CN108490016A - A kind of discrimination method of spina date seed and Yunnan jujube kernel - Google Patents
A kind of discrimination method of spina date seed and Yunnan jujube kernel Download PDFInfo
- Publication number
- CN108490016A CN108490016A CN201810121226.5A CN201810121226A CN108490016A CN 108490016 A CN108490016 A CN 108490016A CN 201810121226 A CN201810121226 A CN 201810121226A CN 108490016 A CN108490016 A CN 108490016A
- Authority
- CN
- China
- Prior art keywords
- yunnan
- spina date
- date seed
- jujube kernel
- sample
- 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.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N24/00—Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects
- G01N24/08—Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects by using nuclear magnetic resonance
Landscapes
- Physics & Mathematics (AREA)
- High Energy & Nuclear 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)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The present invention provides a kind of methods differentiating spina date seed and Yunnan jujube kernel based on hydrogen nuclear magnetic resonance combination Partial Least Squares.This method is built first differentiates model, then predicts discriminating model, then differentiate to unknown sample.Discrimination method provided by the invention not only can effectively distinguish spina date seed and Yunnan jujube kernel, but also can be used for mixing the discriminating of pseudo- sample, and general routine experimentation technical staff can accurately differentiate spina date seed and Yunnan jujube kernel using this method.
Description
Technical field
The present invention relates to medicinal material true and false authentication techniques, particularly belong to a kind of discrimination method of spina date seed and Yunnan jujube kernel.
Background technology
Spina date seed is rhamnaceae plant wild jujube Ziziphus jujuba Mill.var Spinosa (Bunge) Hu ex
The dry mature seed of H.F.Chou.First recorded in《Sheng Nong's herbal classic》, say that " main trusted subordinate's fever and chills, heresy knot gas is poly-, and painful limbs are wet
Numbness, long term usage peace five are hidden, macrobiosis of making light of one's life by commiting suicide ".《Compendium of Materia Medica》Once it records " master is vexatious to sleep ".2015 editions《Chinese Pharmacopoeia》To its work(
It can cure mainly and be described as that " nourishing heart tonifying liver, antitoxic heart-soothing and sedative, arrest sweating promote the production of body fluid.For restlessness of asrhenia type and insomnia, horrified to much dream, body void hidrosis, Tianjin wound
It is thirsty ".Its sedative-hypnotic effect Small side effects than stable more longlasting, steady.In recent years, as rhythm of life is accelerated, people
Study, work and family pressure continue to increase, and the incidence of insomnia also rises year by year.Spina date seed is that traditional Chinese medicine mental-tranquilization is preferred
Drug, application range are related to from single medication and composition of prescription treatment insomnia, to fields such as Chinese patent drug raw materials.Clinical demand
Amount is big, causes price soaring, adulterant and to mix pseudo- phenomenon serious.Most common adulterant is to exactly like the root of Roundfruit Licorice Yunnan of spina date seed
The mature seed of jujube Ziziphus mauritiana Lam. is pierced, practises and claiming " Yunnan jujube kernel ", " reason jujube kernel " and " remote jujube kernel ".Spina date seed
It is similar with Yunnan jujube kernel size, shape, but have certain difference on texture and color.Spina date seed is in oblate or flat ellipse,
There is the lira of a microprotrusion in centre, and smooth surface is glossy, is purplish red or puce.Yunnan jujube kernel is in oblateness, no ordinate
Line, smooth gloss are brown color.There is certain difference in spina date seed, veteran can pass through wild jujube with Yunnan jujube kernel in shape
Benevolence appearance character, as color, shape, length, width and thickness distinguish itself and adulterant Yunnan jujube kernel.But area is difficult to after pulverizing medicinal materials
Divide spina date seed and Yunnan jujube kernel.
