CN102636510B - Proton nmr spectra detects the method for edible oil quality - Google Patents

Proton nmr spectra detects the method for edible oil quality Download PDF

Info

Publication number
CN102636510B
CN102636510B CN201210123448.3A CN201210123448A CN102636510B CN 102636510 B CN102636510 B CN 102636510B CN 201210123448 A CN201210123448 A CN 201210123448A CN 102636510 B CN102636510 B CN 102636510B
Authority
CN
China
Prior art keywords
oil
edible oil
certified products
nmr spectra
proton nmr
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
Application number
CN201210123448.3A
Other languages
Chinese (zh)
Other versions
CN102636510A (en
Inventor
王强
余学军
李中贤
梁志宏
郭晓河
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
High and New Technology Research Center of Henan Academy of Sciences
Original Assignee
High and New Technology Research Center of Henan Academy of Sciences
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by High and New Technology Research Center of Henan Academy of Sciences filed Critical High and New Technology Research Center of Henan Academy of Sciences
Priority to CN201210123448.3A priority Critical patent/CN102636510B/en
Publication of CN102636510A publication Critical patent/CN102636510A/en
Application granted granted Critical
Publication of CN102636510B publication Critical patent/CN102636510B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Edible Oils And Fats (AREA)
  • Fats And Perfumes (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

The invention discloses a kind of method utilizing proton nmr spectra to detect edible oil quality, belong to food detection method field.First the method carries out NMR signal collection for the oils sample of different quality under identical parameter, then integration is carried out to the collection of illustrative plates collected, utilize integrated value to calculate the data such as content and iodine number of the various fatty acid such as saturated fatty acid, oleic acid, linoleic acid, find out the feature of different grease; Reperformance test is carried out to same quality oil sample; Set up oils attribute test database according to the test data of different quality oils, and form analytical test standard; Finally, by the test data in database, Quality Identification is carried out to unknown oils sample.The inventive method have simple to operate, accuracy is high, reproducible, quick economic dispatch advantage, the discriminating being applicable to certified products edible oil or mixing pseudo-edible oil detects, and can differentiate the kind of edible oil.

