JP2000105194A - Device for evaluating taste of farm produce and device for evaluating processing characteristic of farm produce - Google Patents

Abstract

PROBLEM TO BE SOLVED: To eliminate the influence of the degree of deterioration of farm produce that becomes the unstable element of taste and processing characteristic evaluation by determining the conversion coefficient of the taste and processing characteristic evaluation, and by evaluating the test and processing characteristics while limiting to the farm produce where the degree of deterioration is within a specific value. SOLUTION: In a spectral characteristic treatment means 201, the constituent of a sample is measured, and a chemical characteristic value is stored into a storage means 204. A taste evaluation conformity judgment means 202 reads the chemical characteristic value for indicating the degree of deterioration of the sample, and judges whether the sample conforms to taste evaluation or not. A taste evaluation means 203 calculates a taste evaluation value according to the chemical characteristic value and a taste relation expression. In addition to the taste evaluation means, a processing characteristic evaluation value may be calculated by a processing characteristic evaluation means.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus for irradiating visible light or near-infrared light to agricultural products such as cereals and beans to evaluate taste and processing characteristics based on their spectral characteristics. For example, as an optical taste evaluation device for agricultural products or an evaluation device for processing characteristics of agricultural products, a taste evaluation value of agricultural products obtained in advance by a sensory function and a plurality of predetermined wavelengths when the agricultural products are irradiated with visible light or near-infrared light. Determine the conversion factor of the taste evaluation from the correlation with the absorbance in, and directly obtain the taste evaluation value from the absorbance at a predetermined wavelength obtained by irradiating the test sample with visible light or near-infrared light, A conversion factor for taste evaluation is determined from the correlation between the taste evaluation value of agricultural products obtained in advance by sensory function and the content of a plurality of predetermined components that affect the taste of rice such as protein, fatty acids, and amylose, and the conversion factor and the test sample are determined. Is irradiated with visible light or near-infrared light to detect the absorbance at a wavelength corresponding to a predetermined component, and the absorbance is calculated from the absorbance and a predetermined calibration curve. Calculates a taste evaluation value is known from the content of the component.

[0002]

Agricultural products, such as old rice, which have a high degree of deterioration in freshness, such as fat, are converted into free fatty acids by hydrolysis of the lipids, which combine with starch in the lower part of the bran layer to cause stickiness and poor hardness. Therefore, the more free fatty acids, the worse the taste. Further, the free fatty acids become oxides and emit off-flavors such as old rice odor.

[0003] On the other hand, the taste of agricultural products is determined by sensory characteristics. At the time of sensory test, a certain treatment is performed regardless of whether the agricultural products are new or old, and the appearance, aroma, taste, stickiness,
The taste is evaluated in comparison with the reference agricultural products for hardness, etc., but for agricultural products with a high degree of deterioration, evaluation data is inadequate due to instability of rice bran removal at the time of milling, individual differences among people, especially variability in judgment on odors, etc. Become stable. Therefore, when the test sample is irradiated with visible light or near-infrared light to evaluate the taste of the agricultural product based on its spectral characteristics, the taste evaluation obtained by sensory inspection of the agricultural product with a different degree of deterioration from the test sample is determined. If the conversion coefficient is used, the accuracy is reduced. In the same manner as described above, in the evaluation of processing characteristics related to the chemical components of agricultural products, the accuracy is deteriorated by using a conversion coefficient for processing characteristics evaluation obtained by sensory inspection of agricultural products having a different degree of deterioration from the test sample.

[0004] Therefore, the present invention is to determine the conversion factor of the taste evaluation and processing characteristic evaluation and to evaluate the taste and processing characteristic only for agricultural products whose degree of deterioration is not more than a predetermined value.
The purpose of the present invention is to remove the influence of the degree of deterioration of agricultural products, which is an unstable factor in taste evaluation and processing characteristic evaluation.

[0005]

In order to achieve the above object, the present invention is configured as follows.

