JPH0712722A - Method of judging food processing condition - Google Patents

Abstract

PURPOSE:To judge whether or not a stuff fed into a food processing device is suitable for food-processing and whether or not the food-processing is appropriate, by finding the stuff and the ingredients of food processed by the food processing device by means of near infrared analysis. CONSTITUTION:A part of polished rice is fed, as a sample, into a near infrared analyzer 15 during a process of washing and soaking the rice, and is therefore analyzed so as to obtain spectral data. Meanwhile, a part of cooked rice is sampled during dishing up the cooked rice as a food product, and is then fed to a near infrared analyzer 17 for analyzing it for obtaining spectral data. The results obtained by the analyzers 15, 17 are compared and displayed. That is, a computer 16 computes rates of ingredients from the spectral data obtained from the polished rice as a stuff so as to obtain a quality evaluation value alphaof the polished rice. Similarly, a computer 18 computes rate of the ingredints of the cooked rice from the spectral data of the cooked rice so as to obtain a quality evaluation value beta. Further, rates of the evaluation values are obtained, and then whether or not the evaluation values fall in predetermined ranges is indicated.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a food processing state determination method, and can be used, for example, when determining the state of polished rice before cooking rice and cooked rice after cooking rice.

[0002]

2. Description of the Related Art It is known to judge the quality of rice, for example, to measure the taste value by analyzing each component before and after cooking the rice. However, it is not attempted to judge the state before food material and the state after processing on the same scale, and it is not always accurate. In other words, the conventional taste measurement aims to cook the raw white rice and eat it as cooked rice, and evaluates the taste when cooked under appropriate rice cooking conditions. Therefore, for example, even if the cooked rice is evaluated as the best, the cooked rice may be evaluated poorly due to insufficient cooking conditions.

[0003]

The present invention is intended to determine abnormalities in rice cooking conditions, for example, by comparing the above-mentioned evaluation with polished rice and evaluation with cooked rice. The components of the processed product processed by the food processing device are obtained by near-infrared analysis, and the quality evaluation values α and β are calculated from the component values before and after processing, and these are compared to determine the suitability of the processed state. It is a feature.

[0004]

The effects of the present invention are obtained by analyzing the components of raw materials and processed products before food processing with a near infrared analyzer to obtain quality evaluation values α and β and compare them. Therefore, whether or not it is a raw material suitable for food processing, it is possible to determine the processing appropriateness,
It is possible to grasp the variation state due to processing, and it becomes easy to determine the appropriateness of processing or the determination of the processing method, which conventionally requires skill.

[0005]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described with reference to the drawings. FIG. 1 shows an outline of an apparatus in a rice processing plant, which includes a plurality of storage tanks 1, 1, ..., A weighing machine 2, a dipping tank 3,
3, steam-boiled rice cooker 4, cooked rice cooler 5, arranging device 6, and transport elevators 7, 8 and conveyors 9, 10, 11, 12 and the like that connect them.

Of these, the storage tanks 1, 1 ... Have a structure capable of storing raw rice grains of different varieties, and the required amount is measured via the conveyor 9 and the elevator 8 in response to a conveyance command signal from the control unit outside the drawing. This is the configuration that is supplied to the machine 2. A rice washing machine 13 is provided below the weighing machine 2.
Is provided in the form of a water tank having an agitation mechanism inside, and the washing water is supplied to the immersion tanks 3, 3 of the next stage via the hydraulic pipes 14, 14.

A part of the white rice discharged from the weighing machine 2 is supplied to the near infrared analysis device 15. A computer 16 processes the analysis data. The immersion tanks 3, 3
The rice inside is supplied to the steam-type rice cooker 4 via the conveyor 10. In the steam-type rice cooker 4, rice is cooked by being subjected to primary steaming with steam, expansion and softening in a hot water tank, and secondary steaming while thin-layered rice is continuously transferred by a conveyor outside the drawing. Is.

The conveyor 11 is looked into the outlet of the rice cooker 4 so that cooked cooked rice can be transferred and supplied to the cooked rice cooler 5, and while passing through the inside of the cooler 5, it is exposed to cold air to reach a predetermined temperature or lower. The structure is cooled. The arranging device 6 is connected to the outlet side of the cooling device 5 and the product is placed on the conveyor 12 and transferred. In addition,
A near infrared analysis device 17 for receiving a part of cooked rice is connected to the arranging device 6, and a computer 18 for processing the analysis data is also provided.

The near-infrared analyzers 15 and 17 are generally constructed as follows. That is, a sample such as rice is irradiated with near-infrared rays by continuously changing the wavelength, and the transmitted light or reflected light of this rice sample is detected. The light source 19 and the reflecting mirror 2 are used.
0, a diffraction grating 22 driven by a diffraction grating driving motor 21, a cell holder 23 ′ for mounting a sample cell 23 filled with a sample, a transmitted light sensor 24 for detecting transmitted light of the sample, and reflected light from the sample. And a reflected light sensor 25 for detecting

The transmitted light sensor 24 and the reflected light sensor 25 described above.
Is the spectrum data storage unit 26, the chemical component storage unit 2
7. Computer 16, 1 comprising a calibration curve creation unit 28, etc.
8 control units. Of these, the calibration curve creation unit 1
2 is created in a predetermined manner by analyzing the detection data of the reflected light or transmitted light amount of a specific wavelength based on a known chemical component. For unknown samples such as white rice discharged from the weighing machine 2 and rice cooked from the arranging device 6, the chemical component values thereof are calculated based on the calibration curve. The sample is manually packed in the sample cell and manually loaded into the holder 23 ', or each sample is automatically loaded by receiving each sample from an automatic sampling device (not shown).

