A method, system, chip, device and computer readable storage medium for rapidly identifying the origin and evaluating the quality of cubeb based on an electronic nose and an electronic tongue

Abstract

The application discloses a method, system, chip, device and computer readable storage medium for rapidly identifying the producing area of Amomum villosum and evaluating the quality of Amomum villosum based on an electronic nose and an electronic tongue, and belongs to the technical field of traditional Chinese medicine identification. The technical problems to be solved are low detection efficiency and high cost of the existing Amomum villosum identification method. The technical solution points are as follows: a method for rapidly identifying the producing area of Amomum villosum and evaluating the quality of Amomum villosum based on an electronic nose and an electronic tongue, which comprises the following steps: electronic nose test sample preparation and electronic tongue test sample preparation; an electronic nose system adopts a direct headspace air suction method to collect signals of the electronic nose test sample; an electronic tongue system collects signals of the electronic tongue test sample; average values of response values are extracted to form an odor characteristic vector; data analysis and producing area identification / quality evaluation are performed according to the fusion characteristic vector, and finally, model application is performed.

Description

Technical Field

[0001] This invention provides a method, system, chip, device, and computer-readable storage medium for rapid identification of the origin and quality evaluation of Amomum villosum based on the combined use of an electronic nose and an electronic tongue, belonging to the field of traditional Chinese medicine identification technology. Background Technology

[0002] Amomum villosum is a typical medicinal and edible herb. Its quality, efficacy, and market value are highly correlated with its growing region. Yangchun in Guangdong, Changtai in Fujian, Chengmai in Hainan, and Xishuangbanna in Yunnan are the four major Amomum villosum producing areas in China. Significant differences exist in the volatile oil and water-soluble flavor compounds of Amomum villosum from different producing areas, necessitating standardized identification methods for differentiation. Currently, the mainstream identification methods in the industry fall into two categories: Human sensory evaluation: Relies on the comprehensive judgment of senior pharmacists by sight, smell and taste. It is entirely dependent on the personal experience of practitioners. There is no unified quantitative standard for the test results. It is highly subjective, has poor repeatability, and has a long training cycle for professionals. It is not suitable for screening large batches of samples. Large-scale instrumental physicochemical testing: GC-MS, HPLC and other equipment are used to quantitatively detect single chemical components such as bornyl acetate and volatile oil. The detection accuracy is high, but the equipment purchase and maintenance costs are high, the sample pretreatment steps are cumbersome, and each test takes a long time. In addition, it can only quantify a single index and cannot fully characterize the overall flavor quality characteristics of Amomum villosum in terms of "aroma + taste".

[0003] Existing technologies also include solutions that use electronic noses or electronic tongues alone to detect the flavor of Chinese medicinal materials, but both suffer from the drawback of missing information in a single dimension: electronic noses can only collect volatile odor substances and cannot distinguish between cardamom samples with similar odors but large differences in taste profiles; electronic tongues can only detect water-soluble taste substances and lose key volatile flavor fingerprint information, resulting in poor clustering and separation effects based on the origin of a single device and insufficient identification accuracy.

[0004] Relevant patent documents retrieved: Country of Origin: China; Publication Number: CN105181916A; Publication Date: December 23, 2015. This document discloses a method for detecting and quantifying the aroma of traditional Chinese medicine and its corresponding syndromes using electronic nose and electronic tongue sensor technology, including the following steps: (1) Establish a standardized quantitative fingerprint database for the detection of the aroma of Chinese medicinal herbs and their corresponding symptoms; (2) Collect the odor of the Chinese herbal medicine to be tested and its corresponding syndromes to detect quantitative fingerprint spectrum; (3) The detection quantitative fingerprint spectrum of the Chinese medicine odor and its corresponding syndrome of the test sample is compared with the standardized Chinese medicine odor and its corresponding syndrome quantitative fingerprint spectrum library to determine the Chinese medicine odor and its corresponding syndrome of the test sample.

