CN104655812A - Method for rapidly identifying trueness and quality of radix notoginseng - Google Patents
Method for rapidly identifying trueness and quality of radix notoginseng Download PDFInfo
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Abstract
The invention discloses a method for rapidly identifying the trueness and quality of radix notoginseng. The method is characterized by detecting a sample by adopting an electronic nose and an electronic tongue and analyzing and identifying the sample by adopting PCA (principal component analysis) and DFA (dynamic financial analysis) methods, thus distinguishing the trueness and quality of radix notoginseng. The method has the advantages of high recognition rate and high identification speed.
Description
Technical field
The present invention relates to prepared slices of Chinese crude drugs field, particularly relate to the good and bad method for quick identification of a kind of pseudo-ginseng true and false.
Background technology
Pseudo-ginseng is the dry root welding technology of panax araliaceae plant Panax notoginseng (Burk.) F.H.Chen.Because of its effect fall apart the stasis of blood hemostasis, detumescence ding-tong, can be used for spitting of blood, spit blood, bleeding from five sense organs or subcutaneous tissue, has blood in stool, uterine bleeding, traumatism and bleeding, chest ventral spine pain, tumbling and swelling is a kind of important herbal species.
But there is the phenomenon that adulterant mixes in the pseudo-ginseng on market.On the one hand, between pseudo-ginseng and adulterant thereof, appearance character has very high similarity, and add that large is use mainly with powder, powder, all based on faint yellow or yellow-white, causes and not easily effectively distinguishes discriminating.On the other hand, current pseudo-ginseng causes Yield and quality to decline due to climate change, soil pollution etc., and market supply and demand contradiction strengthens and becomes increasingly conspicuous, and causes pseudo-ginseng price high, and under the driving of economic interests, in Notoginseng Root, mix pseudo-phenomenon serious.
Existing multiple method is applied to the discriminating research of pseudo-ginseng at present, as chromatogram, micro-, PCR-RFLP, FT-IR, 2D-IR etc.But these methods exist or workload is large, or time loss is many, or expensive, or the shortcoming that specificity is not high.Therefore a kind of method setting up fast and reliable is significant to differentiate the true and false quality of pseudo-ginseng.
Electronic Nose is a kind of instrument for detecting and distinguish complicated gas, and its sensor array is made up of a series of many sensitive sensor.Electronic tongues is a kind of Artifical Taste analytical instrument, and it is made up of, for the fluid sample of detection of complex one group of specific sensor.This two quasi-instrument have hypersensitivity, efficiency high, consume few feature.At present, as a kind of effective method, the discriminating being successfully applied to multi-product is distinguished, but there are no the qualification adopting Electronic Nose or electronic tongues to carry out pseudo-ginseng true and false quality.
It is that one is usually used in Data Dimensionality Reduction that PCA analyzes (principal component analysis (PCA)), and solves the Multivariable Statistical Methods of linear problem.The method replaces original incoherent variable by producing new variables, and carries out dimensionality reduction by linear combination data, simplifies the task of all variable informations obtaining data centralization.Under normal circumstances, some new variablees, are called major component (PCs), can explain former variable data information, therefore, only consider multiple major component, high dimensional data can be reduced to a lower dimension, and data message loss is little.Current this technology is widely used in the middle of data processing.
It is on the basis of classifying based on priori data that DFA analyzes (Assessing parameters analysis), calculates the border between inhomogeneity, such that inter-class variance is maximum and each variance within clusters is minimum.So this linear combination mode maximise can the dimension contribution rate of maximum difference between Display Group.In this way, the data under same data set with heterogeneity meaning effectively can be distinguished.At present, this technology is widely used in complicated data analysis.
Summary of the invention
The present invention aims to provide the good and bad method for quick identification of a kind of pseudo-ginseng true and false, and the method adopts Electronic Nose and electronic tongues to detect, and discrimination is high, differentiates that speed is fast.
