CN103792247A - Low-field nuclear magnetic resonance detection method for frying use limit of soybean oil - Google Patents
Low-field nuclear magnetic resonance detection method for frying use limit of soybean oil Download PDFInfo
- Publication number
- CN103792247A CN103792247A CN201210435185.XA CN201210435185A CN103792247A CN 103792247 A CN103792247 A CN 103792247A CN 201210435185 A CN201210435185 A CN 201210435185A CN 103792247 A CN103792247 A CN 103792247A
- Authority
- CN
- China
- Prior art keywords
- frying
- magnetic resonance
- nuclear magnetic
- soybean oil
- low
- 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.)
- Granted
Links
Images
Abstract
The invention discloses a low-field nuclear magnetic resonance detection method for a frying use limit of soybean oil. The method is used for judging the use end point in the soybean oil frying process. According to the method, a low-field nuclear magnetic resonance analyzer is used as a main measurement tool, a mathematical model between multi-component relaxation spectrum data and total polar compound (TPC) data of the soybean oil is constructed as a basis, and a nuclear magnetic resonance signal in the soybean frying process is used as a main observation object, so that the frying use limit of the soybean oil is judged by analyzing multi-component transverse relaxation spectrum data of the soybean oil in the frying process. The low-field nuclear magnetic resonance detection method has the advantages of high measurement result accuracy, high repetitiveness, high stability, short time consumption and the like, is convenient for on-site authentication on the quality of the soybean oil in the frying process and supplies reliable oil product information to the work for detecting the quality of the soybean oil in the frying process. By the adoption of methods similar to the method disclosed by the invention, corresponding databases and mathematical models are constructed for other types of edible oil, and the low-field nuclear magnetic resonance detection and frying use limit judgment can be performed on other types of edible oil.
Description
Technical field
The present invention relates to a kind of food detection method, relate in particular to a kind of low-field nuclear magnetic resonance detection method of soybean oil frying operating limit.
Background technology
Edible oil is fried use repeatedly, and oil quality can produce bad change, not only affects oily taste, also can damage people's health.Therefore frying oil is detected, supervised, having become Food Hygiene Surveillance must obligato content.For frying fat and oil, total polar compound (TPC) content of grease is the important indicator of weighing frying fat and oil quality, according to the regulation of GB GB7102.1-2003, generally use the judge index of terminal as frying fat and oil to reach total polar compound content of 27%, the general available column chromatography of the detection of TPC content in grease is carried out, and the method need be used a large amount of organic solvents, complex operation, cost is not only high but also time-consuming.
Low-field nuclear magnetic resonance (LF-NMR) analyser equipment volume is little, detect sample fast, harmless, in real time, without any chemical reagent, and cheap (market price be about above-mentioned instrument 1/3).At present, the mainly longitudinal relaxation time (T to detected object of low-field nuclear magnetic resonance technology
1), T2 (T
2), coefficient of diffusion and CPMG (Carr-Purcell-Meiboom-Gill) echo data analyze, nuclear magnetic resonance technique has been applied to many-sided analysis and research such as grease, protein structure, glassy transition, carbohydrates.But have no the report that application low-field nuclear magnetic resonance technology is carried out the judgement of frying fat and oil quality.
The present invention detects on the basis of the mathematical model between characteristic and its TPC content in evidence the LF-NMR that sets up frying oil, reflects fast its TPC content by the LF-NMR index of detection frying oil, judges whether it reaches the operating limit of frying oil.Final realization replaces traditional column chromatography with LF-NMR technology, realizes the fast detecting of frying oil operating limit.
Summary of the invention
Object of the present invention, exactly in order to provide a kind of low-field nuclear magnetic resonance detection method of soybean oil frying operating limit.