The operation of the above example will be described. When the type and amount of raw white rice necessary for cooking rice is specified by the main operation panel outside the drawing, the discharge port of the corresponding storage tank 1 is opened and transferred to the weighing machine 2. Here, when the specified amount is reached, the supply from the storage tank 1 is stopped. The white rice in the weighing machine 2 is then the rice washing machine 13
The rice is supplied to and washed with rice, reaches the dipping tanks 3 and 3, and is dipped for a predetermined time.

During this washing and soaking process, part of the white rice is supplied as a sample to the near-infrared analyzer 15 to analyze the spectrum data. After soaking for a predetermined time, the raw white rice is put into the steam-type rice cooker 4 to cook rice. Next, the cooked cooked rice is cooled to a predetermined temperature or lower while passing through the cooling device 5, reaches the arranging device, is arranged in a container in a predetermined amount, and is delivered from the product conveyor 12.

On the other hand, part of the cooked rice is sampled in the process of serving as a product and supplied to the near-infrared analysis device 17 to analyze the spectrum data. The detection results of the near-infrared analyzer 15 and the analyzer 17 will be compared and displayed as follows. That is, the computer 16 calculates the component ratio of white rice from the spectrum data of the raw white rice. In addition, the quality evaluation value α of white rice is calculated from the ratio of predetermined components or the complex. Here, the quality evaluation value includes, for example, whether or not the white rice is suitable for processing according to the application such as curry, pilaf, sushi rice, porridge, and the appropriate evaluation value. Similarly, the computer 18 calculates the ingredient ratio of cooked rice from the spectrum data of cooked rice, and similarly calculates the quality evaluation value β. The ratio γ of these evaluation values α and β is calculated, and the ratio γ is set to a preset value δ ₁ , δ ₂ (δ
Compared with ₁ <δ ₂ ), it displays whether or not the quality evaluation value is within a predetermined value range. For example, regarding the suitability of porridge, 90 points of rice suitable for porridge are cooked, and the liquid portion is analyzed by a near-infrared analyzer to determine the quality of porridge. Here, if the result is 70 points, it is intended to determine that the rice-cooking conditions for porridge are poor.

If the ratio γ of the quality evaluation values α and β is within a predetermined value, it is presumed that each of the dipping, cooking, and cooling processes corresponding to the quality capability of the raw white rice has been performed. If it is outside the specified range, it is judged that the processing is not proper, or that the processing method requires some treatment.
Such a judgment can be made more easily and easily than in the past where the expert's sensory evaluation was used. Although the comparison is made using the ratio γ of the quality evaluation values α and β, it may be determined whether or not the difference between the two is a predetermined value.

In the above embodiment, the rice processing apparatus is used as the food processing apparatus, but other configurations may be used. Regarding the near-infrared analyzers 15 and 17, the glass of the sample cell 23 has a variation in the transmittance, and the cell glass is susceptible to scratches and stains when the glass is polished over time. The transmittance also changes, so the measured value changes and is likely to cause an error, but the difference spectrum of the absorbance spectrum of the sample cell glass that is the reference and the absorbance spectrum of the sample cell glass prepared for use The difference spectrum of the sample cell glass used for the measured data and the measured data may be added to correct the analysis value. At this time, when measuring the reference spectrum, reference measurement is performed using a material of a high reflector such as a ceramic plate (FIG. 5).

The noise generated during the measurement is removed by the following processing. In other words, it is costly to prevent transient noise that suddenly occurs due to power supply noise or changes in outside air humidity, but it is costly. Therefore, the same sample was scanned multiple times. Divide the data into multiple groups of data,
When the measured value difference between the divided data groups is not within a predetermined range, the data is removed (FIG. 6). That is, normal reference data is scanned, for example, 32 times, and this is repeated twice for A and B to obtain the average R ₀ , and then C and D 2 times for the sample in the sample cell 23 by the same process. The average value R ₁ is calculated (FIG. 7A). In this way, the absorbance (OD) is obtained as OD = log (R ₀ / R ₁ ), and this completes one measurement, but in this procedure, the number of scanning is reduced to about 5 and the It is intended to compare the values of A to B and C to D within the specified range as a mixed data group (FIG. 7).
(B)). It should be noted that the form in which only the display is performed may be used.

Further, after the power is turned on, noise is measured as an analyzer within a specified time, and the time elapses from the time when the power is turned on among environmental factor noise (noise due to outside air temperature, outside air humidity, sensor deterioration, temperature, etc.). Stabilization detection by
A READY signal indicating that the data is reliable, that is, a display or sound indicating that the measurement may be started may be output (FIG. 8). In addition, such noise measurement within the specified time period makes it possible to detect in advance a temporal change in device noise (noise due to the noise generation condition of the device itself).