Description

Proton nmr spectra detects the method for edible oil quality
Technical field
The invention belongs to food detection method field, be specifically related to the method for nuclear magnetic resonance map detection and identification edible oil quality.
Background technology
Along with developing rapidly of the tertiary industry, China's catering trade scale expanding day, the waste grease of discharging in food and drink waste water is increasing, and lawless person illegally reclaims refinement to these waste greases, poisonous " waste oil " just gets back to dining table again, is detrimental to health.Waste oil generally comprises swill oil, frying oil and discarded animal fat, about the quick detection of waste oil, there are technology or the method for several types in the market, there is the paper chromatography based on detecting conductivity and polar compound total amount, thin-layer chromatography, sensor method for quick, also the method for quick based on detecting heavy-metal pollution thing is had, also have based on detection waste oil acid value, the method for quick such as peroxide value, these methods respectively have superiority in application, the qualitative detection of waste oil can be carried out to a certain extent, but also existing defects, the ratio of mixing waste oil in edible oil generally needs to reach relatively high degree and just can be detected or easily occur false positive (" development and research of waste oil detection technique ", Food technology is with economical, 2011, 36 (1): 41-44, ), (" discrimination method of waste oil ", CN102393426A), such as electrical conductivity method detect lower limit be waste oil addition more than 20%, the lower limit that detects of cholesterol method is that the addition of waste oil is more than 10%, thin layer chromatography is for some not purified oil (such as sesame oil, Chinese prickly ash wet goods) and the oil (as chilli oil) adding other compositions, easily there is false positive, the method that exclusion chromatography (HPSEC) measures triglyceride oxypolymer is applicable to the detection of frying oil, but lower to the accuracy rate of swill oil.Therefore, in order to ensure edible oil quality safety, can differentiate in the urgent need to a kind of the reliable detection method that waste oil mixes pseudo-edible oil fast.Utilize proton nmr spectra to certified products edible oil with mix pseudo-edible oil and carry out discriminating and yet there are no bibliographical information.
Summary of the invention
The object of the invention is to provide that a kind of test speed is fast, accuracy is high, the proton nmr spectra that utilizes that is with low cost, favorable reproducibility differentiates the method for edible oil quality.
The principle of foundation of the present invention is: the edible oil of each kind is all made up of the fatty glyceride substantially determined, even if blending stock, the definite composition of wherein various oil is also known by manufacturer, can calculate its fatty glyceride composition accordingly.But waste oil, due to the problem in source, causes its complicated component changeable, form even if the producer can not talk clearly it, this is the feature that it cannot change.According to this feature, by setting up and the nuclear magnetic resonance map of comparison edible oil, can whether doped with waste oil in the easy edible oil and fat of detection rapidly.
For realizing the object of the invention, first the present invention carries out proton nmr spectra collection for the oils sample of the different quality of variety classes under identical parameters, then integration is carried out to collection of illustrative plates, after the integrated value obtained being calculated according to formula, obtain the eigenwert of different grease; Set up oils qualitative data storehouse according to the proton nmr spectra integrated value of different quality oils or eigenwert, form analytical test standard; By the test data in database, Quality Identification is carried out to unknown oils sample.
The concrete implementation step of the inventive method is as follows:
(1) standard model proton nmr spectra data acquisition: under the same terms, carries out the test of more than twice proton nmr spectra to the certified products edible oil sample of same quality, draws front and back twice or the error of repeatedly test data, correction error; Then repeated proton nmr spectra test is carried out to the certified products edible oil sample of same quality;
(2) standard model data processing: carry out integration to testing the certified products edible oil sample proton nmr spectra obtained, record the integrated value of its hydrogen nuclear magnetic resonance spectrum signature group, utilize its integrated value do X-Y scheme, the three-dimensional plot of integration data or its integrated value is substituted into the eigenwert that formulae discovery obtains certified products edible oil, make the PCA analysis chart of its eigenwert;
(3) foundation of database: under the same terms, tests the proton nmr spectra of a large amount of variety classes different quality certified products edible oils sample, repeats step (2) and process, set up edible oils attribute test database;
(4) sample is differentiated: under the same terms, nuclear magnetic resonance test is carried out to unknown edible oils sample, utilize its hydrogen nuclear magnetic resonance spectrogram of data processing method process of step (2), the edible oils attribute test database model set up with step (3) is compared, Qualitative Identification certified products edible oil or mix pseudo-edible oil, and certified products edible oil kind is judged.
