CN111189955B - Method for judging natural product category based on color change information in thin-layer chromatography dyeing process - Google Patents
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Abstract
The invention discloses a method for judging the category of a natural product based on color change information in a thin-layer chromatography dyeing process, which comprises the following steps: the method comprises the steps of utilizing a thin-layer chromatography plate to sample or develop a sample to be detected, developing the sample-sampled or developed thin-layer chromatography plate, recording a developing process, carrying out imaging processing on an obtained video file, extracting characteristic information of an obtained multi-frame image, matching the obtained characteristic information with characteristic information of various natural products in a constructed database, and obtaining classification information. The method of the invention is simple and convenient to operate and does not need special instruments. The method has the advantages of high identification speed and high accuracy.
Description
Technical Field
The invention belongs to the field of natural products and food and medicine, and particularly relates to a method for judging the category of a natural product based on color change information in a thin-layer chromatography dyeing process.
Background
The natural products including flavonoid aglycone, saponin aglycone, sterol, polyphenol, sugar, flavonoid glycoside, etc. are important active ingredients in plants, and have the effects of bacteriostasis, fresh preservation, antioxidation, aging delay, antibiosis, antivirus, blood fat reduction, cancer resistance, etc. The structure of the natural product determines various physicochemical properties of the natural product, and the understanding of the structure of the natural product has great significance in the fields of food, medicine and the like. The common methods for analyzing the structure of natural products mainly include nuclear magnetism, mass spectrometry, infrared and the like, and although the methods are accurate, the methods require specific solvents, complicated pretreatment processes and expensive instruments.
In recent years, computer technology has been rapidly developed, simulation software such as COMSOL is frequently applied in the fields of biomedicine and the like, molecular simulation also enables people to know the condition of molecular motion, and big data analysis, 5G network construction and the like are also developed vigorously. In this context, however, thin layer chromatography techniques remain surprisingly popular. In recent years, some thin layer chromatography technologies have been used, such as: fluorescence detectors, mass spectrometry, raman spectroscopy, etc., are also used for structural analysis, but this still requires some special instrumentation. Innovations in computer image processing technology make it feasible to extract image color information. Image processing programs represented by ImageJ have been widely used in the field of life science research, such as electrophoretic band quantitative analysis, cell counting, tissue structure quantitative processing, and the like. ImageJ is an open source software developed by NIH that can process and analyze images in various formats in multiple systems, and the presence of Macro files allows a user to edit a series of Macro commands to be automatically executed by ImageJ. The RGB value of the picture can be extracted in various forms, for example, the RGB value of a pixel point is directly read by utilizing a self-contained ColorPicker tool; the picture is broken into RGB channels, the integral value of each channel is calculated, and the like.
In thin layer chromatography, the sample spot is usually developed by a stain, different types of compounds will show different colors, and the relationship between the two has been observed for many years, and the well-known reagent company Sigma and the last century 60-80 have a lot of literature mentioning this phenomenon. Therefore, the ability to collect and process such color information using the latest computer technology would be a revolution in the traditional thin layer chromatography technology.
In the previous scientific research process, the applicant applied for patent documents with publication numbers CN 109959750a and CN 109959751a, wherein a method for identifying and detecting a lipid-soluble natural product thin layer quantitative image and a method for identifying and detecting a water-soluble natural product thin layer quantitative image are respectively disclosed, both of which comprise: (1) carrying out spotting on a sample to be detected containing a fat-soluble (water-soluble) natural product on a thin-layer chromatography plate; (2) carrying out thin-layer chromatography development on the spotted thin-layer chromatography plate by using a specific developing agent system; (3) developing the developed thin-layer chromatography plate by using a coloring agent system; (4) and (4) carrying out image acquisition on the developed thin-layer chromatography plate, and obtaining the content of the water-soluble natural product according to the relation between the image and the content of the water-soluble natural product. In the methods disclosed in the above documents, image information at a certain time point is used as a determination result, and there is a certain limitation in determination accuracy and applicability.
Disclosure of Invention
The invention provides a method for judging the category of a natural product based on color change information in a thin layer dyeing process, which has the advantages of simple process, no need of special instruments, high precision and wide application range.
