CN109959750A - Fat-soluble natural products thin layer quantitative image recognition detection method - Google Patents
Fat-soluble natural products thin layer quantitative image recognition detection method Download PDFInfo
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Abstract
The invention discloses a kind of fat-soluble natural products thin layer quantitative image recognition detection methods, comprising: (1) sample to be tested containing fat-soluble natural products carries out point sample on chromatographic sheet；(2) Development of Thin-Layer Chromatography is carried out to the chromatographic sheet after point sample using petrol ether/ethyl acetate solvent system；(3) it is developed the color using coloring agent system to the chromatographic sheet after expansion；(4) Image Acquisition is carried out to the chromatographic sheet after colour developing and the content of water-soluble natural product is obtained according to the relationship between image and water-soluble natural product assay.Method of the invention is easy to operate, does not need special instrument.Method of the invention is quantitative good, using same expansion system, can carry out quantitative detection to a variety of fat-soluble natural products, accuracy is high.Method test speed of the invention is fast, can be measured simultaneously with multiple samples；The sample containing multiple components can also be detected simultaneously, it is practical.
Description
Technical field
The invention belongs to natural products and food and medicine field, and in particular to a kind of fat-soluble natural products thin layer is quantitatively schemed
As recognition detection method.
Background technique
Fat-soluble natural products includes the types such as carotenoid, sterol.Carotenoid is a kind of important natural colour
Element, be prevalent in animal, higher plant, fungi, the yellow of algae, among orange red or red pigment.Carotenoid
It is the main source of internal vitamin A, while also there is anti-oxidant, immunological regulation, anticancer, anti-aging and other effects.Sterol is wide
It is general to be present in veterinary antibiotics and cereal, it is a kind of important novel foodstuff functional component, it is living with a variety of significant physiology
Property especially cardiovascular protection function.Cardiovascular disease is that the principal disease of human health is threatened in world wide, at present China
Patients with Cardiovascular/Cerebrovascular Diseases alreadys exceed 2.7 hundred million people, dies of nearly 3,000,000 people of cardiovascular and cerebrovascular disease every year, and it is annual total dead to account for China
Die the 51% of the cause of disease, it has also become the primary cause of death of Chinese Adult is that the major public health that 21 century China is faced is asked
One of topic.Therefore sterol and its derivative are attracted extensive attention in food and pharmaceutical research field at present.Sterol and sterol ester are logical
Inhibition cholesterol is crossed in enteral absorption, total cholesterol in blood (TC) and low density lipoprotein cholesterol can be effectively reduced
(LDL-C) content, the content without reducing the high-density lipoprotein cholesterol (HDL-C) beneficial to human body.In pharmacy, life
The high-tech areas such as change, daily use chemicals, food and fine chemistry industry have broad application prospects.Common fat-soluble natural products inspection
Survey method has spectrophotometry method, liquid phase method, but needs dedicated instrument, operates relatively cumbersome.
Nearest computer image processing technology is grown rapidly, and the quantitative analysis of image is feasible.Using ImageJ as representative
Image processing program be widely used in life science field, such as electrophoretic band quantitative analysis, cell count, institutional framework
Quantitative Treatment etc..ImageJ is the public sphere Java image processing program of NIH exploitation.It can have Java any
1.4 or more highest version virtual machine computer on as online applet or can download application program operation.Downloadable distribution
Version is suitable for Windows, Mac OS, Mac OS X and Linux.It can show, edit, and analyze, processing, save and print 8
Position, 16 and 32 bit images.It can read many picture formats, including TIFF, GIF, JPEG, BMP, DICOM, FITS and
"raw".It supports " storehouse ", a series of image of shared single windows.It is multithreading, therefore can be with other operations simultaneously
Row executes the time-consuming operation of such as image file reading etc.It can calculate the area and pixel primary system that user defines selection
Meter.It can measure distance and angle.It can create density histogram and line profile figure.It supports standard picture to handle function
Can, such as contrast operation sharpens, smoothly, edge detection and median filtering.It can carry out geometric transformation, such as scale, rotation and
Overturning.All analyses and processing function can use under any amplification coefficient.The program supports any number of window simultaneously
(image), is only limited by free memory.Spatial calibration can be used for providing the dimensional measurement of real world in millimeters.Also
It can carry out density or gamma calibration.ImageJ is designed using open architecture, provides scalability by java plug-in.It can be with
Customized acquisition, analysis and processing plug-in unit are developed using the built-in editing machine and Java compiler of ImageJ.What user write inserts
Part can solve substantially any image procossing or problem analysis.
