CN109959751B - Water-soluble natural product thin-layer quantitative image identification and detection method - Google Patents
Water-soluble natural product thin-layer quantitative image identification and detection method Download PDFInfo
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Abstract
The invention discloses a water-soluble natural product thin-layer quantitative image identification and detection method, which comprises the following steps: (1) carrying out sample application on a sample to be detected containing a water-soluble natural product on a thin-layer chromatography plate; (2) carrying out thin-layer chromatography step-by-step development on the spotted thin-layer chromatography plate by using a first developing agent and a second developing agent; the first developing agent is a developing system consisting of ethyl acetate/ethanol/water/acetic acid, and the second developing agent is a developing system consisting of trichloromethane/ethyl acetate/formic acid; (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. The method of the invention is simple and convenient to operate and does not need special instruments. The method has the advantages of good quantification and high accuracy. The method has high testing speed and can simultaneously test a plurality of samples.
Description
Technical Field
The invention belongs to the field of natural products and food and medicine, and particularly relates to a thin-layer quantitative image identification and detection method for a water-soluble natural product.
Background
The water-soluble natural products including flavonoid, flavonoid glycoside, anthocyanin and saponin are important active ingredients in plants, and have the effects of inhibiting bacteria, preserving freshness, resisting oxidation, delaying aging, resisting bacteria, resisting virus, reducing blood fat, resisting cancer and the like. The water-soluble natural products of flavonoid, flavonoid glycoside and anthocyanin have excellent antioxidation, can effectively balance free radicals in human body in a mode of eliminating active oxygen clusters or generating stable compounds through reaction, and can terminate free radical chain reaction through metal ion chelating capacity. A large number of in vivo and in vitro experiments and epidemiological data show that the water-soluble natural saponin product has the biological and pharmacological effects of resisting inflammation, reducing blood fat, resisting diabetes, preventing cardiovascular diseases (CVD) and the like, and has wide application prospect in high-tech fields such as pharmacy, biochemistry, daily chemicals, food, fine chemical industry and the like. The common detection methods of the water-soluble natural products comprise a spectrophotometry method and a liquid phase method, but a special instrument is needed, and the operation is relatively troublesome.
Recently, computer image processing technology has been rapidly developed, and quantitative analysis of images has been feasible. 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 a public domain Java image processing program developed by NIH. It can run as an online applet or downloadable application on any computer having a virtual machine of java1.4 or higher. The downloadable release is applicable to Windows, Mac OS, Mac OS X and Linux. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacking," a series of images that share a single window. It is multi-threaded so time consuming operations such as image file reading can be performed in parallel with other operations. It may calculate area and pixel value statistics for the user-defined selection. It can measure distance and angle. It can create a density histogram and a line profile. It supports standard image processing functions such as contrast manipulation, sharpening, smoothing, edge detection and median filtering. It can perform geometric transformations such as scaling, rotation and flipping. All analysis and processing functions can be used at any magnification factor. The program supports any number of windows (images) simultaneously, limited only by the available memory. Spatial calibration can be used to provide real-world dimensional measurements in millimeters. Density or grey scale calibration may also be performed. ImageJ is designed by adopting an open architecture, and expandability is provided through a Java plug-in. Plug-ins may be developed for custom collection, analysis and processing using the built-in editor and Java compiler of ImageJ. User-written plug-ins can solve almost any image processing or analysis problem.