For achieving the above object, the present invention realizes by the following technical solutions:
The good and bad method for quick identification of the pseudo-ginseng true and false disclosed by the invention, comprises the following steps:
S1, sample making, is broken into powder by raw meal stand-by.
S2, adopts detection by electronic nose sample, takes sample by predetermined quality, by predetermined value setting air flow velocity, sampling volume, injector to inject speed, oscillator temperature, concussion time, sample feeding interval time and the detection by electronic nose time respectively in test process.
S3, adopts electronic tongues to detect sample, takes sample size, thin up, refluxing extraction, let cool by predetermined value, filter, get after filtrate is diluted again and carry out electronic tongues detection detection time according to predetermined electronic tongues.
S4, PCA analysis (principal component analysis (PCA)) is carried out to the testing result of Electronic Nose, electronic tongues, the input that the sensor response obtained using Electronic Nose and electronic tongues is respectively analyzed as PCA, according to the PCA analysis result of Electronic Nose, front 3 maximum major components of contribution are adopted to form the first three-dimensional shot chart, then according to the true and false quality of the registration determination Radix Notoginseng powder of the first three-dimensional shot chart and various Notoginseng Root sample; According to the PCA analysis result of Electronic Nose, front 3 maximum major components of contribution are adopted to form the second three-dimensional shot chart, determine that the true and false of this sample is good and bad according to the registration of the standard three-dimensional shot chart of the second three-dimensional shot chart and various Notoginseng Root sample again, or judge whether this sample mixes puppet according to the registration of the standard three-dimensional shot chart of the second three-dimensional shot chart and Radix Notoginseng powder.
S5, carries out DFA analysis respectively to the testing result of Electronic Nose, electronic tongues, and the sensor response obtained using Electronic Nose and electronic tongues is respectively as the input of DFA model; According to the DFA analysis result of Electronic Nose, obtain the first two-dimentional shot chart, more good and bad according to the true and false of the registration determination Radix Notoginseng powder of the first two-dimentional shot chart and various Notoginseng Root sample; According to the PCA analysis result of Electronic Nose, front 3 maximum major components of contribution are adopted to form the second two-dimentional shot chart, determine that the true and false of this sample is good and bad according to the registration of the standard two-dimensional shot chart of the second two-dimentional shot chart and various Notoginseng Root sample again, or judge whether this sample mixes puppet according to the registration of the standard two-dimensional shot chart of the second two-dimentional shot chart and Radix Notoginseng powder.
Preferably, described Electronic Nose is the FOX-4000 type Electronic Nose of Alpha Mos company, and described electronic tongues is the α Astree type electronic tongues of Alpha Mos company.
Further, in step sl, described powder is passed through 100 object screen filtrations.
Preferably, in step s 2, described Electronic Nose uses 17 sensors, be respectively T30/1, T40/2, T40/1, TA/2, T70/2, P10/1, P10/2, P40/1, PA/2, P30/1, P40/2, P30/2, LY2/LG, LY2/G, LY2/AA, LY2/GH, LY2/gCTL, LY2/gCT; Described electronic tongues uses 7 sensors, is respectively ZZ, AB, GA, BB, CA, DA, JE.
Further, in step s3, before each measurement, sensor is activated, calibration and diagnosis, to ensure that data stabilization is reliable, at activation and calibration phase, the hydrochloric acid of 0.01mol/L is used to test the stability that sensor responds, in diagnostic phases, use the hydrochloric acid of 0.01mol/L respectively, the L-sodium of 0.01mol/L sodium chloride and 0.01mol/L is tested sensor.
Further, in step s 2, to sample duplicate measurements 3 times.
Further, in step s3, before detection sample, adopt ionized water rinsing electronic tongues, sample detection sequence is set to replication 10 and encloses, and the data of getting last 3 times carry out Treatment Analysis.
