Wine quality evaluation method, system and device and storage medium

Abstract

The invention provides a wine quality evaluation method and device, a device and a storage medium, relates to the technical field of wine quality evaluation, evaluates the quality grade of wine according to a first quality parameter, a second quality parameter and a taste parameter of the wine, and ensures the evaluation accuracy of the quality grade of the wine. If the quality grade of the wine is lower than the preset quality grade, triggering abnormal tracing of the wine, and determining a plurality of abnormal events of the wine according to the abnormal tracing of the wine; and the plurality of abnormal events are rechecked to determine a subsequent wine brewing process table, so that optimization of the subsequent wine brewing process table is realized. And determining the sales area of the updated wine based on the updated quality grade of the wine, the price level of the wine and the quality grade of the competitive product in the same period, thereby ensuring the accuracy of the sales area of the wine.

Description

Technical Field

[0001] The present invention relates to the technical field of quality evaluation methods, and particularly relates to a quality evaluation method, system, device and storage medium for wine. Background Art

[0002] With the development of technology, wine has gradually been applied in life and is one of people's dinners. Wine is brewed from grapes, and grapes go through multiple processes such as growth, picking, preservation, and brewing. In the prior art, taste parameters of wine are introduced, and the quality grade is evaluated based on the taste parameters of wine and the origin of grapes. Evaluating the quality grade through a single dimension only affects the accuracy of the quality grade evaluation of wine. Summary of the Invention

[0003] Based on this, it is necessary to provide a quality evaluation method, system, device and storage medium for wine in view of the above technical problems.

[0004] A quality evaluation method for wine includes:

[0005] Determine the data space of the corresponding wine based on the model information of the wine and the corresponding wine database, and determine the grade parameters of the grapes according to the traversal of the data space of the wine;

[0006] Determine the first quality parameter of the wine according to the grade parameters of the grapes, the origin of the grapes and the corresponding brewing environment; conduct real-time detection on the wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine and the storage environment of the wine;

[0007] Evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter and the taste parameter of the wine;

[0008] If the quality grade of the wine is lower than the preset quality grade, trigger the abnormal traceability of the wine, and determine multiple abnormal events of the wine according to the abnormal traceability of the wine; determine the subsequent wine brewing process table through the review of multiple abnormal events;

[0009] Real-time update the quality grade of the wine, and determine the updated sales area of the wine based on the updated quality grade of the wine, the price level of the wine and the quality grades of competing products in the same period.

[0010] A quality evaluation system for wine is applied to the above quality evaluation method for wine. The quality evaluation system for wine includes:

[0011] A maturity module, which is used to determine the data space of the corresponding wine based on the model information of the wine and the corresponding wine database, and determine the grade parameters of the grapes according to the traversal of the data space of the wine;

[0012] A quality parameter module, which is used to determine the first quality parameter of the wine according to the grade parameters of the grapes, the origin of the grapes and the corresponding brewing environment; conduct real-time detection on the wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine and the storage environment of the wine;

[0013] A quality grade module, which is used to evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter and the taste parameter of the wine;

[0014] A regulation module, which is used to trigger the abnormal traceability of the wine if the quality grade of the wine is lower than the preset quality grade, determine multiple abnormal events of the wine according to the abnormal traceability of the wine; determine the subsequent wine brewing process schedule according to the review of the multiple abnormal events;

[0015] A sales module, which is used to update the quality grade of the wine in real time, and determine the sales area of the updated wine based on the updated quality grade of the wine, the price level of the wine and the quality grades of the competing products in the same period.

[0016] A device, including a memory and a processor, the memory stores a computer program, and is characterized in that when the processor executes the computer program, the following steps are implemented:

[0017] A storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0018] The above-mentioned wine quality evaluation method, system, device and storage medium determine the data space of the corresponding wine based on the model information of the wine and the corresponding wine database, and determine the grade parameters of the grapes according to the traversal of the data space of the wine; determine the first quality parameter of the wine according to the grade parameters of the grapes, the origin of the grapes and the corresponding brewing environment; conduct real-time detection on the wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine and the storage environment of the wine; evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter and the taste parameter of the wine, which takes into account the overall consideration of the first quality parameter, the second quality parameter and the taste parameter of the wine, and ensures the accuracy of the evaluation of the quality grade of the wine.

[0019] Further, if the quality grade of the wine is lower than the preset quality grade, an abnormal traceability of the wine is triggered, and multiple abnormal events of the wine are determined according to the abnormal traceability of the wine; by reviewing the multiple abnormal events, a subsequent brewing process sheet of the wine is determined, so as to facilitate the optimization of the subsequent brewing process sheet of the wine.

[0020] Therefore, by updating the quality grade of the wine in real time and determining the updated sales area of the wine based on the updated quality grade of the wine, the price level of the wine, and the quality grade of competing products in the same period, it takes into account the overall consideration of the quality grade of the wine, the price level of the wine, and the quality grade of competing products in the same period, ensuring the accuracy of the sales area of the wine. Brief Description of the Drawings

[0021] Figure 1 It is a schematic diagram of the application scenario of the wine quality evaluation method in an embodiment;

[0022] Figure 2 It is a schematic flowchart of the wine quality evaluation method in an embodiment;

[0023] Figure 3 It is a structural block diagram of the wine quality evaluation system in an embodiment;

[0024] Figure 4 It is the internal structure diagram of the device in an embodiment. Detailed Embodiments

[0025] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0026] Embodiment 1

[0027] The wine quality evaluation method provided by the present application is applied to the application environment as Figure 1 shown. Among them, the computer 102 communicates with the server 104 through the network. Among them, the computer 102 includes but is not limited to various personal computers, servers, and wine quality evaluation devices, and the server 104 is implemented by an independent server or a server cluster composed of multiple servers.

[0028] Embodiment 2

[0029] In this embodiment, please refer to Figures 2 to 4 , a wine quality evaluation method is applied to the wine quality evaluation scenario; the wine quality evaluation method includes:

[0030] Step S11: Determine the data space corresponding to the wine based on the wine model information and the corresponding wine database, and determine the grape grade parameters according to the traversal of the wine data space;

[0031] Step S12: Determine the first quality parameter of the wine according to the grape grade parameters, the grape origin, and the corresponding brewing environment; conduct real-time detection of the wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine, and the storage environment of the wine;

[0032] Step S13: Evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter, and the taste parameter of the wine;

[0033] Step S14: If the quality grade of the wine is lower than the preset quality grade, trigger the abnormal traceability of the wine, and determine multiple abnormal events of the wine according to the abnormal traceability of the wine; determine the subsequent wine brewing process table through the review of multiple abnormal events;

[0034] Step S15: Real-time update the quality grade of the wine, and determine the updated sales area of the wine based on the updated quality grade of the wine, the price level of the wine, and the quality grades of competing products in the same period.

[0035] In step S11, determine the data space corresponding to the wine based on the wine model information and the corresponding wine database, and determine the grape grade parameters according to the traversal of the wine data space;

[0036] In the specific implementation process of the present invention, the specific steps are as follows:

[0037] S111: Collect the wine model information, associate the wine model information and the corresponding wine database, and determine the grape sub-data space and the wine brewing sub-data space based on the wine model information and the corresponding wine database;

[0038] S112: Construct the corresponding wine data space according to the grape sub-data space and the wine brewing sub-data space;

[0039] S113: Determine the grape growth data and grape picking data according to the traversal of the wine data space;

[0040] S114: Determine the grape grade parameters according to the grape growth data, the grape picking data, and the wine brewing time point.

