MEAT QUALITY SENSORS

Must be

Most feasible To assess To predict STRATEGY

[1] Innovative research on biophysical basis of meat quality
[2] Make apparatus portable or remote for abattoir use
[3] Correlate data to expert opinion or sensory panel responses
 

SUCCESS IS

FAILURE IS

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SLIDE 1.  FAT is very important in the meat industry because it determines yield.  It is difficult to know how much muscle there is in a carcass, so we assume bone is constant.  Then we estimate fat from subcutaneous fat depth.  Then we predict how much of the carcass weight is muscle.  Hence, our technology for fat depth detection is well developed.  But, for  quality, there is a lot more to measure than just fat depth.



SLIDE 2. This shows a brief history of how technology for fat depth measurement evolved.
  1. The depth of fat used to be measured by cutting through the fat with a scalpel.
  2. Then a light pipe was used so that the operator could see the muscle:fat boundary without slashing through the carcass.
  3. The light pipe and human eye were replaced by a diode detector for the muscle :fat boundary.  An important feature was that the depth of the boundary was found from a depth detector relative to a plate that remained on the meat surface.
  4. Optical fibers were then introduced which enabled us to see inside the carcass.
  5. Broad-band monochromatic measurements were replaced by a diode-array spectrograph which allowed spectrophotometry and multiple regression.
  6. Perhaps the future will allow us to measure both wavelength and angle of measurement through the tissue on one array?

 

SLIDE 3.  Remember the importance of measuring depth in the meat in slide 2? Well, a classic fat-depth probe, such as those developed in Denmark, provides a superior launch-platform for any type of measurement to be made. On the x-axis is depth in the meat. On the y-axis is whatever is being measured at the tip of the probe. THIS ADDS A STEREOLOGICAL  DIMENSION TO THE MEASUREMENT.


SLIDE 4. This is an example of what we might do with a hand-held probe. Red light from a laser has been used to illuminate the meat, then a small-window measurement of reflectance has been used to separate fat from muscle. FAT DEPTH is the high plateau from 0 to 4 mm depth.  There are two measurements:   WAY-IN and WAY-OUT.  There is an offset between way-in and way-out because of tissue deformation (which can be used to gather interesting data on the softness of the tissue - provided temperature is known, because tissues get harder with refrigeration and surface drying). Software has to be quite clever to spot the muscle:fat boundary because, as we will see later, sometimes the muscle can be very pale. Within the muscle can be seen MARBLING (INTRAMUSCULAR) FAT.



SLIDE 5. A LOT OF THINGS AFFECT THE QUALITY OF MEAT.  Some of them originate on the farm while others, especially pH, are determined by transport of animals, method of slaughter, and rate of refrigeration.  As well as causing protein denaturation and major differences in light scattering, pH affects the negative electrostatic repulsion between MYOFILAMENTS. If filaments come close together, the native water between them moves out of the filament lattice, and ultimately ends up as a massive  fluid loss (drip and evaporation) from the meat, as well as causing obvious problems in meat packaging. In the laboratory, we follow the fluid movements by low-angle x-ray diffraction, transmission electron microscopy and interference microscopy.  The challenge is to make comparable measurements with simple sensors!

 
 

SLIDE 6.  Remembering our goal of understanding what we are measuring, here is a way to investigate the effect of pH on the light scattering that occurs within pork.  Light scattering is a very strong effect.  High scattering causes a short light path with little selective absorbance by chromophores so the meat appears pale.  Low scattering allows a long light path, strong absorbance by chromophores, so the meat appears dark. The disk of pork (shown in red) is flushed with buffer (shown in yellow) and measured using the optical fibre.
 

 


SLIDE 7.  The pH of the 0.2 M phosphate buffer is controlled by computer using acid, base and dump valves.  Some flushing was required to remove sarcoplasmic proteins. In retrospect, the ionic concentration was a little too high, causing some solution of myofibrillar proteins.  Despite this, pH effects were reversible and predicable from what we know of the effect of pH on the negative electrostatic repulsion of thick and thin myofilaments in their lattice.
 