Preferably, in step s 2, described predetermined quality is 1.0 grams, air velocity is 150mL/min, sampling volume is 2000 μ L, injector to inject speed is 2000 μ L/s, oscillator temperature 60 DEG C, duration of oscillation are 600s, sample feeding interval time is 600s, the detection by electronic nose time is 120s.
Preferably, in step s3, described sample size is 0.5g, adds water 80 milliliters and dilutes, reflux extracting time 1 hour, let cool, filter, get filtered fluid 20mL and be again diluted to 100mL, measure 80mL and carry out electronic tongues detection, described electronic tongues detection time is 120s, and the sensor response mean value got between 100s and 120s is output valve.
The good and bad method for quick identification of the pseudo-ginseng true and false disclosed by the invention, adopt Electronic Nose and electronic tongues to detect, discrimination is high, differentiates that speed is fast.
Accompanying drawing explanation
Fig. 1 is the three-dimensional shot chart that the PCA adopting FOX-4000 type Electronic Nose to carry out pseudo-ginseng authenticity analyzes;
Fig. 2 is the three-dimensional shot chart that the PCA adopting α Astree type electronic tongues to carry out pseudo-ginseng authenticity analyzes;
Fig. 3 is the two-dimentional shot chart that the DFA adopting FOX-4000 type Electronic Nose to carry out pseudo-ginseng authenticity analyzes;
Fig. 4 is the two-dimentional shot chart that the DFA adopting α Astree type electronic tongues to carry out pseudo-ginseng authenticity analyzes;
Fig. 5 is the three-dimensional shot chart that employing FOX-4000 type Electronic Nose carries out that pseudo-ginseng mixes the PCA analysis of adulterant qualification with it;
Fig. 6 is that employing α Astree type electronic tongues carries out pseudo-ginseng mixes the PCA analysis of adulterant qualification three-dimensional shot chart with it;
Fig. 7 is the two-dimentional shot chart that employing FOX-4000 type Electronic Nose carries out that pseudo-ginseng mixes the DFA analysis of adulterant qualification with it;
Fig. 8 is the two-dimentional shot chart that employing FOX-4000 type Electronic Nose carries out that pseudo-ginseng mixes the DFA analysis of adulterant category authentication with it;
Fig. 9 is that employing α Astree type electronic tongues carries out pseudo-ginseng mixes the DFA analysis of adulterant qualification two-dimentional shot chart with it;
Figure 10 is that employing α Astree II type electronic tongues carries out pseudo-ginseng mixes the DFA analysis of adulterant category authentication two-dimentional shot chart with it;
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with accompanying drawing, the present invention is further elaborated.
Get four strains sample, comprise pseudo-ginseng (numbering 1-9), curcuma zedoary (numbering 10-12), turmeric (numbering 13-15) and Bulbilus boussingaultiae pseudobaselloidis (numbering 16), above-mentioned sample message is in table 1; All samples is pulverized, and crosses 100 mesh sieves, for subsequent use.
Table 1 pseudo-ginseng and adulterant sample message thereof
Artificial adulterated Notoginseng Root, by mixing other adulterants in varing proportions in pseudo-ginseng (NO.1) powder.All material samples are pulverized and are carried out adulterated mixing after crossing 100 mesh sieves.Artificial adulterated information is in table 2.
The artificial adulterated Notoginseng Root sample of table 2
Pseudo-ginseng authenticity
Electronic Nose adopts FOX-4000 electric nasus system (Alpha Mos), by sensor array, and air generator, HS-100 automatic sampler and mode identificating software (Alpha M.O.S., Version 2012.45) composition.18 metal-oxide semiconductor (MOS) chemical sensors comprise three types: T (T30/1, T40/2, T40/1, TA/2, T70/2), P (P10/1, P10/2, P40/1, PA/2, P30/1, P40/2, P30/2) and LY (LY2/LG, LY2/G, LY2/AA, LY2/GH, LY2/gCTL, LY2/gCT).
