Method for providing evaluation of taste, information processing device, taste information providing system, and program

Abstract

Provided is a method for providing evaluation of taste of two or more food products. A method according to the present invention comprises a step (S310) for acquiring an information value of each of at least one taste of each of two or more food products, a step (S314) for generating adjustment information for using the information value as a reference for normalization with respect to one food product selected from the two or more food products, a step (S316) for using the adjustment information to normalize the information value of each of the two or more food products other than said one food product, and a step (S322) for outputting a value obtained by normalizing the information value with respect to each of the two or more food products.

Description

Method for providing taste evaluation, information processing device, taste information providing system, and program

[0001] The present invention relates to providing food taste ratings.

[0002] Various proposals have been made for evaluating the taste of food. In food manufacturing and development, specific evaluators evaluate the taste of prototypes, and Non-Patent Document 1 discloses a method for training such evaluators (panels).

[0003] Hideko Furukawa, "Panel Training and Product Development," Journal of the Brewing Society of Japan, Japan, Brewing Society of Japan, Public Interest Incorporated Foundation, June 15, 1983, Vol. 78, No. 6, pp. 419-422

[0004] When multiple foods are evaluated in the above-described manner, there has been a demand for a technique for comparing the evaluations of the multiple foods.

[0005] The present invention has been devised in view of the above circumstances, and its purpose is to provide a technique for easily carrying out comparative evaluation of the tastes of a plurality of foods.

[0006] A method according to one aspect of the present disclosure is a method for providing taste information about two or more foods, comprising the steps of obtaining analysis results for the components of each of the two or more foods, identifying substances that affect the difference in taste between the two or more foods using the results of a test using the analysis results for the components of each of the two or more foods, and outputting taste information about the two or more foods using the analysis results for the identified substances from the analysis results for the components of each of the two or more foods.

[0007] An information processing device according to another aspect of the present disclosure includes one or more processors and a storage device storing a program that, when executed by the one or more processors, causes the one or more processors to implement the above-described method.

[0008] A taste information providing system according to yet another aspect of the present disclosure includes the above-described information processing device and an analysis device that outputs an analysis result of a food product to the above-described information processing device.

[0009] A program according to yet another aspect of the present disclosure causes one or more processors to perform the above-described method when executed by the one or more processors.

[0010] According to certain aspects of the present disclosure, it becomes easier to comparatively evaluate the taste of multiple foods.

[0011] 15 is a diagram showing a configuration of a taste information providing system 1. FIG. 15 is a diagram showing an example of taste information output by an information processing device 10 ... a screen output as an evaluation result for each of four types of products (products A to D). FIG. 15 is a diagram showing an example of a method for calculating five types of indices. FIG. 15 is a diagram showing an example of a compound identified as a taste substance. FIG. 15 is a diagram showing an example of a compound identified as an aroma substance. FIG. 15 is a diagram showing an example of taste information values ​​for five indices for four products. FIG. 15 is a diagram showing an example of a reference evaluation value and a comparative evaluation value for five indices for four products. FIG. 15 is a diagram showing another example of a screen output as an evaluation result for each of four types of products (products A to D). FIG. 15 is a flowchart of a main routine executed in the information processing device 100. FIG. 15 is a flowchart of a subroutine of step S20 of FIG. 15A and 15B are flowcharts of the subroutine of step S30 in FIG. 15A, which is performed to output taste information (FIGS. 2 to 7), and taste evaluation (FIGS. 8 and 14).

[0012] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals, and description thereof will not be repeated.

[0013] 1 is a diagram showing the configuration of a taste information providing system 1. The taste information providing system 1 mainly includes an information processing device 100 and an analysis device 200. The information processing device 100 obtains analysis results for food from the analysis device 200 and provides information about the taste of the food using the analysis results. The analysis device 200 may be, for example, a liquid chromatograph mass spectrometer and / or a gas chromatograph mass spectrometer.

[0014] In one implementation example, the information processing device 100 is implemented by a general-purpose computer. More specifically, the information processing device 100 includes a CPU (Central Processing Unit) 101, a storage 102, and an input / output port 103.

[0015] The CPU 101 is composed of one or more processors. The storage 102 is an example of a storage device that non-temporarily stores programs and / or data. The information processing device 100 acquires food analysis results from the analysis device 200 via the input / output port 103. The information processing device 100 may be realized by multiple computers working together. In one implementation example, the one or more processors that make up the CPU 101 execute programs non-temporarily stored in the storage 102 (or a storage device outside the information processing device 100 that is accessible by the one or more processors), thereby causing the information processing device 100 to perform various processes.

