CN107271396A - The quick determination method of general flavone content in a kind of tealeaves - Google Patents
The quick determination method of general flavone content in a kind of tealeaves Download PDFInfo
- Publication number
- CN107271396A CN107271396A CN201710690728.5A CN201710690728A CN107271396A CN 107271396 A CN107271396 A CN 107271396A CN 201710690728 A CN201710690728 A CN 201710690728A CN 107271396 A CN107271396 A CN 107271396A
- Authority
- CN
- China
- Prior art keywords
- sample
- general flavone
- tealeaves
- spectrum
- tea samples
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 229930003944 flavone Natural products 0.000 title claims abstract description 61
- 235000011949 flavones Nutrition 0.000 title claims abstract description 61
- GAMYVSCDDLXAQW-AOIWZFSPSA-N Thermopsosid Natural products O(C)c1c(O)ccc(C=2Oc3c(c(O)cc(O[C@H]4[C@H](O)[C@@H](O)[C@H](O)[C@H](CO)O4)c3)C(=O)C=2)c1 GAMYVSCDDLXAQW-AOIWZFSPSA-N 0.000 title claims abstract description 60
- VHBFFQKBGNRLFZ-UHFFFAOYSA-N vitamin p Natural products O1C2=CC=CC=C2C(=O)C=C1C1=CC=CC=C1 VHBFFQKBGNRLFZ-UHFFFAOYSA-N 0.000 title claims abstract description 60
- 150000002212 flavone derivatives Chemical class 0.000 title claims abstract description 57
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000001228 spectrum Methods 0.000 claims abstract description 48
- 239000012141 concentrate Substances 0.000 claims abstract description 13
- 238000010183 spectrum analysis Methods 0.000 claims abstract description 11
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 7
- 238000012937 correction Methods 0.000 claims abstract description 5
- 238000009499 grossing Methods 0.000 claims abstract description 5
- 238000003672 processing method Methods 0.000 claims abstract description 5
- 230000003595 spectral effect Effects 0.000 claims description 17
- 241001122767 Theaceae Species 0.000 claims description 4
- 238000004811 liquid chromatography Methods 0.000 claims description 4
- 230000003287 optical effect Effects 0.000 claims description 4
- 238000001028 reflection method Methods 0.000 claims description 4
- 238000004587 chromatography analysis Methods 0.000 claims description 3
- 238000003306 harvesting Methods 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 238000000227 grinding Methods 0.000 claims description 2
- 239000007788 liquid Substances 0.000 claims description 2
- 238000004128 high performance liquid chromatography Methods 0.000 abstract description 8
- 238000001514 detection method Methods 0.000 abstract description 5
- 238000012360 testing method Methods 0.000 abstract description 4
- 238000002203 pretreatment Methods 0.000 abstract description 3
- 238000013178 mathematical model Methods 0.000 abstract description 2
- 238000011002 quantification Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 238000002329 infrared spectrum Methods 0.000 description 4
- -1 Flavone compound Chemical class 0.000 description 3
- 238000002790 cross-validation Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 208000024172 Cardiovascular disease Diseases 0.000 description 2
- 230000009471 action Effects 0.000 description 2
- 238000003556 assay Methods 0.000 description 2
- HVYWMOMLDIMFJA-DPAQBDIFSA-N cholesterol Chemical compound C1C=C2C[C@@H](O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2 HVYWMOMLDIMFJA-DPAQBDIFSA-N 0.000 description 2
- 238000004737 colorimetric analysis Methods 0.000 description 2
- 230000000144 pharmacologic effect Effects 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000002798 spectrophotometry method Methods 0.000 description 2
- 206010028980 Neoplasm Diseases 0.000 description 1
- KEAYESYHFKHZAL-UHFFFAOYSA-N Sodium Chemical compound [Na] KEAYESYHFKHZAL-UHFFFAOYSA-N 0.000 description 1
- 230000001093 anti-cancer Effects 0.000 description 1
- 239000003963 antioxidant agent Substances 0.000 description 1
- 230000003078 antioxidant effect Effects 0.000 description 1
- 235000006708 antioxidants Nutrition 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000036772 blood pressure Effects 0.000 description 1
- 201000011510 cancer Diseases 0.000 description 1
- 208000026106 cerebrovascular disease Diseases 0.000 description 1
- 239000013043 chemical agent Substances 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 235000012000 cholesterol Nutrition 0.000 description 1
- 235000019504 cigarettes Nutrition 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000002526 effect on cardiovascular system Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000004438 eyesight Effects 0.000 description 1
- 150000002213 flavones Chemical class 0.000 description 1