SLIDE 8. This shows the components connected to the fibre-optic light guide in the experiment to study the effect of pH on the reflectance of the disk of pork. A solenoid-shutter is required in the illumination pathway to find the dark-field current of the photomultiplier.  Programmable stray-light filters are required after the grating monochromator to remove high-order harmonics. Everything is driven from an IEEE488 bus.


 


SLIDE 9.  This shows a dynamic test of reflectance (primarily scattering) change with pH. The key point to note is that reflectance INCREASES as pH DECREASES.  A second point to note is that in this sample of NORMAL pork, changing the pH (by an amount similar to that occurring as a result of a normal amount of post-mortem glycolysis), caused a change in reflectance of about 0.02 (relative to magnesium oxide = 1).


SLIDE 10.  Now we repeat the experiment with PSE  (PALE, SOFTE, EXUDATIVE)  PORK. The reversible change in pH is about the same order of magnitude as found with normal pork, but the relatively small change is superimposed on a very high level of reflectance which originates, now almost certainly as proposed by Bendall, from precipitated or denatured sarcoplasmic proteins (not washed out because they are deposited around the myofibrils).


 

SLIDE 11.  Spectrophotometry through optical fibres is relatively simple, but colorimetry is  more complex. The main point is that colorimeters have air spaces  (from illuminator to sample, and from sample to spectrophotometer).  But when we insert optical fibres directly into soft tissue there is direct contact between fibre cores and tissue fluids. Internal reflectance spectra collected by fibre-optics tend to be related to reflectance spectra by a third power of wavelength. After this transformation, the weighted ordinate method may be used to calculate chromaticity coordinates for colorimetry with reasonable success. Line 1 is the internal spectrum, line 2 is the measured  surface reflectance spectrum, and line 3 is the transformation of the internal spectrum to predict the surface spectrum.

 


SLIDE 12.  The shape of spectra collected by fibre-optics from meat are very useful for steering a robotic probe. Although a robotic probe can navigate relative to the skeleton (using an ultrasonic image of the skeleton produced by transducers surfing on a water jet), it is difficult to know when the optical window of a probe is within a muscle.  Clearly, if the measurement is made from fat between muscles, then the spectrum will be misleading.

Each measurement in a spectrum is compared to every other measurement, to produce a probability  matrix (Pmat)  filled with -1 or +1.  Zero is rare if the full result of A:D conversion is used. Several matrices for classic examples of fat or muscle are averaged to make a cumulative probability matrix (Cpmat) with a range from -1 to +1. The Cpmat for fat is subtracted from the Cpmat for muscle to give a difference in cumulative probability matrix for muscle (Dcpmat-m) with a range from -2 to +2. Similarities are canceled. Differences are enhanced. The mirror image Dcpmat  for fat (Dcpmaf-f) is created by subtracting the Cpmat for muscle from the Cpmat for fat. Thus, the probability of an unknown Pmat originating from muscle is

   SUM (Pmat x  Dcpmat-m) / ( SUM (Pmat x Dcpmat-m) + SUM (Mat x Dcpmat-f))

Unfortunately, the photocopier reduced 10 shades of grey-map dithering to black and white in the matrices plotted for this slide! Here the example was for the robot to separate connective tissue (CT, including fat) from very pale muscle (PSE, pale, soft, exudative pork).  The advantage of this method is speed, since the matrix summation can be done rapidly while the robot is moving,  thus allowing the window to be halted within a known type of tissue with a known probability of success.


SLIDE 13.  Another important point to remember is that, because meat has strong scattering, the penetration of light at different wavelengths varies considerably.