The tlc analysis of natural products is a kind of common high efficiency technical, but traditional thin layer quantitative analysis needs are dedicated
Instrument, using inconvenience.Therefore newest quantitative analysis with computer means are based on, the thin layer for carrying out flavonoids polyphenol is quantitative
Image recognition detection can simplify operation, effectively widen use scope.Have at present and some has been lived using image recognition
Property component quantifying detection research.Such as application number 200510115774.X patent document, it discloses a kind of based on image procossing
The thin layer chromatography quantitative analysis method of technology, comprising steps of (1) takes pictures to form digital picture to sample lamellae is loaded with；(2) right
Shoot image preprocessing: lens distortion calibration filters out noise；(3) it is uniformly distributed using point sample, fore-and-aft distance equipartition principle determines
Control point；(4) according to control point interpolation method structural map as background；(5) background is removed from lens distortion calibration image, according to back
Scape normalizes pixel brightness；(6) (7) are split to thin layer image to integrate the area grayscale after segmentation, quantitatively
Analysis.But this method is only described the General Principle of image analysis, not can be used directly determining for specific natural products
Amount detection.The patent document of application number 201510163742.0 discloses a kind of this resistance to sugared content measuring method of Morinda officinalis, utilizes
Trapezoidal integration integrates chromatographic peak, carries out quantitative analysis according to peak area and sample concentration.But this method is only limitted to one
The measurement of kind specific sugar.The patent document of application number 201810451846.5 discloses a kind of method for identifying honey authenticity, uses
ImageJ software analyzes the oligosaccharides in honey sample.But this method is only limitted to the analysis of a kind of sugar.Therefore it develops and is applicable in
In different types of thin layer image recognition quantitative analysis method, there is important meaning for the quick analysis and identification of natural products
Justice.
Summary of the invention
The present invention provides a kind of fat-soluble natural products thin layer quantitative image recognition detection method and process simplicity, do not need
Special instrument, it is widely applicable.
A kind of fat-soluble natural products thin layer quantitative image recognition detection method, comprising:
(1) sample to be tested containing fat-soluble natural products carries out point sample on chromatographic sheet；
(2) Development of Thin-Layer Chromatography is carried out to the chromatographic sheet after point sample using petrol ether/ethyl acetate solvent system；
(3) it is developed the color using coloring agent system to the chromatographic sheet after expansion；
(4) to fat-soluble natural products thin-layer chromatography image electronization and quantitative analysis: to the chromatographic sheet after colour developing
It carries out Image Acquisition and the content of water-soluble natural product is obtained according to the relationship between image and water-soluble natural product assay.
Fat-soluble natural products thin layer quantitative image recognition detection method of the invention is based on computer picture recognition,
It can be realized and Simultaneous Quantitative Analysis is carried out to different fat-soluble natural products (carotenoid, sterol) and its mixture.
Preferably, the sample to be tested containing fat-soluble natural products carries out point sample in the form of a solution, solution is dense
Degree is 0.01-10mg/mL；Further preferably 0.5-5mg/mL；Point sample amount is 0.1-10 microlitres；Preferably 0.1~1 microlitre.
It is described it is to be detected containing fat-soluble Natural Product Samples can use multi-solvents dissolution, generally using dissolubility it is preferable, Yi Hui
The solvent of hair, preferably, the solvent is one in n-hexane, ethyl alcohol, methylene chloride, acetone, methanol or ethyl acetate etc.
Kind is a variety of.As further preferred, the solvent is one of n-hexane or ethyl acetate or a variety of.
It is unfolded in unified solvent system after the fat-soluble Natural Product Samples point sample to thin-layer chromatography, as excellent
Choosing, the volume ratio of the petrol ether/ethyl acetate are 4~6/1.As further preferred, the body of the petrol ether/ethyl acetate
Product is than being 5/1.
Preferably, carrying out thin layer color to the chromatographic sheet after point sample using petrol ether/ethyl acetate solvent system
The distance of spectral expansion is 35~45 millimeters.As further preferred, development distance is 40 millimeters.In the present invention, the thin layer color
The distance of spectral expansion be using initial point sample central point as starting point, be unfolded using solvent after front end solvent line indicated as terminal
Distance.Certainly, for system is specifically unfolded, can also by control duration of run to two kinds be unfolded systems expansion act on into
Row control.
