CN104569132A - Edible oil identification method based on mass spectrum and principal component analysis - Google Patents
Edible oil identification method based on mass spectrum and principal component analysis Download PDFInfo
- Publication number
- CN104569132A CN104569132A CN201410841302.1A CN201410841302A CN104569132A CN 104569132 A CN104569132 A CN 104569132A CN 201410841302 A CN201410841302 A CN 201410841302A CN 104569132 A CN104569132 A CN 104569132A
- Authority
- CN
- China
- Prior art keywords
- edible oil
- mass
- standard sample
- sample
- mass spectrometric
- 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
Abstract
The invention discloses an edible oil identification method based on mass spectrum and principal component analysis. According to the method, a mass spectrometer is used as an analytical tool, mass spectrum data of edible oil standard samples are acquired, feature mass spectrum data capable of significantly distinguishing all the edible oil standard samples through principal component analysis are extracted with a mass spectrum data pre-screening method, and an edible oil standard sample mass spectrum database is established to effectively identify unknown edible oil samples. According to the method, the edible oil identification capacity is improved through the improvement on a follow-up mass spectrum data processing method, increase of a sample preprocessing step and improvement on technical levels of analytical instruments are not required, large quantities of manpower, material resources and time costs are saved, and the method is a new edible oil identification method.
Description
Technical field
The present invention relates to a kind of edible oil discrimination method, be specifically related to a kind of edible oil discrimination method based on mass spectrum and principal component analysis (PCA).
Background technology
Edible oil is the food material that human lives is indispensable.There is larger difference in the nutritive value of Various Edible and the market price, illegal businessman often through adulterated, adulterate, even use waste oil to pretend to be the means of edible oil to seek exorbitant profit.Therefore, developing effective edible oil discrimination method is current social significant problem in the urgent need to address.
Mass spectrometric analysis method can obtain the mass spectrometric data of each compound in edible oil fast, comprehensively, exactly and carry out qualitative and quantitative analysis, and principal component analytical method can reflect the difference between different sample data effectively.Therefore, in recent years, numerous researcher's integrated use mass spectrum and principal component analysis (PCA) are differentiated edible oil.But current researcher directly carries out principal component analysis (PCA) to all mass spectrometric datas that mass spectrophotometry obtains usually, and the edible oil kind that can differentiate is few and discrimination is remarkable not simultaneously.In order to solve the deficiency that existing method exists, researcher often adopts and improves mass spectrometric analysis method to improve the ability of mass spectrum and principal component analysis (PCA) discriminating edible oil, and the improvement of mass spectrometric analysis method realizes often by increase sample pretreatment step and raising analytical instrumentation techniques level, need to drop into more human and material resources and time cost.
Summary of the invention
In order to solve prior art Problems existing, the object of the present invention is to provide a kind of edible oil discrimination method based on mass spectrum and principal component analysis (PCA), the method pays attention to the distinguishing ability improving edible oil by improving follow-up mass spectrometric data disposal route, without the need to increasing sample pretreatment step and improving analytical instrumentation techniques level, thus realize edible oil simply, fast and differentiate efficiently.
For reaching above object, the present invention adopts following technical scheme:
A kind of edible oil discrimination method based on mass spectrum and principal component analysis (PCA), utilize mass spectrometer as analysis tool, obtain the mass spectrometric data of edible oil standard sample, the characterising mass spectrometry data significantly can distinguishing all edible oil standard samples under principal component analysis (PCA) is extracted by the method for mass spectrometric data prescreen, set up edible oil standard sample mass spectrometric data storehouse, for effective discriminating of unknown edible oil sample; Specifically be made up of following steps:
The foundation in step 1. edible oil standard sample mass spectrometric data storehouse:
(1) parallel 3 ~ 10 mass spectrophotometry are carried out to edible oil standard sample, obtain the mass spectrometric data of mass-to-charge ratio between 50 ~ 1200, comprise the mass-to-charge ratio of each quasi-molecular ions and corresponding mass spectra peak intensity;
(2) carry out principal component analysis (PCA) to the mass-to-charge ratio of each quasi-molecular ions of edible oil standard sample and corresponding mass spectra peak intensity, edible oil standard sample is divided into and is difficult to distinguish and easily distinguish two kinds of series by vision area point effect;