Thin-layer analysis of natural products is a commonly used high-efficiency technique, but the traditional thin-layer quantitative analysis needs a special instrument and is inconvenient to apply. Therefore, based on the latest computer image quantitative analysis means, the thin-layer quantitative image recognition and detection of flavonoid polyphenol can simplify the operation and effectively widen the application range. There have been several studies for quantitative detection of active ingredients using image recognition. For example, patent document No. 200510115774.X discloses a thin layer chromatography quantitative analysis method based on image processing technology, which comprises the following steps: (1) photographing the thin layer plate carrying the sample to form a digital image; (2) preprocessing a shot image: correcting lens distortion and filtering noise; (3) determining control points by using the principles of uniform sample application distribution and equal longitudinal distance division; (4) constructing an image background according to a control point interpolation method; (5) removing a background from the lens distortion correction image, and normalizing the brightness of the pixel points according to the background; (6) thin layer images are segmented (7) and the gray levels of the segmented regions are integrated and quantitatively analyzed. However, the method only describes the general principle of image analysis, and cannot be directly applied to quantitative detection of specific natural products. Patent document No. 201510163742.0 discloses a method for measuring the content of morinda citrifolia, in which a chromatographic peak is integrated by a trapezoidal integration method, and a quantitative analysis is performed based on the peak area and the sample concentration. However, this method is limited to the determination of one specific sugar. Patent document No. 201810451846.5 discloses a method for identifying the authenticity of honey by analyzing oligosaccharides in a honey sample using ImageJ software. However, this method is limited to the analysis of only one type of sugar. Therefore, the development of a thin-layer image identification quantitative analysis method suitable for different types has important significance for rapid analysis and identification of natural products.
Disclosure of Invention
The water-soluble natural product thin-layer quantitative image identification and detection method provided by the invention is simple and convenient in process, does not need a special instrument, and is wide in application range.
A water-soluble natural product thin layer quantitative image identification detection method comprises the following steps:
(1) carrying out sample application on a sample to be detected containing a water-soluble natural product on a thin-layer chromatography plate;
(2) carrying out thin-layer chromatography step-by-step development on the spotted thin-layer chromatography plate by using a first developing agent and a second developing agent; the first developing agent is a developing system consisting of ethyl acetate/ethanol/water/acetic acid, and the second developing agent is a developing system consisting of trichloromethane/ethyl acetate/formic acid;
(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.
Specifically, a thin-layer quantitative image recognition and detection method for water-soluble natural products, which is used for carrying out simultaneous quantitative analysis on different water-soluble natural products (flavonoid, flavonoid glycoside, anthocyanin and saponin) and mixtures thereof based on computer image recognition and comprises the following steps:
(1) carrying out thin-layer chromatography gradual development on different large natural products by utilizing an ethyl acetate/ethanol/water/acetic acid and chloroform/ethyl acetate/formic acid developing agent system;
(2) carrying out thin-layer chromatography color development on different water-soluble natural products by utilizing a uniform coloring agent system;
(3) and (4) electronizing and quantitatively analyzing the water-soluble natural product thin-layer chromatographic image to obtain a final water-soluble natural product thin-layer quantitative result.
In the invention, before detection, the water-soluble natural product can be dissolved by a solvent to prepare a water-soluble natural product sample solution, and then thin-layer chromatography development is carried out; the concentration of the water-soluble natural product sample solution is 0.01-10 mg/mL; further preferably 0.5 to 5 mg/mL. When thin-layer chromatography is adopted, the sample amount is 0.1-10 microliter; preferably 0.1 to 1 microliter. The water-soluble natural product sample to be detected can be dissolved by using various solvents, generally, a solvent with good solubility and easy volatility 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.
The water-soluble natural product sample is spotted to thin-layer chromatography and then is developed in a developing agent system step by step, firstly, the water-soluble natural product sample is developed to the distance of R1 on an ethyl acetate/ethanol/water/acetic acid developing agent plate, then is dried in the air, and is re-developed to the length of R2 by using a chloroform/ethyl acetate/formic acid developing agent.
In the present invention, R1 and R2 are both distances represented by using an initial spotting center point as a starting point and a most front line of a developing agent after development as an end point. Preferably, the R1 is 15-25 mm; and the R2 is 35-45 mm. Of course, for a particular deployment system, the deployment action of both deployment systems can also be controlled by controlling the deployment time. Preferably, R1 is 20 mm; the R2 is 40 mm.
