3,0
~ + 6
Stable isotopes
Geographical origin of wine
2) Stable isotopes
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 11
Jamin et al. J. Agric. Food Chem., 2003
Tap water is enriched:-7 to -15 ‰ δ 18O
Stable isotopes
Addition of water direct juices δ 18O
2) Stable isotopes
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 12
-8 -6 -4 -2 0 2 4 6
Discriminant function 1
-3
-2
-1
0
1
2
3
4
Dis
crim
inant fu
nct
ion 2
EU
China
USA
EUChina USA group centroids
Canonical discriminant analysis (CDA)
Especially for EU-USA differentiation
www.qsaffe.eu
Journal of Agricultural and Food Chemistry, 61, 7225-7233(2013) Nietner,T.; Pfister, M.; Glomb, M.A.; Fauhl-Hassek, C.
Stable isotopes
Geographical origin of feed
2) Stable isotopesAnalysis of Distillers Dried Grains and
Solubles (DDGS) by FT-IR
(directly and after sample extraction)
• DDGS is a global commodity,
• Co-product of ethanol production,
• High nutrient content (protein, fat)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 13
� 1,500-3,000 $ kg-1 natural vanillin
� 40 t year-1
� 15000 t year-1
� 15 $ kg-1
Vanillin
Stable isotopes2) Stable isotopes
SNIF®-NMR
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 14
Analysis of Bergamot oil
AcO HO
1 (R), 2 (S) 3 (R), 4 (S)
**
LinaloolLinalyl acetate
� Wine analysis �Flavour additions (peach)
Enantioselective
analysis3) Chiral analysis
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 15
Microarray technology, microsatellite analysis,
real time PCR, proteomics applicationsProduct adulteration in meat
products, e.g.
• horsemeat,
• Pork in Halal products
Challenges:
• highly processed products
(oil, wine, meat-
and-bone meal)
• targeted !!
Molecular-biological
methods4) Differentiation of species
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 16
Aim: Identification of deviations
Sample preparation
2D data 3D data
FT-IRNMR LC-HR-MS
Applicability:
• Comprehensive characterization
• Differentiation of samples due to:
� Botanical origin
� Geographical origin
� Adulterations
� …
• Detection of emerging adulterated products
Early detection of risks/hazards
Non-targeted analysis5) Fingerprinting
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 17
Non-targeted analysis
variables (e.g. analytical results, meta data)n s
am
ple
s
(poss
ibly
diff
ere
nt
sam
ple
gro
ups)
Cluster 1 2 3 4 5
ppm 4.36 4.35 4.34 4.33 4.32
Sample Code Colour Origin
1379_1_1 red Hungary 0.031 0.054 0.024 0.074 0.100
1380_1_1 red Hungary 0.030 0.129 0.094 0.176 0.192
1381_1_1 white Hungary 0.317 0.267 0.287 0.273 0.179
1388_1_1 red Hungary 0.022 0.116 0.031 0.157 0.086
1389_1_1 red Hungary 0.275 0.180 0.273 0.159 0.184
1390_1_1 red Hungary 0.084 0.140 0.031 0.159 0.087
1391_1_1 red Hungary 0.610 0.419 0.413 0.436 0.398
• Data matrix:
5) Fingerprinting - Multivariate statistics
• Unsupervised methods (pattern recognition)
e.g. Cluster Analysis, Principal Component Analysis (PCA)
• Supervised methods (examine structure)
Discriminant analysis (DA), Class modeling (e.g. SIMCA)
• Quantification Partial Least Squares (PLS) Regression
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 18
Example 1: Determination of melamine
• Investigation of different milk powders
(bought in 2008)
• Analysis using 1H-NMR (400 MHz)
• Identification of melamine via exogenous
signal at 5.93 ppm (NH2 groups)
lactose HO1-α
lactose HO1-βurea
CH3/CH2 fatty acids
lactoce
TMS
DMSO
TMU
7.5 5.0 2.5 ppm
Non-targeted analysis5) Fingerprinting
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 19
• Scope: development of non-targeted analytical procedures
to identify chemical hazards in spices and herbs
• Analysis using 1H-NMR spectroscopy after simple sample
preparation
• Analysis of paprika powder (250 samples), spiked with e.g.
sudan dyes or beetroot
Non-targeted analysis5) Fingerprinting
Example 2: Adulterated paprika powder
http://www.spiced.eu
-160000
-120000
-80000
-40000
0
40000
80000
120000
-120000 -80000 -40000 0 40000 80000 120000 160000
PC
-2 (
21
%)
PC-1 (35 %)
Authentic samples
5 % beetroot
10 % beetroot
20 % beetroot
-160000
-120000
-80000
-40000
0
40000
80000
120000
-120000 -80000 -40000 0 40000 80000 120000 160000
PC
-2 (
21
%)
PC-1 (35 %)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 20
Non-targeted analysis5) Fingerprinting
BfR study
• 495 commercial wines
• Vintages 2006 - 2011
• Different geographical origin
• Steel tank/barrique
• Different quality attributes
• PLS-DA of 353 white wine
samples
Commercial system:
WineScreenerTM
Example 3: Differentiation of white wine by 1H-NMR spectroscopy
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 21
• Scope: discrimination between different seed oils and
authentic/adulterated sunflower oils using FT-IR spectroscopy
• Spiked samples: addition of mineral oil
• Direct analysis of 419 edible oil samples
Wavenumbers (cm-1)
Abso
rbance
mineral oilsunflower oil
� Detection of 0.5 % mineral oilis possible
unpublished Pfister, M.K.-H., Gründler, A., Esslinger, S., Fauhl-Hassek, C.