 


SLIDE 14. This gets us to stage 6 in slide 2 - the future.  Measuring at different  wavelengths and at different directions through the sample makes it possible to look at a correlation matrix to search out the most useful features for prediction. Although  true goniospectrophotometry is possible through meat with optical fibres (angle changes - but path length is constant, as used for slide 13), it is much easier to move the optical fibre under a sample and measure light transmitted through the sample at different angles and different path lengths. This method was first  developed for laser scattering in meat by Birth and Davies in the US 20 years ago in 1978 - now we can add wavelength to angle.  A convenient way to look at the matrix is to use the coefficient of correlation as altitude and plot a surface contour map. A key point to note is that the sign of the correlation may be reversed from low (400 nm) to high (600 nm) wavelengths. This is very important for anyone planning an inexpensive broad-band measurement out in the field. If the band includes plus and minus correlations, then the device will fail!



SLIDE 15.  Let us move on to another important attribute of meat quality - the toughness of cooked meat.



SLIDE 16.  By a fortunate coincidence, COLLAGEN and ELASTIN,  the two dominant protein fibres that cause connective tissue toughness in meat are both fluorescent, emitting blue-white light when excited with UV. Not only this, but peak excitation is at 370 nm, which can be approximated by the very strong 365 nm emission peak of a mercury source.  Furthermore, because fluorescence quenching (fading) proceeds from the outside to the inside of a connective tissue fibre, the RATE OF FADING GIVES FIBRE DIAMETER,  and fibre diameter is correlated with tensile strong. Finally, with luck holding out to an amazing extent, PYRIDINOLINE, one of the dominant cross-links at the molecular level (it can make even a small-diameter fibre heat resistant and strong)  IS STRONGLY FLUORESCENT!



SLIDE 17.  A probe plus depth detector (as in slide 3) can be fitted with a single optical fibre for fluorometry, by splitting excitation and emission pathways using a dichroic mirror (enhanced by appropriate low-pass and high-pass filters). Not only is the use of a single optical fibre a simple method, it is the best method.  Thus near-field effects at the distal window of the fibre dominate the signal.


 

SLIDE 18.  As the single-fibre optical window passes through the tissue it generates a signal revealing the microstructure and strength of the connective tissue within the meat.

 

 SLIDE 19.  To achieve my goal of understanding what  I am measuring in simple, scientific terms, a simple signal processing algorithm is preferable, although doubtless a lot could be achieved with neural networks and fractal dimensions, but then I would not be able to understand  exactly what I  am measuring. Fortunately, it may be shown that the peaks tend to be symmetrical, and this then allows peak height and half peak-width to be found with a few simple flags. Roughly speaking, width can give thickness, and height can give fluorescence intensity, but the stereology is complex because the probe does not pass through all tissue sheets perpendicularly. Thus, some fluorescent structures are seen tangentially.  And it is usually found that direction of measurement through the meat (which is has a strongly anisotropic structure at all levels) is critical for both repeatability and success of prediction.


SLIDE 20.  Electromechanical probes for detecting meat toughness have a bad reputation.  Many designs of penetrometer and torque deformation needles have been investigated and have produced poor predictions of meat toughness.  However, this is possibly because the depth of penetration has been too shallow, and the logic has been to seek a peak measurement to characterize the system.  Peak measurements are risky because they may include a transient spike from an extraneous source not related to the overall tensile strength of the meat. As a probe is being pushed through meat, useful electromechanical data may be collected simply by looking at the depth vector. Commercial probes may trigger the A:D from the shaft-encoder reading depth, which is very economical and ideal for a hard-wired circuit with a fixed register size for data.  But, if a more flexible system is used, with data collection at a fixed rate and a buffer to catch the data, disorders can be detected in the depth vector. Thus, when the probe slows, stops, or even recoils (when the tip hits tough tissue), the event can be quantified and compared with the incoming signal from the primary sensory.  In the example shown, the fluorescence signal peaks when the probe decelerates, thus indicating the cause of the deceleration to be connective tissue.  This provides useful ancillary information, especially when we remember that connective tissue is only one cause of  meat toughness.


SLIDE 21.  The stereology provides a fascinating view of how BEEF ANIMALS GROW their intramuscular connective tissues.



