Colorimetric method for quickly grading amino acid nitrogen

Abstract

The invention relates to the technical field of data processing, and discloses a colorimetric method for quickly grading amino acid nitrogen, which comprises the following steps: firstly, diluting a sample, and directly sampling a liquid sample or diluting the liquid sample to a concentration range according to a proportion; a reagent and a color developing agent are prepared, the reagent comprises a sodium acetate-acetic acid buffer solution with the pH being 4.8, and the color developing agent comprises 15 mL of 37% formaldehyde and 7.8 mL of acetylacetone; adding 1.0-2.0 mL of a sample solution or an ammonia nitrogen standard solution into a 10mL colorimetric tube, adding 4mL of a buffer solution and 4mL of a color developing agent, adding water to a scale, uniformly mixing, heating in a water bath at 100 DEG C for 15 minutes, and cooling to room temperature for later use; carrying out image acquisition; performing color feature extraction, then performing feature calculation, firstly performing color space conversion, converting an image from an RGB space to an HSV or Lab space, and separating brightness and color information; and carrying out quick grading comparison on the amino acid nitrogen according to the extracted color features, and outputting a comparison result. According to the invention, efficient and accurate quick grading of amino acid nitrogen based on the camera can be realized.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, specifically to a colorimetric method for rapid fractionation of amino acid nitrogen. Background Technology

[0002] Amino acid nitrogen is the collective term for free amino acids and some peptide-bonded amino acids in chili peppers, directly affecting their nutritional value and umami intensity. Rapid detection can quantify the umami (such as glutamic acid and aspartic acid) and nutritional value (such as the content of essential amino acids) of chili peppers, providing a scientific basis for variety selection.

[0003] Variety Difference Analysis: The amino acid composition of different chili pepper varieties (such as large red peppers, small red peppers, and green pointed peppers) varies significantly. For example, the total free amino acid content in common Hunan chili peppers ranges from 7.28 to 19.36 mg / g (dry weight). Large red peppers and small red peppers have higher levels of umami amino acids (glutamic acid and aspartic acid), resulting in a more prominent flavor. Rapid grading can clearly identify the quality of varieties and guide adjustments to planting structures. Currently, there is no colorimetric method or device for rapidly grading the amino acid nitrogen content in chili peppers.

[0004] Therefore, to address the above problems, a colorimetric method for rapid fractionation of amino acid nitrogen is needed. Summary of the Invention

[0005] The purpose of this invention is to provide a colorimetric method for rapid classification of amino acid nitrogen. This invention enables efficient and accurate rapid classification of amino acid nitrogen based on a camera, allowing for a fully quantitative operation from color feature extraction to classification determination. It is suitable for automated detection systems and applications in food processing, quality control, and other fields.

[0006] This invention is implemented as follows:

[0007] This invention provides a colorimetric method for rapid fractionation of amino acid nitrogen, specifically performed according to the following steps:

[0008] S1: First, dilute the sample. For liquid samples, take a sample directly or dilute it according to the ratio to the concentration range (e.g., 0.1~1.0 g / 100mL).

[0009] S2: Prepare the reagents and colorimetric reagents. The reagents include a sodium acetate-acetic acid buffer solution at pH 4.8 (60 mL 1 mol / L sodium acetate + 40 mL 1 mol / L acetic acid). The colorimetric reagents include 15 mL 37% formaldehyde + 7.8 mL acetylacetone, with water added to 100 mL and mixed well.

[0010] S3: Perform the colorimetric reaction. Take 1.0~2.0 mL of sample solution or ammonia nitrogen standard solution (0~100 μg NH3-N) into a 10 mL colorimetric tube, add 4 mL of buffer solution and 4 mL of colorimetric reagent, add water to the mark, mix well, and then heat in a 100℃ water bath for 15 minutes. Cool to room temperature before use.

[0011] S4: Perform image acquisition, adjust the camera angle to capture images of the color-developed sample and standard color card;

[0012] S5: Perform color feature extraction, followed by feature calculation. First, convert the color space from RGB to HSV or Lab space to separate brightness and color information. Specifically, follow these steps:

[0013] S5.1: Calculate the RGB mean or HSV components of the sample area, and calculate the Euclidean distance or correlation coefficient between the sample color and the standard color card color.

