Uncooked pork flavor evaluation system for electronic nose monitoring
Through the electronic nose monitoring system combined with multi-dimensional data analysis, the subjectivity and insufficient risk monitoring of traditional pork freshness assessment are solved, and fast and accurate freshness assessment and dynamic optimization are achieved, which improves the flavor and safety of raw pork.
Patent Information
- Application Number
- CN202510801899.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-16
- Publication Date
- 2025-08-19
AI Technical Summary
Traditional pork freshness assessment methods are subjective and inefficient, unable to comprehensively and accurately reflect freshness, and lack comprehensive consideration and dynamic monitoring of various risk substances, making it difficult to control food safety risks and affect the stability of raw food flavor.
The electronic nose monitoring system is adopted, combined with a multi-dimensional data analysis module, including freshness detection, food safety risk warning, consumer preference collection and flavor optimization, and the evaluation standards are generated through algorithm formulas to achieve dynamic optimization of processing and storage conditions.
It has achieved rapid and accurate pork freshness assessment, dynamic monitoring of food safety risks, improved the stability and safety of raw food flavors, and reduced food safety risks.
Smart Images
Figure CN120507487A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of food detection, in particular to a raw pork flavor evaluation system for electronic nose monitoring. Background Art
[0002] In the field of food processing and safety monitoring, the flavor quality and safety of raw pork have always been a key focus of the industry. As consumers' expectations for fresh food quality continue to rise, accurately assessing pork freshness and potential safety risks has become crucial for ensuring both flavor and food safety. Traditional pork freshness assessment methods rely on sensory evaluation or single-indicator testing, which struggles to comprehensively and accurately reflect pork freshness and is subject to subjectivity and low efficiency. Testing for volatile compounds fails to effectively integrate the concentrations of multiple substances, resulting in a complex judgment process that is both time-consuming and labor-intensive and prone to misjudgment. Regarding food safety risk monitoring, existing technologies lack the comprehensive consideration and precise classification of multiple risk substances (such as antibiotics, aflatoxins, and heavy metals), making it difficult to dynamically monitor and proactively control food safety risks. When risk substances exceed standards, timely and targeted measures cannot be taken, leading to the release of problematic pork into the market and posing a threat to consumer health. Furthermore, traditional assessment systems cannot dynamically optimize storage and processing steps based on assessment results, making it difficult to ensure the flavor stability of raw pork. Therefore, there is an urgent need for a system that can integrate multi-dimensional data, accurately assess pork freshness and safety risks, and achieve dynamic optimization to meet the market demand for high-quality raw pork. Summary of the Invention
[0003] (1) Technical problems solved In response to the shortcomings of the existing technology, the present invention provides a raw pork flavor evaluation system for electronic nose monitoring, which has the advantages of multi-dimensional data integration, accurate evaluation and dynamic optimization. It solves the problems of traditional methods such as strong subjectivity, low detection efficiency, incomplete risk monitoring, and inability to control processing and storage conditions in real time.
[0004] (2) Technical solution To achieve the above objectives, the present invention provides the following technical solutions: a raw pork flavor evaluation system for electronic nose monitoring, comprising a pork freshness detection module, a food safety risk warning module, a consumer preference collection module, a data analysis module, a flavor evaluation module, and a flavor optimization module; The pork freshness detection module detects volatile substances in pork through an electronic nose to determine the freshness of the pork; The food safety risk warning module identifies potential risk substances such as drug residues, mold metabolites, and spoilage bacteria metabolites in pork based on electronic nose data; The consumer preference collection module collects the target population's preferences for raw pork flavor through pork surveys, pork sensory scores, and pork market data; The data analysis module integrates multi-dimensional data on freshness, safety risks, and consumer preferences, and generates evaluation criteria through an algorithmic formula; The flavor evaluation module comprehensively scores the raw pork flavor based on the analysis results; The flavor optimization module proposes improvement suggestions based on the evaluation results and verifies the optimization effects through a feedback loop.
[0005] Preferably, the pork freshness detection module detects pork freshness data, including concentration values of protein decomposition products, fatty acid oxidation products, microbial metabolites, carbohydrate degradation products, amino acid conversion products and other flavor-related trace components.
[0006] Preferably, the food safety risk warning module collects potential risk data of pork, including concentrations of antibiotics, aflatoxins, veterinary drugs, heavy metals, biotoxins and pesticides.
