CN-122018344-A - Electronic nose-based method and system for monitoring fermentation quality of coarse cereal staple food on line

CN122018344ACN 122018344 ACN122018344 ACN 122018344ACN-122018344-A

Abstract

The application discloses an electronic nose-based coarse cereal staple food fermentation quality online monitoring method and system, which relate to the technical field of food fermentation monitoring and generate standardized gas response data by acquiring and preprocessing an original gas response signal of an electronic nose sensor array, based on the data matched with the dominant metabolism path and the contribution weight thereof, the current fermentation stage is diagnosed and the final quality is predicted, and the standard template is compared to generate a regulation and control instruction to regulate fermentation parameters, so that the dominant metabolism path in the fermentation process can be monitored in real time, the accurate stage diagnosis and quality prediction are realized, the fermentation process is regulated and controlled in time, and the stability of fermentation quality and the production efficiency are improved.

Inventors

BAI JUHONG
LU FUQING
ZHANG XINGCAN

Assignees

成都农业科技职业学院

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. An electronic nose-based method for monitoring the fermentation quality of coarse cereal staple food on line is characterized by comprising the following steps: Acquiring an original gas response signal generated by the electronic nose sensor array for monitoring gas generated in the target coarse cereal staple food fermentation process in real time, and preprocessing the original gas response signal to generate standardized gas response data; Based on the standardized gas response data, at least one dominant metabolic path and corresponding contribution weight data thereof are matched from a pre-stored metabolic path characteristic database, wherein the metabolic path characteristic database pre-stores standard gas response characteristic data corresponding to metabolic paths of various fermenting microorganisms; Diagnosing the current fermentation stage based on the dominant metabolic path and the contribution weight data to obtain stage diagnosis result data, and generating a prediction of final fermentation quality based on the dominant metabolic path, the contribution weight data and the stage diagnosis result data to obtain quality prediction result data; comparing the stage diagnosis result data and the quality prediction result data with pre-stored standard fermentation process template data, and generating process regulation instruction data for regulating the fermentation process according to the comparison result; and adjusting the fermentation environment parameters or the material composition of the target coarse cereal staple food according to the process regulation instruction data.
2. The method for online monitoring of the fermentation quality of coarse cereal staple food based on an electronic nose according to claim 1, wherein the step of matching at least one dominant metabolic pathway and corresponding contribution weight data thereof from a pre-stored metabolic pathway feature database based on the standardized gas response data comprises: Performing correlation calculation on the standardized gas response data and each group of standard gas response characteristic data in the metabolic path characteristic database to obtain a plurality of correlation metric values; Screening metabolic paths corresponding to standard gas response characteristic data with the correlation measurement value exceeding a preset threshold value from the metabolic path characteristic database according to the correlation measurement value to obtain a candidate metabolic path set; The standardized gas response data are expressed as linear combinations of standard gas response characteristic data corresponding to all candidate metabolic paths in the candidate metabolic path set, and a linear coefficient of each candidate metabolic path is calculated by solving a linear equation set corresponding to the linear combinations to serve as contribution weight data corresponding to the candidate metabolic path; And determining the first N candidate metabolic paths with the largest contribution weight data from the candidate metabolic path set according to the contribution weight data, wherein N is a positive integer.
3. The method for online monitoring of the quality of primary food fermentation of coarse cereals based on an electronic nose according to claim 2, wherein the step of expressing the standardized gas response data as a linear combination of standard gas response characteristic data corresponding to all candidate metabolic pathways in the candidate metabolic pathway set, and calculating a linear coefficient of each candidate metabolic pathway by solving a linear equation set corresponding to the linear combination, as contribution weight data corresponding to the candidate metabolic pathway comprises: Constructing a linear combination equation, wherein the standardized gas response data are used as known vectors, standard gas response characteristic data corresponding to all candidate metabolic paths in the candidate metabolic path set are used as column vectors of a coefficient matrix, and contribution weight data of each candidate metabolic path are used as unknown vectors to be solved; Solving the linear combination equation by adopting a constraint optimization algorithm, wherein the constraint condition applied by the constraint optimization algorithm is that the sum of all the contribution weight data is a fixed constant and each contribution weight data is non-negative; the error between the normalized gas response data and the estimated response data reconstructed from the coefficient matrix and the unknown vector is minimized by iterative computation to obtain contribution weight data for each candidate metabolic pathway that satisfies the constraint condition.
4. The method for online monitoring of quality of primary food fermentation of miscellaneous cereals based on an electronic nose according to claim 1, wherein the step of diagnosing the current fermentation stage based on the dominant metabolic pathway and the contribution weight data to obtain stage diagnosis result data, and generating a prediction of final fermentation quality based on the dominant metabolic pathway, the contribution weight data, and the stage diagnosis result data to obtain quality prediction result data comprises: Matching the dominant metabolism path and the corresponding contribution weight data with a pre-stored fermentation stage discrimination rule, and determining a stage identifier of the current fermentation stage according to a matching result to be used as the stage diagnosis result data, wherein the fermentation stage discrimination rule defines predefined dominant metabolism paths and preset weight ranges corresponding to different fermentation stages; Constructing multidimensional time series data based on a dominant metabolic path set corresponding to each sampling time point from the fermentation start to the current moment, contribution weight data of each dominant metabolic path and corresponding stage diagnosis result data; The multidimensional time series data are input into a pre-trained fermentation quality prediction model to output an evaluation index predicted value related to the final fermentation quality, and the evaluation index predicted value is used as the quality prediction result data.
