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CN106018452A - Peanut variety nondestructive testing method based on nuclear magnetic resonance technology - Google Patents

Peanut variety nondestructive testing method based on nuclear magnetic resonance technology Download PDF

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Publication number
CN106018452A
CN106018452A CN201610286076.4A CN201610286076A CN106018452A CN 106018452 A CN106018452 A CN 106018452A CN 201610286076 A CN201610286076 A CN 201610286076A CN 106018452 A CN106018452 A CN 106018452A
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peanut
sample
magnetic resonance
nuclear magnetic
cpmg sequence
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谭明乾
臧秀
冯骥
陈腾
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Dalian Polytechnic University
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Dalian Polytechnic University
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    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N24/00Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects
    • G01N24/08Investigating or analyzing materials by the use of nuclear magnetic resonance, electron paramagnetic resonance or other spin effects by using nuclear magnetic resonance

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  • High Energy & Nuclear Physics (AREA)
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Abstract

The invention relates to a peanut variety nondestructive testing method based on the nuclear magnetic resonance technology. The peanut variety nondestructive testing method comprises the specific steps that firstly, a plurality of peanut samples are selected, nuclear magnetic resonance transverse relaxation scanning is carried out on the peanut samples with a CPMG sequence, processing is carried out with a one-dimensional inversion Laplace algorithm, and the semaphore of unit mass of the samples is obtained; secondly, CPMG sequence peak point data of the peanut samples is processed with a main ingredient analyzing method, and a main ingredient scatter diagram is obtained; thirdly, peanuts of an unknown variety are taken, and nuclear magnetic resonance transverse relaxation scanning is carried out on the peanut sample of an unknown variety with the same CPMG sequence, measured CPMG sequence peak point data is taken and subjected to main ingredient analysis, and the variety of the peanut sample of an unknown variety is determined with contrast to the main ingredient scatter diagram, obtained in the second step, of the peanut samples. The method has the advantages of being high in analyzing speed and analyzing efficiency, free of pollution to the environment, and free of influences on the health of experiment operators, and can provide a reliable basis for analyzing and identifying the variety of peanuts.