Next, a method of detecting abnormal data of measurement data or an abnormality diagnosis will be described. Generally, in component analysis by a near infrared analyzer, for example, the upper limit value and the lower limit value ratio that are likely to be contained in the substance in the protein content are set in advance, and the outside of the range is determined as abnormal data. However, in such a determination method, as long as it is within the upper and lower limit range, it is determined as an error in measurement and is not regarded as abnormal value data. It is inevitable to rely on the intuition of the operator to determine whether or not a difference has occurred due to the influence of spectral noise.

Therefore, when the absorbance is measured a plurality of times and the average value thereof is obtained, the i-th absorbance and the preceding (i-
1) The spectral noise evaluation index is calculated from the difference spectrum Sn (FIG. 9) of the first absorbance, and it is determined whether or not the noise evaluation index is abnormal data depending on whether the noise evaluation index is at a specified level,
A warning is issued if necessary (FIG. 10). Here, as the noise evaluation index, for example, the measurement wavelength interval is 2 nm.
The root mean square of the _n differential absorbances d _{1 to} dn existing for each is obtained, and the square root thereof is defined as RMS noise (S _RMS ).
That is, S _RMS ² = (d ₁ ² + d ₂ ² + ... + d _n ² ) / n. When the spectral noise obtained in this way deviates from the specified level, it is known to be an abnormal value, and re-measurement can be prompted immediately at the time of measurement, or re-measurement can be performed many times. If an abnormal value appears, it is determined that the noise is not instantaneous or transient noise, and the equipment needs to be adjusted. Since the abnormal value can be removed in this way, the accuracy can be improved.

The above-mentioned noise index calculation standard uses the difference between the absorbance data of the previous time and this time, but the average absorbance from the (im) to the (i-1) th and the absorbance of the i-th time this time are used. You may ask by and. Also, the absorbance data is
When the reference measurement of the ceramic plate or the like and the measurement of the sample data are repeated, the spectral noise index may be calculated for each data of the same type, or the spectral noise index may be calculated by comparing the mixed data.

Further, the level of the spectral noise is divided into N levels in advance, and the number of times of scanning required for one measurement is changed or the number of times of measurement is changed based on the set level. The accuracy of the calibration curve can be stably maintained even when the noise is close to the device limit (FIGS. 11 to 12). Next, the abnormality diagnosis system will be described.

Up to now, there was a function of judging whether the noise level is higher or lower than usual, but there is no technique for investigating the cause. Therefore, when noise generation is detected, at least the amplifier output voltage, the power supply voltage, and the noise generation pattern are checked to determine the cause of noise generation (FIG. 13). To give an example, (a) “=
If "0, = 1", there is an abnormality in the detector system such as the sensor or amplifier. (B) = 1, = 1, = 1, = 1,
If = 0 and = 1, the amplifier is abnormal. (C) =
If 0, = 0, = 1, noise is generated due to outside air humidity. If (d) = 1, = 0, = 0, power supply noise is present. If (e) = 1, = 6, = 0, the motor is abnormal. In addition, if it is randomly generated over each wavelength of the electrical system, it is judged as power noise, if it occurs frequently in a specific wavelength range, it is judged as noise due to outside humidity, and it is generated at both ends of the scan wavelength range. If so, it is determined that the cause is inside the device.

[Brief description of drawings]

FIG. 1 is a flowchart.

FIG. 2 is an explanatory diagram of an apparatus outline.

FIG. 3 is a schematic explanatory view of a near infrared analysis device.

FIG. 4 is a block diagram.

FIG. 5 is a flowchart.

FIG. 6 is a flowchart.

FIG. 7 is a conceptual diagram of measurement.

FIG. 8 is a flowchart.

FIG. 9 is a schematic explanatory diagram of absorbance data processing.

FIG. 10 is a flowchart.

FIG. 11 is a time-RMS noise level generation status explanatory diagram.

FIG. 12 is a flowchart.

FIG. 13 is a flow chart of noise or more diagnosis.

[Explanation of symbols]

1,1 Storage tank 2 Weighing machine 3,3 Immersion tank 4 Steam-type rice cooker 5 Cooked rice cooler 6 Arrangement device 7,8 Conveyor elevator 7,8 9,10,11,12 Conveyor 13 Rice washing machine 14,14 Hydraulic pipe 15 Near infrared analysis device 16 Computer 17 Near infrared analysis device 18 Computer 19 Light source 20 Reflector 21 Diffraction grating drive motor 22 Diffraction grating 23 Sample cell 24 Transmitted light sensor 25 Reflected light sensor 26 Spectral data storage unit 27 Chemical component storage unit 28 Calibration curve creation section

Claims (1)

[Claims] 1. A raw material supplied to a food processing apparatus and a component of a processed product processed by the food processing apparatus are obtained by near infrared analysis, and a quality evaluation value α,
A method for determining a food processing state, which comprises calculating β and comparing these to determine whether or not the processing state is appropriate.