[0041] In an embodiment of the present application, the model information of the wine is collected, and the model information of the wine is associated with the corresponding wine database, and the sub-data space of the grapes and the sub-data space of the wine brewing are determined based on the model information of the wine and the corresponding wine database;

[0042] At this time, the model information of the wine is collected, the model information of the wine is further controlled, and the model information of the wine is associated with the corresponding wine database, and the model information of the wine and the corresponding wine database are introduced.

[0043] Meanwhile, the basic information of the wine includes the variety of the wine (such as Cabernet Sauvignon, Pinot Noir, etc.), the production area (such as Bordeaux, Burgundy, etc.), the name of the winery, the year, etc., and these information are obtained from the label of the wine, the packaging or the official website of the winery; once the model information of the wine is available, the next step is to associate this information with the wine database, which contains a large amount of detailed information about different wine varieties, production areas, wineries and years, including the growth conditions of the grapes, the brewing process, the historical evaluation, etc.; the purpose of the association is to find the data subset that matches the current wine model.

[0044] After associating the wine database, two sub-data spaces are determined according to the model information: the sub-data space of the grapes and the sub-data space of the wine brewing; the sub-data space of the grapes contains information related to grape varieties, growth environment, etc.; while the sub-data space of the wine brewing contains information related to brewing processes, fermentation conditions, aging processes, etc.

[0045] Specifically, assume there is a wine named "Château Lafite Legende Bordeaux Rouge 2015"; step S111 will be carried out in the following manner:

[0046] Record that the variety of the wine is Cabernet Sauvignon, the production area is Bordeaux, the winery is Lafite, and the year is 2015; associate the above model information with the wine database to find the data subset that matches "Château Lafite Legende Bordeaux Rouge 2015".

[0047] Sub-data space of the grapes: Obtain the growth environment data of Cabernet Sauvignon grapes in the Bordeaux production area, such as soil type (mainly limestone and gravel), climate conditions (mild maritime climate, warm in summer, cool in autumn, which is beneficial to the ripening of grapes and the retention of acidity).

[0048] Sub-data space of the wine brewing: Understand the brewing process of Lafite winery's Cabernet Sauvignon dry red wine in 2015, such as fermenting with specific yeast, controlling the fermentation temperature, and aging in oak barrels, etc.; provide detailed data support for the subsequent wine quality evaluation.

[0049] Furthermore, construct a corresponding data space for wine based on the sub-data space of grapes and the sub-data space of wine brewing; determine the growth data and picking data of grapes based on the traversal of the data space of wine.

[0050] At this time, integrate the sub-data space of grapes (including information such as grape variety, growth environment, maturity, etc.) and the sub-data space of wine brewing (including information such as brewing process, fermentation conditions, aging process, etc.) to construct a comprehensive wine data space, which will serve as the basis for subsequent quality evaluation and contain all key information related to wine quality.

[0051] Merge the sub-data space of grapes and the sub-data space of wine brewing, which involves matching and corresponding relevant data fields in the two sub-spaces to ensure data integrity and consistency; after merging the data, data cleaning is required to remove duplicate, incorrect or incomplete data, which is a key step to ensure data quality; to ensure the comparison and analysis of data from different sources, data standardization is required, which includes converting data in different units to a unified unit or converting data in different formats to a unified format. Finally, integrate the cleaned and standardized data into a unified data space, which can be a database, data warehouse or data lake for storing and managing all data related to wine quality.

[0052] At the same time, traverse the entire wine data space to find data fields related to grape growth and picking; extract the growth data of grapes from the data space, which includes the growth cycle of grapes, growth environment parameters (such as temperature, humidity, light, etc.), pest and disease conditions, etc.; similarly, extract the picking data of grapes from the data space, which includes the picking time, picking method, grape maturity indicators (such as sugar content, acidity, etc.); after extracting the data, it is necessary to verify the data to ensure its accuracy and reliability, which involves direct communication with wineries or vineyards to obtain first-hand information.

[0053] Specifically, assume that a data space is being constructed for a wine named "Château Lafite Legende Bordeaux Rouge 2018" as follows:

[0054] Sub-data space of grapes: includes the following information:

[0055] Variety: Cabernet Sauvignon; Growth environment: Bordeaux region, limestone and gravel soil, mild maritime climate; Maturity: determined by measuring the sugar and acidity in grapes, assuming the sugar content is 220 g / L and the acidity is 6.5 g / L (calculated as tartaric acid).

[0056] Sub-data space of wine brewing: includes the following information:

[0057] Brewing process: Traditional method, fermented with specific yeast; Fermentation conditions: Temperature controlled between 25 - 28 °C; Aging process: Aged in oak barrels for 12 months, with 30% being new barrels; After integrating this information, a wine data space containing key information such as grape variety, growth environment, maturity, brewing process, fermentation conditions, and aging process was constructed.

[0058] Traversed the previously constructed wine data space; Extracted the following growth data: Growth period: From April to October, a total of 6 months; Growth environment parameters: Average temperature is 16 °C, average rainfall is 600 mm, and sunshine duration is 1800 hours; Pest and disease situation: Slight infection of black rot, but it was promptly controlled.

[0059] Extracted the following harvesting data: Harvesting time: From October 5th to October 10th, 2018; Harvesting method: Handpicked, selecting grapes with appropriate maturity; Maturity indicators: Sugar content is 220 g / L, acidity is 6.5 g / L (calculated as tartaric acid), meeting the harvesting standards of Château Lafite Rothschild.

[0060] Therefore, determine the grade parameters of the grapes based on the growth data of the grapes, the harvesting data of the grapes, and the brewing time point of the wine.

[0061] At this time, comprehensively consider the growth data of the grapes, the harvesting data, and the brewing time point of the wine to evaluate the quality of the grapes, and accordingly determine the grade parameters of the grapes. These grade parameters will directly affect the final quality and market positioning of the wine.

[0062] Analyze the growth data of the grapes, including the growth period, growth environment (such as climate, soil), pest and disease situation, etc. These data will help understand the health status and maturity of the grapes during the growth process; Through the growth data, evaluate whether the growth conditions of the grapes are superior and whether the grapes have reached the ideal maturity.

[0063] Evaluate the harvesting data of the grapes, especially the harvesting time and the maturity indicators (such as sugar content, acidity) at the time of harvesting; The choice of harvesting time is crucial for the quality of the grapes because it determines the balance of sugar and acidity in the grapes; Through the harvesting data, determine whether the grapes are harvested at the optimal time and the quality of the grapes at the time of harvesting.

[0064] The choice of the brewing time point also affects the quality of the wine; Different seasons, weather conditions, and even different times of the day all have an impact on the brewing process; By considering the brewing time point, ensure that the brewing process is carried out under the most favorable conditions, thereby maximizing the quality of the wine.

[0065] Based on the above analysis, the grape growth data, picking data and brewing time points will be combined to determine the grape grade parameters. These grade parameters include the grape quality grade, maturity grade, flavor characteristics, etc. The grade parameters will serve as an important basis for wine quality evaluation, helping wineries understand the quality level of grapes and formulate appropriate brewing strategies and market positioning accordingly.

[0066] Specifically, suppose you are determining the grape grading parameters for a wine called "Sunnylands Classic Cabernet Sauvignon 2020".

[0067] Growth Data: The grapes thrived in a sunny growing environment with a suitable climate and fertile soil, and were almost free from pests and diseases throughout the growing cycle, indicating that the growing conditions of the grapes were very favorable and conducive to the grapes reaching ideal maturity.

[0068] Picking data: The grapes reached optimal maturity in early October, with a sugar content of 230g / L and an acidity of 6.0g / L (in terms of tartaric acid). The sugar-acid ratio was moderate and the flavor was rich, indicating that the grapes were picked at the best time and were of high quality.