5. The method for online monitoring of the fermentation quality of a staple food of miscellaneous cereals based on an electronic nose as claimed in claim 4, wherein the step of inputting the multidimensional time series data into a pre-trained fermentation quality prediction model to output an evaluation index prediction value regarding the final fermentation quality and using the evaluation index prediction value as the quality prediction result data comprises: Trend analysis is carried out on the contribution weight data of each dominant metabolic path in the multidimensional time series data, and the change rate of the contribution weight of each dominant metabolic path in a preset time window is calculated; according to the change rate, weighting calculation is carried out by combining pre-stored metabolic path influence weight coefficients, so as to obtain a group of metabolic activity intensity change indexes; And matching the metabolic activity intensity change index with a pre-stored quality influence relation table to output an evaluation index predicted value of the final fermentation quality as the quality prediction result data according to a matching result, wherein the quality influence relation table records the corresponding relation between the metabolic activity intensity change index and the final fermentation quality evaluation index.
6. The method for online monitoring of the fermentation quality of coarse cereal staple food based on an electronic nose according to claim 1, wherein the step of comparing the stage diagnosis result data and the quality prediction result data with pre-stored standard fermentation process template data and generating process control instruction data for controlling the fermentation process according to the comparison result comprises: Comparing the stage diagnosis result data with a predefined dominant metabolism path and a preset weight range of a corresponding stage in the standard fermentation process template data, and if the dominant metabolism path does not belong to the predefined dominant metabolism path or the corresponding contribution weight data exceeds the preset weight range, generating first-class deviation alarm data; Comparing the evaluation index predicted value in the quality predicted result data with a final quality target range defined in the standard fermentation process template data, and if the evaluation index predicted value exceeds the target range, generating second-class deviation alarm data; Inquiring a pre-stored regulation strategy mapping table according to at least one of the first type of deviation alarm data and the second type of deviation alarm data to generate a regulation action instruction comprising a regulation object and a regulation quantity to serve as the process regulation instruction data, wherein the regulation strategy mapping table defines the corresponding relation between the deviation type and the regulation action.
7. The method for online monitoring of the quality of fermented coarse cereal staple food based on an electronic nose as claimed in claim 6, wherein the step of querying a pre-stored regulation strategy mapping table according to at least one of the first type of deviation alert data and the second type of deviation alert data to generate a regulation action command including a regulation object and a regulation amount as the process regulation command data comprises: if the first type deviation alarm data exists, determining the current fermentation stage and the type of the deviated dominant metabolic path according to the data; If the second type deviation alarm data exists, determining a final quality evaluation index type which is not up to standard in prediction according to the data; And constructing a composite query condition by the current fermentation stage, the deviated dominant metabolic path type and the final quality evaluation index type which is not up to standard in prediction, carrying out joint query in the pre-stored regulation strategy mapping table, and generating the process regulation instruction data according to a query result, wherein the dimension of the regulation strategy mapping table corresponds to the fermentation stage, the metabolic path deviation type and the quality index deviation type, and regulation action instructions aiming at different composite query conditions are stored in the regulation strategy mapping table.
8. The method for online monitoring of the fermentation quality of coarse cereal staple food based on an electronic nose according to claim 1, wherein the method further comprises: In a controlled fermentation simulation environment, respectively inducing a plurality of purely-cultured fermentation microorganisms to enter and maintain a preset metabolic path activity state, collecting response signals of the electronic nose sensor array during the period that the preset metabolic path activity state is kept stable, and processing the collected response signals to obtain standard gas response signals corresponding to the metabolic path; Performing feature extraction on the standard gas response signals corresponding to each metabolic path to obtain the standard gas response feature data of the metabolic path; and storing the identification information of each metabolic path and the corresponding standard gas response characteristic data in a correlated way to form the metabolic path characteristic database.
9. The method for online monitoring of the fermentation quality of coarse cereal staple food based on an electronic nose according to claim 8, wherein the step of extracting the characteristic of the standard gas response signal corresponding to each metabolic pathway to obtain the standard gas response characteristic data of the metabolic pathway comprises the steps of: Dividing the standard gas response signal in the time dimension to obtain a plurality of time segments; Calculating at least two characteristic parameters of an average value, a maximum value, an ascending slope and a stable value of response signals of each sensor in the electronic nose sensor array in each time segment; And combining and dimension-reducing the characteristic parameters calculated by all the time slices to form standard gas response characteristic data capable of representing the metabolic pathway gas response mode.
10. An electronic nose-based on-line monitoring system for the fermentation quality of a coarse cereal staple food, which is characterized by comprising a memory, a processor and an on-line monitoring program for the fermentation quality of the coarse cereal staple food, which is stored on the memory and can run on the processor, wherein the on-line monitoring program for the fermentation quality of the coarse cereal staple food is configured to realize the steps of the on-line monitoring method for the fermentation quality of the coarse cereal staple food based on the electronic nose as claimed in any one of claims 1 to 9.