That is, according to the first aspect of the present invention, a conversion factor for taste evaluation is determined in advance from the correlation between the sensory evaluation value of agricultural products such as cereals and beans and the spectral characteristics of the agricultural products such as cereals and beans. In the evaluation of the taste of the agricultural product by calculating the taste evaluation value from the spectral characteristics obtained by irradiating the test sample with visible light or near-infrared light, the degree of deterioration is determined by the agricultural product having a degree of deterioration equal to or less than a predetermined value. An agricultural product taste evaluation device comprising a conversion coefficient determining means for determining a conversion coefficient. According to the invention of claim 2, a conversion factor for taste evaluation is determined in advance from the correlation between the sensory evaluation value of agricultural products such as cereals and beans and the spectral characteristics of the agricultural products such as cereals and beans, and this conversion factor and the conversion factor and the visible A taste evaluation value is calculated from spectral characteristics obtained by irradiating light or near-infrared light to evaluate the taste of the agricultural product, wherein a deterioration degree detecting means for detecting the degree of deterioration of the agricultural product; A taste evaluation conformity determining means for determining whether the agricultural product conforms to the taste evaluation based on the degree of deterioration of the agricultural product, wherein the degree of deterioration is evaluated with respect to the agricultural product having a degree of deterioration equal to or less than a predetermined value. It is an evaluation device. According to the invention of claim 3, a conversion coefficient for processing characteristic evaluation is determined in advance from a correlation between the processing characteristic evaluation value of agricultural products such as cereals and beans and the spectral characteristics of the agricultural products such as cereals and beans, and the conversion coefficient and a sample sample are determined. Calculating the processing characteristic evaluation value from the spectral characteristics obtained by irradiating visible light or near-infrared light to evaluate the processing characteristics of the agricultural product, the degree of deterioration is less than a predetermined value of the agricultural product of the processing characteristics evaluation An agricultural product processing characteristic evaluation device comprising a conversion coefficient determining means for determining a conversion coefficient. According to the invention of claim 4, a conversion factor for processing characteristic evaluation is determined in advance from the correlation between the processing characteristic evaluation value of agricultural products such as cereals and beans and the spectral characteristics of the agricultural products such as cereals and beans, and the conversion factor and the test sample are determined. Deterioration degree detecting means for detecting the degree of deterioration of the agricultural product, in which the processing characteristic evaluation value is calculated by calculating the processing characteristic evaluation value from the spectral characteristic obtained by irradiating visible light or near infrared light to the agricultural product, Processing characteristic evaluation conformity determination means for determining whether the agricultural product conforms to the processing characteristic evaluation based on the detected degree of deterioration of the agricultural product, and performing processing characteristic evaluation with the agricultural product having the degree of deterioration equal to or less than a predetermined value. This is a device for evaluating the processing characteristics of agricultural products.

[0007]

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 shows a configuration diagram of a taste evaluation device of the present invention. The taste evaluation device includes a spectroscopic analyzer A and a control processing device B that controls each unit of the spectroscopic analyzer A and performs processing of data obtained from the spectroscopic analyzer A and taste evaluation.

The spectroscopic analyzer A includes a light source 1, a reflecting mirror 2, a diffraction grating 3, a lens 4, a filter wheel 5 for wavelength calibration, a light detector 61 for reflected light, a light detector 62 for transmitted light, and a sample cell 7. , A discharge valve 8, and a reflecting mirror 2, a diffraction grating 3, a lens 4, a wavelength calibration filter wheel 5, a sample cell 7, a reflected light photodetector 61, and a transmitted light photodetector 62, respectively. On the optical path of

The calibration filter is set on the optical path by rotating the drive motor 5a of the wavelength calibration filter wheel 5. In the spectroscopy, the wavelength of the light is changed by rotating the drive motor 3a (stepping motor) of the diffraction grating 3 and continuously switching the angle of the diffraction grating 3 with respect to the optical axis. Sample cell 7
Is configured to be transferred to a measurement position by a sample cell transfer motor (not shown), and to return to a predetermined position after the measurement is completed.

FIG. 2 shows a block diagram of the control processor B.

In FIG. 2, reference numeral 20 denotes a CPU (Central Processing Unit), which performs control processing as described later. CPU 20
Is connected to the light source 3, the diffraction grating drive motor 5, the sample cell transfer motor 22, the transmitted light detector 8, and the reflected light detector 9 via an input / output interface 21. Also, CP
U20 is connected to an input key 24 via an input interface 23 and a display device 26 via an output interface 25. Further, the CPU 20 is connected to a storage device 27 including a ROM for storing a processing procedure described later and a RAM for temporarily storing data.

FIG. 3 shows a processing block diagram of the taste evaluation device. The taste evaluation device firstly includes a spectral characteristic processing unit 201.
In, when the reference plate is set at the measurement position of the spectrometer A and the spectrometer A is operated, the near-infrared ray emitted from the light source 1 reaches the diffraction grating 3 via the reflecting mirror 2,
After being separated here, the light is reflected by the reference plate via the lens 4 and the wavelength calibration filter wheel 5, and the reflected light is detected by the reflected light detector 61. Since the wavelength of the reflected light changes with the rotation of the diffraction grating 3, the reflected light detector 61 continuously detects a signal corresponding to the wavelength. Then, after performing the operation of reading the detection signal (measurement of the reference spectrum) a predetermined number of times, the average of the spectrum is obtained.

Next, the sample cell 7 containing the standard sample whose concentration of the measurement component is known is set at the measurement position by driving a sample cell transfer motor (not shown). Then, when the spectrometer A operates again, the reflected light detector 61 detects the reflected light from the standard sample. Therefore, after measuring the spectrum of the standard sample a predetermined number of times, the average of the measured spectra is obtained, and the absorbance is calculated from the control spectrum and the measured spectrum.

Then, the absorbance is determined for a plurality of standard samples having different concentrations as described above, and a calibration curve at a reference temperature is determined in advance based on the measured absorbance and the known concentration.