[0014] S5.2: Establish the standard curve: Establish a linear regression model based on the relationship between the concentration and color characteristics of the standard color card;

[0015] Next, the concentration is calculated by substituting the sample color characteristics into the model to calculate the amino acid nitrogen concentration.

[0016] S6: Then, perform rapid classification and comparison of amino acid nitrogen based on the extracted color features, and output the comparison results. When classifying the grades, firstly: establish a quantitative relationship between color features and amino acid nitrogen concentration; then predict the amino acid nitrogen concentration based on the sample color features; and finally determine the sample grade according to national standards.

[0017] Furthermore, the present invention provides a colorimetric system for rapid fractionation of amino acid nitrogen: including an image acquisition module to acquire accurate color information of the sample after color development, and to ensure the consistency of the light source to eliminate color deviation;

[0018] The image processing module uses image processing software, including OpenCV or MATLAB color correction algorithms, to correct image color deviations and extract RGB / HSV features, providing a data foundation for classification.

[0019] The standard database module stores color data (such as RGB and HSV values) corresponding to standard color cards for different concentrations of amino acid nitrogen, providing a basis for grading and determining the concentration range by comparing the sample color with the standard color card.

[0020] The grading algorithm module uses linear regression models, threshold judgment, or machine learning algorithms (such as SVM and neural networks) to automatically determine the grade of a sample based on differences in color features, supporting real-time grading.

[0021] The results output module includes an LCD display, printer, or data interface (such as USB or Bluetooth); it displays the concentration values ​​and grades of the grading results and exports data and test records.

[0022] Furthermore, this invention provides a simple colorimetric device for rapid fractionation of amino acid nitrogen, comprising an image acquisition housing, a camera mounted on the image acquisition housing, a first rotating shaft at one end of the image acquisition housing, a first support plate connected to the first rotating shaft, a second rotating shaft connected to the first support plate, and a mounting plate connected to the second rotating shaft. The camera is connected to a server via a connecting cable, and the server is wirelessly connected to a smart terminal.

[0023] Furthermore, the present invention provides a computer-storable medium storing a computer program, characterized in that: when the computer program in the storage medium is run, it executes any one of the above-described colorimetric methods for rapid fractionation of amino acid nitrogen.

[0024] Compared with the prior art, the beneficial effects of the present invention are:

[0025] 1. It can quickly and efficiently classify amino acid nitrogen based on a camera, and can realize the entire process of quantitative operation from color feature extraction to classification judgment. It is suitable for automated detection systems and is applicable to food processing, quality control and other fields. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0027] Figure 1 This is a flowchart of the method of the present invention;

[0028] Figure 2 This is a system structure diagram of the present invention;

[0029] Figure 3 This is a structural diagram of the device of the present invention.

[0030] The components include an image acquisition housing 1, a camera 11, a first rotating shaft 15, a connecting cable 12, a mounting plate 13, and a first support plate 14. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to describe selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] Please see Figures 1-3 This invention provides a colorimetric method for rapid fractionation of amino acid nitrogen.

[0033] S1: First, dilute the sample. For liquid samples, take a sample directly or dilute it according to the ratio to the concentration range (e.g., 0.1~1.0 g / 100mL).

[0034] S2: Prepare the reagents and colorimetric reagents. The reagents include a sodium acetate-acetic acid buffer solution at pH 4.8 (60 mL 1 mol / L sodium acetate + 40 mL 1 mol / L acetic acid). The colorimetric reagents include 15 mL 37% formaldehyde + 7.8 mL acetylacetone, with water added to 100 mL and mixed well.

[0035] S3: Perform the colorimetric reaction. Take 1.0~2.0 mL of sample solution or ammonia nitrogen standard solution (0~100 μg NH3-N) into a 10 mL colorimetric tube, add 4 mL of buffer solution and 4 mL of colorimetric reagent, add water to the mark, mix well, and then heat in a 100℃ water bath for 15 minutes. Cool to room temperature before use.