A method for judging natural product category based on color change information in a thin-layer chromatography dyeing process comprises the following steps: the method comprises the steps of utilizing a thin-layer chromatography plate to sample or develop a sample to be detected, developing the sample-sampled or developed thin-layer chromatography plate, recording a developing process, carrying out imaging processing on an obtained video file, extracting characteristic information of an obtained multi-frame image, matching the obtained characteristic information with characteristic information of various natural products in a constructed database, and obtaining classification information.
When the unknown sample is classified, the color information is extracted according to the model and is matched with the classification characteristics corresponding to the natural products of all classes in the established database, so that the class of the unknown sample is determined.
Further, a method for judging the category of a natural product based on color change information in a thin layer dyeing process comprises the following steps:
(1) spotting a sample to be detected containing a natural product on a thin-layer chromatography plate, and selecting whether to develop or not according to whether the natural product is a mixture or not (the sample to be detected containing a single component can be directly spotted without subsequent development operation, and after the sample is spotted on the mixture, a proper developing agent needs to be selected for development so as to form a developing point containing the single component);
(2) developing the thin-layer chromatography plate by using a coloring agent system;
(3) recording the color development process of the sample point on the thin-layer chromatographic plate, and judging the category of the natural product according to the relationship between the color change and the structure of the sample point.
Specifically, a method for judging the category of a natural product based on color change information in a thin-layer dyeing process, which is based on extracting color characteristics representing the structure of the natural product by computer software and classifying the color characteristics according to the color characteristics, comprises the following steps:
(1) developing the natural product by utilizing a uniform coloring agent system, and recording the developing process by using electronic equipment with a video recording function;
(2) disassembling and analyzing the recorded video, and extracting color information of each natural product;
(3) and comparing in a database to judge the category of the natural product.
The organic compounds have different structures, and the developing speed and the developing chromaticity have larger differences.
Alternatively, the stain system is a p-methoxybenzaldehyde colour developer.
In the invention, the composition of the coloring agent system is that the volume ratio of p-methoxybenzaldehyde/acetic acid/ethanol/sulfuric acid is 9.1-9.5/3.5-4/300-350/12.5. More preferably, the p-methoxybenzaldehyde color-developing agent comprises p-methoxybenzaldehyde/acetic acid/ethanol/sulfuric acid (9.2/3.75/338/12.5, v/v/v/v).
In the invention, the natural product is dissolved by a proper solvent before detection, and the concentration is 1-15 mg/mL. When the sample is applied by thin layer chromatography, the sample application amount is 0.1-10 microliter. The natural product sample to be detected can be dissolved by using various solvents, generally, a volatile solvent with good solubility is adopted, and preferably, the solvent is one or more of ethanol, dichloromethane, acetone, methanol, ethyl acetate and the like; further preferably one or both of ethanol and ethyl acetate.
In the invention, if the natural product is a single natural product, the natural product does not need to be spread in a thin layer; if the product is a mixed natural product, the detection is carried out after the product is developed by using a proper solvent system, and the developed system is petroleum ether/ethyl acetate, chloroform/methanol and the like.
Alternatively, the concentration of the water-soluble natural product in the sample to be detected is 1-15mg/mL, and the sample amount is 0.1-10 microliters.
In the invention, after a sample is developed on the thin-layer chromatography, a p-methoxybenzaldehyde developer is used for developing color, the developing time is 0.1-10 minutes, and the developing temperature is 150-.
The color development process of the natural product or the mixture thereof on the thin-layer chromatography is recorded by equipment with a video recording function. For example, the invention can record the color development process by using a mobile phone or a camera and other devices.
The invention can pre-construct a database before detection, and preferably, the database is constructed by adopting the following method:
selecting various existing natural products or common natural products to establish a classification characteristic database: preparing a sample, unfolding the sample by adopting a thin-layer chromatography plate, developing the unfolded thin-layer chromatography plate, recording the developing process of a sample point on the thin-layer chromatography plate, imaging the obtained video file, extracting the characteristic information of the obtained multi-frame image, and constructing a database according to the extracted characteristic information to obtain database information corresponding to each category.
After the obtained video file is subjected to imaging processing, obtaining image data corresponding to multiple frames, and when a database is constructed or the category of an unknown natural product is judged, extracting the characteristic information by adopting the following operations: and reading RGB values of corresponding color-developing points in the multi-frame images one by one, calculating corresponding R/G, B/G information, obtaining points in a corresponding R/G, B/G coordinate system, and obtaining corresponding characteristic information. The method can disassemble and analyze the collected color development process by using a computer technology, read the RGB value of the sample point by using ImageJ, and select R/G-B/G as the classification characteristic.
