Beef supply program, beef supply system, beef supply method, beef evaluation program, and beef evaluation method

Abstract

The palatability of food after consumption is influenced not only by direct factors such as the ingredients and physical properties of the food, but also by indirect factors that depend on the physiological and psychological state of the consumer, and background factors that depend on awareness and knowledge such as culture and information. Given that the degree to which consumers like food and the factors that make them feel it is desirable differ depending on the attributes of the consumer, the main purpose of this technology is to effectively provide beef that matches the preferences of the consumer, based on the consumer's preferences. [Solution] As a result of diligent research, the inventors identified consumers who prefer fat as "fat-loving consumers" from a consumer group, and found that by providing these fat-loving consumers with beef containing a certain amount or more of aromatic components, it is possible to effectively provide beef that suits the preferences of such consumers.

Description

Technical Field

[0001] The present technology relates to a beef supply program, a beef supply system, a beef supply method, a beef evaluation program, and a beef evaluation method. More specifically, it relates to a technology for providing beef preferred by consumers who prefer beef with a high fat content ratio to such consumers.

Background Art

[0002] Conventionally, research has been conducted on factors that constitute the deliciousness of meat.

[0003] For example, the following Non-Patent Document 1 discloses the relationship between aroma and beef.

Prior Art Documents

Non-Patent Documents

[0004] Review Special Issue - Science of Food, Deliciousness, and Aging - 5 Aroma of Beef and Aging / Masanori Matsuki / Journal of the Japan Society of Taste and Odor Sciences Vol. 11 No. 2 PP. 137-146 August 2004

Summary of the Invention

Problems to be Solved by the Invention

[0005] When consumers eat food, they recognize sensory characteristics such as taste, smell, and texture, and use these to determine their preference for the food. On the other hand, the preference when eating food is affected by indirect factors that depend on the physiological and psychological states of consumers, and background factors that depend on consciousness and knowledge such as culture and information, in addition to direct factors such as the components and physical properties of the food. The degree to which consumers like food and the factors that make them feel favorable differ depending on the attributes of the consumers. Therefore, if it is possible to provide food that matches the preferences of a consumer based on the consumer's preference, the satisfaction of the consumer can be improved. However, when the same food is provided to multiple consumers, the satisfaction for one consumer may be high, but it may not affect the satisfaction for another consumer.

[0006] The primary objective of this technology is to effectively provide beef that matches the preferences of consumers, based on their individual tastes. [Means for solving the problem]

[0007] As a result of diligent research, the inventors identified consumers who prefer fat as "fat-loving consumers" from a consumer group, and found that by providing these fat-loving consumers with beef containing a certain amount or more of aromatic components, it is possible to effectively provide beef that suits the preferences of such consumers.

[0008] In other words, this technology identifies consumers who prefer beef with a high fat content as fat-loving consumers, and provides a beef supply program that offers these fat-loving consumers beef selected based on the content of one or more compounds chosen from lactones, furans, aldehydes, and pyrones. In the beef provision program of this technology, the identification may be made by identifying a consumer as a fat-preference consumer when the consumer's scoring tendency for evaluating the degree of preference for each of several beef products with different fat content percentages, based on sensory characteristics, is similar to the scoring tendency of a model consumer who prefers beef with a high fat content. In this case, the scoring tendency of the model consumer who prefers beef with a high fat content may be defined by having multiple subjects evaluate the degree of preference for multiple beef with different fat content based on sensory characteristics, performing cluster analysis based on the evaluation scores assigned to the multiple beef, identifying a group that prefers beef with a relatively high fat content, extracting the scoring characteristics of the identified group, and generalizing them. The cluster analysis may be performed based on data obtained by standardizing the evaluation scores for each type of beef and transforming the evaluation scores so that the standard deviation is 1. Furthermore, the cluster analysis may be performed using Ward's method. In the beef supply program of this technology, beef with a high fat content, which is preferred by fat-loving consumers, may be beef containing 25g or more of fat per 100g of beef. Furthermore, this technology provides a beef supply system that implements the beef supply program of this technology.

