WO2003034059A1

WO2003034059A1 - Apparatus and process for analyzing cuts of meat

Info

Publication number: WO2003034059A1
Application number: PCT/NZ2002/000221
Authority: WO
Inventors: Anthony Mate Matos
Original assignee: Machinery Developments Limited
Priority date: 2001-10-18
Filing date: 2002-10-18
Publication date: 2003-04-24

Abstract

A method of analyzing cuts of meat is provided. The method includes storinginformation defining a plurality of possible product classes as predetermined values of a set of attributes and detecting attributes of a cut of meat to be analyzed, the detected attributes corresponding to attributes in said set of attributes. For each said possible product class each detected attribute is compared with its corresponding attribute in said set of attributes and dependent on the comparison a total score is computed indicating the likelihood of the cut of meat being a member of that possible product class. The product class of the cut of meat is identified as the possible product class having the total score indicating the most likelihood of the cut of meat being a member of that possible product class. A packaging apparatus and process is also described and claimed.

Description

APPARATUS AND PROCESS FORANALYZING CUTS OFMEAT

Field of the Invention. The present invention relates to an apparatus and process for analyzing cuts of meat.

Background of the Invention.

Devices and processes for acquiring the physical attributes of a cut of meat are known in the art. One such device and process is disclosed in International Patent Publication No. WO 01/88930 and is incorporated herein by reference in its entirety. Another such device and process is disclosed in published New Zealand Patent application No. 335,578 and is incorporated herein by reference in its entirety. These devices and processes can be used in meat packaging operations to provide size information to a bag making device that is used to produce a bag for packaging the cut of meat. Examples of such bag making devices are disclosed in published New Zealand Patent Application No. 263,260 and published New Zealand Patent Application No. 239,153, which are also incorporated herein by reference in their entirety.

These devices and processes are commonly used in meat packaging operations where various classes of meat cuts are packaged at a bagging workstation. A conveyor is generally used to transfer each ofthe various classes of meat cuts to the bagging workstation. It is desirable to package each ofthe cuts of meat in bags having proper characteristics for packaging the cut of meat. For example, it may be desirable to package a cut of meat in a bag having information regarding the cut of meat printed on the bag. Additionally, it may be desirable to package a cut of meat in a bag having physical characteristics such as barrier, non-barrier, or bone guard qualities. In the past, there has not been an apparatus or process for identifying the product class of each ofthe cuts of meat and transmitting the product class information to the bag making device for producing a bag having the proper characteristics for packaging the cut of meat. Any discussion of the prior art throughout the specification should in no way be considered as an admission that such prior art is widely known or forms part of common general knowledge in the field.

Object of the Invention

It is an object ofthe present invention to provide an apparatus and process for identifying cuts of meat by product class.

It is another object ofthe present invention to provide an apparatus having a three dimensional imaging assembly for acquiring and transmitting the physical attributes of each ofthe cuts of meat to a processor to determine the product class of each ofthe cuts of meat. It is a further object of the present invention to provide a process for analyzing the physical attributes of each ofthe cuts of meat to identify each ofthe cuts of meat by product class.

It is still another object ofthe present invention to provide an apparatus and process for transferring the product class information of each ofthe cuts of meat to a bag making device for producing a bag to package each of the cuts of meat.

It is yet another object ofthe present invention to provide an apparatus and process for transferring the product class information of each ofthe cuts of meat to a bag making device for producing a bag to package each ofthe cuts of meat with product information printed on the bag. The above objects are to be read disjunctively with the object to at least provide the public with a useful alternative.

Further objects ofthe present invention may become apparent from the following description.

Definitions

Cut of meat means a portion of an animal carcass that has been separated from the animal carcass.