Described certified products edible oil is respectively the mediation wet goods of soybean oil, peanut oil, sesame oil, palm oil, corn oil, rapeseed oil, cottonseed oil, sunflower oil or known composition.
Carry out integration to proton nmr spectra according to shown in accompanying drawing 1, have nine groups of integrated values, the chemical shift of nine groups of protons is respectively: 1,2-5.34ppm, 3-4.23ppm, 4-2.77ppm, 5-2.31ppm, 6-2.04ppm, 7-1.61ppm, 8-1.28ppm, 9-0.98ppm, 10-0.89ppm.
Described edible oils attribute test database is the integration data X-Y scheme of the hydrogen nuclear magnetic resonance spectrum signature group of various conventional certified products edible oil and fat or the PCA analysis chart of three-dimensional plot and various conventional edible certified products oil eigenwert.
Compared with surveying fake method with traditional grease, this method has the following advantages: 1. simplify experimental procedure.In this method, sample does not need to carry out pre-treatment, can directly test; Sample is without the need to weighing quantitatively, because integral area display itself is exactly each group of peak-to-peak ratio; 2. degree of accuracy is high.Collection of illustrative plates collection, process and undertaken by computing machine, and integrating range is also fixing, avoids the error that human factor causes.3. quick economical.Only test detection sample during detection, after carrying out algebraic manipulation, compare with database, detection speed is fast, and consuming time short, whole test can complete in 5 minutes, reduced workload and testing cost.4. widely applicable.Database is later all applicable to the instrument test data of different model different magnetic field.
The method is not only applicable to various edible oil whether doped with the detection of waste oil, and kind differentiation can be carried out to various edible oil, prevent the edible oil pretending to be price high with cheap edible oil, there is the features such as test speed is fast, accuracy is high, with low cost, the work of edible oils quartile length can be actually used in, can differentiate that waste oil mixes pseudo-edible oil effectively, containment is not sent out retailer and is pretended to be expensive edible oil with cheap edible oil, for the healthy diet of people provides quality assurance.
Accompanying drawing explanation
The integrated value Information Monitoring figure of the corresponding proton in each peak in Fig. 1 certified products edible oil nuclear magnetic resonance figure; 1:C in figure h=CH, all unsaturated fatty acids, 2:C h-OCOR triglyceride, 3:C h 2 -OCOR triglyceride, 4:CH=CH-C h 2-CH=CH 2linoleic acid plus linolenic acid chain, 5:C h 2the all fatty acid chains of-COOH, 6:C h 2 the all unsaturated fatty acid chains of-CH=CH, 7:C h 2 -CH 2the all fatty acid chains of COOH, 8:(C h 2 ) nall fatty acid chains, 9:CH=CH-CH 2-C h 3leukotrienes chain, 10:CH 2cH 2cH 2-C h 3all fatty acid chains except leukotrienes;
Fig. 2 is containing the soybean oil at No. 9 peaks and the X-Y scheme database of rapeseed oil; In figure ▲ and soybean oil, ■ rapeseed oil;
Fig. 3 is not containing the various grease X-Y scheme databases at No. 9 peaks; △ peanut oil in figure, ▼ sesame oil, ◆ palm oil, ● corn oil, ◇ cottonseed oil, ▽ sunflower oil;
Fig. 4 utilizes and judges edible oil sample containing No. 9 peak X-Y scheme database analysises; In figure ▲ and soybean oil, ■ rapeseed oil, ★ adds the rapeseed oil of waste oil;
Fig. 5 utilizes and does not judge edible oil sample containing the X-Y scheme database analysis at No. 9 peaks; △ peanut oil in figure, ▼ sesame oil, ◆ palm oil, ● corn oil, ◇ cottonseed oil, ▽ sunflower oil, ★ adds the sunflower oil of 10% waste oil;
The three-dimensional plot database of the various conventional certified products edible oil of Fig. 6; In figure ▲ and soybean oil, △ peanut oil, ▼ sesame oil, ◆ palm oil, ● corn oil, ◇ cottonseed oil, zero rapeseed oil, ▽ sunflower oil;
Fig. 7 analysis chart of three-dimensional plot database to edible oil quality; In figure ▲ and soybean oil, △ peanut oil, ▼ sesame oil, ◆ palm oil, ● corn oil, ◇ cottonseed oil, zero rapeseed oil, ▽ sunflower oil, ★ adds the peanut oil of 10% waste oil;
The PCA analysis chart database-1 of Fig. 8 various certified products edible oil eigenwert; D soybean oil in figure, H peanut oil, X sesame oil, Y corn oil, K sunflower oil;
The PCA analysis chart database-2 of Fig. 9 various certified products edible oil eigenwert; Z palm oil in figure, M cottonseed oil, C rapeseed oil;
Figure 10 utilizes PCA analysis to judge D soybean oil in edible oil sample quality figure-1, figure, H peanut oil, X sesame oil, Y corn oil, K sunflower oil, and DG soybean oil adds 5% waste oil, and XG sesame oil adds 5% waste oil;
Figure 11 utilizes PCA analysis to judge D soybean oil in edible oil sample quality figure-2, figure, H peanut oil, X sesame oil, Y corn oil, K sunflower oil, and WX mixes pseudo-sesame oil;
Figure 12 utilizes and judges edible blend oil sample containing No. 9 peak X-Y scheme database analysises, in figure ▲ soybean oil, ■ rapeseed oil, ● soybean oil, peanut oil, the blending stock of sesame oil 7:2:1 weight ratio, ★ soybean oil, peanut oil, the blending stock of sesame oil 7:2:1 weight ratio adds 10% waste oil.
Embodiment
One, test material
Soybean oil, peanut oil, sesame oil, palm oil, corn oil, cottonseed oil, rapeseed oil, sunflower oil, sample hose, deuterochloroform (CDCl 3).
Two, test apparatus
BRUKERAvance300 NMR spectrometer with superconducting magnet.
Three, the preparation of test specimen
