Measurement system, meat cutting system, measurement method, and program

Abstract

The invention provides a measuring system comprising: a light source; a light-projecting optical fiber for irradiating the first light from the light source to a fat layer portion of meat to be measured; a light-receiving optical fiber that is provided separately from the light-projecting optical fiber and that receives second light that is output from the fat layer portion of the meat when the fat layer portion of the meat is irradiated with the first light; and a fat layer thickness derivation section for deriving the thickness (i.e., the measured thickness) of the fat layer portion of the meat on the basis of the calibration model and the absorbance of the second light in the vicinity of the absorption wavelength of the fat. The calibration model is information obtained by correlating the thickness (reference thickness) of the fat layer portion of the meat for reference and the absorbance of light output from the fat layer portion of the meat for reference near the absorption wavelength of fat when the light emitted by the light source is irradiated to the fat layer portion of the meat for reference.

Description

Technical Field

[0001] The present invention relates to a measurement system, a meat cutting system, a measurement method, and a program.

[0002] This application claims priority based on Japanese Patent Application No. 2022-167720 filed on October 19, 2022, and incorporates its content by reference into this specification. Background Art

[0003] The excess fat layer on the surface of pork needs to be removed in the meat processing step. Usually, the excess fat layer on the surface of pork is manually removed using a knife. For example, an operator uses a skinner, while holding and moving the pork on a platform, and uses a knife fixed on the platform to remove the fat. The operator does not need to hold the knife, so it is safe and can simplify the operation itself. In order to simplify or automate this operation, various companies are developing various devices. For example, regarding the method of identifying the fat thickness, there are known methods using near-infrared light and impedance (for example, refer to Patent Document 1 and Patent Document 2).

[0004] Prior Art Documents

[0005] Patent Documents

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2007-151619

[0007] Patent Document 2: Japanese Patent Application Laid-Open No. 2010-82070 Summary of the Invention

[0008] Problems to be Solved by the Invention

[0009] In the case of using a skinner, the identification of the fat part and the processing of the meat cannot be automated.

[0010] There is a device that can automatically process the steps from the identification of the fat thickness to the removal for the pork loin and streaky pork. In this device, the fat exposed on the cross-section of the meat is photographed from the side with a camera, and image processing is performed on the obtained image to calculate the thickness of the fat. This device cuts (cuts) at a fixed value based on the thickness data of the fat exposed on the cross-section. Therefore, even if the thickness of the fat changes during cutting, it cannot cut corresponding to the changed fat thickness.

[0011] In order to change the cutting depth during processing, it is necessary to perform real-time and continuous non-destructive measurement of the thickness of the fat inside the meat. In the non-destructive measurement method of fat thickness described in Patent Document 1, internal information of food can be obtained by impedance measurement. However, since the electrodes must be reliably attached to the measurement object, it is difficult to apply it in-line in a food factory.

[0012] On the other hand, near-infrared light has good permeability and has been used for on-line food composition analysis. In Patent Document 2, near-infrared light is irradiated onto a living body, and the amount of transmitted light that is attenuated due to absorption and scattering when passing through the body is monitored, and then converted into the thickness of fat. However, the light transmission phenomenon is very complex, and in addition to the presence of muscle and fat, there are also reasons for the change in the amount of transmitted light, which will reduce the measurement accuracy of the fat thickness.

[0013] An object of the present invention is to provide a measurement system, a meat cutting system, a measurement method, and a program that can improve the measurement accuracy of the thickness of the fat layer.

[0014] Means for solving the problem

[0015] (1) One embodiment of the present invention is a measurement system, which includes: a light source;

[0016] A light-projecting optical fiber that irradiates first light from the light source onto the fat layer portion of meat as a measurement object; a light-receiving optical fiber that is provided separately from the light-projecting optical fiber and receives second light output from the fat layer portion of the meat when the first light is irradiated onto the fat layer portion of the meat; a fat layer thickness derivation unit that derives a measurement thickness based on a calibration model and the absorbance of the second light near the absorption wavelength of fat, where the measurement thickness is the thickness of the fat layer portion of the meat, and the calibration model is information obtained by correlating a reference thickness, which is the thickness of the fat layer portion of a reference meat, with the absorbance of the light output from the fat layer portion of the reference meat when the light emitted by the light source is irradiated onto the fat layer portion of the reference meat near the absorption wavelength of fat.

[0017] (2) According to one embodiment of the present invention, in the aforementioned measurement system, it further includes: a spectroscope for generating a spectrogram of the second light; and an absorbance derivation unit for deriving the absorbance near the absorption wavelength of fat based on the spectrogram of the second light generated by the spectroscope, and the fat layer thickness derivation unit derives the measurement thickness based on the absorbance derived by the absorbance derivation unit and the calibration model.

[0018] (3)According to an embodiment of the present invention, in the aforementioned measurement system, the absorbance derivation unit performs either or both of baseline correction and smoothing processing on the spectral distribution of the second light, and derives the absorbance near the absorption wavelength of fat based on the spectral distribution of the second light that has undergone either or both of baseline correction and smoothing processing.

[0019] (4)According to an embodiment of the present invention, in the aforementioned measurement system, it further includes a creation unit for creating the calibration model.

[0020] (5)According to an embodiment of the present invention, in the aforementioned measurement system, the spectroscope generates a spectral distribution, which is the spectral distribution of the light output from the fat layer portions of a plurality of the reference meats with different fat layer thicknesses when the light is respectively irradiated on the fat layer portions of the plurality of reference meats. Among them, the absorbance derivation unit obtains the absorbance near the absorption wavelength of fat based on the spectral distribution of the light generated by the spectroscope, and the creation unit creates the calibration model by deriving the relationship between the absorbance and the reference thickness of the plurality of reference meats, and the reference thickness corresponds to the spectral distribution of the light used when obtaining the absorbance.

[0021] (6)According to an embodiment of the present invention, in the aforementioned measurement system, the absorbance derivation unit performs either or both of baseline correction and smoothing processing on the spectral distribution of the light, and obtains the absorbance near the absorption wavelength of fat based on the spectral distribution of the light that has undergone either or both of the baseline correction and the smoothing processing.

[0022] (7)According to an embodiment of the present invention, in the aforementioned measurement system, the wavelength near the absorption wavelength of the fat of the second light is 800 nm to 1100 nm.

[0023] (8)An embodiment of the present invention is a meat cutting system, which, in the aforementioned measurement system, includes: an acquisition unit for acquiring information indicating the thickness of the meat fat layer derived by the measurement system according to any one of the above (1) to (7); and a control unit for controlling the separation of the meat into a fat layer and lean meat, wherein the control unit determines the thickness of the fat layer separated from the meat based on the information indicating the thickness of the fat layer of the meat acquired by the acquisition unit.

[0024] (9)One embodiment of the present invention is a measurement method, which is a measurement method performed by a measurement system. The measurement system includes: a light source; a light projecting optical fiber that irradiates a first light from the light source onto a fat layer portion of meat as a measurement object; and a light receiving optical fiber that is disposed separately from the light projecting optical fiber and receives a second light output from the fat layer portion of the meat when the first light is irradiated onto the fat layer portion of the meat. The measurement method includes the following steps: irradiating a first light from the light source onto a fat layer portion of meat; receiving the second light output from the fat layer portion of the meat; and deriving a measurement thickness based on a calibration model and an absorbance of the second light near an absorption wavelength of fat, where the measurement thickness is the thickness of the fat layer portion of the meat as the measurement object. The calibration model is information obtained by correlating a reference thickness of a fat layer portion of a reference meat with an absorbance of light output from the fat layer portion of the reference meat near an absorption wavelength of fat when the light emitted from the light source is irradiated onto the fat layer portion of the reference meat.