[0016] A mouse 300, a keyboard 400, and a display device 500 are connected to the information processing device 100. The information processing device 100 receives input from the outside via the mouse 300 and the keyboard 400, and outputs information by displaying a screen on the display device 500. The information processing device 100 may include a network interface and may communicate with external information devices via a network.

[0017] In this embodiment, sake is mainly used as an example of food. However, the food for which the information processing device 100 provides information on taste is not limited to sake. Any type of product can be the subject of information provision as long as it is a food that can be analyzed by the analysis device 200.

[0018] 2. Flavor Information FIGS. 2 to 7 are diagrams showing examples of flavor information output by the information processing device 100. FIG.

[0019] In one implementation, the information processing device 100 may identify the compounds shown in Figures 2 to 7 as substances (taste substances or aroma substances) that affect the differences in taste between the four types of sake shown in each figure, as described below. In one implementation, the mass spectrometer outputs the content of each compound in the food to the information processing device 100 as the food analysis result. More specifically, the mass spectrometer calculates the content of each compound using the ratio of the peak area of ​​each compound to the peak area of ​​the internal standard in the mass spectrogram. Note that the content of each compound may be calculated using the concentration of the compound in the sample used in the analysis and a calibration curve showing the relationship between concentration and content. Alternatively, the content of each compound may be calculated from the peak area value of the mass spectrogram or chromatogram.

[0020] (Screen 20 in Figure 2) Screen 20 in Figure 2 displays the content of four types of sugars (monosaccharide, disaccharide, maltotriose, and maltotetraose) for each of the four types of sake (products A, B, C, and D).

[0021] The user can use the information displayed on the screen 20 to support his / her consideration of the differences in taste between products A, B, C, and D.

[0022] More specifically, as shown on screen 20, products C and D have a higher total content of the above four types of sugar than products A and B. Products A and B have a higher rice polishing ratio than products C and D. Therefore, based on the results shown on screen 20, the user can conclude that the lower the rice polishing ratio, the more sugars a product contains.

[0023] As shown on screen 20, Product A contains a higher total content of the four types of sugars than Product B. On the other hand, Product B contains a higher proportion of three types of oligosaccharides (disaccharide, maltotriose, and maltotetraose) in the total sugar content than Product A. Oligosaccharides tend to be less sweet than monosaccharides. Therefore, the user can conclude that Product B provides a mild sweetness and a mellow mouthfeel by reducing the irritation of alcohol, acid, and the like.

[0024] The screen 20 is an example of taste information, and is an example of taste information output using the values ​​of taste substances.

[0025] (Screen 30 in Fig. 3) Screen 30 in Fig. 3 displays the content of four organic acids (lactic acid, citric acid, malic acid, and succinic acid) for each of the four types of sake (products A, B, C, and D).

[0026] The user can use the information displayed on the screen 30 to support his / her consideration of the differences in taste between products A, B, C, and D.

[0027] More specifically, organic acids are said to contribute to the refreshing taste and richness of sake, which can be described as a full-bodied, rich, and deep flavor. It is said that the balance of sourness and sweetness, which cancel each other out, gives sake its rich flavor. The higher the rice polishing ratio in sake, the more organic acids it contains. Organic acids contribute to the richness of sake. Products C and D (ginjo sake and daiginjo sake), which tended to contain high amounts of sugar, had relatively low organic acid contents, as shown in Figure 3. For this reason, products C and D are thought to have a sweeter taste than products A and B.

[0028] Furthermore, the quality of sourness varies depending on the type of organic acid. Malic acid and citric acid have a sour taste accompanied by a refreshing sensation, while succinic acid also has a unique umami flavor. Screen 30 shows that all of Products A to D tend to have a high malic acid content. Therefore, based on the results shown on screen 30, the user can conclude that all of Products A to D give a clean, refreshing impression.

[0029] Furthermore, when the ratio of malic acid to succinic acid is 0.8 or higher, the sake is said to have a light aftertaste and a crisp finish. On screen 30, the ratio of malic acid to succinic acid is 0.8 or higher for all of Products A to D. Therefore, based on the results shown on screen 30, the user can conclude that all of Products A to D have a light aftertaste and a crisp finish.

[0030] Furthermore, the total value of organic acids including succinic acid in product B is larger than that of the other products. From this, based on the results displayed on screen 30, it can be concluded that product B is characterized by its particularly umami and rich flavor.

[0031] Screen 30 is an example of taste information, and is an example of taste information output using the values ​​of taste substances.

[0032] (Screen 40 in Fig. 4) Screen 40 in Fig. 4 displays the amino acid content for each of four types of sake (products A, B, C, and D). Screen 40 shows the content of the following 10 compounds:

[0033] ・Proline ・Glutamine ・Glutamic acid ・Lysine ・Isoleucine ・Arginine ・Phenylalanine ・Leucine ・Aspartic acid Screen 40 is accompanied by a string of characters that indicates the type of taste (sweet, bitter, sour, umami) exhibited by each compound.