Description

A kind of peanut varieties lossless detection method based on nuclear magnetic resonance technique
Technical field
The invention belongs to peanut varieties quick nondestructive analysis field, be specifically related to a kind of low-field nuclear magnetic resonance and differentiate The method of peanut varieties.
Background technology
Peanut nutrition is worth height, has the laudatory titles such as Solanum muricatum, Your Highness, papaw, is China or even the world Important industrial crops and oil crop.In recent years, the nutritive value of Semen arachidis hypogaeae by scientific research personnel by experiment by Step confirms, Chris professor Ai Sente of such as state Pennsylvania university is found through experiments, Oleum Arachidis hypogaeae semen meals Food, almost as olive oil meals, has well effect in terms of prevention and cure of cardiovascular disease.The fat of Semen arachidis hypogaeae In 80% be unsaturated fatty acid, in Semen arachidis hypogaeae possibly together with much can anticancer, defying age material (Cui Fenggao. flower Raw communication, 2003,6:11-12).But, the Semen arachidis hypogaeae of different cultivars, in nutritive value and taste flavor all Having the biggest difference, traditional method needs complicated sample pre-treatments in terms of identifying peanut quality, and (Soxhlet is taken out Lifting manipulation) process, waste time and energy, it is impossible to realize the Semen arachidis hypogaeae of different cultivars is carried out lossless quick detection.
Nuclear magnetic resonance technique is an important analysis and detection technology, has been widely used in each neck Territory.
There is the atomic nucleus of fixed magnetic moment, such as 1H, 13C, 31P, 19F, 15N, 129Xe etc., in perseverance Fixed magnetic field, with under the effect of alternating magnetic field, absorbs in the form of an electromagnetic wave or releases energy, and atomic nucleus occurs Transition, produces the phenomenon of NMR signal, i.e. atomic nucleus and radio-frequency region electromagnetic wave generation energy exchange simultaneously. The control instrument of nuclear magnetic resonance, NMR technique and quality is widely used in food, and medicine and chemicals manufacture etc. are numerous Industry.What at present application was more is with the Hydrogen Proton (1H) nuclear magnetic resonance technique as object of study.The week of Hydrogen Proton Enclose and there is the least magnetic field.The most each proton is simultaneously in the small magnetic field of other protons, can be subject to The impact in other proton magnetic fields.And this impact is typically to be determined by the distance between proton, between proton Distance the biggest, influence each other the least.The when that distance when between proton being smaller, the nuclear magnetic resonance, NMR of sample T2 (T2) is less, and on the contrary, the when that distance when between proton being bigger, the T2 of sample is bigger. Therefore, T2 is to be determined with arrangement by the intrinsic molecular structure of sample itself, it is possible to reflect to a certain extent The micro molecule structure of sample.The arrangement relative close of molecular solids, T2 is less;And the arrangement of fluid molecule The most sparse, T2 is bigger.
The protection of geographical sign food China be increasingly subject to pay attention to, from the most indistinguishable not With the Semen arachidis hypogaeae of kind, the present invention is fully recognized that the importance and necessity that peanut varieties differentiates.
Summary of the invention
It is an object of the invention to provide a kind of method identifying peanut varieties, the method can be used for differentiating difference The Semen arachidis hypogaeae of kind, and it is fast, simple to operate to detect speed.
In order to achieve the above object, the invention provides a kind of peanut varieties based on nuclear magnetic resonance technique lossless Detection method, specifically comprises the following steps that
S1, choose some peanut samples, by CPMG sequence, described peanut sample is carried out nuclear-magnetism altogether respectively Shake after transverse relaxation scanning, mass normalisation, with one-dimensional anti-Laplacian algorithm T2 composed into Row processes, and obtains the semaphore of described peanut sample unit mass;The signal recorded according to described peanut sample Amount, draws semaphore-T2 (T2) curve of described peanut sample;
In above-mentioned steps, peanut sample need not do any process, peanut grain.
The parameter of the nuclear magnetic resonance, NMR of described mensuration peanut sample is:
FID sequential parameter: P1=4.00 μ s, TD=1024, NS=6~8, RFD=0.002~0.008ms, TW=8000.000~18000.000ms, RG1=10.0db, DRG1=3~5;
CPMG sequence parameter: NECH=10000~18000, DL1=0.02~0.100ms, RFD=0.002~ 0.06ms, TW=8000.000~18000.000ms, DRG1=3~5, NS=6~8;
The CPMG sequence peak dot number of each peanut sample that step S1 is obtained by S2, employing PCA According to processing, utilize CPMG sequence peak dot data as the factor, carry out principal component analysis, extract main one-tenth Divide PC1, PC2, PC3, utilize these three main constituent to make three-dimensional scatterplot, be the master of each peanut sample Composition scatterplot;
S3, take some unknown kind Semen arachidis hypogaeaes and make sample, use the CPMG sequence pair identical with step S1 Described unknown kind Semen arachidis hypogaeae sample carries out nuclear magnetic resonance, NMR transverse relaxation scanning, takes the CPMG sequence peak dot recorded Data carry out principal component analysis, the main constituent scatterplot of each peanut sample that comparison step S2 prepares, and determine institute State the kind of unknown kind Semen arachidis hypogaeae sample.
Wherein, PC is the abbreviation of principal component.
Under optimal way, in step S1, each peanut sample repeats 3 nuclear magnetic resonance, NMR transverse relaxations scanning, The meansigma methods that semaphore is three testing results of the described peanut sample unit mass obtained.