Product class means a particular type of cut of meat. Examples include, without limitation sirloin, tenderloin, brisket and other cuts as will be appreciated by those skilled in the relevant arts, including any customized cuts that may be made not conforming to a standard cut. Summary of the Invention

According to one aspect ofthe present invention, there is provided a method of analyzing cuts of meat, the method including: storing information defining a plurality of possible product classes as predetermined values of a set of attributes; detecting attributes of a cut of meat to be analyzed, the detected attributes corresponding to attributes in said set of attributes; for each said possible product class comparing each detected attribute with its corresponding attribute in said set of attributes and dependent on the comparison computing a total score indicating the likelihood ofthe cut of meat being a member of that possible product class; identifying the product class ofthe cut of meat as the possible product class having the total score indicating the most likelihood ofthe cut of meat being a member of that possible product class.

Preferably, said set of attributes includes values for cut weight and specific cut dimensions.

Preferably, said set of attributes includes values for at least one of cut volume and cut cross-section.

Preferably, said set of attributes includes values for the symmetry ofthe cut of meat over at least one of a longitudinal and lateral axis.

Preferably, said set of attributes includes values for at least one ofthe cut height variation and cut area variation.

Preferably, said total score is computed as a weighted sum ofthe result for each attribute ofthe step of comparing each detected attribute with its corresponding attribute in said set of attributes, wherein a weighting for each said result is specific for each product class and is predetermined based on the extent that that the particular attribute distinguishes that product class from others of said possible product classes.

According to another aspect ofthe present invention, there is provided a method of packaging cuts of meat in a processing line including a supply of cuts of meat of different classes, the method including receiving cuts of meat from said supply, analyzing each cut of meat in accordance with the method of any one ofthe preceding claims to determine the product class ofthe cut of meat under analysis and varying a packaging process for the cut of meat dependent on the determined product class.

Preferably, the the step of varying a packaging process for the cut of meat dependent on the determined product class includes selecting a type of packaging for the cut of meat dependent on the determined product class.

Preferably, the method includes printing indicia onto packaging for a cut of meat or onto a label for said packaging, wherein the step of varying a packaging process for said cut of meat dependent on the determined product class includes printing different indicia on the packaging dependent on the determined product class.

Preferably, the method further includes printing with said indicia further indicia that specifies particular quality or grade characteristics ofthe cut of meat.

According to another aspect ofthe present invention, there is provided apparatus for analyzing cuts of meat, the apparatus including: detector means for detecting one or more product attributes of a cut of meat; machine readable information storage means containing information defining a plurality of possible product classes as predetermined values of a set of attributes; and a processor in communication with said detector means and said storage means, the processor operable to: for each possible product class retrieve from said storage means the value of each attribute in said set of attributes and compare it with the value of a corresponding attribute detected by said detector means and compute a total score indicating the likelihood ofthe cut of meat belongs to that possible product class dependent on the comparison; and provide an output indicating the possible product class that has the most likelihood that the cut of meat belongs to it.

According to a further aspect ofthe present invention, there is provided a packaging line for cuts of meat from a supply of variable cut classes, the packaging line including apparatus for analyzing cuts of meat in accordance with claim 11, a packaging workstation the operation of which is at least partially controlled by a controller, and transport means for transporting cuts of meat from said supply to said packaging workstation via said apparatus for analyzing cuts of meat, wherein said controller is operable to receive an output from said apparatus for analyzing cuts of meat identifying the product class for a cut of meat and automatically update the operation of said packaging workstation for said cut of meat in response to a change in said output between cuts of meat.

Preferably, the controller updates the operation ofthe packaging workstation by changing the type of packaging supplied for said cut of meat.

Preferably, the packaging workstation further includes a printer for printing indicia onto packaging for said cut of meat or onto a label for said packaging, wherein the controller updates the operation ofthe packaging workstation by causing the workstation to print different indicia on the packaging or label.

Preferably, said controller further controls the printer to print further indicia on said packaging or said label, the further indicia that specifying particular quality or grade characteristics ofthe cut of meat as determined by said processing means dependent on attributes detected by said detecting means.