Take sample 1.0g in 20mL ml headspace bottle, sealing, is positioned over auto injection dish.In test process, system air flow velocity is set to 150mL/min; Sampling volume 2000 μ L, injector to inject speed 2000 μ L/s; Oscillator temperature 60 DEG C, concussion time 600s; Sample feeding is set to 600s interval time; Detection time 120s.Using the maximum response of every root sensor as output valve.All samples difference replication 3 times.
Electronic tongues adopts the α Astree type electronic tongues of Alpha MOS, comprises ZZ, AB, GA, BB, CA, DA and JE 7 cross sensitivity potentiometric sensor arrays; Ag/AgCl contrast electrode (Metrohm, Ltd.); Mechanical stirrer (Metrohm, Ltd.); 16 automatic samplers; Signal processing system (AlphaMOS) and mode identificating software (Alpha M.O.S., Version 2012.45).
Activate sensor before each measurement, calibration and diagnosis, to ensure that data stabilization is reliable.At activation and calibration phase, the hydrochloric acid of 0.01mol/L is used to test the stability that sensor responds.In diagnostic phases, use the hydrochloric acid of 0.01mol/L respectively, the L-sodium of 0.01mol/L sodium chloride and 0.01mol/L is tested sensor.
Take sample 0.5g in plug conical flask, add water 80 milliliters, last 1 hour of refluxing extraction, lets cool, and filters, gets subsequent filtrate 20mL and be diluted to 100mL.Measure 80mL liquid and be placed in beaker, and be loaded into auto injection dish.All samples is set to 120s analysis time, and the sensor response mean value got between 100s and 120s is output valve.Use rinsed with deionized water after often having analyzed single sample, then measure next sample.Sample determination sequence is set to replication 10 and encloses (after all samples measurement of first lap terminates, then carrying out the measurement of next circle).Treatment Analysis is carried out with the data of last 3 times.
PCA analyzes
With the electric signal that Electronic Nose and electronic tongues obtain, namely sensor response (18 variablees of Electronic Nose and 7 variablees of electronic tongues) is as the input of principal component analysis (PCA).
Fig. 1 is according to according to detection by electronic nose result, adopts major component (PC1=99.969%, PC2=0.02634% that front 3 contribution rates are maximum; PC3=0.005049%) the three-dimensional shot chart formed.As shown in Figure 1,4 kind samples are divided into four groups, can obviously distinguish between each group; According to detection by electronic nose result, there is notable difference in pseudo-ginseng and its adulterant each other.
Fig. 2 is according to electronic tongues, adopts major component (PC1=99.952%, PC2=0.04278% that front 3 contribution rates are maximum; PC3=0.004998%) the three-dimensional shot chart formed.As shown in Figure 2, distinguish obviously between 4 different cultivars samples.According to electronic tongues testing result, there is notable difference in pseudo-ginseng and its adulterant each other.
According to above analysis, Electronic Nose and electronic tongues can present similarity between pseudo-ginseng and adulterant thereof or difference, and can realize the True-false distinguish of pseudo-ginseng according to PCA.
DFA analyzes
All variablees of Electronic Nose and electronic tongues are all as the input of DFA model.Sample (No. 1 to No. 6, No. 10 to No. 16) is as model training group, and pseudo-ginseng sample (No. 7 to No. 9) is set as that unknown sample is as test group.
Fig. 3 is foundation Electronic Nose sensor response is the DFA model (DF1=72.732%, DF2=25.096%) inputted, and total contribution rate is 97.828%.
Fig. 4 is foundation electronic tongue sensor response is the DFA model (DF1=91.783%, DF2=7.466%) inputted, and total contribution rate is 99.249%.
These two modelling verifications must be divided into 100, and modelling effect is fabulous.According to the DFA model set up, distinguished significantly for four kinds.Test group unknown sample recognition result (see table 3) is good, and three unknown samples (pseudo-ginseng) all correctly identify.