[0025] (10)One embodiment of the present invention is a program that causes a computer of a measurement system to execute the following steps. The measurement system includes: a light source; a light projecting optical fiber that irradiates a first light from the light source onto a fat layer portion of meat as a measurement object; and a light receiving optical fiber that is disposed separately from the light projecting optical fiber and receives a second light output from the fat layer portion of the meat when the first light is irradiated onto the fat layer portion of the meat. The steps include: irradiating a first light from the light source onto a fat layer portion of meat; receiving the second light output from the fat layer portion of the meat; and deriving a measurement thickness based on a calibration model and an absorbance of the second light near an absorption wavelength of fat, where the measurement thickness is the thickness of the fat layer portion of the meat as the measurement object. The calibration model is information obtained by correlating a reference thickness of a fat layer portion of a reference meat with an absorbance of light output from the fat layer portion of the reference meat near an absorption wavelength of fat when the light emitted from the light source is irradiated onto the fat layer portion of the reference meat.

[0026] Advantages of the Invention

[0027] According to an embodiment of the present invention, a measurement system, a meat cutting system, a measurement method, and a program that can improve the measurement accuracy of the fat layer thickness can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a diagram showing an example of a measurement system according to the present embodiment.

[0029] Figure 2 This is a diagram showing an example of the operation of the measurement system according to the present embodiment.

[0030] Figure 3 This is a diagram showing an example of the effect of the measurement system according to the present embodiment.

[0031] Figure 4 This is a diagram showing an example of the measurement system according to Modification 1 of the embodiment.

[0032] Figure 5A This is a diagram showing an example of the processing of the measurement system according to Modification 1 of the embodiment.

[0033] Figure 5B This is a diagram showing an example of the processing of the measurement system according to Modification 1 of the embodiment.

[0034] Figure 6 This is a diagram showing an example of a spectrogram.

[0035] Figure 7 This is a diagram showing an example of the operation of the measurement system according to Modification 1 of the embodiment.

[0036] Figure 8 This is a diagram showing an example of the meat cutting system according to Modification 2 of the embodiment.

[0037] Figure 9 This is a schematic diagram showing an example of the meat cutting system according to Modification 2 of the embodiment.

[0038] Figure 10 This is a diagram showing an example of the information processing device according to Modification 2 of the present embodiment.

[0039] Figure 11 This is a flowchart showing an example of the operation of the meat cutting system according to Modification 2 of the embodiment.

[0040] Figure 12 This is a diagram showing another example of the meat cutting system according to Modification 3 of the embodiment.

[0041] Figure 13A This shows an example of removing the fat layer using an existing meat cutting system.

[0042] Figure 13B This shows an example of removing the fat layer using the meat cutting system according to Modification 3 of the embodiment. Detailed implementation manners

[0043] Next, a measurement system, a meat cutting system, a measurement method, and a program according to embodiments of the present invention will be described with reference to the accompanying drawings. The embodiments described below are merely examples, and the embodiments of the present invention are not limited to the following embodiments.

[0044] In addition, in all the drawings for explaining the embodiments, parts having the same function are denoted by the same reference numerals, and redundant explanations are omitted.

[0045] In addition, the "based on XX" as used in this application means "at least based on XX", and also includes cases based on other elements in addition to XX. In addition, "based on XX" is not limited to directly using XX, and also includes cases based on performing operations or processing on XX. "XX" is an arbitrary element (for example, arbitrary information).

[0046] Hereinafter, a measurement system according to an embodiment of the present invention will be described with reference to the accompanying drawings. Figure 1 FIG. is a diagram showing an example of a measurement system 100 according to the present embodiment.

[0047] The measurement system 100 measures the thickness (measured thickness) of the fat layer FL of the meat ME as a measurement object. The measurement system 100 includes a light source 101, a light-projecting optical fiber 102, a light-receiving optical fiber 103, a spectroscope 104, an information processing device 110, and an optical fiber holder FH.

[0048] In Figure 1 the example shown, the light-projecting optical fiber 102 and the light-receiving optical fiber 103 are installed at positions spaced apart from the fat layer FL portion of the meat ME. The light-projecting optical fiber 102 and the light-receiving optical fiber 103 may also be contact-mounted on the fat layer FL portion of the meat ME. Here, the meat ME includes a fat layer FL and lean meat RM. The optical fiber holder FH fixes the light-projecting optical fiber 102 and the light-receiving optical fiber 103 to the meat ME.

[0049] The light source 101 emits light (hereinafter also referred to as "first light"). An example of the light source 101 is a halogen lamp. The halogen lamp emits electromagnetic waves in the near-infrared region with a wavelength of 600 nm to 1100 nm.

[0050] The light-projecting optical fiber 102 is connected to the light source 101, and irradiates (inputs) the first light emitted by the light source 101 to the fat layer FL portion of the meat ME. An aspherical lens is installed at the front end of the light-projecting optical fiber 102 on the fat layer FL side of the meat ME. By configuring in this way, the linear propagation property of the first light output from the light-projecting optical fiber 102 can be maintained, and thus the first light can reach the deep part of the meat ME. The light-projecting optical fiber 102 is fixed by the optical fiber holder FH so that the first light output from the light-projecting optical fiber 102 irradiates the fat layer FL of the meat ME.

[0051] The light-receiving optical fiber 103 receives the light (hereinafter also referred to as "second light") that is irradiated from the light-projecting optical fiber 102 to the fat layer FL portion of the meat ME and is affected by at least one of diffusion, absorption, and reflection inside the meat ME. The light-receiving optical fiber 103 outputs the received second light to the spectroscope 104. An aspherical lens is installed at the front end of the light-receiving optical fiber 103 on the fat layer FL side of the meat ME. By configuring in this way, the second light input to the light-receiving optical fiber 103 can be effectively focused. Therefore, the light-receiving optical fiber 103 can make the focused second light reach the spectroscope 104. The light-receiving optical fiber 103 is fixed by the optical fiber bracket FH to be parallel to and spaced apart from the light-projecting optical fiber 102, and can receive the second light. For example, the light-receiving optical fiber 103 is parallel to the light-projecting optical fiber 102 and fixed at a distance of about 10 mm to 30 mm.

[0052] The spectroscope 104 spectroscopically analyzes the second light output from the light-receiving optical fiber 103 for each wavelength and is received by the detector, thereby measuring the absorbance. The spectroscope 104 generates a spectroscopic spectrum by deriving the relationship between the wavelength of the second light and the absorbance.

[0053] The information processing device 110 is implemented by a device such as a personal computer, a server, a smart phone, a tablet computer, or an industrial computer. The information processing device 110 includes an absorbance derivation unit 112, a fat layer thickness derivation unit 114, an output unit 116, and a storage unit 118.

[0054] The storage unit 118 is implemented, for example, by a RAM, a ROM, an HDD, a flash memory, or a hybrid storage device obtained by combining multiple of these components. Part or all of the storage unit 118 may be implemented by an external device such as a network attached storage (NAS) or an external storage server that can be accessed by the processor of the information processing device 110 via a network (not shown) instead of being provided as a part of the information processing device 110.

[0055] The absorbance derivation unit 112 obtains the spectroscopic spectrum from the spectroscope 104 and obtains the absorbance (hereinafter referred to as "fat absorbance") near the absorption wavelength of the fat based on the obtained spectroscopic spectrum. An example near the absorption wavelength of the fat is 800 nm to 1100 nm. Additionally, an example near the absorption wavelength of the fat can also be 900 nm to 1000 nm.