SLIDE 22.  In a large experiment with good  standardisation of  transport, slaughter, refrigeration and aging, the difference between tough and tender meat is very obvious.

 


SLIDE 23.  It is important to remember, however, that connective tissue is ONLY ONE SOURCE of meat toughness.  Thus, correlations of  connective tissue fluorometry with taste panel responses are moderate but not very strong. Other factors than connective tissue are involved!
 

SLIDE 24. Strong connective tissue is not always a problem as it is in beef toughness.  In turkeys, the opposite condition may occur at heavy body weights: the connective tissue may not be strong enough to hold bundles of muscle fibres together when cooked turkey roles are sliced thinly for the delicatessen counter.  A  miniature version of the CT-probe for beef may be used on turkey breast muscles.



SLIDE 25.  After fluorometry, turkey breast muscles were tested rheologically to see how strong they were. A non-destructive test was used (no point in crushing the samples!), which explains the notch at P1 to V in the hysteresis area of the stress-strain relationship where the mechanical force release mechanism was activated.

 


SLIDE 26.  Spectrofluorometry also may be used to assess collagen content.  For example, chicken skin is nice to eat and highly nutritious, but becomes a problem when the level is too high in a processed chicken meat product. Here we see the emission spectra of chicken meat pastes or slurry with various collagen levels.

 


SLIDE 27. And here is the t-statistic for fluorescence versus cooking loss.  Thus, high collagen content caused high cooking loss, and the best wavelength for the sensor was around 480 nm. The match between slides 26 and 27 is fairly obvious in this case, but it is not always like this.  Sometimes the best predictions originate from the edge of the spectrum.  It all depends where the desired information content is strongest relative to spurious information, error and noise.



SLIDE 28.  Let's leave fluorometry, although we have hardly touched some of  its possibilities, and move on to birefringence. Meat is made of muscle fibres (giant, multinucleated cells) which contain contractile organelles - MYOFIBRILS. Myofibrils are important because they confer on meat many of its pleasant textural properties (without which, we might as well eat texturised vegetable protein instead). Myofibrils are transversely striated by A (ANISOTROPIC) and I (ISOTROPIC) bands.  This optical anisotropy originates from the precise longitudinal arrangement of protein filaments within the myofibrils.  Thus, myofibrils are birefringent, with two speeds of light, one along and one across the myofibrils.  When the myofibrils contract, A band length is constant, and I band length decreases.  Thus, overall birefringence tends to increase as sarcomeres get shorter.  To cut a long story short, the key point is that SHORT SARCOMERES CAUSE MEAT TOUGHNESS (because there is more overlapping of thick and thin filaments which, when locked in rigor mortis, produce a dense mat of protein for us to chew through). In slide 28, we are scanning down the length of  a myofibril with a polarised light microscope, showing how we hope to measure sarcomere length from birefringence.


 


SLIDE 29. In the real world, however, we cannot isolate individual cells and organelles very easily, so the challenge is to get the method working on bulk tissue.  Step one was to work with a 1-mm slice of tissue, as shown here.

 

 SLIDE 30.  Here we are testing the relationship between the transmittance of polarised  NIR light and SARCOMERE LENGTH using samples of cold-shortened pork versus restrained pork (unable to shorten as a consequence of  too rapid refrigeration).  As the analyser is rotated (degrees on x-axis) the correlation changes.  If the effect had nothing to do with polarisation, it would not change.  But it only changes with angle for restrained samples, not cold-shortened samples with very short sarcomeres.  NIR is used to reduce scattering (which is inversely proportional to a power of wavelength).
 

SLIDE 31.  Why doesn't the method work with very short sarcomeres? The answer is that birefringence is a measure of ultrastructural neatness.  When filaments are neatly lined up, there are two refractive indices as the electric vector of light interacts with charged groups of amino acids on the neatly aligned filaments.  Unfortunately, thick filaments are 2.5 micrometres long, and thin filaments are 1 micrometer in length. Thus, as the sarcomere contracts from stretched length (say 3.5) down to less than 2.5 micrometres, then the filaments overlap and bend as the thin filaments jam into the Z-line.  Thus, birefringence is reduced below 2.5 micrometres, as we see here.

