A method for determining the producing area of Longjing tea based on food-grade colorimetric sensor

Abstract

The present invention discloses a method for determining the origin of Longjing tea based on a food-grade colorimetric sensor. The method comprises the following steps: using an EGCG standard as a reactant, screening and optimizing the type of metal ions added to each colorimetric point of the sensor and the optimal pH value; constructing a sensor array based on the colorimetric points of the sensor obtained by the screening; collecting Longjing tea samples from different originating and non-originating regions to prepare tea soup samples; obtaining sensor image information of the Longjing tea soup samples from different originating regions before and after reaction in the colorimetric sensor array, and calculating the RGB difference of each colorimetric point before and after reaction; establishing a supervised determination model for originating and non-originating Longjing tea based on the RGB difference information of the sensor images; and determining unknown Longjing tea samples based on the determination model. The determination method according to the present invention can accurately distinguish between originating and non-originating Longjing tea, greatly reducing the risk of chemical reagent leakage to the operator and tea samples during the detection process.

Description

Technical Field

[0001] The present invention relates to the technical field of food detection, and in particular to a method for determining a Longjing tea producing area based on a food-grade colorimetric sensor. Background Art

[0002] Longjing tea is a quintessential premium tea, renowned for its "green color, rich fragrance, mellow flavor, and beautiful appearance." According to the geographical indication definition for Longjing tea in GB / T18650-2008, the administrative area of Hangzhou's Xihu District (West Lake Scenic Area) is designated as the West Lake production area; the administrative areas of Hangzhou's Xiaoshan, Binjiang Yuhang, Fuyang, Lin'an, Tonglu, Jiande, and Chun'an counties (cities, and districts) are designated as the Qiantang production area; and the administrative areas of Shaoxing, Yuecheng, Xinchang, Shangzhou, and Zhuji counties (cities, and districts) in Shaoxing, as well as some townships in Shangyu, Pan'an, Dongyang, and Tiantai counties (cities), are designated as the Yuezhou production area. With the gradual standardization and strengthening of geographical indications, the quality differences of Longjing tea from different production areas have attracted attention, and the identification of Longjing tea's origin has become a key focus. The geographical conditions of each production area are similar and intertwined, and the production and processing methods of "Longjing tea" used are very similar. It is very difficult to identify the Longjing tea production area from the aspects of appearance, aroma, taste, etc.

[0003] Due to Longjing tea's historical reputation and unique status, the supply-demand imbalance has generated unprecedented economic benefits. This pursuit of economic gains has also led to a gradual and chaotic introduction and promotion of Longjing tea. Longjing has been increasingly promoted beyond Zhejiang Province, expanding from "Zhejiang Longjing" to "Guizhou Longjing," "Sichuan Longjing," "Guangxi Longjing," and even to overseas production areas. These factors have resulted in high-quality West Lake Longjing tea often being in short supply in the market.

[0004] The emergence of the above problems has put forward higher requirements on the means of tea quality testing. In order to further improve the problems of selling inferior products as good ones in the current tea market and maintain the stable and healthy development of the tea industry, it is urgent to improve the level of tea quality testing technology and establish scientific and complete testing methods.

[0005] In addition, some methods have been proposed in the prior art, such as using instruments to detect the sensory quality, color difference, and content differences of major chemical components such as tea polyphenols, free amino acids, water extracts, caffeine, and soluble sugars of Longjing tea samples. However, this method is time-consuming, costly, and easily damages the sample. Some other methods use electronic eyes, electronic tongues, and electronic noses to accurately and non-destructively quantify the degree of fermentation of black tea. However, these tests or equipment are time-consuming, expensive, and lack portability, making them less practical and difficult to popularize. Colorimetric sensors are also used in the prior art to determine relevant information about tea leaves, but the impact of these chemical reagents on food and consumer health cannot be ignored. A healthy, non-toxic, rapid, and non-destructive testing method is urgently needed. Furthermore, expensive instruments and equipment—hyperspectral imaging systems—are required, resulting in high costs and inconvenience. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for determining the production area of Longjing tea based on a food-grade colorimetric sensor. The origin refers to the West Lake production area, Qiantang production area, and Yuezhou production area mentioned in the background technology. The detection cost of the present invention is low, and the reagents used are all natural pigments or food-grade materials, which is more suitable for the detection of agricultural products or foods.