Description

Electronic nose-based method and system for monitoring fermentation quality of coarse cereal staple food on line Technical Field The application relates to the technical field of food fermentation monitoring, in particular to an electronic nose-based method and an electronic nose-based system for monitoring the fermentation quality of coarse cereal staple food. Background In the industrial fermentation production of coarse cereal staple foods, quality monitoring depends on artificial experience or rough setting of macroscopic parameters such as temperature, humidity, time and the like for a long time, and direct, on-line sensing and accurate regulation and control of microorganism metabolic activities cannot be realized. The coarse cereal raw material has a multi-matrix characteristic, has a complex microbial community structure, relates to dynamic interaction and metabolic path competition of various flora such as yeast, lactobacillus and the like, and causes the fermentation process to present a highly nonlinear characteristic. Although the electronic nose technology is introduced into the field of food fermentation monitoring due to the advantages of rapidness and no damage, the electronic nose technology is limited in processing complex systems with multiple matrixes and multiple bacterial groups such as coarse cereals. The existing method generally carries out simple association modeling on the mixed gas signals collected by the electronic nose and macroscopic quality indexes such as final product volume, acidity and the like to form 'black box' -type empirical mapping. The method ignores dynamic evolution rules of key metabolic pathways in the fermentation process, such as activity changes and interactions of pathways of glycolysis, lactic acid fermentation and the like, so that the model is seriously dependent on training data of a specific formula, and has weak generalization capability. When the gas signal is abnormal, harmful metabolites often accumulate to irreversible degree, an early warning mechanism is seriously lagged, and the quality degradation process cannot be blocked in time. Meanwhile, due to the lack of deep analysis on the metabolic mechanism, operators are difficult to identify specific metabolic path deviation behind abnormal signals, so that the regulation and control measures are lack of pertinence, and repeated trial and error adjustment of environmental parameters or material composition is often required, so that production efficiency is reduced and resources are wasted. The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present application and is not intended to represent an admission that the foregoing is prior art. Disclosure of Invention The application mainly aims to provide an electronic nose-based method and an electronic nose-based system for monitoring the fermentation quality of coarse cereal staple food on line, aiming at improving the stability of fermentation quality and production efficiency. In order to achieve the above purpose, the application provides an electronic nose-based method for monitoring the fermentation quality of coarse cereal staple food on line, which comprises the following steps: Acquiring an original gas response signal generated by the electronic nose sensor array for monitoring gas generated in the target coarse cereal staple food fermentation process in real time, and preprocessing the original gas response signal to generate standardized gas response data; Based on the standardized gas response data, at least one dominant metabolic path and corresponding contribution weight data thereof are matched from a pre-stored metabolic path characteristic database, wherein the metabolic path characteristic database pre-stores standard gas response characteristic data corresponding to metabolic paths of various fermenting microorganisms; Diagnosing the current fermentation stage based on the dominant metabolic path and the contribution weight data to obtain stage diagnosis result data, and generating a prediction of final fermentation quality based on the dominant metabolic path, the contribution weight data and the stage diagnosis result data to obtain quality prediction result data; comparing the stage diagnosis result data and the quality prediction result data with pre-stored standard fermentation process template data, and generating process regulation instruction data for regulating the fermentation process according to the comparison result; and adjusting the fermentation environment parameters or the material composition of the target coarse cereal staple food according to the process regulation instruction data. In one embodiment, the step of matching at least one dominant metabolic pathway and its corresponding contribution weight data from a pre-stored metabolic pathway characteristics database based on the normalized gas response data comprises: Performing correlation calculat