[0056] The fat layer thickness derivation unit 114 includes a calibration model 114a. The calibration model 114a is information obtained by correlating the thickness of the fat layer FL portion of the reference meat ME (reference thickness) with the absorbance of the light output from the fat layer FL portion of the reference meat ME when the light emitted by the light source 110 is irradiated onto the fat layer FL portion of the reference meat ME near the absorption wavelength of fat. An example of the wavelength near the absorption wavelength of fat for the light used by the fat layer thickness derivation unit 114 is from 800 nm to 1100 nm. Additionally, an example of the wavelength near the absorption wavelength of fat for the light can also be from 900 nm to 1000 nm. The calibration model 114a can be created for each distance (spacing distance) between the light projection optical fiber 102 and the light reception optical fiber 103. The calibration model 114a is created in advance. Details regarding the creation of the calibration model 114a will be described later.

[0057] The fat layer thickness derivation unit 114 obtains information representing the fat absorbance from the absorbance derivation unit 112. The fat layer thickness derivation unit 114 derives the thickness (measurement thickness) of the fat layer FL portion of the meat ME to be measured by obtaining, from the calibration model 114a, the thickness (reference thickness) of the fat layer FL portion of the reference meat ME corresponding to the obtained information representing the fat absorbance.

[0058] The output unit 116 obtains information representing the thickness (measurement thickness) of the fat layer FL portion of the meat ME from the fat layer thickness derivation unit 114 and outputs the information representing the obtained thickness (measurement thickness) of the fat layer FL portion of the meat ME. For example, the output unit 116 can output by sound or can output by displaying on a display unit (not shown).

[0059] All or part of the absorbance derivation unit 112, the fat layer thickness derivation unit 114, and the output unit 116 are functional units (hereinafter referred to as software functional units) implemented, for example, by a processor such as a CPU (Central Processing Unit) executing a program stored in the storage unit 118.

[0060] In addition, all or part of the absorbance derivation unit 112, the fat layer thickness derivation unit 114, and the output unit 116 can be implemented by hardware such as a large scale integration (LSI), an application specific integrated circuit (ASIC), or a field-programmable gate array (FPGA), or can be implemented by a combination of a software functional unit and hardware.

[0061] (Operation of the measurement system)

[0062] Figure 2 is a diagram showing an example of the operation of the measurement system 100 according to an embodiment. Refer to Figure 2 , and the process of the measurement system 100 measuring the thickness (measurement thickness) of the fat layer FL of the meat ME as the measurement object will be described.

[0063] (Step S1-1)

[0064] The light source 101 emits first light.

[0065] (Step S2-1)

[0066] The first light emitted by the light source 101 is input into the light-projecting optical fiber 102.

[0067] (Step S3-1)

[0068] The light-projecting optical fiber 102 irradiates the fat layer FL portion of the meat ME with the first light input from the light source 101.

[0069] (Step S4-1)

[0070] The light-receiving optical fiber 103 receives second light that has been affected by at least one of diffusion, absorption, and reflection inside the meat ME.

[0071] (Step S5-1)

[0072] The second light received by the light-receiving optical fiber 103 is output to the spectroscope 104.

[0073] (Step S6-1)

[0074] The spectroscope 104 spectroscopically analyzes the second light output from the light-receiving optical fiber 103 for each wavelength and is received by the detector, thereby measuring the absorbance. The spectroscope 104 generates a spectroscopic spectrum by deriving the relationship between the wavelength of the second light and the absorbance.

[0075] (Step S7-1)

[0076] In the information processing device 110, the absorbance derivation unit 112 acquires the spectroscopic spectrum from the spectroscope 104.

[0077] (Step S8-1)

[0078] In the information processing device 110, the absorbance derivation unit 112 derives the fat absorbance near the absorption wavelength of fat based on the acquired spectroscopic spectrum.

[0079] (Step S9-1)

[0080] In the information processing device 110, the fat layer thickness derivation unit 114 acquires information indicating the fat absorbance from the absorbance derivation unit 112. Based on the calibration model 114a and the acquired information indicating the fat absorbance, the fat layer thickness derivation unit 114 derives the thickness (measured thickness) of the fat layer FL portion of the meat ME to be measured.

[0081] (Step S10-1)

[0082] In the information processing device 110, the output unit 116 acquires information indicating the thickness (measured thickness) of the fat layer FL portion of the meat ME from the fat layer thickness derivation unit 114, and outputs the information indicating the thickness (measured thickness) of the fat layer FL portion of the obtained meat ME.

[0083] In the foregoing embodiment, as an example, the case where the measurement system 100 includes one light receiving optical fiber 103 is illustrated, but this is not limited to this example. For example, the measurement system 100 may include a plurality of light receiving optical fibers. In this case, a calibration model is provided for each interval distance between the light projecting optical fiber 102 and each of the plurality of light receiving optical fibers. By configuring in this way, it is possible to simultaneously measure the thicknesses (measured thicknesses) of the fat at different multiple positions in the fat layer FL thickness of the meat ME.

[0084] In the foregoing embodiment, it may also be configured that the measurement system 100 does not include the spectroscope 104 and the absorbance derivation unit 112, and the fat layer thickness derivation unit 114 acquires the absorbance of the second light outside the measurement system 100 near the absorption wavelength of the fat.

[0085] In the foregoing embodiment, the absorbance derivation unit 112 may perform either or both of baseline correction and smoothing processing on the spectral distribution of the second light. Examples of baseline correction include differential processing of the spectrum (including second-order differential), standard normal variate (SNV) processing, multiplicative scatter correction (MSC) processing, mean centering processing, etc. Examples of smoothing processing include Savitzky-Golay Smoothing (SG smoothing), etc.

[0086] For example, the absorbance derivation unit 112 can eliminate the influence of the variation in the amount of transmitted light (baseline variation) through general preprocessing methods such as differential processing of the spectrum, Standard Normal Variate (SNV) processing, Multiplicative Scatter Correction (MSC) processing, and mean centering processing. In this case, the absorbance derivation unit 112 derives the absorbance near the absorption wavelength of fat based on the spectral spectrum of the second light obtained by performing any one or both of baseline correction and smoothing processing.

[0087] The effects of the measurement system 100 according to the present embodiment will be described. Figure 3 It is a diagram showing an example of the effects of the measurement system 100 according to the present embodiment. Figure 3 It shows the relationship between the thickness (measured thickness) of the fat layer FL of the meat ME to be measured derived by the measurement system 100 and the actual measured value of the thickness of the fat layer FL of the meat ME to be measured. In Figure 3 it, the horizontal axis is the actual measured value (mm) of the thickness of the fat layer FL of the meat ME, and the vertical axis is the derived value (predicted value) (mm) of the thickness of the fat layer FL of the meat ME. The thickness range of the fat layer FL of the meat ME to be measured is set to 5 mm to 15 mm. The measured spectral data is preprocessed by the absorbance derivation unit 112 (Savitzky-Golay Smoothing (SG smoothing) ±20 nm, second derivative).

[0088] Using multiple derived values of the thickness (measured thickness) of the fat layer FL of the meat ME derived by the measurement system 100, the prediction accuracy was evaluated. According to Figure 3 , the root mean square error (RMSE) is 1.076, and the coefficient of determination R 2 is 0.933. As can be seen from the above, the predicted value and the actual measured value are in very good agreement.

[0089] According to the measurement system 100 of the present embodiment, when the measurement system 100 irradiates a first light on the fat layer FL portion of the meat ME as the measurement object, it receives the second light output from the fat layer FL portion spaced apart from the portion of the meat ME irradiated with the first light. After that, according to the measurement system 100 of the present embodiment, based on the calibration model 114a and the absorbance of the second light near the absorption wavelength of fat, the thickness (measured thickness) of the fat layer FL portion of the meat ME is derived, where the calibration model 114a is information obtained by correlating the thickness (reference thickness) of the fat layer FL portion of the reference meat ME with the absorbance of the light output from the fat layer FL portion of the reference meat ME near the absorption wavelength of fat when the light is irradiated on the fat layer FL portion of the reference meat ME. Therefore, the thickness (measured thickness) of the fat layer FL portion of the meat ME can be derived in a non-destructive manner without damaging the meat ME as the measurement object by using the optical system indirectly.