 

 SLIDE 32.  Now the sensor is getting complex! It is detecting sarcomere length, provided that we do not have any severe cold shortening, but it is also detecting  other things with NIR that may or may not be independent of the plane of polarisation. First we will see what NIR transmittance per se is doing, then we will come back to the problem using polarised light for bulk tissues. Here we see that the transmittance of polarised NIR can predict the water-holding capacity of the sample (in this case, a paste of turkey meat being used in food processing).

 

 SLIDE 33. NIR reflectance and now transmittance are popular methods with much to be said about them.   To cut a long story short, it is the fat content of the sample that is also being detected by NIR.  Fat also has a major effect on meat quality and processing properties. Let us return to the more innovative aspects of how to develop a probe for bulk tissue.  Cutting slices of tissue is no good - we must be able to push the probe into an intact system, as we see here.  The polarisers are mounted on the end of a bifurcated light guide, the illuminating polar being perpendicular to the receiving polar.  There is no way to rotate the receiving polar so it is not an analyser.  A depolariser is need for the mirror which is used to set 100% reflectance.
 
 SLIDE  34.  The bulk-state sensor still works (fortunately!).  Here we see it separating between rest-length and stretched pork.  On the y-axis is the back-scatter of  NIR: in other words, NIR that was rotated or depolarised to get back through the receiving polar.  We are cheating a bit here, however, because we are looking at pre-rigor pork.  In other words, scattering is at a minimum (because the pH has not yet dropped  from anaerobic glycolysis). Scattering is the big problem - when it is high, the back-scatter is telling us about pH as well as sarcomere length. Unfortunately, we are not trying to measure pH, and we must be careful to examine the causality of correlations (the method might appear to work in predicting meat quality, but it may be detecting the effect of pH on meat quality rather than the effect of  sarcomere length on meat quality).  Remember our goal of understanding what we are doing, rather than exploiting blind correlations?

 

 SLIDE 35.  This brings us right up to date with a bulk probe which IS capable of rotating its analyser.  Although polarisation preserving fibres certainly are available, they are very difficult to use for bulk tissues -  the fibres are too small, and the throughput of light is severely limited. Thus, the problem is how to locate the rotary analyser near the bulk tissue, before the optical fibres connected to the photometer.  One answer, as shown here, is to use a graded index lens between the tissue and the analyser, so that the analyser can be rotated within the housing of a hand-held probe under computer control. It is capable of  quantifying the amount of Fresnel reflectance from mirror-like structures within the tissue - such as membranes and refractive index boundaries.  Thus, it has enabled us to measure the contribution of these factors to overall meat paleness.
 
 SLIDE 36.  Using an extinction coefficient  (k) to quantify the proportion of reflected light maintaining its original plane of polarisation (that is, Fresnel reflectance from reflective structures), the probe can predict the processing properties of a saline chicken meat paste.
 

 

 SLIDE 37.  Despite this progress in technology transfer from innovative research to practical application,  many powerful methods remain trapped in the laboratory, such as the de Senarmont method for ellipsometry which is exquisitely sensitive to the state of the muscle fibres in meat and could have tremendous application in industry.  The difficulty is light scattering!

 

 SLIDE 38.  Thus, path difference provides a neat explanation for dark cutting in beef.  At a high pH, birefringence is low, thus suggesting refractive scattering is low.  Thus, light incident on the meat is transmitted deep into its interior and the product looks very dark.