[0034] The user can use the information displayed on the screen 40 to support his / her consideration of the differences in taste between products A, B, C, and D.

[0035] For example, the total amount of amino acids in product B is significantly higher than that of the other products. It is said that when the amount of amino acids is high, sake has a rich, mellow flavor, while when the amount of amino acids is low, sake has a light, refreshing flavor. Therefore, the user can derive the conclusion that product B has a rich, mellow flavor, and the remaining products have a light, refreshing flavor.

[0036] Furthermore, Products B to D contain more bitter amino acids (leucine, isoleucine, phenylalanine, and arginine) than Product A. Bitter amino acids give sake a sharp and dry taste. Therefore, it can be concluded that Products B to D provide a sharp and dry taste compared to Product A.

[0037] Screen 40 is an example of taste information, and is an example of taste information output using the values ​​of taste substances.

[0038] (Screen 50 in Fig. 5) Screen 50 in Fig. 5 displays the content of three aroma components (ethyl caproate (Ethyl hexanoate), isoamyl acetate (Isoamyl acetate), and isobutyl acetate (Isobutyl acetate)) for each of four types of sake (Products A, B, C, and D). In one implementation example, aroma components refer to volatile substances contained in food that have an aroma.

[0039] The user can use the information displayed on the screen 50 to support his / her consideration of the differences in taste (aroma) between products A, B, C, and D.

[0040] More specifically, the aroma of ethyl caproate, which gives a refreshing feeling like green apple or pear, and the aroma of isoamyl acetate and isobutyl acetate, which gives a feeling like banana or melon, are called ginjo aromas and are actually contained in fruits. Ethyl caproate accounts for the majority of the aroma components in Products C and D. Therefore, the user can derive from screen 50 the conclusion that Products C and D give a gorgeous impression.

[0041] Furthermore, the ratio of isoamyl acetate and / or isobutyl acetate to ethyl caproate is higher in Products A and B than in Products C and D. Therefore, the user can derive from screen 50 the conclusion that Products A and B have a refined, sweet fruity aroma.

[0042] The screen 50 is an example of flavor information, and is an example of aroma information output using values ​​of aroma substances.

[0043] (Screen 60 in Fig. 6 and Screen 70 in Fig. 7) Screen 60 in Fig. 6 displays the content of base aroma components among aroma components for each of four types of sake (products A, B, C, and D). More specifically, screen 60 displays the content of two types of base aromas: phenethyl alcohol (2-phenylethanol) and phenethyl acetate (2-phenylethyl acetate).

[0044] The screen 70 in FIG. 7 displays the content of three types of fusel oils (isoamyl alcohol, isobutanol, and propanol) for each of four types of sake (products A, B, C, and D).

[0045] The user can use the information displayed on screen 60 and screen 70 to support their consideration of the differences in taste (aroma) between products A, B, C, and D.

[0046] More specifically, phenethyl acetate and phenethyl alcohol, which impart a rose-like aroma, are compounds with relatively high boiling points that cause the aroma to be perceived after a person has taken a sip of sake. This characteristic is called the base aroma (latent aroma). The base aroma is the source of the distinctive sake aroma.

[0047] As shown on screen 60, products A and B have a higher content of base aroma than products C and D. From this, the user can derive from screen 60 the conclusion that products A and B have a sake-like aroma.

[0048] Furthermore, as shown on the screen 70, products A and B contain more fusel oil than products C and D. From this, the user can derive from the screen 70 the conclusion that products A and B have a mild fragrance.

[0049] Screen 60 and screen 70 are examples of taste information, and are examples of aroma information output using values ​​of aroma substances.

[0050] 3. Taste Evaluation The information processing device 100 can output, as an evaluation result of each product, an index related to the taste of each product, calculated using one or more analysis results of each product.

[0051] 8 is a diagram showing an example of a screen on which evaluation results for each of four types of products (products A to D) are output. Screen 80 in Fig. 8 includes a radar chart showing the values ​​of five types of indices (light, sweet and spicy, sharp, umami, and fruity aroma) for each of products A to D.

[0052] Screen 80 shows radar charts for product B in the upper left, product C in the upper right, product A in the lower left, and product D in the lower right. On screen 80, the value of each index is normalized so that the value of product B is 1. In other words, the index value of each product displayed on screen 80 is normalized using the index value of product B as the reference. A product used as the reference for normalization is also referred to as a "reference product" in this specification. Information identifying the reference product (product B) may also be displayed on screen 80.

