DE202023000435U1 - Fiber optic arrangement for detecting and determining the extent of freezer burn on frozen meat with a color sensor - Google Patents

Abstract

Fiber optic arrangement for detecting and determining the extent of freezer burn on deep-frozen meat with a color sensor (2) consisting of a white light source, fiber optic transmission lines (3), a fiber optic measuring probe (7) with a measuring head (1) and the devices for emitting and receiving light and a color sensor (2) for light detection and a computer (4) for evaluating the measurement data and determining the color data of the meat sample (6), characterized in that the measuring head (1) has at least one lighting fiber (3.1.1) for illuminating the deep-frozen meat sample (6) and contains at least one detection fiber (3.2.1) for detecting the sample remission, the light entry and light exit surfaces of the illumination and detection fibers facing the sample surface being arranged at a distance from one another in the end surface (1.2) of the measuring head (1) in such a way that at a defined measuring distance (1.1) between measuring head (1) and sample (6), which depends on the aperture angle of the illumination and detection fibers and on the distance between the light entry and light exit surfaces of the illumination and detection fibers in the end face (1.2) of the measuring head , no light reflected diffusely or directed from the sample surface but only light (5) scattered several times in the sample volume is conducted through the detection fibers to the color sensor (2), with the defined measuring distance (1.1) being fixed by a mechanical spacer (1.3) or by a device is checked for distance measurement and a measurement of the light remitted by the sample is only triggered if the defined measurement distance is maintained.

Description

technical field

The invention is in the field of optical measurement technology and relates to an arrangement consisting of a fiber-optic measuring probe and a color sensor for detecting and determining the extent of freezer burn on deep-frozen meat using visible white light, with the light scattered back from the sample being analyzed using the color sensor and the fiber optic probe guides both the illuminating light and the light scattered back from the sample. The invention is to be used in particular by processors of deep-frozen meat (catering, butcher shops) but also by suppliers, transport service providers and food retailers.

Background of the Invention

The per capita consumption of frozen food among German consumers in 2021 was 46.1 kilograms [Statista GmbH, https://de.statista.com /statista/statistics/studie/37571/umfrage/per-kopf-verbrauch -from-frozen food]. All frozen products offered to the consumer have a temperature history corresponding to the frozen chain it has passed through. The relevant legislation prescribes various measures to maintain the product quality of frozen products. To prove compliance with the cold chain, food companies are subject to various verification and documentation requirements. Nevertheless, the problem of so-called freezer burn often occurs, especially with meat. This is a denaturation of muscle cells or proteins resulting from irreversible dehydration of the tissue. The process occurs on frozen products where the water present in the tissue sublimes due to short-term increases in temperature and defective packaging that is not airtight. This triggers a cold drying process. Surface layers of tissue close to the edge are particularly frequently affected, as they take on a hard, dry structure and show color changes when thawed. The typical meat flavor is also lost. Such changes cannot be reversed and migrate several millimeters in depth as the damage progresses.

In general, fresh, deep-frozen meat tends to have a rich red-pink colour. The more the meat is affected by freezer burn, the more extensive and grayer its discoloration becomes. Kaess & Weidemann showed through histological investigations that in meat damaged by freezer burn cavities had formed as a result of sublimation of ice crystals [G. Kaess, F.J. Weidemann, Freezer Burn of Animal Tissue. 7. Temperature Influence on Development of Freezer Burn in Liver and Muscle Tissue. J Food Science (1969), 34 , 394-397]. This is of interest for optical freezer burn detection, since the cavities diffusely scatter incident light and make the meat appear lighter than intact, undamaged meat. However, not every color change is synonymous with the presence of freezer burn, because other effects, such as meat aging or fat deposits, can also cause color changes.