The volume ratio of each solvent in the first developing solvent is 5: 2.5 to 3/0.1 to 0.2/0.1 to 0.15; further preferred volume ratios are: ethyl acetate/ethanol/water/acetic acid 5/2.85/0.15/0.12; the volume ratio of solvents in the second developing agent is 1/0.8-1.2/0.01-0.05; a further preferred volume ratio is chloroform/ethyl acetate/formic acid 1/1/0.03.
After the water-soluble natural product sample is developed on the thin-layer chromatography, a p-methoxybenzaldehyde developer is used for developing color, the color developing time is 0.1-10 minutes, and the color developing temperature is 150-.
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 water-soluble natural product comprises one or more of flavonoid, flavonoid glycoside, anthocyanin and saponin; as a further preference, the water-soluble natural product comprises one or more of catechin, quercetin, theasaponin, cyanidin glucoside, oleanolic acid, chlorinated cyanidin, and rutin.
And after the water-soluble natural product sample is developed on the thin-layer chromatography, a camera or a scanner is adopted for electronic image acquisition.
As shown in fig. 1, after the color development is completed, a camera or a scanner can be used to perform electronic image acquisition, so as to complete the electronization of the water-soluble natural product sample image. After the water-soluble natural product sample image is electronized, selecting proper image processing software, such as: ImageJ, and the like, and image optimization processing is performed. Since the quantitative analysis is based on gray scale values, the picture is first converted to a gray scale picture with software.
The image optimization processing of the water-soluble natural product sample comprises denoising and smoothing. And performing a series of operations such as salt and pepper noise removal, correction, edge sharpening, smoothing and the like on the gray level picture to make the picture more suitable for quantitative analysis.
And after the image of the water-soluble natural product sample is optimized, background removal is carried out. And selecting a proper algorithm to remove the interference background in the image to be analyzed.
And after the background of the water-soluble natural product sample image is removed, integrating and quantifying to obtain a quantitative result.
Taking ImageJ software for image processing as an example, the process is as follows:
after the water-soluble natural product sample is developed on a thin-layer chromatography, an HP M1005 scanner is adopted for electronic image acquisition, and the parameters are set as follows: million colors output, resolution 300dpi, brightness and contrast defaults, and pictures saved in TIFF format.
And after the images of the water-soluble natural product samples are electronized, image optimization processing is carried out by adopting ImageJ software.
Firstly, quantitative analysis is based on gray values, so that ImageJ software is started, firstly, "Image" - "Type" - "8-bit" is selected, the picture is converted into a gray picture, then, "Image" - "Adjust" - "bright ness/contrast.
Secondly, performing image optimization processing such as Noise reduction and smoothing on the gray level image, selecting 'Process' -Noise '-Despeckle', replacing each pixel in the image with a median value of pixels in 3-3 neighborhood through a median filter to remove salt and pepper Noise in the image, selecting 'Process' -Noise '-removeoutliers', and replacing pixel points with deviations exceeding a set threshold value with intermediate values of surrounding pixels to correct the image; then selecting 'Process' -Filters '-unsharpmaster-said', extracting fuzzy version to sharpen and enhance image edge; finally, "Process" - "Smooth" is chosen to Smooth the entire image to make the integration baseline more even.
And then, after the image of the water-soluble natural product sample is optimized, removing the background by adopting ImageJ software. Selecting "Process" - "subtactbackground.", based on the "Rollingball" algorithm in ImageJ, giving the appropriate radius of the scroll ball in the pop-up dialog box, and ticking "Lightbackground" and "slidingparadolid", removing the continuous background in the image.
And after the background of the image of the water-soluble natural product sample is removed, integrating and quantifying by adopting ImageJ software to obtain a quantitative result. Clicking 'rectangular selectiontool' to select a target area, clicking 'Ctrl + 1' to determine a band, clicking 'Ctrl + 3' to integrate, connecting two ends of a peak by 'StraightLineSelectiontool' to form a closed graph, and then determining a peak area by 'wandtool' to complete quantitative analysis.
The present invention can use common TLC plates of various specifications, preferably, the standard curve is the same as that of the TLC plate used for actual detection.
