Peppery degree quantitative evaluation method based on individual spicy eating habits and capsaicin content

Abstract

The invention discloses a pungency degree quantitative evaluation method based on individual pungency eating habits and capsaicin content, and relates to the technical field of scientific sensory evaluation and computational modeling of food, and the method comprises the following steps: collecting pungency eating information of an interviewee; meanwhile, physiological change information of the interviewee after eating the pepper is recorded through wearable equipment, the capsaicin content of different pepper samples is measured, a multi-sense pungency degree sensing model is constructed, and the actual feeling of the individual on capsaicin is quantified; calculating a basic pungency degree quantized value of the interviewee; a pungency degree calculation formula is corrected in combination with a multi-sensory perception model, so that individual physiological change factors can be comprehensively considered; and according to a calculation result, dividing the interviewees into different spicy food grades. According to the method, peppery degree calculation is corrected in combination with multiple sensory factors, the actual experience of individuals on peppery taste is comprehensively evaluated, the accuracy is improved, the standardized peppery degree index is established through normalization processing and tolerance grading, and the peppery degree experiences of different crowds have comparability.

Description

Technical Field

[0001] The present invention relates to the technical field of sensory evaluation and computational modeling in food science, and particularly relates to a method for quantitatively evaluating spiciness based on individual chili-eating habits and capsaicin content. Background Art

[0002] Spiciness is a food characteristic widely loved by consumers globally, which is mainly caused by chemical components such as capsaicin stimulating the TRPV1 receptor (transient receptor potential vanilloid 1). In the food industry and consumer market, consumers' tolerance to spiciness varies significantly due to factors such as individual chili-eating habits, intake, and physiological characteristics, resulting in a large difference in the spiciness perception of foods with the same capsaicin content among different populations.

[0003] Currently, although chemical measurement methods in the laboratory can accurately determine the capsaicin content, they cannot reflect an individual's true spiciness experience and lack consideration of chili tolerance and individual physiological differences; while spiciness quantification evaluation methods only estimate spiciness based on capsaicin concentration, ignoring individual chili-eating habits and physiological sensory factors, resulting in poor adaptability to individual spiciness perception.

[0004] Therefore, there is a lack of an accurate spiciness evaluation method that can combine individual chili-eating habits, intake, and capsaicin concentration, and simultaneously consider multiple sensory factors, so that its evaluation results can be applied to research such as food formula optimization, healthy diet guidance, personalized recommendations for consumers, and sensory evaluation. Summary of the Invention

[0005] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the specification of this application, to avoid obscuring the purpose of this part, the abstract, and the title, and such simplifications or omissions shall not be used to limit the scope of the present invention.

[0006] In view of the problems existing in the above-mentioned prior art, the present invention is proposed.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] A method for quantitatively evaluating spiciness based on individual chili-eating habits and capsaicin content, the method comprising the following steps:

[0009] Step 1: By means of a chili-eating visit survey, collect the chili-eating information of the interviewees, and at the same time record the physiological change information of the interviewees after eating chili through a wearable device, and combine the chili-eating information and the physiological change information to establish a multi-dimensional chili tolerance profile for individuals;

[0010] Step 2: According to the types of peppers filled in by the interviewees, collect multiple types of peppers that match the actual consumption of the interviewees. Analyze the pepper-eating habits of different individuals through machine learning algorithms, and match the type of pepper that is closest to the interviewees' taste preferences.

[0011] Step 3: Conduct laboratory tests on the collected pepper samples to determine the capsaicin content of different pepper samples, so as to establish the spiciness benchmark data for different types of peppers. Combine the capsaicin content data, the interviewees' subjective spiciness scores, and the physiological response data to construct a multi-sensory spiciness perception model to quantify the actual feelings of individuals towards capsaicin.

[0012] Step 4: Calculate the basic spiciness quantification value of the interviewees based on their pepper-eating frequency, intake, and the capsaicin content of the corresponding pepper samples. Combine the multi-sensory perception model to modify the spiciness calculation formula so that it can comprehensively consider individual physiological change factors.

[0013] Step 5: Normalize the spiciness quantification values of different individuals to establish a unified pepper-eating grade standard. According to the calculation results, divide the interviewees into different pepper-eating grades.

[0014] As a preferred solution of the spiciness quantification evaluation method based on individual pepper-eating habits and capsaicin content described in the present invention, wherein: the pepper-eating information of the interviewees includes: the frequency of eating peppers in the past period of time; the number of meals of eating peppers per day and the intake per meal; the type of pepper; the interviewees' subjective spiciness scores for different types of peppers; the physiological change information of the interviewees includes: sweating information, heart rate change information, skin temperature change information.