[0007] In one aspect of the present invention, a method for determining the Longjing tea producing area based on a food-grade colorimetric sensor is provided. According to an embodiment of the present invention, the method comprises the following steps:

[0008] S1. Using EGCG standard as reactant, screen and optimize the type of metal ions added to each colorimetric point of the sensor and the optimal pH value;

[0009] S2. constructing a colorimetric sensor array based on the above results;

[0010] S3, obtaining sensor image information of Longjing tea samples from different production areas before and after the reaction in the colorimetric sensor array, and calculating the RGB difference value of each colorimetric point before and after the reaction;

[0011] S4, establishing a judgment model of origin and non-origin Longjing according to the RGB difference information of the sensor image;

[0012] S5. Determine the unknown Longjing tea sample according to the determination model.

[0013] In addition, the method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to the above embodiment of the present invention may also have the following additional technical features:

[0014] In some embodiments of the present invention, in step S1, the screening and optimization method specifically includes the following steps:

[0015] S101. Based on the ability of EGCG to bind to metal ions, metal ion receptors that can react with EGCG were selected: Fe 2+ and Zn 2+ ;

[0016] S102, selecting a receptor material and an indicator according to the metal ion receptor, and preparing a receptor aqueous solution, an indicator solution, and a pH adjuster solution;

[0017] S102. In a microplate, a pH regulator solution, an indicator aqueous solution, and a receptor aqueous solution of different pH values are added to a single well to perform a pH gradient experiment;

[0018] S103, selecting the pH value at which the color change is obvious in the pH gradient test as the optimal pH value reagent combination as the detection array point to construct a colorimetric sensor array.

[0019] In some embodiments of the present invention, in step S101:

[0020] Anthocyanin was selected as the indicator, and the indicator solution was prepared as follows: an anthocyanin indicator solution with a concentration of 0.01 mmol / L was prepared using distilled water.

[0021] The receptor materials are food-grade zinc sulfate and food-grade ferrous sulfate. The food-grade ferrous sulfate is used with distilled water to prepare a ferrous sulfate receptor aqueous solution with a concentration of 0.01 mmol / L. The food-grade zinc sulfate is used with distilled water to prepare a zinc sulfate receptor aqueous solution with a concentration of 2 mmol / L.

[0022] The pH adjusting agent solution is a 20 mmol / L 4-hydroxyethylpiperidin ethanesulfonic acid aqueous solution adjusted using edible white vinegar and food-grade baking soda aqueous solution.

[0023] In some embodiments of the present invention, in step S102, the pH selected for the pH gradient experiment is 3, 4, 5, 6, 7, or 8; the volume ratio of the indicator solution to the pH adjuster solution is 2:3; when the acceptor aqueous solution in the ELISA plate well is a ferrous sulfate acceptor aqueous solution, the volume ratio of the indicator solution to the acceptor aqueous solution is 10:1; and when the acceptor aqueous solution in the ELISA plate well is a zinc sulfate acceptor aqueous solution, the volume ratio of the indicator solution to the acceptor aqueous solution is 1:1.

[0024] In step S103, in the pH gradient experiment, anthocyanin and Fe 2+ The color changes significantly at pH = 6, 7, and 8. 2+ The color changes significantly at pH = 6 and 7.

[0025] In some embodiments of the present invention, in step S2, a reagent combination with obvious color change in the pH gradient test is selected as a detection array point to construct a colorimetric sensor array, and the colorimetric sensor array is composed of an indicator and a receptor, wherein the indicator is anthocyanin and the receptor is Fe 2+ or Zn 2+ The colorimetric sensor array includes 5 detection points, which are as follows: anthocyanin and Fe 2+ At the detection points under pH=6, 7, and 8, anthocyanin and Zn 2+ Detection array points under pH=6,7 environment.

[0026] In some embodiments of the present invention, in step S3, the method for preparing the tea sample comprises the following steps:

[0027] S301, collecting Longjing tea samples from different production areas, and grinding them to obtain tea powder;

[0028] S302, weighing tea powder, adding it into distilled water at 70° C. and brewing it for 5 minutes to obtain tea soup, and then filtering it through an aqueous filter membrane to obtain the tea soup sample.

[0029] In some embodiments of the present invention, in step S302:

[0030] The mass ratio of tea powder to distilled water is 1:50;

[0031] 1 mL of tea soup was filtered through an aqueous filter membrane with a pore size of 0.22 μm.