Further, with respect to a standard sample whose measurement components are known, for example, respective absorbance spectra at temperatures near 3 degrees Celsius, near 20 degrees Celsius, and near 34 degrees Celsius are determined. Subsequently, when the temperature is 20 degrees Celsius, Based on the absorbance spectrum as a reference, calculate the amount of deviation from the absorbance spectrum when the temperature is 3 degrees Celsius, and calculate the amount of deviation between the absorbance spectrum when the temperature is 34 degrees Celsius and the reference spectrum in advance. deep. And
These calculated shift amounts are stored in the storage device 27 in advance. Then, the sample cell 7 containing the sample rice to be measured is set at the measurement position, and the calibration curve obtained as described above is obtained.
The composition of the sample rice is measured based on the deviation and the amount of shift, and the chemical property values obtained as a result of the measurement are stored in the storage device 27 as the storage unit 204.

Next, in the taste evaluation conformity determination means 202, a chemical property value indicating the degree of deterioration of the sampled rice is read from the storage means 204, and it is determined whether or not the sample rice conforms to the taste evaluation. The degree of deterioration of the sampled rice is determined, for example, from the degree of fatty acid, and brown rice having a concentration of 30 mgKOH / 100 g or less and polished rice having a concentration of 6 mgKOH / 100 g or less are determined to be suitable for taste evaluation. Then, those having a fatty acid degree higher than this are determined to be unsuitable for taste evaluation. The degree of deterioration of the sample rice is
In addition, water-soluble acidity, PH acidity, germination rate, enzyme activity,
The determination may be made based on the bound lipid content, color tone change, skin roughness, and the like. These values can be measured by a physicochemical analyzer or an optical analyzer using near-infrared light.

Next, the taste evaluation means 203 reads the chemical characteristic value of the sampled rice from the storage means 204 and calculates a taste evaluation value from the chemical characteristic value and the conversion coefficient of the taste evaluation. The conversion factor is as follows.
gKOH / 100g or less, 6mgKOH / 10 for polished rice
It is set based on the taste evaluation value of rice obtained by sensory test of rice of 0 g or less. Then, the calculated taste evaluation value is output to the display device 26 and displayed.

Next, an index value different from the taste evaluation value is determined by regression analysis from the absorbance when the rice is irradiated with near-infrared light of a plurality of specific wavelengths, and the predicted value of the obtained index value is determined by sensory taste. A description will be given of a rice taste evaluation method of calculating a comprehensive taste evaluation value by substituting the estimated value into a regression equation.

This taste evaluation method detects the absorbance when irradiating rice with a plurality of near-infrared lights having specific wavelengths necessary for calculating a specific index value (G value) for estimating the taste of rice. I do. Then, a G value is obtained by multiplying the plurality of detected absorbances by a constant for converting into a G value. Next, a rice taste estimation value is calculated using a taste evaluation coefficient for converting the G value to a sensory taste estimation value (taste total evaluation value).

Specifically, the taste of rice is related to magnesium, and if the content of amylose in nitrogen, potassium or starch constituting protein is high, the taste is reduced. Therefore, G = Mg / K / N / Aml. Here, Mg: magnesium (mg / 100 g) K: potassium (mg / 100 g) N: nitrogen (%) Aml: amylose (%) G = k0 + k1 * X1 + k2 * X2 +. + Kn * Xn (1) Here, ki is a constant, and a large number of rice are chemically analyzed to determine a G value, and absorbance at a specific wavelength is measured, and is previously determined by a multiple regression analysis. Next, this G value is converted into a taste estimation value T. T = A * G + B (2) Here, A and B are taste evaluation coefficients, which are constants determined in advance by the correlation between the taste-evaluated overall taste-based evaluation value and the G value. From the above equations (1) and (2), the estimated rice taste is calculated. At this time, magnesium, potassium, nitrogen, and amylose are calculated by independent regression equations, respectively, and displayed on the display device 26 as a multidimensional map. As a result, the relationship between the estimated value of the taste of rice and the contained components is displayed on a map,
You can recognize at a glance the guidelines for improving fertilizer application.

In the above example, the taste estimation value was obtained from the specific index value (G value). However, the conversion of the taste evaluation was performed based on the correlation between the taste evaluation value obtained in advance by the sensory function and the absorbance due to the irradiation of near-infrared light. The coefficient may be determined by the determining means, and the taste evaluation value may be directly obtained from the conversion coefficient and the absorbance at a predetermined wavelength.

Next, an apparatus for evaluating taste based on physicochemical analysis values, which is another pillar of taste evaluation, will be described. This device calculates the physicochemical analysis value from the spectral characteristics obtained by irradiating the rice with near-infrared light, multiplies this value by a specific constant for conversion, and looks, aroma, taste, stickiness, hardness,
One or more total sensory evaluation values (T values) are calculated. The specific constant for the conversion at this time is set based on a sensory evaluation value obtained by performing a sensory test on rice whose degree of deterioration is equal to or less than a predetermined value.