[0015] As a preferred solution of the spiciness quantification evaluation method based on individual pepper-eating habits and capsaicin content described in the present invention, wherein: the process of constructing the multi-sensory spiciness perception model is as follows:

[0016] S301: First, construct a physiological response index P according to the physiological change information of the interviewees r ;

[0017] S302: Determine the basic contribution value of capsaicin content to spiciness: α·C p β ; where α represents the adjustment factor of the overall spiciness, β represents the exponential influence factor of capsaicin content on the perceived spiciness; C p represents the capsaicin content of the laboratory-tested pepper samples;

[0018] S303: According to the physiological response index P r and the basic contribution value of capsaicin content to spiciness: α·C p β, and the subjective spiciness scores S of the interviewees for different types of peppers are used to calculate the comprehensive spiciness perception value L of the interviewees for peppers by using a non - linear combination function. p ; The calculation formula is:

[0019]

[0020] Among them, γ represents the subjective spiciness enhancement factor; δ represents the physiological response adaptability adjustment coefficient; η represents the exponential term adjustment parameter.

[0021] As a preferred scheme of the spiciness quantification and evaluation method based on individual pepper - eating habits and capsaicin content described in the present invention, wherein: the physiological response index P r The selected physiological indicators include: heart rate change ΔHR; skin temperature change ΔT s ; sweating amount SW; The calculation formula is:

[0022]

[0023] Among them, w1, w2, w3 are the weight coefficients corresponding to different physiological indicators, and P r ∈[0,1], indicating from no response 0 to extremely strong physiological response 1.

[0024] As a preferred scheme of the spiciness quantification and evaluation method based on individual pepper - eating habits and capsaicin content described in the present invention, wherein: the basic spiciness quantification value L b The calculation method is:

[0025] S401: First, calculate the annual total intake according to the pepper - eating frequency and single - intake amount in the pepper - eating information filled in by the interviewee;

[0026] S402: Combine the annual total intake and the capsaicin content to calculate the annual total capsaicin intake;

[0027] S403: Obtain the capsaicin intake tolerance factor through the annual total capsaicin intake, and obtain the pepper - eating frequency tolerance factor through the pepper - eating frequency, and the sum of the two represents the basic spiciness quantification value L b .

[0028] As a preferred scheme of the spiciness quantification and evaluation method based on individual pepper - eating habits and capsaicin content described in the present invention, wherein: the calculation formula of the capsaicin intake tolerance factor is:

[0029] The calculation formula of the pepper - eating frequency tolerance factor is:

[0030] Among them, respectively represent the weights of the capsaicin intake tolerance factor and the spicy food frequency tolerance factor in the overall spiciness perception; C a represents the annual capsaicin intake; F s represents the spicy food frequency.

[0031] As a preferred embodiment of the spiciness quantification and evaluation method based on individual spicy food habits and capsaicin content described in the present invention, wherein: the comprehensive spiciness perception value L obtained through the multi-sensory perception model p is used to correct the basic spiciness quantification value L b , then the corrected spiciness quantification value is: L i = θ1L b + θ2L p .

[0032] Wherein, θ1 and θ2 respectively represent the adjustment coefficients corresponding to the basic spiciness quantification value and the comprehensive spiciness perception value.

[0033] As a preferred embodiment of the spiciness quantification and evaluation method based on individual spicy food habits and capsaicin content described in the present invention, wherein: normalize the individual corrected spiciness quantification value i calculated for all interviewees, and establish an individual spicy food tolerance level according to the normalized L value, which are respectively:

[0034] The first threshold ≤ L < the second threshold, intolerance level;

[0035] The second threshold ≤ L < the third threshold, low tolerance level;

[0036] The third threshold ≤ L < the fourth threshold, medium tolerance level;

[0037] The fourth threshold ≤ L ≤ the fifth threshold, high tolerance level.

[0038] The present invention also discloses a computer device, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it realizes the steps of the above-mentioned spiciness quantification and evaluation method based on individual spicy food habits and capsaicin content.

[0039] The present invention also discloses a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it realizes the steps of the above-mentioned spiciness quantification and evaluation method based on individual spicy food habits and capsaicin content.

[0040] Advantages of the present invention:

[0041] 1. The present invention combines the spicy food frequency, intake and long-term capsaicin exposure level of an individual to construct a personalized spiciness calculation model, realizing accurate spiciness evaluation for different individuals; using a logarithmic function to simulate the decreasing effect of spiciness tolerance, making the calculation closer to the actual situation.