- 235000013305 food Nutrition 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 239000004570 mortar (masonry) Substances 0.000 description 1
- 230000001473 noxious effect Effects 0.000 description 1
- 238000005502 peroxidation Methods 0.000 description 1
- 231100000614 poison Toxicity 0.000 description 1
- 231100000572 poisoning Toxicity 0.000 description 1
- 230000000607 poisoning effect Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 239000010453 quartz Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 239000003440 toxic substance Substances 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
- G01N2021/3572—Preparation of samples, e.g. salt matrices
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using FTIR
Landscapes
- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The quick determination method of general flavone content in a kind of tealeaves, it is related to the detection technique field of tealeaves general flavone content, including setting up model and detecting step, Calibration standard spectrum is imported by TQ Analyst spectral analysis softwares, and form general flavone value contrast in general flavone content, then each sample measured with high performance liquid chromatography in corresponding correcting sample concentration each sample.The present invention first concentrates the spectrum of each Tea Samples to lead correcting sample and pre-processed using first derivative+Norris derivative smoothings filter processing method, the Quantitative Analysis Model of general flavone in tealeaves is set up with the method for multiplicative scatter correction method and offset minimum binary, the model can fast quantification, quickly and accurately detect general flavone content in tealeaves.Directly detected, saved after cumbersome pre-treatment, Mathematical Models as former state using sample, the spectrogram that only need to scan testing sample with instrument can quickly obtain general flavone content in tealeaves.
Description
Technical field
The present invention relates to the detection technique field of tealeaves general flavone content, and in particular to detects tea with near-infrared spectrum technique
The technology of general flavone content in leaf.
Background technology
Flavone compound is widely distributed, and species is various.There is research to show that it is anti-in anti-oxidant, anti-lipid peroxidation
Should, effect is obvious in terms of prevention of cardiovascular disease, anti-cancer.
Tealeaves not only have refresh oneself clear away heart-fire, the pharmacological action such as clearing away summerheat, removing toxic substances are sobered up, fall fire improving eyesight, moreover it is possible to mitigate and inhale
Murder by poisoning of the cigarette to health, there is reduction cholesterol and blood pressure, improves immunity.To cardiovascular and cerebrovascular diseases, cancer etc.,
There is certain pharmacological action.Flavones content in tealeaves relatively enriches.At present, for the research ratio of flavone compound in tealeaves
It is more, but have focused largely in the Study on extraction of tealeaves general flavone.
The assay method of flavone compound mainly has：Colorimetric method, ultraviolet spectrophotometry, high performance liquid chromatography etc..
Although colorimetric method method is simple, the natrium nitrosum used is noxious material；Ultraviolet spectrophotometry uses chromatography post separation,
Method is cumbersome, takes time and effort；High performance liquid chromatography sensitivity is high, but needs chemical agent to extract, and is not suitable for quick
On-line checking.
Near-infrared spectrum technique be it is a kind of it is easy to use, analysis is quick, do not destroy the new technique of sample, it is not necessary to
Sample is chemically treated, is the new analytical technology of safe green.NIR technology can determine sample simultaneously
In a variety of chemical compositions and physical parameter, analysis result can accurately approach traditional assay method.
At present, NIR technology has become a kind of efficient analysis method, is widely used in oil, chemistry, system
The industry-by-industries such as medicine, agricultural, food.
The content of the invention
In order to which the content to general flavone in tealeaves realizes simple, quick, pollution-free, safe and reliable detection, the present invention is carried
Go out a kind of method of general flavone content in non-destructive prediction tealeaves based on near-infrared spectrum technique.
The present invention includes setting up model and detecting step.