Preferably, said controller is the same device as the processor of said apparatus for analyzing cuts of meat.

Further aspects of this invention, which should be considered in all its novel aspects will become apparent from the following description given by way of possible embodiments thereof and in which reference is made to the accompanying drawings.

Brief Description of the Drawings

FIG. 1 is a meat packaging system including an identification device ofthe present invention.

FIG. 2 is a flow chart ofthe product evaluation sequence for identifying the product class of each cut of meat.

FIG. 3 is an example of an array used as part of the product evaluation sequence ofthe present invention.

FIG. 4 is an example of indicia that may be printed onto packaging.

Detailed Description of the Drawings

The present invention relates to an apparatus and process for identifying the probable product class of cuts of meat by comparing measured properties of each ofthe cuts of meat to reference values for the properties of each ofthe product classes. The invention may provide improved distribution and handling ofthe cuts of meat after they have been packaged by the application of identifying indicia onto the packages for the meat.

Referring now to the drawings, FIG. 1 illustrates a meat packaging system 10 where cuts of meat are transferred along a conveyor 11, in this embodiment represented by a series of conveyors 12, through a cut-sizing device 14 to a bagging workstation 16. The bagging workstation 16 may include one or more bag making devices, in this embodiment four bag making devices 18a-18d such as the devices disclosed in either or both of published New Zealand Patent Applications 263,260 and 239,153, which are incorporated herein by reference in their entirety. The bagging workstation 16 may also include a loading apparatus 17 for assisting in the loading of cuts of meat into bags. The loading apparatus.17 may be the apparatus described in International Patent Publication No. WO 02/076832, which is hereby incorporated herein in its entirety. The bag making devices 18a-d may be controlled by a processor 15 as described in International Patent Publication No. WO 01/88930, which is also hereby incorporated herein by reference in its entirety. The bagging workstation 16 may alternatively include any other bag making device, or any number of bag making devices, apparent to one skilled in the art. An appropriate communication channel 19 is provided between the processor 15 and bag making devices 18a-d.

The processor 15 need not be a single device and may for example include multiple microprocessors or microcontrollers in communication with each other. The processor 15 includes an associated memory 21, which contains the instructions to control the operation of the processor 15 and information defining the product classes for comparison with the measurement data received from the cut-sizing device 14.

After the cuts of meat have been packaged in bags at the bagging workstation 16, they are conveyed away by a conveyor 23, typically for loading into cartons or location in a temporary cool store. Each bag making device 18a-d includes a printer 20 for applying indicia to the bags. The printers 20 may be controlled by the processor 15, either directly or through a local controller (not shown) for each bag making device 18a-d or group of bag making devices 18. The printers 20 may thermally print indicia onto plastic tubing used to make the bags. The cut-sizing device 14 may include a three dimensional (3D) imaging assembly

(not shown) to determine the 3D measurements ofthe cuts of meat. Specifically, the 3D imaging assembly determines the length ofthe cuts of meat as well as the height and width ofthe cuts of meat at various positions along the length ofthe cuts of meat. For example, the 3D imaging assembly may include a 670nm laser configured vertically and a sensor such as the sensor sold by Cam Sensor under the trademark CS3, mounted at 50 degrees to the horizontal to receive the reflected light. The 3D imaging assembly may also include photocells in a substantially horizontal plane and photocells in a substantially vertical plane. Alternatively, the 3D imaging assembly may include any 3D profiling devices apparent to one skilled in the art.

The cut-sizing device 14 communicates with the processor 15, which receives the measurements from the 3D imaging assembly through communication channel 17 and identifies the product class of each ofthe cuts of meat. The processor 15 then communicates the result of this identification process to the bagging devices 18a-d as described in more detail herein below. The processor 15 may be a programmable logic controller (PLC), a personal computer based controller (PC), a processor internal to the laser assembly or camera assembly, or any other processor apparent to one skilled in the art. The processor may be a processor for controlling the bagging workstation 16 as described above, or the processor may be coupled to the processor associated with the bagging workstation 16. The processor 15 may use triangulation to construct a 3D array of points to represent the dimensions of each ofthe cuts of meat or the processor 15 may determine the dimensions ofthe cuts of meat in any manner apparent to one skilled in the art. Accordingly, the cut-sizing device 14 may be the device disclosed in International Patent Publication No. WO 01/88930.