[0069] Brewing time: Choose a sunny day in mid-October for brewing, when the temperature is moderate and the humidity is low, which is conducive to the fermentation and aging of the grapes.

[0070] Based on the above analysis, the grape grade parameters of this wine are determined to be "Special Grade", which means that the grapes are of superior quality, moderate maturity, and rich and balanced flavor, which will provide an important basis for subsequent brewing strategies and market positioning.

[0071] In one example of the present application, the level parameter matching expression is as follows:

[0072] Table 1 Example of level parameter matching table

[0073]

[0074]

[0075] In this example, the actual growth data, picking data, and brewing time of the grapes are compared with the grade standards in the matching table to determine the grade of the grapes.

[0076] In step S12, a first quality parameter of the wine is determined according to the grade parameter of the grape, the origin of the grape and the corresponding winemaking environment; the wine is tested in real time, and a second quality parameter of the wine is determined according to the component content of the wine, the color of the wine and the storage environment of the wine;

[0077] In the specific implementation process of the present invention, the specific steps are as follows:

[0078] S121: Obtain the grade parameters of the grapes, and determine the origin of the grapes and the corresponding wine-making environment based on the detection of the data space of the wine;

[0079] S122: Construct multiple first-quality combinations based on the grade parameters of the grapes, the origin of the grapes, and the corresponding wine-making environment. Determine the corresponding multiple first-quality characteristics based on the identification of the multiple first-quality combinations, and determine the first-quality parameter of the wine based on the interaction of the multiple first-quality characteristics;

[0080] S123: Conduct real-time detection on the ordinary wine and output the corresponding detection report. Determine the component content and color degree of the wine based on the traversal of the detection report;

[0081] S124: Collect the storage environment of the wine based on the traceability of the wine. Determine the second-quality parameter of the wine based on the interaction of the component content, color degree, and storage environment of the wine.

[0082] In the embodiment of the present application, obtain the grade parameters of the grapes, and determine the origin of the grapes and the corresponding wine-making environment based on the detection of the data space of the wine;

[0083] At this time, obtain the grade parameters of the grapes. At the same time, the data space of the wine is a database or system containing information on the entire process of wine production; it contains information on grape varieties, origins, brewing processes, aging times, etc. in many aspects; by comparing the information in the data space with known origin characteristics, determine the specific origin of the grapes; origin information is crucial for understanding the flavor characteristics and quality of the wine. At the same time, introduce the wine-making environment, which includes multiple aspects such as the geographical location of the winery, climate conditions, soil types, brewing facilities and technologies of the winery, and these factors jointly affect the quality and flavor of the wine.

[0084] Specifically, the grade parameter of the Cabernet Sauvignon grapes used in this wine obtained from the previous steps is "extra grade", which means that this batch of grapes has reached extremely high standards in terms of growth conditions, maturity, and picking timing.

[0085] Accessed the data space of the wine and input the grade parameters of the Cabernet Sauvignon grapes and other relevant information; the data space returned multiple origins and wine-making environments related to this batch of grapes; by comparing the information in the data space with known origin characteristics, it was determined that this batch of grapes was produced from a premium winery in the Bordeaux region of France; the Bordeaux region is famous for its high-quality wines, and its unique soil and climate conditions provide a superior environment for grape growth.

[0086] Further analyzing the information in the data space, it is learned that this winery has advanced brewing facilities and technologies, and its brewing process conforms to the traditions of the Bordeaux region; in addition, the winery also pays attention to environmental protection and sustainable development, providing good external conditions for wine production.

[0087] Furthermore, based on the grade parameters of the grapes, the origin of the grapes, and the corresponding brewing environment, multiple first-quality combinations are constructed. According to the identification of the multiple first-quality combinations, the corresponding multiple first-quality characteristics are determined. Based on the interaction of the multiple first-quality characteristics, the first-quality parameter of the wine is determined;

[0088] At this time, based on the grade parameters, origin, and brewing environment of the grapes, multiple quality combinations are constructed; each combination represents a specific wine quality scenario, and these scenarios are jointly affected by different factors (such as grape maturity, climate, soil type, brewing process, etc.).

[0089] After constructing the quality combinations, it is necessary to identify the quality characteristics exhibited by the wine in each combination. These characteristics include aroma, taste, color, structure, etc., which together constitute the overall sensory experience of the wine; optionally, identifying quality characteristics involves methods such as sensory analysis, chemical analysis, or instrumental analysis; sensory analysis is completed through the evaluation of wine-tasting experts, while chemical and instrumental analysis involve the quantitative determination of various chemical components (such as phenolic substances, aroma compounds, etc.) in the wine.

[0090] After identifying multiple quality characteristics, it is necessary to analyze the interactions between these characteristics to determine the first-quality parameter of the wine. This parameter is a comprehensive evaluation index used to measure the overall quality level of the wine; optionally, determining the quality parameter involves weighting, scoring, or comprehensive evaluation of the quality characteristics; weighting is based on the importance of the characteristics or consumer preferences, while scoring is based on the results of sensory evaluation; comprehensive evaluation involves using mathematical models or algorithms to integrate the information of multiple quality characteristics.

[0091] Specifically, assume that a quality combination is being constructed and its quality parameter is being determined for a wine named "Sunny Manor Classic Cabernet Sauvignon"; based on the premium grade parameters of the grapes, the unique climate and soil type in the Bordeaux origin, and the winery's traditional brewing process, three quality combinations are constructed: A (high maturity, warm climate, traditional brewing), B (medium maturity, mild climate, innovative brewing), C (low maturity, cool climate, blended brewing).

[0092] For each quality combination, sensory analysis and chemical analysis are carried out; for example, combination A exhibits rich fruit aroma, rich taste, and deep red color; combination B has fresh fruit aroma, light taste, and bright color; combination C has a unique aroma, soft taste, and delicate color.

[0093] After analyzing the quality characteristics of each quality combination, a comprehensive evaluation index is used to determine the first quality parameter of the wine. This index takes into account the performance in multiple aspects such as aroma, taste, color, etc., and weights each characteristic according to consumer preferences; finally, the first quality parameter of "Sunshine Manor Classic Cabernet Sauvignon" is determined to be "high quality", which means it performs excellently in multiple aspects, has a rich fruity aroma, a full taste, and a deep red color, while maintaining good balance and harmony.

[0094] Furthermore, real-time detection is carried out on ordinary wine, and a corresponding test report is output. Based on the traversal of this test report, the component content and color degree of the wine are determined;

[0095] At this time, real-time detection is carried out on ordinary wine, and real-time detection of ordinary wine is introduced. After the detection is completed, the system will automatically or manually generate a detailed test report. This report should contain detailed information on all test results, including but not limited to component content, color degree, aroma description, taste evaluation, etc.; the test report is presented in electronic or paper form and contains charts, data tables, and explanatory texts so that readers can easily understand the test results.

[0096] After obtaining the test report, it is necessary to traverse and analyze the data in the report to determine the specific component content and color degree of the wine, which involves the interpretation, comparison, and calculation of the data; optionally, traversing the test report involves finding specific data points (such as alcohol content, sugar content, etc.) and using these data to calculate other parameters (such as acid-sugar ratio, phenolic index, etc.); for the color degree, a specific instrument (such as a color difference meter) is needed to measure and interpret it with reference to the standard curve or data table in the test report.