[0053] 9 is a diagram showing an example of a method for calculating five types of indexes. As shown in Fig. 9, the value Vt1 of the index "sharpness" is calculated as the ratio of the content of malic acid to the content of succinic acid in each product.

[0054] The value Vt2 of the "Tanrei" index is calculated as the total content of organic acids identified as "taste substances" (described below) in each product. The lower the organic acid content, the more "Tanrei" the sake is said to be. From this, it can be considered that the smaller the value Vt2 of a certain sake, the higher the degree to which that sake is "Tanrei."

[0055] In the past, the content of all organic acids was sometimes used as an index of taste. In contrast, in the present embodiment, among the organic acids, some of the organic acids are identified as taste substances that affect the difference in taste between Products A to D. In other words, only the content of some of the organic acids is used as the content of organic acids that affect the difference in taste between Products A to D. As a result, the value Vt2 of the index "Tanrei" is calculated as a value that more accurately represents the difference between Products A to D.

[0056] The value Vt3 of the "sweetness / dryness" index is calculated by subtracting the content of organic acids identified as "taste substances," described below, from the glucose content in each product. As mentioned above, in sake, the sourness and sweetness cancel each other out, resulting in a moderately harmonious taste. From this, it can be thought that the higher the value Vt3 of a certain sake, the sweeter the sake, and the lower the value, the drier the sake.

[0057] The content of organic acids identified as taste substances is used to calculate value Vt3, as in the calculation of value Vt2. As a result, value Vt3, like value Vt2, is calculated as a value that more accurately represents the differences between products A to D.

[0058] The value Vt4 of the indicator "umami" is calculated as the sum of the content of amino acids identified as "taste substances" (described below) and the content of succinic acid in each product.

[0059] In the past, the contents of all amino acids were sometimes used as an index of taste. However, in the present embodiment, some amino acids are specified as taste substances that affect the difference in taste between Products A to D. In other words, the contents of only some amino acids are used as the contents of amino acids that affect the difference in taste between Products A to D. This allows the value Vt4 of the "umami" index to be calculated as a value that more accurately represents the difference between Products A to D.

[0060] The value Vt5 of the "fruity aroma" index was calculated by dividing the total content of three aroma components (ethyl caproate, isoamyl acetate, and isobutyl acetate) in each product by the content of isoamyl alcohol. As described below, ethyl caproate, isoamyl acetate, and isobutyl acetate are identified as aroma substances among the aroma components.

[0061] In the past, the value obtained by dividing the content of ethyl caproate by the content of isoamyl alcohol was sometimes used as an index of fruity aroma. However, in the present embodiment, in addition to ethyl caproate, isoamyl acetate and isobutyl acetate can be identified as aroma substances that affect the difference in taste between Products A to D. In other words, the contents of a larger number of substances than in the past are used as the contents of aroma components that affect the difference in taste between Products A to D. This allows the value Vt5 of the "fruity aroma" index to be calculated as a value that more accurately represents the difference between Products A to D.

[0062] 10 is a diagram showing examples of compounds identified as tastants. In FIG. 10, the compounds are shown together with their classifications and taste characteristics. In one implementation example, when the information processing device 100 identifies tastants, it may acquire the taste characteristics of each tastant by searching a database that associates substances with taste characteristics, generate a table such as that shown in FIG. 10, and store the table in the storage 102.

[0063] FIG. 11 is a diagram showing examples of compounds identified as fragrance substances. In FIG. 11 , the compounds are shown together with their classifications and fragrance characteristics. In one implementation example, when the information processing device 100 identifies fragrance substances, it may acquire the fragrance characteristics of each fragrance substance by searching a database that associates substances with fragrance characteristics, generate a table such as that shown in FIG. 11 , and store the table in the storage 102.

[0064] The calculation methods for the five indices are not limited to those shown in Figure 9. The user may change the calculation methods for the five indices as appropriate by referring to the types of substances identified as taste substances and aroma substances and / or the characteristics of their tastes or aromas. Furthermore, the number of calculated indices is not limited to five. It may be one type, or any number of types equal to or greater than two.

[0065] 4. Identification of Taste Substances Identification of taste substances will now be described.

[0066] The information processing device 100 acquires the analysis results of taste components for each of the products A to D. Taste components are also called flavor components and refer to components that provide some kind of taste.

[0067] The analysis results represent the content of each of two or more components. For example, when a certain amount of each product is input into a liquid chromatograph mass spectrometer (analysis device 200), the content of each component is calculated as the ratio of the peak area of ​​each component to the peak area of ​​the internal standard. The information processing device 100 obtains the content of each component from the analysis device 200 as the analysis results of the taste components.

