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Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food Science, UBC Date: Nov. 7 th , 2016 1

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Page 1: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Detection of food fraud and

adulteration using novel

spectroscopic techniques

Xiaonan Lu

Assistant Professor

Food Science, UBC

Date: Nov. 7th, 2016

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Page 2: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Food fraud incidents

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Page 3: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Oceana Survey of US Seafood:

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Page 4: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

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Page 5: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Food fraud incidents (con’t)

Figure 1. Food fraud incidents categorized by food group

(summarized by Food Protection and Defense Institute)

http://www.foodfraudresources.com/ema-incidents/ 4

Page 6: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Definition of food fraud• Food fraud

“the deliberate and intentional substitution,

addition, tampering, or misrepresentation of food,

food ingredients, or food packaging; or false or

misleading statements made for food products for

economic gain” – Spink and Moyer, 2011

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Page 7: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Definition of food fraud (Con’t)

Figure 2. Food protection risk matrix (Spink & Moyer, 2011)

Food

Quality

Food

Fraud1

Food

Safety

Food

Defense

Motivation

Gain: Economic

Harm:

Public Health,

Economic, or

Terror

Unintentional Action Intentional

1Includes the subcategory of economically motivated

adulteration and food counterfeiting

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Page 8: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Economic loss of all parties (i.e. food industry,

government, consumers)

Weaken consumers trust in food industry and

government

Potential health risks

allergens incorporated

pathogen contaminated

poisoning

Detriments of food fraud

Food safety

&

Food defense

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Page 9: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Traditional analytical techniques

• complex

• time consuming

Sample preparation

• complicated instrumentation

• marker specific methodology

LC/GC• complicated

instrumentation

• marker specific methodology

UV/DAD/MS

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Page 10: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Traditional techniques (con’t)

• Fail to achieve:

rapid analysis

high-throughput screening

user-friendly procedures

detection of new types of deceptive behaviors

• Alternative:

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Page 11: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Vibrational spectroscopies

• Raman and FT-IR spectroscopies

Vibrational signals of functional groups

Scattering or absorption spectra

Figure 3. Vibrational modes of molecules

symmetrical

stretching

Rocking Wagging TwistingFigure 4. Representative

Raman spectra

Asymmetrical

stretching

Scissoring

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Page 12: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Vibrational spectroscopies (con’t)

• NMR spectroscopy

Vibrational signals of nucleus

Resonance frequency spectra

NMR: nuclear magnetic resonance

Figure 5. Nucleic magnetic moment changes in

NMR spectroscopyFigure 6. Representative 1H

NMR spectrum

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Page 13: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Vibrational spectroscopies (con’t)

• Advantages

Non/less-destructive

Rapid

Comprehensive chemical composition

Unique fingerprinting features

Able to emerge any extraneous materials

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Page 14: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Current projects in the lab

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Page 15: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

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Page 16: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

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Page 17: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

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Page 18: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

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Page 19: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

• Detection and quantification of beef and pork offal in

ground beef meat

Two types of

beef meat

Three types of

pork offal

Three types of

beef offal

Raman spectrometer

FT-IR spectrometer

Chemometric analyses

Figure 7. Schematic illustration of

experimental design 18

Page 20: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Figure 8. Differentiation of beef meat and offal pure samples by

PCA models. Left, representative PCA for Raman spectroscopy;

right, representative PCA for FT-IR spectroscopy (n=30)

PCA: principal component analysis19

Page 21: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

• Detection and quantification of Sudan I in paprika

powder (Hu and Lu, 2016, Nature npj Science of Food, submitted)

paprika

powder

Sudan I

solution liquid extraction

centrifugation

rotor

evaporation

re-dissolve

Liquid-state

NMR tubesolid & liquid

mixture

HR MAS

solid-state

NMR rotor

supernatant

collection

HR MAS: high resolution magic angle spinning

Figure 10. Schematic illustration of experimental design

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Page 22: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

y = 19122x + 28542R² = 0.9968

0.0E+00

2.0E+06

4.0E+06

6.0E+06

8.0E+06

1.0E+07

1.2E+07

0 200 400 600

Sp

ectr

a in

ten

sity a

t 8

.57

pp

m (

AU

)

Sudan I concentration in paprika powder (mg/kg)

Figure 11. Left, representative liquid-state 1H NMR spectra of Sudan I in paprika powder at

different concentrations (bottom to top: 20, 50, 100, 250 and 500 mg/kg); right, linear

regression of Sudan I concentration and NMR spectra intensity at 8.57 ppm (n=3)

Liquid-state 1H NMR

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Page 23: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

y = 268.73x - 13248R² = 0.9885

0.0E+00

1.0E+05

2.0E+05

3.0E+05

4.0E+05

5.0E+05

6.0E+05

7.0E+05

0 500 1000 1500 2000 2500

HR MAS solid-state 1H NMR

Spectr

a inte

nsity a

t 7.8

9 p

pm

(A

U)

Sudan I concentration in paprika powder (mg/kg)

Figure 12. Left, representative HR MAS solid-state 1H NMR spectra of Sudan I in paprika

powder at different concentrations (bottom to top: 225, 675, 1350, 1800 and 2250 mg/kg);

left, linear regression of Sudan I concentration and NMR spectra intensity at 7.89 ppm (n=3)

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Page 24: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Next step…

Comparison and integration of

chemical library (UBC) &

molecular library (Guelph)

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Page 25: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

BOLD Systems

Web-Accessible Data and

DNA Barcodes

Specimen Collection Data

Tissue Sample Photograph

PCR Amplify SequenceExtract DNA

The DNA Barcoding Workflow – Library Building

Courtesy by Bob Hanner (University of Guelph) 24

Page 26: Detection of food fraud and adulteration using novel … Food... · Detection of food fraud and adulteration using novel spectroscopic techniques Xiaonan Lu Assistant Professor Food

Acknowledgement• Lu Food Safety Engineering Lab

• Yaxi Hu

• Prof. Eunice Li-Chan

• Dean Rickey Yada

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