[0097] Specifically, assume that real-time detection is being carried out on an ordinary wine named "Classic Mellow Dry Red" and its component content and color degree are determined;

[0098] "Classic Mellow Dry Red" is detected using a near-infrared spectrometer. This technology can non-destructively measure multiple components in the wine, such as alcohol content, sugar, acidity, and phenolic substances; after the detection is completed, a detailed test report is obtained; the report lists the alcohol content as 12.5%, the sugar content as 2.0 g / L, the total acidity as 6.0 g / L (calculated as tartaric acid), and the phenolic index as 120 (a relative index indicating the content of phenolic substances); in addition, the report also contains a description of the color degree, that is, "deep ruby red, slightly purple at the edge".

[0099] The data in the inspection report was traversed, and the specific component contents of "Classic Mellow Dry Red" were determined: the alcohol content was 12.5%, the sugar content was 2.0 g / L, and the total acidity was 6.0 g / L; for the color degree, the description in the report was referred to and quantified into a color difference value (this requires actual measurement using a color difference meter, but in this example, it is assumed that there is a standardized color degree evaluation system).

[0100] Therefore, based on the traceability of the wine, the storage environment of the wine was collected, and the second quality parameter of the wine was determined based on the interaction of the component content of the wine, the color degree of the wine, and the storage environment of the wine.

[0101] At this time, a database of wines was introduced, and the traceability of the wine was triggered based on the wine and the database of the wine to facilitate the collection of the storage environment of the wine.

[0102] After the storage environment is collected, it is necessary to analyze it in combination with the component content and color degree information of the wine determined in the previous steps; the component content includes alcohol, sugar, acidity, phenolic substances, etc., and the color degree describes the color characteristics and changes of the wine; after analyzing the relationship between the storage environment, component content, and color degree, the second quality parameter of the wine is determined based on the interaction of this information, and this parameter is a comprehensive evaluation index used to measure the quality retention of the wine under a specific storage environment.

[0103] Specifically, assume that the second quality parameter of a wine named "Classic Mellow Dry Red 2018" is being determined;

[0104] Using the database of the wine, the entire storage environment information of this wine from the winery to the hands of the final consumer was collected; the information shows that this wine maintained a constant low-temperature environment during transportation, was stored in a professional wine cellar, the temperature was controlled at 12 - 14 °C, the humidity was maintained at 65% - 75%, and direct sunlight and vibration were avoided.

[0105] According to the previous test results, it is known that the component content of this wine is: alcohol content 13.5%, sugar 2.2 g / L, total acidity 5.8 g / L (calculated as tartaric acid), and the phenolic substance index 150; the color degree is deep ruby red, slightly purple at the edge, showing good maturity and structure.

[0106] After analyzing the relationship between the storage environment and the component content and color degree, the second quality parameter of this wine was determined to be "excellent storage state" because its storage environment meets the best conditions for wine storage, and the component content and color degree information indicate that the wine maintained good quality during storage without obvious oxidation or aging phenomena.

[0107] In an example of the present application, the preservation environment matching representation is as follows:

[0108] Table 2 Example of Preservation Environment Matching Representation

[0109] Storage environmental conditions Temperature range (°C) Humidity range (%) Lighting conditions Quality parameters Ideal storage environment 12-14 65-75 Light protection Excellent Good storage environment 10-16 60-80 Weak light Good Average storage environment 8-20 55-85 With light but not strong Average Poor storage environment <8 or >20 <55 or >85 Strong light Poor

[0110] Suppose there is a bottle of wine with a preservation environment of 13°C in temperature, 70% in humidity, and stored away from light; according to the preservation environment matching table, the preservation environment of this bottle of wine belongs to the "ideal preservation environment", so it is preliminarily judged that its quality parameter is "excellent".

[0111] In step S13, evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter, and the taste parameter of the wine;

[0112] In the specific implementation process of the present invention, the specific steps are as follows:

[0113] S131: Conduct taste tests on the wine for different groups of people and output multiple taste test reports;

[0114] S132: Determine the taste parameter of the wine according to multiple taste test reports and the weights of the corresponding groups of people;

[0115] S133: Interact the first quality parameter, the second quality parameter, and the taste parameter of the wine, and evaluate the quality grade of the wine according to the interaction of the first quality parameter, the second quality parameter, and the taste parameter of the wine.

[0116] In the embodiment of the present application, conduct taste tests on the wine for different groups of people and output multiple taste test reports; determine the taste parameter of the wine according to multiple taste test reports and the weights of the corresponding groups of people;

[0117] At this time, organize people with different backgrounds and taste preferences to conduct taste tests on the wine, collect diverse taste feedback, so as to comprehensively understand the acceptance and preference of the wine among different consumer groups.

[0118] Optionally, ensure that the wine sample is in the best tasting condition, i.e., it has been fully decanted and is at an appropriate temperature; divide the participants into different groups according to factors such as age, gender, occupation, and drinking habits, such as expert sommeliers, wine enthusiasts, and ordinary consumers; provide a unified tasting guide, including pre-tasting preparations, precautions during the tasting process, and feedback requirements after the tasting, to ensure the consistency and comparability of the test; use a standardized questionnaire or spreadsheet to collect the tasting feedback from the participants, including evaluations of aspects such as aroma, taste, aftertaste, and overall impression; organize the collected data and generate an independent taste test report for each group, which should include information such as the overall evaluation of the group, the main evaluation points, and the distribution of preferences.

[0119] Furthermore, combine the tasting feedback and weights of different groups of people to determine a parameter that can reflect the overall taste performance of the wine. At the same time, assign weights to different groups of people according to the target market, product positioning, or professional requirements; for example, if the target market is ordinary consumers, give them a higher weight; if professional recognition is pursued, give expert sommeliers a higher weight; combine the tasting feedback and weights of each group of people and process them using the weighted average method or other statistical methods; based on the integrated data, determine the taste parameter of the wine, which is a numerical value (such as a taste score) or a descriptive term (such as "rich", "balanced", etc.).

[0120] Specifically, assume that the weights assigned to three groups of people are as follows:

[0121] Expert sommeliers: weight 0.4 (due to their professionalism and experience); wine enthusiasts: weight 0.3 (due to their certain understanding of wine and willingness to purchase); ordinary consumers: weight 0.3 (due to their representing a wide market acceptance);

[0122] Based on the above weights and taste test reports, use the weighted average method to calculate the taste parameter:

[0123] Calculation of taste score: Assume that the score reported by expert sommeliers is 90 points, the score reported by wine enthusiasts is 80 points (considering that some feedback indicates that the acidity is slightly high), and the score reported by ordinary consumers is 75 points (considering the wide distribution of preferences); then the taste parameter (score) = 0.4×90 + 0.3×80 + 0.3×75 = 85.5 points; Therefore, it is said that the taste parameter of "Classic Mellow Dry Red 2020" is 85.5 points, which is a score that combines the tasting feedback and weights of different groups of people and can better reflect the taste performance of this wine in the overall market.

[0124] Furthermore, the first quality parameter, the second quality parameter of the wine, and the taste parameter of the wine are interacted, and the quality grade of the wine is evaluated according to the interaction of the first quality parameter, the second quality parameter, and the taste parameter of the wine.

[0125] At this time, comprehensively considering the first quality parameter of the wine (based on grape variety, origin, brewing process, etc.), the second quality parameter (based on the interaction of storage environment, composition, and color degree), and the taste parameter (based on taste tests of different groups of people), the quality grade of the wine is comprehensively evaluated.