[0009] Next, this technology identifies consumers who prefer beef with a high fat content as fat-loving consumers, and provides a method for providing beef to these fat-loving consumers, which is selected based on the content of one or more compounds chosen from lactones, furans, aldehydes, and pyrones. Furthermore, this technology provides a beef evaluation program that assesses whether beef meets the preferences of fat-loving consumers, based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones contained in the beef. Furthermore, this technology provides a beef evaluation method that assesses whether beef meets the preferences of fat-loving consumers, based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones contained in the beef. [Brief explanation of the drawing]

[0010] [Figure 1] This shows the workflow for the beef supply program. [Figure 2] This is an example of a questionnaire for evaluating the sensory characteristics of beef. [Figure 3] This result identifies a group that prefers beef with a relatively high fat content, based on cluster analysis conducted by multiple subjects to evaluate the sensory characteristics of several types of beef with different fat content. [Figure 4] This is an example of a questionnaire listing several terms related to the aroma of beef. [Figure 5] This figure shows the correlation between consumer groups classified based on their preference for beef based on its fat content and terms related to aroma. [Modes for carrying out the invention]

[0011] Preferred embodiments of the present technology are described below. However, the embodiments shown below are merely examples of typical embodiments of the present technology, and the present technology is not limited to these preferred embodiments, but can be freely modified within the scope of the present technology.

[0012] [Beef Provision Program] Consumer preferences for food and the factors that make them find it appealing are influenced by factors other than direct factors such as the food's ingredients and physical properties. Therefore, this technology identifies consumers with specific preferences and provides them with beef that aligns with those preferences, thereby increasing their satisfaction. More specifically, in this technology's beef provision program, consumers who prefer beef with a high fat content are identified as fat-preference consumers, and these identified fat-preference consumers are provided with beef selected based on the content of one or more compounds chosen from lactones, furans, aldehydes, and pyrones.

[0013] In this specification, "program" refers to a workflow that systematically organizes multiple processes in a sequential manner. In the beef supply program of this technology, for example, the program is executed using a computer or the like based on the workflow shown in Figure 1. The details of each process described in the workflow of Figure 1 will be explained below. The beef supply program of this technology may also be recorded on a recording medium that can be read by a computer or the like.

[0014] <Identifying consumers who prefer beer> In the beef supply program of this technology, as step S101 of the workflow in Figure 1, "Identification of Fat-Preferenced Consumers," consumers who prefer beef with a high fat content are identified from among consumers as fat-preferenced consumers who are the target of the beef supply program of this technology.

[0015] Here, the identification is made when the consumer's scoring tendency for evaluating the degree of preference for each of several beef products with different fat content percentages, based on sensory characteristics, is similar to the scoring tendency of a model consumer who prefers beef with a high fat content, and the consumer is identified as a fat-preference consumer.

[0016] In this specification, "evaluation of sensory characteristics" refers to evaluating the characteristics of an object using the five human senses such as smell and taste. That is, "evaluation of the sensory characteristics of beef by consumers" means that consumers evaluate the characteristics of the target beef using their five senses. Such evaluation is, for example, that each consumer subjectively scores and evaluates the target beef based on their five senses using a questionnaire as shown in FIG. 2. Note that since such evaluation is subjectively scored by consumers based on their five senses, different scoring results are obtained for each consumer depending on their preferences. Also, the questionnaire shown in FIG. 2 is merely an example of a questionnaire for evaluating the sensory characteristics of beef, and the questionnaire items are not limited to this example and may be modified or added as appropriate.

[0017] Here, "beef" refers to the muscle tissue of cattle belonging to the Bovidae family for food use. Such cattle are not particularly limited. The beef targeted by this technology has greatly different components such as the fat content ratio depending on factors such as breeding conditions, breed, genetics, growth stage, etc. In particular, the fat content ratio is a factor that greatly divides consumer preferences because it also affects sensory characteristics such as the tenderness of beef. The inventors have found that consumers who prefer beef with a high fat content ratio have an improved satisfaction by ingesting beef with a high content ratio of specific aroma components, and conversely, consumers who do not prefer beef with a high fat content ratio do not have much improvement in satisfaction by ingesting beef with a high content ratio of such specific aroma components. That is, the target for providing beef by the beef providing program of this technology is the group of consumers who prefer beef with a high fat content ratio.