(3) the mass spectra peak intensity of often kind of edible oil standard sample many experiments is average, then compare the difference of mass spectra peak intensity under the identical mass-to-charge ratio of all edible oil standard model, descending screening 20 ~ 200 mass spectrometric datas; The effect of this step extracts the mass spectrometric data that between Various Edible standard model, difference is large on the whole;
(4) mass spectra peak intensity difficulty being distinguished the many experiments of edible oil standard sample is average, then the difference of mass spectra peak intensity under the identical mass-to-charge ratio of more difficult differentiation edible oil standard sample, the mass spectrometric data of descending screening number identical with step 3; The effect of this step extracts the large mass spectrometric data of difficult differentiation edible oil standard sample room difference;
(5) mass spectrometric data of step 3 and step 4 being screened is in comprehensive in conjunction with ratio 1:1 ~ 1:10, remove the mass spectrometric data repeated, principal component analysis (PCA) is carried out to edible oil standard sample used, is set up the standard model mass spectrometric data storehouse effectively can differentiating edible oil by adjustment in conjunction with ratio; This database comprises the feature mass-to-charge ratio and corresponding mass spectra peak intensity that significantly can embody difference between all edible oil standard model;
The discriminating of the unknown edible oil sample of step 2.:
The mass spectrometric analysis method of edible oil standard sample is adopted to carry out mass spectrophotometry to unknown edible oil sample, the corresponding mass spectrometric data of unknown edible oil sample is extracted according to the feature mass-to-charge ratio in edible oil standard sample mass spectrometric data storehouse, carry out principal component analysis (PCA) together with edible oil standard sample mass spectrometric data storehouse, differentiate that whether unknown edible oil sample is the class in edible oil standard sample according to the score of each major component.
Described mass spectrophotometry adopts solute migration electron spray ionisation method to carry out mass spectrophotometry.
Compared to the prior art, tool has the following advantages in the present invention:
Method by mass spectrum and principal component analysis (PCA) discriminating edible oil of the present invention can be widely used in the various animal and plant fats differentiating to comprise edible vegetable oil, waste oil, vegetable fat, animal fat, repeatedly fried grease.The method improves the distinguishing ability of edible oil by improving follow-up mass spectrometric data disposal route, without the need to increasing sample pretreatment step and improving analytical instrumentation techniques level, thus realize edible oil simply, fast and differentiate efficiently.
The invention has the beneficial effects as follows:
(1) adopt spectrometer analysis method working sample, finding speed is fast, and simple to operate, result accurately has good Repeatability and Reproducibility, can meet the requirement that batch samples detects fast.
(2) the method improves the distinguishing ability of edible oil by improving follow-up mass spectrometric data disposal route, without the need to increasing sample pretreatment step and improving analytical instrumentation techniques level, saves a large amount of human and material resources and time cost.
(3) principal component analysis (PCA) result is short and sweet, effectively can judge unknown edible oil sample whether as the one of edible oil standard sample.
Accompanying drawing explanation
Fig. 1 is difficult to the classification distinguishing and easily distinguish sample.
The result that Fig. 2 all edible oil standard model mass spectrometric data is refined.
Fig. 3 is difficult to the result distinguishing the refinement of edible oil standard sample mass spectrometric data.
The identification result that Fig. 4 combines in 1:1 ratio.
The identification result that Fig. 5 combines in 1:2 ratio.
The unknown edible oil sample of Fig. 6 differentiates example 1 identification result.
The unknown edible oil sample of Fig. 7 differentiates example 2 identification result.
The unknown edible oil sample of Fig. 8 differentiates example 3 identification result.
Embodiment
Below in conjunction with specific embodiment, the present invention is described in further detail.
Embodiment 1
1. the foundation in edible oil standard sample mass spectrometric data storehouse
Get 6 kinds of known edible oil oil samples (sunflower oil, olive oil, mustard oil, rapeseed oil, corn oil and peanut oil) as standard model, adopt solute migration electron spray ionisation method to carry out mass spectrophotometry.Labor condition is as follows: mass charge ratio range: 50 ~ 1200; Capillary tip bore: 15 μm; Spray voltage: 2kv; Ionization pattern: positive ion mode; Mass spectrometer: Thermo Scientific TSQ Quantum Access MAX triple quadrupole mass spectrometer.
(1) first in kapillary, add 25 μ L analyzes pure methanol solvate; The known oil sample of 2 μ L is injected again in kapillary; Finally add spray voltage, carry out mass spectrophotometry, get the data after signal stabilization, each oil sample repeats 5 experiments.