Table 3 pseudo-ginseng and adulterant DFA recognition result thereof
Pseudo-ginseng quality (certified products with mix adulterant) is differentiated
PCA analyzes
Fig. 5 is according to Electronic Nose, adopts the three-dimensional shot chart that the maximum major component (PC1=99.967%, PC2=0.02908%, PC3=0.003823%) of front 3 contribution rates is formed.In figure, sample is divided into four groups (pseudo-ginseng, a1, a2 and a3).A1, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma zedoary powder different proportion; A2, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma powder different proportion; A3, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and Bulbilus boussingaultiae pseudobaselloidis powder different proportion.By in Fig. 5, each sample component is distributed in different regions.Show that pseudo-ginseng is mixed pseudo-sample can obviously be distinguished from different.
Fig. 6 is according to electronic tongues, adopts the three-dimensional shot chart that the maximum major component (PC1=99.958%, PC2=0.03774%, PC3=0.004052%) of front 3 contribution rates is formed.In figure, sample is divided into four groups (pseudo-ginseng, a1, a2 and a3).A1, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma zedoary powder different proportion; A2, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma powder different proportion; A3, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and Bulbilus boussingaultiae pseudobaselloidis powder different proportion.The pseudo-ginseng shown in Fig. 6 is mixed pseudo-sample can obviously be distinguished from different.
DFA analyzes
Electronic Nose
All variablees of Electronic Nose are all as the input variable of DFA model.All adulterated samples and pseudo-ginseng (NO.1) are as the training group of model, and 4 of Stochastic choice samples are as test group sample.
Fig. 7 is whether the DFA model set up is adulterated with Division identification Radix Notoginseng powder.DFA result shows, and Radix Notoginseng powder and adulterated sample area are divided obviously, and all unknown samples are all correctly identified.
Fig. 8 is that the DFA model set up is with Division identification Radix Notoginseng powder and the concrete adulterated sample classification of Radix Notoginseng powder.In figure, sample is divided into four groups (pseudo-ginseng, a1, a2 and a3).A1, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma zedoary powder different proportion; A2, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma powder different proportion; A3, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and Bulbilus boussingaultiae pseudobaselloidis powder different proportion.DFA result shows, and Radix Notoginseng powder and adulterated sample area are divided obviously, and all unknown samples all correctly identify.
Electronic tongues
All variablees of electronic tongues are all as the input variable of DFA model.All adulterated samples and Radix Notoginseng powder (NO.1) are as the training group of model, and 4 of Stochastic choice samples are as test group sample.
Fig. 9 is whether the DFA model set up is adulterated with Division identification Radix Notoginseng powder.DFA result shows, and Radix Notoginseng powder and adulterated sample area are divided obviously, and all unknown samples are all correctly identified.
Figure 10 is that the DFA model set up is with Division identification Radix Notoginseng powder and the concrete adulterated sample classification of Radix Notoginseng powder.In figure, sample is divided into four groups (pseudo-ginseng, a1, a2 and a3).A1, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma zedoary powder different proportion; A2, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and curcuma powder different proportion; A3, what this group comprised mix pseudo-sample is mixed by pseudo-ginseng and Bulbilus boussingaultiae pseudobaselloidis powder different proportion.DFA result shows, and Radix Notoginseng powder and adulterated sample area are divided obviously, and all unknown samples are all correctly identified.
Certainly; the present invention also can have other various embodiments; when not deviating from the present invention's spirit and essence thereof; those of ordinary skill in the art can make various corresponding change and distortion according to the present invention, but these change accordingly and are out of shape the protection domain that all should belong to the claim appended by the present invention.
Claims (10)
1. the good and bad method for quick identification of the pseudo-ginseng true and false, is characterized in that, comprise the following steps:
S1, sample making, is broken into powder by raw meal stand-by;
S2, adopts detection by electronic nose sample, takes sample by predetermined quality, by predetermined value setting air flow velocity, sampling volume, injector to inject speed, oscillator temperature, concussion time, sample feeding interval time and the detection by electronic nose time respectively in test process;
S3, adopts electronic tongues to detect sample, takes sample, thin up, refluxing extraction, let cool by predetermined quality, filter, get after filtrate dilutes constant volume again and carry out electronic tongues detection detection time according to predetermined electronic tongues.