[0090] Here, the vicinity of the absorption wavelength of fat of the second light is 800 nm to 1100 nm. By configuring in this way, the absorbance of the second light near the absorption wavelength of fat can be obtained. Therefore, compared with the case of deriving the thickness (measured thickness) of the fat layer FL portion of the meat ME based on the calibration model 114a and the absorbance of the second light at the absorption wavelength of fat determined in advance, the thickness (measured thickness) of the fat layer FL portion of the meat ME can be derived with high precision.

[0091] In addition, the measurement system 100 generates the spectral spectrum of the second light and derives the absorbance near the absorption wavelength of fat based on the generated spectral spectrum of the second light. The measurement system 100 derives the thickness (measured thickness) of the fat layer FL portion of the meat ME based on the derived absorbance and the calibration model 114a. By measuring the absorbance of each wavelength of the second light and capturing (detecting) the absorption peak caused by fat from the generated spectral spectrum of the second light, the absorption wavelength of fat can be obtained. Therefore, by using the calibration model 114a, the thickness (measured thickness) of the fat layer FL portion of the meat ME can be derived indirectly from the obtained absorption wavelengths. That is, compared with the case of deriving the thickness of the fat layer FL portion of the meat ME based on the calibration model 114a and the absorbance of the second light at the absorption wavelength of fat determined in advance, the thickness (measured thickness) of the fat layer FL portion of the meat ME can be derived with high precision.

[0092] In addition, the measurement system 100 performs either or both of baseline correction and smoothing on the spectral distribution of the second light, and derives the absorbance near the absorption wavelength of fat based on the spectral distribution of the second light on which either or both of baseline correction and smoothing have been performed. Therefore, compared with the case where neither or both of baseline correction and smoothing are performed on the spectral distribution of the second light, measurement errors and errors between workpieces can be excluded, and thus the estimation accuracy of the thickness (measured thickness) of the fat layer FL portion of the meat ME can be improved.

[0093] (Modification Example 1 of the Embodiment)

[0094] Figure 4 FIG. shows an example of a measurement system 100a according to Modification Example 1 of the embodiment. The measurement system 100a according to Modification Example 1 of the embodiment is a system that has a function of creating a calibration model 114a on the basis of the measurement system 100.

[0095] The measurement system 100a measures the fat thickness (measured thickness) of the meat ME. The measurement system 100a includes a light source 101, a light-projecting optical fiber 102, a light-receiving optical fiber 103, a spectroscope 104, an information processing device 110a, and an optical fiber holder FH.

[0096] The information processing device 110a is implemented by a device such as a personal computer, a server, a smart phone, a tablet computer, or an industrial computer. The information processing device 110a includes an absorbance derivation unit 112, a fat layer thickness derivation unit 114, an output unit 116, a storage unit 118, an input unit 119a, and a creation unit 120a.

[0097] The process of creating the calibration model 114a for the information processing device 110a will be described.

[0098] In each part of the fat layer FL of a plurality of reference meat ME with different fat layer FL thicknesses, the first light emitted from the light source 101 is irradiated via the light-projecting optical fiber 102. The thicknesses (reference thicknesses) of the fat layers FL of the plurality of reference meat ME are all known.

[0099] The light-receiving optical fiber 103 receives multiple beams of second light, which are respectively input from the light-projecting optical fiber 102 into each part of the fat layer FL of a plurality of meat ME, and are affected by at least one of diffusion, absorption, and reflection inside the meat ME (inside the fat layer FL of the meat ME) as described above.

[0100] The spectroscope 104 spectrally analyzes each beam of the multiple beams of second light output from the light-receiving optical fiber 103 by wavelength, and measures the absorbance by receiving with a detector. The spectroscope 104 generates multiple spectral distributions of the second light.

[0101] Figure 5A and Figure 5B is a diagram showing an example of the processing of the measurement system 100a according to Modification 1 of the embodiment. Figure 5A is a diagram showing an example of the spectroscopic spectrum obtained by the absorbance derivation unit 112. In Figure 5A , the horizontal axis is the wavelength (nm) and the vertical axis is the absorbance. In Figure 5A , as an example, for the case where the thickness of the fat layer is 5 mm, 10 mm, and 15 mm, the 5-mm and 10-mm fat layers were measured three times each, and the 15-mm fat layer was measured six times. As a result, the case where the wavelength is from 630 nm to 1030 nm is shown. According to Figure 5A , it can be seen that the absorbance varies depending on the thickness of the fat layer FA, but the same characteristics are obtained.

[0102] Figure 5B is Figure 5A an enlarged view of the portion of the spectroscopic spectrum shown in Figure 5B from a wavelength of 880 nm to 980 nm. From

[0103] Figure 6 is a diagram showing an example of the spectroscopic spectrum. Figure 6 represents the spectroscopic spectrum of the light that is irradiated onto the lean meat RM of the meat ME by the light emitted from the light source 101 and is affected by at least one of diffusion, absorption, and reflection inside the lean meat RM. In Figure 6 , the horizontal axis is the wavelength (nm) and the vertical axis is the absorbance. In addition, the thickness of the lean meat RM is 30 mm. From Figure 6 , it can be seen that the absorbance peaks at a wavelength of approximately 980 nm.

[0104] From Figure 5B and Figure 6 , it can be seen that in the spectroscopic spectrum obtained by irradiating the fat layer FL of the meat ME with the light emitted from the light source 101, the absorbance peaks at a wavelength of approximately 930 nm, and in the spectroscopic spectrum obtained by irradiating the lean meat RM portion with the light emitted from the light source 101, the absorbance peaks at a wavelength of approximately 980 nm. Therefore, it is possible to determine whether it is the fat layer FL or the lean meat RM based on the spectroscopic spectrum. Returning to Figure 4 continue the description.

[0105] The absorbance derivation unit 112 obtains a plurality of spectral spectra from the spectroscope 104, and obtains the fat absorbance of light near the absorption wavelength of fat from each of the obtained plurality of spectral spectra. An example of the vicinity of the absorption wavelength of fat of light is from 800 nm to 1100 nm. In addition, an example of the vicinity of the absorption wavelength of fat of light may also be from 900 nm to 1000 nm.

[0106] The input unit 119a inputs information. As an example, the input unit 119a may include an operation unit such as a keyboard and a mouse. In this case, the input unit 119a inputs information corresponding to the operation performed by the user on the operation unit. As another example, the input unit 119a may also input information from an external device. The external device may be, for example, a removable storage medium. Information indicating the thickness (reference thickness) of each fat layer FL of the plurality of reference meats ME is input in the input unit 119a.

[0107] The creation unit 120a obtains information for indicating the thickness (reference thickness) of each fat layer FL of the plurality of reference meats ME input to the input unit 119a. The creation unit 120a obtains the fat absorbance corresponding to the information indicating the thickness (reference thickness) of each fat layer FL of the obtained plurality of reference meats ME from the absorbance derivation unit 112. The creation unit 120a derives the relationship between the thickness (reference thickness) of the fat layer FL of the reference meat ME and the fat absorbance based on a plurality of information obtained by associating the thickness (reference thickness) of the fat layer FL of the reference meat ME with the fat absorbance, thereby creating the calibration model 114a.

[0108] For example, the creation unit 120a uses general regression analysis methods such as simple regression, multiple regression, principal component analysis (PCA) regression, and partial least squares regression (PLS regression) to create the calibration model 114a based on a plurality of information obtained by associating the thickness (reference thickness) of the fat layer FL of the reference meat ME with the fat absorbance. The creation unit 120a outputs the created calibration model 114a to the fat layer thickness derivation unit 114. The fat layer thickness derivation unit 114 stores the calibration model 114a output by the creation unit 120a.