A specific index value (G) for obtaining a sensory evaluation value
The value) is calculated based on at least a plurality of components based on magnesium and potassium and physicochemical analysis values such as a breakdown value, and a combination thereof. In addition,
To obtain the taste, stickiness and overall sensory evaluation value, G = Mg / K G = Mg / K / NG = Mg / K / N / Aml G = Mg * (Mg + K) / K / NG = Mg * P / K / NG = a * Mg + b * K + c * N + d * Aml, etc., and the T value is determined from the G value by the same method as described above. Here, P: phosphorus (mg / 100 g)
It is. When the sensory evaluation value of hardness is obtained, H =
It can be obtained by setting such as 1 / G.

The sensory evaluation value of the fragrance is calculated by multiplying the output of the odor sensor for detecting the fragrance component of rice as a physicochemical analysis value and a specific constant for conversion. The output of the odor sensor increases in accordance with the degree of deterioration of the rice, and when the degree of deterioration exceeds a predetermined value, the sensory evaluation value of the scent varies and is not stable. Therefore, in the sensory evaluation of the fragrance, by limiting the degree of deterioration to rice having a degree of deterioration equal to or less than a predetermined value, the evaluation value is stabilized and the accuracy is improved. Further, in determining the degree of deterioration, it may be determined whether or not the degree of deterioration matches the taste evaluation by using the output of the odor sensor instead of the fatty acid degree described above. In this case, as the deterioration degree detecting means, there are those, such as variety odor sensor configured with C ₆₀ or the like having a semiconductor-type odor sensor or a fullerene molecular structure of detecting the volatile components from the US, near the sample cell the sensor (Not shown), measurement can be performed in parallel with components such as minerals.

The sensory evaluation value of the appearance of rice is calculated by multiplying the output of a whiteness meter or the like as a physicochemical analysis value by a specific constant for conversion. It is known that the appearance evaluation of cooked rice is closely related to the whiteness and color tone of the polished rice before cooking. That is, when rice with low whiteness or rice with a yellow tint is cooked, the sensory evaluation value decreases. In addition, under predetermined rice polishing conditions, the color tone and whiteness of brown rice and rice are deeply related,
For example, rice with a high degree of whiteness of brown rice has a high degree of whiteness after rice polishing and a high sensory evaluation value of the appearance after cooking. However, when the deterioration progresses, the measured values of whiteness and color tone of rice are not stable due to fading or rough surface. For example, brown rice that has deteriorated has significantly roughened skin, and the measured value of whiteness is apparently high, which may be different from the evaluation after rice polishing or rice cooking. Therefore, in the sensory evaluation of the appearance of rice, by limiting the degree of deterioration to rice having a degree of deterioration equal to or less than a predetermined value, the evaluation value is stabilized and the accuracy is improved.

In addition, a viscoelastic characteristic value (balance between stickiness and hardness) of cooked rice measured by a texturometer,
Sensory evaluation of thermal gelatinization characteristic values (characteristic values of maximum viscosity, breakdown, setback, etc.) measured by amyography of milled rice powder, and iodine coloration measured by cooking quality test of cooked rice liquor as physicochemical analysis values Calculate the value.

When the deterioration proceeds, a clear difference appears in the viscoelastic characteristic value in the form that the viscosity decreases and the hardness increases. In addition, the higher the breakdown value, the better the taste of the rice, but if the deterioration progresses, the thermal gelatinization characteristic value, for example, the breakdown value may increase, and the evaluation becomes inappropriate. . Therefore, in the sensory evaluation of rice based on the viscoelastic characteristic value and the thermal gelatinization characteristic value, the evaluation value is stabilized and the accuracy is improved by limiting the degree of deterioration to rice having a predetermined degree or less.

Further, the smaller the value of the iodine coloration of the cooked rice liquid, the more sticky and good-tasting rice is.
When the deterioration proceeds, the degree of iodine coloration of the rice cooking liquid may decrease, and the evaluation becomes inappropriate. Therefore, in the sensory evaluation of rice based on the degree of iodine coloration of the rice cooking liquid, by limiting the degree of deterioration to rice having a degree of deterioration equal to or less than a predetermined value, the evaluation value is stabilized and accuracy is improved.