In order to achieve the above object, the present invention has adopted following technical scheme: a kind of low-field nuclear magnetic resonance detection method of soybean oil frying operating limit, mainly comprises the following steps:
(1) foundation of standard model database
According to GB/T509.202-2003 specified standard, detect the TPC content of soybean oil after the difference frying time by post layer folding method, set up the standard model database that the TPC content of soybean oil changed with the frying time;
(2) low-field nuclear magnetic resonance of standard model detects
Utilize the CPMG pulse train of low-field nuclear magnetic resonance instrument to measure the T2 T of soybean oil in frying process
2, obtaining its low-field nuclear magnetic resonance by data analysis and detect data, described detection data comprise the initial time T of first peak
21, the second peak initial time T
22, the 3rd peak initial time T
23, first peak peak area number percent S
21, the second peak peak area number percent S
22, the 3rd peak peak area number percent S
23and single component relaxation time T
2W;
(3) low-field nuclear magnetic resonance detects the foundation of data and TPC content mathematical model
Adopt multiple regression analysis method and the data rejected backward in testing result and step (1) the gained standard model database of quantity method to step (2) to carry out correlation analysis, thereby set up the mathematical model between TPC content and the low-field nuclear magnetic resonance testing result of soybean oil:
TPC＝116.955+0.490×T
21-0.895×T
2w
In formula, T
21the numerical value initial time T that is first peak
21millisecond numerical value, T
2wnumerical value be single component relaxation time T
2wmillisecond numerical value;
(4) detection of testing sample
Testing sample is carried out to low-field nuclear magnetic resonance detection according to step (2), by the T recording
2Wand T
21in the mathematical model that data substitution step (3) is set up, calculate the TPC content of this sample, if TPC content>=27% judges that testing sample has met or exceeded operating limit.
The cycle tests of transverse relaxation described in the present invention is conventional nuclear-magnetism pulse train, i.e. cpmg sequence row utilize instrument to carry the CPMG die-away curve that T-invfit software measures LF-NMR and carry out inverting matching, can obtain the polycomponent relaxation time (T of sample
2) data collection of illustrative plates.In the time sample being regarded as to overall composition and analyzed, can inverting obtain the one-component relaxation time (T of sample
2w, unit: ms), detect characteristic (T by screening suitable LF-NMR
21, T
22, T
23, S
21, S
22, S
23, T
2W) and the Related Mathematical Models of foundation, checking and TPC content, finally reach by the LF-NMR index of sample and reflect fast the wherein object of TPC content, judge whether it reaches the operating limit of frying oil.
The low-field nuclear magnetic resonance detection method of soybean oil frying operating limit of the present invention has following advantage and disadvantage:
1, the present invention can guarantee fast and accurately frying oil sample to be carried out to nuclear magnetic resonance spectroscopy test, goes out the TPC content of frying oil sample by the calculated with mathematical model of setting up, and judges fast whether this frying oil sample exceedes the frying limit.Compared with classic method, this method not only can improve detection speed greatly, has also improved the accuracy and the stability that detect.
2, the speed of sample test is fast, consuming time short, and test can complete substantially in 2-3 minute.
Accompanying drawing explanation
Fig. 1 is TPC content situation over time in soybean oil frying French fries process;
Fig. 2 is T in soybean oil frying French fries process
2situation over time;
Fig. 3 is T
21peak initial time is with the situation of change of frying time;
Fig. 4 is T
22peak initial time is with the situation of change of frying time;
Fig. 5 is T
23peak initial time is with the situation of change of frying time;
Fig. 6 is S
21with the situation of change of frying time;
Fig. 7 is S
22with the situation of change of frying time;
Fig. 8 is S
23with the situation of change of frying time;
Fig. 9 is the one-component relaxation collection of illustrative plates in soybean oil frying French fries process;
Figure 10 is T
2Wwith the situation of change of frying time;
Figure 11 is the relation curve of TPC content measured value and predicted value.