[0068] For example, if the content of 151 types of hydrophilic metabolites (sugars, amino acids, organic acids, nucleosides, nucleotides, etc.) is obtained as the analysis results of the taste components of each product, the analysis results of four types of products will include 604 measurement values ​​(contents).

[0069] The information processing device 100 performs an analysis of variance (ANOVA) test on the analysis results of the four types of products. The information processing device 100 then identifies, in the test results, components corresponding to measured values ​​with a p-value of 0.05 or greater as taste substances. Examples of identified taste substances are the compounds listed in FIG. 10 . This allows components that particularly influence differences in taste to be identified from among the multiple components that make up taste.

[0070] The information processing device 100 employs an ANOVA test as a test for the analysis results of three or more types of products, and employs a student's t-test or a Mann-Whitney u-test as a test for the analysis results of two types of products.

[0071] The information processing device 100 may obtain the analysis results used to identify taste substances from a gas chromatograph mass spectrometer.

[0072] The identified taste substances may be limited to those contained in a predetermined group of ingredients for each taste. For example, if the taste is "light and refreshing," no ingredients other than organic acids may be used as taste substances. This allows components that contribute little to the taste to be removed from the basis of the taste information.

[0073] [5. Identification of Fragrance Substances] Identification of fragrance substances will now be described.

[0074] The information processing device 100 obtains the analysis results of aroma components for each of products A to D. The analysis results indicate the content of each of two or more components. For example, when a certain amount of each product is input into a gas chromatograph mass spectrometer (analysis device 200), the content of each component is calculated as the ratio of the peak area of ​​each component to the peak area of ​​the internal standard. The information processing device 100 obtains the content of each component from the analysis device 200 as the analysis results of aroma components.

[0075] The information processing device 100 performs an ANOVA (analysis of variance) test on the analysis results of the four types of products. The information processing device 100 then identifies, in the test results, components corresponding to measured values ​​with a p-value of 0.05 or greater as aroma substances. Examples of identified aroma substances are the compounds listed in FIG. 11 . This allows components that particularly influence differences in taste to be identified from among the multiple components that make up taste.

[0076] The information processing device 100 employs an ANOVA test as a test for the analysis results of three or more types of products, and employs a student's t-test or a Mann-Whitney u-test as a test for the analysis results of two types of products.

[0077] The information processing device 100 may obtain the analysis results obtained by identifying aroma substances from a liquid chromatograph mass spectrometer.

[0078] The aroma substances to be identified may be limited to those contained in a predetermined group of components for each flavor. For example, for a flavor of "light and refreshing," no components other than organic acids may be used as aroma substances. This allows components that contribute little to the flavor to be removed from the basis of the flavor information.

[0079] 6. Taste Information Value The information processing device 100 calculates the values ​​of the indices shown in Fig. 9 as the taste information value of each product. That is, the values ​​of the indices Vt1 to Vt5 each constitute an example of a taste information value.

[0080] 7. Reference Evaluation Value and Comparative Evaluation Value A "reference evaluation value" and a "comparative evaluation value" are defined as values ​​used in a radar chart such as that shown in Fig. 8. These values ​​will be explained below.

[0081] 8, the information processing device 100 adjusts the taste information values ​​so that the index values ​​of one product among multiple types of products are all 1. For this purpose, the information processing device 100 performs a common calculation on the taste information values ​​of all products.

[0082] More specifically, when the value of the index Vt1 of product B is P1b, an operation f(x) for setting the value of P1b to 1 is identified. In this case, f(P1b) = 1. This operation is performed on the values ​​P1a, P1c, and P1d of the index Vt1 of products A, C, and D, respectively. This operation converts the values ​​P1a, P1c, and P1d of the index Vt1 of products A, C, and D, respectively, into values ​​N1a, N1c, and N1d. At this time, the radar chart displays 1, N1a, N1c, and N1d as the values ​​of the index Vt1 of products B, A, C, and D, respectively.

[0083] For a more specific explanation, assume that the values ​​(taste information values) of the index Vt1 for products B, A, C, and D are 3, 4, 2, and 3, respectively. An example of an operation for setting the taste information value of product B to 1 is to "subtract 2." When this operation is performed on the taste information values ​​of products A, C, and D, 1, 2, 0, and 3 are derived as values ​​N1a, N1c, and N1d, respectively. In this case, the radar chart displays 1, 2, 0, and 3 as the values ​​of the index Vt1 for products B, A, C, and D, respectively.

[0084] The "reference evaluation value" refers to the value displayed on the radar chart for the reference product. In the above example, this is the value for product B, which is 1.

[0085] The "comparison evaluation value" refers to the value formed on the radar chart for products other than the reference product. In the above example, the values ​​for products A, C, and D are 2, 0, and 1, respectively. As a result, the "comparison evaluation value" refers to the normalized value for the taste evaluation value of product B.