Under optimal way, also include step S2 ' between step S2 and step S3: use chemical gauging step The oil content of peanut sample described in rapid S1 or moisture content;Described oil content or moisture content are recorded with step S1 The semaphore-T2 curve of described peanut sample be fitted, and then obtain described peanut sample Kind predictive value and the dependency of actual value.
The present invention uses in Origin 8.5 and makees correlation analysis, choose described peanut sample kind predictive value with Two row variable data of actual value, select statistics → descriptive statistics → correlation successively Coefficient → pearson ' s correlation method is analyzed, and obtains the relative coefficient of two groups of numerical value.
Different peanut varieties presents different states in terms of the index such as oil content, moisture content, sets up oil-containing The dependency of rate or moisture content and spin spinrelaxation, if correlation coefficient is more than 80%, explanation can be by low The spin spinrelaxation T2 of field nuclear-magnetism technical measurement predicts peanut varieties.
Under optimum way, the assay method of described oil content is soxhlet extraction, and concrete operations are:
After described peanut sample freeze-day with constant temperature 3 hours, weigh about 15 grams, pour into and mortar is crushed to oily Thing leaches, and is fully enclosed in filtration paper cylinder;Adding petroleum ether, solid-liquid ratio is 1g:10ml;It is transferred to surname extraction In device, it is placed in 60 DEG C of constant water bath box extraction, until the petroleum ether in extraction tube detects oil-free through sheet glass Stop extracting during mark, reclaim extracting solution;Extract complete by after filtration paper cylinder natural drying 24 hours, 105 DEG C of bakings Dry 4 hours, take out and be cooled to room temperature, weigh;By rotated for described extracting solution be evaporated to steam without solution after, Weigh oil quality, and calculate the oil content of peanut sample.
Under optimum way, the assay method of described moisture content is for utilizing electric drying oven with forced convection, and 105 DEG C are dried to perseverance Weight, measures moisture loss amount and is the actual water content of described peanut sample.
Advantages of the present invention:
1, the inventive method identify Semen arachidis hypogaeae kind time detection speed fast, simple to operate, it is not necessary to physics smash, The pre-treatment steps such as chemical extraction, characteristic component separation, can directly use peanut grain to identify;Use low field Nuclear-magnetism technology makes a distinction, the most convenient and swift, simple to operate, and provides for protection terrestrial reference food Strong means, can not only improve detection speed, and can realize Non-Destructive Testing, are greatly promoted detection effect Rate.
2, the inventive method is during identifying, it is not necessary to using any auxiliary reagent, analysis cost is low.
3, the inventive method has analysis speed soon, and analysis efficiency is high, and environmentally safe, to experimental implementation The health of person such as has no effect at the outstanding advantages, can be that analysis and identification peanut varieties provides reliable foundation.
Accompanying drawing explanation
Fig. 1 is the photo figure of the Semen arachidis hypogaeae of different cultivars;
Fig. 2 be different cultivars Linyi, Shandong Semen arachidis hypogaeae (four, Shandong is red for Shandong blackcurrant pigment, Shandong blighted peanuts, The little white sand in Shandong, Shandong major peanut) the T2 relaxation time scheme;
Fig. 3 is to scheme in the T2 relaxation time of four Folium Styracis Suberifoliae Semen arachidis hypogaeaes of different sources;
Fig. 4 be different cultivars Linyi, Shandong Semen arachidis hypogaeae (four, Shandong is red for Shandong blackcurrant pigment, Shandong blighted peanuts, The little white sand in Shandong, Shandong major peanut) principal component analysis figure;
Fig. 5 is the principal component analysis figure of four Folium Styracis Suberifoliae Semen arachidis hypogaeaes of different sources.
Detailed description of the invention
Below in conjunction with the accompanying drawings, further illustrate the essence of the present invention with embodiments of the invention, but be not right The restriction of the present invention.
Embodiment 1: utilize magnetic nuclear resonance method to identify the different cultivars Semen arachidis hypogaeae in the same place of production
Step 1: take the peanut sample in the Linyi, Shandong of five different cultivars gathered in the crops then, the black flower in Linyi, Shandong Raw (Shandong blackcurrant pigment), Linyi, Shandong blighted peanuts (Shandong blighted peanuts), raw (four, the Shandong of four, Linyi, Shandong Flos Carthami Red), Linyi, Shandong little white sand Semen arachidis hypogaeae (the little white sand in Shandong), Linyi, Shandong major peanut rice (Shandong major peanut) as mark Quasi-product, every kind of 500g.
Semen arachidis hypogaeae selected by the present embodiment meets the normal distribution rule of Semen arachidis hypogaeae colony, and Shandong blackcurrant pigment is black;Mountain Four, east is red for cerise, glossy;Shandong blighted peanuts is light red, and Shandong major peanut is lighter than blighted peanuts, Grain is the fullest;The little white sand in Shandong is the most saturating the white of powder, as it is shown in figure 1, laboratory observation for convenience, Peanut pellets in this figure remains crust.