Although the above description has been made with reference to glutinous rice, the present invention can also be applied to the evaluation of glutinous rice in appearance, fragrance, taste, stiffness, spread, hardness, and overall sensory evaluation. not only that,
The present invention can also be applied to sensory evaluation of foods produced from raw materials such as wheat, barley, coffee beans, and corn. For example,
The present invention can also be applied to sensory evaluation such as color, appearance, hardness, viscoelasticity, smoothness, taste, and overall quality of boiled noodles of flour. When calculating the taste evaluation value of this wheat bread or noodle, G = M
Set as g * N / K. Hereinafter, a method for evaluating the taste of boiled wheat noodles will be described as a representative example thereof. Physicochemical analysis values (G value,
G = Mg * N / K G = Characteristic values of maximum viscosity, breakdown, setback, etc. (amylograph) I = f (L, a, b) (color tone) Next, boiled noodles are manufactured from the sample for which the physicochemical analysis values have been calculated, and the data obtained by conducting a sensory test are converted into color, appearance, hardness, viscoelasticity, smoothness, taste, and overall as a sensory evaluation value T. And a conversion formula from the G value (I value) to the T value is prepared. T = A * G (or I) + B (A and B are constants) Quick and simple by using the above-mentioned conversion formula from G value (I value) by visual and near-red analysis to T value. The sensory taste evaluation value can be obtained. Beans such as soybeans, red beans and coffee beans also have the same effect as rice and wheat. As an example, a conversion factor for taste evaluation of tofu is determined in advance from the correlation between the spectral characteristics of the raw soybean for tofu production and the sensory evaluation value of the product tofu, and the conversion factor and the test raw soybean are irradiated with visible to near red light. In the evaluation of the taste of the raw material soybean by calculating the taste evaluation value from the spectral characteristics obtained by the method, the raw material soybean is used for the evaluation of the taste of tofu as a tofu based on the degree of deterioration detection of the raw material soybean and the detected degree of deterioration of the raw material soybean. A taste evaluation suitability determination means for determining whether or not the taste is good, when the degree of deterioration is limited to a raw material soybean having a predetermined value or less and the conversion coefficient of the taste evaluation as the tofu is determined and the taste evaluation as the tofu is performed. Will be described. Tofu is a food with high locality compared to rice and wheat, and there is no standardized method for the sensory evaluation of tofu nationwide.However, as with processed rice and wheat, the appearance color, hardness, elasticity, tongue, etc. Evaluation is made based on evaluation items such as texture, taste characteristics such as sweetness, bitterness, and richness, and overall evaluation value of taste. In general, those that have a soft and smooth tongue and feel a sweet and rich taste are considered good. These evaluation items were the protein content Cp, total sugar content Cs, and unsaturated fatty acid content of the raw soybeans.
The contents of multiple chemical components such as Cf are greatly involved. For example, the taste evaluation value Tg of sweetness and the taste evaluation value Th of hardness are expressed as follows: Tg = bCs + cCf (b and c are constants) Th = a'Cp + b'Cs + c'Cf (a ', b', c 'Is a constant) A plurality of chemical component values are obtained by a spectroscopic analysis method and substituted into the above-mentioned taste evaluation formula to calculate each taste evaluation value. On the other hand, the degree of deterioration (or, conversely, the degree of freshness) of the raw soybeans varies depending on the drying / adjustment treatment and storage conditions. Deteriorated soybeans have a change in lipids, and in particular, as the unsaturated fatty acids are oxidized and converted to saturated fatty acids, exhibit poor taste characteristics and texture, mainly sweetness, and are not very good in taste. The process is as complicated and diverse as rice and wheat, and lacks quantitative stability as a taste evaluation. Therefore, the degree of degradation of the sample soybean is determined from the degree of fatty acid, the degree of water-soluble acidity, the degree of PH acidity, the rate of germination, the change in color tone, and the like. Therefore, the conversion factors b, c, a ', b', and c 'of the taste evaluation when calculating the sweetness and hardness taste evaluation values of the above-described representative examples limit the degree of deterioration to a predetermined value or less. It is determined by the correlation between a plurality of chemical component values of a large number of test material soybeans and a taste evaluation value by sensory test of a product tofu produced from the test material soybeans under predetermined process conditions. As a method of calculating the taste evaluation value, the sensory evaluation value may be directly obtained from the spectral characteristics. Further, a texture characteristic value by a text cholometer or a taste sensor characteristic value such as a biosensor is obtained from a spectral characteristic as a substitute characteristic value of a sensory evaluation value, and then a taste evaluation value is determined from a relationship between the substitute characteristic value and the sensory evaluation value. It is also good. By excluding the evaluation of the deteriorated raw material soybean by the above configuration, the taste evaluation of the product tofu can be accurately, promptly and simply performed. This is true not only for tofu but also for processing miso and soy milk.

As shown in FIG. 4, the results of the above-mentioned taste evaluation are obtained by dividing a two-dimensional coordinate into nine segments in which the vertical axis is the G value (or T value) and the horizontal axis is the freshness (or the degree of deterioration). Indicate to which position it belongs. From this segment, the taste evaluation value and the freshness can be separately recognized separately. Here, freshness = 100−brown rice fatty acid degree or freshness = 100−milled rice fatty acid degree * 5. That is, freshness = 100−deterioration degree can be expressed.
In addition to the fatty acid degree and odor, various means for determining the degree of deterioration may be used. For example, freshness = germination rate freshness = 100−color tone change degree.

Each of the above segments clearly indicates a target yield of milled rice. For example, segments 1, 2, 4
Good yield rice and high freshness, so target yield of 90
% To reduce bran dropping. Segments 3, 5,
In Nos. 6 and 7, since the taste and freshness are moderate, the target yield of milled rice is set to 89%. Segments 8 and 9 have low taste and freshness, so that the target yield of milled rice is 88% and the amount of rice bran is increased. It should be noted that the target yield value of rice milling is set individually according to the type of rice milling machine. As described above, by separately displaying the taste evaluation value and the freshness of which the freshness is within a predetermined value as a numerical value, it is possible to control rice yield and control the work rationally.