[0042] 2. The present invention combines multi-sensory factors to correct the spiciness calculation, comprehensively evaluate the individual's true experience of spiciness, improve the accuracy, and establish a standardized spiciness index through normalization processing and tolerance level division, making the spiciness experiences of different populations comparable, and it is applicable to scenarios such as the food industry and personalized recommendations for consumers. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them:

[0044] Figure 1 It is a schematic diagram of the principle framework of a spiciness quantification and evaluation method based on an individual's spicy food habit and capsaicin content proposed by the present invention;

[0045] Figure 2 It is a schematic diagram of the method flow of a spiciness quantification and evaluation method based on an individual's spicy food habit and capsaicin content proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following will give a detailed description of the specific embodiments of the present invention in conjunction with the drawings of the specification.

[0047] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0048] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation manner of the present invention. The "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that mutually excludes other embodiments.

[0049] Referring to Figure 1-2 , in one embodiment of the present invention, a spiciness quantification and evaluation method based on an individual's spicy food habit and capsaicin content is provided, and this method includes the following steps:

[0050] Step 1: Collect the chili-eating information of the interviewees through chili-eating visits and surveys, including: the frequency of eating chili peppers in the past period; the number of meals of chili peppers eaten per day and the intake per meal; the types of chili peppers; the subjective spiciness scores of the interviewees for different types of chili peppers (the scoring range is set as [0, 10], where 0 means no spiciness at all and 10 means extremely spicy). At the same time, record the physiological change information of the interviewees after eating chili peppers through wearable devices, including: sweating information, heart rate change information, skin temperature change information. Combine the chili-eating information and physiological change information to establish an individual's multi-dimensional chili tolerance profile;

[0051] Step 2: According to the types of chili peppers filled in by the interviewees, collect multiple types of chili peppers that match the actual consumption of the interviewees. Analyze the chili-eating habits of different individuals through machine learning algorithms to match the type of chili pepper that is closest to the interviewee's taste preference.

[0052] Specifically: Train the model with the data collected from the interviewees. Specifically, the model selection: Use a combination of collaborative filtering and classification algorithms for personalized chili pepper matching; Further, based on collaborative filtering: Use the K-Nearest Neighbors (KNN) algorithm to analyze the chili-eating preferences of similar users and recommend the types of chili peppers that may match the interviewee's taste. Based on the classification algorithm: Use decision tree or random forest to classify the interviewee's chili-eating behavior and predict the type of chili pepper that they are most likely to accept. The above algorithm models are all well-known technical means in the field.

[0053] Step 3: Conduct laboratory tests on the collected chili pepper samples (such as: using high performance liquid chromatography (HPLC) to measure), determine the capsaicin content of different chili pepper samples to establish the spiciness benchmark data of different types of chili peppers; Combine the capsaicin content data, the interviewees' subjective spiciness scores and physiological response data to construct a multi-sensory spiciness perception model to quantify the actual feelings of individuals towards capsaicin,

[0054] Specifically, the process of constructing the multi-sensory spiciness perception model is as follows:

[0055] S301: First, construct a physiological response index P according to the physiological change information of the interviewees r ;

[0056] The physiological response index P r The selected physiological indicators include: heart rate change ΔHR; skin temperature change ΔT s ; sweating amount SW; The calculation formula is:

[0057]

[0058] Among them, w1, w2, and w3 are weight coefficients corresponding to different physiological indicators, and P r ∈[0, 1], representing from no response 0 to extreme strong physiological response 1.

[0059] S302: Determine the basic contribution value of capsaicin content to spiciness: α·C p β ; among them, α represents the adjustment factor of the overall spiciness, β represents the exponential influence factor of capsaicin content on perceived spiciness; C p represents the capsaicin content of the chili sample detected in the laboratory.

[0060] S303: According to the physiological response index P r , the basic contribution value of capsaicin content to spiciness: α·C p β , and the subjective spiciness score S of the interviewees for different chili types, use a non - linear combination function to calculate the comprehensive spiciness perception value L of the interviewees for chili p ; the calculation formula is:

[0061]

[0062] Among them, γ represents the subjective spiciness enhancement factor; δ represents the physiological response adaptability adjustment coefficient; η represents the exponential term adjustment parameter. Among them, in the numerator: (1 + γ·S) represents the enhancement effect of subjective spiciness. And in the denominator, the exponential term simulates physiological adaptability (feedback enhancement such as profuse sweating, increased heart rate, increased skin temperature, etc., the body produces an adaptive response, and the nervous system reduces spiciness through a negative feedback mechanism to reduce discomfort). When the physiological response is strong, P r is large, and the exponential term approaches 0, making the spiciness perception value decrease.