[0086] The calculation for normalizing the taste information value is also referred to as “adjustment information” in this specification. The adjustment information is not limited to addition or subtraction, and any function may be used as the adjustment information.

[0087] Fig. 12 is a diagram showing an example of taste information values ​​for five indices for four products. Fig. 13 is a diagram showing an example of reference evaluation values ​​and comparative evaluation values ​​for five indices for four products. The derivation of the reference evaluation values ​​and comparative evaluation values ​​will be described in more detail with reference to Figs. 12 and 13 .

[0088] As shown in FIG. 12, the information processing device 100 calculates taste information values ​​of five types of indices (Vt1 to Vt5) for each of the four products.

[0089] Then, the information processing device 100 converts the five types of taste information values ​​of one of the four products (product B) into reference information values ​​using a given function, as shown in Fig. 13. For each of the five types of indices (Vt1 to Vt5), a different function is used to convert the taste information value into a reference information value.

[0090] The information processing device 100 then converts the five types of taste information values ​​into comparative evaluation values ​​for each of the remaining three products. For example, a function for the index Vt1 is used to convert the taste information value for the index Vt1 into a comparative evaluation value. A function for each of the indexes Vt2 to Vt5 is used to convert the taste information value for each of the indexes Vt2 to Vt5 into a comparative evaluation value.

[0091] 8. Identifying Similar Products The information processing device 100 may identify products that have a similar taste to a certain product.

[0092] In one example, the information processing device 100 identifies a product having the smallest difference (total) between the reference evaluation value and the comparison evaluation value for one or more indicators as a product having a similar taste.

[0093] In the example shown in FIG. 13, the sums Sa, Sc, and Sd of the differences between the reference evaluation value and the comparative evaluation value of each of products A, C, and D are calculated according to the following formulas (1) to (3).

[0094] Sa = (1-Na1) + (1-Na2) + (1-Na3) + (1-Na4) + (1-Na5) ... (1) Sc = (1-Nc1) + (1-Nc2) + (1-Nc3) + (1-Nc4) + (1-Nc5) ... (2) Sd = (1-Nd1) + (1-Nd2) + (1-Nd3) + (1-Nd4) + (1-Nd5) ... (3) The information processing device 100 may identify the product among products A, C, and D that has the smallest difference value as a product similar to product B.

[0095] The information processing device 100 may also identify the product among products A, C, and D that has the smallest absolute value of the difference as the product similar to product B.

[0096] The information processing apparatus 100 may also identify, among the products A, C, and D, a product whose difference value (or absolute value) is smaller than a given threshold value as a product similar to the product B.

[0097] 14 is a diagram showing another example of a screen output as an evaluation result for each of four types of products (products A to D). The information processing device 100 may display information indicating products identified as similar products. The screen 81 in FIG. 14 further includes a message 81A in addition to the screen 80 in FIG. 8. In the example in FIG. 14, the message 81A includes the character string "This product is similar to product B."

[0098] Note that, when all values ​​(or absolute values) of the totals Sa, Sc, and Sd exceed a specific threshold, the information processing device 100 may determine that there is no product similar to product B among products A, C, and D. When determining that there is no similar product, the information processing device 100 may output a screen 80 to which information indicating that there is no product similar to product B has been added.

[0099] 9. Processing Flow (Main Routine) Fig. 15 is a flowchart of a main routine executed in information processing device 100. In one implementation example, information processing device 100 starts the processing of Fig. 15 in response to a start instruction input by a user. In one implementation example, in information processing device 100, one or more processors constituting CPU 101 execute a given program, thereby realizing the processing described herein.

[0100] In step S10, the information processing device 100 acquires the analysis results of each of the two or more foods from the analysis device 200.

[0101] In step S20, the information processing device 100 identifies evaluation substances. The evaluation substances are a general term for the taste substances and aroma substances described above.

[0102] In step S30, the information processing device 100 outputs statistical information on the evaluation substance from the analysis results acquired in step S10, and ends the processing of FIG.

[0103] (Identifying Evaluation Substances) FIG. 16 is a flowchart of the subroutine of step S20 in FIG.

[0104] In step S200, the information processing device 100 performs a test (the above-mentioned ANOVA, Student's t test, or Mann-Whitney u-test) on the analysis results acquired in step S10. In step S200, the information processing device 100 may perform a test for each of the taste components and the aroma components. That is, the information processing device 100 may perform a test for the analysis results of the taste components, and also perform a test for the analysis results of the aroma components.