FIG. 2 illustrates an embodiment of a product evaluation sequence, generally referenced by arrow 20, that the processor 15 uses to identify the product class of each of the cuts of meat. As shown in FIG. 2, when a cut of meat passes through the cut-sizing device 14, the 3D imaging assembly analyses the cut of meat and transmits the cut of meat's attributes to the processor 15, see step 22. As part of step 22, the processor uses data acquired by the 3D imaging assembly to determine various attributes ofthe cut of meat, including cut length, cut width, and cut height. By determining the cut width and cut height measurements at fixed intervals along the length ofthe cut, the processor can determine additional cut attributes such as: cut volume, maximum cross sectional area, maximum cut height, average cut height, cut height variation, cut area variation, longitudinal symmetry, lateral symmetry, width/length ratio. Other attributes can be determined and used to classify the cuts as well. Cut height variation may be defined as the absolute difference between the height ofthe cut one-quarter ofthe length in from the front ofthe cut, and the height ofthe cut one-quarter ofthe length in from the back ofthe cut. Cut area variation may be defined as the absolute difference between the cross sectional area ofthe cut one-quarter ofthe length in from the front ofthe cut, and the cross sectional area ofthe cut one-quarter ofthe length in from the back ofthe cut. The longitudinal symmetry may be defined as the sum ofthe differences of height at various equi-distances away from the center ofthe cut measured in the longitudinal direction. The lateral symmetry may be defined as the sum ofthe differences of height at various equi-distances away from the center ofthe cut measured in the lateral direction. It is important to note that the measurements listed provide the same or similar results whether the cut of meat is loaded forward or backwards on the conveyor 12. Depending on the specific product attribute, the measured values may be averaged or otherwise evaluated to determine from multiple measurements a single value that can be used. For example, when determining the product width, a number of measurements at spaced intervals across the cut of meat may be taken, with the average, maximum or 75 percentile for example being used as a single measurement for the product width. The processor 15 is then loaded with the first reference statistical values associated with each ofthe possible product classes in step 24. The statistical values are stored in memory 21 and may include the average and standard deviation, the average and range, or any other relevant statistical information as would be apparent to one skilled in the art of each ofthe attributes ofthe cuts of meat for each ofthe possible product classes. The statistical values may be based on previous measurements of various cuts in each ofthe possible product classes by the cut-sizing device 14. Alternatively, the statistical values may be determined in any other manner apparent to one skilled in the art. Moreover, the statistical values may be loaded into the processor prior to the initiation ofthe product evaluation sequence 20. After the processor 15 has received the cut of meat's attributes via step 22 and received the statistical values of each ofthe possible product classes via step 24, the processor 15 compares the first attribute ofthe cut of meat to the statistical values for the first attribute ofthe first possible product class in step 26. The comparison between the first attribute ofthe cut of meat and the statistical values for the first attribute ofthe first possible product class is assigned a statistical score. The score is based on the likelihood ofthe cut of meat being a member ofthe first possible product class. For example, the comparison ofthe cut of meat's length with the statistical values for the length ofthe first possible product class may receive a score between zero and one hundred. A score of zero may indicate a very unlikely match and a score of one hundred may indicate a very likely match. The score may then be multiplied by a weighting factor to adjust for the significance ofthe cut of meat's length in determining the possible product class. The weighting factor may be different for the same attribute in different possible product classes depending on the extent to which the particular attribute differentiates the product class from the other possible product classes. For example, if cuts in one product class are known to be significantly longer than the cuts in most or all ofthe other product classes, then the length attribute may be more heavily weighted. Similarly, if cuts of one product class have a similar length to other cuts of product classes, then the length attribute will be lightly weighted, or even given a zero weighting. In the simplest of embodiments ofthe present invention, the set of product attributes used may include only one attribute, although using multiple attributes is anticipated to increase the accuracy of the system in most cases.