[0063] Step Four: Calculate the basic spiciness quantification value of the interviewee based on the chili - eating frequency, intake of the interviewee, and the capsaicin content of the corresponding chili sample; combine the multi - sensory perception model to modify the spiciness calculation formula so that it can comprehensively consider individual physiological change factors.

[0064] Specifically: The calculation method of the basic spiciness quantification value L b is as follows:

[0065] S401: First, calculate the annual total intake according to the chili - eating frequency and single - time intake in the chili - eating information filled in by the interviewee; it can be expressed by the following formula: I a = F s × I s × 52 weeks;

[0066] Among them, F sIndicates the frequency of eating spicy food per week, I s Indicates the intake in a single week;

[0067] S402: Calculate the total annual capsaicin intake by combining the annual total intake and the capsaicin content = I s ×C p ;

[0068] S403: When the intake increases, the perception of spiciness does not increase linearly but tends to saturate. The perceived increment of capsaicin stimulation is simulated by a logarithmic function and decreases with the increase of intake. Therefore, the ln(1 + x) structure is used to simulate the non-linear growth of spiciness tolerance.

[0069] That is, the capsaicin intake tolerance factor is obtained from the total annual capsaicin intake, and the calculation formula is: The spiciness frequency tolerance factor is obtained from the spiciness frequency, and the calculation formula is: The sum of the two represents the basic spiciness quantification value Among them, respectively represent the weights of the capsaicin intake tolerance factor and the spiciness frequency tolerance factor in the overall spiciness perception; C a represents the annual capsaicin intake; F s represents the spiciness frequency.

[0070] Furthermore, the comprehensive spiciness perception value L obtained through the multi-sensory perception model p is used to correct the basic spiciness quantification value L b , then the corrected spiciness quantification value is: L i = θ1L b + θ2L p .

[0071] Among them, θ1 and θ2 respectively represent the adjustment coefficients corresponding to the basic spiciness quantification value and the comprehensive spiciness perception value.

[0072] Step Five: Normalize the spiciness quantification values of different individuals to establish a unified spiciness level standard; according to the calculation results, divide the interviewees into different spiciness levels.

[0073] Specifically, normalize the individual corrected spiciness quantification values L of all interviewees i , and the normalization calculation formula is: L = (L i - min(L i )) / (max(L i ) - min(L i ))).

[0074] Establish individual spicy tolerance levels based on the normalized L value, which are as follows:

[0075] The first threshold ≤ L < the second threshold, intolerance level;

[0076] The second threshold ≤ L < the third threshold, low tolerance level;

[0077] The third threshold ≤ L < the fourth threshold, medium tolerance level;

[0078] The fourth threshold ≤ L ≤ the fifth threshold, high tolerance level.

[0079] In summary, the present invention combines the individual's spicy eating frequency, intake, and long-term capsaicin exposure level to construct a personalized spiciness calculation model, achieving precise spiciness assessment for different individuals; uses a logarithmic function to simulate the decreasing effect of spiciness tolerance, making the calculation closer to reality; the present invention combines multiple sensory factors to correct the spiciness calculation, comprehensively evaluating the individual's true experience of spiciness, improving the accuracy, and through normalization processing and tolerance level division, establishing a standardized spiciness index, making the spiciness experiences of different populations comparable, and is applicable to scenarios such as the food industry and consumer personalized recommendations.

[0080] This embodiment also provides a computer device, applicable to a situation of a spiciness quantification and assessment method based on an individual's spicy eating habits and capsaicin content, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement a spiciness quantification and assessment method based on an individual's spicy eating habits and capsaicin content as proposed in the above embodiment.

[0081] This computer device can be a terminal. This computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of this computer device is used to provide computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of this computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of this computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of this computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0082] This embodiment also provides a storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the method for quantitatively evaluating spiciness based on individual spicy food habits and capsaicin content proposed in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc.

