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Raman Spectroscopic Studies on Meat Quality

Raman Spectroscopic Studies on Meat Quality. Ph.D. Research Degree by Renwick Beattie Supervisors: 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, 06 th November, 2000.

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Raman Spectroscopic Studies on Meat Quality

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  1. Raman Spectroscopic Studies on Meat Quality Ph.D. Research Degree by Renwick Beattie Supervisors: 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.

  2. 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 systems • Meat lipids – adipose and intramuscular fat • Aspects of meat quality – cooking and ageing • Future plans • Potential for Raman • Introduction to resonance Raman spectroscopy

  3. hn hn hn hn’ hn’ hn hn Rayleigh Intensity 0 n-n’ Raman Spectroscopy • Irradiate sample with monochromatic radiation • Collect inelastically scattered light • Frequency difference gives vibrational spectrum

  4. Advantages Disadvantages • Minimal sample prep. • Very general • Rich in information • Aqueous samples • “Special” techniques • Weak effect • Expensive • Experimentally difficult • Fluorescence interferes

  5. 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.

  6. Diffraction Grating Lasers Ti-Saph Ar+ l=785nm C.C.D. Telescope Depolariser Spectrograph Sample Holographic Notch Filter Schematic layout diagram for the CCD system

  7. Comparison of NIR & Raman Spectroscopy:- principles of measurement Near Infrared Reflectance Raman Spectroscopy Non 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

  8. 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 under development 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

  9. Absorbance Raman Intensity Foodstuffs Raman NIR • Sample preparation frequently required • Sensitive to water • Main food groups all give spectra • No sample preparation • Insensitive to water • Main food groups all give detailed spectra Carbohydrate Protein Fat 1800 1400 1000 600 1100 1300 1500 1700 1900 2100 2300 2500 Wavenumber (cm-1) Wavelength (nm)

  10. NIR Spectra of Water

  11. Absorbance Raman Intensity Comparison of the effect of water on the spectra of sugars. NIR Raman Honey Granular Fructose 1800 1400 1000 600 1100 1300 1500 1700 1900 2100 2300 2500 Wavenumber (cm-1) Wavelength (nm)

  12. 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.

  13. O HO CH2 OH HO CH O O CH2 HO OH OH Triglycerides • Previous work suggests- • cis/trans isomer ratios • iodine values • but may be fluorescence problems with unpurified samples unless FT Raman is used

  14. Raman Spectrum of a Triglyceride H-C-H H-C-H C-C Scattering Intensity =C-H C=C C1-C2 C=O 800 1000 1200 1400 1600 Raman Shift/cm-1

  15. 5 4.5 4 3.5 CH2 3 2.5 C=O 2 1.5 1 0.5 0 0 5 10 15 20 EFFECT OF INCREASING CHAIN LENGTH Model Fats : FAMEs R2 = 0.991 C8 Relative Band Intensity C7 C6 C5 1400 1600 1000 1800 1200 Chain length Wavenumber (cm-1)

  16. 0.5 0.45 0.4 R2 = 0.982 0.35 Relative Peak Area 0.3 0.25 0.2 0.15 0.1 20 30 40 50 60 70 80 90 100 Iodine Value 800 1000 1200 1400 1600 1800 EFFECT OF INCREASING UNSATURATION Model Fats : FAMEs Commercial Fats and Oils n(C=C) d(=C-H) d(CH2) n(C=O) 18:4cis 18:2cis 18:1cis 18:0 Wavenumber (cm-1)

  17. Comparison of the Raman spectrum of butter fat in different physical states 80oC Raman Intensity 21oC -10oC -176oC 1200 1700 700 Raman Shift / cm-1

  18. Raman Intensity 800 1000 1200 1400 1600 Raman Shift/cm-1 Spectra of Various Animal Fats Chicken Pork Lamb Beef

  19. 0.14 0.13 0.12 Unsaturation Level 0.11 0.1 0.09 0 1000 2000 3000 4000 5000 6000 Depth Unsaturation Level vs. Depth through a cross section of lamb adipose tissue

  20. Raman spectra of intramuscular fat before and after cooking. Chicken raw Chicken 60 min Beef raw Beef 60 min Raman signal 700 900 1100 1300 1500 1700 Raman Shift / cm-1

  21. Fat Composition and Content Determination • Fat 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).

  22. Phenylalanine d(CH2) sc n(C-C):a-helix Tyrosine + Phenylalanine Tyrosine d(CH2) tw n(C-N) n(COO- ) Methionine Tryptophan Cysteine Amide I n(C-C,N) Amide III 600 800 1000 1200 1400 1600 Raman Shift cm-1 Peak Identity in Raman Spectrum of Meat

  23. Raman spectra of various types of meat Amide I Phenylalanine Amide III a-helix mode Chicken Raman Intensity Pork Beef 650 1000 1400 1750 Raman Shift / cm-1

  24. Difference spectra showing changes in protein secondary structure upon cooking of meat samples. (Sample after 60 minutes cooking - sample after10 minutes cooking time) a-helix b-sheet Pork Relative Intensity Beef 600 1000 1500 Raman Shift / cm-1

  25. Projected Residual Effect of Proteolysis on the Raman Spectrum of Meat 1 Day 14 Days Amide I a-helix b-sheet Cys Met Tyr Skeletal n(C-N) Amide III CH2sc Difference 600 800 1000 1200 1400 1600 Raman Shift cm-1

  26. Principal Component Analysis of the Raman spectra of Pork as it is aged Day 1 1 0 0 Day 4 49Bc 94Ac Day 7 8 0 Day 10 93Ac 6 0 47Ab 49Bb 47Ac 34Bc 49Ac 50Bc 34Ac 4 0 93Bc 94Ab 47Bc 50Ac 50Bb 94Bb 93Ab 34Bb 2 0 49Ab 94Bc 34Ab t[3] 50Ab 47Bb 0 93Bb 49Ba 34Aa 49Aa 93Ba 94Ba - 2 0 93Aa 50Ba 47Aa 47Ba 49Ad 94Bd 47Ad 50Aa 93Bd - 4 0 94Ad 49Bd 50Ad 93Ad - 6 0 47Bd 34Ad 34Bd - 8 0 50Bd - 1 0 0 - 1 0 0 0 1 0 0 t[2]

  27. Loadings for PCA analysis of Pork ageing Cys Met Tyr Peptide Bond bands 0.080 Skeletal Amide III Amide I 0.040 0.000 p[2] -0.040 2nd component: amide hydrolysis and residue effects -0.080 0.100 0.050 p[3] 0.000 -0.050 3rd component: secondary structure and residue shifts -0.100 0 100 200 300 400 500 600 700 800 Pixel Num

  28. Conclusions • 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.

  29. 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

  30. 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? 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.

  31. 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 Beattie Mr. Griff Kirkpatrick Mr. Colum Connelly

  32. hn hn’ hn lmax hn’ Chromophore Excitation hn hn hn’ Rayleigh Non-Resonance Raman Resonance Raman Intensity 0 n-n’ Resonance Raman Spectroscopy • Irradiate sample with monochromatic radiation corresponding to adsorption band in UV-Vis spectrum • 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. • Bands associated with this adsorption are enhanced by a factor of ~103 to 104 relative to the ground state Raman and Rayleigh.

  33. 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.

  34. 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.

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