[0005] Relevant non-patent literature retrieved: The journal is titled "Frontiers in Chemistry," and the article titled "Development of a variety and quality evaluation method for Amomi fructus using GC, electronic tongue, and electronic nose," volume number 11, published in June 2023. This article discloses a scheme for evaluating the quality of Amomi fructus using gas chromatography, electronic nose, and electronic tongue. However, it relies on GC chromatographic data for modeling, making the method complex, and it does not provide model predictions for Amomi fructus and its origin.

[0006] The prior art represented by the aforementioned documents has at least the following unresolved technical problems or defects: Patent CN105181916A is a general-purpose framework for the identification and detection of the aroma of traditional Chinese medicine. It is a broad-spectrum and general solution. However, it does not optimize the sensor array and acquisition parameters for the specific characteristics of Amomum villosum, such as the easy volatility of volatile oil, subtle differences in flavor from different places of origin, and large fluctuations in effective components at different harvesting periods. When directly used for Amomum villosum detection, subtle differences in flavor from different places of origin cannot be effectively distinguished, and it lacks the ability to adapt to the detection of special medicinal materials. Summary of the Invention

[0007] The purpose of this invention is to provide: This invention provides a rapid identification and quality evaluation method for Amomum villosum based on the combined use of an electronic nose and an electronic tongue, and related technologies, to solve the technical problems of existing Amomum villosum identification methods, such as subjectivity, low detection efficiency, high cost, incomplete information based on a single flavor dimension, and lack of standardized and dedicated detection processes.

[0008] Terminology Explanation: Unless otherwise defined, all technical terms used herein have the same meanings as commonly understood by one of ordinary skill in the art to which the subject matter pertains. Unless otherwise stated, all patents, patent inventions, and publications cited throughout this document are incorporated herein by reference in their entirety. Where multiple definitions exist for terms, the definitions provided in this chapter shall prevail.

[0009] It should be understood that the above brief description and the following detailed description are exemplary and for illustrative purposes only, and do not limit the subject matter of the invention in any way. In this invention, the singular is used in conjunction with the plural unless otherwise specifically stated. It should also be noted that, unless otherwise stated, the use of “or” or “or” means “and / or”. Furthermore, the use of the term “comprising” and other forms such as “including,” “containing,” and “contains” are not limiting.

[0010] The definitions of standard chemical and Chinese medicinal material testing terms can be found in the reference "Analysis and Testing of Traditional Chinese Medicine" by Shi Weijing.

[0011] Unless otherwise stated, conventional methods within the scope of the art, such as electronic nose sensor signal baseline correction, electronic tongue membrane potential calibration, principal component analysis (PCA), linear discriminant analysis (LDA), ultrasonic extraction of samples, centrifugation, and other conventional detection and data processing methods, shall be used.

[0012] Unless specifically defined herein, the use of all commercially available products herein employs standard techniques. For example, it may be carried out using the manufacturer's instructions for use with the kit, or in accordance with methods known in the art or the description of this invention. The techniques and methods described herein can generally be implemented according to conventional methods well known in the art, based on the descriptions in the various summary and more specific documents cited and discussed in this specification.

[0013] The terms “optional / arbitrary” or “optionally / arbitrarily” mean that the event or situation described below may or may not occur, including both the occurrence and non-occurrence of the event or situation.

[0014] In a first aspect, the present invention provides: a method for rapid identification and quality evaluation of Amomum villosum origin based on the combined use of an electronic nose and an electronic tongue, comprising the following steps: S1. Electronic nose test sample preparation: Place the Amomum villosum sample powder in a container and allow the container to stand and reach equilibrium; Electronic tongue test sample preparation: Add the Amomum villosum sample powder to water, stir, sonicate, centrifuge, and take the supernatant; S2. The electronic nose system uses the direct headspace inhalation method to acquire signals from the electronic nose test sample, and acquires the response values ​​of each sensor throughout the entire sampling period. S3. The electronic tongue system acquires signals from the electronic tongue test sample to obtain the relative intensity value of taste indicators, bitter aftertaste, astringent aftertaste, and richness. S4. Extract the average response value from the response value to form an odor feature vector; The relative intensity values ​​of taste indicators and the measurements of sourness, bitterness, astringency, umami, sweetness, saltiness, bitterness aftertaste, astringency aftertaste, and richness are extracted to form a taste feature vector; the odor feature vector and the taste feature vector are combined to form a fused feature vector. S5. Perform data analysis and origin identification / quality evaluation based on the fused feature vectors, and finally apply the model.

