CN104502389A - Detection method for coconut milk - Google Patents
Detection method for coconut milk Download PDFInfo
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- CN104502389A CN104502389A CN201510038775.2A CN201510038775A CN104502389A CN 104502389 A CN104502389 A CN 104502389A CN 201510038775 A CN201510038775 A CN 201510038775A CN 104502389 A CN104502389 A CN 104502389A
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Abstract
The invention establishes a detection method for identifying coconut milk quality with a hydrogen NMR (nuclear magnetic resonance)-pattern recognition technology: adopt a 1H-NMR technology to measure a coconut milk sample, pick up information and transform the information into a data matrix. Make use of a PLS-DA method to analyze data, and establish an identification model. Result: the coconut milk sample containing additive can be distinguished from a qualified coconut milk sample effectively, and simultaneously, coconut milk samples of five manufacturers can also reflect that a certain difference exists. The method is a reliable, fast and effective detection means for identifying the entire quality of the coconut milk, and can distinguish true and false coconut milk and the products of different manufacturers.
Description
Technical field
The present invention relates to a kind of detection method, specifically, relate to the detection method that employing hydrogen nuclear magnetic resonance-mode identification technology is differentiated coconut milk, belong to the technical field of food being carried out to Quality Control Analysis technique study.
Background technology
Food security is directly connected to the healthy of people and quality of life, how effectively to monitor food quality, is a difficult problem of pendulum in face of scientific worker.The food inspection technology rationalization inspection that China commonly uses, spectral technique, chromatographic technique, microwave digestion technology and biotechnology etc.But food composition is complicated, different detection techniques often can only detecting portion composition and have the deficiencies such as complex pretreatment.In recent years, apply hydrogen nuclear magnetic resonance (
1h-NMR) be the mode identification technology sight line entering people just progressively of detection method.
1the feature that H-NMR has fast, do not destroy sample, can detect Multiple components simultaneously, is just meeting the detection demand of food complicated ingredient.Certainly,
1the overlap of H nuclear magnetic resonance map signal makes collection of illustrative plates become very complicated, but pattern-recognition (pattern recognition, PR) method can information extraction to greatest extent from the data of complexity.
Coconut milk is a kind of daily drink with certain nutritive value processed by Coconut Juice and coconut meat, it preserves the peculiar flavour of coconut, and unsaturated fatty acid and rich in protein, not containing sterol, there is good summer-heat removing, promote the production of body fluid to quench thirst effect, from once the dark favor by consumers in general of coming out.The raw material coconut of coconut milk is mainly distributed in Hainan Province of China.Therefore, the coconut milk secondary industry of Hainan Region is also relatively flourishing, and is wherein no lack of esbablished corporation.But in the production of food industry, the phenomenon of the illegal sale of other compositions etc. of adulterating in personation famous-brand and high-quality goods original producton location, food is of common occurrence.
The invention provides a kind of new method of the coconut milk quartile length based on hydrogen nuclear magnetic resonance-mode identification technology, can effectively distinguish coconut milk certified products and adulterant, also can show the difference of different manufacturer.
Summary of the invention
The object of this invention is to provide a kind of based on the detection method of hydrogen nuclear magnetic resonance-mode identification technology to coconut milk quartile length, for checking the true and false of coconut milk, adulterated, the method can the inherent total quality of objective effective detection coconut milk product, the defect avoiding traditional food inspection technology only to analyze the part Testing index in coconut milk complex system bringing.
Technical scheme of the present invention: with hydrogen nuclear magnetic resonance technology for detection method, principal component analysis (PCA) in mode in recognition technology and ginsenoside are analysis means, by the coconut milk qualified samples of some through sample preparation, measure, based on the normal data obtained after data processing, form standard model database, verify with method with part qualified samples and failed test sample, final with 95% credibility interval of java standard library data for benchmark, discriminatory analysis is carried out to coconut milk sample to be measured, as testing sample drops in 95% credibility interval by the data that same procedure obtains, then differentiate as qualified, otherwise be defective.
The present invention includes following analytical procedure:
(1) sample pre-treatments: accurate absorption coconut milk 0.1mL-5mL, 20 DEG C of-80 DEG C of evaporated under reduced pressure, residue adds 0.2mL-0.8mL DMSO-d
6dissolve in rearmounted 2mL centrifuge tube, be more than or equal to centrifugal 2min-30min under 5000r/min condition, get supernatant 0.5mL immigration 5mm nuclear magnetic tube to be measured;
(2) assay method is hydrogen nuclear magnetic resonance method; Nuclear magnetic resonance analyser refers to 300MHz, the instrument of 400MHz, 500MHz, 600MHz or more;
(3)
1the condition determination of H-NMR: constant temperature at 296K, with DMSO-d
6as internal lock, scan 16-128 time, sampling time territory is 64k, spectrum width is-1500Hz-13000Hz, and the sampling time is 2.66s, and recurrent interval D1 is 3.00s, the presaturation pulse train (zgpr) of employing standard suppresses water peak-to-peak signal, namely obtains each sample
1h-NMR composes;
(4) data processing and analysis: the principal component analysis (PCA) or the offset minimum binary-techniques of discriminant analysis that refer to mode identification technology;
(5) discriminatory analysis method: based on the data mainly obtained after above-mentioned sample preparation, mensuration, collection of illustrative plates and data processing by the qualified coconut milk sample of some, form basic sample data storehouse and verify, with 95% credibility interval of this database data for benchmark, Qualitive test is carried out to coconut milk sample to be measured; The data that testing sample obtains by same procedure compared with database data, the data as testing sample drop in 95% credibility interval of database data, then differentiate that this sample is qualified, as dropped on outside 95% credibility interval, then differentiate as defective;
Coconut milk sample refers to coconut milk (slurry and meat) raw material or its beverage manufactured goods.