Get soybean oil 20 microlitre, add 0.6mLCDCl 3dissolving is placed in Φin 5mm sample hose, obtain testing sample solution.Using such method obtains 14 portions of soybean oils, 14 portions of peanut oil, 12 parts of sesame oil, 7 parts of palm oils, 6 portions of corn oils, 7 portions of cottonseed oils, 7 portions of rapeseed oils, 7 portions of sunflower oils, 8 portions of blending stocks.
Four, process of the test
1. collection of illustrative plates measures
Condition determination: temperature: 295K, CDCl 3for internal lock, each collection of illustrative plates scans 16 times, spectrum width 20ppm, recurrent interval 2s, pulse train: zg30.
By above-mentioned obtained sample solution working sample in nuclear magnetic resonance analyser 1hNMR collection of illustrative plates, obtains sample free damping signal (FID signal).
2. collection of illustrative plates process and integration
The sample F ID signal obtained by said determination carries out Fourier transform, and line phase of going forward side by side corrects and baseline correction, using the chemical shift 0ppm of TMS as interior mark, and calibration graph.
After correction, proton nmr spectra test is carried out to above-mentioned all kinds of certified products edible oil, carry out integration for soybean oil respectively according to shown in accompanying drawing 1, have nine groups of integrated values, the chemical shift of nine groups of protons is respectively: 1,2-5.34ppm, 3-4.23ppm, 4-2.77ppm, 5-2.31ppm, 6-2.04ppm, 7-1.61ppm, 8-1.28ppm, 9-0.98ppm, 10-0.89ppm, A, B, C, D, E, F, G, H, I represent the area of above-mentioned nine groups of integrations respectively.
The foundation of 3 standard databases
3.1 directly utilize integral area
According to different certified products edible oil grouping, integral area is utilized to set up the database (table 1-9) of different certified products edible oil.
3.2 utilize integrated value to calculate the eigenwerts such as grease composition and iodine number
Bring associated quad value into following formula to calculate:
[ω-3UFA]=H/(H+I)
[ω-6 linoleic acid]=(3C-4H)/3D
[MUFA]=E/2D-H/(H+I)-(3C-4H)/3D
[SFA]=1-E/2D
[IV]=[(A-B/4)/D]×86
In above-mentioned formula, [ω-3UFA] is the ratio of omega-3 unsaturated fatty acid in grease; [ω-6 linoleic acid] is the ratio of linoleic acid in grease; [MUFA] is the ratio of monounsaturated fatty acids in grease; [SFA] is the ratio of saturated fatty acid in grease; The iodine number that [IV] is grease.The result of calculation of various certified products grease eigenwert is listed in table 10-table 18 respectively.
4. data analysis
Two groups or three groups of choosing in the integral area of edible oil and fat hydrogen nuclear magnetic resonance spectrum signature group are parameter, draw X-Y scheme or the three-dimensional plot of the integration data of various conventional certified products edible oil and fat hydrogen nuclear magnetic resonance spectrum signature group, or the grease eigenwert input SIMCA-P11.5 calculated is carried out to principal component analysis (PCA) and obtains PCA analysis chart ,one or more comparisons of the analysis result of unknown sample and above-mentioned X-Y scheme, three-dimensional plot and PCA analysis chart are identified.
The integral area of table 1 soybean oil
A B C D E F G H I
2.41 1.00 0.96 1.52 2.47 1.68 12.79 0.21 2.10
2.40 1.00 0.96 1.52 2.49 1.70 12.79 0.18 2.09
2.41 1.00 0.96 1.52 2.48 1.73 12.79 0.20 2.08
2.41 1.00 0.95 1.52 2.49 1.72 12.82 0.19 2.11
2.41 1.00 0.95 1.51 2.48 1.67 12.83 0.21 2.10
2.40 1.00 0.94 1.52 2.48 1.67 12.81 0.20 2.11
2.40 1.00 0.96 1.52 2.47 1.70 12.76 0.19 2.09
2.40 1.00 0.96 1.51 2.48 1.72 12.80 0.18 2.09
2.41 1.00 0.96 1.52 2.48 1.71 12.87 0.20 2.10
2.38 1.00 0.94 1.51 2.47 1.69 12.84 0.20 2.09
2.47 1.00 1.01 1.56 2.50 1.74 12.48 0.20 1.98
2.49 1.00 1.00 1.53 2.53 1.76 12.79 0.20 2.11
2.43 1.00 0.97 1.55 2.51 1.79 12.85 0.18 2.06
2.41 1.00 0.90 1.49 2.49 1.68 13.63 0.22 2.33
The integral area of table 2 peanut oil
A B C D E F G H I
1.93 1.00 0.54 1.50 2.33 1.67 14.57 0.00 2.28
1.93 1.00 0.54 1.51 2.34 1.68 14.54 0.00 2.26
1.94 1.00 0.54 1.49 2.34 1.62 14.56 0.00 2.27
1.93 1.00 0.54 1.52 2.34 1.67 14.53 0.00 2.25
1.93 1.00 0.54 1.51 2.34 1.64 14.59 0.00 2.27
1.93 1.00 0.54 1.52 2.34 1.67 14.58 0.00 2.25
1.94 1.00 0.55 1.51 2.34 1.76 14.65 0.00 2.27
1.96 1.00 0.56 1.51 2.34 1.69 14.53 0.00 2.27
1.92 1.00 0.52 1.51 2.38 1.60 14.68 0.00 2.28
1.97 1.00 0.56 1.50 2.36 1.57 14.53 0.00 2.25
2.02 1.00 0.60 1.55 2.44 1.72 14.34 0.00 2.24
1.97 1.00 0.56 1.55 2.44 1.77 14.39 0.00 2.21
1.99 1.00 0.56 1.53 2.38 1.71 14.83 0.00 2.31
2.02 1.00 0.56 1.51 2.44 1.71 14.63 0.00 2.40
The integral area of table 3 sesame oil
A B C D E F G H I
2.09 1.00 0.64 1.51 2.54 1.59 13.70 0.00 2.27
2.09 1.00 0.64 1.50 2.51 1.62 13.62 0.00 2.25
2.12 1.00 0.66 1.50 2.52 1.59 13.63 0.00 2.28
2.12 1.00 0.66 1.52 2.53 1.65 13.63 0.00 2.26
2.08 1.00 0.63 1.52 2.59 1.58 13.78 0.00 2.30
2.09 1.00 0.64 1.53 2.60 1.63 13.84 0.00 2.27
2.09 1.00 0.63 1.53 2.59 1.62 13.81 0.00 2.30
2.08 1.00 0.64 1.53 2.53 1.61 13.80 0.00 2.27
2.14 1.00 0.68 1.53 2.62 1.64 13.67 0.00 2.27
2.14 1.00 0.68 1.53 2.60 1.64 13.68 0.00 2.29
2.13 1.00 0.67 1.53 2.51 1.75 13.34 0.00 2.18
2.20 1.00 0.67 1.53 2.61 1.64 14.36 0.00 2.46
The palmitic integral area of table 4
A B C D E F G H I
0.98 1.00 0.13 1.50 1.29 1.89 15.94 0.00 2.14
0.96 1.00 0.11 1.49 1.27 1.63 16.37 0.00 2.25
1.04 1.00 0.12 1.47 1.37 1.66 16.41 0.00 2.36
0.97 1.00 0.10 1.49 1.28 1.68 16.29 0.00 2.32
0.98 1.00 0.09 1.46 1.28 1.67 16.45 0.00 2.41
0.98 1.00 0.10 1.48 1.30 1.62 16.36 0.00 2.36
1.13 1.00 0.14 1.47 1.54 1.60 15.99 0.00 2.31
The integral area of table 5 corn oil