(2) principal component analysis (PCA) is carried out to all mass spectrometric datas of 6 kinds of edible oil standard samples, according to differentiation effect edible oil standard sample is divided into and is difficult to distinguish and easily distinguish two kinds of series, as shown in Figure 1, as can be seen from Fig. 1 principal component analysis (PCA) result, mustard oil and olive oil can easily be distinguished, and corn oil, sunflower oil, peanut oil and rapeseed oil (particularly corn oil and sunflower oil) are difficult to distinguish comparatively speaking, and the result that most of oil sample obtains is disperseed very much.
(3) first average for the mass spectra peak intensity of often kind of edible oil standard sample 5 experiments, compare the difference of peak intensity under 6 kinds of identical mass-to-charge ratioes of edible oil standard sample again, descending screening 50 mass spectrometric datas carry out principal component analysis (PCA) (mass-to-charge ratio: 125, 121, 899, 401, 901, 635, 109, 903, 640, 897, 639, 900, 116, 904, 902, 637, 137, 641, 379, 875, 642, 877, 203, 644, 242, 337, 146, 602, 898, 929, 385, 636, 181, 141, 363, 115, 519, 616, 225, 931, 873, 396, 517, 920, 339, 906, 100, 905, 604, 93), as shown in Figure 2, as can be seen from Fig. 2 principal component analysis (PCA) result, after data screening, the principal component analysis (PCA) result of identical oil sample is all in narrower scope, illustrate that extracting the mass spectrometric data that between Various Edible standard model, difference is large on the whole makes distinguishing ability be improved.But discrimination is still remarkable not between difficult differentiation edible oil (corn oil, sunflower oil, peanut oil and rapeseed oil).
(4) difficulty is distinguished edible oil standard sample (corn oil, sunflower oil, peanut oil and rapeseed oil) peak intensity of 5 experiments is average, the difference of peak intensity under the identical mass-to-charge ratio of more difficult differentiation edible oil standard sample again, descending screening 50 mass spectrometric data (mass-to-charge ratioes: 109, 90, 635, 899, 116, 203, 875, 146, 903, 602, 640, 904, 900, 181, 115, 897, 337, 642, 641, 616, 902, 906, 100, 905, 611, 877, 93, 931, 637, 339, 907, 143, 873, 618, 113, 876, 636, 656, 298, 371, 920, 908, 604, 933, 898, 657, 922, 122, 917, 880), principal component analysis (PCA) is carried out to all edible oil standard model, as shown in Figure 3, as can be seen from Figure 3, be difficult to the corn oil distinguished before, sunflower oil, the principal component analysis (PCA) result significant difference of peanut oil and rapeseed oil, illustrate that this step can extract the large mass spectrometric data of difficult differentiation edible oil standard sample room difference.And the olive oil easily distinguished before and mustard oil can not effectively be differentiated, this is because this secondary data obtains by screening based on the corn oil, sunflower oil, peanut oil and the rapeseed oil that are difficult to distinguish.
(5) mass spectrometric data of step 3 and step 4 being refined is comprehensive in 1:1 ratio (50:50), remove the mass spectrometric data repeated, totally 67 mass spectrometric data (mass-to-charge ratioes: 933, 931, 929, 922, 920, 917, 908, 907, 906, 905, 904, 903, 902, 901, 900, 899, 898, 897, 880, 877, 876, 875, 873, 657, 656, 644, 642, 641, 640, 639, 637, 636, 635, 618, 616, 611, 604, 602, 519, 517, 401, 396, 385, 379, 371, 363, 339, 337, 298, 242, 225, 218, 203, 181, 146, 143, 141, 137, 125, 122, 121, 116, 115, 113, 109, 100, 93), principal component analysis (PCA) is carried out to edible oil standard sample used, as shown in Figure 4, as can be seen from Fig. 4 principal component analysis (PCA) result, can carry out good discrimination to all edible oil standard model, but be difficult to the discrimination distinguished in oil sample between sunflower oil and corn oil need to improve.