[0126] Collect and organize the specific values or descriptions of the first quality parameter, the second quality parameter, and the taste parameter; according to the evaluation criteria, market positioning, or consumer preferences of the wine, assign corresponding weights to the three parameters; the assignment of weights is based on expert opinions, market research, or historical data; analyze the correlation or interaction between the three parameters to determine their combined influence on the quality grade of the wine; for example, high-quality grape varieties and brewing processes (high first quality parameter) need to be in a suitable storage environment (high second quality parameter) to fully display their flavors, while the taste parameter directly reflects consumers' acceptance and preference for the wine; based on the integrated data and weight assignment, use the weighted average method, fuzzy comprehensive evaluation method, or other appropriate methods to calculate the comprehensive score or quality grade of the wine; the quality grade is a numerical range (such as 1 - 100 points) and also descriptive terms (such as "excellent", "good", "average", etc.).

[0127] Specifically, assume that the quality grade of a wine named "Manor Select Dry Red 2019" is being evaluated; the first quality parameter, the second quality parameter, and the taste parameter of this wine are as follows:

[0128] First quality parameter: Based on high-quality grape varieties, ideal origin, and exquisite brewing process, the score is 85 points (out of 100 full marks); Second quality parameter: In a suitable storage environment (constant temperature, moderate humidity, light-proof storage), the composition and color degree of the wine are well maintained, and the score is 90 points (out of 100 full marks); Taste parameter: Through taste tests of different groups of people, the comprehensive score is 80 points (out of 100 full marks), indicating that the wine has good performance in aspects such as aroma, taste, and aftertaste, but some consumers think its acidity is slightly high.

[0129] The weights assigned to the three parameters are as follows:

[0130] First quality parameter: Weight 0.4 (because it determines the basic quality of the wine); Second quality parameter: Weight 0.3 (because it affects the quality maintenance of the wine during storage); Taste parameter: Weight 0.3 (because it directly reflects consumers' acceptance and preference).

[0131] Based on the above data and weights, the comprehensive score of the wine is calculated using the weighted average method:

[0132] Comprehensive score = Score of the first quality parameter * Weight 0.4 + Score of the second quality parameter * Weight 0.3 + Score of the taste parameter * Weight 0.3 = 85 * 0.4 + 90 * 0.3 + 80 * 0.3 = 85 points.

[0133] Assume that the quality grades of the wine are divided into the following ranges:

[0134] Above 90 points is "excellent"; 80 - 89 points is "good"; 70 - 79 points is "average"; below 70 points is "poor"; Therefore, the comprehensive score of "Manor Selection Dry Red 2019" is 85 points, belonging to the "good" quality grade, which indicates that the wine has good performance in terms of grape variety, origin, brewing process, storage environment, and taste, but there is still room for improvement to meet the taste preferences of more consumers.

[0135] In step S14, if the quality grade of the wine is lower than the preset quality grade, an abnormal traceability of the wine is triggered, and multiple abnormal events of the wine are determined according to the abnormal traceability of the wine; the brewing process table of the subsequent wine is determined through the review of multiple abnormal events;

[0136] In the specific implementation process of the present invention, the specific steps are as follows:

[0137] S141: Match the corresponding preset quality grade according to the model information and time of the wine, and compare the quality grade of the wine with the preset quality grade;

[0138] S142: If the quality grade of the wine is lower than the preset quality grade, determine the corresponding quality grade difference based on the quality grade of the wine and the preset quality grade, and trigger the abnormal traceability of the wine according to the quality grade difference, the database of the wine, and the current brewing process table of the wine;

[0139] S143: Determine multiple abnormal events of the wine according to the abnormal traceability of the wine, and trigger the review of the corresponding data based on the multiple abnormal events of the wine to achieve the review of multiple abnormal events;

[0140] S144: Determine the data to be optimized according to the review of multiple abnormal events, and determine the subsequent brewing process table of the wine according to the data to be optimized and the current brewing process table of the wine, so as to optimize the brewing process table of the wine.

[0141] In an embodiment of the present application, a corresponding preset quality grade is matched according to the model information and time of the wine, and the quality grade of the wine is compared with the preset quality grade; if the quality grade of the wine is lower than the preset quality grade, a corresponding quality grade difference is determined based on the quality grade of the wine and the preset quality grade, and an abnormal traceability of the wine is triggered according to the quality grade difference, the database of the wine, and the current brewing process sheet of the wine.

[0142] At this time, the model information and time of the wine are introduced to ensure that the quality of the wine meets the established standards, and the preset quality grade is accurately located through the model information and time information.

[0143] Obtain the model information (such as brand, series, year, etc.) and time information (such as production date, inspection date, etc.) of the wine from the production records or management system of the wine; in the preset quality grade database, find the corresponding preset quality grade according to the model information and time information, and this database contains the quality grade standards of different types of wine at different time points; compare the actually detected quality grade of the wine with the preset quality grade to determine whether it meets the standard.

[0144] When the quality of the wine does not meet the preset standard, quickly locate the cause of the problem in order to take corrective measures; determine the quality grade difference between the actual quality grade and the preset quality grade. For example, if the preset is "excellent" and the actual is "good", the difference is one grade; combine the database of the wine (including raw material sources, brewing process parameters, storage conditions, etc.) and the current brewing process sheet to analyze the reasons for the quality decline; according to the analysis results, trigger an abnormal traceability process, including rechecking the raw material quality, checking the brewing process parameters, evaluating the storage conditions, etc.

[0145] Specifically, assume there is a "Manor Selection Dry Red 2022", and its production record shows that the production date is September 2022 and the inspection date is January 2023; in the preset quality grade database, for the "Manor Selection Dry Red" series, the preset quality grade for the 2022 vintage is "excellent"; in the actual inspection, the quality grade of "Manor Selection Dry Red 2022" is rated as "good"; at this time, it is necessary to compare the actually detected "good" grade with the preset "excellent" grade, and it is found that the actual quality grade is lower than the preset standard.

[0146] In step S141, it has been found that the actual quality grade of "Manor Selection Dry Red 2022" is lower than the preset standard; at this time, it is necessary to calculate the quality grade difference, that is, the difference between "excellent" and "good", and here it is simply quantified as a quality grade difference.

[0147] Next, analyze by combining the database of the "Manor Selection Dry Red" series and the current brewing process sheet; the database shows that the raw material quality of this batch of wine is good, but the parameter settings for a certain key step (such as fermentation temperature or time) during the brewing process are not precise enough; the current brewing process sheet also reflects the specific operation of this step; based on these analyses, trigger the abnormal traceability process, review the raw material quality records, carefully check the brewing process parameter settings (especially the parameters related to fermentation), and evaluate whether the storage conditions have had a negative impact on the quality; through this process, more accurately locate the cause of the problem and take corresponding corrective measures to improve the quality grade of the wine.

[0148] Furthermore, determine multiple abnormal events of the wine based on the abnormal traceability of the wine, and trigger the review of the corresponding data based on the multiple abnormal events of the wine to achieve the review of multiple abnormal events;

[0149] At this time, determine specific abnormal events through the abnormal traceability process, and review the data involved in these events to ensure the accuracy and integrity of the data, providing a basis for subsequent improvement measures.

[0150] In the abnormal traceability process, based on the information collected and the analysis results, determine multiple specific abnormal events that cause the wine quality not to meet the preset standards. These events involve multiple aspects such as raw material quality, brewing process, and storage conditions; for each determined abnormal event, trigger the review process of the corresponding data, which includes finding and collecting all the original data, records, and analysis reports related to the abnormal event to ensure the integrity and traceability of the data.

[0151] Conduct a detailed review and comparison of the reviewed data to verify the accuracy and consistency of the data. This process involves multiple links such as data checking, retesting, and evaluation; record the review results, including the verification of data accuracy, the confirmation or not of abnormal events, and any necessary corrective measures or suggestions. These records will serve as the basis for subsequent improvement measures and the continuous improvement process.