Step 2: open NM12 type nuclear magnetic resonance analyser (Shanghai Niu Mai scientific & technical corporation) at 25 DEG C is stable Instrument about 30min, takes 7g in test dedicated hard glass tubing, it is ensured that its height is more than 20mm every time, FID sequential parameter: 90 ° of burst length P1=4.00 μ s, sampling number TD=1024, sample frequency SW =200.0KHz, radio frequency signal frequency main value SF=11MHz, radiofrequency signal side-play amount O1=788292.7Hz, Accumulative frequency NS=8.When starting control parameter RFD=0.002ms in sampling time, the wait of repeated sampling Between TW=8000.00ms, analog gain RG1=10.0db, digital gain DRG1=3, wherein SF and O1 Jointly representing mid frequency, O1 detects every time and is all automatically adjusted, and finds the suitableeest TW=8000.00ms value, Then Carr-Purcell-Meiboom-Gill (CPMG) sequence is utilized, when measuring the transverse relaxation of peanut sample Between T2:CPMG sequential parameter: SF=11MHz, O1=788292.7Hz, P1=4.00 μ s, 180 ° of pulses Time P2=8.00 μ s, signal sampling counts TD=415992, echo number NECH=10000, time delay DL1=0.10ms, SW=200KHz, RFD=0.002ms, TW=8000.00ms, RG1=10.0db, DRG1=3, repeated sampling times N S=8.
Step 3: use one-dimensional anti-Laplacian algorithm as T2 T2 inversion algorithm (iteration time Number: 1000000), every part of sample repeated sampling 3 times, ask its meansigma methods as the semaphore of each sample, Then semaphore is obtained normalized signal measured by each sample as mass normalisation.Again every part of sample is returned One change signal amplitude, as vertical coordinate, takes T2 value and draws laterally relaxing of each kind as abscissa, drafting spectrogram Henan characteristic collection of illustrative plates (Fig. 2).
The T2 trend of the Semen arachidis hypogaeae of different cultivars is identical as seen from Figure 2, but the flower of different cultivars at each peak Raw peak area and appearance time are the most incomplete same.Shandong major peanut, Shandong blackcurrant pigment, four, Shandong Flos Carthami life, Shandong blighted peanuts, the little white sand in Shandong, T21 < have oils and fats peak at 1ms, but peak area and Go out peak position to be different from.As one of feature of different cultivars Semen arachidis hypogaeae, Semen arachidis hypogaeae can be made a distinction herein With Rapid identification.
Step 4: utilize CPMG sequence peak dot data as the factor, carry out principal component analysis: by Semen arachidis hypogaeae sample In the transverse relaxation number of product, T21, T22, T23, A21, A22, A23 carry out principal component analysis as the factor, Wherein, T21, T22, T23 represent three transverse relaxation appearance times respectively, and A21, A22, A23 are respectively It is three areas going out peak.According to analysis result, choose three kinds of main constituents, the most named PC1, PC2, PC3, utilize these three main constituent to make three-dimensional scatterplot (Fig. 3).
Above-mentioned CPMG peak dot data are the data collecting pea form under CPMG sequence, i.e. apply After 90 ° of radio-frequency pulses, being applied with the most again multiple 180 ° of radio-frequency pulses, the signal obtained is that a plurality of index is bent The attenuation curve that line is formed by stacking.
Main constituent scatterplot is the visual representation of identification result, and the essence whether different samples can be distinguished is The difference of sample constituent, the relaxation characteristic of heterogeneity proton there are differences, and these differences are to pass through Relaxation curve and main constituent scatterplot can intuitively embody.
Can be fine from figure 3, it can be seen that magnetic resonance relaxation data can be utilized to combine PCA The Semen arachidis hypogaeae of different cultivars is distinguished on ground.
Embodiment 2: magnetic nuclear resonance method is used for distinguishing four the Flos Carthamis lifes of Jilin white sand and four, Linyi, Shandong Flos Carthami Raw
It is raw raw with four, Linyi, Shandong Flos Carthami right as detection that the present embodiment have chosen four Flos Carthamis of Jilin white sand As, two kinds of four red cerises that are, glossy, and four, Jilin is red more deeper than the color in Shandong, such as Fig. 1 Shown in.
Step 1: use method and parameter as identical in embodiment 1, to four Folium Styracis Suberifoliae Semen arachidis hypogaeaes of Jilin white sand and mountain Four, Linyi, east Flos Carthami is raw to be measured, and draws its T2 relaxation spectrogram (Fig. 4), is analyzed permissible to this figure Find out that the Semen arachidis hypogaeae of same kind different sources there are differences on its peak height with peak area.
Step 2: in order to more obviously find out difference, uses the method in embodiment 1, in conjunction with principal component analysis Method drawing three-dimensional scatterplot (Fig. 5), the Semen arachidis hypogaeae that different sources can be better seen can utilize nuclear-magnetism to believe Number good differentiation, explanation magnetic resonance method can differentiate the Semen arachidis hypogaeae of different sources effectively intuitively.
Containing fat and moisture, the different types of flower of Semen arachidis hypogaeae or the same place of production of different sources in the food such as Semen arachidis hypogaeae Raw oil content, moisture content certainly exist difference, by the relaxation of the various sample of nuclear magnetic resonance spectroscopy software collection Henan signal, mathematically carries out back analysis to relaxation signals, and can obtain that other means are difficult to obtain treats The inversional curve of test sample product, reflects the relaxation collection of illustrative plates of different sample.In conjunction with chemometrics method master Component analysis, it is achieved the discriminating of different Semen arachidis hypogaeaes.
The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention not office Being limited to this, any those familiar with the art is in the technical scope of present disclosure, according to this The technical scheme of invention and inventive concept thereof in addition equivalent or change, all should contain the protection in the present invention Within the scope of.