[0032] In some embodiments of the present invention, in step S3, the sensor image information includes RGB images of array points in the colorimetric sensor array before and after adding the tea sample, as well as R, G and B difference information;

[0033] The acquisition of the sensor image information specifically includes the following steps:

[0034] S303, using a camera to capture an image of the colorimetric sensor array constructed in step S1 as a pre-reaction image;

[0035] S304, then adding tea samples to the constructed colorimetric sensor array, reacting for 5 minutes, and capturing images with a camera with the same parameters as post-reaction images;

[0036] S305 , extracting RGB values from the pre-reaction image and the post-reaction image, where RGB represents red, green, and blue, and calculating the RGB difference between each detection array point before and after the reaction.

[0037] In some embodiments of the present invention, in step S4, the method for establishing the determination model includes the following steps:

[0038] S401. For each array point in the colorimetric sensor array, the R, G, B values of the image before the reaction are subtracted from the R, G, B values of the image after the reaction to obtain a difference, and image information with a dimension three times the number of array points is obtained based on the difference;

[0039] S402, the image information obtained from all tea samples forms an image information matrix, the image information matrix is used as an independent variable, and the category assignment of each tea sample is used as a dependent variable;

[0040] S403. Use principal component analysis to reduce the data dimension to 2 dimensions, then input it into a support vector machine classifier to establish a PCA-SVM model for origin identification, and use cross-validation to optimize the penalty coefficients of key parameters of the model.

[0041] In some embodiments of the present invention, step S5 specifically includes the following steps: collecting image information of an unknown Longjing tea sample, bringing it into the established PCA-SVM model, obtaining a category assignment, and judging whether the origin of the unknown Longjing tea sample is the place of origin or not according to the category assignment.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The Longjing tea sample production area determination method of the present invention can distinguish the Longjing tea production area, has a fast detection speed, low cost and high accuracy, and the food-grade sensor array greatly reduces the harm of chemical components to the human body, reduces costs and expands economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A colorimetric sensor array constructed for a method for determining the Longjing tea producing area based on a food-grade colorimetric sensor in an embodiment of the present invention;

[0045] Figure 2 In (a), the colorimetric sensor array in the embodiment of the present invention is Fe 2+ (b) is a diagram of the colorimetric sensor array with Fe in the embodiment of the present invention. 2+ (c) is a graph showing the change in the Euclidean distance of the receptor before and after the reaction; (d) is a graph showing the change in the Euclidean distance of the receptor before and after the reaction; (e) is a graph showing the change in the Euclidean distance of the receptor before and after the reaction; (f) is a graph showing the change in the Euclidean distance of the receptor before and after the reaction; (g) is a graph showing the change in the Euclidean distance of the receptor before and after the reaction; (h 2+ (d) is a diagram of the colorimetric sensor array with Zn 2+ (e) is a diagram showing the change in the Euclidean distance of the receptor before and after the reaction; (f) is a diagram showing the change in the Euclidean distance of the colorimetric sensor array element before and after the reaction according to an embodiment of the present invention;

[0046] Figure 3In the figure, (a) is the discriminant division result diagram of the PCA-SVM model for 26 modeling samples under the first two principal component dimensions in an embodiment of the present invention; (b) is the discriminant confusion matrix result diagram of the PCA-SVM model for 26 modeling samples in an embodiment of the present invention; (c) is the discriminant division result diagram of the PCA-SVM model for 26 unknown samples under the first two principal component dimensions in an embodiment of the present invention; (d) is the discriminant confusion matrix result diagram of the PCA-SVM model for 26 unknown samples in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] 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. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0048] A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor comprises the following steps:

[0049] (1) Using EGCG standard as the reactant, screen and optimize the type of metal ions added to each colorimetric point of the sensor and the optimal pH value:

[0050] Longjing tea samples produced in different production areas have different climatic conditions and processing methods. The content of major chemical components in the dry tea, such as tea polyphenols, free amino acids, water extracts, caffeine, and soluble sugars, will also vary. Among them, the catechin EGCG (epigallocatechin gallate) is the main variable substance. Therefore, the content of catechins can actually best reflect the production area of Longjing tea samples. The catechin monomer EGCG has the ability to bind to metal ions. Based on this, the metal ion receptor that can react with it is selected: Fe 2+ (FeSO4, food grade), Zn 2+ (ZnSO4, food grade).

[0051] Based on the principle that they are non-toxic and harmless while functioning as indicators, the pH indicators chosen were anthocyanins, curcumin, and shikonin. Subsequently, the choice of indicator was further optimized through preliminary experiments. These experiments revealed that curcumin and shikonin did not produce a significant color change with the two receptors, ferrous sulfate and zinc sulfate, under the experimental conditions. Therefore, anthocyanins were selected as the optimized indicator.