A B C D E F G H I
2.40 1.00 0.79 1.51 2.59 1.82 13.88 0.00 2.61
2.35 1.00 0.78 1.53 2.49 1.82 14.07 0.00 2.56
2.43 1.00 0.80 1.55 2.65 1.86 13.33 0.00 2.62
2.46 1.00 0.76 1.55 2.66 1.83 14.13 0.00 2.59
2.44 1.00 0.77 1.55 2.69 1.80 13.98 0.00 2.60
2.40 1.00 0.80 1.57 2.58 1.83 13.84 0.00 2.63
The integral area of table 6 cottonseed oil
A B C D E F G H I
2.09 1.00 0.82 1.56 2.12 1.77 12.94 0.00 2.18
2.11 1.00 0.82 1.55 2.14 1.91 13.12 0.00 2.25
2.23 1.00 0.87 1.56 2.29 1.79 13.14 0.00 2.26
2.09 1.00 0.86 1.55 2.31 1.87 12.96 0.00 2.22
2.16 1.00 0.86 1.56 2.22 1.90 13.54 0.00 2.24
2.11 1.00 0.85 1.56 2.16 1.81 13.22 0.00 2.25
2.00 1.00 0.87 1.55 2.28 1.80 13.18 0.00 2.25
The integral area of table 7 rapeseed oil
A B C D E F G H I
2.22 1.00 0.60 1.55 2.82 1.72 14.08 0.27 2.12
2.22 1.00 0.58 1.55 2.82 1.72 13.98 0.27 2.12
2.23 1.00 0.58 1.55 2.72 1.71 14.11 0.28 2.13
2.24 1.00 0.62 1.55 2.70 1.70 14.54 0.28 2.12
2.20 1.00 0.61 1.56 2.83 1.72 14.01 0.28 2.11
2.21 1.00 0.59 1.55 2.84 1.72 14.05 0.27 2.11
2.20 1.00 0.58 1.55 2.70 1.71 14.17 0.27 2.12
The integral area of table 8 sunflower oil
A B C D E F G H I
2.45 1.00 0.92 1.55 2.66 1.74 12.93 0.00 2.25
2.45 1.00 0.98 1.55 2.66 1.74 13.03 0.00 2.24
2.52 1.00 0.98 1.59 2.65 1.74 12.94 0.00 2.25
2.43 1.00 0.94 1.55 2.70 1.75 12.95 0.00 2.25
2.43 1.00 0.96 1.54 2.60 1.75 12.96 0.00 2.25
2.46 1.00 0.93 1.54 2.59 1.74 13.11 0.00 2.24
2.44 1.00 0.93 1.55 2.66 1.74 12.88 0.00 2.25
Table 9 soybean oil: peanut oil: the integral area of sesame oil 7:2:1 weight ratio blending stock
A B C D E F G H I
2.18 1.00 0.93 1.50 2.34 1.99 11.58 0.07 1.65
2.28 1.00 0.90 1.52 2.44 1.86 12.34 0.13 1.88
2.16 1.00 0.89 1.48 2.31 1.97 11.62 0.13 1.81
2.16 1.00 0.92 1.52 2.33 1.89 11.51 0.08 1.67
2.26 1.00 0.89 1.49 2.37 1.83 12.23 0.14 1.98
2.22 1.00 0.92 1.48 2.39 1.86 11.80 0.12 1.79
2.17 1.00 0.85 1.40 2.27 2.02 11.38 0.16 1.86
2.13 1.00 0.88 1.42 2.31 2.10 11.12 0.09 1.69
Table 10 calculates the eigenwert of soybean oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0909 0.4474 0.2742 0.1875 122.21
0.0793 0.4737 0.2661 0.1809 121.64
0.0877 0.4561 0.2719 0.1842 122.21
0.0826 0.4583 0.2781 0.1809 122.21
0.0909 0.4437 0.2866 0.1788 123.02
0.0866 0.4430 0.2862 0.1842 121.64
0.0833 0.4649 0.2643 0.1875 121.64
0.0793 0.4768 0.2651 0.1788 122.45
0.0870 0.4561 0.2727 0.1842 122.21
0.0873 0.4459 0.2846 0.1821 121.31
0.0913 0.4786 0.2334 0.1967 122.70
0.0870 0.4784 0.2604 0.1742 125.91
0.0804 0.4716 0.2594 0.1886 121.11
0.0860 0.4072 0.3416 0.1651 124.42
Table 11 calculates the eigenwert of peanut oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.3600 0.4167 0.2233 96.32
0.0000 0.3576 0.4172 0.2252 95.68
0.0000 0.3624 0.4228 0.2148 97.54
0.0000 0.3553 0.4145 0.2303 95.05
0.0000 0.3576 0.4172 0.2252 95.68
0.0000 0.3553 0.4145 0.2303 95.05
0.0000 0.3642 0.4106 0.2252 96.25
0.0000 0.3709 0.4040 0.2252 97.39
0.0000 0.3444 0.4437 0.2119 95.11
0.0000 0.3733 0.4133 0.2133 98.61
0.0000 0.3871 0.4000 0.2129 98.21
0.0000 0.3613 0.4258 0.2129 95.43
0.0000 0.3660 0.4118 0.2222 97.80
0.0000 0.3709 0.4371 0.1921 100.81
Table 12 calculates the eigenwert of sesame oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.4238 0.4172 0.1589 104.79
0.0000 0.4267 0.4100 0.1633 105.49
0.0000 0.4400 0.4000 0.1600 107.21
0.0000 0.4342 0.3980 0.1678 105.80
0.0000 0.4145 0.4375 0.1480 103.54
0.0000 0.4183 0.4314 0.1503 103.42
0.0000 0.4118 0.4346 0.1536 103.42
0.0000 0.4183 0.4085 0.1732 102.86
0.0000 0.4444 0.4118 0.1438 106.24
0.0000 0.4444 0.4052 0.1503 106.24
0.0000 0.4379 0.3824 0.1797 105.67
0.0000 0.4379 0.4150 0.1471 109.61
Table 13 calculates palmitic eigenwert
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.0836 0.3472 0.5692 41.76
0.0000 0.0703 0.3537 0.5760 40.64
0.0000 0.0809 0.3861 0.5330 46.24
0.0000 0.0652 0.3658 0.5689 41.64
0.0000 0.0639 0.3756 0.5605 43.27
0.0000 0.0656 0.3738 0.5606 42.53
0.0000 0.0975 0.4284 0.4741 51.74
Table 14 calculates the eigenwert of corn oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.5251 0.3313 0.1435 122.40
0.0000 0.5117 0.2993 0.1890 118.00
0.0000 0.5174 0.3353 0.1474 120.75
0.0000 0.4878 0.3692 0.1430 122.46
0.0000 0.4997 0.3693 0.1311 121.75
0.0000 0.5105 0.3140 0.1755 118.16
Table 15 calculates the eigenwert of cottonseed oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.5260 0.1549 0.3191 101.23
0.0000 0.5271 0.1624 0.3106 103.01
0.0000 0.5621 0.1749 0.2630 109.45
0.0000 0.5557 0.1883 0.2560 101.89
0.0000 0.5501 0.1645 0.2853 105.46
0.0000 0.5433 0.1488 0.3079 102.49
0.0000 0.5579 0.1744 0.2677 96.57
Table 16 calculates the eigenwert of rapeseed oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.1146 0.1479 0.6448 0.0927 109.31
0.1126 0.1397 0.6581 0.0897 109.21
0.1145 0.1395 0.6222 0.1238 110.01
0.1165 0.1602 0.5938 0.1295 110.72
0.1170 0.1532 0.6380 0.0918 107.36
0.1142 0.1468 0.6544 0.0846 108.76
0.1144 0.1383 0.6172 0.1302 107.89
Table 17 calculates the eigenwert of sunflower oil
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.5925 0.2668 0.1407 122.32
0.0000 0.6293 0.2282 0.1425 121.87
0.0000 0.6144 0.2218 0.1638 122.96
0.0000 0.6072 0.2649 0.1279 121.11
0.0000 0.6218 0.2216 0.1566 122.04
0.0000 0.5997 0.2387 0.1616 122.93
0.0000 0.6000 0.2581 0.1419 121.45
Table 18 calculates the eigenwert of table 9 blending stock
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0429 0.5501 0.1833 0.2237 110.24
0.0624 0.4841 0.2591 0.1945 114.80
0.0683 0.4849 0.2293 0.2175 111.31
0.0431 0.5375 0.1832 0.2362 108.15
0.0675 0.4707 0.2574 0.2044 115.80
0.0605 0.5146 0.2299 0.1951 114.16
0.0781 0.4547 0.2808 0.1864 118.37
0.0522 0.5302 0.2288 0.1888 113.40
For better illustrating the present invention, for the differentiation of grease, enumerate embodiment as follows:
embodiment 1 directly utilizes integral area to be differentiated edible oil by X-Y scheme
Standard model carries out proton nmr spectra test according to the method described above and carries out integration, find through experiment, soybean oil and rapeseed oil is only had to have No. 9 peaks in conventional edible oil, therefore according to or without No. 9 peaks, grease can be divided into two classes, utilize the 2 d plane picture that integrated value A and C does, as accompanying drawing 2 and accompanying drawing 3, as standard database.
Can be separated completely by the visible various grease of accompanying drawing, grease to be measured is carried out proton nmr spectra test according to the method described above and carries out integration, utilize the standard database of its integrated value A and C and foundation to compare and judge.
The waste oil sample adding 5% as us in rapeseed oil carries out proton nmr spectra test according to the method described above and carries out integration, obtains data as follows:
Table 19 adds the integral area of the rapeseed oil of 5% waste oil
A B C D E F G H I
2.10 1.00 0.66 1.56 2.66 1.83 12.52 0.15 1.76
No. 9 peaks are had owing to only having soybean oil and rapeseed oil, therefore only need to utilize accompanying drawing 2 as standard database, by contrasting known with standard database, see accompanying drawing 4, the sample adding waste oil drops on outside soybean oil and rapeseed oil characteristic area, and clearly showing is not pure rapeseed oil.
Table 20 adds the integral area of the sunflower oil of 5% waste oil
A B C D E F G H I
2.31 1.00 0.90 1.48 2.50 1.68 11.88 0.00 2.06
The same, there is no the Fig. 3 at No. 9 peaks as standard database, by testing sample and its contrast known, the sunflower oil adding waste oil drops on outside each edible oil and fat standard feature region, as accompanying drawing 5, can obviously differentiate out not to be pure sunflower oil.
embodiment 2 directly utilizes integral area to be differentiated grease by three-dimensional plot
Standard model carries out proton nmr spectra test according to the method described above and carries out integration, and utilize integrated value A, C, E do three-dimensional plot, various edible oil can separate completely, as accompanying drawing 6, as standard database.
Edible oil to be measured carried out proton nmr spectra test according to the method described above and carries out integration, utilizing its integrated value A, C, E and standard database accompanying drawing 6 to compare and judge.Such as
Table 21 is as follows respectively containing the integration data of two peanut oil samples of 10% waste oil
A B C D E F G H I
1.91 1.00 0.62 1.43 2.23 1.97 12.57 0.00 1.99
1.87 1.00 0.68 1.50 2.27 2.07 12.28 0.00 1.60
Its distribution in standard database three-dimensional plot accompanying drawing 6, as Fig. 7, drops on outside each edible oil standard characteristic area, can obviously differentiate out that this sample is not pure peanut oil.
embodiment 3 differentiates grease by carrying out PCA analysis
Standard model carries out proton nmr spectra test according to the method described above and carries out anomalous integral calculating, the eigenwert of edible oil is utilized to carry out PCA analysis as variable, each group can be separated completely, as the PCA analysis chart data of standard edible oil eigenwert, as accompanying drawing 8 and accompanying drawing 9.
Edible oil to be measured carried out proton nmr spectra test according to the method described above and carries out anomalous integral calculating, carrying out PCA analysis using its eigenwert as variable, by judging oil quality with standard model storehouse accompanying drawing 8 and accompanying drawing 9 comparison.Such as
Table 22 adds integral area and the eigenwert of the soybean oil of 5% waste oil
A B C D E F G H I
2.29 1.00 0.89 1.44 2.36 1.78 12.34 0.21 2.07
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0906 0.4280 0.2998 0.1816 121.77
Table 23 adds integral area and the eigenwert of the sesame oil of 5% waste oil
A B C D E F G H I
2.05 1.00 0.72 1.52 2.50 1.78 12.56 0.00 1.88
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.4772 0.3462 0.1766 102.18
Analysis chart, as accompanying drawing 10, can be found out, in Figure 10, the Data distribution8 of DG and XG difference criterion distance soybean oil D and sesame oil X is comparatively far away, judges that these two kinds of oil are not all soybean oil and the sesame oil of certified products.
Table 24 mixes integral area and the eigenwert of pseudo-sesame oil
A B C D E F G H I
2.20 1.00 0.74 1.56 2.7 1.70 13.58 0.00 2.33
2.18 1.00 0.73 1.51 2.52 1.68 13.36 0.00 2.30
[ω-3 UFA] [ω-6 linoleic acid] [MUFA] [SFA] IV
0.0000 0.4744 0.3910 0.1346 107.50
0.0000 0.4834 0.3510 0.1656 109.92
As accompanying drawing 11 obviously can find out that these two kinds of oil samples are not the sesame oil of certified products.
Embodiment 4 is to the judgement of the blending stock of known composition
Utilize integration data in table 9 to set up the database of the blending stock (soybean oil: peanut oil: sesame oil weight ratio 7:2:1) of known composition, utilize the X-Y scheme analysis with No. 9 peaks to judge to add the blending stock of 10% waste oil, as accompanying drawing 12.
Table 257:2:1 weight ratio blending stock adds the integral area of 10% waste oil
A B C D E F G H I
2.09 1.00 0.84 1.47 2.25 1.95 11.69 0.11 1.74
Sample drops on outside this blending stock standard feature region, can obviously differentiate out that this sample does not meet known proportion mediation oil composition.