The processor 15 then determines a total theoretical score, or in other words the score that would result if the cut was a perfect match to the reference cut for the particular cut attribute in step 28. The score and theoretical score are then stored in an array 44 in the memory 21. An example of an embodiment ofthe array 44 is shown in FIG. 3. The embodiment shown in FIG. 3 is described in greater detail below.

Referring back to FIG. 2, the processor 15 may determine whether all ofthe attributes ofthe cut of meat have been compared to the statistical values for the attributes ofthe first possible product class and assigned a score in step 32. If all ofthe attributes ofthe cut of meat have been compared, the processor may continue on to step 34 as described below. However, if there are additional attributes ofthe first possible product class that have not been compared and assigned scores, the processor may return to step 26, loading the second product attribute as indicated by step 30, to compare the second attribute ofthe cut of meat to the statistical values for the second attribute ofthe first possible product class. The processor 15 may then compare the second attribute ofthe cut of meat to the statistical values for the second attribute ofthe first possible product class and assign a corresponding score and store the total theoretical store in steps 26 and 28 respectively. The processor again determines whether all ofthe attributes ofthe cut of meat have been compared to the attributes ofthe first possible product class and assigned a score in step 32. Accordingly, the remaining attributes ofthe cut of meat are compared to the remaining statistical values for the attributes ofthe first possible product class and assigned scores via step 26. This process continues until a score has been assigned for the comparison of each ofthe attributes ofthe cut of meat to each ofthe statistical values for the attributes ofthe first possible product class.

Once all ofthe attributes ofthe cut of meat have been compared to the corresponding statistical values ofthe first possible product class and assigned scores via step 26, the processor assigns a confidence score for the first possible product class via step 34. The confidence score may be calculated by dividing the sum ofthe scores for the comparison of each attribute ofthe cut of meat to each possible product class by the sum ofthe theoretical scores for the comparison of each cut of meat to each ofthe possible product classes. A higher confidence score may indicate a higher likelihood a cut of meat is ofthe possible product class for which the confidence score is assigned. Alternatively, the confidence score may be assigned in any manner apparent to one skilled in the art.

The processor 15 then determines whether all ofthe possible product classes have been assigned a confidence score via step 38. If every possible product class has been assigned a confidence score, the processor continues on to step 40 as described below. However, if the processor 15 determines there is a possible product class that has not been assigned a confidence score the processor returns to step 26 to compare the first attribute ofthe cut of meat to the statistical values for the first attribute ofthe possible product class that has not been assigned a confidence score via step 26. As described above, the processor then compares each ofthe attributes ofthe cut of meat to the statistical values for the attributes ofthe possible product class and assigns scores for each ofthe comparisons via step 26, and assigns a confidence score for the possible product class via step 34.

Once all ofthe possible product classes have been assigned a confidence score via step 34, the processor then determines the likely product class ofthe cut of meat via step 40. The likely product class ofthe cut of meat may be determined by selecting the possible product class with the highest confidence score.

After the likely product class has been determined for the cut of meat via step 40, the processor 15 may transmit the likely product class information as well as the information regarding the measured and calculated attributes ofthe cut of meat to the bag making device, printer, or other machine in the line having a controller. The bag making device 18 may then use the information transmitted by the processor 15 to: select an appropriate feed of tube stock to make a bag for packaging the cut of meat; print a label containing a product code, a description, or a logo on the bag for packaging the cut of meat; make an appropriately sized bag for packaging the cut of meat; or any other activity apparent to one skilled in the art. For example, selecting an appropriate feed of tube stock to make a bag for packaging the cut of meat may include selecting a feed of tube stock having appropriate barrier qualities, appropriate width, appropriate markings, or any other attribute apparent to one skilled in the art. The printers 20 may apply the selected information directly onto the tubing that forms the bags made by the bag making apparatus 18a-d.