[0052] Then, edible white vinegar and baking soda (food grade) aqueous solution were used to adjust the pH value of 20mM HEPES aqueous solution to a pH gradient of 3, 4, 5, 6, 7, and 8. The optimized anthocyanin indicator was prepared with distilled water to prepare a 0.01mM indicator aqueous solution, and the receptor Fe2+ Prepare an aqueous solution of 0.01 mM receptor Zn with distilled water. 2+ A receptor aqueous solution with a concentration of 2 mM was prepared using distilled water.

[0053] Optimize the amount of indicator and receptor added, that is, add 30 μL of any HEPES aqueous solution with a pH value of 3-8, the corresponding 20 μL indicator aqueous solution and 2 μL of Fe 2+ Acceptor aqueous solution or 20 μL of Zn 2+ In the pH gradient experiment, it was found that anthocyanin and Fe 2+ The color changes significantly at pH = 6, 7, and 8. 2+ The color changes significantly at pH = 6 and 7.

[0054] (2) Construction of colorimetric sensor array

[0055] A colorimetric sensor array was constructed, which consists of an indicator and a receptor, wherein the indicator is anthocyanin and the receptor is Fe 2+ (FeSO4, food grade) or Zn 2+ (ZnSO4, food grade), the colorimetric sensor includes 5 detection points, the 5 detection points are as follows: anthocyanin and Fe 2+ Under pH=6, 7, and 8, anthocyanin and Zn 2+ Under the environment of pH=6, 7, these five detection array points constitute a sensor array.

[0056] (3) Detection of catechin content in Longjing tea samples from different production areas:

[0057] According to the national standard method for the detection of tea polyphenols and catechins in tea (GB / T8313-2008), the catechin content in Longjing tea samples from 6 different production areas was tested for verification. The relationship between catechin content and production area was as follows: Origin: EGCG (21.73-32.67 mg / g), EGC (14.73-19.91 mg / g), C (1.05-2.05 mg / g), EC (9.76-14.01 mg / g), ECG (8.74-16.44 mg / g), total catechins (66.17-78.46 mg / g). Non-origin: EGCG (15.03-20.39 mg / g), EGC (7.04-14.76 mg / g), C (1.05-1.82 mg / g), EC (5.43-7.78 mg / g), ECG (5.11-9.83 mg / g), total catechins (38.86-56.25 mg / g).

[0058] (4) Verification of the colorimetric sensor array using EGCG standards:

[0059] Prepare an aqueous solution of EGCG standard with distilled water at a concentration of 20 mg / mL. First, add 30 μL of the aforementioned 20 mM HEPES aqueous solution with a pH of 6, 7, or 8 and 20 μL of the corresponding indicator aqueous solution to a single well in the ELISA plate. Then place it in a dark box and use a mobile phone camera to take an image of it as the initial picture; then, add the corresponding amount of receptor Fe 2+ 、Zn 2+ After the aqueous solution, the colorimetric sensing array of the five points is completed, and the image is obtained in the same way as before the reaction. Then, the 20 mg / mL EGCG aqueous solution prepared above is added to each well, wherein Fe 2+ 148 μL of Zn was added to the receptor system. 2+ 130 μL of the receptor system was added and reacted for 5 min. The images after the reaction were obtained using the same method. See Table 1 for details.

[0060] Table 1 Contents of reagents in colorimetric sensor array

[0061] Buffer (μL) Anthocyanins (μL) Metal ions (μL) EGCG standard (μL) <![CDATA[Zn 2+ ]]> 30 20 20 130 <![CDATA[Fe 2+ ]]> 30 20 2 148

[0062] Extract the RGB value of each point in the pictures before and after the reaction, and calculate the Euclidean distance between the before reaction and the initial point, and between the after reaction and the initial point. The results are as follows: Figure 3 As shown, Fe 2+ 、Zn 2+ Under the experimental conditions, both receptors can react with the indicator anthocyanin. After adding 20 mg / mL EGCG aqueous solution, it can react with Fe 2+ 、Zn 2+ The two receptors bind to each other, releasing part of the indicator originally bound to the receptors and partially restoring the color of the released indicator under the experimental conditions. It can be seen that there is a difference in the image color before and after the EGCG aqueous solution is added to the colorimetric sensor array, such as Figure 2 As shown in Figure 2 As shown in (b), the Euclidean distance after the reaction is lower than the value before the reaction in the pH range of 6-8. Figure 2 As shown in (d), the Euclidean distance after the reaction was lower than that before the reaction in the pH range of 6-7. This proves that the constructed colorimetric sensor array can be used for EGCG detection.