Preferably, using P-methoxybenzal-dehyde after the fat-soluble Natural Product Samples are unfolded on thin-layer chromatography
Color developing agent develops the color, and developing time 0.1-10 minutes, colour temp 150-250 degree.
Preferably, the coloring agent system is P-methoxybenzal-dehyde color developing agent.
Preferably, the volume ratio group of the P-methoxybenzal-dehyde color developing agent becomes methoxybenzaldehyde/acetic acid/second
Alcohol/sulfuric acid=9.1~9.5/3.5~4/300~350/12.5.As further preferred, the methoxybenzaldehyde/acetic acid/
Ethyl alcohol/sulfuric acid volume ratio is 9.2/3.75/338/12.5.
Preferably, the fat-soluble natural products includes one of carotenoid, sterol or a variety of.It is further excellent
It is selected as one of beta carotene, capsorubin, cupreol, stigmasterol or a variety of.
Preferably, carrying out Image Acquisition using camera or scanner.
After the completion of colour developing, camera can be used or scanner carries out electronic Image Acquisition, complete water-soluble natural product sample
The electronization of product image.After the fat-soluble Natural Product Samples image electronic, suitable image processing software is selected,
Such as: ImageJ carries out image optimization processing.Quantitative analysis is based on gray value, therefore first converts picture into gray scale picture with software.
The image of acquisition is handled using ImageJ, and finally carries out integrating quantitatively, is contained using integrated value and sample
Relationship between amount obtains the concentration of the sample to be tested containing fat-soluble natural products.
It includes denoising that the fat-soluble Natural Product Samples image optimization, which is handled, smooth.To above-mentioned gray scale picture into
Row removes salt-pepper noise, corrects, and sharpens edge, smoothly waits sequence of operations, makes picture more suitable for quantitative analysis.
After the fat-soluble Natural Product Samples image optimization processing, background removal is carried out.Suitable algorithm is selected, it will
Jamming pattern removes in image to be analyzed.
After the fat-soluble Natural Product Samples image background removal, integrate quantitatively, obtain quantitative result.
For carrying out image procossing using ImageJ software, process are as follows:
After the fat-soluble Natural Product Samples develop the color on thin-layer chromatography, electronics is carried out using HP M1005 scanner
Change Image Acquisition, parameters setting are as follows: million kinds of color outputs, resolution ratio 300dpi, brightness and contrast's default value, picture
It is saved with tiff format.
After the fat-soluble Natural Product Samples image electronic, image optimization processing is carried out using ImageJ software.
Firstly, quantitative analysis is based on gray value, therefore start ImageJ software, " Image "-" Type "-" 8-bit " is first selected, by picture
It is converted into gray scale picture, " Image "-" Adjust "-" Brightness/Contrast... " is then selected, in the dialogue of pop-up
" Auto " is clicked in frame, picture contrast and lightness is adjusted, keeps area visualization degree to be analyzed higher.
Secondly, carrying out noise reduction and smooth etc. reason to gray level image, first " Process "-" Noise "-is selected
" Despeckle ", by a median filter by each pixel in image replace with the intermediate value of pixel in its 3*3 neighborhood with
The salt-pepper noise in image is removed, deviation is more than to set by reselection " Process "-" Noise "-" RemoveOutliers... "
The pixel for determining threshold value replaces with the median of surrounding pixel to correct image；Then reselection " Process "-" Filters "-
" Unsharp Mask... " extracts blurry versions to sharpen and enhance image border；Finally select " Process "-" Smooth "
Smooth whole image is so that integral baseline is more steady.
Then, after fat-soluble Natural Product Samples image optimization processing, background is carried out using ImageJ software and is gone
It removes.It selects " Process "-" SubtractBackground... ", based on " Rollingball " algorithm in ImageJ, is popping up
Dialog box in give suitable ball radius, and choose " Lightbackground " and " Slidingparaboloid ", will
Continuous background in image removes.
After the fat-soluble Natural Product Samples image background removal, integrate quantitatively using ImageJ software, obtain
To quantitative result." RectangularSelectionTool " selection target region is clicked, " Ctrl+1 " is clicked and determines band, point
It hits " Ctrl+3 " to be integrated, be connected peak both ends with " StraightLine SelectionTool " after forming closed figure,
Peak area is determined with " wandtool ", completes quantitative analysis.
The common chromatographic sheet of various specifications can be used in the present invention, preferably, standard curve with it is actually detected
Chromatographic sheet used is identical.
Preferably, the standard curve between building sample size and integrated value in advance, when detection, according to obtained integral
Value and the standard curve obtain the concentration of the sample to be tested containing water-soluble natural product.