Someone studies the discrimination method of spina date seed and Yunnan jujube kernel in recent years, but there is certain limitation.Such as
Character discriminating is only used for the unbroken medicinal material of appearance;Microscopical characters, physics and chemistry discriminating, thin-layer chromatography, ultraviolet spectra, infrared light
Though spectrum, HPLC-ELSD, high performance capillary electrophoresis, UPLC-QTOF/MS, DNA fingerprinting can distinguish spina date seed and Yunnan jujube kernel,
It is not suitable for mixing the discriminating of sample after pseudo- Yunnan jujube kernel.
Invention content
The purpose of the present invention is to provide a kind of method differentiating spina date seed and Yunnan jujube kernel, this method simultaneously can be used for acid
The discriminating of sample after pseudo- Yunnan jujube kernel is mixed in jujube kernel.
In order to achieve the above object, the present invention provides a kind of discrimination method of spina date seed and Yunnan jujube kernel, includes the following steps:
(1) spina date seed and Yunnan each 0.2g of jujube kernel powder are weighed respectively, are respectively placed in 10mL centrifuge tubes, are added distilled water and first
Alcohol each 1.5mL, chloroform 3mL, whirlpool mixing 1min, ultrasonic extraction 25min are extracted after centrifuging (3500r/min) 25min at room temperature
Liquid is divided into 2 layers up and down, and upper layer is methanol water phase, and lower layer is chloroform phase, and methanol-water is mutually moved in round-bottomed flask, is concentrated under reduced pressure and steams
It is dry, obtain spina date seed and Yunnan jujube kernel extract;
(2) above two extract uses the heavy water buffer solution (containing 0.01%TSP) 400 of deuterated methanol 400 μ L and pH6 respectively
It is transferred in centrifuge tube after μ L dissolvings, 13000rpm centrifuges 10min, pipettes 600 μ L of supernatant respectively and is divided in nuclear magnetic tube
Analysis obtains spina date seed and Yunnan jujube kernel nuclear magnetic resonance spectroscopy;
(3) spina date seed and Yunnan jujube kernel nuclear magnetic resonance spectroscopy are imported into MestReNova softwares, baseline is carried out after being calibrated with TSP
Adjustment and phasing;Then with 0.01 section to chemical shift δH0.72~9.15 progress subsection integral, deletion δ H4.68~
Integrated value corresponding to 4.92 (remaining water peaks) and δ H 3.34~3.38 (residual methanol peak) section, the data after integral are led
Enter progress area normalization processing in excel;
(4) differentiate the foundation of model:
A. spina date seed and Yunnan jujube kernel sample are total to the data after N number of samples normalization import SIMCA-P13.0 softwares in into
Row Partial Least Squares (PLS) is analyzed;Spina date seed sample is assigned a value of 1, and Yunnan jujube kernel sample is assigned a value of 2;Normalizing will be passed through using PLS
The integral relative value data matrix (X variables) and class variable (Y variables) for changing processing carry out linear regression, obtain discrimination model;
B. PLS principles are based on, by leaving-one method (leave-one-out) to discrimination model in SIMCA-P13.0 softwares
In N number of class variable Y calculated;N samples are divided into 7 groups by system, if serial number divided by 7, the identical sample of gained remainder is
One group, the sample for not participating in modeling is calculated with the model of wherein 6 groups Sample Establishings every time;Obtain the actual value of PLS models
(observed) with predicted value (predicted), the prediction threshold value of spina date seed and Yunnan jujube kernel is determined, i.e., when predicted value P≤1.13
For spina date seed, P >=1.90 are Yunnan jujube kernel, are the sample that Yunnan jujube kernel is mixed in spina date seed between 1.13 < P < 1.90;
(5) differentiate unknown sample:
The method that unknown sample is pressed step (1)~(3), obtains intensity integration data, after normalization in steps for importing (4)
Discriminating model, obtain the predicted value P of class variable Y, when P≤1.13 be spina date seed, P >=1.90 be Yunnan jujube kernel, 1.13 < P <
1.90 be to mix adulterant.