[0036] S4: Perform image acquisition, adjust the camera angle to capture images of the color-developed sample and standard color card;

[0037] S5: Perform color feature extraction, followed by feature calculation. First, convert the color space from RGB to HSV or Lab space to separate brightness and color information. Specifically, follow these steps:

[0038] S5.1: Calculate the RGB mean or HSV components of the sample area, and calculate the Euclidean distance or correlation coefficient between the sample color and the standard color card color; convert RGB to HSV, where:

[0039] H (hue): The basic properties of color (0°~360°);

[0040] S (Saturation): The purity of color (0%~100%);

[0041] V (brightness): the lightness of a color (0%~100%);

[0042]

[0043]

[0044]

[0045] Among them, Δ=max(R,G,B)−min(R,G,B);

[0046] RGB to Lab color space conversion, where Lab color space is based on human vision, including:

[0047] L (brightness): 0 (black) ~ 100 (white).

[0048] a (red-green axis): -128~127.

[0049] b (yellow-blue axis): -128~127.

[0050]

[0051]

[0052]

[0053] in, Xn, Yn, and Zn are reference white points (e.g., D65 light source);

[0054] S5.2: Establish the standard curve: Establish a linear regression model based on the relationship between the concentration and color characteristics of the standard color card;

[0055] Next, perform concentration calculations by substituting the sample color characteristics into the model to calculate the amino acid nitrogen concentration: Follow these steps:

[0056] The region mean is calculated by averaging the RGB or HSV components of the region of interest (ROI) in the sample image.

[0057]

[0058] Where N is the number of pixels in the ROI, and ci is the value of the i-th pixel;

[0059] Next, Euclidean distance is calculated to determine the difference between the sample color and the standard color card color.

[0060]

[0061] c iterates through the RGB or Lab components.

[0062] Correlation coefficient calculation measures the linear correlation between the sample color and the standard color chart color.

[0063]

[0064] Wherein, μˉsample and μˉstandard are the average colors of the sample and standard color cards, respectively;

[0065] S6: Then, perform rapid classification and comparison of amino acid nitrogen based on the extracted color features, and output the comparison results. When classifying the grades, firstly: establish a quantitative relationship between color features and amino acid nitrogen concentration; then predict the amino acid nitrogen concentration based on the sample color features; and finally determine the sample grade according to national standards.

[0066] Establish a standard curve to establish a quantitative relationship between color characteristics and amino acid nitrogen concentration. Steps: Data acquisition: Measure the color characteristics (such as the H component of HSV or the a component of Lab) of standard solutions with different concentrations (e.g., 0.1 g / 100 mL, 0.3 g / 100 mL, 0.5 g / 100 mL).

[0067] Then establish a linear regression model: assuming that the concentration y and the color feature x have a linear relationship:

[0068]

[0069] Where a is the slope and b is the intercept;

[0070] Fit the standard data using the least squares method.

[0071]

[0072] Where n is the number of standard solutions, and xi and yi are the color characteristics and concentration of the i-th standard solution.

[0073] Predicting amino acid nitrogen concentration based on sample color characteristics

[0074]

[0075] Where x^ represents the color characteristics of the sample (such as the mean H or the a component), and y^ represents the predicted concentration.

[0076] 3. Classification

[0077] Objective: To determine the sample grade according to national standards, as shown in Table 1;

[0078] Table 1. Grade Reference Table

[0079] grade Concentration range (g / 100mL) Special ≥0.8 Level 1 0.7~0.8 Level 2 0.6~0.7 Level 3 <0.6

[0080] In this embodiment, the present invention provides a colorimetric system for rapid fractionation of amino acid nitrogen: including an image acquisition module to acquire accurate color information of the sample after color development, and to ensure the consistency of the light source to eliminate color deviation;

[0081] The image processing module uses image processing software, including OpenCV or MATLAB color correction algorithms, to correct image color deviations and extract RGB / HSV features, providing a data foundation for classification.

[0082] The standard database module stores color data (such as RGB and HSV values) corresponding to standard color cards for different concentrations of amino acid nitrogen, providing a basis for grading and determining the concentration range by comparing the sample color with the standard color card.

[0083] The grading algorithm module uses linear regression models, threshold judgment, or machine learning algorithms (such as SVM and neural networks) to automatically determine the grade of a sample based on differences in color features, supporting real-time grading.

[0084] The results output module includes an LCD display, printer, or data interface (such as USB or Bluetooth); it displays the concentration values ​​and grades of the grading results and exports data and test records.

