CN101975788B - Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) - Google Patents
Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) Download PDFInfo
- Publication number
- CN101975788B CN101975788B CN2010102688253A CN201010268825A CN101975788B CN 101975788 B CN101975788 B CN 101975788B CN 2010102688253 A CN2010102688253 A CN 2010102688253A CN 201010268825 A CN201010268825 A CN 201010268825A CN 101975788 B CN101975788 B CN 101975788B
- Authority
- CN
- China
- Prior art keywords
- oil
- oils
- quality
- sample
- test
- 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.)
- Active
Links
Images
Landscapes
- Edible Oils And Fats (AREA)
Abstract
The invention discloses a method for identifying the quality of edible oil with low-field NMR (Nuclear Magnetic Resonance), suitable for identifying and measuring genuine edible oil and inferior drainage oil. The method rapidly and accurately identifies the genuine edible oil and the inferior drainage oil by using the difference between the relaxation time map data of the genuine edible oil and the inferior drainage oil as a main identification reference, using NMR signals of the genuine edible oil and the inferior drainage oil as main observation objects and using the comparison and the analysis of the transversal relaxation time map data of the genuine edible oil and the inferior drainage oil as main measures. The method of the invention has high measuring result accuracy, good repetition and stability, short duration, and the like, is beneficial to the realization of the one-site identification of the qualities of various kinds of edible oil and provides reliable oil quality information for detecting the qualities of various kinds of edible oil.
Description
Technical field
The invention belongs to low-field nuclear magnetic resonance oils attributional analysis field, be specifically related to the method that a kind of low-field nuclear magnetic resonance is differentiated the edible oil quality.
Background technology
The food that a certain amount of edible oil of feed that people every day is all direct or indirect or edible oil were handled.The quality of edible oil is directly related with health with human diseases.In recent years, all parts of the country the lawless person occurs and collect food and beverage waste oil and grease or poor oil (waste oil), after the processed, sell eating house, grease workshop with knockout price, mix in the edible oil and reap staggering profits.The waste oil complicated component contains multiple poisonous and harmful element.
Though the multinomial physical and chemical index of waste oil all is different from normal edible oil and fat,, be difficult to distinguish with oil with common edible from outward appearance and sense organ through " waste oil " of refining.The waste oil detection method has much at present, but has the defective (separate sources " waste oil " characteristics are different) that can not use a kind of detection method to detect all sources " waste oil ".And it is big to detect error, and the possibility of erroneous judgement is arranged.If " waste oil " mixes content more after a little while, then can't detect.Therefore, in order to ensure edible oil quality safety, press for a kind of waste oil of can differentiating fast and mix the reliable detection method of pseudo-edible oil.
Nowadays, catering industry consumes a large amount of edible oils every day, but the quality of oil never has better approach and means are tested.Also emerged in large numbers various low grade oilses on the market, wherein waste oil just belongs to wherein a kind of.
The low-field nuclear magnetic resonance analytical technology can be distinguished the difference of certified products edible oil and waste oil fast and accurately through relaxation time spectrum data analysis.Survey pseudo-measuring method with traditional grease and compare, nuclear magnetic resonance method can keep the integrality of sample, is a kind of nondestructive detection means; Method of operating is simply quick, measures accurately, and repeatability is high; Sample need not to add solvent, and quantitative measurement need not standard specimen; Measurement result does not receive the influence of sample of material size and appearance luster, and operator's technology and decision influence are less.Therefore, nuclear magnetic resonance technique is that a kind of very potential grease is surveyed pseudo-new technology fast.
The present invention is fully recognized that importance and the necessity that the edible oil quality is differentiated; And recognized the huge advantage that NMR relaxation time series analysis method is differentiated in the oils quality; Adopt the relaxation time spectrum data to differentiate that oil quality can not only improve detection speed and accuracy greatly, also making on-the-spot oil quality identify simultaneously becomes possibility.