The present invention carry out quantitative analysis when, can construct in advance integrated value (for ImageJ be peak area) with sample size it
Between standard curve then after obtaining integrated value, the content of sample can be directly obtained, i.e. realization sample to be tested is determined
Quantization.
A kind of method of specific production standard curve is as follows:
(i) taking setting concentration (for example can be 1.0,2.0,3.0mg/L, can be multiple groups) setting volume (can be 0.5
Microlitre) standard sample, point sample is carried out on chromatographic sheet；
(ii) thin-layer chromatography is carried out step by step to the chromatographic sheet after point sample using petrol ether/ethyl acetate solvent system
Expansion；
(iii) it is developed the color using coloring agent system to the chromatographic sheet after expansion；
(iv) Image Acquisition is carried out to the chromatographic sheet after colour developing, obtains integrated value；
(v) according to step (i)~(iv) method, the corresponding integrated value of multiple groups standard sample is obtained, makes sample concentration
Standard curve between integrated value.
Petrol ether/ethyl acetate solvent system uses and development system used in detection process.That is, the petroleum
Ether/ethyl acetate volume ratio is 4~6/1.As further preferred, the volume ratio of the petrol ether/ethyl acetate is 5/1.
Development distance also selects numerical value identical with development distance used in detection process, can be one between 35~45 millimeters
Value.
Preferably, development distance is identical as actually detected development distance in the process, the point of use when building standard curve
Batten part, color condition and Image Acquisition and treatment conditions with it is consistent in detection process.
The present invention can be used for the detection of single component sample, can be used for the detection of mixed composition sample, be used for
When the detection of mixed composition sample, the Image Acquisition to each component sample spot is realized respectively using image acquisition units, then
Calculate separately the concentration value of sample.Certainly, using the present invention, we can also once realize the detection of multiple samples, when detection,
Multiple samples can be subjected to point sample on the same chromatographic sheet, then carry out Image Acquisition and calculating respectively.
As shown in Figure 1, for five concentration, successively raised sample uses method of the invention to be detected, i.e., by sample
Point sample position on point sample to same chromatographic sheet respectively, as long as distance can be avoided interference between each other；Then it opens up
It opens, develops the color, be then scanned using computer scanning instrument, read the corresponding image of each sample respectively, integrated,
The concentration value of counter sample is finally obtained, testing result is suitable with individually detection, almost without interference effect.
The present invention has the advantages that compared with existing detection method
(1) method of the invention is easy to operate, does not need special instrument.
(2) method of the invention is quantitative good, using same expansion system, can carry out to a variety of fat-soluble natural products
Quantitative detection, accuracy are high.
(3) method test speed of the invention is fast, can be measured simultaneously with multiple samples；Simultaneously can also to contain multiple groups
The sample of part is detected, practical.
Detailed description of the invention
Fig. 1 is for five concentration procedure chart that successively raised sample uses method of the invention to be detected.
Specific embodiment
Below with reference to embodiment, the present invention is described in further detail, and embodiments of the present invention are not limited thereto.
Color developing agent used in the examples is P-methoxybenzal-dehyde coloring agent, consisting of P-methoxybenzal-dehyde/second
Acid/ethyl alcohol/sulfuric acid (9.2/3.75/338/12.5, v/v/v/v).
Standard curve is made first, the method is as follows:
(i) standard sample for taking setting concentration, it is enterprising in chromatographic sheet (using the same chromatographic sheet of embodiment 1)
Row point sample；In the present embodiment, using 0.5,1.0,2.0,3.0,4.0mg/L five group of standard sample, solvent is n-hexane, point sample body
Product is 0.5 microlitre；
(ii) after dry, thin layer color is carried out to the chromatographic sheet after point sample using petrol ether/ethyl acetate (5/1, v/v)
Spectral expansion；Development distance is 20 millimeters, is then dried；
(iii) it is developed the color using P-methoxybenzal-dehyde coloring agent to the chromatographic sheet after expansion: 250 DEG C of warm tables
Heating develops the color for 15 seconds；
(iv) it is scanned after thin layer colour developing with computer scanner, resolution ratio is set as 300dpi.Scan obtained figure
Picture carries out denoising, smoothing processing with ImageJ, then removes background, finally carries out quantitative integration, respectively obtains 0.5,1.0,
2.0,3.0,4.0mg/L five groups of corresponding integrated values of standard sample；
(v) standard curve between sample concentration and integrated value is made.
