The Queen’s University of Belfast

Supervisors:Dr SEJ Bell Dr BW Moss

Potential Applications of Raman Spectroscopy in Predicting Meat

Quality

René Beattie

Roskilde, August, 2001.

• Introduction to resonance Raman spectroscopy

• Introduction to Raman spectroscopy

• Comparison with NIR

• Previous work on Raman spectroscopy of meat

• Current research: Initial work on lipids – model systemsMeat lipids – adipose and intramuscular fatAspects of meat quality – cooking and ageing

• Future plans and potential for Raman

Raman Spectroscopy

• Irradiate sample with monochromatic radiation

hn

hn

hn

hn

hnhn’

hn’

• Collect inelastically scattered light

Rayleigh

Intensity

-n n’0

• Frequency difference gives vibrational spectrum

• Weak effect

Advantages

• Minimal sample prep.

Disadvantages

• Very general

• Rich in information

• Aqueous samples

• “Special” techniques

• Expensive

• Experimentally difficult

• Fluorescence interferes

• Diode lasers: Wide range of wavelengths and also tunable lasers to allow increased flexibility.

Low-Cost, Compact Raman Spectrometers

Enabling Technologies

• Notch filter:Eliminate the strong laser line, preventing detector saturation.

• CCDs (Charge Coupled Detectors):Ultra high quantum efficiency detectors for detection of very low levels of light.

>$100k

~$10k

$60k

Schematic layout diagram for the CCD system

HolographicNotch Filter

Sp

ectr

og

rap

hC

.C.D

.

Depolariser

Sample

DiffractionGrating

Telescope

Ar+ Ti-SaphLasers

l=785nm

Raman Techniques: Dispersive Raman Spectroscopy

In food analysis fluorescence and expense are the major problems. FT Raman spectroscopy overcomes fluorescence, but at an even higher cost.

Radiation on the boundary of visible and near-infrared radiation:

Most basic form of Raman spectroscopy:

UV/ Visible radiation – use conventional optics and detection equipment

Uses conventional visible optical equipment

Reduces fluorescence

Cheaper

Comparison of NIR & Raman Spectroscopy:- principles of measurement

Near Infrared Reflectance Raman Spectroscopy

Non Destructive Non Destructive

Spectroscopic Spectroscopic

Molecular Vibrations + Electronic Configuration

Molecular Vibrations

Difficult to assign peaks Assignable peaks

Particle size + Physical State Physical State

Large water effect Low water interference

Comparison of NIR & Raman Spectroscopy:- Practical Aspects

Near Infrared Reflectance Raman Spectroscopy

Large area of measurement Small area of measurement

Fibre optic system Fibre optic system

Compact systems

Compact systems

User friendly User friendly

Cost £30k upwards* Cost £30k upwards*

* This price is for a general purpose bench-top instrument, rather than smaller task orientated devices

Foodstuffs

• Sample preparation frequently required

• Main food groups all give spectra

Wavenumber (cm-1)

1800 1400 1000 6001100 1300 1500 1700 1900 2100 2300 2500

Wavelength (nm)

Carbohydrate

Protein

Fat

RamanNIR

• No sample preparation

• Main food groups all give detailed spectra

Ab

sorb

ance

Ram

an In

tens

ity

Wavenumber (cm-1)

1800 1400 1000 6001100 1300 1500 1700 1900 2100 2300 2500

Wavelength (nm)

Ab

sorb

ance

Ram

an In

tens

ity

Protein

Water

Comparison of NIR and Raman Spectra of Protein

Problems Encountered in Literature

Background:

Not part of the Raman Signal – generally should be removed

Signal Intensity:

Absolute intensity hard to control – need internal standard

Glass – not suitable for NIR excitation (>700nm)

Fluorescence, elastic light scattering, absorption and other photon emitting processes

Depends on exact focal position, laser power, notch tuning, sample absorption and system alignment.