Freezer burn is one of the most common defects seen in frozen poultry and is considered a potential food safety hazard. Atmospheric oxygen and the brief thawing effect can cause germs in the meat to multiply exponentially. For processors of frozen meat, but also for suppliers, transport service providers and food retailers, it is of great importance to ensure the prescribed product quality and for warranty and liability reasons that the deep-frozen goods delivered are in perfect condition, i.e. free of freezer burn. In practice, quality assurance is currently carried out almost exclusively by imprecise, random visual inspections. Due to the increasing economic importance of quality and food safety, there is a need for an objective, safe and fast detection method for freezer burn on deep-frozen meat in butcher shops, food retailers, transport service providers and in the catering trade.

State of the art

At present, freezer burn can only be detected with the required level of certainty when it has been thawed. The meat quality in the deep-frozen state cannot be assessed with sufficient accuracy. So far, no measuring techniques or other arrangements are known that detect freezer burn on frozen meat. Detection methods for determining the freshness of meat are known from the prior art, but these relate exclusively to the thawed state. The freshness and quality of slaughtered meat is determined by a large number of parameters. Not only the origin and living condition of the animals play a role, but also the heterogeneity of the muscle fiber structure (transverse and longitudinal striations) and the proximity of muscle meat to cartilage and bone. The postmortem autolytic and proteolytic processes are directly related to the storage conditions. Furthermore, microbiological degradation processes can be a determination the time of slaughter and thus the freshness more difficult. The complex structure of muscle tissue requires a good knowledge of the anatomy in order to be able to carry out a correct sample evaluation. A search for methods, some of which have been established for decades, reveals a broad basis of basic veterinary medical and food hygiene test methods for assessing the quality of slaughtered meat and meat products. The quality check initially concerns subjective parameters such as tenderness, juiciness, aroma and taste. Those skilled in the art refer to these as sensory parameters. The implementation requires a corresponding long-term training. Alternatively, attempts have long been made to objectify sensory quality testing with the help of physical, chemical and microbiological parameters.

The physico-chemical parameters include the electrical conductivity, the dielectric impedance and the pH value. Devices have been developed for individual parameters that are particularly suitable for local puncture measurements in pieces of meat. So describes DE 3814634A1 a device for measuring the pH value in meat and DE 3925331A1 a conductivity probe for quality testing. However, these methods cannot be used for deep-frozen meat (frozen meat). In addition, the parameters mentioned can only depict excerpts of the complex spoilage process. The correlation between the subjectively assessed quality and the various biochemical-physical parameters is moderate.

For more than ten years, attempts have been made to miniaturize optical spectroscopic methods (especially Raman, UV-VIS, IR and fluorescence spectroscopy) and to use them for quality control of meat [J.-L. Damez, S. Clerjon, Meat quality assessment using biophysical methods related to meat structure. Meat Science (2008), 80(1), 132-149]. The results are promising, but no corresponding system has been able to establish itself on the market to date.

It is also known that color has long been used as a criterion in assessing the quality of non-frozen meat [J. C. Wagner, Measurement of the color as a quality parameter in beef with regard to the determination of reference values in the general administrative regulation for food hygiene, dissertation for obtaining a doctorate in veterinary medicine from the veterinary faculty of the Ludwig-Maximilians-University in Munich, 2006]. The meat color is essentially determined by the concentration and condition of the myoglobin in the muscles. In addition, the structure of the muscle surface plays an important role in the remission of light and thus in color development. Defects in meat maturation that lead to off-colors are, for example, PSE characteristics (pale, soft, exudative), which are expressed in the extremely light and pale color of the muscles and occur primarily in pigs, and DFD characteristics (dry, firm, dark ), which lead to a very dark color of the muscles and often occur in cattle.

Colors can be expressed in numerical values and described objectively with color values for hue and lightness. The L*a*b* color space is now the global standard for color measurement. The L*a*b* model, also known as the CIE Lab model, describes all perceivable colors using a three-dimensional color space in which the lightness value L* is perpendicular to the color plane (a*, b*). The color axis a* (red-green axis) is divided into a green (-a*) and a red (+a*) area. The b* color axis (blue-yellow axis) is divided accordingly into a blue (-b*) and a yellow (+b*) area. By specifying a value triple (L*, a*, b*), it is possible to describe a color exactly.