When the type of an unknown natural product is judged, after a certain sample to be detected is unfolded, the obtained sample points (or color development points) can be one independent sample point or a plurality of color development points can be unfolded in sequence, when characteristic extraction is carried out, the recording and characteristic extraction of the color development process are required to be carried out on one sample point one by one, one sample point can obtain characteristic information with the same quantity as the number of image frames, and the characteristic information forms the characteristic information of components corresponding to the sample point. When constructing a database, it is constructed in the same way.
The invention can utilize the self-contained function of Matlab to disassemble the video file into frames to obtain the multi-frame image.
The invention can utilize ImageJ to read the RGB value. During reading, the RGB value of a certain point may be used as the RGB value corresponding to the color development point, or multiple points may be selected as the RGB value corresponding to the color development point, for example, a rule may be set according to the shape (generally, circular, quasi-circular, elliptical, or quasi-elliptical) of the color development point, a specific sampling point is obtained according to a sampling rule, and then the RGB values of the points are read to obtain an average value, so as to obtain the RGB value corresponding to the color development point. Of course, the RGB values can also be read by manual selection.
Preferably, ImageJ is used to read the RGB values of at least three points on each color-rendering point, and the average value is calculated to obtain the corresponding RGB value.
Preferably, when the database is constructed, the existing natural products are classified according to polarity, and a scatter diagram with R/G, B/G as horizontal, vertical and horizontal coordinates is constructed for each type of color development point corresponding to each type of natural products, so that the database corresponding to the type of natural products is obtained.
Preferably, a scatter diagram with R/G, B/G as horizontal, vertical and horizontal coordinates is constructed according to the R/G, B/G value corresponding to the sample to be detected, and the scatter diagram is compared with scatter diagrams of various natural products in a database to obtain a classification result.
Preferably, when the database is constructed, the minimum circumscribed rectangle of a plurality of groups of R/G, B/G data corresponding to a plurality of images corresponding to the same color point is obtained to obtain the characteristic region of the natural product corresponding to the color point; and (4) judging the probability of the R/G, B/G value corresponding to the sample to be detected belonging to each characteristic region in the database one by one, wherein the class with the highest probability is the class to which the sample to be detected belongs, and obtaining a classification result.
In the invention, the natural product category comprises one or more of simple phenols, phenolic acids, flavonoids, flavonoid glycosides, flavonoid aglycones, saponins and aglycones thereof, sterols and saccharides. The carotenoid, anthocyanin and aglycone substances thereof can be judged by naked eyes due to obvious color characteristics.
When the database is constructed for feature extraction, the invention can perform sample application, color development and feature extraction on a plurality of samples one by one, can also perform sample application on a plurality of natural products to prepare mixed samples, and can also perform sample application, color development and feature extraction on a plurality of single-component samples simultaneously.
Similarly, in the detection process, the sample to be detected can be subjected to sample application, color development and feature extraction on a single-component sample to be detected, and the sample to be detected can also be subjected to sample application, color development and feature extraction on a natural product with mixed components. In the process of feature extraction, automatic selection and feature extraction of a target color development area can be realized by setting software parameters.
The invention can record the natural product color developing process for a certain sample to be detected or a sample with a known component when a database is constructed, and then can process the natural product color developing process by using proper computer software. Since the color change of the whole color development process needs to be observed, the video is disassembled in units of frames by using software.
Selecting suitable image processing software, such as: ImageJ, etc., extracting color information in the color development process. And extracting proper classification characteristics from the color information, establishing a database, and classifying unknown natural products.
For example, color information extraction in the color development process is performed by using Matlab and ImageJ software, and the process is as follows:
after the natural product is spotted (developed) on a thin-layer chromatography, an iPhone8 is adopted to record the color development process, and a Matlab self-contained function is used to disassemble a video into frames.
In order to judge the structure of the natural product through Color information and determine the category of the natural product, ImageJ software is started, firstly, 'rectangle' is selected, an area to be analyzed is framed, then a 'Color Picker' tool is selected, three pixel points are randomly selected in a sample point area, the software automatically reads RGB values of the pixel points, and R/G-B/G is selected as a classification characteristic.