Discrimination method provided by the invention not only can effectively distinguish spina date seed and Yunnan jujube kernel, but also can be used for mixing
The discriminating of pseudo- sample, general routine experimentation technical staff can accurately differentiate spina date seed and Yunnan jujube kernel using this method.
Description of the drawings
Fig. 1 spina date seed methanol water phases1H NMR figures
The Yunnan Fig. 2 jujube kernel methanol water phase1H NMR figures
Fig. 3 spina date seeds mix 40% Yunnan jujube kernel methanol water phase1H NMR figures
Specific implementation mode
Embodiment 1 differentiates the foundation of model
The spina date seed 18 batches of separate sources is collected, Yunnan jujube kernel 7 batches refers to table 1, table 2
1 separate sources spina date seed sample message of table
2 separate sources Yunnan jujube kernel sample message of table
1, instrument, reagent
Instrument:Nuclear Magnetic Resonance, Rotary Evaporators, Ultrasound Instrument and centrifuge.Heavy water, deuterated methanol, deuterochloroform, TSP,
Potassium dihydrogen phosphate, sodium hydroxide, methanol, chloroform and deionized water.
2, sample preparation:Sample powder 0.2g is weighed, is placed in 10mL centrifuge tubes, adds distilled water and methanol each respectively
1.5mL, chloroform 3mL, whirlpool mixing 1min, ultrasonic extraction 25min centrifuge (3500r/min) 25min, extracting solution point at room temperature
For 2 layers (upper layer is water-soluble portion, that is, methanol water phase, and lower layer is chloroform phase), methanol water layer is moved into 25mL round bottoms with liquid-transfering gun
In flask, reduced pressure is evaporated, and chloroform layer discards.With 400 μ L of deuterated methanol and buffering heavy hydrogen water (KH before measuring2PO4It is dissolved in D2O
In, it is dissolved in the deuterated sodium hydroxides of 1mol/L and adjusts pH value to 6, contains 0.01%TSP) 400 μ L dissolvings, lysate moves to 1.5mL
In centrifuge tube, (13000r/min) 10min is centrifuged, it is to be measured in 500mm nuclear magnetic tubes to pipette 600 μ L of supernatant.
3, collection of illustrative plates acquires:Sample measures at 25 DEG C on 600MHz NMR instrument, and measurinng frequency frequency 600.13MHz is swept
Range 5~15ppm of ﹣, scanning times 64scans are retouched, water peak is suppressed using Noesygppr1d sequences, is locked with deuterated methanol
, inside it is designated as TSP.
4, collection of illustrative plates pre-processes:Each sample free damping (FID) signal measured is imported into MestReNova (version
8.0.1, Mestrelab Research, Santiago de Compostlla, Spain), it is calibrated with TSP (0.0), carries out base
Line adjusts and phasing.Then subsection integral is carried out to chemical shift section δ 0.72~δ of H H9.15 with 0.01 segmentation, to δ
H4.68~δ H4.92 (remaining water peak) and δ 3.34~δ of H H3.38 (residual methanol peak) are without integral.By the data after integral
It imports in excel, carries out area normalization processing.Spina date seed methanol water layer1H NMR and Yunnan jujube kernel methanol water layer1H NMR figures
Spectrum is shown in Fig. 1, Fig. 2.
5, differentiate the structure of model
Data after 18 batches of spina date seeds (number 1~18) and 7 batches of Yunnan jujube kernels (D1~D7) totally 25 samples normalizations are led
Enter progress PLS analyses in SIMCA-P13.0 softwares.Sample spina date seed is assigned a value of 1, and Yunnan jujube kernel is assigned a value of 2.Using offset minimum binary
Method by Jing Guo normalized integral relative value data matrix (X variables) and class variable (Y variables) carry out linear regression, obtain
To discrimination model.