[0063] (5) Preparation of Longjing tea samples from different production areas

[0064] First, we collected and labeled Longjing tea samples from six different origins. A total of 26 samples were ground into powder, and each sample was divided into two parts: one for modeling and one for verification.

[0065] Preparation of Longjing tea samples from different producing areas: 0.1g of tea powder was weighed for each sample, added to 5mL of distilled water at 70°C, and brewed for 5 minutes to obtain the tea soup. The tea samples were prepared using a tea-to-water ratio of 1:50, brewed with 70°C water. 1mL of the tea soup was then aspirated and filtered through a 0.22μm aqueous filter membrane to obtain the tea soup sample. The 0.22μm aqueous filter membrane, manufactured by Tianjin Linghang Experimental Equipment Co., Ltd., can partially eliminate the effects of tea soup color. This is because the aqueous filter membrane can filter out some color-causing macromolecules. Therefore, after filtration, the tea soup becomes lighter in color, eliminating the effects of tea soup color.

[0066] (6) Obtaining sensor image information of Longjing tea samples from different production areas:

[0067] First, use the mobile phone camera to take an image of the colorimetric sensor array constructed above, which is used as the pre-reaction image. Then, the three Fe 2+ 148 μL of tea sample to be tested was added to the receptor system. 2+ 130 μL of the tea sample to be tested was added to the receptor system, and the reaction was carried out for 5 minutes. The image was taken with a camera with the same parameters, which was used as the post-reaction image. The RGB values in the images before and after the reaction were extracted. RGB represents the three colors of red, green and blue. It was used as the coordinates in the RGB three-dimensional space, and the Euclidean distance before and after the reaction was calculated. That is, the coordinates before the reaction are (x1, y1, z1), and the coordinates after the reaction are (x2, y2, z2). Among them, x1, y1, and z1 represent the R1, G1, and B1 values before the reaction, respectively, and x2, y2, and z2 represent the R2, G2, and B2 values before the reaction, respectively. The Euclidean distance before and after the reaction can be expressed as d 12 .

[0068]

[0069] (6) Establish a qualitative discrimination model based on the image information and the origin of Longjing tea and determine the origin of unknown samples:

[0070] For each array point in the colorimetric sensor array, the R, G, and B values of the pre-reaction image were subtracted from the R, G, and B values of the post-reaction image, resulting in a 5×3=15-dimensional image matrix, where 5 represents the number of array points and 3 represents the R, G, and B difference. Using the 15-dimensional image matrix as the independent variable and the class assignments of the 26 modeling samples (origin assigned a value of 1, non-origin assigned a value of 2) as the dependent variable, principal component analysis was used to reduce the data dimensionality to 2 dimensions. This data was then input into a support vector machine classifier to establish a PCA-SVM model for origin identification. Cross-validation was used to optimize the penalty coefficients for key model parameters.

[0071] The best PCA-SVM model obtained by optimization is verified one by one on the 26 validation samples that are not involved in the modeling. Similarly, the image information of each sample is collected and brought into the built PCA-SVM model to obtain the predicted category assignment. The category assignments predicted by the model are compared one by one with the true values. If they are the same, it means that the classification is correct and the accuracy rate is calculated. Figure 3 , all 26 samples were judged with an accuracy rate of 100%.

[0072] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they should all fall within the scope of protection of the present invention.

Claims

1. A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor, characterized in that: The following steps are involved: S1. Using EGCG standard as reactant, screen and optimize the type of metal ions added to each colorimetric point of the sensor and the optimal pH value; S2. constructing a colorimetric sensor array based on the results obtained in step S1; S3, obtaining sensor image information of Longjing tea samples from different production areas before and after the reaction in the colorimetric sensor array, and calculating the RGB difference value of each colorimetric point before and after the reaction; S4. Establishing a judgment model of origin and non-origin Longjing according to the RGB difference information of the sensor image, wherein the method for establishing the judgment model comprises the following steps: S401. For each array point in the colorimetric sensor array, the R, G, B values of the image before the reaction are subtracted from the R, G, B values of the image after the reaction to obtain a difference, and image information with a dimension three times the number of array points is obtained based on the difference; S402, the image information obtained from all tea samples forms an image information matrix, the image information matrix is used as an independent variable, and the category assignment of each tea sample is used as a dependent variable; S403, using principal component analysis to reduce the data dimension to 2 dimensions, then inputting it into a support vector machine classifier to establish a PCA-SVM model for origin identification, and using cross-validation to optimize the penalty coefficients of key parameters of the model; S5. Determine the unknown Longjing tea sample based on the determination model: collect image information of the unknown Longjing tea sample, bring it into the established PCA-SVM model, obtain category assignment, and determine whether the origin of the unknown Longjing tea sample is the original place of origin or not according to the category assignment.