[0109] All or part of the input unit 119a and the creation unit 120a are functional units (hereinafter referred to as software functional units) implemented by, for example, a processor such as a CPU executing a program stored in the storage unit 118. In addition, all or part of the input unit 119a and the creation unit 120a can be implemented by hardware such as a large-scale integration (LSI), an application-specific integrated circuit (ASIC), or a field-programmable gate array (FPGA), or can be implemented by a combination of a software functional unit and hardware.

[0110] (Process of creating a calibration model)

[0111] Figure 7 is a diagram showing an example of the process of creating a calibration model for the measurement system 100a according to Modification 1 of the embodiment. Refer to Figure 7 and the process of creating the calibration model 114a for the measurement system 100a will be described. In steps S2-2 to S9-2, the steps S1-1 to S8-1 of Figure 2 can be applied, so the description thereof is omitted here.

[0112] (Step S1-2)

[0113] In the information processing device 110a, information indicating the thickness (reference thickness) of each fat layer FL of a plurality of reference meats ME is input to the input unit 119a.

[0114] (Step S10-2)

[0115] In the information processing device 110a, the creation unit 120a acquires information indicating the thickness (reference thickness) of each fat layer FL of a plurality of reference meats ME input to the input unit 119a. The creation unit 120a acquires the fat absorbance corresponding to the information indicating the thickness (reference thickness) of each fat layer FL of the plurality of reference meats ME obtained from the absorbance derivation unit 112. The creation unit 120a associates the thickness (reference thickness) of the fat layer FL of the reference meat ME with the fat absorbance.

[0116] (Step S11-2)

[0117] In the information processing apparatus 110a, the creation unit 120a determines whether to create the calibration model 114a. For example, the creation unit 120a determines to create the calibration model 114a when the association with the fat absorbance is completed for all the information indicating the thickness (reference thickness) of the fat layer FL of the plurality of reference meats ME obtained in step S1-2, and determines not to create it when the association is not completed. When the creation unit 120a determines to create the calibration model 114a, it proceeds to step S12-2, and when the creation unit 120a determines not to create the calibration model 114a, it returns to step S2-2.

[0118] (Step S12-2)

[0119] In the information processing apparatus 110a, the creation unit 120a derives the relationship between the thickness (reference thickness) of the fat layer FL of the reference meat ME and the fat absorbance based on a plurality of pieces of information obtained by correlating the thickness (reference thickness) of the fat layer FL of the reference meat ME with the fat absorbance, and thus creates the calibration model 114a. For example, the creation unit 120a uses methods such as PLS regression analysis, principal component regression analysis, multiple regression analysis, and simple regression analysis to create the calibration model 114a.

[0120] (Step S13-2)

[0121] In the information processing apparatus 110a, the creation unit 120a outputs the created calibration model 114a to the fat layer thickness derivation unit 114. The fat layer thickness derivation unit 114 stores the calibration model 114a output by the creation unit 120a.

[0122] In the first modification of the foregoing embodiment, the absorbance derivation unit 112 may perform either or both of baseline correction and smoothing processing on the spectral spectrum of light, and obtain the absorbance near the absorption wavelength of fat based on the spectral spectrum of light that has undergone either or both of baseline correction and smoothing processing. By configuring in this way, compared with the case where neither baseline correction nor smoothing processing is performed on the spectral spectrum of light, the influence of baseline fluctuations and the like can be excluded, and thus the accuracy of the absorbance near the absorption wavelength of fat can be improved.

[0123] In the first modification of the foregoing embodiment, the calibration model 114a may also be created by a device different from the information processing apparatus 110a. For example, it may be implemented as a calibration model creation device.

[0124] The measurement system 100a according to Modification Example 1 of the embodiment creates a calibration model 114a. Thus, a calibration model 114a can be created for each measurement system 100a. Therefore, compared with the case where a calibration model 114a is not created for each measurement system 100a, that is, the case where a calibration model created by another measurement system 100a is used, the derivation accuracy of the thickness (measured thickness) of the fat layer FL of the meat ME to be measured can be improved.

[0125] In addition, when the measurement system 100a irradiates light on each part of the fat layer FL of a plurality of reference meats ME with different fat layer FL thicknesses, it generates a spectral spectrum of the light output from the fat layer FL part of the reference meat ME, obtains the absorbance near the absorption wavelength of fat based on the generated spectral spectrum of the light, and creates the calibration model 114a by deriving the relationship between the absorbance and the thickness (reference thickness) of the fat layer FL part of the reference meat ME corresponding to the spectral spectrum of the light used when obtaining the absorbance. Therefore, based on multiple combinations of the absorbance and the thickness (reference thickness) of the fat layer FL part of the reference meat ME, the relationship between the absorbance and the thickness (reference thickness) of the fat layer FL part of the reference meat ME can be derived.

[0126] In addition, the measurement system 100a performs either or both of baseline correction and smoothing processing on the spectral spectrum of the light, and derives the absorbance near the absorption wavelength of fat based on the spectral spectrum of the light that has undergone either or both of baseline correction and smoothing processing. Therefore, compared with the case where neither baseline correction nor smoothing processing is performed on the spectral spectrum of the light, measurement errors and errors between workpieces can be excluded, and thus the derivation accuracy of the absorbance near the absorption wavelength of fat can be improved.

[0127] (Modification Example 2 of the embodiment)

[0128] Modification Example 2 of the embodiment is an example in which the measurement system 100 is applied to a meat cutting system. Figure 8 FIG. is a diagram showing an example of a meat cutting system 200 according to Modification Example 2 of the embodiment. Figure 9 FIG. is a schematic diagram showing an example of a meat cutting system 200 according to Modification Example 2 of the embodiment.

[0129] The meat cutting system 200 is a system that cuts the meat ME to be measured to separate the meat ME into a fat layer FL and a lean meat RM. The meat cutting system 200 includes a measurement system 100b, a control device 210, a cutting device 250, a belt conveyor BC, and a sensor SEN.

[0130] The measurement system 100b includes a light source 101, a beam splitter 104, an optical system 105, and an information processing device 110b. The optical system 105 includes a light-projecting optical fiber 102 and a light-receiving optical fiber 103.

[0131] The belt conveyor BC includes a belt for conveying and a roller conveyor, and conveys the meat ME to be measured to the cutting device 250.

[0132] The sensor SEN is realized by, for example, a photoelectric sensor and is provided at a predetermined position. The sensor SEN detects the situation where the meat ME has been conveyed to a predetermined position on the belt conveyor BC. When the sensor SEN detects that the meat ME has been conveyed to a predetermined position on the belt conveyor BC, the sensor SEN outputs detection notification information for notifying the situation where the meat ME has been detected to the control device 210.

[0133] The control device 210 includes a communication unit 212, an acquisition unit 214, and a control unit 216.

[0134] The communication unit 212 is realized by a communication module. The communication unit 212 communicates with external communication devices such as the light source 101, the information processing device 110b, the cutting device 250, the belt conveyor BC, and the sensor SEN via a network (not shown). The communication unit 212 communicates by, for example, a communication method such as a wired LAN. The communication unit 212 can also communicate by, for example, a wireless communication method such as a wireless LAN, Bluetooth (registered trademark), or LTE (registered trademark).

[0135] The communication unit 212 receives the detection notification information sent by the sensor SEN. The acquisition unit 214 acquires the detection notification information received by the communication unit 212.

[0136] The control unit 216 controls the measurement system 100b, the cutting device 250, the belt conveyor BC, and the sensor SEN. The control unit 216 acquires the detection notification information from the acquisition unit 214, and based on the acquired detection notification information, generates a "measurement start trigger" for causing the information processing device 110b to start measurement. The control unit 216 sends the generated measurement start trigger from the communication unit 212 to the light source 101 and the information processing device 110b.

[0137] The light source 101 receives the measurement start trigger sent by the control device 210 and emits light based on the received measurement start trigger.

