Raman Spectroscopic Studies on Meat Quality

Ph.D. Research Degree by Renwick BeattieSupervisors: Drs B. Moss and S. Bell

Faculty of Agriculture and Science,The Queen’s University of Belfast

Funded by: Department of Agriculture and Rural Development, N.I.

Monday, 06th November, 2000.

• Introduction to Raman spectroscopy• Comparison with NIR• Previous work on research area• Current results from research:

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

• Future plans• Potential for Raman• Introduction to resonance Raman spectroscopy

Raman Spectroscopy

• Irradiate sample with monochromatic radiation

• Collect inelastically scattered light

• Frequency difference gives vibrational spectrum

hn

hn

hn

hn

hnhn’

hn’

Rayleigh

Intensity

-n n’0

• Weak effect

• Expensive

• Experimentally difficult

• Fluorescence interferes

Advantages

• Minimal sample prep.

• Very general

• Rich in information

• Aqueous samples • “Special” techniques

Disadvantages

Low-Cost, Compact Raman Spectrometers

Enabling Technologies

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

• 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.

Schematic layout diagram for the CCD system

DiffractionGrating

HolographicNotch Filter

Sp

ectr

ogra

ph

C.C

.D.

Ar+ Ti-SaphLasers

Telescope

Sample

Depolariser

l=785nm

Comparison of NIR & Raman Spectroscopy:- principles of measurement

Near Infrared Reflectance Raman SpectroscopyNon Destructive Non Destructive

Spectroscopic Spectroscopic

Molecular Vibrations + Molecular Vibrations

Electronic Configuration

Difficult to assign peaks Assignable peaks

Particle size Physical State

Large water effect Low water interference

Near Infrared Reflectance Raman Spectroscopy

Large area of measurement Small area of measurement

Fibre optic system Fibre optic system

Compact systems Compact systems underdevelopment

Cost £30k upwards* Cost £30k upwards*

User friendly Considerable Training needed

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

Comparison of NIR & Raman Spectroscopy:- Practical Aspects

Foodstuffs• Sample preparation frequently required

• Sensitive to water

• 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

• Insensitive to water

• Main food groups all give detailed spectra

Ab

sorb

ance

Ram

an In

tens

ity

1

1.5

2

2.5

1100 1300 1500 1700 1900 2100 2300 2500

Wavelength

Ab

sorb

ance

water

NIR Spectra of Water

Wavenumber (cm-1)

1800 1400 1000 6001100 1300 1500 1700 1900 2100 2300 2500

Wavelength (nm)

Honey

Granular Fructose

Ab

sorb

ance

Ram

an In

tens

ity

RamanNIR

Comparison of the effect of water on the spectra of sugars.

Previous Work Whole Muscle:

• Observed spectra very similar to myosin spectrum (~50% of the total muscle protein).

• Intact Muscle contains ~20% bound water, remaining supercooled at –10 0C.

Intact single fibers:

• 70% a-helical structure (78% for myosin).

• Contraction did not significantly change the secondary structure of the fiber.

• Amino acid residue peaks changed upon interaction with Ca2+ and ATP (which affect the effective charge density of the fiber).

Isolated proteins:

Myosin, Actin, Acto-myosin, Tropomyosin, Troponin and sub-fragments.

Effect of different conditions (pH, salts and temperature) on protein secondary structure.

Previous work suggests-

• cis/trans isomer ratios

• iodine values

but may be fluorescence problems with unpurified samples unless FT Raman is used

Triglycerides

OH

OOH

O

OH

O

HO

HO

HO

CH2

CH2

CH

Sc

atte

rin

g In

ten

sit

yRaman Spectrum of a Triglyceride

C=O

C=C

H-C-H

=C-H

H-C-H

C-C

C1-C2

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

nten

sity

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

nten

sity

Lamb

Beef

Chicken

Unsaturation Level vs. Depth through a cross section of lamb adipose tissue

0.09

0.1

0.11

0.12

0.13

0.14

0 1000 2000 3000 4000 5000 6000

Depth

Un

sat

ura

tio

n L

ev

el

Raman spectra of intramuscular fat before and after cooking. R

aman

sig

nal

Chickenraw

Chicken 60 min

Beefraw

Beef60 min

700 900 1100 1300 1500 1700

Raman Shift / cm-1

Fat Composition and Content DeterminationFat Composition:

• Similar to determination for free fat except:-

Problems:

• Fat peaks mixed in with protein peaks

• Carbonyl stretch, the usual internal standard, is unsuitable as the protein matrix shifts the peak below the amide I band.

Solutions:

• Isolate Fat peaks by taking baseline at set points each side of each peak.

• Use the C1-C2 stretching mode as an internal standard.

Fat Content:

• Ratio the C1-C2 stretch or the C-C stretch at 1060 cm-1 to the phenylalanine peak (internal standard for meat protein).