[0015] In some implementations, the amount of Amomum villosum powder in the electronic nose test sample in step S1 is 0.1 g / 100 mL container volume.

[0016] In some implementations, the concentration of Amomum villosum powder in the electronic tongue test sample in step S1 is 1 g / 100 mL.

[0017] In some implementations, the response value in step S2 includes the response value of a sensor sensitive to nitrogen oxides (W5S) and / or a sensor sensitive to inorganic sulfides (W1W).

[0018] In some implementations, the signal acquisition time of the electronic nose system in step S2 is 80 seconds, and the data from 70-72 seconds is extracted as feature values.

[0019] In some implementations, the sensors of the electronic tongue system described in step S3 include at least one of the following: umami sensor (AAE), salty sensor (CT0), sour sensor (CA0), bitter sensor (CO0), astringent sensor (AE1), and sweet sensor (GL1).

[0020] In some implementations, the relative intensity value in step S3 is obtained by calculating the difference between the membrane potential Vs and the reference liquid potential Vr when the electronic tongue system signal is acquired for 30 seconds. Preferably, the reference solution is an aqueous solution containing 30 mM KCl and 0.3 mM tartaric acid.

[0021] In some implementations, in step S3, the bitter aftertaste, astringent aftertaste, and richness are obtained by testing the sensor in the sample, washing it in a reference solution, measuring the membrane potential Vr' of the reference solution, and calculating the difference between Vr' and Vr.

[0022] In some implementation schemes, the data analysis in step S5 is as follows: performing PCA analysis on the fused feature vector to establish a PCA identification model; and performing LDA analysis in conjunction with known origins to establish an LDA prediction model.

[0023] Preferably, the PCA analysis is performed by performing PCA analysis on the fused feature vectors of all samples, observing the distribution of samples from different origins on the PCA score map, with the cumulative contribution rate of the electronic nose PCA being higher than 99%, and the cumulative contribution rate of the electronic tongue PCA reaching 97.14%, and the sample points being clustered and separated, thus establishing a PCA identification model.

[0024] Preferably, the LDA analysis is performed as follows: given the origin label, LDA analysis is conducted to further amplify the differences between groups, achieve a clear classification of origin, and establish an LDA prediction model.

[0025] In some implementations, the origin identification / quality evaluation in step S5 is: comparing key sensor response values ​​and key taste indicators to achieve rapid identification.

[0026] Preferably, the key sensor response values ​​are in the order of response intensity of W5S / R2 and W1W / R7.

[0027] Preferably, the key taste indicators include: taste feature vectors of bitterness, astringency, bitter aftertaste, and astringency aftertaste.

[0028] In some implementations, the model application in step S5 is as follows: inputting the fused feature vector into the established PCA prediction model or LDA identification model, and outputting its origin prediction result or quality similarity score.

[0029] Secondly, the present invention provides a system for rapid identification of the origin and quality evaluation of Amomum villosum, comprising: an electronic nose device, an electronic tongue device, and a data processing unit that connects and controls the electronic nose and the electronic tongue; the data processing unit performs data analysis and origin identification / quality evaluation based on fused feature vectors, and finally applies the model.

[0030] Thirdly, the present invention provides a chip comprising a processor and a memory, wherein the memory stores machine-executable instructions of the above-described method.

[0031] Fourthly, the present invention provides: a device for rapid identification and quality evaluation of Amomum villosum origin based on the combined use of an electronic nose and an electronic tongue, including the aforementioned chip.

[0032] Fifthly, the present invention provides a computer-readable storage medium storing a program for performing the method.