[0138] The information processing device 110b receives the measurement start trigger sent by the control device 210, and based on the received measurement start trigger, starts the measurement of the thickness (measured thickness) of the fat layer FL of the meat ME. The information processing device 110b measures the thickness (measured thickness) of the fat layer FL of the meat ME. The information processing device 110b sends information indicating the thickness (measured thickness) of the fat layer FL of the meat ME, that is, thickness information, to the control device 210.

[0139] In the control device 210, the communication unit 212 receives the thickness information sent by the information processing device 110b. The acquisition unit 214 acquires the thickness information received by the communication unit 212. The control unit 216 acquires the thickness information from the acquisition unit 214. The control unit 216 generates control information based on the acquired thickness information, and the control information includes information for indicating the thickness of the fat layer FL separated from the meat ME. The control unit 216 outputs the generated control information from the communication unit 212 to the cutting device 250.

[0140] The cutting device 250 acquires the control information output by the control device 210. Based on the information indicating the thickness of the fat layer FL separated from the meat ME included in the acquired control information, the cutting device 250 separates the meat ME into the fat layer FL and the lean meat RM by cutting the meat ME.

[0141] In the control device 210, all or part of the acquisition unit 214 and the control unit 216 are, for example, functional units (hereinafter referred to as software functional units) implemented by a processor such as a CPU executing a program stored in a storage unit (not shown). In addition, all or part of the acquisition unit 214 and the control unit 216 can be implemented by hardware such as an LSI, an ASIC, or an FPGA, or can be implemented by a combination of a software functional unit and hardware. In addition, in the above control device 210, a structure in which the acquisition unit 214 is not provided can also be adopted. In this case, in the control device 210, the control unit 216 acquires the thickness information received by the communication unit 212, and the control unit 216 generates control information including information for indicating the thickness of the fat layer FL separated from the meat ME based on the acquired thickness information. Then, the control unit 216 outputs the generated control information from the communication unit 212 to the cutting device 250.

[0142] Figure 10 FIG. is a diagram showing an example of the information processing device 110b according to Modification 2 of the present embodiment. The information processing device 110b includes an absorbance derivation unit 112, a communication unit 113b, a fat layer thickness derivation unit 114, an output unit 116, and a storage unit 118.

[0143] The communication unit 113b is implemented by a communication module. The communication unit 113b communicates with an external communication device such as the control device 210 via a network (not shown). The communication unit 113b communicates by a communication method such as a wired LAN, for example. The communication unit 113b may also communicate by a wireless communication method such as a wireless LAN, Bluetooth (registered trademark), or LTE (registered trademark).

[0144] The communication unit 113b receives a measurement start trigger sent by the control device 210.

[0145] The absorbance derivation unit 112 acquires the measurement start trigger received by the communication unit 113b and starts measurement based on the acquired measurement start trigger.

[0146] Figure 11 It is a flowchart showing an example of the operation of the meat cutting system 200 according to the second modification of the embodiment. Refer to Figure 11 and the process of the meat cutting system 200 cutting the meat ME as the measurement object will be described.

[0147] (Step S1-3)

[0148] The belt conveyor BC conveys the meat ME to the cutting device 250 under the control of the control device 210.

[0149] (Step S2-3)

[0150] The sensor SEN detects the situation where the meat ME is conveyed to a predetermined position on the belt conveyor BC under the control of the control device 210.

[0151] (Step S3-3)

[0152] The sensor SEN outputs detection notification information to the control device 210.

[0153] (Step S4-3)

[0154] In the control device 210, the communication unit 212 receives the detection notification information sent by the sensor SEN. The acquisition unit 214 acquires the detection notification information received by the communication unit 212. The control unit 216 acquires the detection notification information from the acquisition unit 214 and generates a measurement start trigger based on the acquired detection notification information.

[0155] (Step S5-3)

[0156] In the control device 210, the control unit 216 sends the generated measurement start trigger from the communication unit 212 to the information processing device 110b and the light source 101.

[0157] (Step S6-3)

[0158] In the measurement system 100b, the light source 101 emits first light according to the received measurement start trigger. The first light emitted by the light source 101 is input to the light projection optical fiber 102. The light projection optical fiber 102 irradiates the fat layer FL portion of the meat ME to be measured with the first light input from the light source 101.

[0159] In the information processing device 110b, the communication unit 113b receives the measurement start trigger sent by the control device 210. The absorbance derivation unit 112 acquires the measurement start trigger received by the communication unit 113b and starts the measurement based on the acquired measurement start trigger.

[0160] (Step S7-3)

[0161] The light receiving optical fiber 103 receives second light that is affected by at least one of diffusion, absorption, and reflection inside the meat ME to be measured.

[0162] (Step S8-3)

[0163] The second light received by the light receiving optical fiber 103 is output to the spectroscope 104. The spectroscope 104 measures the absorbance by splitting the second light output from the light receiving optical fiber 103 for each wavelength and receiving it with a detector. The spectroscope 104 generates a spectral spectrum by deriving the relationship between the wavelength of the second light and the absorbance.

[0164] (Step S9-3)

[0165] In the information processing device 110b, the absorbance derivation unit 112 acquires the spectral spectrum from the spectroscope 104. The absorbance derivation unit 112 derives the fat absorbance near the absorption wavelength of the fat based on the acquired spectral spectrum.

[0166] (Step S10-3)

[0167] In the information processing device 110b, the fat layer thickness derivation unit 114 acquires the information indicating the fat absorbance from the absorbance derivation unit 112. The fat layer thickness derivation unit 114 derives the thickness (measured thickness) of the fat layer FL portion of the meat ME based on the calibration model 114a and the acquired information indicating the fat absorbance.

[0168] (Step S11-3)

[0169] In the information processing device 110b, the output unit 116 acquires the information indicating the thickness (measured thickness) of the fat layer FL portion of the meat ME from the fat layer thickness derivation unit 114, and generates thickness information based on the acquired information indicating the thickness (measured thickness) of the fat layer FL portion of the meat ME.

[0170] (Step S12-3)

[0171] In the information processing device 110b, the output unit 116 transmits the generated thickness information from the communication unit 113b to the control device 210.

[0172] (Step S13-3)

[0173] In the control device 210, the communication unit 212 receives the thickness information transmitted by the information processing device 110b. The acquisition unit 214 acquires the thickness information received by the communication unit 212. The control unit 216 acquires the thickness information from the acquisition unit 214. The control unit 216 generates control information based on the acquired thickness information, and the control information includes information indicating the thickness of the fat layer FL separated from the meat ME.

[0174] (Step S14-3)

[0175] In the control device 210, the control unit 216 outputs the generated control information from the communication unit 212 to the cutting device 250.

[0176] (Step S15-3)

[0177] The cutting device 250 acquires the control information output by the control device 210. The cutting device 250 determines the thickness of the fat layer FL separated from the meat ME based on the information indicating the thickness (measured thickness) of the fat layer FL separated from the meat ME included in the acquired control information.

[0178] (Step S16-3)

[0179] The cutting device 250 cuts the meat ME by performing control based on the thickness of the fat layer FL separated from the meat ME determined in step S15-3, thereby separating the meat ME into the fat layer FL and the lean meat RM.

[0180] After that, the processing from step S1-3 to step S16-3 is continued.

[0181] In the modification 2 of the foregoing embodiment, the measurement system 100b may include an input unit 119a and a creation unit 120a. By configuring in this way, a calibration model 114a can be created in the measurement system 100b.

[0182] In the modification 2 of the foregoing embodiment, as Figure 9 shown, the case where the first light emitted from the light source 101 onto the workpiece is irradiated onto the fat layer FL of the meat ME as the measurement object to measure the thickness (measured thickness) of the fat layer FL of the meat ME has been described, but it is not limited to this example. For example, the first light emitted from the lower surface of the workpiece by the light source 101 may also be irradiated onto the fat layer FL of the meat ME as the measurement object.