[0018] The fat content rate in beef varies depending on the part of the meat. Generally, it is low in imported beef such as that from Australia or the United States, or beef of dairy breeds, and tends to be high in beef produced in Japan (especially "Japanese Black cattle"). Consumers who prefer beef with a high fat content rate, for example, significantly respond to the sweet fruit-like aroma components and fatty fat-like aroma components felt in Japanese Black cattle beef, and it has been found that by consuming beef with a high content rate of such aroma components, the satisfaction can be further improved. On the other hand, as described above, conversely, consumers who do not prefer beef with a high fat content rate have been found not to have much improvement in satisfaction by consuming beef with a high content rate of the above aroma components.

[0019] In this specification, "beef with a high fat content rate" refers to, for example, beef containing fat at a rate of 25 g or more (25% by weight or more), 30 g or more (30% by weight or more), 35 g or more (35% by weight or more), 40 g or more (40% by weight or more), etc. per 100 g of beef. The upper limit of the fat contained in "beef with a high fat content rate" is not particularly limited and is specified within the range of fat that can be contained in beef. Here, the fat content in the above beef can be measured using the value measured in accordance with the nuclear magnetic resonance method defined in AOAC Official Method 2008.06.

[0020] Since there is a physical upper limit to the range of fat that can be contained in beef, when evaluating beef based only on the fat content rate, if the fat content rate in beef exceeds a certain value, it has been difficult to further improve the satisfaction of consumers who prefer beef with a high fat content rate.

[0021] Whether a target consumer prefers beef with a high fat content can be determined by having them consume multiple types of beef with different fat content and evaluating their preference based on their own criteria. Therefore, in the beef provision program of this technology, identifying whether a target consumer is a fat-preference consumer can be done, for example, by comparing the scoring trend of the consumer's evaluation of the degree of preference for each type of beef based on sensory characteristics with the scoring trend of a model consumer who prefers beef with a high fat content, which is determined based on previously acquired data. If the scoring trends of the two are similar, the consumer can be identified as a fat-preference consumer.

[0022] Here, the type of beef used to identify the scoring tendency that the target consumer uses to determine whether or not they prefer beef with a high fat content requires a minimum number of data points necessary for basic statistical calculations, for example, n=3 or more. Furthermore, from the viewpoint of improving the accuracy of the statistical calculations, a larger number of data points is preferable. For this reason, the type of beef used for the above determination can be adjusted to the extent that multiple types of beef with different fat content and characteristics can be prepared. In this technology, depending on the availability of beef, for example, n=5 or more, 7 or more, 10 or more, etc., can be used to identify the scoring tendency of the target consumer.

[0023] The scoring tendencies of the model consumers who prefer beef with a high fat content can be determined, for example, by having multiple subjects evaluate the degree of preference for multiple types of beef with different fat content based on their sensory characteristics, and then performing cluster analysis based on the evaluation scores assigned to these multiple types of beef. This allows for the identification of a group that prefers beef with a relatively high fat content, and the scoring tendencies of that identified group can then be used to define the scoring tendencies.

[0024] To identify the scoring tendencies of model consumers who prefer beef with a high fat content, the number of subjects required for cluster analysis must be sufficient to identify multiple clusters. In this technology, at least enough subjects are needed to identify two clusters: a group of consumers who prefer beef with a high fat content and a group of consumers who do not. From the perspective of ensuring the reliability of the distance and variance between identified clusters, a larger number of subjects for data acquisition is preferable. The number of subjects required for the above identification can be adjusted within the range of subjects that can be prepared, for example, 50 or more, 100 or more, 150 or more, 200 or more, etc. These subjects are preferably randomly selected from general consumers who have not undergone any selection or training.

[0025] Furthermore, when identifying the scoring tendencies of model consumers who prefer beef with a high fat content, it is preferable to use the same type of beef that the target consumers used to determine whether or not they prefer beef with a high fat content. For the same reason, it is preferable to use the same type and number of types of beef as the target consumers used to determine whether or not they prefer beef with a high fat content when identifying the scoring tendencies of model consumers who prefer beef with a high fat content. By matching the type of beef used in both cases, the scoring conditions for both cases are standardized. This allows for a favorable comparison of the scoring tendencies of both cases.