Summary of the invention
The present invention seeks to: provide a kind of low-field nuclear magnetic resonance to differentiate the method for edible oil quality; This method not only can be suitable for the quality measurement of various edible oils; And test speed is fast, accuracy is high, good stability; Be a kind of can really applying in the middle of the actual edible oils quality discriminating work, effective waste oil is mixed pseudo-edible oil quality and is differentiated detection method.
Technical scheme of the present invention is: a kind of low-field nuclear magnetic resonance is differentiated the method for edible oil quality; It is characterized in that the oils sample that at first is directed against different qualities carries out the NMR signal collection under identical parameters; Utilize T2 spectrum and T2 and diffusion coefficient correlation spectrum that known standard specimen is analyzed; Find out the nuclear magnetic resonance test data difference of different quality oils samples, and same quality oils sample is carried out the reperformance test checking; Based on the result who analyzes test data and oils quality are carried out correspondingly then, confirm the correlation of oils quality and nuclear magnetic resonance data; Then, set up oils attribute test database, and form the analytical test standard based on the test data of different quality oils; At last, through the test data in the database unknown oils sample being carried out quality identifies.
The implementation step that the inventive method is concrete is following:
1) sample test analysis: be listed as through cpmg sequence certified products oil, poor oil are carried out the transverse relaxation analysis; And adopt the anti-Laplce's algorithm of one dimension to compose inversion algorithm as T2; Draw the relaxation time spectrum of certified products oil and poor oil; If the relaxation time spectrum of the two is not exclusively overlapping, then the miscella to them carries out the transverse relaxation analysis, and draws relaxation time spectrum; If certified products oil still exists in miscella with the poor oil non-overlapping portions, and proportional with poor oil content in the miscella, then select this part as oils quality judging standard; If certified products oil exists in miscella with the poor oil non-overlapping portions but is disproportionate with miscella; Then certified products oil, poor oil and their miscella three are carried out T2 and coefficient of diffusion correlation analysis through the PGSE-CPMG sequence; And adopt two-dimentional anti-Laplce's algorithm as T2 and coefficient of diffusion correlativity spectrum inversion algorithm; Draw T2 and the coefficient of diffusion correlativity spectrum of certified products oil, liquid inferior and miscella thereof, find in this spectrum fully independently certified products oil or poor oil composition as oils quality judging standard;
2) standard specimen reperformance test: above like the described test analysis of step 1) through the certified products oil of same quality or poor oil sample being carried out twice; With twice or the error of test data repeatedly before and after understanding, thereby understand the probability of miscarriage of justice of low-field nuclear magnetic resonance method in the edible oil quality is identified;
3) the sample data storehouse is set up: after oils quality judging standard is established; Carry out corresponding with the oils quality test data based on analysis result; Confirm the correlation of oils quality and nuclear magnetic resonance data; Then, set up oils attribute test database, with the formation of convenient edible oil quality measurement and industry testing standard based on the nuclear magnetic resonance test data of different quality oils samples;
4) sample measurement: utilize the test data of the database the inside of step 3) foundation that unknown oils sample is carried out the quality evaluation.
Can carry out temperature variation testing to certified products oil, poor oil and miscella thereof simultaneously in the said step 1) of the inventive method; Said temperature variation testing is meant the oils sample is heated up or cooling test; To draw the influence of temperature to different oils qualities; And find out correlativity, thereby confirm the correlativity of oils quality and temperature.
The said step 3) of the inventive method specifically is according to determined oils quality judging standard; The ratio that accounts for the bulk sample signal with this part signal in the miscella is Y; Certified products oil in the miscella or poor oil content are X; Carry out the once linear match and obtain fitting a straight line y=kX+b, then y is the measured value of Y; According to the mode analytic sample of standard specimen signal measurement, find the corresponding sample signal y in standard specimen signal area; Utilize certified products oil or poor oil content X in the y value calculation sample that obtains in calibration line and the sample analysis, thereby find out the difference of different quality oils samples and set up oils attribute test database with this.