The invention can use common thin-layer chromatography plates with various specifications, and preferably, the database is established to be the same as the thin-layer chromatography plate used for actual classification so as to further improve the classification precision.
When the method is used for carrying out the class judgment, a natural product classification database needs to be constructed in advance, and then the class judgment of the sample can be realized after RGB values of unknown natural products are obtained.
A method for constructing a natural product classification database comprises the following steps:
(i) selecting different compounds in all types of natural products to be researched, dissolving the compounds to proper concentrations, and then carrying out point sample application on a thin-layer chromatographic plate one by one;
(ii) the sample point can be dyed by a dyeing agent system without unfolding;
(iii) recording the sample point color development process, and extracting color information according to the method;
(iv) and (3) displaying all the compounds in a scatter diagram with R/G as an abscissa and B/G as an ordinate (of course, the R/G as the ordinate and the B/G as the abscissa can be used, and keeping uniformity), so as to obtain the natural product classification database.
Preferably, when constructing the natural product taxonomy database, as many compounds as possible should be selected to contain all natural product classes, so that the database is more accurate.
In extreme cases, when the characteristic information of the sample to be detected is different from the characteristic information of all categories in the database greatly, manual analysis can be added, and if the sample to be detected is judged to contain new components, the new components can be used as new categories, and the characteristic information is added into the database so as to perfect the database and keep the database updated.
The invention can be used for judging the category of a single natural product, is also suitable for mixed natural products, and can even be used for judging the category of a synthetic compound on the basis of updating a database. Meanwhile, the invention has high flux, and during detection, a plurality of samples can be spotted on the same thin-layer chromatographic plate, and then color development process recording and color information extraction and classification are carried out.
Compared with the existing category judgment method, the method has the following advantages:
(1) the method for judging the natural product type based on the color change information in the thin layer dyeing process is simple and convenient to operate and does not need a special instrument.
(2) The method of the invention utilizes computer technology to revolutionize the traditional thin-layer chromatography technology, and the color on the thin-layer chromatography is used for representing the structure of a natural product.
(3) The method has high flux, and can measure a plurality of samples in the same system; the mixture can be judged, and the practicability is high.
Drawings
FIG. 1 is a database of information corresponding to natural products of sterols, phenolic acids, polyphenols;
FIG. 2 is database information corresponding to flavonoid glycosides, sugar natural products;
FIG. 3 is a graph showing the comparison of the cholesterol to be detected with the characteristic information of natural products of sterols in the database in the examples;
FIG. 4 is a graph showing the comparison of epicatechin to be detected with the characteristic information of polyphenol natural products in the database in the examples;
FIG. 5 is a graph comparing the characteristic information of caffeic acid to be detected with the characteristic information of natural phenolic acid products in the database in the example;
FIG. 6 is a graph showing characteristic information of rutin to be detected and natural flavonoid glycoside products in the database;
FIG. 7 is a graph showing the comparison of the information on the characteristics of sucrose to be tested and the natural products of saccharides in the database in the examples.
Detailed Description
The present invention will be described in further detail with reference to examples, but the embodiments of the present invention are not limited thereto.
The color developing agent adopted in the embodiment is p-methoxybenzaldehyde coloring agent, and the composition of the color developing agent is p-methoxybenzaldehyde/acetic acid/ethanol/sulfuric acid (9.2/3.75/338/12.5, v/v/v/v).
Firstly, a natural product classification database is established, and the method comprises the following steps:
(i) selecting 35 compounds of 5 main natural products: simple polyphenols (catechin C, pyrogallic acid, tyrosol, hydroquinone, catechol, EGC, EGCG, theaflavin), phenolic acids (gallic acid, ferulic acid, syringic acid, 4-coumaric acid), saccharides (glucose, L-rhamnose monohydrate, L-arabinose, D-xylose, D-mannose, D-fructose, maltose, trehalose, gentiobiose, D-raffinose, stachyose), sterols (sitosterol, stigmasterol, ergosterol), flavonoid glycosides (quercetin, hyperoside, quercetin-3-glucose-7-gentiobiose, calycosin, isorhamnetin-3-O-neohesperidin, isorhamnetin-3-O-glucoside, isoquercitrin, formononetin, isoliquiritin), after dissolving with a proper solvent, spotting one by one on a thin layer chromatography plate, wherein the spotting volume is 0.5 microliter and the concentration is 1-15 mg/mL.