[0007] Preferably, the consumer preference collection module collects consumer preference data, including consumers' actual ratings of pork flavor and consumers' preference ratings of pork flavor.
[0008] Preferably, the data analysis module includes a freshness analysis unit, a warning safety risk analysis unit and a preference matching analysis unit.
[0009] Preferably, the freshness analysis unit calculates the pork freshness comprehensive index based on the pork freshness data , and its calculation formula is:
[0010] In the formula, Indicates the comprehensive index of pork freshness. represents the concentration of the volatile substance in item i, represents the weight coefficient of the concentration of the i-th volatile substance, Represents model parameters.
[0011] Preferably, the early warning safety risk analysis unit calculates the early warning safety risk index based on the pork potential risk data , and its calculation formula is:
[0012] In the formula, Represents the early warning safety risk index, represents the concentration of the jth risk substance, Indicates the national standard concentration limit of the jth risk substance, represents the risk level coefficient of the jth risk substance, Indicates the total number of risk substance types.
[0013] Preferably, the preference matching analysis unit calculates the pork flavor preference based on the consumer preference data. , and its calculation formula is:
[0014] In the formula, Indicates pork flavor preference, represents the actual rating of pork flavor by the kth consumer, represents the kth consumer’s preference score for pork flavor, Indicates the number of consumers.
[0015] Preferably, the flavor evaluation module is based on the pork freshness comprehensive index , to determine the freshness level, according to the early warning safety risk index , risk level classification, according to pork flavor preference , and conduct flavor compatibility evaluation.
[0016] Preferably, the flavor optimization module formulates a targeted optimization plan based on the evaluation results of the flavor evaluation module, and after optimization, each module is tested and evaluated again to form a closed-loop optimization.
[0017] Compared with the prior art, the present invention provides a raw pork flavor evaluation system for electronic nose monitoring, which has the following beneficial effects: 1. The present invention calculates the pork freshness comprehensive index As a quantitative indicator for measuring the freshness of pork, it provides the core basis for the system's subsequent flavor evaluation and optimization decisions. On the one hand, it integrates the concentrations of multiple volatile substances into a single value, simplifies the complex freshness judgment process, and enables the system to quickly and accurately evaluate the freshness of pork; on the other hand, based on this index, the system can dynamically adjust storage conditions and processing time parameters, thereby effectively extending the shelf life of pork, ensuring the stability of raw food flavor, and reducing food safety risks caused by unfresh meat.
[0018] 2. The present invention calculates the early warning safety risk index As an early warning scale for pork food safety risks, it helps the system to detect potential safety hazards in a timely manner. The index comprehensively considers the concentrations of multiple risk substances, national standard limits and risk levels, and can accurately grade the safety status of pork. Based on the index, the system can trigger early warning mechanisms at different levels in real time. For example, when the risk level is low, it prompts to increase the frequency of detection, and when the risk level is high, it immediately blocks the circulation of problematic pork. At the same time, it can also optimize the management and control measures of breeding and processing links in a targeted manner, realize dynamic monitoring and active prevention and control of food safety risks, and improve the safety of the entire system.
[0019] 3. The present invention uses the above algorithm formula to compare the difference between consumers' actual ratings of pork flavor and ideal ratings, and calculates the preference for pork flavor. The smaller the difference, the higher the pork flavor preference. The closer it is to 1, the more the pork flavor meets the consumer's preference; the greater the difference, the lower the pork flavor preference. The smaller the value, the less the pork flavor matches consumer preferences. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] Figure 1 This is a flow chart of the system of the present invention. DETAILED DESCRIPTION
[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0022] See also Figure 1 , a raw pork flavor evaluation system for electronic nose monitoring, including a pork freshness detection module, a food safety risk early warning module, a consumer preference collection module, a data analysis module, a flavor evaluation module, and a flavor optimization module; The pork freshness detection module uses an electronic nose to detect volatile substances (such as ammonia and hydrogen sulfide) in pork to determine the freshness of the pork. As the basic input of the system, it must be executed first to ensure the accuracy of subsequent analysis. Stale meat may directly affect the flavor and safety. The food safety risk warning module uses electronic nose data to identify potential risk substances such as drug residues, mold metabolites, and spoilage bacteria metabolites in pork, closely following freshness testing, as spoiled or contaminated meat may pose both safety risks and flavor abnormalities. The consumer preference collection module collects information on the target population's preferences for raw pork flavor (such as fat-to-lean ratio and seasoning needs) through pork research, pork sensory evaluation, and pork market data. After completing basic testing, it runs and provides a reference standard for "ideal flavor" for subsequent analysis. The data analysis module integrates multi-dimensional data on freshness, safety risks, and consumer preferences, generates evaluation criteria through three algorithmic formulas, and transforms raw data into evaluable information; The flavor evaluation module comprehensively scores the raw pork flavor based on the analysis results, such as "normal," "offensive," and "not in line with preferences." This module relies on data analysis output to directly guide optimization. Based on the evaluation results, the flavor optimization module proposes improvement suggestions (such as adjusting feed formula, processing technology or storage conditions) and verifies the optimization effect through a feedback loop as the final output of the system to achieve closed-loop control.