[0026] Ideally, the beef used to identify the scoring tendencies of model consumers who prefer beef with a high fat content and the beef used to determine whether the target consumers prefer beef with a high fat content should be the same. However, since the scoring periods for both usually do not coincide, this can be addressed by using a sample set of beef that includes the same type of beef.

[0027] Here, "beef of the same type" refers to beef whose composition is similar due to similar factors affecting the beef's composition and physical properties, such as the production area, rearing conditions, breed, genetics, and growth stage.

[0028] In this technology, in order to identify the scoring tendencies of model consumers who prefer beef with a high fat content, it is desirable that all subjects participating in the evaluation evaluate the degree of preference for all beef varieties with different fat content based on their sensory characteristics. Furthermore, depending on the types (number) of beef used in the evaluation, subjects may not be able to evaluate all of the beef at once. For this reason, the combination of subjects and the beef to be evaluated may be planned using a Latin square method, and the timing of the evaluation may be adjusted.

[0029] As described above, by using multiple prepared subjects and multiple beef samples with different fat content percentages, and performing cluster analysis using the evaluation scores based on sensory characteristics assigned by these subjects to the beef samples as the base data, it is possible to identify consumer groups that prefer beef with a relatively high fat content.

[0030] In this technology, by extracting and generalizing the scoring characteristics of the consumer group identified above as preferring beef with a relatively high fat content, it is possible to define the scoring tendencies of a model consumer who prefers beef with a high fat content.

[0031] In this technology, it is determined whether the scoring trend of consumers, based on sensory characteristics, for each type of beef they rate is similar to the scoring trend of a model consumer who prefers beef with a high fat content. If it is determined that they are similar, the consumer is identified as a fat-preference consumer. The above determination is made based on whether the consumer's scoring trend possesses the scoring characteristics of the group of consumers identified as preferring beef with a relatively high fat content.

[0032] In this technology, the cluster analysis may use evaluation scores based on sensory characteristics assigned to the beef by the multiple subjects as the base data. Alternatively, the evaluation scores for each of the beef may be standardized based on the average score (subtracting the average score from the evaluation score and dividing the resulting value by the standard deviation), and the analysis may be performed based on data where the standard deviation is 1.

[0033] In this technology, the cluster analysis can be performed by any method. For example, it can be performed by methods such as Ward's method or the group average method.

[0034] <Selection of beef> Next, in the beef supply program of this technology, as step S102 of the "Beef Selection" process in the workflow of Figure 1, beef that can improve the satisfaction of fat-loving consumers, as identified above, is selected based on specific criteria. The selection of this beef is based on the content of aroma components that are significantly associated with the aroma of beef with a high fat content (so-called Wagyu beef). More specifically, the selection is based on the content of specific aroma components such as sweet fruity or milky aroma components, fatty aroma components, savory or burnt aroma components, almond-like aroma components, and caramel-like aroma components. Such aroma components are envisioned to be, for example, one or more compounds selected from lactones, furans, aldehydes, and pyrones.

[0035] For consumers who prefer fatty beef, the beef offered can be selected from the aforementioned "beef with a high fat content" that meets the criteria for the content of specific aroma components, as described above. This allows for the selection of beef with a high fat content that better suits the preferences of fat-loving consumers. In particular, even if the fat content of the beef exceeds a certain value, evaluating the beef based on the content of these aroma components can further improve the satisfaction of consumers who prefer beef with a high fat content.

[0036] Examples of the aforementioned specific aroma components include lactones, which are sweet, fruity, or milky aroma components. Examples of lactones include γ-butyrolactone, γ-crotonolactone, γ-dodecalactone, δ-dodecalactone, and δ-tetradecalactone.