2. A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to claim 1, characterized in that: In step S1, the screening and optimization method specifically includes the following steps: S101. Based on the ability of EGCG to bind to metal ions, metal ion receptors that can react with EGCG were selected: Fe 2 + and Zn 2+ ; S102, selecting a receptor material and an indicator according to the metal ion receptor, and preparing a receptor aqueous solution, an indicator solution, and a pH adjuster solution; S102. In a microplate, a pH regulator solution, an indicator aqueous solution, and a receptor aqueous solution of different pH values are added to a single well to perform a pH gradient experiment; S103, selecting the pH value at which the color change is obvious in the pH gradient test as the optimal pH value reagent combination as the detection array point to construct a colorimetric sensor array.

3. A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to claim 2, characterized in that: In step S101: Anthocyanin was selected as the indicator, and the indicator solution was prepared as follows: an anthocyanin indicator solution with a 0.01 mmol / L aqueous solution was prepared with distilled water; The receptor materials are food-grade zinc sulfate and food-grade ferrous sulfate. Food-grade ferrous sulfate is used with distilled water to prepare a 0.01 mmol / L aqueous solution of ferrous sulfate receptor. Food-grade zinc sulfate is used with distilled water to prepare a 2 mmol / L aqueous solution of zinc sulfate receptor. The pH adjuster solution is a 20 mmol / L 4-hydroxyethylpiperidinethanesulfonic acid aqueous solution adjusted using edible white vinegar and food-grade baking soda aqueous solution.

4. A method for determining a Longjing tea producing area based on a food-grade colorimetric sensor according to claim 3, characterized in that: In step S102, the pH selected for the pH gradient experiment is 3, 4, 5, 6, 7, and 8; the volume ratio of the indicator solution to the pH adjuster solution is 2:3; when the acceptor aqueous solution in the ELISA plate well is a ferrous sulfate acceptor aqueous solution, the volume ratio of the indicator solution to the acceptor aqueous solution is 10:1; when the acceptor aqueous solution in the ELISA plate well is a zinc sulfate acceptor aqueous solution, the volume ratio of the indicator solution to the acceptor aqueous solution is 1:1; In step S103, in the pH gradient experiment, anthocyanin and Fe 2+ The color changes significantly at pH = 6, 7, and 8. 2+ The color changes significantly at pH = 6 and 7.

5. A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to claim 4, characterized in that: In step S2, a reagent combination with obvious color change in the pH gradient test is selected as a detection array point to construct a colorimetric sensor array, which is composed of an indicator and a receptor, wherein the indicator is anthocyanin and the receptor is Fe 2+ or Zn 2+ The colorimetric sensor array includes 5 detection points, which are as follows: anthocyanin and Fe 2+ At the detection points under pH=6, 7, and 8, anthocyanin and Zn 2+ Detection array points under pH=6,7 environment.

6. A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to claim 1, characterized in that: In step S3, the method for preparing the tea sample includes the following steps: S301, collecting Longjing tea samples from different production areas, and grinding them to obtain tea powder; S302. Weigh tea powder, add it into 70° C. distilled water and brew for 5 minutes to obtain tea soup, which is then filtered using an aqueous filter membrane to obtain the tea soup sample.

7. A method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to claim 6, characterized in that: In step S302: The mass ratio of tea powder to distilled water is 1:50; 1 mL of tea soup was filtered through an aqueous filter membrane with a pore size of 0.22 μm.

8. The method for determining the Longjing tea producing area based on a food-grade colorimetric sensor according to claim 1, wherein: In step S3, the sensor image information includes RGB images of array points in the colorimetric sensor array before and after adding the tea sample, as well as R, G and B difference information; The acquisition of the sensor image information specifically includes the following steps: S303, using a camera to capture an image of the colorimetric sensor array constructed in step S1 as a pre-reaction image; S304, then adding tea samples to the constructed colorimetric sensor array, reacting for 5 minutes, and capturing images with a camera with the same parameters as post-reaction images; S305 , extracting RGB values from the pre-reaction image and the post-reaction image, where RGB represents red, green, and blue, and calculating the RGB difference between each detection array point before and after the reaction.

Images