[0023] The advantages are: the system of the present invention uses an electronic nose sensor array combined with three algorithm formulas to achieve real-time analysis of volatile substance concentrations and calculation of a comprehensive freshness index. At the same time, it integrates risk substance detection data, builds a graded early warning mechanism, and dynamically optimizes processing technology and storage parameters based on the evaluation results, thereby improving the flavor stability and safety of raw pork.
[0024] The pork freshness detection module detects pork freshness data, including the concentration values of protein decomposition products (such as ammonia and amine compounds), fatty acid oxidation products (such as aldehydes and ketones), microbial metabolites (such as esters and acids), sugar degradation products (such as alcohols and furan compounds), amino acid conversion products (such as indole, hydrogen sulfide and other sulfur-containing compounds), and other flavor-related trace components. The above multi-dimensional volatile substance concentration data can not only objectively reflect the degree of pork spoilage, but also avoid the subjective errors of traditional sensory evaluation, quickly identify stale meat, and reduce the risk of foodborne diseases caused by microbial metabolism (such as ammonia substances produced by protein degradation).
[0025] The food safety risk warning module collects potential risk data on pork, including antibiotics, aflatoxins, veterinary drugs, heavy metals, biological toxins and pesticides, to solve the problems of single and lagging traditional testing, and to issue timely warnings when the concentration exceeds the standard. Based on the comparison between the concentration of risk substances and the national standard limit (such as heavy metal exceeding the standard triggering a first-level warning), a graded response from "prompting strengthened testing" to "blocking circulation" is achieved.
[0026] The consumer preference collection module collects consumer preference data, including consumers' actual ratings of pork flavor and consumers' preference ratings of pork flavor. By comparing consumers' satisfaction with actual flavor (such as acceptance of fat-to-lean ratio) with ideal preferences (such as seasoning requirements), it identifies product improvement directions.
[0027] The data analysis module includes a freshness analysis unit, a warning safety risk analysis unit, and a preference matching analysis unit.
[0028] The freshness analysis unit calculates the pork freshness comprehensive index based on the pork freshness data , and its calculation formula is:
[0029] In the formula, Indicates the comprehensive index of pork freshness. represents the concentration of the volatile substance in item i, The weight coefficient representing the concentration of the i-th volatile substance, which includes sulfides, alcohols, aldehydes and ketones, methyl compounds, aromatic compounds, organic sulfides and other volatile organic compounds. 、 、 、 、 、 、 Respectively represent the concentration values of sulfides, alcohols, aldehydes and ketones, methyl compounds, aromatic compounds, organic sulfides and other volatile organic compounds. 、 、 、 、 、 、 Respectively represent the weight coefficients of sulfides, alcohols, aldehydes and ketones, methyl compounds, aromatic compounds, organic sulfides and other volatile organic compounds in volatile substances, Represents model parameters.
[0030] Advantages: By calculating the comprehensive index of pork freshness As a quantitative indicator for measuring the freshness of pork, it provides the core basis for the system's subsequent flavor evaluation and optimization decisions. On the one hand, it integrates the concentrations of multiple volatile substances into a single value, simplifies the complex freshness judgment process, and enables the system to quickly and accurately evaluate the freshness of pork; on the other hand, based on this index, the system can dynamically adjust storage conditions and processing time parameters, thereby effectively extending the shelf life of pork, ensuring the stability of raw food flavor, and reducing food safety risks caused by unfresh meat.