Claims (4)

1. the method for a proton nmr spectra detection edible oil quality, it is characterized in that, realize as follows: (1) standard model proton nmr spectra data acquisition: under the same terms, more than twice proton nmr spectra test is carried out to the certified products edible oil sample of same quality, draw front and back twice or the error of repeatedly test data, correction error; Then repeated proton nmr spectra test is carried out to the certified products edible oil sample of same quality;
(2) standard model data processing: test in the certified products edible oil sample proton nmr spectra obtained and comprise nine groups of proton peak, respectively integration is carried out to these nine groups of peaks, record the integrated value of its hydrogen nuclear magnetic resonance spectrum signature group, utilize its integrated value do X-Y scheme, the three-dimensional plot of integration data or its integrated value is substituted into the eigenwert that following formulae discovery obtains certified products edible oil, make the major component PCA analysis chart of its eigenwert:
[ω-3UFA]=H/(H+I)
[ω-6 linoleic acid]=(3C-4H)/3D
[MUFA]=E/2D-H/(H+I)-(3C-4H)/3D
[SFA]=1-E/2D
[IV]=[(A-B/4)/D]×86
In above-mentioned formula, [ω-3UFA] is the ratio of omega-3 unsaturated fatty acid in grease; [ω-6 linoleic acid] is the ratio of linoleic acid in grease; [MUFA] is the ratio of monounsaturated fatty acids in grease; [SFA] is the ratio of saturated fatty acid in grease; The iodine number that [IV] is grease; A, B, C, D, E, H, I represent the area of above-mentioned nine groups of proton peak wherein seven groups of proton peak integrations respectively;
(3) foundation of database: under the same terms, tests the proton nmr spectra of a large amount of variety classes different quality certified products edible oil, repeats step (2) and processes, set up edible oils attribute test database;
(4) sample is differentiated: under the same terms, nuclear magnetic resonance test is carried out to unknown edible oils sample, utilize its hydrogen nuclear magnetic resonance spectrogram of data processing method process of step (2), the edible oils attribute test database model set up with step (3) is compared, Qualitative Identification certified products edible oil or mix pseudo-edible oil, and certified products edible oil kind is judged.
2. proton nmr spectra according to claim 1 detects the method for edible oil quality, it is characterized in that, described edible oils attribute test database is the X-Y scheme of the integration data of various conventional certified products edible oil or the major component PCA analysis chart of three-dimensional plot and various conventional certified products edible oil eigenwert.
3. proton nmr spectra according to claim 1 and 2 detects the method for edible oil quality, it is characterized in that, described certified products edible oil is respectively the blending stock of soybean oil, peanut oil, sesame oil, palm oil, corn oil, rapeseed oil, cottonseed oil, sunflower oil or known composition.
4. proton nmr spectra according to claim 1 and 2 detects the method for edible oil quality, and it is characterized in that, the eigenwert of described certified products edible oil comprises leukotrienes, linoleic acid, oleic acid, saturated fatty acid, monounsaturated fatty acids and iodine number.
CN201210123448.3A 2011-04-28 2012-04-25 Proton nmr spectra detects the method for edible oil quality Active CN102636510B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201210123448.3A CN102636510B (en) 2011-04-28 2012-04-25 Proton nmr spectra detects the method for edible oil quality