For the accuracy of detection, for every group of standard sample, Parallel testing three times, takes the average value of integrated value right for its
The integrated value answered.
For the sample of different component, it is required to carry out the drafting of standard curve according to the method described above.
After sample colour developing during production standard curve and in embodiment, subsequent image treatment process are as follows:
Electronic Image Acquisition, parameters setting are carried out to the chromatographic sheet after colour developing using HP M1005 scanner
Are as follows: the output of hundred million colors, resolution ratio 300dpi, brightness and contrast's default value, picture are saved with tiff format.
Image optimization processing is carried out using ImageJ software.Firstly, quantitative analysis is based on gray value, therefore it is soft to start ImageJ
Part first selects " Image "-" Type "-" 8-bit ", picture is converted into gray scale picture, then selects " Image "-
" Adjust "-" Brightness/Contrast... ", in the dialog box of pop-up click " Auto ", adjustment picture contrast and
Lightness keeps area visualization degree to be analyzed higher.
Secondly, carrying out noise reduction and smooth etc. reason to gray level image, first " Process "-" Noise "-is selected
" Despeckle ", by a median filter by each pixel in image replace with the intermediate value of pixel in its 3*3 neighborhood with
The salt-pepper noise in image is removed, deviation is more than to set by reselection " Process "-" Noise "-" RemoveOutliers... "
The pixel for determining threshold value replaces with the median of surrounding pixel to correct image；Then reselection " Process "-" Filters "-
" Unsharp Mask... " extracts blurry versions to sharpen and enhance image border；Finally select " Process "-" Smooth "
Smooth whole image is so that integral baseline is more steady.
Then, background removal is carried out using ImageJ software.It selects " Process "-
" SubtractBackground... " is given in the dialog box of pop-up and is closed based on " Rollingball " algorithm in ImageJ
Suitable ball radius, and " Lightbackground " and " Slidingparaboloid " are chosen, by the continuous background in image
It removes.
After image background removal, integrate quantitatively using ImageJ software, obtain quantitative result.It clicks
" RectangularSelectionTool " selection target region clicks " Ctrl+1 " and determines band, clicks " Ctrl+3 " and carries out
Integral is connected peak both ends with " StraightLine SelectionTool " after forming closed figure, true with " wandtool "
Determine peak area, obtains corresponding integrated value.
Embodiment 1
By beta carotene hexane solution, with 0.5 microlitre of capillary point sample to thin-layer chromatography after solvent volatilizes, merging
Petroleum ether: 40 millimeters of length is expanded in ethyl acetate (5:1) solvent.It then takes out and is contaminated after solvent volatilizes with anisaldehyde
Toner dyeing is placed into 250 DEG C of warm tables and heats 15 seconds and develops the color.It is scanned after thin layer colour developing with computer scanner,
Resolution ratio is set as 300dpi.It scans obtained image and carries out denoising, smoothing processing with ImageJ, then remove background, most
After carry out quantitative integration, integrated value compared with standard value by obtaining measurement result.Actual value is β-carrot of 1.50mg/mL
Plain solution, measured value 1.58mg/mL, error 5%.
The chromatographic sheet of use is purchased from market, and specification (silica gel material, coating layer thickness: 0.2-0.25 millimeters, silica white
Granularity: 10-40 microns).
Embodiment 2
By capsorubin ethyl acetate solution, with 0.5 microlitre of capillary point sample to thin-layer chromatography after solvent volatilizes, merging
Petroleum ether: 40 millimeters of length is expanded in ethyl acetate (5:1) solvent.It then takes out and is contaminated after solvent volatilizes with anisaldehyde
Toner dyeing is placed into 250 DEG C of warm tables and heats 15 seconds and develops the color.It is scanned after thin layer colour developing with computer scanner,
Resolution ratio is set as 300dpi.It scans obtained image and carries out denoising, smoothing processing with ImageJ, then remove background, most
After carry out quantitative integration, integrated value compared with standard value by obtaining measurement result.Actual value is 1.50mg/mL by Quercetin
Ethanol solution, measured value 1.59mg/mL, error 6%.
Embodiment 3
By cupreol hexane solution, with 0.5 microlitre of capillary point sample to thin-layer chromatography after solvent volatilizes, be placed in stone
Oily ether: 40 millimeters of length is expanded in ethyl acetate (5:1) solvent.It then takes out and is dyed after solvent volatilizes with anisaldehyde
Agent dyeing is placed into 250 DEG C of warm tables and heats 15 seconds and develops the color.It is scanned after thin layer colour developing with computer scanner, point
Resolution is set as 300dpi.It scans obtained image and carries out denoising, smoothing processing with ImageJ, then remove background, finally
Quantitative integration is carried out, integrated value compared with standard value by obtaining measurement result.Actual value is that the cupreol of 1.50mg/mL is molten
Liquid, measured value 1.53mg/mL, error 2%.