(ii) After the solvent is volatilized, developing the developed thin-layer chromatographic plate by utilizing a p-methoxybenzaldehyde coloring agent: the heat block was heated at 250 ℃ and the process was recorded with iphone8 for 10-20 seconds.
(iii) Resolving the video into frames by using a VideoReader function in Matlab;
(iv) opening each frame of image by using ImageJ, randomly selecting 3 pixel points in each sample region point, reading RGB values of the pixel points by using a Color Picker tool, calculating the average value to obtain the RGB value of the sample point, and performing the operation on hundreds of frames of images in a video by using a Macro file carried by the ImageJ to obtain Color change information of each sample in the Color development process;
(v) dividing the sample points into two types, namely a large polarity group (saccharides and flavonoid glycosides) and a small polarity group (sterols, simple polyphenols and phenolic acids), drawing the sample points into a scatter diagram by taking R/G as a horizontal coordinate and B/G as a vertical coordinate, and observing and analyzing the relationship among different natural products to obtain a natural product classification database, as shown in fig. 1 and 2;
when judging the type of the unknown natural product, firstly determining the approximate polarity of the unknown natural product according to the plate running characteristics of the unknown natural product in different developing agents, and then repeating the operations (ii) to (v) to judge which type of natural product the natural product has the highest contact ratio with.
Example 1
Dissolving cholesterol in hot ethyl acetate at a concentration of 2mg/mL, spotting 0.5 microliter with a quantitative capillary onto a thin-layer chromatography plate, and after the solvent is evaporated, dyeing with p-methoxybenzaldehyde dye at 250 ℃ for 15 seconds, wherein the dyeing process is recorded by iPhone 8. And (3) disassembling the obtained video into a frame by using a VideoReader function in Matlab, reading RGB values by using ImageJ, repeatedly operating a series of images by using a Macro Macro file to obtain all R/G and B/G, and then drawing all points in the color development process of the sample into a database, wherein as shown in figure 3, the coincidence degree of the result and simple polyphenols in the database is high, and the judgment is accurate.
The thin layer chromatography plate is purchased from the market and has the specification (silica gel material, the thickness of the coating is 0.2-0.25 mm, and the granularity of silica gel powder is 10-40 microns).
Example 2
Dissolving epicatechin in ethanol at a concentration of 5mg/mL, spotting 0.5 microliter with a quantitative capillary onto a thin-layer chromatography plate, after the solvent is volatilized, dyeing with p-methoxybenzaldehyde dye at 250 ℃ for 15 seconds, and recording the dyeing process with iPhone 8. And (3) disassembling the obtained video into a frame by using a VideoReader function in Matlab, reading an RGB value by using ImageJ, repeatedly operating a series of images by using a Macro Macro file to obtain all R/G and B/G, and then drawing all points in the color development process of the sample into a database, wherein as shown in figure 4, the coincidence degree of the result and the flavanonoside glycoside in the database is high, and the judgment is accurate.
The thin layer chromatography plate is purchased from the market and has the specification (silica gel material, the thickness of the coating is 0.2-0.25 mm, and the granularity of silica gel powder is 10-40 microns).
Example 3
Dissolving caffeic acid in ethanol at concentration of 15mg/mL, spotting 0.5 μ l with quantitative capillary onto thin layer chromatography plate, drying solvent, dyeing with p-methoxybenzaldehyde at 250 deg.C for 15 s, and recording with iPhone 8. And (3) disassembling the obtained video into a frame by using a VideoReader function in Matlab, reading an RGB value by using ImageJ, repeatedly operating a series of images by using a Macro Macro file to obtain all R/G and B/G, and then drawing all points in the color development process of the sample into a database, wherein as shown in figure 5, the coincidence degree of the result and the saponins in the database is high, and the judgment is accurate.
The thin layer chromatography plate is purchased from the market and has the specification (silica gel material, the thickness of the coating is 0.2-0.25 mm, and the granularity of silica gel powder is 10-40 microns).
Example 4
Dissolving rutin in methanol (2-3 drops of trichloromethane), wherein the concentration is 5mg/mL, spotting 0.5 microliter by using a quantitative capillary tube to a thin-layer chromatographic plate, dyeing by using a p-methoxybenzaldehyde dyeing agent at 250 ℃ for 15 seconds after the solvent is volatilized, and recording by using iPhone8 in the dyeing process. And (3) disassembling the obtained video into a frame by using a VideoReader function in Matlab, reading an RGB value by using ImageJ, repeatedly operating a series of images by using a Macro Macro file to obtain all R/G and B/G, and then drawing all points in the color development process of the sample into a database, wherein as shown in figure 6, the coincidence degree of the result and the sterols in the database is high, and the judgment is accurate.