[0105] In step S202, the information processing device 100 identifies substances based on the p-values ​​obtained as a result of the testing in step S200. More specifically, the information processing device 100 identifies substances having a p-value of 0.05 or less as taste substances or aroma substances. Thereafter, the information processing device 100 returns control to FIG. 15 .

[0106] (Output of statistical information - output of flavor information) Figure 17 is a flowchart of the subroutine of step S30 in Figure 15, which is executed to output flavor information (Figures 2 to 7). In one implementation example, an instruction to output flavor information is input to the information processing device 100. In response to the input of the instruction, the information processing device 100 executes the subroutine of Figure 17.

[0107] In step S30, the information processing device 100 identifies the values ​​of the evaluation substances in step S300. More specifically, the information processing device 100 extracts the analysis results of each of the one or more evaluation substances identified in step S20 from the analysis results acquired in step S10.

[0108] In step S302, the information processing device 100 generates screen information (display information) to be displayed as taste information.

[0109] In step S304, the information processing device 100 outputs the display information generated in step S302 to the display device 500. As a result, the screen described with reference to Fig. 2 etc. is displayed as taste information. Thereafter, the information processing device 100 returns control to Fig. 15.

[0110] Note that output to the display device 500 is one form of output of taste information. The taste information may be output in a form other than display (for example, audio).

[0111] (Output of statistical information - output of taste evaluation) Figure 18 is a flowchart of the subroutine of step S30 in Figure 15, which is executed to output the taste evaluation (Figures 8 and 14). In one implementation example, an instruction to execute output of the taste evaluation is input to the information processing device 100. In response to the input of the instruction, the information processing device 100 executes the subroutine in Figure 18. The subroutine in Figure 18 may be executed in parallel with the subroutine in Figure 17, or before or after the subroutine in Figure 17.

[0112] In step S30, the information processing device 100 calculates taste information values ​​of one or more indices for each of the two or more foods in step S310.

[0113] In step S312, the information processing device 100 identifies a reference product. In one implementation example, the reference product is designated by a user. The information processing device 100 identifies the reference product from two or more foods in response to a designation input from the user.

[0114] In step S314, the information processing device 100 generates adjustment information (calculation for normalization). The adjustment information is information representing a calculation for making the taste information value of the reference product 1.

[0115] In step S316, the information processing device 100 calculates a comparative evaluation value (FIG. 13) for each of the two or more foods other than the reference product.

[0116] In step S318, information processing device 100 identifies products similar to the reference product.

[0117] In step S320, information processing device 100 generates display information for outputting the taste evaluation (for example, screen information for displaying screen 80 in FIG. 8 or screen 81 in FIG. 14).

[0118] In step S322, the information processing device 100 outputs the display information generated in step S320 to the display device 500. As a result, the screen described with reference to Fig. 8 or 14 is displayed as the taste evaluation. Thereafter, the information processing device 100 returns control to Fig. 15.

[0119] Note that output to the display device 500 is one form of outputting the taste evaluation. The taste evaluation may be output in a form other than a display (for example, audio).

[0120] According to the present embodiment described above, for each of two or more foods, information values ​​of one or more tastes are output in a state normalized with respect to one particular food as a reference, thereby providing information on the tastes of the two or more foods as relative information, thereby providing an accurate evaluation of the two or more foods.

[0121] Aspects It will be understood by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0122] (Item 1) A method according to one aspect is a method for providing an evaluation of the taste of two or more foods, and may include the steps of: acquiring an information value for one or more tastes for each of the two or more foods; generating adjustment information for one food selected from the two or more foods to use the information value as a standard for normalization; normalizing the information value for each of the two or more foods other than the one food using the adjustment information; and outputting the normalized information value for each of the two or more foods.

[0123] According to the method described in paragraph 1, it becomes easy to comparatively evaluate the taste of a plurality of foods.

[0124] (Clause 2) In the method according to paragraph 1, the step of outputting the normalized values ​​of the information values ​​may include displaying the normalized values ​​of the information values ​​as one graph for each of the two or more foods.

[0125] According to the method of paragraph 2, the evaluation is provided in an easy-to-read format. (3) In the method of paragraph 2, the graph may be a radar chart.

[0126] According to the method described in Section 3, when the evaluation to be provided includes multiple types of information values, the evaluation is provided in an easy-to-read format.

[0127] (4) The method according to any one of paragraphs 1 to 3 may further include a step of acquiring the contents of taste substances and aroma substances for each of the two or more foods, and the step of acquiring information values ​​for each of the one or more tastes may include calculating the information values ​​using the contents of the taste substances and the contents of the taste substances.

[0128] According to the method described in paragraph 4, an accurate evaluation of the taste of food is provided for each of taste components and aroma components.

[0129] (Item 5) In the method according to any one of items 1 to 4, the contents of the taste substances and the aroma substances may be measured using a liquid chromatograph or a gas chromatograph.