Current Research

Model Lipids: Chain length

Unsaturation Level

cis/trans isomerisation

Physical State

Adipose Tissue: Speciation

Correlation with GC data

Composition variation within sample

Meat: Ageing

Cooking

Pressure Treatment

Intramuscular Fat

Sensory panels

Triglycerides

HO

HO

HO

CH2

CH2

CH

OH

O18:2t

OH

O16:1c

OH

O14:0

• Physical state

• Chain length

• Unsaturation Level / Iodine values

• Cis/trans isomer ratios

Ra

ma

n In

ten

sit

y/ a

rbit

ary

un

its

Raman Spectrum of a Triglyceride

C=O

C=C

H-C-H

=C-H

H-C-H

C-CC1-C2

+ CH3

800 1000 1200 1400 1600

Raman Shift/cm-1

EFFECT OF INCREASING CHAIN LENGTH

C5

C6

C7

C8

1200 1400 1600 18001000

Wavenumber (cm-1)

CH2

C=O

Chain length

Re

lati

ve

Ba

nd

In

ten

sit

y0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

R2 = 0.991

0 5 10 15 20

Model Fats : FAMEs

EFFECT OF INCREASING UNSATURATION

Wavenumber (cm-1)

1200 1400 1600 18001000800

18:4cis

18:2cis

18:1cis

18:0

n(C=C)

n(C=O)d(CH2)d(=C-H)

Model Fats : FAMEs

R2 = 0.982

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

20 30 40 50 60 70 80 90 100

Iodine Value

Rel

ativ

e P

eak

Are

a

Commercial Fats and Oils

700 1200 1700Raman Shift / cm-1

Ram

an I

nte

nsi

ty 80oC

21oC

-10oC

-176oC

Comparison of the Raman spectrum of butter fat in different physical states

Pork

Spectra of Various Animal Fats

800 1000 1200 1400 1600Raman Shift/cm-1

Ram

an I

nte

nsi

ty

Lamb

Beef

Chicken

-1 0 0 0 0

-5 0 0 0

0

5 0 0 0

1 0 0 0 0

-1 0 0 0 0 0 1 0 0 0 0

t[3

]

t[2]

ChickenLambBeefPork

PLS Discriminant Analysis of Adipose Data

0 . 0 0 0

0 . 0 4 0

0 . 0 8 0

0 . 1 2 0

0 . 1 6 0

w*c

[1]

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 6 0 0

- 0 . 1 0

0 . 0 0

0 . 1 0

0 . 2 0

w*c

[3]

NUM

- 0 . 1 0

0 . 0 0

0 . 1 0

w*c

[2]

PLSDA Weightings for Adipose Data

Component 1Average Spectrum

Component 2Unsaturation Level

Component 3Solid fat content

-8 0 0 0

-6 0 0 0

-4 0 0 0

-2 0 0 0

0

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

1 2 0 0 0

-1 0 0 0 0 -5 0 0 0 0 5 0 0 0 1 0 0 0 0

u[2

]

t[2]

PLS Analysis of Adipose Data

ChickenLambBeefPork

-8 0 0 0

-6 0 0 0

-4 0 0 0

-2 0 0 0

0

2 0 0 0

4 0 0 0

6 0 0 0

8 0 0 0

1 0 0 0 0

-8 0 0 0 -6 0 0 0 -4 0 0 0 -2 0 0 0 0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0

u[2

]

t[2]

PLS Analysis of Lamb Adipose Data

Unsaturation Profile of pork adipose tissue

0.29

0.3

0.31

0.32

0.33

0.34

0.35

0.36

0.37

0.38

0 2000 4000 6000 8000 10000 12000 14000

depth/ mm

Un

satu

rati

on

Lev

el /

Ram

an b

and

ratio

Previous Raman Work Whole Muscle: • Spectra dominated by myosin (main component).

• Water Content.

Intact single fibers:

• Again dominated by myosin.

• Contraction had little effect.

• Ions affected individual amino acids.

Isolated proteins:

• Effect of different conditions (pH, salts and

temperature) on protein structure.

• All major proteins in meat.