Embodiment
(1) foundation of standard model database
In cooking fryer, add 6L soybean oil, oil temperature is 180 ± 5 ℃, gets in 60g French fries input cooking fryer for every batch and fries 3min, and 4 batches of fryings per hour, fry 12h every day continuously, continue altogether 36h.In frying process, every 2h gets 150mL oil sample, is cooled to room temperature, after elimination precipitation, stores in sample bottle, and-4 ℃ of refrigerations are for subsequent use.The column chromatography of application GB/T509.202-2003 is measured the TPC content of frying oil sample, gets the mean value of three measurement results, and result as shown in Figure 1.
As seen from Figure 1, in frying process, the equal content of the TPC of soybean oil raises gradually, and is good linear relation (R with the frying time
2=0.970).Model calculating according to matching is known, and in the time adding French fries frying 28.95h, the TPC content in frying oil will reach operating limit value 27%.While frying 30h in test, in frying oil, TPC actual measurement content has reached 28.79%, has exceeded the operating limit of frying oil, and theoretical analysis and verification experimental verification have identical preferably.
(2) LF-NMR of standard model detects
Utilize the T2 (T of the CPMG pulse train working sample of LF-NMR
2).2.5mL sample is moved into nuclear magnetic resonance test tube, first at 32 ℃ of constant temperature 10min, then be placed in nuclear-magnetism probe and stablize 1min post-sampling, after sampling, sample is placed in again to 32 ℃ of constant temperature 5min, sample to carry out next time, result is got measurement mean value three times;
1. polycomponent relaxation collection of illustrative plates (T
2)
Soybean oil carries out in frying process at interpolation French fries, and LF-NMR detects the polycomponent relaxation collection of illustrative plates (T obtaining
2) as shown in Figure 2.Appearance order called after T is respectively pressed in each peak
21peak, T
22peak and T
23peak, corresponding peak area number percent (area at this peak accounts for the percentage of whole figure area under spectrum) is expressed as S
21, S
22and S
23.
By finding out in Fig. 2, after adding French fries in soybean oil and frying, its polycomponent relaxation collection of illustrative plates (T
2) Changing Pattern is similar, the soybean oil T at frying initial stage
2collection of illustrative plates is by T
22, T
23two main peaks form, and along with the prolongation of frying time, have T in its collection of illustrative plates 18ms left and right
21small peak occurs, and collection of illustrative plates entirety has the trend that moves to left gradually, peak area ratio S
21also increase gradually S
22, S
23ratio also slightly changes.After frying 2h, there is T in soybean oil
21small peak, in order further to analyze the Changing Pattern of LF-NMR signal in frying process, by T
21, T
22, T
23peak initial time is listed in respectively Fig. 3, Fig. 4, Fig. 5 with the situation of change of frying time.
Can be found out by Fig. 3, Fig. 4, in frying process, soybean oil T
21, T
22peak initial time all shortens with the prolongation of frying time, and is good linear relation (R
2> 0.90).And T in Fig. 5
23peak initial time changes without evident regularity with the frying time.
This variation may to grease in high temperature frying process owing to being hydrolyzed, the product such as lipid oxidation thing and superoxide that generates of the complex chemical reaction such as thermal polymerization and thermal oxide polymerization is relevant, compared with triglyceride composition in grease, the oxidation product degree of polymerization forming in frying process increases relatively, and LF-NMR detects the T obtaining
2relaxation time can be reflected the variation of spinning nucleon kind and physicochemical environment thereof.When oxidation product forms and runs up to a certain degree, at T
2on spectrogram, there is T
21characteristic peak, and with the increase of the reaction product degree of polymerization, the suffered binding force of hydrogen proton in its molecule is increased, cause relaxation process to shorten, thereby show as T
2dwindling of value.And along with the prolongation of frying time, in grease, form the oxidation material degree of polymerization and also increase gradually, thereby cause oil sample T
2relaxation distributes and moves to left gradually, and with T
21, T
22reducing of peak initial time is the most remarkable.
Further study soybean oil each peak area in frying process and accounted for whole T
2number percent (the S of figure area under spectrum
21, S
22, S
23) with frying the time variation, as shown in Fig. 6, Fig. 7, Fig. 8.