The cpmg sequence row that relate in the inventive method are to be used for the conventional nuclear-magnetism pulse train that transverse relaxation is analyzed; The PGSE-CPMG sequence then is to be used for transverse relaxation and the conventional nuclear-magnetism pulse train that spreads correlation analysis; The anti-Laplce's algorithm of one dimension that relates among the present invention simultaneously is the conventional algorithm that is used for the relaxation time spectrum inverting; And two-dimentional anti-Laplce's algorithm is the conventional algorithm that is used for T2 and the inverting of coefficient of diffusion correlativity spectrum.
Advantage of the present invention is:
1. the inventive method can guarantee fast and accurately edible oil sample is carried out the nuclear magnetic resonance spectroscopy test, so that understand the quality of edible oil sample, thereby differentiates low grade oils fast and accurately, for people's diet provides quality assurance.Compare with traditional method, the inventive method has not only improved detection speed, and accuracy that detects and also raising greatly of stability.
2, the inventive method is fast for the detection speed of edible oil sample quality, weak point consuming time, and whole test basically can be at 4 minutes with interior completion.
Description of drawings
Fig. 1 is the relaxation time spectrum of pure soy bean sample;
Fig. 2 is the soybean oil sample relaxation time spectrum behind the adding 2% frying oil sample;
Fig. 3 is the soybean oil sample relaxation time spectrum behind the adding 5% frying oil sample;
Fig. 4 is the soybean oil sample relaxation time spectrum behind the adding 10% frying oil sample;
Fig. 5 is the soybean oil sample relaxation time spectrum behind the adding 20% frying oil sample;
Fig. 6 is the soybean oil sample relaxation time spectrum behind the adding 50% frying oil sample;
Fig. 7 is the soybean oil sample relaxation time spectrum behind the adding 100% frying oil sample;
Fig. 8 is old oil content of frying and small peak ratio correlation figure.
Embodiment
Embodiment: the invention discloses the method that a kind of low-field nuclear magnetic resonance is differentiated the edible oil quality, its practical implementation step is following:
1) sample test analysis: be listed as through cpmg sequence certified products oil, poor oil are carried out the transverse relaxation analysis; And adopt the anti-Laplce's algorithm of one dimension to compose inversion algorithm as T2; Draw the relaxation time spectrum of certified products oil and poor oil; If the relaxation time spectrum of the two is not exclusively overlapping, then the miscella to them carries out the transverse relaxation analysis, and draws relaxation time spectrum; If certified products oil still exists in miscella with the poor oil non-overlapping portions, and proportional with poor oil content in the miscella, then select this part as oils quality judging standard; If certified products oil exists in miscella with the poor oil non-overlapping portions but is disproportionate with miscella; Then certified products oil, poor oil and their miscella three are carried out T2 and coefficient of diffusion correlation analysis through the PGSE-CPMG sequence; And adopt two-dimentional anti-Laplce's algorithm as T2 and coefficient of diffusion correlativity spectrum inversion algorithm; Draw T2 and the coefficient of diffusion correlativity spectrum of certified products oil, liquid inferior and miscella thereof, find in this spectrum fully independently certified products oil or poor oil composition as oils quality judging standard;
2) standard specimen reperformance test: above like the described test analysis of step 1) through the certified products oil of same quality or poor oil sample being carried out twice; With twice or the error of test data repeatedly before and after understanding, thereby understand the probability of miscarriage of justice of low-field nuclear magnetic resonance method in the edible oil quality is identified;
3) the sample data storehouse is set up: after oils quality judging standard is established; Carry out corresponding with the oils quality test data based on analysis result; Confirm the correlation of oils quality and nuclear magnetic resonance data; Then, set up oils attribute test database, with the formation of convenient edible oil quality measurement and industry testing standard based on the nuclear magnetic resonance test data of different quality oils samples;
4) sample measurement: utilize the test data of the database the inside of step 3) foundation that unknown oils sample is carried out the quality evaluation.
Can carry out temperature variation testing to certified products oil, poor oil and miscella thereof simultaneously in the said step 1); Said temperature variation testing is that finger is heated up the oils sample or cooling test; To draw the influence of temperature to different oils qualities; And find out correlativity, thereby confirm the correlativity of oils quality and temperature.