[0033] The present invention has at least the following beneficial effects: 1. More Comprehensive Identification Dimensions: This study is the first to propose combining an electronic nose (olfactory sensor array) and an electronic tongue (taste sensor array) for the analysis of Amomum villosum. Experiments demonstrate that the electronic nose can effectively distinguish four origins (PCA cumulative contribution rate >99%, LDA complete separation), with Yangchun from Guangdong showing the strongest aroma intensity. The electronic tongue also effectively distinguishes origins (PCA cumulative contribution rate reaches 97.14%) and reveals unique taste profiles such as "high astringency and low bitterness" in Changtai, Fujian, and "high bitterness and astringency" in Hainan and Yunnan. The combined use of these two technologies provides a dual evidence chain of "odor fingerprint" + "taste map," resulting in more comprehensive identification evidence and more reliable results.

[0034] 2. It achieves rapid and objective identification: The entire testing process can be completed within tens of minutes (direct powder testing + aqueous solution testing), without the need for complex pretreatment, and is entirely based on instrument detection and software analysis. The results are presented in charts and data, completely eliminating the influence of human subjective factors and realizing the objectification, standardization and digitization of cardamom identification.

[0035] 3. Key characteristic sensor indicators that can be used for identification were discovered: The experiment clarified the key odor sensors (such as W5S / R2 which is sensitive to nitrogen oxides and W1W / R7 which is sensitive to inorganic sulfides) and key taste indicators (such as astringency, bitterness, saltiness and sourness contribute the most to PC1 / PC2) to distinguish cardamom from different origins.

[0036] 4. The optimal detection mode was optimized and determined, improving the method's universality and stability: Through comparative experiments, the optimal detection mode for Amomum villosum was determined: For the electronic nose, the direct headspace aspiration method for testing powder samples (0.1 g / 100 mL headspace) is the simplest to operate and has the best distinguishing effect; for the electronic tongue, 1 g / 100 mL aqueous solution was determined to be the optimal test concentration. This optimization scheme makes the method more repeatable and practical.

[0037] 5. This method lays the foundation for establishing a quality database and intelligent identification model for Amomum villosum: The multidimensional data generated by this method (response values ​​of 10 odor sensors and multiple taste index values) can be used to construct a standard database of "odor-taste" for Amomum villosum from different origins. Furthermore, it utilizes pattern recognition algorithms such as PCA, LDA, and cluster analysis to establish an identification model, providing a core technical solution for developing intelligent and portable rapid identification equipment for Amomum villosum. Attached Figure Description

[0038] Figure 1 This is the overall flowchart of the present invention.

[0039] Figure 2 PCA principal component analysis diagrams of Amomum villosum (powder) samples from four different origins using an electronic nose.

[0040] Figure 3 The image shows the LDA analysis results of Amomum villosum (powder) samples from four different origins using an electronic nose.

[0041] Figure 4 Loading analysis graph showing the contribution rate of each sensor in the electronic nose to the principal components.

[0042] Figure 5 Electronic tongue PCA principal component analysis diagrams of Amomum villosum (powder) samples from four different origins. Detailed Implementation

[0043] The following non-limiting embodiments are intended to enable those skilled in the art to gain a more comprehensive understanding of the present invention, but do not limit the invention in any way. The following content is merely an exemplary description of the scope of protection claimed by the present invention, and those skilled in the art can make various changes and modifications to the present invention based on the disclosed content, and such changes should also fall within the scope of protection claimed by the present invention.

[0044] The present invention will be further described below by way of specific embodiments. Unless otherwise specified, all instruments, devices, equipment, reagents, products, etc., used in the embodiments of the present invention are obtained through conventional commercial means.

[0045] Example 1 A rapid method for identifying the origin and evaluating the quality of Amomum villosum based on the combined use of an electronic nose and an electronic tongue includes the following steps: Step S1: Sample preparation Electronic nose test sample preparation: Accurately weigh 0.1g of Amomum villosum sample powder, place it in a 100mL clean beaker, seal it with double-layer plastic wrap, and let it stand at room temperature for 10 minutes to equilibrate and make the headspace gas uniform.