In the above segments, the suitability or unsuitability of the blend is specified. For example, when rice is polished at the above target yield, blending is possible between adjacent segments.
In the case of brown rice, blending can be performed between adjacent vertical segments. By displaying the taste evaluation value and the freshness with freshness within a predetermined range as different numerical values, various blending indexes can be set and rational blend management can be performed, and the quality after blending is stabilized.

The segmentation boundary value of the above segment is made variable depending on the purpose, variety, place of production, year, etc. of rice. For example, in the case of varieties that are easily degraded, varieties with many immature grains, and production areas, the freshness division boundary value is set strictly. Further, since there are few non-defective products in the poor year, the division boundary value is set loosely.

The segmentation boundary value of the segment is made variable depending on the milling conditions such as the type of milling machine and milling yield.
For example, when a rice polishing means is provided at the latter stage of the rice polishing, the division boundary value of the freshness is set loosely. In addition, when the rice bran yield is increased and the bran is left, the dividing boundary value of the freshness is set strictly.

It is preferable that the result of the above-mentioned taste evaluation is determined based on the direction and the distance from the position using the evaluation value of the reference rice at the coordinates as the reference point. The freshness φ and the evaluation value T of the reference sample are set at a point A (φ0, T0). Here, the reference sample may be Nipponbare from Shiga Prefecture, or the user may arbitrarily set it as a measured value or a virtual value. Therefore, the sample point P
Let (φ, T) be the geometric distance as an example of the distance between point A and point P, and let it be r. Then, for example, the following determination is made. When r <r1, it is equivalent to the reference sample A. When r1 <r <r2 Although the judgment cannot be clearly made in the uncertainty region, unlike the reference sample A, it is judged that the evaluation is close to the following. When r2 <r Each of the four quadrants defined by the line φ = φ0 and T = T0 is evaluated as follows.・ P1 zone: good for evaluation value T for sample A, good for freshness φ ・ P2 zone: bad for evaluation value T for sample A, good for freshness φ ・ P3 zone: good for evaluation value T for sample A Poor, poor in freshness φ ・ P4 zone: good in evaluation value T with respect to sample A, poor in freshness φ As described above, the relative evaluation of the sample to be evaluated and the reference sample is usually performed to obtain the reference sample. Quantitatively quantifies the evaluation value as a relative evaluation value to the sensory test.The sensory test is used to calculate the taste evaluation value as the absolute evaluation value. By clarifying the degree of deterioration, it can be applied to a range of a predetermined degree of deterioration, and the reliability of the numerical value calculated as the relative evaluation is high. It has the characteristic that the evaluation value according to the actual situation can be obtained, such as being equivalent to the reference sample. Further, the user can set one or more points arbitrarily as a reference sample (either an actual measurement value or a virtual value) based on the past results of the rice milling operation, the blending operation, etc. Combining the quantitative evaluation values makes the evaluation more reliable and produces a great effect. Alternatively, pass / fail may be determined based on a direction and a distance from an arbitrary reference point.

The result of the above taste evaluation is the T value (or
G value) and freshness may be multiplied by the following equation. Comprehensive evaluation = T^a(Or G^a) ・ (Freshness)^b  Here, a and b are constants. Constants a and b are for rice
Change according to the method, variety, production area, year, etc. Or
Changes depending on milling conditions such as mill type and milling yield
I do. Alternatively, change according to storage conditions such as storage temperature.
You. Freshness greatly influences taste evaluation
Because it shows more complex characteristics, the conventional taste evaluation value
Because the taste is evaluated taking into account the deterioration information, the accuracy is poor.
Is difficult to use for rating, but as described above, taste evaluation
Value (sensory value in the state of high freshness) and freshness (degree of deterioration)
) To calculate the overall evaluation value as a rating.
Therefore, even if the sample has deteriorated,
To obtain a comprehensive evaluation value that accurately captures the current quality.
Can be given a reasonable rating.

Next, an apparatus for correcting the taste evaluation value calculated by the taste evaluation apparatus of the present invention according to the degree of deterioration of sample rice will be described. Since the taste evaluation device of the present invention evaluates the taste only for rice having a degree of deterioration equal to or less than a predetermined value, the taste evaluation cannot be performed for rice having a degree of deterioration equal to or more than a predetermined value. Therefore, even if the degree of deterioration of rice is equal to or more than a predetermined value, a correction is made in accordance with the degree of deterioration so that stable taste evaluation can be performed regardless of the degree of deterioration.