S4, PCA analysis (principal component analysis (PCA)) is carried out to the testing result of Electronic Nose, electronic tongues, the input that the sensor response obtained using Electronic Nose and electronic tongues is respectively analyzed as PCA, according to the PCA analysis result of Electronic Nose, front 3 maximum major components of contribution are adopted to form the first three-dimensional shot chart, then according to the true and false quality of the registration determination Radix Notoginseng powder of the first three-dimensional shot chart and various Notoginseng Root sample; According to the PCA analysis result of Electronic Nose, front 3 maximum major components of contribution are adopted to form the second three-dimensional shot chart, determine that the true and false of this sample is good and bad according to the registration of the standard three-dimensional shot chart of the second three-dimensional shot chart and various Notoginseng Root sample again, or judge whether this sample mixes puppet according to the registration of the standard three-dimensional shot chart of the second three-dimensional shot chart and Radix Notoginseng powder.
S5, carries out DFA analysis respectively to the testing result of Electronic Nose, electronic tongues, and the sensor response obtained using Electronic Nose and electronic tongues is respectively as the input of DFA model; According to the DFA analysis result of Electronic Nose, obtain the first two-dimentional shot chart, more good and bad according to the true and false of the registration determination Radix Notoginseng powder of the first two-dimentional shot chart and various Notoginseng Root sample; According to the PCA analysis result of Electronic Nose, front 3 maximum major components of contribution are adopted to form the second two-dimentional shot chart, determine that the true and false of this sample is good and bad according to the registration of the standard two-dimensional shot chart of the second two-dimentional shot chart and various Notoginseng Root sample again, or judge whether this sample mixes puppet according to the registration of the standard two-dimensional shot chart of the second two-dimentional shot chart and Radix Notoginseng powder.
2. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, is characterized in that: in described pseudo-ginseng true and false quality, the described pseudo-ginseng true and false refers to: pseudo-ginseng and adulterant thereof; Described pseudo-ginseng quality refers to: Radix Notoginseng powder and Radix Notoginseng powder thereof respectively with the potpourri of adulterant powder.
3. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, it is characterized in that: described Electronic Nose is the FOX-4000 Electronic Nose of Alpha Mos company, described electronic tongues is the α Astree electronic tongues of Alpha Mos company.
4. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, is characterized in that: in step sl, by described powder by 100 object screen filtrations.
5. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 2, it is characterized in that: in step s 2, described Electronic Nose uses 17 sensors, be respectively T30/1, T40/2, T40/1, TA/2, T70/2, P10/1, P10/2, P40/1, PA/2, P30/1, P40/2, P30/2, LY2/LG, LY2/G, LY2/AA, LY2/GH, LY2/gCTL, LY2/gCT; Described electronic tongues uses 7 sensors, is respectively ZZ, AB, GA, BB, CA, DA, JE.
6. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, it is characterized in that: in step s3, before each measurement, sensor is activated, calibration and diagnosis, to ensure that data stabilization is reliable, at activation and calibration phase, the hydrochloric acid of 0.01mol/L is used to test the stability that sensor responds, in diagnostic phases, use the hydrochloric acid of 0.01mol/L respectively, the L-sodium of 0.01mol/L sodium chloride and 0.01mol/L is tested sensor.
7. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, is characterized in that: in step s 2, to sample duplicate measurements 3 times.
8. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, it is characterized in that: in step s3, before detection sample, adopt ionized water rinsing electronic tongues, sample detection sequence is set to replication 10 and encloses, and the data of getting last 3 times carry out Treatment Analysis.
9. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, it is characterized in that: in step s 2, described predetermined quality is 1.0g, air velocity is 150mL/min, sampling volume is 2000 μ L, injector to inject speed is 1800 μ L/s, oscillator temperature 60 DEG C, duration of oscillation be 600s, sample feeding interval time is 600s, the detection by electronic nose time is 120s.
10. the good and bad method for quick identification of the pseudo-ginseng true and false according to claim 1, it is characterized in that: in step s3, described sample size is 1.0g, adds water 80 milliliters and dilutes, reflux extracting time 1 hour, let cool, filter, get filtered fluid 20mL and be again diluted to 100mL, measure 80mL and carry out electronic tongues detection, described electronic tongues detection time is 120s, and the sensor response mean value got between 100s and 120s is output valve.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN110031401A (en) * | 2018-01-12 | 2019-07-19 | 云三七(深圳)大数据科技有限责任公司 | A kind of method for quick identification of Radix Notoginseng powder |
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101961360A (en) * | 2009-07-24 | 2011-02-02 | 天津天士力现代中药资源有限公司 | Near infrared spectrum identification method for pseudo-ginseng |
| CN101975845A (en) * | 2010-09-21 | 2011-02-16 | 成都中医药大学 | Automatic detecting system for quality of traditional Chinese medicines |
| KR20110019265A (en) * | 2009-08-19 | 2011-02-25 | 서울대학교산학협력단 | Est-derived ssr primer sets for discrimination of panax ginseng cultivars and panax quinquefolius and uses thereof |
| CN103399050A (en) * | 2013-07-15 | 2013-11-20 | 浙江大学 | Method for rapidly evaluating ginseng-adulterated American ginseng based on mouth feel information |
| CN103487558A (en) * | 2013-07-30 | 2014-01-01 | 中国标准化研究院 | Detection method for abnormal samples in mode identification and analysis of tea quality through intelligent sensory signals |
| CN103575765A (en) * | 2013-10-14 | 2014-02-12 | 浙江大学 | Method for rapidly detecting mutton adulteration |
-
2014
- 2014-12-16 CN CN201410784877.4A patent/CN104655812B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101961360A (en) * | 2009-07-24 | 2011-02-02 | 天津天士力现代中药资源有限公司 | Near infrared spectrum identification method for pseudo-ginseng |
| KR20110019265A (en) * | 2009-08-19 | 2011-02-25 | 서울대학교산학협력단 | Est-derived ssr primer sets for discrimination of panax ginseng cultivars and panax quinquefolius and uses thereof |
| CN101975845A (en) * | 2010-09-21 | 2011-02-16 | 成都中医药大学 | Automatic detecting system for quality of traditional Chinese medicines |
| CN103399050A (en) * | 2013-07-15 | 2013-11-20 | 浙江大学 | Method for rapidly evaluating ginseng-adulterated American ginseng based on mouth feel information |
| CN103487558A (en) * | 2013-07-30 | 2014-01-01 | 中国标准化研究院 | Detection method for abnormal samples in mode identification and analysis of tea quality through intelligent sensory signals |
| CN103575765A (en) * | 2013-10-14 | 2014-02-12 | 浙江大学 | Method for rapidly detecting mutton adulteration |
Non-Patent Citations (3)
| Title |
|---|
| 吴浩 等: "电子鼻、电子舌分析和感官评价在鱼糜种类区分中的应用", 《食品工业科技》, no. 18, 31 December 2013 (2013-12-31) * |
| 杜瑞超 等: "电子舌对中药滋味的区分辨识", 《中国中药杂志》, vol. 38, no. 2, 31 January 2013 (2013-01-31) * |
| 田程 等: "中药人参与西洋参饮片的电子鼻检测方法及识别模式", 《中国中药杂志》, vol. 37, no. 8, 30 April 2012 (2012-04-30) * |
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| CN107561036A (en) * | 2017-07-06 | 2018-01-09 | 成都中医药大学 | A kind of detection method of bletilla kind and the true and false |
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