Set up model step as follows：
1）The Tea Samples of 20~80 parts of different cultivars, different water content in harvest and different manufacture crafts are taken, again will after grinding respectively
Two parts are divided into per portion sample, standard sample collection Tea Samples and Calibration tealeaves sample for setting up model are obtained
Product；
2）High effective liquid chromatography for measuring is respectively adopted in the Tea Samples that standard sample is concentrated, and obtains standard sample and concentrates each tea
The standard value of the general flavone content of leaf sample；
3）Adopt and make Antaris Fourier Transform Near Infrared instruments, using integrating sphere diffusing reflection method to Calibration tealeaves
Sample carries out spectral scan respectively, obtains the spectrum that correcting sample concentrates each Tea Samples；
4）The spectrum of each Tea Samples in Calibration is imported in TQ Analyst spectral analysis softwares, and by efficient liquid
The standard sample that phase chromatography is measured concentrates the standard value of the general flavone content of each Tea Samples and correcting sample to concentrate each tealeaves
The spectrum of sample is corresponded in input TQ Analyst spectral analysis softwares, using first derivative+Norris derivative smoothings
Filter processing method is first concentrated the spectrum of each Tea Samples to lead correcting sample and pre-processed, then using multiplicative scatter correction method
The Quantitative Analysis Model of general flavone in tealeaves is set up with the method for offset minimum binary.
Detecting step is as follows：
1）It is placed in after Tea Samples to be measured are ground in Antaris Fourier Transform Near Infrared instruments, it is unrestrained anti-using integrating sphere
Shooting method, uses Result spectral scan software collection spectrum, the cm of scanning optical spectrum scope 10000-1~4000 cm-1, setting
The cm of resolution ratio 8-1, after background scans, spectrum is carried out to Tea Samples scanning times 64 times, the x of optimized gain 4, rotary sample cup
Scanning, obtains Tea Samples spectrum to be measured；
2）The Quantitative Analysis Model of general flavone in above-mentioned tealeaves is called, is clicked in TQ Analyst spectral analysis software toolbars
Quantity buttons, select the Tea Samples spectrum to be measured in the spectrum dialog box of ejection, through TQ Analyst spectrum point
Software analysis is analysed, general flavone content in Tea Samples to be measured is produced.
In order to set up more objective model, the present invention when setting up model using many parts of different Tea Samples, can be with
Obtain more preferably, more fully spectral information, then by TQ Analyst spectral analysis softwares by Calibration standard spectrum
Import, and obtain corresponding correcting sample and concentrate general flavone content in each sample, measured again with high performance liquid chromatography with this
General flavone value is contrasted one by one in each sample.The present invention uses first derivative+Norris derivative smoothing filter processing methods
First concentrate the spectrum of each Tea Samples to lead correcting sample to pre-process, then using multiplicative scatter correction method and offset minimum binary
Method set up the Quantitative Analysis Model of general flavone in tealeaves, the model can fast quantification, quickly and accurately detect in tealeaves
General flavone content.Directly detected, saved after cumbersome pre-treatment, Mathematical Models as former state using sample, need to only swept with instrument
General flavone content in tealeaves, only 0.1 hour used time can be analyzed by retouching the spectrogram of testing sample.With without calculate, need not
Sample pre-treatments, the spy high, reproducible without any chemical reagent, stable quick, environmental protection, easily operated, accuracy rate
Point.
Brief description of the drawings
Fig. 1 is the atlas of near infrared spectra of tealeaves.
Fig. 2 is the predicted value of tealeaves general flavone content and the relationship model figure of standard value.
Fig. 3 is the predicted value of the cross-validation of tealeaves general flavone content and the relationship model figure of standard value.
Fig. 4 is the external certificate predicted value of tealeaves general flavone content and the relationship model figure of standard value.
Embodiment
Present invention is described in detail with reference to Figure of description：Accompanying drawing is only provided to be used with reference to explanation, non-
To limit the present invention.
First, the preparation of Tea Samples：
Different cultivars is collected, different water content in harvest, 45 parts of the Tea Samples of different manufacture crafts take every part of Tea Samples accurately to claim
5 g are taken, and is respectively placed in mortar and grinds, it is standby.
2nd, the preparation of Calibration and standard sample collection：
5 parts of Tea Samples are arbitrarily chosen from the 45 parts of Tea Samples ground, A, B, C, D, E is respectively labeled as.
Then Tea Samples A is divided into two parts, 2.5g/ parts, obtains A1, A2, by this method by Tea Samples B, C, D, E
Two parts are divided into, A1, A2, B1, B2, C1, C2, D1, D2, E1 and E2 is obtained, totally 10 parts of Tea Samples.