Based on PLS principles, by leaving-one method (leave-one-out) in discrimination model in SIMCA-P13.0 softwares
25 class variable Y are calculated.25 samples are divided into 7 groups by system, if serial number divided by 7, the identical sample of gained remainder
It is one group, the sample for not participating in modeling is calculated with the model of wherein 6 groups Sample Establishings every time.The actual value of PLS models
Be shown in Table 3 with the differentiation table of predicted value, table 3 give the predicted value of 18 spina date seeds and 7 Yunnan jujube kernel sample class variable Y with it is true
Real value, 25 samples have obtained correct classification.As can be seen from the table 0.89≤P≤1.13 be spina date seed, 1.96≤P≤
2.02 be Yunnan jujube kernel, so we show that P≤1.13 are spina date seed, P >=1.90 are Yunnan jujube kernel, and 1.13 < P < 1.90 are to mix puppet
Product.
3 25 kinds of sample discriminant analyses of table
Embodiment 2 differentiates unknown sample
The spina date seed 9 batches of separate sources is collected, Yunnan jujube kernel 6 batches refers to table 4, table 5
4 separate sources spina date seed sample message of table
5 separate sources Yunnan jujube kernel sample message of table
It will be mixed for the 3 of model testing batches of spina date seeds (number 19~21), 2 batches of Yunnan jujube kernels (D-8, D-9) and four batches of mixing
Adulterant (CW1-4) carries out sample preparation and data acquisition and processing (DAP) by the method for 1 step 2~4 of embodiment, is accumulated accordingly
The discriminating model that split-phase establishes Value Data matrix, steps for importing 5, is judged, spina date seed mixes 40% Yunnan by PLS predicted values
Jujube kernel methanol water phase1H NMR spectras are shown in Fig. 3.
Mix pseudo- sample preparation:6 batches of spina date seeds (number 22~27) respectively take 50mg mixings, 4 crowdes of Yunnan jujube kernel (number D-10~D-
13) 50mg mixings are respectively taken.Sample after above-mentioned mixing is mixed into wild jujube with the ratio of Yunnan jujube kernel 20%, 40%, 60% and 80%
In benevolence sample (number is respectively CW1~CW4).Table 6 is that 5 batches of unknown samples and 4 batches make the predicted value for mixing pseudo- sample by oneself, is as a result shown
Showing discriminating model provided by the invention not only can accurately differentiate unknown sample, and can also accurate judgement whether be incorporation wild jujube
Benevolence mixes adulterant Yunnan jujube kernel.
Table 6:The discriminating of unknown sample
Claims (1)
1. the discrimination method of a kind of spina date seed and Yunnan jujube kernel, it is characterised in that include the following steps:
(1) spina date seed and Yunnan each 0.2g of jujube kernel powder are weighed respectively, are respectively placed in 10mL centrifuge tubes, are added distilled water and methanol each
1.5mL, chloroform 3mL, whirlpool mixing 1min, ultrasonic extraction 25min, extracting solution is divided into after 3500r/min centrifuges 25min at room temperature
Upper and lower 2 layers, upper layer is methanol water phase, and lower layer is chloroform phase, methanol-water is mutually moved in round-bottomed flask, reduced pressure is evaporated, and is obtained
Spina date seed and Yunnan jujube kernel extract;
(2) above two extract uses heavy water buffer solution 400 μ Ls of 400 μ L of the deuterated methanol and pH6 containing 0.01%TSP to dissolve respectively
After be transferred in centrifuge tube, 13000rpm centrifuge 10min, pipette 600 μ L of supernatant respectively and analyzed in nuclear magnetic tube, obtain
Spina date seed and Yunnan jujube kernel nuclear magnetic resonance spectroscopy;
(3) spina date seed and Yunnan jujube kernel nuclear magnetic resonance spectroscopy are imported into MestReNova softwares, baseline adjustment is carried out after being calibrated with TSP
And phasing;Then with 0.01 section to chemical shift δH0.72~9.15 carries out subsection integral, deletes remaining water peak δ