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
CN201110108182.0 2011-04-28
CN2011101081820A CN102269720A (en) 2011-04-28 2011-04-28 Method for identifying edible oil quality through combination of nuclear magnetic resonance and pattern recognition method
CN201210123448.3A CN102636510B (en) 2011-04-28 2012-04-25 Proton nmr spectra detects the method for edible oil quality

Publications (2)

Publication Number Publication Date
CN102636510A CN102636510A (en) 2012-08-15
CN102636510B true CN102636510B (en) 2015-12-02

Family

ID=45052082

Family Applications (2)

Application Number Title Priority Date Filing Date
CN2011101081820A Pending CN102269720A (en) 2011-04-28 2011-04-28 Method for identifying edible oil quality through combination of nuclear magnetic resonance and pattern recognition method
CN201210123448.3A Active CN102636510B (en) 2011-04-28 2012-04-25 Proton nmr spectra detects the method for edible oil quality

Family Applications Before (1)

Application Number Title Priority Date Filing Date
CN2011101081820A Pending CN102269720A (en) 2011-04-28 2011-04-28 Method for identifying edible oil quality through combination of nuclear magnetic resonance and pattern recognition method

Country Status (1)

Country Link
CN (2) CN102269720A (en)

Families Citing this family (25)

* Cited by examiner, † Cited by third party
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
CN102749349B (en) * 2012-06-20 2015-09-16 山东大学 A kind of method differentiating authenticity of hide glue
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
CN102901744A (en) * 2012-11-08 2013-01-30 厦门大学 Method for detecting authenticity of peanut oil
CN102901745B (en) * 2012-11-08 2015-11-11 厦门大学 A kind of discrimination method of olive oil
CN102967616A (en) * 2012-11-08 2013-03-13 厦门大学 Deep sea fish oil identification method
CN103207200B (en) * 2013-03-08 2016-05-04 厦门大学 Judge the method for waste oil by characterization compound relative amount
CN103245685B (en) * 2013-03-27 2016-01-20 江苏省农业科学院 The fresh grain quality of a kind of Fresh edible soybean 1h NMR evaluation method
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
CN104655666A (en) * 2013-11-21 2015-05-27 上海理工大学 Low field nuclear magnetic resonance detection method of edible gelatin quality
CN104950006B (en) * 2014-03-27 2017-09-26 中国科学院青岛生物能源与过程研究所 A kind of method of the quick intracellular content of polyunsaturated fatty acid of judgement oil-containing microorganism
CN104198518A (en) * 2014-09-24 2014-12-10 中国科学院大连化学物理研究所 Method for true and false identification and content determination of sesame oil
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
CN106680307B (en) * 2016-11-17 2018-10-09 四川农业大学 A method of Seed Vigor among Soybean is differentiated based on nuclear magnetic resonance technique
CN106950241B (en) * 2017-02-27 2019-10-01 南昌大学 A kind of method of other adulterated oil type and contents in prediction tea oil
CN106950243B (en) * 2017-03-31 2018-11-06 安徽农业大学 A method of detection aged rice
CN107703173A (en) * 2017-06-23 2018-02-16 孟扬 A kind of identification apparatus and method of the rare species timber based on 1H NMR datas storehouse
CN108387599B (en) * 2018-03-26 2020-04-14 江南大学 Method for detecting oxidation products of edible oil by combining nuclear magnetic resonance hydrogen spectrum with gas chromatography external standard method
CN108982570A (en) * 2018-09-30 2018-12-11 厦门大学 A kind of edible oil quality discrimination method based on nuclear magnetic resonance technique
CN111610214B (en) * 2019-02-25 2023-06-13 苏州纽迈分析仪器股份有限公司 Standard substance and standard sample for testing solid fat content and preparation method thereof
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
CN110632114B (en) * 2019-09-29 2022-09-23 极晨智道信息技术(北京)有限公司 Method for rapidly detecting various edible oil analysis indexes based on NMR technology
CN111337528B (en) * 2020-01-17 2023-05-23 钛和中谱检测技术(江苏)有限公司 Nuclear magnetic resonance hydrogen spectrometry for identifying beef, pork or duck meat mixed in mutton
CN111537542A (en) * 2020-06-01 2020-08-14 四川轻化工大学 Method for rapidly identifying Daqu grade
CN117928655B (en) * 2024-03-22 2024-07-05 济宁万生环保材料有限公司 Material reaction instant acid value data on-line monitoring system

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1547929A (en) * 2003-05-05 2004-11-24 ���Ⱥ;� Method for obtaining oil composition and oil composition obtained thereby
CN101975788A (en) * 2010-09-01 2011-02-16 苏州纽迈电子科技有限公司 Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance)
CN102154038A (en) * 2011-02-21 2011-08-17 中国人民解放军第二炮兵工程学院 Vegetable oil and ester ether biodiesel and new use thereof
CN102221533A (en) * 2011-06-09 2011-10-19 西北农林科技大学 Method for quantitatively detecting adulteration of peanut oil based on ultraviolet spectrum
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
CN102393426A (en) * 2011-10-28 2012-03-28 李涛 Identification method for illegal cooking oil

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS57115136A (en) * 1981-01-08 1982-07-17 Fuji Oil Co Ltd Preparation of cheese-like food

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1547929A (en) * 2003-05-05 2004-11-24 ���Ⱥ;� Method for obtaining oil composition and oil composition obtained thereby
CN101975788A (en) * 2010-09-01 2011-02-16 苏州纽迈电子科技有限公司 Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance)
CN102154038A (en) * 2011-02-21 2011-08-17 中国人民解放军第二炮兵工程学院 Vegetable oil and ester ether biodiesel and new use thereof
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
CN102221533A (en) * 2011-06-09 2011-10-19 西北农林科技大学 Method for quantitatively detecting adulteration of peanut oil based on ultraviolet spectrum
CN102393426A (en) * 2011-10-28 2012-03-28 李涛 Identification method for illegal cooking oil

Also Published As

Publication number Publication date
CN102269720A (en) 2011-12-07
CN102636510A (en) 2012-08-15

Similar Documents

Publication Publication Date Title
CN102636510B (en) Proton nmr spectra detects the method for edible oil quality
CN101975788B (en) Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance)
CN106950241B (en) A kind of method of other adulterated oil type and contents in prediction tea oil
CN101825594B (en) Method for quick nondestructive detection of freshness of freshwater fish
CN102706915B (en) A kind of detection method of waste oil
CN104122246A (en) Raman-spectrum measuring method for detecting content of melamine in milk products with different matrixes
CN103901094A (en) Oil detection and identification method based on ion mobility spectrometer
CN102565169A (en) Electrochemical fingerprint chromatogram identification method for edible oil
CN103344696B (en) A kind of method utilizing FAIMS detection pork freshness
CN103267760A (en) Method and kit for detecting illegal cooking oil
CN111189868B (en) Method for rapidly screening adulterated illegal cooking oil in edible oil by using low-field nuclear magnetic resonance
CN104597013B (en) A kind of fluorescent spectrometry surveys the method that cholesterol level differentiates gutter oil
CN104237370A (en) Method for rapidly identifying counterfeit sesame oil with sesame oil essence
CN202049112U (en) Pearl quality detecting device
CN103954691B (en) Nondestructive testing method for material component fraction
CN105911195A (en) Preparation method for edible oil standard substance containing capsicine compound
CN104215479B (en) A kind of biological test method of quick detection Chinese medicine comprehensive toxicity
CN103389318B (en) A kind of method differentiating true and false beef and mutton
CN102901744A (en) Method for detecting authenticity of peanut oil
CN101984351A (en) Measuring method of grade of magnetic iron made of fine iron powder and measuring device thereof
CN103163288A (en) Optimized automation-adaptable platelet aggregation function inspection and analysis method
CN105372224A (en) Method for identifying different species of feed grease based on Fourier Ramman spectrum
CN102901745A (en) Method for identifying olive oil
CN103674994A (en) Gelatin standard database construction method and system, and gelatin identification method and system
CN102818825A (en) Method for detecting prohibited additive acid orange II in food

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