Fig. 6, Fig. 7, Fig. 8 show, with the prolongation of frying time, the S of oil sample
21, S
22all increase gradually, and S
23reduce gradually.Wherein, S
21be good linear relation (R with the frying time
2> 0.90), this is due to T
21
What characteristic peak reflected is formation and the accumulation that is different from a class oxidation product of triglyceride composition in frying process
Process, along with the prolongation of frying time, has similar T
21the compounds content of value increases, thereby the signal response of its LF-NMR is increased, and causes T
2corresponding peak area (S in collection of illustrative plates
21) increase.
2. one-component relaxation collection of illustrative plates (T
2W, ms)
The oil sample that difference is fried to the time is regarded an overall composition as and is carried out inverting, can obtain the one-component relaxation collection of illustrative plates in soybean oil frying process, as shown in Figure 9.
As shown in Figure 9, with frying time lengthening, the one-component relaxation time (T of French fries frying oil
2w) reduce gradually, without the T of material/French fries frying condition soybean oil
2Wvalue with frying the time variation relation as shown in figure 10.
Figure 10 shows, in frying process, and soybean oil T
2Wvalue all significantly shortens with the prolongation of frying time,
And between the two, be good linear relation (R
2> 0.90).This be due to, under the complex chemical reaction effects such as hydrolysis, thermal polymerization and thermal oxide polymerization that the constituent of oil sample occurs in high temperature frying process, there is change, this just makes LF-NMR detect the T of the reflection sample global feature obtaining
2Walso there is change in relaxation behavior.
(3) LF-NMR detects the foundation of data and TPC content mathematical model.Adopt multiple regression analysis method, application is rejected backward quantity method inapparent independent variable is rejected, and finally makes only to comprise between remarkable variable and variable and form optimum combination in model.Dependent variable is chosen TPC content, and independent variable is chosen LF-NMR testing result (T
21, T
22, T
23, S
21, S
22, S
23, T
2W), set up the TPC content of soybean oil and the mathematical model of LF-NMR testing result is, TPC=116.955+0.490 × T
21-0.895 × T
2w(1), coefficient of determination R
2=0.987.
(4) detection of sample and checking:
The first step, instrumental calibration.
The soybean oil standard model of known TPC content is carried out to low nuclear-magnetism transverse relaxation and analyze, by measured T
2Wand T
21substitution formula calculates in (1), when the relative deviation < 5% of result of calculation and standard content, can carry out testing sample test.
Second step, carries out LF-NMR detection by soybean oil testing sample according to step (2), by the T recording
2Wand T
21in data substitution formula (1), calculate the TPC content of this sample and judge whether to reach operating limit that (operating limit is 27% according to national regulation, in the time of TPC content > 27%, exceed operating limit, can not continue to use).
In order to verify the reliability of regression equation, get altogether 9 different frying times (2h, 6h, 10h, 14h, 18h,
22h, 26h, 30h, 34h) sample carry out validation test, sample actual measurement TPC content and model calculate
Predicted value correlation analysis result as shown in figure 11.
As seen from Figure 11, the oil sample TPC content and the measured value that utilize the model of setting up to calculate have good correlativity, R
2can reach 0.991, illustrate in trial stretch, the model of setting up has good prediction effect.Therefore, can utilize the LF-NMR of oil sample to detect characteristic, i.e. T
2W, T
21, by the mathematical model effectively variation of reflection oil sample TPC content fast of setting up.
Standard specimen reperformance test:
Be necessary the oils sample of same quality to carry out reperformance test, to understand the probability of miscarriage of justice of nuclear magnetic resonance test oils quality.The sample of same frying degree is (N > 3) in repeated detection, and its testing result relative deviation is answered < 5%.
Adopt similar approach of the present invention, other edible oil is set up to corresponding database and mathematical model, can carry out to other edible oil the judgement of low-field nuclear magnetic resonance detection and frying operating limit.