Integrated value corresponding to 3.34~3.38 section of H4.68~4.92 and residual methanol peak δ H imports the data after integral
Area normalization processing is carried out in excel;
(4) differentiate the foundation of model:
A. spina date seed and Yunnan jujube kernel sample are total in the importing SIMCA-P13.0 softwares of the data after N number of samples normalization and are carried out partially
Least square method (PLS) is analyzed;Spina date seed sample is assigned a value of 1, and Yunnan jujube kernel sample is assigned a value of 2;It will be passed through at normalization using PLS
The integral relative value data matrix (X variables) and class variable (Y variables) of reason carry out linear regression, obtain discrimination model;
B. be based on PLS principles, by leaving-one method in SIMCA-P13.0 softwares to discrimination model in N number of class variable Y count
It calculates;N samples are divided into 7 groups by system, if serial number divided by 7, the identical sample of gained remainder is one group, uses wherein 6 groups of samples every time
The model of this foundation calculates the sample for not participating in modeling;PLS models actual value and predicted value, determine spina date seed and
The prediction threshold value of Yunnan jujube kernel, i.e., when predicted value P≤1.13 are spina date seed, P >=1.90 are Yunnan jujube kernel, between 1.13 < P < 1.90
To mix the sample of Yunnan jujube kernel in spina date seed;
(5) differentiate unknown sample:
The method that unknown sample is pressed step (1)~(3), obtains intensity integration data, the mirror after normalization in steps for importing (4)
Other model obtains the predicted value P of class variable Y, and when P≤1.13 are spina date seed, P >=1.90 are Yunnan jujube kernel, 1.13 < P < 1.90
To mix adulterant.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810121226.5A CN108490016A (en) | 2018-02-07 | 2018-02-07 | A kind of discrimination method of spina date seed and Yunnan jujube kernel |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201810121226.5A CN108490016A (en) | 2018-02-07 | 2018-02-07 | A kind of discrimination method of spina date seed and Yunnan jujube kernel |
Publications (1)
Publication Number | Publication Date |
---|---|
CN108490016A true CN108490016A (en) | 2018-09-04 |
Family
ID=63344639
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201810121226.5A Pending CN108490016A (en) | 2018-02-07 | 2018-02-07 | A kind of discrimination method of spina date seed and Yunnan jujube kernel |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108490016A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114487180A (en) * | 2022-01-20 | 2022-05-13 | 广西壮族自治区食品药品检验所 | Adulteration detection method of jujube kernels in Tianwang heart tonifying preparation |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2009244015A (en) * | 2008-03-31 | 2009-10-22 | Osaka Univ | Quality evaluation method of angelica acutiloba |
CN104713895A (en) * | 2015-03-13 | 2015-06-17 | 中国科学院武汉物理与数学研究所 | Method for distinguishing between pure and syrup-adulterated honey based on combination of hydrogen nuclear magnetic resonance and partial least square method |
CN105223222A (en) * | 2015-11-04 | 2016-01-06 | 宁波大学 | A kind of discrimination method of difference porphyra haitanensis harvest time |
EP3070150A2 (en) * | 2015-03-20 | 2016-09-21 | Authentix, Inc. | Fuel markers |
CN107543838A (en) * | 2017-09-20 | 2018-01-05 | 北京市食品安全监控和风险评估中心(北京市食品检验所) | A kind of adulterated magnetic resonance detection method for planting butter cream in dilute cream |
-
2018
- 2018-02-07 CN CN201810121226.5A patent/CN108490016A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2009244015A (en) * | 2008-03-31 | 2009-10-22 | Osaka Univ | Quality evaluation method of angelica acutiloba |
CN104713895A (en) * | 2015-03-13 | 2015-06-17 | 中国科学院武汉物理与数学研究所 | Method for distinguishing between pure and syrup-adulterated honey based on combination of hydrogen nuclear magnetic resonance and partial least square method |
EP3070150A2 (en) * | 2015-03-20 | 2016-09-21 | Authentix, Inc. | Fuel markers |