[0037] As a selection criterion for beef in this technology's beef supply program, for example, when using lactone content as a criterion, the γ-butyrolactone content is preferably 1500 ng / g or more, more preferably 1600 ng / g or more, even more preferably 1700 ng / g or more, and particularly preferably 1800 ng / g or more. The γ-crotonolactone content is preferably 1000 ng / g or more, more preferably 1200 ng / g or more, even more preferably 1300 ng / g or more, and particularly preferably 1500 ng / g or more. Next, the γ-dodecalactone content is preferably 800 ng / g or more, and particularly preferably 1000 ng / g or more. Next, the δ-dodecalactone content is preferably 165 ng / g or more, even more preferably 170 ng / g or more, and particularly preferably 180 ng / g or more. Next, the δ-tetradecalactone content is preferably 5000 ng / g or more, more preferably 5500 ng / g or more, and particularly preferably 6000 ng / g or more. The upper limit of the lactone content is not particularly limited and is specified within the range that can be contained in beef.

[0038] In the beef supply program of this technology, one of the aroma components used as a selection criterion for beef is, for example, aldehydes, which are fatty, fat-like aroma components. Examples of aldehydes include furfural and phenylacetaldehyde.

[0039] As a selection criterion for beef in this technology's beef supply program, for example, when using aldehyde content as a criterion, the furfural content is preferably 1100 ng / g or more, more preferably 1500 ng / g or more, and particularly preferably 2000 ng / g or more. Similarly, the phenylacetaldehyde content is preferably 3500 ng / g or more, more preferably 5000 ng / g or more, and particularly preferably 7000 ng / g or more. The upper limit of the above aldehyde content is not particularly limited and is specified within the range that can be contained in beef.

[0040] In the beef supply program of this technology, the selection criteria for beef include aroma components such as furans, which bring out savory, burnt, and almond-like aromas. Examples of furans include hydroxymethylfurfural and furfural, which is classified as an aldehyde.

[0041] As a selection criterion for beef in this technology's beef supply program, for example, if the furan content is used as a criterion, the hydroxymethylfurfural content is preferably 1800 ng / g or more, more preferably 2000 ng / g or more, and particularly preferably 3000 ng / g or more. The upper limit of the above furan content is not particularly limited and is specified within the range that can be contained in beef.

[0042] In the beef supply program of this technology, one of the selection criteria for beef is the aroma components, such as pyrones, which produce a sweet aroma similar to caramel. In particular, pyrones contained in beef can be evaluated as aromas associated with vanilla-like or fruity sweetness. Examples of pyrones include maltol.

[0043] As a selection criterion for beef in this technology's beef supply program, for example, if the pylon content is used as a criterion, the maltol content is preferably 15 ng / g or more, more preferably 20 ng / g or more, and particularly preferably 30 ng / g or more. The upper limit of the pylon content mentioned above is not particularly limited and is specified within the range that can be contained in beef.

[0044] In this technology's beef supply program, the aroma components listed above (lactones, furans, aldehydes, and pyrones) can be selected based on the content of individual compounds to better suit the preferences of fat-loving consumers, or they can be selected based on the combination of the content of multiple compounds.

[0045] The content of the above-mentioned aroma components can be suitably measured using a gas chromatograph-mass spectrometer (GC-MS) in accordance with the measurement method described in section 6, Aroma Components, of the "Livestock Improvement Center Technical Manual 21 Manual for Physicochemical Analysis and Sensory Evaluation of Meat, National Livestock Improvement Center."

[0046] <Beef provision> In this technology's beef supply program, step S103 of the "Beef Supply" process in the workflow shown in Figure 1 provides beef selected in step S102 from among beef with a high fat content to fat-loving consumers identified in step S101. This effectively provides fat-loving consumers with beef that matches their preferences, potentially improving their satisfaction. On the other hand, for consumers not identified as fat-loving consumers (consumers who do not prefer beef with a high fat content), the process of selecting beef that does not affect their satisfaction is omitted, and beef with a low fat content can be effectively provided. This efficiently improves the satisfaction of these consumers as well.

[0047] [Beef supply system] This technology can also be implemented as a beef supply system that implements the beef supply program of this technology.

[0048] Here, "system" refers to a computing environment constructed by interconnecting processing units such as personal computers to achieve a specific function or purpose.

[0049] The beef supply system of this technology can execute the beef supply program of this technology as a whole system by implementing the beef supply program of this technology.