For this reason, for example, the taste evaluation value is corrected by the following formula. In the case of brown rice, the corrected taste evaluation value = taste evaluation value x (100-fatty acid degree) / 100 In the case of polished rice, the corrected taste evaluation value = taste evaluation value x (100-fatty acid degree * 5) / 100 Although the example relating to taste evaluation has been described, it is important to evaluate the degree of deterioration in the evaluation of the processing characteristics of agricultural products, and rice processing, wheat processing, and bean processing will be sequentially described below. First, rice processing will be described. In the rice cooking process, the weight loss (water content) during rice cooking is generally about 1.4 to 1.6 times the weight of white rice, and is appropriately adjusted during rice cooking. In recent rice cookers, microcomputer thermal control has been adopted to cope with incompatibilities in water weight loss, but water weight loss is appropriate in order to obtain appropriate finished rice for various raw rice. is important. The water loss is governed by a plurality of chemical component values of the raw rice and can be measured by spectroscopic analysis means like the taste evaluation value. However, when the deterioration has progressed, the rice has been cooked by increasing the water loss by 10%, but the rice is not stable and sufficiently finished. Therefore, estimating the water weight loss of rice within a range in which the degree of deterioration is limited greatly contributes to stabilization of the quality of finished cooked rice. This is not limited to water loss during rice cooking, but is not limited to rice milling yield, rice milling resistance (easiness of rice milling), rice flour processing characteristics, and other chemical properties of rice. Applied to the processing characteristic evaluation value related to the component. Also in the processing of wheat, similarly to the above, the present invention is applied to characteristic evaluation values of a plurality of chemical components of wheat in the processing step. As an example thereof, estimation of the bran contamination rate, which is one of the milling characteristic evaluation values, in a range in which the degree of deterioration is limited will be described. The bran mixing ratio indicates the amount of crushed husk mixed in the product flour, which indicates the ease of peeling during husk milling and is governed by multiple chemical component values of raw wheat, and the water weight loss of rice Can be measured by the spectroscopic analysis means in the same manner as described above. However, when the deterioration progresses, especially in the raw wheat in which the germination rate is lowered, the bran mixing ratio is unstable and it cannot be said that the wheat flour is a sufficiently finished flour. Therefore, estimating the bran mixing ratio in a range in which the degree of deterioration is limited greatly contributes to stabilization of quality during milling. This is applied to processing characteristic evaluation values relating to a plurality of chemical components of wheat, such as the yield at the time of milling wheat, the milling resistance at the time of milling (easiness of milling), and other evaluation values of milling characteristics. Further, since beans have a high lipid content and protein content, the modification of lipids and proteins due to the degree of deterioration of raw materials is not limited to the evaluation of the taste of processed products.For example, in the case of soybean, the coagulation characteristics during tofu processing and the amount of okara production, The yield of tofu,
It significantly affects various qualities such as the yield of soymilk. These quality characteristic evaluation values are governed by a plurality of chemical component values of the raw material soybean, and can be measured by spectroscopic analysis means in the same manner as the water weight loss of rice. Therefore, in the range where the degree of deterioration is limited, estimating the characteristic evaluation values at the time of various processings such as the coagulation characteristics during the tofu processing and the amount of okara generation, that is, the yield of the tofu, the yield of soymilk, it is the quality of the processing It greatly contributes to stabilization. Regarding the processing characteristic evaluation value affected by freshness, rice processing characteristic evaluation values such as water loss during rice cooking with freshness within a predetermined value, rice resistance during rice polishing, bran mixing ratio during wheat flour processing The evaluation value of flour milling characteristics such as tofu, the solidification characteristics during tofu processing, the evaluation value of tofu processing characteristics such as yield, and the freshness (degree of deterioration) of the raw material are evaluated in two parts, and the processing characteristics possessed by the raw material are evaluated. Can be evaluated more accurately than the one which is uniquely evaluated as an evaluation value, setting conditions such as processing conditions can be predicted, appropriate processing can be performed according to the raw material, and the quality of the finished product can be stabilized. In a typical implementation, a two-dimensional display as shown in FIG. 4 is desirable. Further, it may be advanced according to the contents such as three-dimensional display. In the processing characteristic evaluation value affected by the freshness, the conventional method is evaluated in consideration of the deterioration information. Therefore, the accuracy is poor. By multiplying the processing characteristic evaluation value in a high state and the freshness (degree of deterioration) to calculate an overall evaluation value as a rating, a reasonable rating that accurately captures the current quality can be obtained. In addition, for companies that process cooked rice, milling, tofu, etc., whether the degree of deterioration (freshness) of the grains or beans in the raw material state is detected, and whether it is suitable for evaluating not only the taste but also the quality during processing By simply determining whether or not it is non-conforming, it is contributing to the improvement of the quality of the finished product.