(6) discrimination owing to being difficult in step 5 distinguish in oil sample between sunflower oil and corn oil is obvious not, therefore need to improve step 4 screen the ratio of mass spectrometric data, get front 25 mass spectrometric datas of step 3, 50 mass spectrometric datas of step 4, be 1:2 in conjunction with ratio, remove repeating data and obtain 58 mass spectrometric data (mass-to-charge ratioes: 933, 931, 922, 920, 917, 908, 907, 906, 905, 904, 903, 902, 901, 900, 899, 898, 897, 880, 877, 876, 875, 873, 657, 656, 644, 642, 641, 640, 639, 637, 636, 635, 618, 616, 611, 604, 602, 401, 379, 371, 339, 337, 298, 242, 203, 181, 146, 143, 137, 125, 122, 121, 116, 115, 113, 109, 100, 93), principal component analysis (PCA) is carried out to edible oil standard sample used, as shown in Figure 5, as can be seen from Figure 5, discrimination between corn oil and sunflower oil has obvious lifting, all edible oil standard model all can significantly be differentiated, therefore the mass spectrometric data storehouse of edible oil standard sample has been set up.
2. the discriminating of unknown edible oil sample
The mass spectrometric analysis method of edible oil standard sample is adopted to carry out mass spectrophotometry to unknown edible oil sample, feature mass-to-charge ratio according to standard sample mass spectrometric data storehouse extracts corresponding mass spectrometric data, principal component analysis (PCA) is carried out together with edible oil standard sample mass spectrometric data storehouse, differentiate that whether unknown edible oil sample is the class in edible oil standard sample according to the score of each major component, as shown in Figure 6, show from Fig. 6 principal component analysis (PCA) result, test 6 kinds of oil samples all in oil sample and edible oil standard sample and there is significant difference, therefore edible oil standard sample (sunflower oil is not belonged to, olive oil, mustard oil, rapeseed oil, corn oil and peanut oil) in one.
Embodiment 2
The mass spectrometric analysis method of edible oil standard sample is adopted to carry out mass spectrophotometry to unknown edible oil sample, feature mass-to-charge ratio according to standard sample mass spectrometric data storehouse extracts corresponding mass spectrometric data, principal component analysis (PCA) is carried out together with edible oil standard sample mass spectrometric data storehouse, differentiate that whether unknown edible oil sample is the class in edible oil standard sample according to the score of each major component, as shown in Figure 7, show from Fig. 7 principal component analysis (PCA) result, test oil sample is consistent with sunflower oil result in edible oil standard sample, and therefore this test oil sample is sunflower oil.
Embodiment 3
The mass spectrometric analysis method of edible oil standard sample is adopted to carry out mass spectrophotometry to unknown edible oil sample, feature mass-to-charge ratio according to standard sample mass spectrometric data storehouse extracts corresponding mass spectrometric data, principal component analysis (PCA) is carried out together with edible oil standard sample mass spectrometric data storehouse, differentiate that whether unknown edible oil sample is the class in edible oil standard sample according to the score of each major component, as shown in Figure 8, show from Fig. 8 principal component analysis (PCA) result, test oil sample is consistent with olive oil result in edible oil standard sample, and therefore this test oil sample is olive oil.
Claims (2)
1. the edible oil discrimination method based on mass spectrum and principal component analysis (PCA), it is characterized in that: utilize mass spectrometer as analysis tool, obtain the mass spectrometric data of edible oil standard sample, the characterising mass spectrometry data significantly can distinguishing all edible oil standard samples under principal component analysis (PCA) is extracted by the method for mass spectrometric data prescreen, set up edible oil standard sample mass spectrometric data storehouse, for effective discriminating of unknown edible oil sample; Specifically be made up of following steps:
The foundation in step 1. edible oil standard sample mass spectrometric data storehouse:
(1) parallel 3 ~ 10 mass spectrophotometry are carried out to edible oil standard sample, obtain the mass spectrometric data of mass-to-charge ratio between 50 ~ 1200, comprise the mass-to-charge ratio of each quasi-molecular ions and corresponding mass spectra peak intensity;
(2) carry out principal component analysis (PCA) to the mass-to-charge ratio of each quasi-molecular ions of edible oil standard sample and corresponding mass spectra peak intensity, edible oil standard sample is divided into and is difficult to distinguish and easily distinguish two kinds of series by vision area point effect;
(3) the mass spectra peak intensity of often kind of edible oil standard sample many experiments is average, then compare the difference of mass spectra peak intensity under the identical mass-to-charge ratio of all edible oil standard model, descending screening 20 ~ 200 mass spectrometric datas; The effect of this step extracts the mass spectrometric data that between Various Edible standard model, difference is large on the whole;
(4) mass spectra peak intensity difficulty being distinguished the many experiments of edible oil standard sample is average, then the difference of mass spectra peak intensity under the identical mass-to-charge ratio of more difficult differentiation edible oil standard sample, the mass spectrometric data of descending screening number identical with step 3; The effect of this step extracts the large mass spectrometric data of difficult differentiation edible oil standard sample room difference;
(5) mass spectrometric data of step 3 and step 4 being screened is in comprehensive in conjunction with ratio 1:1 ~ 1:10, remove the mass spectrometric data repeated, principal component analysis (PCA) is carried out to edible oil standard sample used, is set up the standard model mass spectrometric data storehouse effectively can differentiating edible oil by adjustment in conjunction with ratio; This database comprises the feature mass-to-charge ratio and corresponding mass spectra peak intensity that significantly can embody difference between all edible oil standard model;
The discriminating of the unknown edible oil sample of step 2.:
The mass spectrometric analysis method of edible oil standard sample is adopted to carry out mass spectrophotometry to unknown edible oil sample, the corresponding mass spectrometric data of unknown edible oil sample is extracted according to the feature mass-to-charge ratio in edible oil standard sample mass spectrometric data storehouse, carry out principal component analysis (PCA) together with edible oil standard sample mass spectrometric data storehouse, differentiate that whether unknown edible oil sample is the class in edible oil standard sample according to the score of each major component.