When the quantitative analysis is carried out, a standard curve between the integral value (for ImageJ, the peak area) and the sample content can be constructed in advance, and then the content of the sample can be directly obtained after the integral value is obtained, namely the quantification of the sample to be detected is realized.
One specific method of making the standard curve is as follows:
(i) taking standard samples with set concentration (such as 1.0, 2.0, 3.0mg/L, and multiple sets of samples can be arranged in parallel) and set volume (such as 0.5 microliter), and carrying out spotting on a thin-layer chromatography plate;
(ii) carrying out thin-layer chromatography step-by-step development on the spotted thin-layer chromatography plate by using a first developing agent and a second developing agent; the first developing agent is a developing system consisting of ethyl acetate/ethanol/water/acetic acid, and the second developing agent is a developing system consisting of trichloromethane/ethyl acetate/formic acid;
(iii) developing the developed thin-layer chromatography plate by using a coloring agent system;
(iv) carrying out image acquisition on the developed thin-layer chromatography plate to obtain an integral value;
(v) (iv) obtaining integral values corresponding to the plurality of sets of standard samples according to the method of the steps (i) to (iv), and preparing a standard curve between the sample concentration and the integral values.
The distance between the first developing agent and the second developing agent can be determined by the above-mentioned description of the detection method, such as first developing the developing agent on a developing agent plate with ethyl acetate/ethanol/water/acetic acid to a distance of R1, then drying the developing agent, and then developing the developing agent plate with chloroform/ethyl acetate/formic acid to a length of R2. The R1 is 15-25 mm; and the R2 is 35-45 mm. Of course, for a particular deployment system, the deployment action of both deployment systems can also be controlled by controlling the deployment time. Preferably, the developing system used for the actual detection is the same as the developing system used for the standard curve preparation.
Preferably, the standard curve is constructed such that the development distance is the same as that in the actual detection process, and the spotting condition, the developing condition, and the image collecting and processing condition are the same as those in the detection process.
The invention can be used for detecting single component samples and mixed component samples, and when the invention is used for detecting mixed component samples, the invention respectively realizes the image acquisition of each component sample point by using the image acquisition unit and then respectively calculates the concentration value of the sample. Of course, the invention can also realize the detection of a plurality of samples at one time, and during the detection, the samples can be spotted on the same thin-layer chromatographic plate, and then the image acquisition and the calculation are respectively carried out. As shown in fig. 1, six samples with sequentially increased concentrations are detected by the method of the present invention, i.e., the samples are respectively spotted on the same thin layer chromatography plate at spotting positions, and the distance between the samples is only required to avoid interference; and then developing, scanning by using a computer scanner, respectively reading images corresponding to the samples, integrating, and finally obtaining the concentration values of the corresponding samples, wherein the detection results are equivalent to the detection results of the respective independent detections and almost have no interference effect.
Compared with the existing detection method, the invention has the following advantages:
(1) the thin-layer quantitative image identification and detection method of the water-soluble natural product is simple and convenient to operate and does not need a special instrument.
(2) The method of the invention adopts the same development system, can detect various water-soluble natural products, and has the advantages of good quantification, simple operation and high accuracy.
(3) The method has high testing speed, and can simultaneously test a plurality of samples; can also detect samples containing a plurality of components, and has strong practicability.
Drawings
FIG. 1 is a diagram showing the procedure of detection using the method of the present invention for six samples whose concentrations are sequentially increased.