[0040]

For example, when rice deteriorates, its components and properties change by oxidizing action, and the change in the taste of rice is complicated and diversified. Therefore, the evaluation value of the taste of rice greatly varies and becomes unstable. Therefore, in the present invention, when the degree of deterioration is equal to or less than a predetermined value, determination of a conversion coefficient for taste evaluation and taste evaluation are performed. Therefore, according to the present invention, since the taste evaluation is performed by removing the influence of the degree of deterioration of the agricultural product, which is an unstable factor of the taste evaluation, accuracy and reliability are greatly improved as compared with the conventional evaluation data. That is, conventionally, since one taste evaluation value including deterioration was used, for example, it was not clear whether or not the deterioration was remarkable. Therefore, the quality information lacked specificity. It was a reality that it was difficult to stand. That is, any change from a raw material to a product during a processing step is accompanied by a change in a chemical component present in the raw material. Therefore, changes and alterations in the chemical composition of the raw materials due to deterioration are processed,
It was greatly involved in the treatment process, greatly affected the quality of the finished product, and the control and adjustment were insufficient. However, by dividing the evaluation into two as described above, the taste evaluation value at the time when the deterioration state is good or the taste evaluation value and the deterioration state can be evaluated in parallel. It can be used for index, rice yield control, blending guideline, water control / heat control of rice cooking process, etc. In addition, regarding the processing characteristic evaluation value affected by the freshness, rice processing characteristic evaluation values such as water loss during rice processing, freshness resistance during rice polishing, etc., and bran quality during wheat milling, where the freshness is within a predetermined value Evaluation value of milling characteristics such as mixing ratio, solidification characteristics during tofu processing, evaluation value of tofu processing characteristics such as yield, and freshness of raw materials (degree of deterioration)
Is divided into two and evaluated, the more accurate evaluation can be performed than the one that uniquely evaluates the processing characteristics possessed by the raw material as an evaluation value. Process, and the quality of finished products is stable.

[Brief description of the drawings]

FIG. 1 is a diagram showing the overall configuration of an embodiment of the present invention.

FIG. 2 is a block diagram of the control processing system.

FIG. 3 is a processing block diagram of the taste evaluation device.

FIG. 4 is a diagram showing the taste evaluation results in two-dimensional coordinates in a segment diagram.

FIG. 5 shows the results of taste evaluation on two-dimensional coordinates φ = φ0, T =
It is a figure displayed in four quadrants divided by the T0 line.

[Explanation of symbols]

 Reference Signs List 1 light source 2 reflecting mirror 3 diffraction grating 4 lens 5 wavelength calibration filter wheel 6 photodetector 7 sample cell 8 discharge valve 20 CPU 21 input / output interface 22 sample cell transfer motor 23 input interface 24 input key 25 output interface 26 display device 27 Storage device A Spectroscopic analyzer B Control processor

Claims (4)

[Claims] 1. A conversion factor for taste evaluation is determined in advance from a correlation between a sensory evaluation value of agricultural products such as cereals and beans and the spectral characteristics of agricultural products such as cereals and beans, and the conversion factor and visible light or Calculating a taste evaluation value from spectral characteristics obtained by irradiating near-infrared light to evaluate the taste of the agricultural product, wherein a conversion factor for determining a conversion factor of the taste evaluation with the agricultural product having a degree of deterioration of not more than a predetermined value. An apparatus for evaluating the taste of agricultural products, comprising a determination unit. 2. A conversion factor for taste evaluation is determined in advance from a correlation between a sensory evaluation value of an agricultural product such as cereals and beans and the spectral characteristics of the agricultural product such as a cereal and beans, and the conversion factor and visible light or A device for calculating the taste evaluation value from the spectral characteristics obtained by irradiating near-infrared light and evaluating the taste of the agricultural product, wherein a deterioration degree detecting means for detecting the degree of deterioration of the agricultural product; 2. A taste evaluation suitability determining means for judging whether or not the agricultural product conforms to the taste evaluation according to the degree, and the taste evaluation is performed on the agricultural products whose degree of deterioration is equal to or less than a predetermined value. A taste evaluation device for agricultural products. 3. A conversion coefficient for processing characteristic evaluation is determined in advance from a correlation between the processing characteristic evaluation value of agricultural products such as cereals and beans and the spectral characteristics of the agricultural products such as cereals and beans, and the conversion coefficient and the conversion coefficient are visualized in the test sample. A processing characteristic evaluation value is calculated from spectral characteristics obtained by irradiating light or near-infrared light to evaluate the processing characteristics of the agricultural product. A processing characteristic evaluation device for agricultural products, comprising a conversion coefficient determining means for determining the processing coefficient. 4. A conversion coefficient for processing characteristic evaluation is determined in advance from a correlation between the processing characteristic evaluation value of agricultural products such as cereals and beans and the spectral characteristics of the agricultural products such as cereals and beans, and the conversion coefficient and the conversion factor are visualized in a test sample. A processing characteristic evaluation value is calculated from spectral characteristics obtained by irradiating light or near-infrared light to evaluate processing characteristics of the agricultural product; and a deterioration degree detecting means for detecting a deterioration degree of the agricultural product. Processing characteristic evaluation conformity determination means for determining whether the agricultural product conforms to the processing characteristic evaluation based on the degree of deterioration of the agricultural product, and performing the processing characteristic evaluation with the agricultural product having the degree of deterioration equal to or less than a predetermined value. 4. The apparatus for evaluating processing characteristics of agricultural products according to claim 3.