[0050] Furthermore, each processing unit constituting the beef supply system of this technology may be a finished product that functions independently, or it may be incorporated into the system to function as a whole system.

[0051] [Beef serving method] This technology may also be implemented as a beef provision method in which, in step S101 of the workflow shown in Figure 1, fat-loving consumers are identified, beef is selected from among beef with a high fat content in step S102, and the selected beef is provided to the identified fat-loving consumers in step S103. In this case, the beef provision method of this technology allows the work that can be performed in each step of the beef provision program of this technology to be performed in each step.

[0052] [Beef Evaluation Program] This technology may be implemented as a beef evaluation method that assesses whether beef with a high fat content meets the preferences of fat-loving consumers, based on the content of the aforementioned specific aroma components. In particular, since there is a physical upper limit to the range of fat that can be contained in beef, even if the fat content in beef exceeds a certain value, evaluating the beef based on the content of these aroma components can further improve the satisfaction of consumers who prefer beef with a high fat content. The specific aroma components that can serve as the standard in this case are envisioned to be one or more compounds selected from, for example, lactones, furans, aldehydes, and pyrones, similar to the beef provision program of this technology.

[0053] [Beef Evaluation Method] This technology may be implemented as a beef evaluation program that evaluates whether beef with a high fat content meets the preferences of fat-loving consumers, based on the content of the aforementioned specific aroma components. In this case, the criteria that can be adopted in the beef evaluation program of this technology can also be suitably adopted in the beef evaluation method of this technology.

[0054] Furthermore, this technology can be configured as follows: [1] Consumers who prefer beef with a high fat content are identified as fat-loving consumers, A beef supply program that provides the aforementioned fat-loving consumers with beef selected based on the content of one or more compounds chosen from lactones, furans, aldehydes, and pyrones. [2] The beef supply program according to [1], wherein the identification is made by identifying a consumer as a fat-preference consumer when the consumer's scoring tendency for evaluating the degree of preference for each of the multiple beef products with different fat content based on sensory characteristics is similar to the scoring tendency of a model consumer who prefers beef with a high fat content. [3] The beef serving program described in [2] is defined by having multiple subjects evaluate the degree of preference for multiple beef with different fat content based on sensory characteristics, performing cluster analysis based on the evaluation scores given to the multiple beef, thereby identifying a group that prefers beef with a relatively high fat content, extracting the scoring characteristics of the identified group, and generalizing them. [4] The cluster analysis is performed based on data obtained by standardizing the evaluation scores for each type of beef and transforming the evaluation scores so that the standard deviation is 1, as described in [3]. [5] The cluster analysis is performed by Ward's method, as described in [3] or [4], for the beef supply program. [6] The beef with a high fat content is beef containing 25g or more of fat per 100g of beef, as described in any of [1] to [5]. A beef supply system that implements any of the beef supply programs described in [7], [1], through [6]. [8] Consumers who prefer beef with a high fat content are identified as fat-loving consumers, A method for providing beef to the aforementioned fat-loving consumers, comprising providing beef selected based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones. [9] A beef evaluation program that assesses whether beef meets the preferences of fat-loving consumers based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones contained in the beef.

[10] A beef evaluation method that evaluates whether beef is in line with the preferences of fat-loving consumers, based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones contained in the beef. [Examples]

[0055] The technology will be described in detail below based on specific examples. However, this technology is not limited in any way to the examples shown below.

[0056] [Generalization of the scoring of model consumers who prefer beef with a high fat content] <Beef used for evaluation> To identify model consumers who prefer beef with a relatively high fat content, seven types of beef (longissimus dorsi muscle) with different rearing conditions, breeds, genetics, and growth stages were prepared. Table 1 shows these beef samples and their moisture and fat content. The moisture content of the beef was measured according to the microwave drying method specified in AOAC Official Method 2008.06. The fat content of the beef was measured according to the nuclear magnetic resonance method specified in AOAC Official Method 2008.06.

[0057] [Table 1]

[0058] Each of the seven types of beef listed above was thawed and prepared into a 4mm thick, 4cm diameter disc. Both sides were then grilled for 30 seconds each on a 180°C household induction hot plate to create test beef samples.