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 standard curve is made, and the method comprises the following steps:
(i) taking a standard sample with a set concentration, and carrying out spotting on a thin-layer chromatography plate (the same thin-layer chromatography plate as that in example 1 is adopted); in this example, five sets of standard samples (the samples are the same as those to be detected in each example) of 0.5, 1.0, 2.0, 3.0 and 4.0mg/L are used, the solvent is ethanol, and the spotting volume is 0.5 microliter;
(ii) after drying, carrying out thin-layer chromatography step-by-step development on the sample-applied thin-layer chromatography plate by using a first developing agent and a second developing agent;
spreading with ethyl acetate/ethanol/water/acetic acid (5/2.85/0.15/0.12, v/v/v/v) developer for 20 mm, air drying, and spreading with chloroform/ethyl acetate/formic acid (1/1/0.03, v/v/v) developer to 40 mm length;
(iii) developing the developed thin-layer chromatographic plate by using a p-methoxybenzaldehyde coloring agent: heating the heating table at 250 ℃ for 15 seconds to develop color;
(iv) after the thin layer was developed, it was scanned with a computer scanner with a resolution set at 300 dpi. Denoising and smoothing the scanned image by using ImageJ, removing a background, and finally performing quantitative integration to obtain integral values corresponding to five groups of standard samples of 0.5, 1.0, 2.0, 3.0 and 4.0 mg/L;
(v) a standard curve between the sample concentration and the integrated value was made.
For the accuracy of detection, for each set of standards, three replicates were tested, and the average of the integrated values was taken as its corresponding integrated value.
For samples with different components, standard curves are required to be drawn according to the method.
In the process of making the standard curve and after the sample in the embodiment is developed, the subsequent image processing process is as follows:
adopting an HP M1005 scanner to carry out electronic image acquisition on the developed thin-layer chromatographic plate, wherein the parameters are set as follows: million colors output, resolution 300dpi, brightness and contrast defaults, and pictures saved in TIFF format.
And adopting ImageJ software to perform image optimization processing. Firstly, quantitative analysis is based on gray values, so that ImageJ software is started, firstly, "Image" - "Type" - "8-bit" is selected, the picture is converted into a gray picture, then, "Image" - "Adjust" - "bright ness/contrast.
Secondly, carrying out Noise reduction, smoothing and other processing on the gray level image, selecting 'Process' - 'Noise' - 'Despeckle', replacing each pixel in the image by a median filter to a median of pixels in 3 x 3 neighborhood thereof so as to remove salt and pepper Noise in the image, then selecting 'Process' - 'Noise' - 'removeoutliers', and replacing a pixel point with a deviation exceeding a set threshold value by a median of surrounding pixels so as to correct the image; then selecting 'Process' -Filters '-Unsharp mask.', and extracting a fuzzy version to sharpen and enhance the image edge; finally, "Process" - "Smooth" is chosen to Smooth the entire image to make the integration baseline more even.
Then, ImageJ software was used for background removal. Selecting "Process" - "subtactbackground.", based on the "Rollingball" algorithm in ImageJ, giving the appropriate radius of the scroll ball in the pop-up dialog box, and ticking "Lightbackground" and "slidingparadolid", removing the continuous background in the image.
And after the image background is removed, integrating and quantifying by adopting ImageJ software to obtain a quantitative result. Clicking 'rectangular selecting tool' to select a target area, clicking 'Ctrl + 1' to determine a strip, clicking 'Ctrl + 3' to perform integration, connecting two ends of a peak by using 'StraightLine selecting tool' to form a closed graph, and then determining a peak area by using 'wandtool' to obtain a corresponding integral value.
Example 1
The (+) -catechin ethanol solution is spotted by a capillary tube with 0.5 microliter to thin layer chromatography, after the solvent is evaporated, spread on a developing agent plate with ethyl acetate/ethanol/water/acetic acid (5/2.85/0.15/0.12, v/v/v/v) for a distance of 20 mm, then dried, and then spread again to a length of 40 mm with chloroform/ethyl acetate/formic acid (1/1/0.03, v/v/v) developing agent. Then taking out the mixture, drying the solvent, dyeing the mixture by a p-methoxybenzaldehyde coloring agent, and placing the mixture on a heating table at 250 ℃ for heating for 15 seconds to develop color. After the thin layer was developed, it was scanned with a computer scanner with a resolution set at 300 dpi. And (3) denoising and smoothing the scanned image by using ImageJ, removing the background, and finally performing quantitative integration, wherein the integral value is compared with a standard value to obtain a measurement result. Actual value was 1.20mg/mL of (+) -catechin solution, measured 1.22mg/mL with an error of 2%.