Aspects of Meat Quality

Meat Quality:

• Texture/ Tenderness

• Taste

• Appearance/ Colour

• Fat Content

Tenderness:

• Ageing/ proteolysis

• Protein composition

• Storage conditions

• Cooking/ processing conditions

Raman spectra of the main components of meat

Raman Shift / cm-1

Ra

ma

n In

ten

sit

y

600

Protein

1000 1400 1800

The fine structure of skeletal muscle and meat

Z Line

A Band I Band

M Line

MyosinActin

H Zone

600 140012001000800 1600Raman Shift cm-1

Effect of Ageing on the Raman Spectrum of Meat

1 Day

Projected Residual

11 Days

Difference

Tyr SkeletalMetCys CH2scAmide IIIn(C-N) Amide I-a helix b-sheet

-100

-80

-60

-40

-20

0

20

40

60

80

100

-100 0 100

t[3

]

t[2]

Day 1Day 4

Day 11Day 8

Principal Component Analysis of the Raman spectra of Pork as it is aged

-1 0 0

-5 0

0

5 0

1 0 0

-1 0 0 0 1 0 0

t[3]

t[2]

Day 1Day 4

Day 11Day 8

PLS Disriminant Analysis of the Raman spectra of Pork as it is aged

- 0 . 1 0

0 . 0 0

0 . 1 0

w*c

[2]

0 . 0 0 0

0 . 0 4 0

0 . 0 8 0

0 . 1 2 0

0 . 1 6 0

w*c

[1]

- 0 . 0 5 0

0 . 0 0 0

0 . 0 5 0

0 . 1 0 0

0 . 1 5 0

w*c

[3]

0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0NUM

Weightings for PLS Disriminant Analysis of the Raman spectra of Pork as it is aged

Component 1: Average(unscaled normalised data)

Component 2: amide hydrolysis and residue effects

Component 3: secondary structure and residue shifts

-1 0 0

-5 0

0

5 0

1 0 0

-1 0 0 -8 0 -6 0 -4 0 -2 0 0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 0 1 6 0

u[2

]

t[2]

Day 1Day 4

Day 11Day 8

PLS of the Raman spectra of Pork as it is aged – Component 2, proteolysis

Effect of Cooking on Components of BeefR

ela

tiv

e In

ten

sit

y

Raman Shift / cm-1650 900

Protein

175015001200

Possible Plans for Meat Research:

• Speciation of meat (by muscle and/or fat).

• Cold shortening – contraction of meat.

• Tenderness – state of contraction, hydrolysis of proteins etc.

• Taste – can Raman predict which pieces of meat taste good?

• Final internal temperature of cooked meats.

• Fatty Acid composition – incorporate work on lipids.

• Investigate applications for Resonance Raman

Raman spectra will be compared to standard tests and to taste tests

The future of Raman

Meat Quality Attributes Instrumental/Rapid Method

Appearance

Flavour

Texture

Reflectance

Electronic nose +Raman?

NIR? Raman?

Nutritional Quality

Proximate Analysis

Characterisation:-

Lipid

Protein/Amino Acids

Carbohydrates

NIR? Raman?

Raman

Raman?

Raman?

Conclusions

• Raman is a powerful probe of the structure of

the protein and fat within meat.

• Raman can be used to investigate the extent and

process of proteolysis.

• Analysis underway to correlate Raman data with :

o fat content

o time of cooking

o processing treatment.

o tenderness

My supervisors: Dr SEJ Bell and Dr BW Moss

Lab Mates: Clare, Antionette, Monica, Lyndsay, Kate, Roma, Colin, Steve, Andrew, Philip and Fiona.

Technical help: Alan, Colum, Griff and Ernie

? Institute?

Funding: DARD (NI)

Acknowledgements

Resonance Raman Spectroscopy

• Increases the probability of change in vibrational state

before energy is released.

hn

hn’

hn

hn’

hn’

hn

• Excite the particular bond involved in the adsorption to give

longer lived excited state.

Excitation

lmax

• Irradiate sample with

monochromatic radiation

corresponding to

adsorption band in UV-

Vis spectrum

hnChromophore

• Bands associated with

this adsorption are enhanced

by a factor of ~103 to 104

relative to the ground state

Raman and Rayleigh.

RayleighIn

ten

sity

-n n’0

Non-Resonance Raman

Resonance Raman

Applications of Resonance Raman Spectroscopy

Resonance Raman spectroscopy (RRS) probes particular bonds (chromophores) resulting in:

• Very precise information about specific bonds.

• Detection of very low concentrations of the chromophore (less than 10-6 M).

• Detection of very small changes in the chromophore.

This is useful for meat analysis because:

The amide bond of meat is a chromophore and has a well established relationship with the secondary and tertiary structure of the protein.

RRS can improve analysis of changes in amide bonding hence structure of the protein or level of proteolysis.