Said step 3) specifically is according to determined oils quality judging standard; The ratio that accounts for the bulk sample signal with this part signal in the miscella is Y; Certified products oil in the miscella or poor oil content are X, carry out the once linear match and obtain fitting a straight line y=kX+b, and then y is the measured value of Y; According to the mode analytic sample of standard specimen signal measurement, find the corresponding sample signal y in standard specimen signal area; Utilize certified products oil or poor oil content X in the y value calculation sample that obtains in calibration line and the sample analysis, thereby find out the difference of different quality oils samples and set up oils attribute test database with this.
The cpmg sequence row that relate in the inventive method are to be used for the conventional nuclear-magnetism pulse train that transverse relaxation is analyzed; The PGSE-CPMG sequence then is to be used for transverse relaxation and the conventional nuclear-magnetism pulse train that spreads correlation analysis; The anti-Laplce's algorithm of one dimension that relates among the present invention simultaneously is the conventional algorithm that is used for the relaxation time spectrum inverting; And two-dimentional anti-Laplce's algorithm is the conventional algorithm that is used for T2 and the inverting of coefficient of diffusion correlativity spectrum.
Below for adopting said method to carry out the concrete Test Example that the edible oil quality is differentiated:
One, the purpose of this test is:
1, the NMR signal difference of the different quality oil of test;
2, the poor oil that in certified products oil, adds different amounts, the detection signal difference, and find out the method for testing that adds poor oil content in the certified products oil;
3, set up the test model of nuclear-magnetism and oil quality;
Two, test material
The old oil of frying behind selection certified products soybean oil, the frying flour, nuclear-magnetism test tube, no nuclear magnetic signal bottle
Three, test apparatus
MicroMR magnetic resonance imaging analysis appearance
Four, the preparation of test specimen
1,7 oil samples altogether comprise the pure soy bean sample, and other six samples make for the old oil of frying that in certified products soybean oil sample, adds 2%, 5%, 10%, 20%, 50,100% mass parts respectively; 2, the quality of all oil samples is all identical; 3, all oil samples are all put into same type and are not had the bottle of nuclear magnetic signal;
Five, process of the test
Adopt MicroMR magnetic resonance imaging analysis appearance that sample is carried out test analysis; The T2 that specifically is 7 samples of employing cpmg sequence row measurement earlier is after the relaxation time; Adopt the anti-Laplce's algorithm of one dimension to compose inversion algorithm again, draw the relaxation time spectrum of each sample, see Fig. 1～Fig. 7 as T2; From 7 width of cloth figure, can see; The main difference of the sample behind pure soy bean sample and the old oil of adding frying is to add a short relaxation can appear in the oily always sample of frying in test result small peak; All indicate the small peak ratio among Fig. 2 to Fig. 7 and accounted for the relation of resultant signal ratio; Can see, when in the pure soy bean sample, adding the old oil of frying of different content, along with the increase of the old oily addition of frying; The area of small peak is also increasing gradually, and what following form disclosed is the pairing variation tendency of small peak:
Fry old oil content (%) small peak signal proportion (%)
0 0
2 0.25
5 0.36
10 0.68
20 0.9
50 2.38
100 5.18
Can find out from last table data; Along with the increase of the old oil content of frying, the small peak proportion is also increasing gradually, and Fig. 8 is old oil content of frying and small peak ratio correlation figure; The ratio that accounts for the bulk sample signal with each small peak in the miscella is Y; The old oil content of frying in the miscella is X, carries out the once linear match and obtains fitting a straight line y=0.0502X+0.0506, and y is the measured value of Y; Content and the little peak area that can find out the old oil of frying demonstrate extraordinary correlativity.Analyze oils quality sample (non-test is prepared) at random according to the mode of standard specimen signal measurement, find the corresponding sample signal y in standard specimen signal area; Utilize the old oil content X of frying in the y value calculation sample that obtains in calibration line and the sample analysis; Thereby find out the difference of different quality oils samples and set up oils attribute test database, with the formation of convenient edible oil quality measurement and industry testing standard with this; Thereby find out the difference of different quality oils samples and set up oils attribute test database with this.Utilize the test data of the database the inside of above-mentioned foundation that unknown oils sample is carried out the quality evaluation at last.