[0152] Specifically, through the abnormal traceability process, two abnormal events are determined for the "Manor Selection Dry Red 2022" whose quality does not meet the preset standards: one is the unstable temperature control during the fermentation process, and the other is the improper humidity control in the storage conditions.

[0153] For the first abnormal event (unstable temperature control during the fermentation process), trigger the review process of the corresponding data, which includes finding the temperature records during the fermentation process, the calibration records of the control equipment, and the training records of the operators, etc.; a professional team conducts a detailed review of these data and finds that the temperature records have fluctuations, and the fluctuation range exceeds the preset standards; at the same time, the calibration records of the control equipment show that the equipment was not calibrated in a timely manner before the abnormality occurred.

[0154] Regarding the second abnormal event (improper humidity control in the storage condition), the review process for the corresponding data is also triggered, which includes searching for humidity records in the storage warehouse, operation records of dehumidification equipment, and logs of warehouse management staff, etc.; After review, it is found that the humidity records show that the humidity during storage exceeded the ideal range, and there was a malfunction in the dehumidification equipment during the abnormal event that was not handled in a timely manner.

[0155] After completing the data review of the two abnormal events, the review results are recorded, and corresponding corrective measures and suggestions are put forward, such as strengthening the temperature monitoring and equipment calibration during the fermentation process, optimizing the humidity control system in the storage warehouse, and strengthening the training of operators, etc. These measures and suggestions will serve as the basis for subsequent improvement measures and continuous improvement processes to ensure that the quality of "Manor Selection Dry Red 2022" meets the preset standards and improve the overall production quality and efficiency.

[0156] Therefore, the data to be optimized is determined based on the review of multiple abnormal events, and the subsequent wine brewing process schedule is determined according to the data to be optimized and the current wine brewing process schedule, so as to realize the optimization of the wine brewing process schedule.

[0157] At this time, by analyzing the review results of multiple abnormal events, the data points that need to be optimized are determined, and the wine brewing process schedule is adjusted and optimized accordingly to improve product quality and production efficiency.

[0158] Carefully review the review results of multiple abnormal events, including the verification of data accuracy, the confirmation of abnormal events, and any relevant corrective measures or suggestions; Based on the review results, identify the key data points that led to the abnormal events, which are raw material quality indicators, brewing process parameters, storage condition settings, etc.; Mark these data points as data to be optimized.

[0159] Review the current brewing process schedule, analyze the position and role of the data to be optimized in the process schedule, and how they affect the overall quality of the wine; According to the analysis results of the data to be optimized and the current brewing process schedule, formulate specific optimization plans, which involve adjusting process parameters, improving equipment performance, optimizing storage conditions, strengthening quality control, etc.; Integrate the optimization plan into the current brewing process schedule to form a new, more accurate and efficient brewing process schedule; Ensure that the new process schedule can reflect all the identified improvement points and help improve the quality and production efficiency of the wine.

[0160] Specifically, assume that in step S143, two abnormal events that caused the quality of "Manor Selection Dry Red 2022" to not meet the preset standards were determined through recheck, and the relevant data points to be optimized were identified: one is the temperature control parameters during the fermentation process (such as the temperature fluctuation range and set value), and the other is the humidity control parameters of the storage warehouse (such as the target humidity range and the operation strategy of the dehumidification equipment); Next, the current brewing process sheet was evaluated, and it was found that both the temperature control parameters and the humidity control parameters had clear set values and monitoring requirements in the process sheet, but there were certain deviations and instabilities in actual operations.

[0161] Based on these analyses, the following optimization plan was developed:

[0162] For the temperature control during the fermentation process, the temperature set value was adjusted to ensure that it fluctuated within a more precise and stable range, and the calibration and maintenance of the temperature monitoring equipment were strengthened. For the humidity control of the storage warehouse, the operation strategy of the dehumidification equipment was optimized to ensure that the warehouse humidity was always maintained within the ideal range, and the training and log records of the warehouse management personnel were strengthened.

[0163] Then, these optimization plans were integrated into the current brewing process sheet to form a new brewing process sheet; the new process sheet more accurately reflected the requirements of temperature control and humidity control, and helped to improve the quality and production efficiency of "Manor Selection Dry Red 2022".

[0164] Finally, the new brewing process sheet was implemented, and the changes in product quality and production efficiency were continuously monitored; by collecting feedback data, it was found that the product quality had been significantly improved, and at the same time, the production efficiency had also increased. These results verified the effectiveness of the optimization plan and provided valuable experience for subsequent continuous improvement.

[0165] In an example of this application, an example of weight and score calculation:

[0166] The corresponding weights were introduced. Fermentation temperature set value: the weight was 0.5 (high importance), the benchmark score was 90, and the actual score was 80 (due to the temperature fluctuation exceeding the preset range); Storage humidity control: the weight was 0.3 (medium importance), the benchmark score was 80, and the actual score was 70 (due to the humidity exceeding the ideal range); Yeast type selection: the weight was 0.2 (low importance), the benchmark score was 70, and the actual score was 70 (stable performance, no adjustment required).

[0167] Optimization plan formulation:

[0168] For the set value of the fermentation temperature, adjust the set value to a more precise range and strengthen the calibration and maintenance of the temperature monitoring equipment; for the storage humidity control, optimize the operation strategy of the dehumidification equipment to ensure that the warehouse humidity is always maintained within the ideal range; in terms of the selection of yeast types, although the actual score is the same as the benchmark score, the current selection still needs to be maintained and the monitoring strengthened to ensure stability.

[0169] Example of a new brewing process:

[0170] (Based on the original brewing process table, add or update the following content)

[0171] Fermentation stage: Adjust the set value of the fermentation temperature to the range of XX - XX °C and strengthen the calibration and maintenance of the temperature monitoring equipment; Storage stage: Optimize the operation strategy of the dehumidification equipment to ensure that the warehouse humidity is maintained within the range of XX% - XX%; Preparation before fermentation: Maintain the current selection of yeast types and strengthen the monitoring to ensure stability.

[0172] In step S15, update the quality grade of the wine in real time, and determine the sales area of the updated wine based on the updated quality grade of the wine, the price level of the wine, and the quality grades of competing products in the same period;

[0173] In the specific implementation process of the present invention, the specific steps are as follows:

[0174] S151: Use the subsequent brewing process table of the wine to brew the wine and update the quality grade of the wine in real time to determine the updated quality grade of the wine;

[0175] S152: Determine the quality grades of competing products in the same period based on the model information of the wine and the competing product matching table;

[0176] S153: Determine multiple advantageous features based on the interaction of the updated quality grade of the wine, the price level of the wine, and the quality grades of competing products in the same period, and determine the sales area of the updated wine based on the multiple advantageous features and the past sales data table of the wine.

[0177] In the embodiment of the present application, use the subsequent brewing process table of the wine to brew the wine and update the quality grade of the wine in real time to determine the updated quality grade of the wine;

[0178] At this time, the subsequent winemaking process schedule is introduced, and the winemaking of wine is carried out in accordance with the subsequent winemaking process schedule. At the same time, during the winemaking process, regular quality inspections of the wine are required. These inspections include chemical analysis (such as sugar content, acidity, alcohol content, etc.), sensory evaluation (such as color, aroma, taste, etc.), and microbiological testing; according to the test results, the quality grade of the wine is updated in real time, which is based on a pre-defined quality standard and grading system. After the winemaking is completed, based on the results of all quality inspections, the updated quality grade of the wine is finally determined, and this grade will be used for subsequent pricing, marketing, and sales strategy formulation.