10 parts of Tea Samples are divided into two groups by more than：
One group is standard sample collection, is made up of A1, B1, C1, D1 and E1.
Another group is Calibration, is made up of A2, B2, C2, D2 and E2.
Remaining 40 parts of Tea Samples are also divided into two parts respectively by the above process again, so that 40 parts of Tea Samples are divided into
Standard sample collection for setting up model（It is made up of 40 parts of Tea Samples）And Calibration（It is made up of 40 parts of Tea Samples）.
3rd, model is set up：
1st, 40 parts of Tea Samples for concentrating standard sample, are respectively adopted high effective liquid chromatography for measuring and go out exact level, respectively
Obtain standard sample collection（It is made up of 40 parts of Tea Samples）General flavone content standard value.
2nd, the foundation of Calibration spectrum：
Adopt and make Antaris Fourier Transform Near Infrared instruments（Thermo Fisher companies of the U.S.）, use integrating sphere diffusing reflection
Method concentrates 40 parts of Tea Samples to carry out spectral scan respectively correcting sample.Wherein, 45 min of spectrometer start preheating, environment
Temperature is room temperature, and each Tea Samples are put in specimen cup, uses Result spectral scan softwares, scanning optical spectrum scope 10000
cm-1~4000 cm-1, setting resolution ratio 8cm-1, scanning times 64 times, the x of optimized gain 4, rotary sample cup.Background is carried out to sweep
After retouching, Tea Samples are carried out with spectral scan, every part of Tea Samples scan 3 times, the spectrum for measuring 3 times is averaged, 40 are obtained
Group Calibration standard spectrum.
3rd, the foundation of model：
40 groups of Calibration standard spectrums are imported in TQ Analyst spectral analysis softwares, and by high performance liquid chromatography
The 40 groups of general flavone content standard values measured are corresponded with sample spectra and inputted, using first derivative+Norris derivative smoothings
Filter processing method is first pre-processed to each group Calibration standard spectrum, then using multiplicative scatter correction method（MSC）With
Offset minimum binary（PLS）Method set up the Quantitative Analysis Model of general flavone in tealeaves.
Meanwhile, it is corresponding that TQ Analyst spectral analysis softwares also show 40 groups of Calibration standard spectrums of the above
The predicted value of general flavone in tealeaves.
10000 cm scanned in above Antaris Fourier Transform Near Infrared instruments-1~4000 cm-1Spectrum model
Interior different spectral regions are enclosed to be analyzed, it is as shown in the table.
Following table is influence contrast table of the selection of different spectrum ranges to parameter.
| Sequence number | Spectral region/cm-1 | The coefficient correlation of predicted value and standard value | Calibration set mean square deviation deviation | Main cause subnumber |
| 1 | 5395.85~5174.20 | 0.9686 | 0.174 | 4 |
| 2 | 5164.60~5005.78 | 0.9910 | 0.0856 | 5 |
| 3 | 4960.02~4562.54 | 0.9752 | 0.153 | 4 |
| 4 | 4491.79~4351.18 | 0.9464 | 0.223 | 6 |
| 5 | 4288.91~4296.71 | 0.8807 | 0.328 | 3 |
According to TQ Analyst spectral analysis softwares, when predicted value and the coefficient correlation of standard value（R）Closer to 1 when, then
The effect of the model prediction of foundation is better；And verify mean square deviation closer to 0 when, then the effect for the model prediction set up is better.
As seen from the above table：Optimized spectrum area is 5164.60 cm-1~5005.78 cm-1.Reject after the larger point of error, build
The predicted value of vertical model and the coefficient correlation of standard value（R）For 0.9910, calibration set mean square deviation deviation（RMSEC）For
0.0856, cross-validation mean square deviation（RMSECV）For 0.0929（As shown in Figure 3）, this PLS model can be used for quick, accurate
Prediction testing sample general flavone content.
The predicted value and standard value of general flavone content form Fig. 2 linear relationship chart in 40 pairs of Tea Samples by more than, by
Linear relationship number figure is drawn：The coefficient correlation of predicted value and standard value（R）For 0.9910.