Technically, there are two different methods for color measurement: tristimulus and spectral methods. In the three-area method, the color values are determined by placing color filters (red, green, blue) in front of radiation receivers (e.g. photodiodes), through which their spectral sensitivity is adapted to a standardized observer. With the spectral method, the color values are determined from the spectral remission, which is determined with a spectrometer in the entire visible spectral range.

The results of the color measurement depend on the measurement geometry. Measurement geometry is the angle at which a sample is illuminated and observed. In the field of color measurement of non-transparent foods such as meat, three measurement geometries standardized according to DIN 5033 are common. With the 45°/0° geometry, the sample is illuminated at an angle of 45° and the observation angle is 0°, ie the measurement is perpendicular to the sample. d/8° or d/0° designates arrangements in which the illumination takes place diffusely via an integrating sphere and the light reflected from the sample is detected at 8° or under 0°. In order to eliminate specular reflections from the sample surface, instruments with a d/8° geometry usually have a specular trap built into the integrating sphere. When the gloss trap is open and positioned at -8° to the measurement aperture, the directed reflected light is eliminated. In practice, the direction of illumination and the direction of observation can be interchanged without this has an influence on the measurement result. Thus d/8° and 8°/d or 45°/0° and 0°/45° geometries are equivalent.

Lighting also has an important influence on meat color. In order for color measurements to be comparable and repeatable, the color measurement must be carried out with a clearly defined type of light. Light types with a defined spectral distribution, so-called standard light types, have been standardized by the CIE. Today, the use of standard illuminant D65 is recommended for most color measurements. A type of light corresponding to average natural daylight with a color temperature of approx. 6500 K is defined as standard light type D65 (daylight).

In recent scientific publications where meat color is important, the Minolta chroma meter, type CR-100 to CR-400, is used very often [B. Hulsegge, B. Engel, W. Buist, GM Merkus, RE Klont, Instrumental color classification of veal carcasses. Meat Science (2002), 57(2), 191-195]. The Minolta Chroma-Meter is a three-range measuring device with a d/0° measuring geometry and a xenon flash lamp to generate the light type D65.

Another way to measure color objectively is to use a camera connected to a computer. The camera takes a picture of the sample and the computer calculates the color values. Here, a larger area can be recorded and inhomogeneities can be recognized better compared to the Minolta chroma meter.

However, the measuring devices and measuring geometries described according to the prior art are unsuitable for detecting freezer burn on deep-frozen meat using a color measurement and for assessing its extent. On the one hand, this is due to the fact that there are often individual ice crystals, a layer of ice, transparent packaging film and possibly a thin layer of water on the surface of the deep-frozen meat samples. The surface of meat damaged by freezer burn can also be atypically lightened or discolored as a result of contact with ambient air and the resulting oxidation reactions. This considerably complicates and falsifies the measurement of freezer burn damage using color measuring devices according to the prior art, since the diffuse and directed reflections reflected directly from the surface can be much more powerful than the remission from deeper tissue layers that is actually of interest. On the other hand, freezer burn damage to meat goes up to several millimeters below the surface, especially as the damage progresses, i.e. the dehydration. So freezer burn is not just a superficial effect. State-of-the-art color measuring devices for food, however, always detect diffuse reflections from the surface with or without specular inclusions. Although the remissions from deeper tissue layers, which characterize the freezer burn and its extent, are also measured, they are covered by the stronger directional and diffuse reflections from the surface and can no longer be separated from them.

Description of the invention

The object of the invention is therefore to provide an arrangement that suppresses both the diffuse and the directed reflections (gloss) of the surface when measuring the color of deep-frozen meat, so that only the remissions from deeper layers of the sample are measured.

A fiber-optic measuring probe with a special arrangement of illumination and detection fibers in the measuring head of the probe is used to solve this task. The light entry and exit surfaces of the illumination and detection fibers are in the end surface of the measuring head of the measuring probe. A white light source (e.g. halogen lamp, flash lamp or LED) is used to illuminate the sample. The illumination fibers of the fiber optic measuring probe are connected to the white light source, which can also be integrated in the color sensor. The detection fibers of the measuring probe are connected to a commercially available color sensor via an interface, which outputs L*a*b* color values to a computer.