Claims (5)

1. a peanut varieties lossless detection method based on nuclear magnetic resonance technique, it is characterised in that specifically walk Rapid as follows:
S1, choose some peanut samples, by CPMG sequence, described peanut sample is carried out nuclear-magnetism altogether respectively Shake after transverse relaxation scanning, mass normalisation, with one-dimensional anti-Laplacian algorithm T2 composed into Row processes, and obtains the semaphore of described peanut sample unit mass;The signal recorded according to described peanut sample Amount, draws the semaphore-T2 curve of described peanut sample;
The parameter of the nuclear magnetic resonance, NMR of described mensuration peanut sample is:
FID sequential parameter: P1=4.00 μ s, TD=1024, NS=6~8, RFD=0.002~0.008ms, TW=8000.000~18000.000ms, RG1=10.0db, DRG1=3~5;
CPMG sequence parameter: NECH=10000~18000, DL1=0.02~0.100ms, RFD=0.002~ 0.06ms, TW=8000.000~18000.000ms, DRG1=3~5, NS=6~8;
The CPMG sequence peak dot number of each peanut sample that step S1 is obtained by S2, employing PCA According to processing, utilize CPMG sequence peak dot data as the factor, carry out principal component analysis, extract main one-tenth Divide PC1, PC2, PC3, utilize these three main constituent to make three-dimensional scatterplot, be the master of each peanut sample Composition scatterplot;
S3, take some unknown kind Semen arachidis hypogaeaes and make sample, use the CPMG sequence pair identical with step S1 Described unknown kind Semen arachidis hypogaeae sample carries out nuclear magnetic resonance, NMR transverse relaxation scanning, takes the CPMG sequence peak dot recorded Data carry out principal component analysis, the main constituent scatterplot of each peanut sample that comparison step S2 prepares, and determine institute State the kind of unknown kind Semen arachidis hypogaeae sample.
The most according to claim 1, peanut varieties lossless detection method based on nuclear magnetic resonance technique, it is special Levying and be, in step S1, each peanut sample repeats 3 nuclear magnetic resonance, NMR transverse relaxations scanning, described To the meansigma methods that semaphore is three testing results of peanut sample unit mass.
The most according to claim 1, peanut varieties lossless detection method based on nuclear magnetic resonance technique, it is special Levy and be, also include step S2 ' between step S2 and step S3: use chemical gauging step S1 institute State oil content or the moisture content of peanut sample;The described flower that described oil content or moisture content are recorded with step S1 Semaphore-T2 the curve of raw sample is fitted, and then obtains the prediction of described peanut sample kind Value and the dependency of actual value.
The most according to claim 3, peanut varieties lossless detection method based on nuclear magnetic resonance technique, it is special Levying and be, the assay method of described oil content is soxhlet extraction, and concrete operations are:
After described peanut sample freeze-day with constant temperature 3 hours, weigh about 15 grams, pour into and mortar is crushed to oily Thing leaches, and is fully enclosed in filtration paper cylinder;Adding petroleum ether, solid-liquid ratio is 1g:10ml;It is transferred to surname extraction In device, it is placed in 60 DEG C of constant water bath box extraction, until the petroleum ether in extraction tube detects oil-free through sheet glass Stop extracting during mark, reclaim extracting solution;Extract complete by after filtration paper cylinder natural drying 24 hours, 105 DEG C of bakings Dry 4 hours, take out and be cooled to room temperature, weigh;By rotated for described extracting solution be evaporated to steam without solution after, Weigh oil quality, and calculate the oil content of peanut sample.
The most according to claim 3, peanut varieties lossless detection method based on nuclear magnetic resonance technique, it is special Levying and be, the assay method of described moisture content is for utilizing electric drying oven with forced convection, and 105 DEG C dry to constant weight, and measures Moisture loss amount is the actual water content of described peanut sample.
CN201610286076.4A 2016-04-29 2016-04-29 Peanut variety nondestructive testing method based on nuclear magnetic resonance technology Pending CN106018452A (en)