[0046] Electronic tongue test sample preparation: Accurately weigh 1.0 g of Amomum villosum sample powder, place it in a beaker, add 100 mL of purified water, stir and sonicate for 20 minutes (twice, 10 minutes each time), then centrifuge at 4000 rpm for 10 minutes, and take the supernatant as the test solution.

[0047] Step S2: Electronic nose signal acquisition An electronic nose system is used, equipped with 10 metal oxide sensors (such as W1C, W5S, W3C, W6S, W5C, W1S, W1W, W2S, W2W, W3S).

[0048] The direct headspace aspiration method is adopted: the electronic nose injection needle is inserted into the headspace of the sealed beaker prepared in step S1.

[0049] Set the detection parameters as follows: injection flow rate 400 mL / min, sampling time 80 seconds, sensor cleaning and zeroing time 5 seconds. Collect the response values ​​of each sensor throughout the entire sampling period, especially the response values ​​during the steady-state phase (extracting data from 70-72 seconds as feature values, as described in the report).

[0050] Step S3: Electronic tongue signal acquisition A taste analysis system is used, equipped with taste sensors for umami (AAE), saltiness (CT0), sourness (CA0), bitterness (CO0), astringency (AE1), and sweetness (GL1).

[0051] A 30 mM KCl + 0.3 mM tartaric acid solution was used as a reference solution.

[0052] Following the standard cleaning-equilibration-testing procedure, the sensor was immersed in the supernatant of the Amomum villosum aqueous solution prepared in step S1. The membrane potential Vs was collected after 30 seconds and compared with the reference liquid potential Vr. The relative intensity values ​​of taste indicators such as sour, sweet, bitter, salty, umami, and astringent were calculated. At the same time, the bitter aftertaste (Aftertaste-B), astringent aftertaste (Aftertaste-A), and richness were calculated.

[0053] Step S4: Feature Data Extraction and Fusion The average response values ​​(e.g., R1 to R10) of 10 sensors at characteristic time points (70-72 seconds) are extracted from the electronic nose data to form an odor feature vector.

[0054] The measured values ​​of indicators such as sourness, bitterness, astringency, umami, sweetness, saltiness, bitter aftertaste, astringent aftertaste, and richness are extracted from the electronic tongue data to form a taste feature vector.

[0055] The odor feature vector and the taste feature vector are combined to form a fused feature vector, which is used to characterize the comprehensive "odor-taste" fingerprint information of the cardamom sample.

[0056] Step S5: Data Analysis and Origin Identification / Quality Evaluation Principal Component Analysis (PCA): PCA analysis was performed on the fused feature vectors of all samples to observe the distribution of samples from different origins on the PCA score map. The cumulative PCA contribution rate of the electronic nose was >99%, and the cumulative PCA contribution rate of the electronic tongue reached 97.14%. Sample points were clustered and separated, allowing for the establishment of a PCA identification model. LDA linear discriminant analysis: LDA analysis is performed with known origin labels to further amplify the differences between groups. The samples from the four origins are completely separated without overlap, and an LDA prediction model can be established. Key indicator comparison: Directly compare the response values ​​of key sensors (response intensity order of W5S / R2 and W1W / R7: Yangchun, Guangdong > Changtai, Fujian > Chengmai, Hainan > Xishuangbanna, Yunnan) and key taste indicators (combination characteristics of bitterness and astringency) to achieve rapid identification; Model application: The fused feature vector obtained after processing the cardamom sample by S1-S4 is input into the established PCA or LDA identification model, and the origin prediction result or quality similarity score can be output.

[0057] Verification of technical effectiveness and / or analysis of technical problem solving Compared with existing technologies, this invention uses an electronic nose and electronic tongue to simultaneously collect multi-dimensional features of Amomum villosum aroma and taste, and constructs a fused feature vector. Combined with a PCA and LDA dual-layer discrimination model, it significantly improves the differentiation effect of Amomum villosum from different origins. Compared with existing combined schemes that rely on gas chromatography-assisted modeling, this invention eliminates complex chromatographic detection steps, simplifies the sample pretreatment process, significantly reduces equipment purchase and consumable maintenance costs, and significantly improves the efficiency of batch sample screening. At the same time, it makes up for the deficiency that a single electronic nose or electronic tongue can only obtain single-dimensional flavor information, fully covering information on volatile oils and water-soluble flavor substances, and significantly improving the differentiation of origin sample characteristics.