[0059] <Evaluation of beef by test subjects> In the first evaluation test, 29 participants, in the second evaluation test, 25 participants, in the third evaluation test, 29 participants, and in the fourth evaluation test, 27 participants were randomly selected from general consumers who had not been selected or trained (a total of 110 participants). They consumed the seven types of beef mentioned above and evaluated the degree of their preference according to their own standards.

[0060] The seven types of beef mentioned above were evaluated by a total of 110 subjects, with evaluation timings allocated systematically based on the Latin grid method. Table 2 shows the allocation of each type of beef to the subjects based on the Latin grid method during the first evaluation trial. The same method as shown in Table 2 was used for the allocation of each type of beef to the subjects in the second through fourth evaluation trials.

[0061] [Table 2]

[0062] The subjects evaluated the seven types of beef described above using the questionnaire shown in Figure 2, according to the aforementioned allocation, under the evaluation test conditions described below. The scores for the evaluation were based on the eight categories in the questionnaire shown in Figure 2, ranging from "very undesirable" to "very desirable," with "very undesirable" being the lowest score (1 point) and "very desirable" being the highest score (8 points).

[0063] <Conditions for the evaluation test> Evaluation was conducted in an environment where each subject was isolated by a desk partition (room temperature: 21°C, humidity: 50%, under fluorescent lighting). After evaluating one beef sample, a one-minute break is taken before evaluating the next beef sample.

[0064] <Cluster analysis of the results of the subjects' evaluation of beef> Based on the evaluation scores for the "Overall, including texture" item in the questionnaire shown in Figure 2, the average score for each type of beef was calculated. Subsequently, using this average score as a baseline, cluster analysis was performed using Ward's method on data obtained by transforming the evaluation scores so that the standard deviation was 1. Figure 3 shows the dendrogram created by the cluster analysis and the relationship between the groups identified as clusters.

[0065] As shown in the tree diagram in Figure 3, the subjects who participated in the evaluation test were identified as a total of four groups, Groups 1 through 4, as described below. <Group 1> : A group of consumers who tend to avoid beef with a relatively high fat content (a group of consumers who prefer lean meat with a low fat content). <Group 2> A group of consumers who prefer beef with an intermediate fat content. <Group 3> A group of consumers who prefer beef with a high fat content and tend to avoid beef with a low fat content. <Group 4> A group of consumers who prefer beef with a high fat content.

[0066] Table 3 shows the evaluation results of seven types of beef by 29 subjects in the first evaluation trial, along with the assigned groups. Similarly, Table 4 shows the results of the second evaluation trial, Table 5 shows the results of the third evaluation trial, and Table 6 shows the results of the fourth evaluation trial.

[0067] [Table 3]

[0068] [Table 4]

[0069] [Table 5]

[0070] [Table 6]

[0071] In this evaluation test, based on the results described above, consumers in groups 3 and 4 were identified as groups that prefer beef with a high fat content. Based on this, the scoring characteristics of this group that prefers beef with a high fat content were extracted and generalized to create a scoring trend for a model consumer that prefers beef with a high fat content.

[0072] [Evaluation based on sensory characteristics and its correlation with aroma components] In this evaluation test, in addition to the subjects' responses to the questionnaire shown in Figure 2, an evaluation using the Check-All-That-Apply (CATA) method was conducted using a list of multiple aroma-related terms. Specifically, for each of the seven types of beef, the subjects selected one or more aroma-related terms from the questionnaire shown in Figure 4 that applied.

[0073] Figure 5 shows the changes in preference ratings for each of the four consumer groups identified above, when they perceived the scents listed in the questionnaire in Figure 4. The analysis in Figure 5 was performed using data compiled from the degree of preference perceived by subjects according to their own standards, based on the questionnaire in Figure 2, and the evaluation results for each term, based on the questionnaire in Figure 4. Penalty analysis was used to correlate this data.

[0074] The results in Figure 5 show that consumers in groups 3 and 4, who prefer beef with a high fat content (so-called Wagyu beef), responded significantly more to aroma-related terms and their preference ratings changed more than consumers in groups 1 and 2, who do not prefer beef with a high fat content.