Claims (1)
1. a low-field nuclear magnetic resonance detection method for soybean oil frying operating limit, is characterized in that, mainly comprises the following steps:
(1) foundation of standard model database
According to GB/T509.202-2003 specified standard, detect the TPC content of soybean oil after the difference frying time by post layer folding method, set up the standard model database that the TPC content of soybean oil changed with the frying time;
(2) low-field nuclear magnetic resonance of standard model detects
Utilize the CPMG pulse train of low-field nuclear magnetic resonance instrument to measure the T2 T of soybean oil in frying process
2, obtaining its low-field nuclear magnetic resonance by data analysis and detect data, described detection data comprise the initial time T of first peak
21, the second peak initial time T
22, the 3rd peak initial time T
23, first peak peak area number percent S
21, the second peak peak area number percent S
22, the 3rd peak peak area number percent S
23and single component relaxation time T
2W;
(3) low-field nuclear magnetic resonance detects the foundation of data and TPC content mathematical model
Adopt multiple regression analysis method and the data rejected backward in testing result and step (1) the gained standard model database of quantity method to step (2) to carry out correlation analysis, thereby set up the mathematical model between TPC content and the low-field nuclear magnetic resonance testing result of soybean oil:
TPC＝116.955+0.490×T
21-0.895×T
2w
In formula, T
21the numerical value initial time T that is first peak
21millisecond numerical value, T
2wnumerical value be single component relaxation time T
2wmillisecond numerical value;
(4) detection of testing sample
Testing sample is carried out to low-field nuclear magnetic resonance detection according to step (2), by the T recording
2Wand T
21in the mathematical model that data substitution step (3) is set up, calculate the TPC content of this sample, if TPC content>=27% judges that testing sample has met or exceeded operating limit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210435185.XA CN103792247B (en) | 2012-11-02 | 2012-11-02 | The low-field nuclear magnetic resonance detection method of soybean oil frying operating limit |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210435185.XA CN103792247B (en) | 2012-11-02 | 2012-11-02 | The low-field nuclear magnetic resonance detection method of soybean oil frying operating limit |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103792247A true CN103792247A (en) | 2014-05-14 |
| CN103792247B CN103792247B (en) | 2016-03-23 |
Family
ID=50668119
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210435185.XA Active CN103792247B (en) | 2012-11-02 | 2012-11-02 | The low-field nuclear magnetic resonance detection method of soybean oil frying operating limit |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103792247B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106353356A (en) * | 2015-07-17 | 2017-01-25 | 阿斯派克人工智能有限公司 | Device and method used for quantitative detection on processed material |
| 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 |
| CN110187297A (en) * | 2019-06-11 | 2019-08-30 | 东南大学 | A kind of low-field nuclear magnetic resonance relaxation detection method inhibiting signal specific |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10267870A (en) * | 1997-03-25 | 1998-10-09 | Matsushita Refrig Co Ltd | Method for judging quality of food |
| JPH11142354A (en) * | 1997-11-06 | 1999-05-28 | Kobe Steel Ltd | Method for evaluating interior quality of fruit |
| 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) |
| CN102135509A (en) * | 2011-01-13 | 2011-07-27 | 浙江大学 | Method for measuring characteristic molecule group in bio-oil |
| 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 |
| CN102721716A (en) * | 2012-07-04 | 2012-10-10 | 中国科学院研究生院 | Edible oil quality inspection method based on 1H-nuclear magnetic resonance (NMR) fingerprint spectra and multivariate analysis |
-
2012
- 2012-11-02 CN CN201210435185.XA patent/CN103792247B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10267870A (en) * | 1997-03-25 | 1998-10-09 | Matsushita Refrig Co Ltd | Method for judging quality of food |
| JPH11142354A (en) * | 1997-11-06 | 1999-05-28 | Kobe Steel Ltd | Method for evaluating interior quality of fruit |