[0058] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A method for rapid identification of the origin and quality evaluation of Amomum villosum based on the combined use of an electronic nose and an electronic tongue, characterized in that, Includes the following steps: S1. Electronic nose test sample preparation: Place the Amomum villosum sample powder in a container and allow the container to stand and reach equilibrium; Electronic tongue test sample preparation: Add the Amomum villosum sample powder to water, stir, sonicate, centrifuge, and take the supernatant; S2. The electronic nose system uses the direct headspace inhalation method to acquire signals from the electronic nose test sample, and acquires the response values ​​of each sensor throughout the entire sampling period. S3. The electronic tongue system acquires signals from the electronic tongue test sample to obtain the relative intensity value of taste indicators, bitter aftertaste, astringent aftertaste, and richness. S4. Extract the average response value from the response value to form an odor feature vector; The relative intensity values ​​of taste indicators and the measurements of sourness, bitterness, astringency, umami, sweetness, saltiness, bitterness aftertaste, astringency aftertaste, and richness are extracted to form a taste feature vector; the odor feature vector and the taste feature vector are combined to form a fused feature vector. S5. Perform data analysis and origin identification / quality evaluation based on the fused feature vectors, and finally apply the model.

2. The method according to claim 1, characterized in that, In the electronic nose test sample of step S1, the amount of Amomum villosum powder is 0.1g / 100mL container volume; in the electronic tongue test sample of step S1, the concentration of Amomum villosum powder is 1g / 100mL.

3. The method according to claim 1, characterized in that, The response value mentioned in step S2 includes the response value of a sensor sensitive to nitrogen oxides and / or a sensor sensitive to inorganic sulfides. The signal acquisition time of the electronic nose system in step S2 is 80 seconds, and the data from 70-72 seconds is extracted as feature values.

4. The method according to claim 1, characterized in that, The sensors of the electronic tongue system described in step S3 include at least one of the following: umami sensor, salty sensor, sour sensor, bitter sensor, astringent sensor, and sweet sensor; The relative intensity value in step S3 is calculated by comparing the membrane potential Vs of the electronic tongue system after 30 seconds of signal acquisition with the reference liquid potential Vr; the reference liquid is an aqueous solution of KCl and tartaric acid. The bitter aftertaste, astringent aftertaste, and richness mentioned in step S3 are obtained by: after the electronic tongue system acquires the signal of the electronic tongue test sample, it is cleaned in the reference solution, and then the membrane potential Vr' of the reference solution is measured, and the difference between Vr' and Vr is calculated.

5. The method according to claim 1, characterized in that, The data analysis in step S5 is as follows: perform PCA analysis on the fused feature vector to establish a PCA identification model; combine the known place of origin to perform LDA analysis to establish an LDA prediction model.

6. The method according to claim 1, characterized in that, Step S5, the identification of origin / quality evaluation, involves comparing the response values ​​of key sensors and key taste indicators to achieve rapid identification. The model application in step S5 is as follows: input the fused feature vector into the established PCA prediction model or LDA identification model, and output its origin prediction result or quality similarity score.

7. A system for rapid identification of the origin and quality evaluation of Amomum villosum, characterized in that, include: An electronic nose device, an electronic tongue device, and a data processing unit that connects and controls the electronic nose and electronic tongue; the data processing unit performs data analysis and origin identification / quality evaluation based on fused feature vectors, and finally applies the model.

8. A chip comprising a processor and a memory, characterized in that, The memory stores machine-executable instructions for the method according to any one of claims 1-6; The processor can execute machine-executable instructions in memory to run the method.

9. An edge computing device, characterized in that, It integrates the chip and peripheral interface circuit described in claim 8.

10. A computer-readable storage medium, characterized in that, The system contains a program for performing the method described in any one of claims 1-6.

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