The thin layer chromatography plate is purchased from the market and has the specification (silica gel material, the thickness of the coating is 0.2-0.25 mm, and the granularity of silica gel powder is 10-40 microns).
Example 5
Dissolving sucrose in water at concentration of 2mg/mL, spotting 0.5 microliter with quantitative capillary onto thin layer chromatography plate, drying solvent, dyeing with p-methoxybenzaldehyde at 250 deg.C for 15 s, and recording with iPhone 8. And (3) disassembling the obtained video into a frame by using a VideoReader function in Matlab, reading an RGB value by using ImageJ, repeatedly operating a series of images by using a Macro Macro file to obtain all R/G and B/G, and then drawing all points in the color development process of the sample into a database, wherein as shown in figure 7, the coincidence degree of the result and saccharides in the database is high, and the judgment is accurate.
The thin layer chromatography plate is purchased from the market and has the specification (silica gel material, the thickness of the coating is 0.2-0.25 mm, and the granularity of silica gel powder is 10-40 microns).
According to the experimental results, the method can effectively classify various natural products, and is high in precision and applicability.
For the detection of mixed samples, the sample application and color development can be carried out according to a similar method, and the analysis and classification can be carried out on a plurality of sample points one by one.
Claims (5)
1. A method for judging natural product category based on color change information in a thin-layer chromatography dyeing process is characterized by comprising the following steps: carrying out sample application or development on a sample to be detected by utilizing a thin-layer chromatography plate, developing the sample application or developed thin-layer chromatography plate, recording the developing process, carrying out imaging processing on the obtained video file, extracting the characteristic information of the obtained multi-frame image, and matching the obtained characteristic information with the characteristic information of various natural products in the constructed database to obtain classification information;
the database is constructed by adopting the following method:
selecting an existing natural product, expanding a sample to be detected by adopting a thin-layer chromatography plate, developing the expanded thin-layer chromatography plate, recording the developing process of a sample point on the thin-layer chromatography plate, imaging the obtained video file, extracting characteristic information of the obtained multi-frame image, and constructing a database according to the extracted characteristic information;
when the database is constructed, classifying the existing natural products according to polarity, and constructing a scatter diagram with R/G, B/G as horizontal, vertical and horizontal coordinates aiming at each type of corresponding color development point to obtain the database;
the operation of extracting the characteristic information is as follows: reading RGB values of corresponding color-developing points in the multi-frame images one by one, calculating corresponding R/G, B/G information, obtaining points in a corresponding R/G, B/G coordinate system, and obtaining corresponding characteristic information;
constructing a scatter diagram with R/G, B/G as horizontal, vertical and horizontal coordinates according to the R/G, B/G value corresponding to the sample to be detected, and comparing the scatter diagram with the scatter diagram in the database to obtain a classification result;
when the database is constructed, a plurality of groups of R/G, B/G data corresponding to a plurality of images corresponding to the same developing point are calculated to obtain the minimum circumscribed rectangle of the R/G, B/G data, and the characteristic region of the natural product corresponding to the developing point is obtained; and (4) judging the probability of the R/G, B/G value corresponding to the sample to be detected belonging to each characteristic region in the database one by one, wherein the class with the highest probability is the class to which the sample to be detected belongs, and obtaining a classification result.
2. The method for determining the category of the natural product based on the color change information in the thin-layer chromatography dyeing process as claimed in claim 1, wherein the video file is disassembled into frames by using a Matlab self-contained function to obtain the multi-frame image.
3. The method for determining the class of natural products based on color change information during thin layer chromatography staining of claim 1, wherein the reading of the RGB values is performed using ImageJ.
4. The method for determining the category of natural products based on the color change information in the thin layer chromatography dyeing process as claimed in claim 3, wherein ImageJ is used to read the RGB values of at least three points on each color development point, and the average value is calculated to obtain the corresponding RGB value of the point.
5. The method of claim 1, wherein the natural product is one or more of sterol, sugar, flavonoid aglycone, flavonoid glycoside, saponin aglycone, and phenolic compound.
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