[0179] Specifically, assume that in step S144, the winemaking process schedule of "Estate Selection Dry Red" is optimized, with particular emphasis on temperature control and yeast strain selection during fermentation.

[0180] In step S151, the winemaker begins to make a new batch of "Estate Selection Dry Red" according to the optimized process schedule; during fermentation, they strictly control the temperature to ensure that the yeast is active within the optimal temperature range, thus producing a richer aroma and a more balanced taste; at the same time, they select carefully chosen yeast strains to further enhance the flavor characteristics of the wine.

[0181] During the winemaking process, the winemaker conducts regular quality inspections; they measure the sugar content, acidity, and alcohol content of the wine to ensure that these indicators meet the expected standards; in addition, they also conduct sensory evaluations, tasting wine samples at different stages to evaluate the changes in their color, aroma, and taste.

[0182] After the winemaking is completed, based on the results of all quality inspections, the winemaker determines that the quality grade of the new batch of "Estate Selection Dry Red" is "Extra Grade", which reflects the excellent performance of the wine in terms of aroma, taste, and overall quality.

[0183] Furthermore, based on the model information of the wine and the competitive product matching table, the quality grades of contemporaneous competitive products are determined;

[0184] At this time, the model information of the wine and the competitive product matching table are introduced. The model information of the wine includes key elements such as brand, series, year, origin, etc.; the competitive product matching table is a database containing information on the main competitive products in the market; the competitive product matching table contains key data such as the model, brand, price, quality grade, and market feedback of the competitive products.

[0185] Based on the model information of its own wine, search for similar or same-type products in the competitive product matching table; the matching process involves comparisons in multiple dimensions, such as brand awareness, product series positioning, price range, etc.; further, after matching the competitive products, consult their quality grade information; the quality grade is determined based on multiple factors such as professional evaluations, consumer feedback, industry standards, etc.; ensure that the obtained quality grade information is up-to-date and reliable.

[0186] Specifically, assume that the brand of its own wine is "Manor Selection" and the model is "Classic Dry Red in 2023"; the brand of "Manor Selection Classic Dry Red in 2023" is "Manor Selection", the series is "Classic", the year is "2023", and the origin is a specific wine-producing area; further, through market research, a matching table containing information on the main dry red wines in the market is obtained; this matching table includes brands such as "Noble Manor" and "Classic Winery".

[0187] In the matching table, products similar to "Manor Selection Classic Dry Red in 2023" are found, such as "Noble Manor Premium Dry Red in 2023" and "Classic Winery Reserve Dry Red in 2023"; these two products are similar to the company's own products in terms of brand awareness, product series positioning, price range, etc.; consulting the matching table, it is found that the quality grade of "Noble Manor Premium Dry Red in 2023" is "High Quality", while the quality grade of "Classic Winery Reserve Dry Red in 2023" is "Extra Grade".

[0188] Therefore, multiple advantageous features are determined based on the interaction of the updated quality grade of the wine, the price level of the wine, and the quality grades of contemporaneous competitive products; the sales area of the updated wine is determined based on the multiple advantageous features and the past sales data table of the wine.

[0189] Specifically, the updated quality grade of the wine is introduced. At the same time, the price level of the wine reflects the value positioning of the wine and needs to match the consumers' willingness to pay; regarding the quality grades of contemporaneous competitive products, understanding the advantages and disadvantages of competitors helps to highlight the unique selling points of the company's own products; considering the above factors comprehensively, analyze the advantageous features of the wine compared to competitors, such as high quality, unique flavor, high cost performance, etc.

[0190] Multiple advantageous features and the past sales data table of the wine are introduced. At the same time, collect past sales data, which includes information such as sales volume, sales amount, and consumer preferences in different sales areas; analyze the sales trends, identify the areas of sales growth or decline, and the changes in consumer preferences; based on the advantageous features of the wine, select the sales areas that are most likely to generate high sales volume and high profits; for different sales areas, formulate differentiated sales strategies, such as promotional activities, channel selection, etc.

[0191] Specifically, assume that after optimization, the quality grade of "Manor Selection Classic Dry Red 2023" has been upgraded to "Extra Grade", and the price level remains in the mid - to - high - end market. At the same time, among the main competitors in the market, the quality grades of "Noble Manor Enjoyment Dry Red 2023" and "Classic Winery Reserve Dry Red 2023" are "High Quality" and "Extra Grade" respectively, but their prices are slightly higher than that of "Manor Selection Classic Dry Red 2023".

[0192] "Manor Selection Classic Dry Red 2023" shows the advantage of high cost - performance in the market with an "Extra Grade" quality grade and a relatively affordable price. Compared with "Noble Manor Enjoyment Dry Red 2023", it is price - competitive. Compared with "Classic Winery Reserve Dry Red 2023", although they have the same quality grade, its price is lower. Therefore, the determined advantageous features are "Extra Grade Quality, Affordable Price".

[0193] By collecting past sales data, it is found that the sales volume of the "Manor Selection" series is relatively high in first - tier cities in East China and South China, and consumers prefer mid - to - high - end quality wines. Analyzing the sales trend shows that as consumers' requirements for wine quality increase, the demand in the mid - to - high - end market continues to grow. Combining with the advantageous features of "Extra Grade Quality, Affordable Price", select first - tier cities in East China and South China as the main sales regions. When formulating sales strategies, consider increasing advertising investment, holding tasting activities, cooperating with high - end catering channels, etc. in these regions to enhance brand awareness and market share.

[0194] In an embodiment of the present application, an example of advantageous feature matching is as follows:

[0195] Table 3 Example of Advantageous Feature Matching Table

[0196] Advantageous features Weight Score of self-produced wine Average score of competitors High quality 0.4 9 (Extra grade) 7.5 (Ranging from fine to extra grade) Unique flavor 0.3 8 (Rich fruity aroma) 6 (Average fruity aroma) Cost performance 0.2 9 (Affordable price) 7 (Slightly high price) Brand awareness 0.1 7 (Medium awareness) 8 (Higher awareness)

[0197] Calculate the comprehensive advantage score:

[0198] High - quality score: 0.4 * 9 = 3.6; Unique flavor score: 0.3 * 8 = 2.4; Cost - performance score: 0.2 * 9 = 1.8; Brand awareness score: 0.1 * 7 = 0.7; Overall advantage score: 3.6 + 2.4 + 1.8 + 0.7 = 8.5.

[0199] Based on past sales data, it is found that first - tier cities in East China and South China have a relatively high demand for high - quality and uniquely - flavored wines. Consumers in these regions prefer mid - to - high - end quality wines and are relatively less sensitive to price. Combining with the overall advantage score of 8.5 (high competitiveness), it is decided to take first - tier cities in East China and South China as the main sales regions. When formulating sales strategies, consider increasing advertising investment, holding tasting activities, cooperating with high - end catering channels, etc. in these regions to enhance brand awareness and market share.

[0200] Example 3

[0201] In this embodiment, as Figure 3 shown, a quality evaluation system for wine is provided, including:

[0202] A maturity module 21, configured to determine a corresponding data space of the wine based on the model information of the wine and the corresponding wine database, and determine the grape grade parameters according to the traversal of the data space of the wine;

[0203] A quality parameter module 22, configured to determine the first quality parameter of the wine according to the grape grade parameters, the origin of the grapes, and the corresponding wine-making environment; perform real-time detection on the wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine, and the storage environment of the wine;

[0204] A quality grade module 23, configured to evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter, and the taste parameter of the wine;

[0205] A regulation module 24, configured to trigger abnormal traceability of the wine if the quality grade of the wine is lower than a preset quality grade, determine multiple abnormal events of the wine according to the abnormal traceability of the wine; determine the subsequent wine-making process schedule through rechecking of the multiple abnormal events;

[0206] A sales module 25, configured to update the quality grade of the wine in real time, and determine the updated sales area of the wine based on the updated quality grade of the wine, the price level of the wine, and the quality grades of competing products in the same period.