Embodiment 4
By stigmasterol ethyl acetate solution, with 0.5 microlitre of capillary point sample to thin-layer chromatography after solvent volatilizes, be placed in stone
Oily ether: 40 millimeters of length is expanded in ethyl acetate (5:1) solvent.It then takes out and is dyed after solvent volatilizes with anisaldehyde
Agent dyeing is placed into 250 DEG C of warm tables and heats 15 seconds and develops the color.It is scanned after thin layer colour developing with computer scanner, point
Resolution is set as 300dpi.It scans obtained image and carries out denoising, smoothing processing with ImageJ, then remove background, finally
Quantitative integration is carried out, integrated value compared with standard value by obtaining measurement result.Actual value is the stigmasterol acetic acid of 2.10mg/mL
Ethyl ester solution, measured value 2.14mg/mL, error 2%.
Embodiment 5
Beta carotene, capsorubin, cupreol hexane solution (actual content are as follows: beta carotene: 1.31%,
Capsorubin: 1.42%, cupreol: 2.25%), and with 0.5 microlitre of capillary point sample to thin-layer chromatography after solvent volatilizes, use
Petroleum ether: 40 millimeters of length is expanded in ethyl acetate (5:1) solvent.It then takes out after solvent volatilizes with to methoxyl group
Benzaldehyde staining reagent is placed into 250 DEG C of warm tables and heats 15 seconds and develops the color.Thin layer colour developing after with computer scanner into
Row scanning, resolution ratio are set as 300dpi.It scans obtained image and carries out denoising, smoothing processing with ImageJ, then remove
Background finally carries out quantitative integration, and integrated value compared with standard value by obtaining measurement result.Error is 3-5%.
Claims (10)
1. a kind of fat-soluble natural products thin layer quantitative image recognition detection method characterized by comprising
(1) sample to be tested containing fat-soluble natural products carries out point sample on chromatographic sheet；
(2) Development of Thin-Layer Chromatography is carried out to the chromatographic sheet after point sample using petrol ether/ethyl acetate solvent system；
(3) it is developed the color using coloring agent system to the chromatographic sheet after expansion；
(4) Image Acquisition is carried out to the chromatographic sheet after colour developing, according to the pass between image and water-soluble natural product assay
System, obtains the content of water-soluble natural product.
2. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that institute
It states the sample to be tested containing fat-soluble natural products and carries out point sample, solution concentration 0.01-10mg/mL, point in the form of a solution
Sample amount is 0.1-10 microlitres.
3. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that institute
The volume ratio for stating petrol ether/ethyl acetate is (4~6)/1.
4. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that benefit
It is 35~45 with the distance that petrol ether/ethyl acetate solvent system carries out Development of Thin-Layer Chromatography to the chromatographic sheet after point sample
Millimeter.
5. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that institute
Stating coloring agent system is P-methoxybenzal-dehyde color developing agent.
6. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 5, which is characterized in that institute
The volume ratio group for stating P-methoxybenzal-dehyde color developing agent becomes methoxybenzaldehyde/acetic acid/ethyl alcohol/sulfuric acid=9.1~9.5/3.5
~4/300~350/12.5.
7. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that institute
Stating fat-soluble natural products includes one of carotenoid, sterol or a variety of.
8. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that benefit
Image Acquisition is carried out with camera or scanner.
9. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that right
The image of acquisition is handled using ImageJ, and finally carries out integrating quantitatively, utilizes the pass between integrated value and sample size
System, obtains the concentration of the sample to be tested containing water-soluble natural product.
10. fat-soluble natural products thin layer quantitative image recognition detection method according to claim 1, which is characterized in that
Standard curve between building sample size and integrated value in advance, when detection, according to obtained integrated value and the standard
Curve obtains the concentration of the sample to be tested containing water-soluble natural product.
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| CN111402347A (en) * | 2020-03-20 | 2020-07-10 | 吴刚 | New crown pneumonia epidemic situation prevention and control system based on Internet of things |
| CN113804592A (en) * | 2021-09-24 | 2021-12-17 | 中国石油化工股份有限公司 | Method for detecting gel particles in PAN spinning stock solution |
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