In one embodiment, the information printed onto a bag or onto label may include a group code and one or more product codes. Referring to Figure A, a portion of a bag 41 a group code, for example Tl may indicate the class ofthe product, for example a tenderloin. The product codes, in the example in Figure 4 Wl and FI may indicate selected measured attributes or characteristics determined from measured attributes. Wl may indicate a weight range that the cut falls within, the weight measured by suitable scales 100 (see Figure 1). FI may be an indication ofthe cut quality, dependent on the particular shape ofthe cut. For example, if the reference possible product classes represent the ideal shape, FI may indicate a high quality cut having a confidence score in the range of 80 to 100%.

The printers 20 may alternatively be located downstream in the processing line of the packaging apparatus 18, in which case the processor 15 may include two parts, one concerned with control ofthe packaging apparatus 18 and another concerned with the control ofthe printers 20. In one embodiment, a measurement ofthe cut weight may be used in combination with the other product attributes measured by the cut-sizing device 14 to establish the product class, the weight measurement treated in the same way as the measurements of other attributes, being assigned a weighting factor to indicate it relative importance to the other attributes and incorporated into the confidence score.

Referring now to FIG. 3, the statistical data for each attribute, or property, is stored for each possible product class in a statistical data column 46. Additionally, the measurements ofthe cut of meat as determined by the cut-sizing device 14 are stored in a measurement column 48. The Z value is then calculated and stored in a Z value column 50. Z value is calculated using the following formula: Z = (measured value - average)/ standard deviation. The normalized value, the conversion ofthe Z value into a probability using the normal distribution, is stored in a normalized value column 52. The score is attained by multiplying the normalized value by 100 and is stored in a score column 54. The adjusted points are determined by multiplying the score and the weighting factor and are stored in a cut points column 56. In the embodiment illustrated in FIG. 3, the weighting factor is the value labeled points that is stored in the statistical data column 46. The total possible points for each property, or attribute, is stored in a total possible points column 58.

A totals section 60 includes the sum of all the values stored in the cut points column 56, the sum of all the values stored in the total possible points column 58, and the confidence score, or cut score. The confidence score, or cut score, is the sum ofthe values in the cut points column 56 divided by the sum ofthe values in the total possible points column 58, shown as a percentage. The confidence score for each possible product class is compared to other confidence scores for the remaining product classes to determine ofthe possible product classes, which is the most likely product class for each cut of meat. As discussed herein above, the possible product class with the highest confidence score may be selected as the product class and this information communicated to processor 15 so that an appropriate code may be printed onto the bag produced for the particular cut of meat by one ofthe printers 20.

Where in the foregoing description, reference has been made to specific components or integers ofthe invention having known equivalents, then such equivalents are herein incorporated as is individually set forth. Although this invention has been described by way of example and with reference to possible embodiments thereof, it is to be understood that modifications or improvements may be made thereto without departing from the scope ofthe invention as defined in the appended claims.

Claims

Claims:

1. A method of analyzing cuts of meat, the method including: storing information defining a plurality of possible product classes as predetermined values of a set of attributes; detecting attributes of a cut of meat to be analyzed, the detected attributes corresponding to attributes in said set of attributes; for each said possible product class comparing each detected attribute with its corresponding attribute in said set of attributes and dependent on the comparison computing a total score indicating the likelihood ofthe cut of meat being a member of that possible product class; identifying the product class ofthe cut of meat as the possible product class having the total score indicating the most likelihood ofthe cut of meat being a member of that possible product class.

2. The method of claim 1 , wherein said set of attributes includes values for cut weight and specific cut dimensions.

3. The method of claim 1 or claim 2, wherein said set of attributes includes values for at least one of cut volume and cut cross-section.