[0207] Example 4

[0208] In this embodiment, a device is provided. The internal structure diagram is as Figure 4As shown in the figure. The device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the device is used to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and a database is deployed on the non-volatile storage medium, and the database is used to store user behavior data and user portraits. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the device is used to communicate with other devices on which application software is deployed. When the computer program is executed by the processor, it implements a method for evaluating the quality of wine. The display screen of the device is a liquid crystal display screen or an electronic ink display screen, and the input device of the device is a touch layer covered on the display screen, and is also a key, a trackball or a touchpad provided on the device housing, or an external keyboard, touchpad or mouse, etc.

[0209] For any combination of the technical features of the above embodiments, for the sake of brevity of description, not all combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0210] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements are made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the appended claims.

Claims

1. A method for evaluating the quality of wine, characterized in that, Including: Determine the data space corresponding to the wine based on the model information of the wine and the corresponding wine database, and determine the grade parameters of the grapes according to the traversal of the data space of the wine; Determine the first quality parameter of the wine according to the grade parameters of the grapes, the origin of the grapes, and the corresponding wine-making environment; conduct real-time detection of the wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine, and the storage environment of the wine; Evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter, and the taste parameter of the wine; If the quality grade of the wine is lower than the preset quality grade, trigger the abnormal traceability of the wine, and determine multiple abnormal events of the wine according to the abnormal traceability of the wine; determine the subsequent wine-making process schedule according to the review of the multiple abnormal events; Update the quality grade of the wine in real time, and determine the sales area of the updated wine based on the updated quality grade of the wine, the price level of the wine, and the quality grades of competing products in the same period.

2. The quality evaluation method of wine according to claim 1, characterized in that The determining the data space corresponding to the wine based on the model information of the wine and the corresponding wine database, and determining the grade parameters of the grapes according to the traversal of the data space of the wine includes: Collect the model information of the wine, associate the model information of the wine and the corresponding wine database, and determine the sub-data space of the grapes and the sub-data space of wine-making based on the model information of the wine and the corresponding wine database; Construct the data space corresponding to the wine according to the sub-data space of the grapes and the sub-data space of wine-making; Determine the growth data of the grapes and the picking data of the grapes based on the traversal of the data space of the wine; Determine the grade parameters of the grapes according to the growth data of the grapes, the picking data of the grapes, and the wine-making time point of the wine.

3. The quality evaluation method of wine according to claim 2, characterized in that, The determining the first quality parameter of the wine according to the grade parameters of the grapes, the origin of the grapes, and the corresponding wine-making environment; Conduct real-time detection of the ordinary wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine, and the storage environment of the wine, including: Obtain the grade parameters of the grapes, and determine the origin of the grapes and the corresponding wine-making environment based on the detection of the data space of the wine; Construct multiple first quality combinations according to the grade parameters of the grapes, the origin of the grapes, and the corresponding wine-making environment, determine the corresponding multiple first quality characteristics according to the identification of the multiple first quality combinations, and determine the first quality parameter of the wine based on the interaction of the multiple first quality characteristics.

4. The quality evaluation method of wine according to claim 3, characterized in that, The determining the first quality parameter of the wine according to the grade parameters of the grapes, the origin of the grapes, and the corresponding wine-making environment; Conduct real-time detection of the ordinary wine, and determine the second quality parameter of the wine according to the component content of the wine, the color degree of the wine, and the storage environment of the wine, further including: Conduct real-time detection of the ordinary wine, and output the corresponding detection report, and determine the component content of the wine and the color degree of the wine according to the traversal of the detection report; Collect the storage environment of the wine based on the traceability of the wine, and determine the second quality parameter of the wine based on the interaction of the component content of the wine, the color degree of the wine, and the storage environment of the wine.

5. The quality evaluation method of wine according to claim 1, characterized in that, Evaluating the quality grade of the wine according to the first quality parameter, the second quality parameter and the taste parameter of the wine includes: Conduct taste tests on the wine for different groups of people and output multiple taste test reports; Determine the taste parameter of the wine according to multiple taste test reports and the weights of the corresponding groups of people; Interact the first quality parameter, the second quality parameter and the taste parameter of the wine, and evaluate the quality grade of the wine according to the interaction of the first quality parameter, the second quality parameter and the taste parameter of the wine.

6. The quality evaluation method of wine according to claim 1, characterized in that If the quality grade of the wine is lower than the preset quality grade, trigger the abnormal traceability of the wine, and determine multiple abnormal events of the wine according to the abnormal traceability of the wine; Determine the subsequent wine brewing process table by rechecking multiple abnormal events, including: Match the corresponding preset quality grade according to the model information and time of the wine, and compare the quality grade of the wine with the preset quality grade; If the quality grade of the wine is lower than the preset quality grade, determine the corresponding quality grade difference based on the quality grade of the wine and the preset quality grade, and trigger the abnormal traceability of the wine according to the quality grade difference, the wine database and the current brewing process table of the wine; Determine multiple abnormal events of the wine according to the abnormal traceability of the wine, and trigger the recheck of the corresponding data based on the multiple abnormal events of the wine to achieve the recheck of multiple abnormal events; Determine the data to be optimized according to the recheck of multiple abnormal events, and determine the subsequent wine brewing process table according to the data to be optimized and the current brewing process table of the wine, so as to optimize the wine brewing process table.

7. The quality evaluation method of wine according to claim 1, characterized in that, The real-time update of the quality grade of the wine, and determine the sales area of the updated wine based on the updated quality grade of the wine, the price level of the wine, and the quality grade of the competing products in the same period, including: Use the subsequent wine brewing process table to brew the wine, and real-time update the quality grade of the wine to determine the updated quality grade of the wine; Determine the quality grade of the competing products in the same period based on the model information of the wine and the competing product matching table; Determine multiple advantageous features according to the interaction of the updated quality grade of the wine, the price level of the wine, and the quality grade of the competing products in the same period, and determine the sales area of the updated wine according to the multiple advantageous features and the previous sales data table of the wine.

8. A quality evaluation system for wine, characterized in that, The wine quality evaluation system is applied to the wine quality evaluation method as described in any one of claims 1-7, and the wine quality evaluation system includes: A maturity module for determining the corresponding data space of the wine based on the model information of the wine and the corresponding wine database, and determining the grape grade parameter according to the traversal of the data space of the wine; A quality parameter module, configured to determine a first quality parameter of the wine according to the grade parameter of the grape, the origin of the grape, and the corresponding wine-making environment; perform real-time detection on the wine, and determine a second quality parameter of the wine according to the component content of the wine, the color degree of the wine, and the storage environment of the wine; A quality grade module, configured to evaluate the quality grade of the wine according to the first quality parameter, the second quality parameter of the wine, and the taste parameter of the wine; A regulation module, configured to trigger an abnormal traceability of the wine if the quality grade of the wine is lower than a preset quality grade, determine multiple abnormal events of the wine according to the abnormal traceability of the wine; determine a subsequent wine-making process schedule based on a review of the multiple abnormal events; A sales module, configured to update the quality grade of the wine in real time, and determine an updated sales area of the wine based on the updated quality grade of the wine, the price level of the wine, and the quality grades of competing products in the same period.

9. A device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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