[0085] In this embodiment, the present invention provides a simple colorimetric device for rapid fractionation of amino acid nitrogen, comprising an image acquisition housing 1, a camera 11 mounted on the image acquisition housing 1, a first rotating shaft 15 at one end of the image acquisition housing 1, a first support plate 14 connected to the first rotating shaft 15, a second rotating shaft connected to the first support plate 14, and a mounting plate 13 connected to the second rotating shaft. The camera is connected to a server via a connecting cable, and the server is wirelessly connected to a smart terminal.

[0086] In this embodiment, the present invention provides a computer-storable medium storing a computer program, characterized in that: when the computer program in the storage medium is run, it executes any one of the above-described colorimetric methods for rapid fractionation of amino acid nitrogen.

[0087] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations will be apparent to those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A colorimetric method for rapid fractionation of amino acid nitrogen, characterized in that: Follow these steps: S1: First, dilute the sample. Take a sample of the liquid sample directly or dilute it to the concentration range according to the ratio. S2: Prepare the reagents and colorimetric reagents. The reagents include sodium acetate-acetic acid buffer solution at pH 4.

8. The colorimetric reagents include 15 mL of 37% formaldehyde + 7.8 mL of acetylacetone, with water added to 100 mL and mixed well. S3: Perform the colorimetric reaction. Take 1.0~2.0mL of sample solution or ammonia nitrogen standard solution into a 10mL colorimetric tube, add 4mL of buffer solution and 4mL of colorimetric reagent, add water to the mark, mix well, and then heat in a 100℃ water bath for 15 minutes. Cool to room temperature before use. S4: Perform image acquisition, adjust the camera angle to capture images of the color-developed sample and standard color card; S5: Perform color feature extraction and feature calculation. First, convert the color space to convert the image from RGB to HSV or Lab space to separate brightness and color information. S6: Then, based on the extracted color features, perform rapid classification and comparison of amino acid nitrogen and output the comparison results.

2. The colorimetric method for rapid fractionation of amino acid nitrogen according to claim 1, characterized in that: In step S5, the following steps are performed: S5.1: Calculate the RGB mean or HSV components of the sample area, and calculate the Euclidean distance or correlation coefficient between the sample color and the standard color card color. S5.2: Establish the standard curve: Establish a linear regression model based on the relationship between the concentration and color characteristics of the standard color card; Next, the concentration is calculated by substituting the sample color characteristics into the model to calculate the amino acid nitrogen concentration.

3. The colorimetric method for rapid fractionation of amino acid nitrogen according to claim 1, characterized in that: In step S6, the grades are classified. First, a quantitative relationship between color characteristics and amino acid nitrogen concentration is established. Then, the concentration of amino acid nitrogen is predicted based on the color characteristics of the sample; and the sample grade is determined according to national standards.

4. A colorimetric system for rapid fractionation of amino acid nitrogen, characterized in that: It includes an image acquisition module to obtain accurate color information of the sample after color development, ensuring consistent light source to eliminate color deviation; The image processing module uses image processing software, including OpenCV or MATLAB color correction algorithms, to correct image color deviations and extract RGB / HSV features, providing a data foundation for classification. The standard database module stores color data of standard color cards corresponding to different concentrations of amino acid nitrogen, providing a basis for grading and determining the concentration range by comparing the sample color with the standard color card. The grading algorithm module uses linear regression models, threshold judgment, or machine learning algorithms to automatically determine the grade of a sample based on differences in color characteristics, supporting real-time grading. The results output module includes an LCD display, printer, or data interface; it displays the concentration values ​​and grades of the grading results, and exports data and test records.

5. A simple colorimetric device for rapid fractionation of amino acid nitrogen, characterized in that, The system includes an image acquisition housing (1), on which a camera (11) is mounted. A first rotating shaft (15) is located at one end of the image acquisition housing (1), and a first support plate (14) is connected to the first rotating shaft (15). A second rotating shaft is connected to the first support plate (14), and a mounting plate (13) is connected to the second rotating shaft. The camera is connected to a server via a connecting cable, and the server is wirelessly connected to a smart terminal.

6. A computer-storable medium storing a computer program, characterized in that: When the computer program in the storage medium is executed, it performs a colorimetric method for rapid fractionation of amino acid nitrogen as described in any one of claims 1-4.

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