4th, model testing：
The each sample that the standard sample being made up of 5 parts of Tea Samples is concentrated is respectively adopted high effective liquid chromatography for measuring and gone out accurately
Content, obtains the general flavone content standard value of 5 parts of Tea Samples, as a result as follows：
General flavone content is 2.45 % in A1 Tea Samples.
General flavone content is 2.64 % in B1 Tea Samples.
General flavone content is 2.83 % in C1 Tea Samples.
General flavone content is 3.04 % in D1 Tea Samples.
General flavone content is 3.49 % in E1 Tea Samples.
Above high performance liquid chromatography is 1 hour to the detection used time of general flavone content in each Tea Samples.
Adopt and make Antaris Fourier Transform Near Infrared instruments（Thermo Fisher companies of the U.S.）, it is unrestrained using integrating sphere
Method for reflection concentrates 5 parts of Tea Samples to correcting sample（A2, B2, C2, D2 and E2）Spectral scan is carried out respectively.Wherein, spectrum
Instrument start 45 min of preheating, environment temperature is room temperature, and each Tea Samples are put in specimen cup, soft using Result spectral scans
Part, the cm of scanning optical spectrum scope 10000-1~4000 cm-1, setting resolution ratio 8cm-1, scanning times 64 times, the x of optimized gain 4,
Rotary sample cup.Carry out after background scans, Tea Samples are carried out with spectral scan, every part of Tea Samples are scanned 3 times, will measure 3
Secondary spectrum is averaged, and obtains 5 groups of Calibration standard spectrums.
5 groups of Calibration standard spectrums are imported in TQ Analyst spectral analysis softwares, and by high performance liquid chromatography
5 groups of general flavone content standard values that method is measured are corresponded with sample spectra and inputted, and 5 groups of Calibration standard spectrums are set
For checking, you can obtain general flavone content in the corresponding Tea Samples of A2, B2, C2, D2 and E2 Tea Samples, then pass through TQ
Analyst spectral analysis softwares are analyzed, and obtain the outside crosscheck collection coefficient correlation of general flavone quantitative calibration models（R）
0.9939（As shown in Figure 4）, verify mean square deviation（RMSEP）For 0.0918.
Following table is predicted value and standard value contrast table of the model to general flavone content in verification sample：
| Sequence number | Standard value（%） | Predicted value（%） | Deviation（%） |
| A | 2.45 | 2.63 | 0.18 |
| B | 2.64 | 2.61 | 0.03 |
| C | 2.83 | 2.85 | 0.02 |
| D | 3.04 | 3.16 | 0.12 |
| E | 3.49 | 3.49 | 0.00 |
As seen from the above table, the equal ＜ 0.20 of deviation of cross validation results, shows set up tea outside the model that this method is set up
General flavone content near-infrared quantitative model is accurate and effective in leaf.
5th, in unknown sample tealeaves general flavone content measure：
The g of Tea Samples 2.5 of unknown general flavone content is separately weighed, grinds and is placed in quartz specimen cup, be positioned over Fu Antaris
In in leaf transformation near infrared spectrometer, using integrating sphere diffusing reflection method, using Result spectral scan software collection spectrum, sweep
Retouch the cm of spectral region 10000-1~4000 cm-1, setting resolution ratio 8cm-1, scanning times 64 times, the x of optimized gain 4, rotation
Specimen cup.After background scans, spectral scan is carried out to Tea Samples, the Tea Samples spectrum letter of unknown general flavone content is obtained
Breath.
The model set up is recalled, the Quantity buttons in TQ Analyst spectral analysis software toolbars are clicked on,
The spectrum of this unknown sample is selected in the spectrum dialog box of ejection, Tea Samples spectral information to be measured is analyzed, you can
Obtain the analysis report of the sample general flavone content.
About 0.1 hour when the process is shared, it is significantly smaller than high performance liquid chromatography to general flavone content in each Tea Samples
Detection time.It can be seen that, the inventive method can the unknown Tea Samples of fast prediction general flavone content.