CN105223222A (en) * | 2015-11-04 | 2016-01-06 | 宁波大学 | A kind of discrimination method of difference porphyra haitanensis harvest time |
CN107543838A (en) * | 2017-09-20 | 2018-01-05 | 北京市食品安全监控和风险评估中心(北京市食品检验所) | A kind of adulterated magnetic resonance detection method for planting butter cream in dilute cream |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN114487180A (en) * | 2022-01-20 | 2022-05-13 | 广西壮族自治区食品药品检验所 | Adulteration detection method of jujube kernels in Tianwang heart tonifying preparation |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109297929B (en) | Method for establishing quality grading of salvia miltiorrhiza decoction pieces by utilizing near infrared technology | |
CN109444290B (en) | Construction method and detection method of UPLC (ultra performance liquid chromatography) characteristic map of plantain herb | |
CN109270187B (en) | Chinese medicine preparation quality evaluation method based on metabonomics and full-ingredient semi-quantitative analysis | |
CN108152434A (en) | A kind of lookup method of the Chinese medicine specific component based on visualization Information in Mass Spectra | |
CN104101674B (en) | A kind of method of screening Yinchenhao Tang, Oriental Wormwood Decoction effective substance | |
CN107917896A (en) | Radix glycyrrhizae method for quick identification based near infrared spectrum and Clustering Analysis Technology | |
CN110187020A (en) | Astragalus root components evaluation method based on treatment atrophic gastritis spectrum effect relationship | |
Li et al. | Metabolic discrimination of different Rhodiola species using 1H-NMR and GEP combinational chemometrics | |
CN111323491B (en) | Construction method and quality detection method of UPLC characteristic spectrum of radix Saposhnikoviae medicinal material | |
CN109406682A (en) | The UPLC characteristic spectrum construction method and detection method of ginger medicinal material | |
CN115060822A (en) | Fingerprint spectrum quantitative analysis method based on Chinese medicine imprinting template component cluster | |
CN113777183B (en) | Glossy privet fruit medicinal material and its processed product characteristic spectrum construction method and multi-index component content detection method | |
CN106370763A (en) | UPLC method for detecting components in radix puerariae, radix puerariae extract and radix puerariae-containing preparation | |
CN102608248B (en) | Relinqing granules and polygonum capitatum thin-layer fingerprint chromatogram determination method | |
CN108490016A (en) | A kind of discrimination method of spina date seed and Yunnan jujube kernel | |
CN110638990B (en) | Extraction process of cassia twig, peony and rhizoma anemarrhenae prescription preparation extract | |
CN108226325A (en) | Roripa montana gives birth to the method for building up of arteries and veins oral liquid composition finger-print | |
CN102119997B (en) | Method for establishing HPLC (high performance liquid chromatography) finger-print of ophiopogon japonicus and standard finger-print thereof | |
CN115267008B (en) | Construction method of characteristic spectrum and comparison spectrum of bamboo juice pinellia ternate and distinguishing method of different processed products of pinellia ternate | |
CN103257191B (en) | Method for assaying kidney tonifying and life lengthening capsule fingerprint | |
CN109828053A (en) | The raw HERBA DENDROBII of a kind of pair of stone and the method for setting raw HERBA DENDROBII progress chromatographic identification | |
CN109884219A (en) | The construction method and detection method of Rhizoma Atractylodis Macrocephalae UPLC characteristic spectrum | |
CN106918673A (en) | A kind of method for building up of the finger-print of Chinese medicine composition | |
CN107782798B (en) | Method for detecting qi-tonifying astragalus-ginseng dropping pills by using dual-wavelength UPLC | |
CN113759011B (en) | Method for establishing characteristic spectrum of starwort root and preparation thereof |
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 | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180904 |
|
RJ01 | Rejection of invention patent application after publication |