[0183] (Modification Example 3 of the Embodiment)

[0184] Figure 12 This is a diagram showing another example of the meat cutting system 200 according to Modification Example 3 of the embodiment. In Figure 12 , (1) shows the case of measuring the thickness (measurement thickness) of the fat layer FL from the workpiece (side surface) as shown in Figure 9 . (2) is the position where the meat ME to be measured is transferred from the belt conveyor BC01 to the belt conveyor BC02. At this position, the measurement system 100b can also irradiate the first light emitted by the light source 101 from the lower surface of the workpiece to the fat layer FL of the meat ME to measure the thickness (measurement thickness) of the fat layer FL of the meat ME. In this case, since the fat surface is the lower surface, the measurement system 100b can measure the thickness (measurement thickness) of the fat layer FL with the optical fiber set at a fixed position. (3) shows the case of measuring the thickness (measurement thickness) of the fat layer FL from below the belt conveyor BC02. In this case, in the belt conveyor BC02, a light-transmissive belt can also be used to irradiate the first light emitted by the light source 101 from the lower surface of the workpiece to the fat layer FL of the meat ME, and measure the thickness (measurement thickness) of the fat layer FL of the meat ME. In the belt conveyor BC02, the first light emitted by the light source 101 from the lower surface of the workpiece can also be irradiated to the fat layer FL of the meat ME through the gap of the roller conveyor, and measure the thickness (measurement thickness) of the fat layer FL of the meat ME.

[0185] In the aforementioned Modification Example 3 of the embodiment, as an example, the case where the light source 101 receives the measurement start trigger sent by the control device 210 and emits light based on the received measurement start trigger has been described, but it is not limited to this example. For example, the light source 101 can always emit light regardless of the measurement start trigger sent by the control device 210.

[0186] For the meat cutting system 200 according to Modification Example 3 of the embodiment, the meat cutting system 200 includes: an acquisition unit 214 that acquires information indicating the thickness (measured thickness) of the fat layer FL of the meat ME derived by the measurement system 100b; and a control unit 216 that controls the separation of the meat ME into the fat layer FL and the lean meat RM. The control unit 216 determines the thickness of the fat layer FL separated from the meat ME based on the information indicating the thickness (measured thickness) of the fat layer FL of the meat ME acquired by the acquisition unit 214. Therefore, the fat layer FL can be separated from the meat ME according to the thickness of the fat layer FL of the meat ME derived by the measurement system 100b. That is, when the thickness of the fat layer FL of the meat ME conveyed on the belt conveyor BC changes in the conveying direction of the meat ME, the measurement system 100b measures the thickness (measured thickness) of the fat layer FL of the meat ME that changes in the conveying direction. Through the control corresponding to the change in the thickness (measured thickness) of the fat layer FL of the meat ME measured in this way by the control unit 216, the cutting device 250 can separate the fat layer FL from the meat ME.

[0187] The effect of the meat cutting system according to Modification Example 3 of the embodiment will be described. Figure 13A An example of removing the fat layer FL by a conventional meat cutting system is shown. According to Figure 13A , the thickness TH01 of the fat layer FL is measured from the side of the meat ME, and based on the measured thickness TH01 of the fat layer FL, the meat ME is separated into the fat layer FL and the lean meat RM. Therefore, when the thickness of the fat layer FL changes in the conveying direction, it is impossible to follow this change for processing. For example, if the thickness of the fat layer FL increases in the conveying direction, a part of the fat layer FL will remain on the lean meat RM, and if the thickness of the fat layer FL decreases in the conveying direction, a part of the lean meat RM will remain on the fat layer FL.

[0188] Figure 13B An example of removing the fat layer FL by the meat cutting system 200 according to Variant Example 3 of the embodiment is shown. According to Figure 13B , in addition to the thickness TH01 of the fat layer FL on the side of the meat ME, the thicknesses TH02 to TH0n (n is an integer satisfying n > 1) of the fat layer FL at a plurality of positions inside the meat ME are also measured. At the thicknesses TH01 to TH0n (measured thicknesses) of the fat layer FL measured, the meat ME is separated into the fat layer FL and the lean meat RM. That is, the control unit 216 controls the cutting device 250 so that the meat ME is separated into the fat layer FL and the lean meat RM according to the thicknesses TH01 to TH0n (measured thicknesses) of the fat layer FL measured. In Figure 13BIn an example of removing the fat layer FL using the meat cutting system 200 shown, when the thickness of the fat layer FL changes in the conveying direction, the thickness of the fat layer FL can be measured following the change. Therefore, when the thickness of the fat layer FL increases in the conveying direction, a part of the fat layer FL does not remain on the lean meat RM, and when the thickness of the fat layer FL decreases in the conveying direction, a part of the lean meat RM does not remain on the fat layer FL, so that the fat layer FL and the lean meat RM can be separated. In addition, as described above, the number of light receiving optical fibers 103 included in the measurement system 100b of the meat cutting system 200 can be one or more. In the structure where the measurement system 100b of the meat cutting system 200 has one light receiving optical fiber 103, it is possible to continuously measure the thickness of the fat layer FL at different positions of the meat ME along the conveying direction of the meat ME using one light receiving optical fiber 103, and perform the measurement of the thicknesses TH02 to TH0n (n is an integer satisfying n>1) (measured thickness) of multiple parts of the fat layer FL inside the meat ME. In addition, in the structure where the measurement system 100b of the meat cutting system 200 has multiple light receiving optical fibers 103, it is possible to simultaneously perform the measurement of the thicknesses TH02 to TH0n (n is an integer satisfying n>1) (measured thickness) of multiple parts of the fat layer FL inside the meat ME. For example, as Figure 12 shown, for the meat ME conveyed on the belt conveyor, the measurement system 100b of the meat cutting system 200 having one or more light receiving optical fibers 103 can be used to measure the thicknesses TH02 to TH0n (n is an integer satisfying n>1) (measured thickness) of multiple parts of the fat layer FL inside the meat ME.

[0189] <Configuration example>

[0190] As a configuration example, the measurement system includes: a light source; a light projecting optical fiber for irradiating a first light from the light source to the fat layer portion of the meat as the measurement object; a light receiving optical fiber disposed separately from the light projecting optical fiber for receiving a second light output from the fat layer portion of the meat when the first light is irradiated to the fat layer portion of the meat; and a fat layer thickness deriving unit for deriving the thickness of the fat layer portion of the meat (i.e., the measured thickness) based on a calibration model and the absorbance of the second light near the absorption wavelength of the fat. The calibration model is information obtained by correlating the thickness of the fat layer portion of the reference meat (i.e., the reference thickness) with the absorbance of the light output from the fat layer portion of the reference meat when the light emitted from the light source is irradiated to the fat layer portion of the reference meat near the absorption wavelength of the fat.

[0191] As a configuration example, it further includes: a spectroscope that generates a spectral spectrum of the second light; and an absorbance derivation unit that derives an absorbance near the absorption wavelength of fat based on the spectral spectrum of the second light generated by the spectroscope, wherein the fat layer thickness derivation unit derives a measured thickness based on the absorbance derived by the absorbance derivation unit and a calibration model.

[0192] As a configuration example, the absorbance derivation unit performs either or both of baseline correction and smoothing on the spectral spectrum of the second light, and derives an absorbance near the absorption wavelength of fat based on the spectral spectrum of the second light that has undergone either or both of baseline correction and smoothing.

[0193] As a configuration example, it further includes a creation unit that creates a calibration model.