4. The method of any one ofthe preceding claims, wherein said set of attributes includes values for the symmetry ofthe cut of meat over at least one of a longitudinal and lateral axis.

5. The method of any one ofthe preceding claims, wherein said set of attributes includes values for at least one ofthe cut height variation and cut area variation.

6. The method of any one ofthe preceding claims, wherein said total score is computed as a weighted sum ofthe result for each attribute ofthe step of comparing each detected attribute with its corresponding attribute in said set of attributes, wherein a weighting for each said result is specific for each product class and is predetermined based on the extent that that the particular attribute distinguishes that product class from others of said possible product classes.

7. A method of packaging cuts of meat in a processing line including a supply of cuts of meat of different classes, the method including receiving cuts of meat from said supply, analyzing each cut of meat in accordance with the method of any one ofthe preceding claims to determine the product class ofthe cut of meat under analysis and varying a packaging process for the cut of meat dependent on the determined product class.

8. The method of claim 7 wherein the step of varying a packaging process for the cut of meat dependent on the determined product class includes selecting a type of packaging for the cut of meat dependent on the determined product class.

9. The method of claim 7 or claim 8 including printing indicia onto packaging for a cut of meat or onto a label for said packaging, wherein the step of varying a packaging process for said cut of meat dependent on the determined product class includes printing different indicia on the packaging dependent on the determined product class.

10. The method of claim 9, further including printing with said indicia further indicia that specifies particular quality or grade characteristics ofthe cut of meat.

11. Apparatus for analyzing cuts of meat, the apparatus including: detector means for detecting one or more product attributes of a cut of meat; machine readable information storage means containing information defining a plurality of possible product classes as predetermined values of a set of attributes; and a processor in communication with said detector means and said storage means, the processor operable to: for each possible product class retrieve from said storage means the value of each attribute in said set of attributes and compare it with the value of a corresponding attribute detected by said detector means and compute a total score indicating the likelihood ofthe cut of meat belongs to that possible product class dependent on the comparison; and provide an output indicating the possible product class that has the most likelihood that the cut of meat belongs to it.

12. A packaging line for cuts of meat from a supply of variable cut classes, the packaging line including apparatus for analyzing cuts of meat in accordance with claim 11, a packaging workstation the operation of which is at least partially controlled by a controller, and transport means for transporting cuts of meat from said supply to said packaging workstation via said apparatus for analyzing cuts of meat, wherein said controller is operable to receive an output from said apparatus for analyzing cuts of meat identifying the product class for a cut of meat and automatically update the operation of said packaging workstation for said cut of meat in response to a change in said output between cuts of meat.

13. The packaging line of claim 12, wherein the controller updates the operation of the packaging workstation by changing the type of packaging supplied for said cut of meat.

14. The packaging line of claim 12 or claim 13, wherein the packaging workstation further includes a printer for printing indicia onto packaging for said cut of meat or onto a label for said packaging, wherein the controller updates the operation of the packaging workstation by causing the workstation to print different indicia on the packaging or label.

15. The packaging line of claim 14, wherein said controller further controls the printer to print further indicia on said packaging or said label, the further indicia that specifying particular quality or grade characteristics ofthe cut of meat as determined by said processing means dependent on attributes detected by said detecting means.

16. The packaging line of any one of claims 12 to 15, wherein said controller is the same device as the processor of said apparatus for analyzing cuts of meat.

17. A method of analyzing cuts of meat substantially as herein described with reference to the accompanying drawings.

18. A method of packaging cuts of meat from a source of cuts of varying product class substantially as herein described with reference to the accompanying drawings.

19. Apparatus for analyzing cuts of meat substantially as herein described with reference to the accompanying drawings.

20. A packaging line for cuts of meat from a supply of variable cut classes substantially as herein described with reference to the accompanying drawings.