2. a kind of edible oil discrimination method based on mass spectrum and principal component analysis (PCA) according to claim 1, is characterized in that: described mass spectrophotometry adopts solute migration electron spray ionisation method to carry out mass spectrophotometry.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410841302.1A CN104569132A (en) | 2014-12-29 | 2014-12-29 | Edible oil identification method based on mass spectrum and principal component analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410841302.1A CN104569132A (en) | 2014-12-29 | 2014-12-29 | Edible oil identification method based on mass spectrum and principal component analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104569132A true CN104569132A (en) | 2015-04-29 |
Family
ID=53085694
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410841302.1A Pending CN104569132A (en) | 2014-12-29 | 2014-12-29 | Edible oil identification method based on mass spectrum and principal component analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104569132A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106442767A (en) * | 2016-08-31 | 2017-02-22 | 四川恒康植物油脂有限公司 | Method for identifying quality of rapeseed oil |
| TWI612304B (en) * | 2016-11-15 | 2018-01-21 | 財團法人食品工業發展硏究所 | Method for distinguishing whether grease is degraded |
| CN108780065A (en) * | 2016-03-14 | 2018-11-09 | 株式会社岛津制作所 | Analytical data of mass spectrum resolver and analytical data of mass spectrum parsing program |
| CN115436539A (en) * | 2022-09-20 | 2022-12-06 | 浙江工商大学 | Tuna variety and part identification method based on lipidomics analysis method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2221611A1 (en) * | 2009-02-12 | 2010-08-25 | Testo AG | System for monitoring quality of cooking oil |
| CN102636554A (en) * | 2012-04-24 | 2012-08-15 | 河北工业大学 | Method for identifying drainage oil |
| CN103293118A (en) * | 2013-05-11 | 2013-09-11 | 江南大学 | Hogwash oil identification method based on near infrared reflectance spectroscopy |
| CN103743851A (en) * | 2014-02-14 | 2014-04-23 | 中国农业科学院油料作物研究所 | Single-column two-dimensional liquid chromatography-mass spectrometry analysis method for triglyceride in edible oil and application of method |
| CN103901094A (en) * | 2014-04-22 | 2014-07-02 | 武汉矽感科技有限公司 | Oil detection and identification method based on ion mobility spectrometer |
| CN104089926A (en) * | 2014-07-18 | 2014-10-08 | 湖南省食品测试分析中心 | NIR (Near Infrared Ray) spectral analysis model and method for identifying excessive content of cadmium in rice |
| CN104155359A (en) * | 2014-08-22 | 2014-11-19 | 中国农业科学院油料作物研究所 | Edible vegetable oil authenticity quick screening method based on ionic migration spectrometry |
-
2014
- 2014-12-29 CN CN201410841302.1A patent/CN104569132A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2221611A1 (en) * | 2009-02-12 | 2010-08-25 | Testo AG | System for monitoring quality of cooking oil |
| CN102636554A (en) * | 2012-04-24 | 2012-08-15 | 河北工业大学 | Method for identifying drainage oil |
| CN103293118A (en) * | 2013-05-11 | 2013-09-11 | 江南大学 | Hogwash oil identification method based on near infrared reflectance spectroscopy |
| CN103743851A (en) * | 2014-02-14 | 2014-04-23 | 中国农业科学院油料作物研究所 | Single-column two-dimensional liquid chromatography-mass spectrometry analysis method for triglyceride in edible oil and application of method |
| CN103901094A (en) * | 2014-04-22 | 2014-07-02 | 武汉矽感科技有限公司 | Oil detection and identification method based on ion mobility spectrometer |
| CN104089926A (en) * | 2014-07-18 | 2014-10-08 | 湖南省食品测试分析中心 | NIR (Near Infrared Ray) spectral analysis model and method for identifying excessive content of cadmium in rice |
| CN104155359A (en) * | 2014-08-22 | 2014-11-19 | 中国农业科学院油料作物研究所 | Edible vegetable oil authenticity quick screening method based on ionic migration spectrometry |