During a measurement, the end face of the measuring head of the fiber optic measuring probe faces the sample surface so that the illuminating fibers illuminate the sample. The distance between the light entry and light exit surfaces of the illumination and detection fibers in the end face of the measuring head is selected in such a way that below a defined maximum distance MA between the measuring head and the meat sample, diffuse and directional reflections from the surface of the sample are no longer within the aperture angle of the detection fibers and so that they can no longer get into the detection fibers. In this way, only light that penetrates the sample and is scattered multiple times in its volume is detected. The detected light follows a curved path in the sample due to multiple scattering.

MA

Maximalabstand zwischen Probe und Messkopf

a

Abstand zwischen Lichtein- und Lichtaustrittsflächen der Beleuchtungs- und Detektionsfasen in der Endfläche des Messkopfes (Rand zu Rand)

α

Voller Aperturwinkel der Beleuchtungs- und Detektionsfasen

The maximum distance between the sample and the measuring head can be determined from the aperture angle of the illumination and detection fibers and the distance between the light entry and light exit surfaces of the Illumination and detection phases in the end face of the measuring head can be calculated according to the following equation: $$\text{MA}=\text{a}/(2*(\text{tan}\left(\mathrm{a}/2\right))$$

MA

Maximum distance between sample and measuring head

a

Distance between the light entry and light exit surfaces of the illumination and detection fibers in the end face of the measuring head (edge to edge)

a

Full aperture angle of the illumination and detection phases

With measurement distances between the sample and the measuring head that are smaller than MA, the cones formed by the aperture angles of the illumination and detection fibers no longer overlap on the surface of the meat sample.

To ensure a correct measuring distance between measuring head and sample, a mechanical spacer is used or the distance is controlled by other methods such as a distance measurement. The measuring distance is preferably set in such a way that unevenness in the sample is also tolerated.

With the arrangement according to the invention of fiber-optic measuring probe, color sensor and evaluation computer, color values can be measured which are suitable for recognizing damage from freezer burn and for assessing its extent. Dehydration of the meat in near-surface layers is characteristic of freezer burn. Water has an absolute absorption minimum in the blue wavelength range. In the red, however, its absorption is up to two orders of magnitude higher than in the blue. This means that water practically does not absorb blue light at all, but remits it very well. Red light, on the other hand, is well absorbed by water and is hardly remitted. Meat samples with freezer burn therefore show higher values of the color values a* and b* when measured with the arrangement according to the invention compared to intact samples without damage. This means that the reflected light contains more red and less blue components due to the lack of water. As the damage increases, the color measured with the arrangement according to the invention shifts more and more in the +a* and +b* direction.

In addition, in the case of freezer burn damage, the brightness L* measured with the arrangement according to the invention increases in comparison to an undamaged sample, since the sublimation of ice crystals has created cavities which diffusely backscatter more light.

In order to achieve reproducible measurement results in color measurement and to be able to ensure good comparability from measurement system to measurement system, the color measurement device including the fiber optic measurement probe must be calibrated before the measurements or the existing calibration must be checked. For this purpose, reference color charts with known color values are measured. A difference between target and actual values leads to correction terms that are taken into account in the data evaluation.

Before meat samples can be examined for freezer burn, a representative quantity of deep-frozen reference samples with and without freezer burn must first be measured using the arrangement according to the invention. After the measurement, the reference samples are to be thawed and checked for freezer burn, because up to now it has only been possible to reliably detect freezer burn when they have been thawed. The measured color reference values are then divided into groups such as e.g. B. "freezer burn, severe", "freezer burn, mild" and "okay". This can be done with a graphical evaluation or with computer-aided methods such as cluster analysis. The recorded color reference values of different types of meat form a color data library.