[0083] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for quantitatively evaluating the spiciness of food based on individual spicy food habits and capsaicin content, characterized in that: The method comprises the following steps: Through the method of spicy food consumption survey, the spicy food consumption information of the respondents was collected, and the physiological changes of the respondents after eating chili were recorded through wearable devices. By combining the spicy food consumption information and the physiological change information, a multi-dimensional spicy food tolerance profile of the individual was established; According to the types of peppers reported by the respondents, we collected multiple types of peppers that the respondents actually ate, analyzed the spicy eating habits of different individuals through machine learning algorithms, and matched the types of peppers that were closest to the respondents' taste preferences; The collected pepper samples were tested in the laboratory to determine the capsaicin content of different pepper samples in order to establish baseline data on the spiciness of different pepper types. A multi-sensory spiciness perception model was constructed by combining the capsaicin content data, the respondents' subjective spiciness ratings, and physiological response data to quantify the actual feelings of individuals towards capsaicin. The basic spiciness quantification value of the respondents was calculated based on their frequency of eating spicy food, the amount of spicy food they consumed, and the capsaicin content of the corresponding pepper samples. The spiciness calculation formula was modified based on the multi-sensory perception model to take into account individual physiological changes. The spiciness quantification values ​​of different individuals were normalized to establish a unified standard for spiciness levels; based on the calculation results, the respondents were divided into different spiciness levels.

2. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 1, characterized in that: The respondents’ spicy food consumption information included: the frequency of chili consumption in the past period; the number of chili meals per day and the amount of chili consumed per meal; the types of chili; the respondents’ subjective spiciness ratings for different types of chili; The respondent's physiological change information includes: sweat information, heart rate change information, and skin temperature change information.

3. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 2, characterized in that: The multi-sensory spiciness perception model construction process is as follows: S301: First, construct the physiological response index P based on the physiological change information of the respondents. r ; S302: Determine the basic contribution value of capsaicin content to the spicy sensation: α·C p β ; Among them, α represents the adjustment factor of the overall spiciness, and β represents the index influence factor of capsaicin content on the perceived spiciness; C p It means that the laboratory tests the capsaicin content of pepper samples; S303: According to the physiological response index P r , the basic contribution of capsaicin content to spicy sensation: α·C p β , and the respondents' subjective spiciness ratings S for different types of peppers, and the nonlinear combination function is used to calculate the respondents' comprehensive spiciness perception value L of peppers p ; The calculation formula is: Among them, γ represents the subjective spicy enhancement factor; δ represents the physiological response adaptability adjustment coefficient; η represents the exponential term adjustment parameter.

4. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 3, characterized in that: The physiological response index P r The selected physiological indicators include: heart rate change ΔHR; skin temperature change ΔT s ;Sweat volume SW;Calculation formula: Among them, w1, w2, w3 are weight coefficients corresponding to different physiological indicators, P r ∈[0,1], representing from no reaction 0 to extremely strong physiological reaction 1.

5. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 4, characterized in that: The basic spiciness quantification value L b The calculation method is: S401: First, calculate the total annual intake based on the frequency of spicy food and single intake in the spicy food information filled in by the respondents; S402: Calculate the total annual capsaicin intake by combining the annual total intake and the capsaicin content; S403: The capsaicin intake tolerance factor is calculated based on the total annual capsaicin intake, and the spicy food frequency tolerance factor is calculated based on the spicy food frequency. The sum of the two is used to represent the basic spicy quantification value L b .

6. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 5, characterized in that: The calculation formula of the capsaicin intake tolerance factor is: The calculation formula of the spicy food frequency tolerance factor is: in, They represent the weights of capsaicin intake tolerance factor and spicy frequency tolerance factor in the overall spiciness perception; C a represents the annual capsaicin intake; F s Indicates the frequency of eating spicy food.

7. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 6, characterized in that: The comprehensive spiciness perception value L obtained through the multi-sensory perception model p To correct the basic spicy quantization value L b , then the corrected spiciness quantification value is: L i =θ1L b +θ2L p . Among them, θ1 and θ2 represent the adjustment coefficients of the basic spiciness quantification value and the comprehensive spiciness perception value respectively.

8. The method for quantitatively evaluating the spicy taste based on individual spicy food habits and capsaicin content according to claim 7, characterized in that: Calculate the individual corrected spiciness quantification value L for all respondents i Normalization is performed, and the individual spicy tolerance levels are established based on the normalized values, which are: The first threshold ≤ L < the second threshold, intolerance level; The second threshold ≤ L < the third threshold, low tolerance level; The third threshold ≤ L < the fourth threshold, medium tolerance level; Fourth threshold ≤ L ≤ fifth threshold, high tolerance level.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a method for quantitatively evaluating the spiciness based on individual spicy food habits and capsaicin content as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for quantitatively evaluating the spiciness based on individual spicy food habits and capsaicin content as described in any one of claims 1 to 8 are implemented.

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