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
The quercetin ethanol solution is spotted by a capillary tube for 0.5 microliter to thin layer chromatography, after the solvent is volatilized, the solution is spread on a developing agent plate by using ethyl acetate/ethanol/water/acetic acid (5/2.85/0.15/0.12, v/v/v/v) for a distance of 20 mm, then the solution is dried in the air, and then the solution is re-spread to a length of 40 mm by using chloroform/ethyl acetate/formic acid (1/1/0.03, v/v/v) developing agent. Then taking out the mixture, drying the solvent, dyeing the mixture by a p-methoxybenzaldehyde coloring agent, and placing the mixture on a heating table at 250 ℃ for heating for 15 seconds to develop color. After the thin layer was developed, it was scanned with a computer scanner with a resolution set at 300 dpi. And (3) denoising and smoothing the scanned image by using ImageJ, removing the background, and finally performing quantitative integration, wherein the integral value is compared with a standard value to obtain a measurement result. The actual value of the quercetin ethanol solution is 1.51mg/mL, the measured value is 1.53mg/mL, and the error is 1.5%.
Example 3
The theasaponin ethanol solution is spotted by a capillary tube for 0.5 microliter to thin layer chromatography, after the solvent is volatilized, the theasaponin ethanol solution is spread on a developing agent plate by ethyl acetate/ethanol/water/acetic acid (5/2.85/0.15/0.12, v/v/v/v) for a distance of 20 mm, then the theasaponin ethanol solution is dried in the air, and then the theasaponin ethanol solution is re-spread to a length of 40 mm by chloroform/ethyl acetate/formic acid (1/1/0.03, v/v/v) developing agent. Then taking out the mixture, drying the solvent, dyeing the mixture by a p-methoxybenzaldehyde coloring agent, and placing the mixture on a heating table at 250 ℃ for heating for 15 seconds to develop color. After the thin layer was developed, it was scanned with a computer scanner with a resolution set at 300 dpi. And (3) denoising and smoothing the scanned image by using ImageJ, removing the background, and finally performing quantitative integration, wherein the integral value is compared with a standard value to obtain a measurement result. The actual value of the tea saponin ethanol solution is 2.5mg/mL, the measured value is 2.62mg/mL, and the error is 5%.
Example 4
The cyanidin glucoside ethanol solution is spotted by a capillary tube by 0.5 microliter to a thin layer chromatography, after the solvent is volatilized, the solution is spread on a developing agent plate by ethyl acetate/ethanol/water/acetic acid (5/2.85/0.15/0.12, v/v/v/v) for a distance of 20 mm, then is dried, and is re-spread to a length of 40 mm by chloroform/ethyl acetate/formic acid (1/1/0.03, v/v/v) developing agent. Then taking out the mixture, drying the solvent, dyeing the mixture by a p-methoxybenzaldehyde coloring agent, and placing the mixture on a heating table at 250 ℃ for heating for 15 seconds to develop color. After the thin layer was developed, it was scanned with a computer scanner with a resolution set at 300 dpi. And (3) denoising and smoothing the scanned image by using ImageJ, removing the background, and finally performing quantitative integration, wherein the integral value is compared with a standard value to obtain a measurement result. The actual value was 1.50mg/mL cyanidin glucoside solution, the measurement was 1.53mg/mL with an error of 2%.