The procedure for examining meat samples for freezer burn using the invention is as follows: At least three measurement points are selected on each sample and measured at points using the arrangement according to the invention. Measurement points close to the edge, which are particularly frequently affected by drying out due to freeze burn, and points which show a color deviation from the rest of the sample that is visible to the eye, are preferably selected. After the end user has measured a sample to be assessed for freezer burn, the frozen goods are automatically classified with the aid of a PC, based on the determined color values and the color reference values from the color data library. By comparing the measured color values with those of the color data library, it is possible to reliably differentiate between samples with freeze burn and samples that are in perfect condition, and the degree of damage can be evaluated.

The arrangement according to the invention for detecting freezer burn on deep-frozen meat is characterized by the advantages mentioned below.

The invention makes it possible for the first time to examine deep-frozen meat objectively for freezer burn without thawing it. This is particularly advantageous since an inspection after thawing is larger delivery batches take a long time, the thawing process complicates the question of legal liability in the case of limited product quality (supplier or customer) and the goods are often to be sold on frozen, so that an additional thawing process would reduce the meat quality. The sensor system according to the invention works non-destructively, ie the sample is not changed by the measurement. In addition, it makes it possible to detect freezer burn down to a depth of a few mm below the surface and to provide information about the degree of freezer burn damage (“strong”, “weak”, no damage, okay”). Another advantage of the invention is that it is easy and safe to use, so that it can be used immediately without extensive training or expert knowledge, without endangering the operator or other people. Furthermore, the sensor system according to the invention is so reliable that at least 90% of the samples affected by freezer burn are correctly identified as such. Finally, the invention works quickly, requiring less than a minute of time per sample.

embodiment of the invention

• 1 Faseroptische Anordnung zur Detektion und Bestimmung des Ausmaßes von Gefrierbrand an tiefgefrorenem Fleisch mit einem Farbsensor
• 2 Faseroptische Messsonde der Anordnung zur Detektion und Bestimmung des Ausmaßes von Gefrierbrand an tiefgefrorenem Fleisch
• 3 Abstandshalter der faseroptischen Messsonde

The invention is explained in more detail as an exemplary embodiment using the following schematic figures:

• 1 Fiber optic arrangement for detecting and determining the extent of freezer burn on frozen meat with a color sensor
• 2 Fiber optic measuring probe arrangement for detecting and determining the extent of freezer burn on deep-frozen meat
• 3 Fiber optic probe spacer

1 shows a schematic diagram of the fiber optic arrangement for detecting and determining the extent of freezer burn on deep-frozen meat with a color sensor. The arrangement is formed from the color sensor 2, the fiber-optic measuring probe 7 connected to it with a fiber bundle 3 and the measuring head 1 and a computer 4 for determining and evaluating the color values. The fiber bundle 3 contains detection and illumination fiber bundles 3.1, 3.2 consisting of illumination and detection fibers 3.1.1, 3.2.1 made of quartz glass. The color sensor contains an LED white light source, which is connected to the lighting fiber bundle 3.1 via the interface 2.1. The detection fiber bundle 3.2 is connected to the detection unit of the color sensor. In the end surface 1.2 of the measuring head 1, the light exit surfaces of the illumination fibers 3.1.1 are arranged in a ring in this exemplary embodiment. The light entry surfaces of several detection fibers 3.2.1 are located in the center of the ring with a diameter of four millimeters. The distance 3.4 between the light entry and light exit surfaces of the illumination and detection fibers 3.1.1, 3.2.1 in the end surface 1.2 of the measuring head 1 is 1.5 mm in this exemplary embodiment. With a fixed distance 1.1 of less than 3.4 mm between measuring head 1 and meat sample 6, the diffuse and directed reflections of the surface of the sample are no longer within the aperture angle of the detection fibers 3.2.1 and can therefore no longer be forwarded in the detection fibers. In this way, only light 5 that has been scattered multiple times in sample 6 is detected. A mechanical spacer 1.3 is used to ensure a correct measuring distance 1.1. The measurement distance is fixed in such a way that unevenness in the sample 6 is also tolerated. In this exemplary embodiment, a measuring distance 1.1 of 1 mm is used. In order to block out any ambient light that may interfere with the measurement, the spacer 1.3 can be designed in such a way that it shields the end surface 1.2 of the measuring head 1 from the ambient light. The color sensor 2 is connected to a computer 4 for evaluating the color measurement and for controlling the measurement process. The control software running on the computer 4 guides the user through the measurement process. First, the type of meat to be tested (eg chicken breast, beef steak) is queried. The user then selects the measuring points on the sample, places the measuring head 1 with the spacer 1.3 on the sample and starts the measurements. The computer 4 then compares the measured color values with the color values in a color data library, automatically classifies the frozen goods and displays the result.