[0194] As a configuration example, when the spectroscope irradiates light onto each part of the fat layer portions of a plurality of reference meats with different fat layer thicknesses respectively, it generates a spectral spectrum of the light output from the fat layer portions of the plurality of reference meats. The absorbance derivation unit obtains an absorbance near the absorption wavelength of fat based on the spectral spectrum of the light generated by the spectroscope. The creation unit creates a calibration model by deriving the relationship between the absorbance and the reference thicknesses of the plurality of reference meats corresponding to the spectral spectrum of the light used when obtaining the absorbance.

[0195] As a configuration example, the absorbance derivation unit performs either or both of baseline correction and smoothing on the spectral spectrum of the light, and obtains an absorbance near the absorption wavelength of fat based on the spectral spectrum of the light that has undergone either or both of baseline correction and smoothing.

[0196] As a configuration example, it is a meat cutting system, including: an acquisition unit that acquires information indicating the fat layer thickness of meat derived by a measurement system; and a control unit that controls the separation of meat into a fat layer and lean meat. The control unit determines the thickness of the fat layer separated from the meat based on the information indicating the thickness of the fat layer of the meat acquired by the acquisition unit. Even when the offset amount of the remaining fat layer has been determined, the cutting position can be calculated and executed.

[0197] Above, although the embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the present invention. These embodiments can be implemented in various other ways, and various omissions, substitutions, changes, and combinations can be made without departing from the spirit of the present invention. These embodiments and their variants are included within the scope and gist of the invention, and at the same time are included within the scope of the invention described in the claims and its equivalents.

[0198] In addition, the aforementioned measurement systems 100, 100a, 100b, and the control device 210 have a computer inside. Moreover, the processes of the respective processes of the aforementioned devices are stored in a computer-readable recording medium in the form of a program, and the above processes are performed by the computer reading and executing this program. Here, the so-called computer-readable recording medium refers to a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, and the like. In addition, the computer program can also be distributed to the computer via a communication line, and the computer that has received this distribution executes this program.

[0199] In addition, the above program can also be a program for implementing a part of the aforementioned functions.

[0200] Furthermore, it can also be a program that can implement the aforementioned functions through a combination with a program already recorded in the computer system, that is, a so-called differential file (differential program).

[0201] Explanation of Reference Numerals

[0202] 100, 100a, 100b... Measurement systems;

[0203] 101... Light source;

[0204] 102... Optical fiber for light projection;

[0205] 103... Optical fiber for light reception;

[0206] 104... Spectrometer;

[0207] 110, 110a, 110b... Information processing devices;

[0208] 112... Absorbance derivation unit;

[0209] 113b... Communication unit;

[0210] 114... Subcutaneous fat layer thickness derivation unit;

[0211] 114a... Calibration model;

[0212] 116... Output unit;

[0213] 118... Storage unit;

[0214] 119a... Input unit;

[0215] 120a... Creation unit;

[0216] 200... Meat cutting system;

[0217] 210... Control device;

[0218] 212... Communication unit;

[0219] 214... Acquisition unit;

[0220] 216... Control unit;

[0221] 250... Cutting device.

Claims

1. A measurement system, wherein, comprising: a light source; a light-projecting optical fiber that irradiates a first light from the light source onto a fat layer portion of meat as a measurement object; a light-receiving optical fiber that is provided separately from the light-projecting optical fiber and receives a second light output from the fat layer portion of the meat when the first light is irradiated onto the fat layer portion of the meat; a fat layer thickness derivation unit that derives a measurement thickness, which is the thickness of the fat layer portion of the meat, based on a calibration model and an absorbance of the second light near an absorption wavelength of fat; wherein the calibration model is information obtained by correlating a reference thickness, which is the thickness of a fat layer portion of reference meat, with an absorbance of light output from the fat layer portion of the reference meat near an absorption wavelength of fat when the light emitted from the light source is irradiated onto the fat layer portion of the reference meat.

2. The measurement system according to claim 1, wherein, further comprising: a spectroscope that generates a spectroscopic spectrum of the second light; and an absorbance derivation unit that derives an absorbance near an absorption wavelength of fat based on the spectroscopic spectrum of the second light generated by the spectroscope, wherein the fat layer thickness derivation unit derives the measurement thickness based on the absorbance derived by the absorbance derivation unit and the calibration model.

3. The measurement system according to claim 2, wherein, the absorbance derivation unit performs either or both of baseline correction and smoothing on the spectroscopic spectrum of the second light, and derives an absorbance near an absorption wavelength of fat based on the spectroscopic spectrum of the second light that has undergone either or both of baseline correction and smoothing.

4. The measurement system according to claim 2, wherein, further comprising: a creation unit that creates the calibration model.

5. The measurement system according to claim 4, wherein, the spectroscope generates a spectroscopic spectrum, which is a spectroscopic spectrum of light output from the fat layer portions of a plurality of pieces of reference meat having different fat layer thicknesses when the light is irradiated onto the fat layer portions of the plurality of pieces of reference meat, the absorbance derivation unit obtains an absorbance near an absorption wavelength of fat based on the spectroscopic spectrum of the light generated by the spectroscope, and the creation unit creates the calibration model by deriving a relationship between the absorbance and the reference thicknesses of the plurality of pieces of reference meat, the reference thicknesses corresponding to the spectroscopic spectrum of the light used to obtain the absorbance.

6. The measurement system according to claim 5, wherein, the absorbance derivation unit performs either or both of baseline correction and smoothing on the spectroscopic spectrum of the light, and obtains an absorbance near an absorption wavelength of fat based on the spectroscopic spectrum of the light that has undergone either or both of baseline correction and smoothing.

7. The measurement system according to claim 1, wherein, the vicinity of the absorption wavelength of fat of the second light is from 800 nm to 1100 nm.

8. A meat cutting system, wherein, Comprising: An acquisition unit that acquires information indicating the thickness of the fat layer of meat derived from the measurement system according to any one of claims 1 to 7; And A control unit that performs control to separate the meat into a fat layer and lean meat, wherein the control unit determines the thickness of the fat layer separated from the meat based on the information indicating the thickness of the fat layer of the meat acquired by the acquisition unit.

9. A measurement method, which is a measurement method executed by a measurement system, the measurement system Comprising: A light source; A light-projecting optical fiber that irradiates a first light from the light source onto the fat layer portion of the meat to be measured; And A light-receiving optical fiber that is arranged separately from the light-projecting optical fiber and receives a second light output from the fat layer portion of the meat when the fat layer portion of the meat is irradiated with the first light, The measurement method includes the following steps: Irradiating a first light from the light source onto the fat layer portion of the meat; Receiving the second light output from the fat layer portion of the meat; Deriving a measurement thickness based on a calibration model and the absorbance of the second light near the absorption wavelength of fat, the measurement thickness being the thickness of the fat layer portion of the meat to be measured, wherein the calibration model is information obtained by correlating the reference thickness of the fat layer portion of the reference meat with the absorbance of the light output from the fat layer portion of the reference meat near the absorption wavelength of fat when the light emitted by the light source is irradiated onto the fat layer portion of the reference meat.

10. A program that causes a computer of a measurement system to execute the following steps, the measurement system Comprising: A light source; A light-projecting optical fiber that irradiates a first light from the light source onto the fat layer portion of the meat to be measured; And A light-receiving optical fiber that is arranged separately from the light-projecting optical fiber and is used to receive a second light output from the fat layer portion of the meat when the fat layer portion of the meat is irradiated with the first light, The steps include: Irradiating a first light from the light source onto the fat layer portion of the meat; Receiving the second light output from the fat layer portion of the meat; Deriving a measurement thickness based on a calibration model and the absorbance of the second light near the absorption wavelength of fat, the measurement thickness being the thickness of the fat layer portion of the meat to be measured, wherein the calibration model is information obtained by correlating the reference thickness of the fat layer portion of the reference meat with the absorbance of the light output from the fat layer portion of the reference meat near the absorption wavelength of fat when the light emitted by the light source is irradiated onto the fat layer portion of the reference meat.

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