Peak Identity in Raman Spectrum of Meat

600 140012001000800 1600Raman Shift cm-1

Ph

enyl

alan

ine

Tyr

osin

e

Cys

tein

e

Met

hio

nin

e

n(C-C,N) Amide III Amide I

n(C

-C):a

-hel

ix

n(C

-N)

d(C

H2)

sc

d(C

H2)

tw

n(C

OO

- )

Try

pto

ph

an

Tyr

osin

e +

Ph

enyl

alan

ine

Chicken

Pork

Beef

Raman Shift / cm-1

Ram

an I

nte

nsi

ty

650 1000 1400

Raman spectra of various types of meat

1750

Amide Ia-helix mode Phenylalanine Amide III

Difference spectra showing changes in protein secondary structure upon cooking of meat samples.

(Sample after 60 minutes cooking - sample after10 minutes cooking time)

Rel

ativ

e In

ten

sity

Raman Shift / cm-1

Pork

Beef

a-helix

b-sheet

600 15001000

600 140012001000800 1600Raman Shift cm-1

1 Day

Effect of Proteolysis on the Raman Spectrum of Meat

Projected Residual

14 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]

34Aa

34Ab

34Ac

34Ad

34Bb

34Bc

34Bd

47Aa

47Ab 47Ac

47Ad47Ba

47Bb

47Bc

47Bd

49Aa

49Ab

49Ac

49Ad

49Ba

49Bb

49Bc

49Bd

50Aa

50Ab

50Ac

50Ad

50Ba

50Bb

50Bc

50Bd

93Aa

93Ab

93Ac

93Ad

93Ba

93Bb

93Bc

93Bd

94Ab

94Ac

94Ad

94Ba

94Bb94Bc

94Bd

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

t[2]

Day 1Day 4

Day 10Day 7

0.100

0

p[3

]

Pixel Num

0.050

-0.100

0.000

-0.050

100 400300200 700600500 800

p[2

]

0.080

-0.080

-0.040

0.000

0.040

Loadings for PCA analysis of Pork ageing

Peptide Bond bands

2nd component: amide hydrolysis and residue effects

3rd component: secondary structure and residue shifts

Tyr

Skeletal

MetCys

Amide III Amide I

The results so far have indicated dispersive Raman Spectroscopy can be applied to:-

• Quantitative analysis of Fatty acid parameters: chain length, unsaturation level, solid fat.

• Understanding some of the mechanisms of biochemical change in proteins during cooking and formation of meat.

Correlations currently under investigation include:-

• Quantitative analysis of fat composition in butters, adipose tissue and meat.

• Quantitation of total fat content in meat.

• Speciation using fat and/or meat.

• Level of proteolysis in muscle/meat.

Conclusions

Plans for 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.

• Leanness/ Total fat content.

• Fatty Acid composition – incorporate work on lipids.

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

The future of RamanMeat Quality Attributes

AppearanceFlavourTexture

Nutritional Quality

Proximate AnalysisCharacterisation:-LipidProtein/Amino AcidsCarbohydrates

Instrumental/Rapid Method

ReflectanceElectronic nose +Raman?NIR? Raman?

NIR? Raman?

RamanRaman?Raman?

Dispersive Raman spectroscopy has long been neglected for food analysis, largely due to the problem of fluorescence and expense. However, our research has shown that by using a laser on the boundary of visible and near-infrared radiation, one can easily determine many nutritional and qualitative parameters using the cheaper dispersive Raman instruments rather than expensive FT-NIR Raman instruments.

Acknowledgements

DARD – for the award of a postgraduate studentship, enabling me to carry out this research.

Drs Bruce Moss and Steven Bell, for their supervision and help

Dr Ann Fearon Mr. Alan BeattieMr. Griff Kirkpatrick Mr. Colum Connelly

Resonance Raman Spectroscopy

• Excite the particular bond involved in the adsorption to give longer lived excited state.

• Increases the probability of change in vibrational state before energy is released.

• Irradiate sample with monochromatic radiation corresponding to adsorption band in UV-Vis spectrum

• Bands associated with this adsorption are enhanced by a factor of ~103 to 104 relative to the ground state Raman and Rayleigh.

hn

hn’

hn

hn’

hn’

hn

Excitation

lmax

hnChromophore

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 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.

Resonance Raman Spectroscopy of Proteins.

The amide bonds of proteins has a strong adsorption band in the UV and 204 nm lasers can be used to provide RR spectra with the bands due to the amide bonds enhanced.

RRS has recently been used to probe the dynamic changes involved in protein folding and unfolding.

The peptide (penta-alanine) was probed with a 1.9 mm laser to give a 3 ns temperature jump (~60 0C). The peptide was then probed with the 204 nm laser at a pulse rate of 3 ns to follow peptide folding from a few ns up to a few ms.

Initial increase due to temperature is observed before actual unfolding begins at around 50 ns. After 95 ns the peptide is ~30% unfolded.

Kinetic calculations from the results indicate it is not a simple transition between two states, but involves intermediate conformations.