[0075] [Identifying consumers with a preference for fat] If the target consumer evaluates the degree of preference for each type of beef based on sensory characteristics under the same conditions as in the evaluation test described above, it is possible to determine whether or not they possess the characteristics of the scoring tendency of the model consumer who prefers beef with a high fat content, based on the results of the model consumer's scoring tendency. If, as a result of the above determination, the target consumer's scoring tendency possesses the characteristics of the model consumer's scoring tendency, it is determined that the target consumer's scoring tendency is similar to that of the model consumer, and the target consumer can be identified as a fat-preference consumer.

[0076] [Identifying beef that aligns with the preferences of fat-loving consumers] For the seven types of beef used in the evaluation test described above, measurement samples were prepared by processing each under the same conditions as those used to prepare the test samples. The percentage of aroma components related to sweetness, milky odor, and greasy odor that consumers who prefer beef with a high fat content would react to significantly was measured using a gas chromatograph-mass spectrometer (GC-MS) in accordance with the measurement method described in Section 6, Aroma Components, of the "Livestock Improvement Center Technical Manual 21 Manual for Physicochemical Analysis and Sensory Evaluation of Meat, National Livestock Improvement Center." The measured values ​​were calculated as the least squares mean by performing an analysis of variance based on the results of measurements taken with n=3 samples. The results are shown in Table 7.

[0077] [Table 7]

[0078] The results in Table 7 above also show that beef with a high fat content tends to have a relatively high content of aroma components related to sweetness, milky odor, and greasy smell. Based on these results, by selecting beef with relatively high content of these aroma components from among "beef with a high fat content," it is possible to select beef with a high fat content that better suits the preferences of fat-loving consumers.

[0079] Furthermore, for "beef with a high fat content," the content of these aromatic components can be used as a criterion to appropriately evaluate whether the beef meets the preferences of fat-loving consumers. In particular, even if the fat content of the beef exceeds a certain value, evaluating the beef based on the content of these aromatic components can further improve the satisfaction of consumers who prefer beef with a high fat content. Moreover, it can also serve as an indicator for considering breeding methods to ensure that the content of the above-mentioned aromatic components is above a certain level for cattle related to "beef with a high fat content."

Claims

1. Using a computer, Consumers who prefer beef with a high fat content are identified as fat-loving consumers. A beef supply program that selects beef to be offered to the aforementioned fat-loving consumers based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones.

2. The beef serving program according to claim 1, wherein the identification is made by identifying a consumer as a fat-preference consumer when the consumer's scoring tendency for evaluating the degree of preference for each of the multiple beef products with different fat content percentages based on sensory characteristics is similar to the scoring tendency of a model consumer who prefers beef with a high fat content.

3. The beef serving program according to claim 2, wherein the scoring tendencies of model consumers who prefer beef with a high fat content are defined by having multiple subjects evaluate the degree of preference for multiple beef with different fat content based on sensory characteristics, performing cluster analysis based on the evaluation scores assigned to the multiple beef, identifying a group that prefers beef with a relatively high fat content, extracting the scoring characteristics of the identified group, and generalizing them.

4. The beef supply program according to claim 3, wherein the cluster analysis is performed based on data obtained by standardizing the evaluation scores for each beef item and transforming the evaluation scores so that the standard deviation is 1.

5. The beef serving program according to claim 3, wherein the cluster analysis is performed by Ward's method.

6. The beef supply program according to claim 1, wherein the beef with a high fat content is beef containing 25g or more of fat per 100g of beef.

7. A beef serving system that implements the beef serving program described in any one of claims 1 to 6.

8. Using a computer, Consumers who prefer beef with a high fat content are identified as fat-loving consumers. A method for providing beef to the aforementioned fat-loving consumers, comprising selecting beef based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones.

9. Using a computer, A beef evaluation program that assesses whether beef meets the preferences of fat-loving consumers based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones in the beef.

10. Using a computer, A beef evaluation method that assesses whether beef meets the preferences of fat-loving consumers, based on the content of one or more compounds selected from lactones, furans, aldehydes, and pyrones contained in the beef.

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