Claims (1)
1. the quick determination method of general flavone content in a kind of tealeaves, it is characterised in that：Including setting up model and detecting step；
Set up model step as follows：
1）The Tea Samples of 20~80 parts of different cultivars, different water content in harvest and different manufacture crafts are taken, again will after grinding respectively
Two parts are divided into per portion sample, standard sample collection Tea Samples and Calibration tealeaves sample for setting up model are obtained
Product；
2）High effective liquid chromatography for measuring is respectively adopted in the Tea Samples that standard sample is concentrated, and obtains standard sample and concentrates each tea
The standard value of the general flavone content of leaf sample；
3）Adopt and make Antaris Fourier Transform Near Infrared instruments, using integrating sphere diffusing reflection method to Calibration tealeaves
Sample carries out spectral scan respectively, obtains the spectrum that correcting sample concentrates each Tea Samples；
4）The spectrum of each Tea Samples in Calibration is imported in TQ Analyst spectral analysis softwares, and by efficient liquid
The standard sample that phase chromatography is measured concentrates the standard value of the general flavone content of each Tea Samples and correcting sample to concentrate each tealeaves
The spectrum of sample is corresponded in input TQ Analyst spectral analysis softwares, using first derivative+Norris derivative smoothings
Filter processing method is first concentrated the spectrum of each Tea Samples to lead correcting sample and pre-processed, then using multiplicative scatter correction method
The Quantitative Analysis Model of general flavone in tealeaves is set up with the method for offset minimum binary；
Detecting step is as follows：
1）It is placed in after Tea Samples to be measured are ground in Antaris Fourier Transform Near Infrared instruments, it is unrestrained anti-using integrating sphere
Shooting method, uses Result spectral scan software collection spectrum, the cm of scanning optical spectrum scope 10000-1~4000 cm-1, setting
The cm of resolution ratio 8-1, after background scans, spectrum is carried out to Tea Samples scanning times 64 times, the x of optimized gain 4, rotary sample cup
Scanning, obtains Tea Samples spectrum to be measured；
2）The Quantitative Analysis Model of general flavone in above-mentioned tealeaves is called, is clicked in TQ Analyst spectral analysis software toolbars
Quantity buttons, select the Tea Samples spectrum to be measured in the spectrum dialog box of ejection, through TQ Analyst spectrum point
Software analysis is analysed, general flavone content in Tea Samples to be measured is produced.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710690728.5A CN107271396A (en) | 2017-08-14 | 2017-08-14 | The quick determination method of general flavone content in a kind of tealeaves |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710690728.5A CN107271396A (en) | 2017-08-14 | 2017-08-14 | The quick determination method of general flavone content in a kind of tealeaves |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107271396A true CN107271396A (en) | 2017-10-20 |
Family
ID=60080336
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710690728.5A Withdrawn CN107271396A (en) | 2017-08-14 | 2017-08-14 | The quick determination method of general flavone content in a kind of tealeaves |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107271396A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111272696A (en) * | 2020-03-24 | 2020-06-12 | 山东大学 | Method for rapidly detecting essence doped in Pu' er tea |
| CN112946156A (en) * | 2021-03-10 | 2021-06-11 | 安徽农业大学 | Method for rapidly judging grade of black tea |
| CN114486798A (en) * | 2021-12-16 | 2022-05-13 | 皖西学院 | Method for rapidly predicting content of total flavonoids in fiddlehead |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103743703A (en) * | 2013-12-20 | 2014-04-23 | 贵州省分析测试研究院 | Method for detecting main components in tea leaves by adopting near infrared spectrum |
| CN105424640A (en) * | 2015-11-27 | 2016-03-23 | 浙江大学 | Method for detecting lead chrome green addition content of tea leaves |
| CN106323903A (en) * | 2015-06-26 | 2017-01-11 | 云南天士力帝泊洱生物茶集团有限公司 | Establishment and detection methods of infrared-spectroscopy fingerprint map of Pu'er tea extract |
| CN106568738A (en) * | 2016-10-31 | 2017-04-19 | 湖北省农业科学院果树茶叶研究所 | Method of using near infrared spectroscopy to rapidly determine fresh leaves of tea in different quality grades |
-
2017