Example 5
Oleanolic acid, quercetin, (+) -catechin, chlorinated cyanidin, rutin ethanol solution (actual content is respectively: oleanolic acid: 1.21 mg/mL; quercetin: 1.31 mg/mL; (+) -catechin: 1.17 mg/mL; chlorinated cyanidin: 2.54 mg/mL; rutin: 1.12mg/mL), spotting 0.5 microliter with capillary to thin layer chromatography, after the solvent is evaporated, spreading with ethyl acetate/ethanol/water/acetic acid (5/2.85/0.15/0.12, v/v/v/v) developer for 20 mm distance, then drying, and re-spreading with chloroform/ethyl acetate/formic acid (1/1/0.03, v/v/v/v) developer to 40 mm length. Then taking out the mixture, drying the solvent, dyeing the mixture by a p-methoxybenzaldehyde coloring agent, and placing the mixture on a heating table at 250 ℃ for heating for 15 seconds to develop color. After the thin layer was developed, it was scanned with a computer scanner with a resolution set at 300 dpi. And (3) denoising and smoothing the scanned image by using ImageJ, removing a background, and finally performing quantitative integration, wherein the integral value is compared with a standard value to obtain a measurement result, and the content value is oleanolic acid: 1.17 mg/mL; and (3) quercetin: 1.27 mg/mL; (+) -catechin: 1.15 mg/mL; chlorinated cyanidin: 2.46 mg/mL; rutin: 1.09 mg/mL. The error is less than 3%.
Claims (8)
1. A water-soluble natural product thin layer quantitative image identification detection method is characterized by comprising the following steps:
(1) carrying out sample application on a sample to be detected containing a water-soluble natural product on a thin-layer chromatography plate;
(2) carrying out thin-layer chromatography step-by-step development on the spotted thin-layer chromatography plate by using a first developing agent and a second developing agent; the first developing agent is a developing system consisting of ethyl acetate/ethanol/water/acetic acid, and the second developing agent is a developing system consisting of trichloromethane/ethyl acetate/formic acid;
(3) developing the developed thin-layer chromatography plate by using a coloring agent system;
(4) collecting images of the developed TLC plate, and obtaining the content of the water-soluble natural product according to the relation between the images and the content of the water-soluble natural product;
the volume ratio of each solvent in the first developing agent is 5/2.5-3/0.1-0.2/0.1-0.15; the volume ratio of solvents in the second developing agent is 1/0.8-1.2/0.01-0.05;
the water-soluble natural product comprises one or more of catechin, quercetin, tea saponin, cyanidin glucoside, oleanolic acid, chlorinated cyanidin and rutin.
2. The quantitative image recognition and detection method for the water-soluble natural product thin layer as claimed in claim 1, wherein in the step (2), the water-soluble natural product thin layer is firstly unfolded to a distance of R1 by using a first developing agent, then dried, and then re-unfolded to a distance of R2 by using a second developing agent, wherein the R1 is 15-25 mm; and the R2 is 35-45 mm.
3. The quantitative image identification and detection method for the water-soluble natural product thin layer as claimed in claim 1, wherein the staining agent system is a p-anisaldehyde color developing agent.
4. The quantitative image recognition and detection method for the water-soluble natural product thin layer as claimed in claim 3, wherein the composition volume of the stain system is as follows: p-methoxybenzaldehyde/acetic acid/ethanol/sulfuric acid of 9.1 to 9.5/3.5 to 4/300 to 350/12.5.
5. The method for identifying and detecting the thin-layer quantitative image of the water-soluble natural product according to claim 1, wherein the concentration of the water-soluble natural product in the sample to be detected is 0.01-10mg/mL, and the sample amount is 0.1-10 microliters.
6. The method for quantitative image identification and detection of water-soluble natural product thin layers as claimed in claim 1, wherein electronic image acquisition is performed by a camera or a scanner.
7. The thin-layer quantitative image identification and detection method for the water-soluble natural products, as claimed in claim 1, is characterized in that the collected images are processed by ImageJ, and finally, integral quantification is carried out, and the concentration of the sample to be detected containing the water-soluble natural products is obtained by utilizing the relation between the integral value and the content of the sample.
8. The method for quantitative image identification and detection of water-soluble natural product thin layer as claimed in claim 1, characterized in that a standard curve between the content of the sample and the integral value is constructed in advance, and the concentration of the sample to be detected containing the water-soluble natural product is obtained according to the integral value and the standard curve during detection.
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