 

 SLIDE 39.  Coming full circle back to the importance of innovative research, sensors can be particularly useful when incorporated into classical experimental apparatus, such as the rigorometer developed in 1939 for the study of post-mortem metabolism in muscle. Here the scientific question is why are 45 minute post-mortem measurements an unreliable guide to the ultimate quality of the meat?  Apart from the obvious point that post-mortem metabolism has only just started at this convenient time for industrial measurements (when carcasses move from the kill-floor to the meat cooler), the problem may originate from transient osmotic uptake of intercellular fluid because of  glycogenolysis (big molecules splitting into lots of smaller ones). Impedance measurements are particularly useful because capacitance is strongly correlated with ATP level.  This is exploited in many of the commercially available meters for testing meat quality - but they do not work very well at 45 minutes!
 


 
SLIDE 40.  Here is the result of an experiment.  The strip of pre-rigor pork was periodically loaded. At it developed rigor mortis (caused by lack of ATP and measured by NMR), the stress-strain hysteresis area and amount of elongation decreased. These classic  changes were highly predictable from the fibre-optic sensor.


SLIDE 41.   Electrical capacitance of cell membranes is a good measure of ATP availability (ion pumps in cell membrane are open without energy from ATP, thus providing a shunt between electrolytes on each side).  In the laboratory, the method can validated by NMR . Impedance measurements are relatively simple in theory, but the main problem we have in the meat industry is the high static charge on many hanging carcasses.  This is surprising, since the abattoir air is very humid, the carcasses are wet, and the overhead rail may be grounded. Battery-operated apparatus is the simplest solution.

 


SLIDE 42. Hybrids between dynamic rheology and optoelectric sensors can be made portable and moved out into the real world. Optical fibres are mounted in hypodermic needles, thus allowing spectrophotometry of what ever is between the tips of the touching needles.  Similarly, the metal of the needle provides two electrodes for impedance measurements.  Moving one needle away from the other  allows us to test the rheology of the sample, while the amount and rate of entry of tissue fluid into the space can be followed optically - before a final scan for spectrophotometry and impedance at different frequencies. There are no results yet, this one is still a prototype being programmed!

 


SLIDE 43.  The prime mover need not be electromechanical.  Vacuum has some advantages for  deforming soft tissue like meat, as we see in this vacuum-applied fibre-optic probe for measuring softness. Pale pork has a high reflectance, which can be detected statically.  But, if  the pork is soft as well as pale, then the meat bulges upwards into the vacuum giving a steep SLOPE in the vacuum:reflectance relationship.


SLIDE 44. Finally, it is important to remember that SLAUGHTERING is one of the main operations in the meat industry. Many parameters can be monitored indirectly using load cells and electrical transformers - including the completeness of exsanguination (bleeding), the voltages and amperages of stunning currents (monitored to ensure that stunning is effective and humane), and reflex activity.  REFLEX ACTIVITY is particularly important because it accelerates glycolysis, enhancing the pH-decline rates which earlier we saw had a profound effect on meat quality.


SLIDE 45. The patterns of reflex activity detected by a load cell as the carcass bounces may be used diagnostically, sometimes enabling the source of activity to be tracked to a particular part of the carcass.  Different types of reflex activity are useful in checking whether stunning has been done humanely.



SLIDE 46. EMG can take us down to the cellular level in understanding which muscle fibres are contracting, where we can relate to ACTION POTENTIALS AND MOTOR UNITS.  Thus, from a relatively simple device such as a load cell, it is possible to gain an amazing amount of information. Perhaps, eventually, we may have sensors throughout the meat industry enabling true quality management to improving average meat quality. In doing so, we also have the opportunity to enhance our scientific understanding of meat quality.


WANT MORE INFORMATION ?
 

[1] MEAT PRODUCTION
H.J. Swatland (1994) Structure and Development of Meat Animals. Technomic Publishing, Basel ISBN 1-56676-120-4

[2] MEAT SENSORS
H.J. Swatland (1995) On-line Evaluation of Meat. Technomic Publishing, Basel ISBN 1-56676-3339

[3] SOFTWARE
H.J. Swatland (1998) Computer Operation for Microscope Photometry. CRC Press, Boca Raton, Florida ISBN 0-8493-1697-9