- 2017-08-14 CN CN201710690728.5A patent/CN107271396A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103743703A (en) * | 2013-12-20 | 2014-04-23 | 贵州省分析测试研究院 | Method for detecting main components in tea leaves by adopting near infrared spectrum |
| CN106323903A (en) * | 2015-06-26 | 2017-01-11 | 云南天士力帝泊洱生物茶集团有限公司 | Establishment and detection methods of infrared-spectroscopy fingerprint map of Pu'er tea extract |
| CN105424640A (en) * | 2015-11-27 | 2016-03-23 | 浙江大学 | Method for detecting lead chrome green addition content of tea leaves |
| CN106568738A (en) * | 2016-10-31 | 2017-04-19 | 湖北省农业科学院果树茶叶研究所 | Method of using near infrared spectroscopy to rapidly determine fresh leaves of tea in different quality grades |
Non-Patent Citations (1)
| Title |
|---|
| 赵杰文等: "近红外光谱法快速检测绿茶中儿茶素的含量", 《光学学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111272696A (en) * | 2020-03-24 | 2020-06-12 | 山东大学 | Method for rapidly detecting essence doped in Pu' er tea |
| CN112946156A (en) * | 2021-03-10 | 2021-06-11 | 安徽农业大学 | Method for rapidly judging grade of black tea |
| CN114486798A (en) * | 2021-12-16 | 2022-05-13 | 皖西学院 | Method for rapidly predicting content of total flavonoids in fiddlehead |
| CN114486798B (en) * | 2021-12-16 | 2024-03-26 | 皖西学院 | Method for rapidly predicting total flavone content in pteridium aquilinum |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103776777B (en) | Method for identifying ginsengs with different growth patterns by using near infrared spectrum technology and determining content of components in ginsengs | |
| Meng et al. | Discrimination and content analysis of fritillaria using near infrared spectroscopy | |
| CN101493431A (en) | Method for detecting fresh degree of chicken meat by electronic nose | |
| CN107271396A (en) | The quick determination method of general flavone content in a kind of tealeaves | |
| CN105352913B (en) | A kind of method of near infrared spectrum detection Ganodenna Lucidum P.E polyoses content | |
| CN109490246A (en) | A kind of rapid detection method of root of purple-flowered peucedanum quality of medicinal material | |
| CN108107019A (en) | A kind of method that versicolorin content in corn is quickly detected based near infrared spectroscopy | |
| CN105092513A (en) | Method for determining content of drug components in mixture drug | |
| CN104596979A (en) | Method for measuring cellulose of reconstituted tobacco by virtue of near infrared reflectance spectroscopy technique | |
| Chen et al. | Rapid identification of three varieties of Chrysanthemum with near infrared spectroscopy | |
| CN112666119A (en) | Method and system for detecting ginseng tract geology based on terahertz time-domain spectroscopy | |
| CN108593863A (en) | A kind of online test method in extraction of traditional Chinese medicine and device | |
| Chen et al. | Two-dimensional correlation spectroscopy reveals the underlying compositions for FT-NIR identification of the medicinal bulbs of the genus Fritillaria | |
| Chen et al. | Determination of marker constituents in radix Glycyrrhizae and radix Notoginseng by near infrared spectroscopy | |
| CN113960241A (en) | Method for rapidly screening illegal addition of prohibited chemicals in health care products based on thin-layer chromatography-near infrared spectrum coupling technology | |
| P Guo et al. | Application of near-infrared spectroscopy (NIRS) as a tool for quality control in traditional Chinese medicine (TCM) | |
| CN109030410B (en) | Construction method of royal jelly near-infrared quantitative correction model and royal jelly detection method | |
| Yang et al. | Determination of total flavonoids for Paris polyphylla var. yunnanensis in different geographical origins using UV and FT-IR spectroscopy | |
| CN101308120A (en) | Cigar flavour quality control method | |
| CN109738391B (en) | Method for evaluating quality of dried ginger medicinal material based on near infrared spectrum technology | |
| CN109342355A (en) | The construction method of neck waist recovering capsule near-infrared quantitative calibration models and the detection method of neck waist recovering capsule | |
| CN102106888A (en) | Quality control method for extraction process of Chinese medicine ainsliaea fragrans champ | |
| CN105466878B (en) | A method of utilizing lycopene in infrared spectrum measurement catsup | |
| CN104535527B (en) | Method for monitoring quercetin in extraction process of folium ginkgo in real time by applying near-infrared technology | |
| CN108693140A (en) | A kind of method of muskone content in quick detection Xingnaojing oral preparation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20171020 |