Reference List

1

Measuring head of the fiber optic measuring probe

1.1

Distance between measuring head and sample

1.2

End face of the measuring head of the fiber optic probe

1.3

Spacer on the measuring head of the fiber optic measuring probe

2

color sensor

2.1

Interface to the white light source of the color sensor (fiber connection for lighting)

2.2

Interface to the detection unit of the color sensor (fiber connection for detection)

2.3

Connection between color sensor and computer for evaluation

3

fiber bundles

3.1

lighting fiber bundle

3.1.1

Illumination fibers in the end face of the measuring head

3.1.2

Aperture angle of an illumination fiber

3.2

detection fiber bundle

3.2.1

Detection fibers in the end face of the measuring head

3.2.2

Aperture angle of a detection fiber

3.3

Fiber sleeve with fiber bundle branching

3.4

Distance between illumination and detection fibers

4

Computers (PCs, tablets, smartphones)

5

Multiple scattering of illuminating light in the sample

6

sample

7

Fiber optic probe

QUOTES INCLUDED IN DESCRIPTION

This list of documents cited by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent Literature Cited

• DE 3814634 A1 [0006]
• DE 3925331 A1 [0006]

Claims (4)

Fiber optic arrangement for detecting and determining the extent of freezer burn on deep-frozen meat with a color sensor (2) consisting of a white light source, fiber optic transmission lines (3), a fiber optic measuring probe (7) with a measuring head (1) and the devices for emitting and receiving light and a color sensor (2) for light detection and a computer (4) for evaluating the measurement data and determining the color data of the meat sample (6), characterized in that the measuring head (1) has at least one lighting fiber (3.1.1) for illuminating the deep-frozen meat sample (6) and contains at least one detection fiber (3.2.1) for detecting the sample remission, the light entry and light exit surfaces of the illumination and detection fibers facing the sample surface being arranged at a distance from one another in the end surface (1.2) of the measuring head (1) in such a way that at a defined measuring distance (1.1) between measuring head (1) and sample (6), which depends on the aperture angle of the illumination and detection fibers and on the distance between the light entry and light exit surfaces of the illumination and detection fibers in the end face (1.2) of the measuring head , no light reflected diffusely or directed from the sample surface but only light (5) scattered several times in the sample volume is conducted through the detection fibers to the color sensor (2), with the defined measuring distance (1.1) being fixed by a mechanical spacer (1.3) or by a device is checked for distance measurement and a measurement of the light remitted by the sample is only triggered if the defined measurement distance is maintained. Fiber optic arrangement for detecting and determining the extent of freezer burn on frozen meat with a color sensor claim 1 , characterized in that the illumination fibers (3.1.1) of the illumination fiber bundle (3.1) are arranged in a ring in the end face (1.2) of the measuring head (1), with the detection fibers (3.1.2) of the detection fiber bundle (3.2) being located in the center of the ring . Fiber optic arrangement for detecting and determining the extent of freezer burn on frozen meat with a color sensor claim 2 , characterized in that the diameter of the ring formed by the illumination fibers (3.1.1) of the illumination fiber bundle (3.1) in the end face (1.2) of the measuring head (1) is in the range from 1 mm to 1 cm and is preferably 4 to 5 mm . Fibre-optical arrangement for detecting and determining the extent of freezer burn on deep-frozen meat with a color sensor according to one of the preceding claims, characterized in that the spacer (1.3) is opaque and shields the end surface (1.2) of the measuring head (1) from ambient light.

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