Above-mentioned experiment can prove low nuclear-magnetism method of testing can record in the certified products soybean oil, add 2% or the old oil of above frying after oil quality differentiate, and accurately in the specimen institute adds the oily always content of frying.The Blind Test checking is carried out in suggestion.From test data and test result; Low-field nuclear magnetic resonance differentiates that the method for edible oil quality is a kind of method of testing very quickly and easily; And can obtain accurate test data, a kind of detection method of quick nondestructive is provided for oil quality analysis and Quality Detection.
Claims (3)
1. a low-field nuclear magnetic resonance is differentiated the method for edible oil quality; It is characterized in that the oils sample that at first is directed against different qualities carries out the NMR signal collection under identical parameters; Utilize T2 spectrum and T2 and diffusion coefficient correlation spectrum that known standard specimen is analyzed; Find out the nuclear magnetic resonance test data difference of different quality oils samples, and same quality oils sample is carried out the reperformance test checking; Based on the result who analyzes test data and oils quality are carried out correspondingly then, confirm the correlation of oils quality and nuclear magnetic resonance data; Then, set up oils attribute test database, and form the analytical test standard based on the test data of different quality oils; At last, through the test data in the database unknown oils sample being carried out quality identifies;
The practical implementation step of said method is following:
1) sample test analysis: be listed as through cpmg sequence certified products oil, poor oil are carried out the transverse relaxation analysis; And adopt the anti-Laplce's algorithm of one dimension to compose inversion algorithm as T2; Draw the relaxation time spectrum of certified products oil and poor oil; If the relaxation time spectrum of the two is not exclusively overlapping, then the miscella to them carries out the transverse relaxation analysis, and draws relaxation time spectrum; If certified products oil still exists in miscella with the poor oil non-overlapping portions, and proportional with poor oil content in the miscella, then select this part as oils quality judging standard; If certified products oil exists in miscella with the poor oil non-overlapping portions but is disproportionate with miscella; Then certified products oil, poor oil and their miscella three are carried out T2 and coefficient of diffusion correlation analysis through the PGSE-CPMG sequence; And adopt two-dimentional anti-Laplce's algorithm as T2 and coefficient of diffusion correlativity spectrum inversion algorithm; Draw T2 and the coefficient of diffusion correlativity spectrum of certified products oil, poor oil and miscella thereof, find in this spectrum fully independently certified products oil or poor oil composition as oils quality judging standard;
2) standard specimen reperformance test: above like the described test analysis of step 1) through the certified products oil of same quality or poor oil sample being carried out twice; With twice or the error of test data repeatedly before and after understanding, thereby understand the probability of miscarriage of justice of low-field nuclear magnetic resonance method in the edible oil quality is identified;
3) the sample data storehouse is set up: after oils quality judging standard is established; Carry out corresponding with the oils quality test data based on analysis result; Confirm the correlation of oils quality and nuclear magnetic resonance data; Then, set up oils attribute test database, with the formation of convenient edible oil quality measurement and industry testing standard based on the nuclear magnetic resonance test data of different quality oils samples;
4) sample measurement: utilize the test data of the database the inside of step 3) foundation that unknown oils sample is carried out the quality evaluation.
2. low-field nuclear magnetic resonance according to claim 1 is differentiated the method for edible oil quality; It is characterized in that to carry out temperature variation testing to certified products oil, poor oil and miscella thereof simultaneously in the said step 1); Said temperature variation testing is that finger is heated up the oils sample or cooling test; Drawing the influence of temperature, and find out correlativity, thereby confirm the correlativity of oils quality and temperature different oils qualities.