[0130] According to the method described in Section 5, accurate values ​​are obtained as the analysis results of taste components and aroma components.

[0131] (Item 6) In the method according to any one of Items 1 to 5, the content of the taste substance may be measured using a liquid chromatograph, and the content of the aroma substance may be measured using a gas chromatograph.

[0132] Since many taste substances are liquid or solid at room temperature, and many aroma substances are gaseous at room temperature, the method described in Section 6 can obtain accurate values ​​as the analysis results of taste components and aroma components.

[0133] (Clause 7) The method according to paragraph 4 may further comprise a step of identifying the taste substances and aroma substances from the components as substances that affect the difference in taste between the two or more foods, using a test result based on the analysis results of the components of the two or more foods.

[0134] According to the method described in paragraph 7, the evaluation of the taste of two or more foods is based on substances that affect the difference in taste between the two or more foods, which makes the evaluation of the taste of the two or more foods more accurate.

[0135] (Clause 8) The method of any one of clauses 1 to 7 may further include a step of identifying a food from the two or more foods that has a taste similar to the one food, based on a normalized value of the information value of each of the two or more foods.

[0136] The method described in Section 8 provides easy-to-understand information about which of two or more foods is similar to one food that has been used as the standard for normalization.

[0137] (Clause 9) An information processing device according to one embodiment may include one or more processors and a storage device storing a program that, when executed by the one or more processors, causes the one or more processors to implement the method described in any one of clauses 1 to 8.

[0138] According to the information processing device described in paragraph 9, an accurate evaluation of the taste of food is provided to general consumers.

[0139] (10th Clause) A taste information providing system according to one aspect may include the information processing device according to the 9th clause, and an analysis device that outputs a food analysis result to the information processing device.

[0140] According to the taste information providing system described in paragraph 10, accurate evaluations of food tastes are provided to general consumers.

[0141] (Item 11) A program according to one aspect may be executed by one or more processors to cause the one or more processors to implement the method according to any one of items 1 to 8.

[0142] The program described in paragraph 11 provides general consumers with an accurate evaluation of the taste of food.

[0143] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the description of the above-described embodiments, and is intended to include all modifications within the meaning and scope of the claims. Furthermore, it is intended that each technique in the embodiments can be implemented alone or, if necessary, in combination with other techniques in the embodiments to the extent possible.

[0144] 1 Taste information providing system, 20, 30, 40, 50, 60, 70, 80, 81 Screen, 81A Message, 100 Information processing device, 101 CPU, 102 Storage, 103 Input / output port, 200 Analysis device, 300 Mouse, 400 Keyboard, 500 Display device

Claims

1. 1. A method for providing a taste rating of two or more food products, comprising: acquiring information values ​​of one or more tastes for each of the two or more foods; generating adjustment information for one food selected from the two or more foods to use the information value as a standard for normalization; normalizing the information values ​​of each of the two or more foods other than the one food using the adjustment information; and outputting a normalized value of the information value for each of the two or more food items.

2. 2. The method for providing a taste evaluation of claim 1, wherein the step of outputting the normalized values ​​of the information values ​​includes displaying the normalized values ​​of the information values ​​as one graph for each of the two or more foods.

3. The method for providing a taste evaluation according to claim 2 , wherein the graph is a radar chart.

4. further comprising a step of acquiring the contents of taste substances and aroma substances of each of the two or more foods; 2. The method for providing a taste evaluation according to claim 1, wherein the step of obtaining an information value for each of the one or more tastes includes calculating the information value using the content of the taste substances and the content of the aroma substances.

5. The method for providing an evaluation of taste according to claim 4, wherein the contents of the taste substances and the aroma substances are measured using a liquid chromatograph or a gas chromatograph.

6. The content of the taste substance is measured using a liquid chromatograph; The method for providing a taste evaluation according to claim 4, wherein the content of the aroma substances is measured using a gas chromatograph.

7. 5. The method for providing a taste evaluation according to claim 4, further comprising a step of identifying the taste substances and the aroma substances from the components as substances that affect the difference in taste between the two or more foods, using the results of a test using the analytical results of each component of the two or more foods.

8. 2. The method for providing a taste evaluation of claim 1, further comprising a step of identifying a food from the two or more foods that has a taste similar to the one food based on the normalized value of the information value of each of the two or more foods.

9. one or more processors; a storage device storing a program that, when executed by the one or more processors, causes the one or more processors to implement the method according to claim 1 .

10. The information processing device according to claim 9 ; and an analysis device that outputs the analysis results of the food to the information processing device.

11. A program that, when executed by one or more processors, causes the one or more processors to perform the method of claim 1.