| 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) |
| CN102135509A (en) * | 2011-01-13 | 2011-07-27 | 浙江大学 | Method for measuring characteristic molecule group in bio-oil |
| 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 |
| CN102721716A (en) * | 2012-07-04 | 2012-10-10 | 中国科学院研究生院 | Edible oil quality inspection method based on 1H-nuclear magnetic resonance (NMR) fingerprint spectra and multivariate analysis |
Non-Patent Citations (3)
| Title |
|---|
| 周凝 等: "米糠毛油掺伪食用植物油的低场核磁共振检测", 《食品与发酵工业》 * |
| 王永巍 等: "低场核磁共振技术检测煎炸油品质", 《食品科学》 * |
| 王永巍 等: "煎炸油掺伪食用植物油的低场核磁共振检测", 《科学仪器服务民生学术大会论文集》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106353356A (en) * | 2015-07-17 | 2017-01-25 | 阿斯派克人工智能有限公司 | Device and method used for quantitative detection on processed material |
| 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 |
| CN110187297A (en) * | 2019-06-11 | 2019-08-30 | 东南大学 | A kind of low-field nuclear magnetic resonance relaxation detection method inhibiting signal specific |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103792247B (en) | 2016-03-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101975788B (en) | Method for identifying quality of edible oil with low-field NMR (Nuclear Magnetic Resonance) | |
| CN104764869B (en) | Transformer gas fault diagnosis and alarm method based on multidimensional characteristics | |
| Hou et al. | Rapid identification of edible oil species using supervised support vector machine based on low-field nuclear magnetic resonance relaxation features | |
| Li et al. | Prediction of egg storage time and yolk index based on electronic nose combined with chemometric methods | |
| CN102252992B (en) | Method for performing near-infrared on-line detection in process of extracting Chinese medicines | |
| CN103134850B (en) | A kind of tea leaf quality method for quick based on characteristic perfume | |
| CN105300923A (en) | Correction method of measuring point free temperature compensation model during process of online application of near infrared spectrum analyzer | |
| CN101995389B (en) | Method for fast recognition of crude oil variety through near infrared spectrum | |
| CN106950241B (en) | A kind of method of other adulterated oil type and contents in prediction tea oil | |
| CN107817223A (en) | The construction method of quick nondestructive real-time estimate oil property model and its application | |
| CN100575950C (en) | A kind of predicting method for fruit maturity | |
| CN101799411B (en) | Quick detection method of oil quality spectrum for lubricating oil | |
| WO2017084119A1 (en) | Near-infrared physical parameter measuring method having measuring-point-free temperature compensation function | |
| CN107505346B (en) | The method for predicting to be especially the chemical displacement value of NMR spin system in biological fluid sample in class of fluids sample | |
| CN102841069B (en) | Method for rapidly identifying types of crude oil by using mid-infrared spectrum | |
| CN103792247B (en) | The low-field nuclear magnetic resonance detection method of soybean oil frying operating limit | |
| CN105136736A (en) | Online near infrared sample size determination method | |
| CN106560699A (en) | Combined detection method used for identification of producing area of Wuyi rock tea | |
| CN104596886B (en) | Diesel oxidation stability determining method | |
| CN103134763B (en) | The method of oil density is predicted by infrared spectrum | |
| CN107632010A (en) | A kind of quantitative approach of combination LIBS to steel samples | |
| CN110245446A (en) | A kind of distribution cable method for predicting residual useful life | |
| CN105954228A (en) | Method for measuring content of sodium metal in oil sand based on near infrared spectrum | |
| CN109614714A (en) | A kind of method for establishing model of acidified milk fragrance aesthetic quality control | |
| CN102221534A (en) | Mid-infrared spectrum method for quickly identifying engine fuel type |
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 | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20171120 Address after: Kolding road high tech Zone of Suzhou City, Jiangsu province 215000 No. 78 Su Gaoxin Software Park Building No. 2 Patentee after: SUZHOU NIUMAG ELECTRONIC TECHNOLOGY CO., LTD. Address before: 200093 Shanghai military road, Yangpu District, No. 516 Patentee before: University of Shanghai for Science and Technology |
|
| TR01 | Transfer of patent right |