Non-Patent Citations (1)
| Title |
|---|
| 方小伟 等: "表面解吸常压化学电离质谱法快速筛查劣质食用油", 《现代科学仪器》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108780065A (en) * | 2016-03-14 | 2018-11-09 | 株式会社岛津制作所 | Analytical data of mass spectrum resolver and analytical data of mass spectrum parsing program |
| CN108780065B (en) * | 2016-03-14 | 2021-03-19 | 株式会社岛津制作所 | Mass spectrometry data analysis device, method, and non-transitory computer-readable medium |
| CN106442767A (en) * | 2016-08-31 | 2017-02-22 | 四川恒康植物油脂有限公司 | Method for identifying quality of rapeseed oil |
| TWI612304B (en) * | 2016-11-15 | 2018-01-21 | 財團法人食品工業發展硏究所 | Method for distinguishing whether grease is degraded |
| CN115436539A (en) * | 2022-09-20 | 2022-12-06 | 浙江工商大学 | Tuna variety and part identification method based on lipidomics analysis method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Li et al. | A combination of chemometrics methods and GC–MS for the classification of edible vegetable oils | |
| CN104569132A (en) | Edible oil identification method based on mass spectrum and principal component analysis | |
| CN107328842B (en) | Based on mass spectrogram without mark protein quantitation methods | |
| US20180364210A1 (en) | Edible oil analysis system and method | |
| CN105486744B (en) | Identify the method for edible oil | |
| CN102749315A (en) | Method for rapidly detecting hogwash oil by synchronous fluorescence spectrum | |
| CN106932510A (en) | The sorting technique of one vegetable oil | |
| CN102998350B (en) | Method for distinguishing edible oil from swill-cooked dirty oil by electrochemical fingerprints | |
| Pereira et al. | Precision in petroleomics via ultrahigh resolution electrospray ionization fourier transform ion cyclotron resonance mass spectrometry | |
| Alves et al. | Electrospray ionization mass spectrometry and partial least squares discriminant analysis applied to the quality control of olive oil | |
| CN102636554B (en) | Method for identifying drainage oil | |
| CN110702483B (en) | Pretreatment method for identifying seafood or meat at ultra-fast speed | |
| Han et al. | Benefit of the use of GCxGC/MS profiles for 1D GC/MS data treatment illustrated by the analysis of pyrolysis products from east Asian handmade papers | |
| Gornushkin et al. | Linear correlation for identification of materials by laser induced breakdown spectroscopy: Improvement via spectral filtering and masking | |
| CN116541750A (en) | Identification method of coix seed origin, terminal equipment and storage medium | |
| CN103616449A (en) | Method for identifying kitchen waste oil | |
| CN104677854A (en) | Method for near infrared rapid recognition of olive oil and rapeseed oil doped in olive oil | |
| CN104360004B (en) | Method for combining LC-Q-TOF ((liquid chromatography-quadrupole-time offlight mass spectrometer) with statistic analysis to identify true-false of edible bird nest | |
| CN209606321U (en) | A kind of peanut oil doping soybean oil discriminating gear of double excitation LIF technology | |
| KR101468581B1 (en) | Standard marker for determining place of origin or age of processed ginseng, establishing method thereof, or method for determining place of origin or age using the same | |
| CN110554106B (en) | Identification method for adulteration of vegetable oil | |
| CN110208358A (en) | A kind of high-frequency vibration atomization ionization probe device and method | |
| CN114720551B (en) | Method for rapidly identifying aging years of pericarpium citri reticulatae by fusing multiple sample introduction modes | |
| CN113125546B (en) | Hair mass spectrum detection chip and hair rapid identification method | |
| Lu et al. | A review: role of mass spectrometry in the quality and authenticity identification of olive oil |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20150429 |