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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107991337A (en) * 2017-12-11 2018-05-04 四川大学 It is a kind of to be suitable for the drying low-field nuclear magnetic resonance Non-Destructive Testing line with shell fruit
CN108445035A (en) * 2018-04-25 2018-08-24 中国农业大学 A method of corn monoploid seed is differentiated based on nuclear magnetic resonance CPMG attenuation curves
CN109254027A (en) * 2018-11-01 2019-01-22 西南石油大学 A kind of mud cake closure evaluating apparatus and evaluation method based on low-field nuclear magnetic resonance
CN109696450A (en) * 2019-01-17 2019-04-30 南京林业大学 A kind of method of enabling non-destructive determination simple grain vegetable seeds oil content
CN112285144A (en) * 2020-10-15 2021-01-29 青岛农业大学 Method for detecting breast myopathy of white feather broiler chicken by using low-field nuclear magnetic resonance

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002056000A1 (en) * 2001-01-12 2002-07-18 Universite De Victor Segalen Bordeaux 2 Discriminating method with location and/or identification of situations of biological perturbations by spectrometry and pattern recognition
WO2013062260A1 (en) * 2011-10-26 2013-05-02 한국표준과학연구원 Method and apparatus for identifying extremely-low-magnetic-field nuclear magnetic resonance material
EP2664941A1 (en) * 2012-05-17 2013-11-20 Istituto di Ricerche Chimiche e Biochimiche "G. Ronzoni" Method for deciding whether a sample is consistent with an established production norm for heterogeneous products
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
CN104950005A (en) * 2014-03-26 2015-09-30 中国科学院大连化学物理研究所 Qualitative analysis method for distinguishing water contents of lightly dried sea cucumber, salt dried sea cucumber and expanded sea cucumber

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2002056000A1 (en) * 2001-01-12 2002-07-18 Universite De Victor Segalen Bordeaux 2 Discriminating method with location and/or identification of situations of biological perturbations by spectrometry and pattern recognition
WO2013062260A1 (en) * 2011-10-26 2013-05-02 한국표준과학연구원 Method and apparatus for identifying extremely-low-magnetic-field nuclear magnetic resonance material
EP2664941A1 (en) * 2012-05-17 2013-11-20 Istituto di Ricerche Chimiche e Biochimiche "G. Ronzoni" Method for deciding whether a sample is consistent with an established production norm for heterogeneous products
CN104950005A (en) * 2014-03-26 2015-09-30 中国科学院大连化学物理研究所 Qualitative analysis method for distinguishing water contents of lightly dried sea cucumber, salt dried sea cucumber and expanded sea cucumber
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

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
姜潮 等: "基于低场核磁共振技术的大米品种快速鉴别", 《食品工业科技》 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107991337A (en) * 2017-12-11 2018-05-04 四川大学 It is a kind of to be suitable for the drying low-field nuclear magnetic resonance Non-Destructive Testing line with shell fruit
CN108445035A (en) * 2018-04-25 2018-08-24 中国农业大学 A method of corn monoploid seed is differentiated based on nuclear magnetic resonance CPMG attenuation curves
CN109254027A (en) * 2018-11-01 2019-01-22 西南石油大学 A kind of mud cake closure evaluating apparatus and evaluation method based on low-field nuclear magnetic resonance
CN109696450A (en) * 2019-01-17 2019-04-30 南京林业大学 A kind of method of enabling non-destructive determination simple grain vegetable seeds oil content
CN112285144A (en) * 2020-10-15 2021-01-29 青岛农业大学 Method for detecting breast myopathy of white feather broiler chicken by using low-field nuclear magnetic resonance
CN112285144B (en) * 2020-10-15 2022-12-27 青岛农业大学 Method for detecting breast myopathy of white feather broiler chicken by using low-field nuclear magnetic resonance

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Application publication date: 20161012