3. low-field nuclear magnetic resonance according to claim 1 is differentiated the method for edible oil quality; It is characterized in that said step 3) specifically is according to determined oils quality judging standard; The ratio that accounts for the bulk sample signal with this part signal in the miscella is Y; Certified products oil in the miscella or poor oil content are X, carry out the once linear match and obtain fitting a straight line y=kX+b, and then y is the measured value of Y; According to the mode analytic sample of standard specimen signal measurement, find the corresponding sample signal y in standard specimen signal area; Utilize certified products oil or poor oil content X in the y value calculation sample that obtains in calibration line and the sample analysis, thereby find out the difference of different quality oils samples and set up oils attribute test database with this.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010102688253A CN101975788B (en) | 2010-09-01 | 2010-09-01 | Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010102688253A CN101975788B (en) | 2010-09-01 | 2010-09-01 | Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101975788A CN101975788A (en) | 2011-02-16 |
| CN101975788B true CN101975788B (en) | 2012-02-15 |
Family
ID=43575691
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2010102688253A Active CN101975788B (en) | 2010-09-01 | 2010-09-01 | Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101975788B (en) |
Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102269720A (en) * | 2011-04-28 | 2011-12-07 | 王士桥 | Method for identifying edible oil quality through combination of nuclear magnetic resonance and pattern recognition method |
| KR101287426B1 (en) | 2011-10-26 | 2013-07-18 | 한국표준과학연구원 | Target Discrimination Method by using Ultra-Low Field NMR and Ultra-Low Field NMR Target Discrimination Apparatus |
| CN102706915B (en) * | 2012-06-28 | 2016-04-27 | 厦门大学 | A kind of detection method of waste oil |
| CN103674994B (en) * | 2012-09-21 | 2016-04-13 | 苏州纽迈分析仪器股份有限公司 | The method for building up of gelatin standard database and system, gelatin discrimination method and system |
| CN103792247B (en) * | 2012-11-02 | 2016-03-23 | 上海理工大学 | The low-field nuclear magnetic resonance detection method of soybean oil frying operating limit |
| CN103207200B (en) * | 2013-03-08 | 2016-05-04 | 厦门大学 | Judge the method for waste oil by characterization compound relative amount |
| CN103344661B (en) * | 2013-07-05 | 2016-02-24 | 上海适济生物科技有限公司 | A kind of method using hydrogen nuclear magnetic resonance method to identify adulterated oil and waste oil |
| CN103399028A (en) * | 2013-07-24 | 2013-11-20 | 厦门大学 | Detection method of juice |
| CN104713895B (en) * | 2015-03-13 | 2017-01-18 | 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 |
| CN107014846A (en) * | 2016-01-27 | 2017-08-04 | 沈阳药科大学 | A kind of method for detecting vegetable oil Overheating Treatment and application thereof |
| CN105806872A (en) * | 2016-04-29 | 2016-07-27 | 大连工业大学 | Method for identifying different sturgeon roes by low field nuclear magnetism technology |
| CN107505350A (en) * | 2017-10-20 | 2017-12-22 | 河南工业大学 | A kind of grape-kernel oil based on low field nuclear-magnetism mixes pseudo- method for quick identification |
| CN107941837A (en) * | 2017-11-14 | 2018-04-20 | 山东省分析测试中心 | The method that low-field nuclear magnetic resonance differentiates donkey-hide gelatin quality |
| CN108120944B (en) * | 2017-11-16 | 2019-12-06 | 上海理工大学 | weighted iterative low-field nuclear magnetic resonance T2 spectrum inversion algorithm |
| CN109540957A (en) * | 2018-12-29 | 2019-03-29 | 北京泓泰天诚科技有限公司 | A kind of Permanent magnetic MR spectrometer |
| CN112305003A (en) * | 2019-07-31 | 2021-02-02 | 上海纽迈电子科技有限公司 | Edible oil analysis model establishment method, edible oil analysis method and edible oil analysis device |
| CN111189868B (en) * | 2020-02-18 | 2021-06-15 | 南京农业大学 | Method for rapidly screening adulterated illegal cooking oil in edible oil by using low-field nuclear magnetic resonance |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101526489A (en) * | 2008-03-04 | 2009-09-09 | 普拉德研究及开发股份有限公司 | Method for detecting contents of paraffin and asphaltene in oil |