[0031] The early warning safety risk analysis unit calculates the early warning safety risk index based on the potential risk data of pork , and its calculation formula is:
[0032] In the formula, Represents the early warning safety risk index, represents the concentration of the jth risk substance (such as antibiotics, aflatoxins, veterinary drugs, heavy metals, biotoxins and pesticides), Indicates the national standard concentration limit of the jth risk substance, Indicates the risk level coefficient of the jth risk substance, including levels 1-3, Indicates the total number of risk substance types.
[0033] Advantages: By calculating the early warning safety risk index As an early warning scale for pork food safety risks, it helps the system to detect potential safety hazards in a timely manner. The index comprehensively considers the concentrations of multiple risk substances, national standard limits and risk levels, and can accurately grade the safety status of pork. Based on the index, the system can trigger early warning mechanisms at different levels in real time. For example, when the risk level is low, it prompts to increase the frequency of detection, and when the risk level is high, it immediately blocks the circulation of problematic pork. At the same time, it can also optimize the management and control measures of breeding and processing links in a targeted manner, realize dynamic monitoring and active prevention and control of food safety risks, and improve the safety of the entire system.
[0034] The preference matching analysis unit calculates pork flavor preference based on consumer preference data , and its calculation formula is:
[0035] In the formula, Indicates pork flavor preference, represents the actual rating of pork flavor by the kth consumer, represents the kth consumer’s preference score for pork flavor, Indicates the number of consumers; The advantage is that the above algorithm formula is used to compare the difference between consumers' actual ratings of pork flavor and their ideal ratings, and calculate the preference for pork flavor. The smaller the difference, the higher the pork flavor preference. The closer it is to 1, the more the pork flavor meets the consumer's preference; the greater the difference, the lower the pork flavor preference. The smaller the value, the less the pork flavor matches consumer preferences.
[0036] The flavor evaluation module is based on the pork freshness comprehensive index , to determine the freshness level, when the pork freshness comprehensive index When ≥0.8, the freshness is judged as "excellent"; when 0.6≤Pork Freshness Comprehensive Index When the pork freshness comprehensive index is less than 0.8, the freshness is judged as “good”; when the pork freshness comprehensive index is less than 0.8, the freshness is judged as “good”; When the value is less than 0.6, the freshness is judged as “poor” and the warning safety risk index is used. , divide the risk level, and when the warning safety risk index When ≤0.3, the safety risk is judged to be "low"; when 0.3<warning safety risk index When the safety risk index is ≤0.7, the safety risk is judged to be “medium”; when the warning safety risk index is When the value is greater than 0.7, the safety risk is judged to be “high”. , to evaluate the flavor compatibility, when the pork flavor preference When ≥0.8, the flavor compatibility is judged as "highly compatible"; when 0.6≤ pork flavor preference When the flavor preference is less than 0.8, the flavor compatibility is judged as “moderate compatibility”; when the pork flavor preference is less than 0.8, the flavor compatibility is judged as “moderate compatibility”; When <0.6, the flavor compatibility is judged as “low compatibility”; Note: The final comprehensive score is given by comprehensively evaluating the freshness level, safety risk level and flavor compatibility: if the freshness is "excellent", the safety risk is "low" and the flavor compatibility is "highly compatible", the comprehensive score is "normal"; if the freshness is "poor" or the safety risk is "high", the comprehensive score is "off-flavor"; if the flavor compatibility is "lowly compatible", the comprehensive score is "not in line with" preference.
[0037] The flavor optimization module formulates a targeted optimization plan based on the evaluation results of the flavor evaluation module. When the value is below 0.6, it is judged that the freshness is insufficient and it is recommended to optimize the storage conditions, such as lowering the storage temperature to 0-4°C, increasing the carbon dioxide concentration in the modified atmosphere packaging, and inhibiting the growth of microorganisms; at the same time, optimize the processing technology and adopt rapid cooling technology to reduce microbial contamination during the processing. When the range is higher than 0.7, it is determined that there is a high safety risk, and the sale of the batch of pork will be stopped immediately. The breeding process will be traced back, and the use of feed and veterinary drugs will be checked. The sanitation management of the slaughtering and processing process will be strengthened, the disinfection procedures will be strictly implemented, and the equipment and environment will be fully tested. When the pork flavor preference is higher than 0.7, the pork flavor preference will be higher than 0.7. When it is below the range of 0.6, it is determined that the flavor is greatly different from consumer preferences. Based on consumer survey feedback, the feed formula is adjusted, for example, increasing the content of specific fatty acids to improve the meat flavor; optimizing the processing technology, such as adjusting the marinating time and seasoning ratio, or improving the aging treatment method to enhance the flavor of raw pork. After optimization, each module is tested and evaluated again to form a closed-loop optimization.