Non-targeted analysis5) Fingerprinting
Example 4: Identification of adulterated edible oils
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 22
Probennr. 164_367893_3678 64_3678 121_3756136_375693_3756 79_3756 57_3868 74_3868 89_3868 101_386888_3869 129_386969_3869 191_4167…
3456 112 112 112 112 112 112 112 453 3425 45324 234 345 4567 234 112
456 678 3489 356 234 345 4567 4567 4567 723 5647 234 345 4567 453 3421
1234 112 112 112 112 112 112 112 234 563 45673 4563 567 3456 567 23455678 216 1890 567 4563 567 3456 784 112 112 112 112 112 112 112 112
2974 4563 567 3456 216 1890 567 345 678 3489 356 234 345 4567 4567 112
1964 234 345 4567 456 321 56745 456 112 112 112 112 112 112 112 1124503 237 4567 5678 4567 723 5647 934 216 1890 567 4563 567 3456 784 456
45 112 112 112 112 112 112 112 4563 567 3456 216 1890 567 345 234
389 456 4563 45673 4567 723 5647 523 234 345 4567 456 321 56745 456 678476 453 3425 45324 234 345 4567 234 237 4567 5678 4567 723 5647 934 956
4387 112 112 112 112 112 112 112 112 112 112 112 112 112 112 234
34 3467 3456 67845 456 321 56745 678 456 4563 45673 4567 723 5647 523 1234231964 456 321 56745 4563 567 3456 345 453 3425 45324 234 345 4567 234 67436
5629 112 112 112 112 112 112 112 112 112 112 112 112 112 112 45896
456 3421 453 45673 4567 723 5647 130 3467 3456 67845 456 321 56745 678 34213459 2345 784 45673 456 321 56745 453 456 321 56745 4563 567 3456 345 4538
4782 112 112 112 112 112 112 112 112 112 112 112 112 112 112 8978
32 4567 723 5647 234 345 4567 453 3421 453 45673 4567 723 5647 130 563784 234 563 45673 4563 567 3456 567 2345 784 45673 456 321 56745 453 456
...
N
K
H
Chromatography-MS
H
Sample1
Sample N
…
data preprocessing
m/z_Scan
Sample
Rubert J., Lacina O., Fauhl-Hassek C., Hajslova J. Anal Bioanal Chem 2014 May 28.
Springer AE, Riedl J, Esslinger S, Roth T, Glomb MA, Fauhl-Hassek C, J Agr.Food Chem. 2014 62(28): 6844-51
Non-targeted analysis5) Fingerprinting – 3 dimensional data
Example 5: Wine authentication (grape varieties)
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 23
• „good practice“
• conduction
• publication
within one lab
BfR research: “Non Targeted Analysis” in foodauthentication (2007-2013):
Out of 267 only 196 publications state n n (Ø)= 118 samples
Validation of non-targeted methodsNon-targeted analysis
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 24
Lab 1
1
2
3
4
n
Research
Food Screener™ from Bruker
Proprietary measurement procedure
Lab 1
n + x
Lab 2 Lab 3
n + x n + x
Lab 4 Lab n
?
Data consistencyNon-targeted analysis
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 25
• 38 partners
• funded by EU with 9,000,000 €
• Jan 2014 – Dec 2018
Addressing the gap between existing knowledge & accessibility
• Network of experts
• Data sharing
• Food Fraud Early Warning System
EU-project ‚Food Integrity‘ – Ensuring the Integrity of the European food chain
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 26
• Globalization also in case of fraud, prediction hardly possible
• Fraudsters taking health risks to consumers
• Divers range analytical approaches for food authentication
• Authentication needs „reference data“
Application of consistent MethodsAcceptance of authentic ranges
• Trend to multivariate data evaluation
Often feasibility studies with limited data sets
Not yet fully applicable in official control
Summary 1
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 27
Management activities :
• Food Fraud Net
• Authentication in VO (EG) Nr. 882/2004
• EU-RL Food Authenticity ?
• Research: „FoodIntegrity“
Melamine (2008)
Horsemeat (2013)
Summary 2
Scientific activities:
• Detection of unknown additives
• Non-targeted analysis
Carsten Fauhl-Hassek, 2015-02-18, 32nd Meeting of the Forum of FLEP Page 28
• Non-targeted strategies, e.g. using NMR, MS, FT-IR will
become increasingly important
• Combination with targeted applications
• Implementation of methods/approaches from research to
routine analysis/official control
Control 2035 ?
Outlook