| CN101713754A (en) * | 2009-11-20 | 2010-05-26 | 中国石化集团华北石油局 | Method for analyzing oil mass fraction of drilling well fluid by nuclear magnetic resonance |
-
2010
- 2010-09-01 CN CN2010102688253A patent/CN101975788B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101526489A (en) * | 2008-03-04 | 2009-09-09 | 普拉德研究及开发股份有限公司 | Method for detecting contents of paraffin and asphaltene in oil |
| CN101713754A (en) * | 2009-11-20 | 2010-05-26 | 中国石化集团华北石油局 | Method for analyzing oil mass fraction of drilling well fluid by nuclear magnetic resonance |
Also Published As
| Publication number | Publication date |
|---|---|
| CN101975788A (en) | 2011-02-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101975788B (en) | Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) | |
| CN102636510B (en) | Proton nmr spectra detects the method for edible oil quality | |
| CN104122225B (en) | The illegal additive discrimination method of a kind of Folium Camelliae sinensis based on near-infrared spectrum technique | |
| CN101943669B (en) | Method for measuring oil content of drilling fluid through low-field NMR (Nuclear Magnetic Resonance) | |
| CN101398412B (en) | Gas-chromatography fingerprinting for rapidly identifying edible oil | |
| CN103245628B (en) | The method for quick of food plant oil quality | |
| CN104198518A (en) | Method for true and false identification and content determination of sesame oil | |
| CN102735642B (en) | Method for quickly and losslessly identifying virgin olive oil and olive-residue oil | |
| CN103412047B (en) | A kind of method of True-false distinguish of metal by ultrasonic non-destructive detection method | |
| Cai et al. | An expert system based on 1H NMR spectroscopy for quality evaluation and adulteration identification of edible oils | |
| CN103792198A (en) | Intermediate infrared-near infrared correlation spectrum discriminating method for melamine-doped milk | |
| CN103645155A (en) | Quick nondestructive testing method for tenderness of fresh mutton | |
| CN102565169A (en) | Electrochemical fingerprint chromatogram identification method for edible oil | |
| CN103712948B (en) | The fast non-destructive detection method of TVB-N content in fresh Carnis caprae seu ovis | |
| CN106556680A (en) | Method for rapidly predicting fat oxidation degree of meat and meat product based on electronic nose technology | |
| CN202049112U (en) | Pearl quality detecting device | |
| CN103575765A (en) | Method for rapidly detecting mutton adulteration | |
| CN111443173A (en) | Method for detecting adulterated illegal cooking oil in edible peanut oil based on electronic nose method | |
| CN102901744A (en) | Method for detecting authenticity of peanut oil | |
| CN105807017A (en) | Method for discriminating ham grades by using electronic nose | |
| Muniz et al. | Using 1H low-field NMR relaxometry to detect the amounts of Robusta and Arabica varieties in coffee blends | |
| CN103048313A (en) | Method for identifying tea picking time by use of inductively coupled plasma spectroscopy (ICP) | |
| CN102901745B (en) | A kind of discrimination method of olive oil | |
| CN105372224A (en) | Method for identifying different species of feed grease based on Fourier Ramman spectrum | |
| Ding et al. | Detection of fruits in warehouse using Electronic nose |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C56 | Change in the name or address of the patentee | ||
| CP03 | Change of name, title or address |
Address after: 215000 Jiangsu province Suzhou New District kolding Road No. 78 Su Gaoxin Software Park Building No. 2 Patentee after: SUZHOU NIUMAG ELECTRONIC TECHNOLOGY CO., LTD. Patentee after: University of Shanghai for Science and Technology Patentee after: Shanghai Niumag Electronic Technology Co., Ltd. Address before: 215163, room 2, building 101, Dalian Software Park, Suzhou science and technology zone, Suzhou New District, Jiangsu Patentee before: Suzhou Niumai Electronics Co., Ltd. Patentee before: University of Shanghai for Science and Technology Patentee before: Shanghai Niumag Electronic Technology Co., Ltd. |