[0038] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.
Claims
1. A raw pork flavor evaluation system for electronic nose monitoring, characterized in that: It includes pork freshness detection module, food safety risk warning module, consumer preference collection module, data analysis module, flavor evaluation module, and flavor optimization module; The pork freshness detection module detects volatile substances in pork through an electronic nose to determine the freshness of the pork; The food safety risk warning module identifies potential risk substances such as drug residues, mold metabolites, and spoilage bacteria metabolites in pork based on electronic nose data; The consumer preference collection module collects the target population's preferences for raw pork flavor through pork surveys, pork sensory scores, and pork market data; The data analysis module integrates multi-dimensional data on freshness, safety risks, and consumer preferences, and generates evaluation criteria through an algorithmic formula; The flavor evaluation module comprehensively scores the raw pork flavor based on the analysis results; The flavor optimization module proposes improvement suggestions based on the evaluation results and verifies the optimization effects through a feedback loop.
2. The raw pork flavor evaluation system for electronic nose monitoring according to claim 1, characterized in that: The pork freshness detection module detects pork freshness data, including concentration values of protein decomposition products, fatty acid oxidation products, microbial metabolites, sugar degradation products, amino acid conversion products, and other flavor-related trace components.
3. The raw pork flavor evaluation system for electronic nose monitoring according to claim 1, characterized in that: The food safety risk early warning module collects data on potential risks of pork, including concentrations of antibiotics, aflatoxins, veterinary drugs, heavy metals, biotoxins and pesticides.
4. The raw pork flavor evaluation system for electronic nose monitoring according to claim 1, characterized in that: The consumer preference collection module collects consumer preference data, including consumers' actual ratings of pork flavor and consumers' preference ratings of pork flavor.
5. The raw pork flavor evaluation system for electronic nose monitoring according to claim 1, characterized in that: The data analysis module includes a freshness analysis unit, a warning safety risk analysis unit and a preference matching analysis unit.
6. The raw pork flavor evaluation system for electronic nose monitoring according to claim 5, characterized in that: The freshness analysis unit calculates the pork freshness comprehensive index based on the pork freshness data , and its calculation formula is: In the formula, Indicates the comprehensive index of pork freshness. represents the concentration of the volatile substance in item i, represents the weight coefficient of the concentration of the i-th volatile substance, Represents model parameters.
7. The raw pork flavor evaluation system for electronic nose monitoring according to claim 5, characterized in that: The early warning safety risk analysis unit calculates the early warning safety risk index based on the pork potential risk data , and its calculation formula is: In the formula, Represents the early warning safety risk index, represents the concentration of the jth risk substance, Indicates the national standard concentration limit of the jth risk substance, represents the risk level coefficient of the jth risk substance, Indicates the total number of risk substance types.
8. The raw pork flavor evaluation system for electronic nose monitoring according to claim 5, characterized in that: The preference matching analysis unit calculates the pork flavor preference based on the consumer preference data , and its calculation formula is: In the formula, Indicates pork flavor preference, represents the actual rating of pork flavor by the kth consumer, represents the kth consumer’s preference score for pork flavor, Indicates the number of consumers.
9. The raw pork flavor evaluation system for electronic nose monitoring according to claim 1, characterized in that: The flavor evaluation module is based on the pork freshness comprehensive index , to determine the freshness level, according to the early warning safety risk index , risk level classification, according to pork flavor preference , and conduct flavor compatibility evaluation.
10. The raw pork flavor evaluation system for electronic nose monitoring according to claim 1, characterized in that: The flavor optimization module formulates a targeted optimization plan based on the evaluation results of the flavor evaluation module. After optimization, each module is tested and evaluated again to form a closed-loop optimization.