In one embodiment of the invention, its step (1) is accurate absorption coconut milk 0.5mL, and 45 DEG C of evaporated under reduced pressure, residue adds 0.5mL DMSO-d
6dissolve in rearmounted 2mL centrifuge tube, centrifugal 5min under 15000r/min condition, get supernatant 0.5mL and move in 5mm nuclear magnetic tube;
In one embodiment of the invention, scanning 32 times in its step (3), spectrum width is 8000.0Hz.
Advantage and disadvantage of the present invention is: adopt hydrogen nuclear magnetic resonance-ginsenoside method first, 56 × 184 data matrixes obtained using the specification product of A company coconut milk (Y1-56) are as training set, coconut milk (Y57-64,8 × 184 of other companies; Y65-70,6 × 184; Y71-78,8 × 184; Y79-90,12 × 184) and the data matrix that obtains of additive test sample (Y91-94,4 × 184) carry out respectively verifying and distinguishing as different test sets separately.Result shows, this method can accurately judge coconut milk certified products and unacceptable product, can the preventative monitoring coconut milk various exceptions of producing, overcome the defect of current standard methods, there is analytical cycle simultaneously short, operation is simple, the significantly reduced feature of environmental pollution, therefore the method can be used as a kind of effective ways controlling coconut milk inherent quality, and along with constantly including in of more certified products data, training set sample size continues to increase, the representativeness of database increases thereupon, the accuracy differentiated also just improves thereupon, this more effectively can implement comprehensive quality control to coconut milk.
Accompanying drawing explanation
The PLS-DA score scatter diagram of Fig. 1 different company coconut milk sample;
The PLS-DA score scatter diagram of the qualified coconut milk sample of Fig. 2 and additive sample;
The PLS-DA score scatter diagram of Fig. 35 company's coconut milk samples.
Embodiment
1 instrument, software, sample
Instrument: rotary evaporator SENCOR-201 (Shen Shun bio tech ltd, Shanghai); Benchtop microcentrifuge TG-16S (Sichuan Shu Ke Instrument Ltd.); Electronic balance Sartorius BS 224s (Beijing Sai Duolisi instrument system company limited); Nuclear magnetic resonance analyser Bruker AV II-400 (Brruker company, Germany); Thermostat water bath W201D (Shen Shun bio tech ltd, Shanghai); DMSO-d
6(ARMAR chemicals).
Data analysis software: Excel; MestReNova8.1.1; SIMCA-P 11.5;
This is tested coconut milk sample used and all comes from the specification product that market is sold, have collected the coconut milk product of 5 brands altogether: wherein Y1-56 is A company sample, Y57-64 is B company sample, and Y65-70 is C company sample, Y71-78 is D company sample, and Y79-90 is E company sample.The specification product of one batch, Ling Qu A company two bottles, carry out additive experiment, and additive 1 (essence) is liquid, and additive 2 (sweetener) is powder.Coconut milk sample message is in table 1.
Table 1 sample source information table
The preparation of 2 samples
The preparation of coconut milk test sample: accurate absorption coconut milk 0.5mL, 45 DEG C of evaporated under reduced pressure, residue adds 0.5mL DMSO-d
6dissolve in rearmounted 2mL centrifuge tube, centrifugal 5min under 15000r/min condition, get supernatant and move into 5mm nuclear magnetic tube, be i.e. obtained confession
1the sample solution (each sample parallel prepares two test samples) that H-NMR spectrum measures.
The preparation of additive test sample: before sampling, add additive 1 and additive 2 in A company coconut milk certified products.The consumption of additive 1 is 0.25mL/ bottle, and the consumption of additive 2 is 20mg/ bottle.After interpolation, shake up, then operate equally by the preparation method of certified products test sample, i.e. obtained confession
1additive test sample solution (often kind of parallel preparation of additive two samples) that H-NMR spectrum measures.
3
1the condition determination of H-NMR
Constant temperature at 296K, with DMSO-d
6as internal lock, scan 32 times, sampling time territory is 64k, and spectrum width is 8000.0Hz, and the sampling time is 2.66s, and recurrent interval D1 is 3.00s, adopts the presaturation pulse train (zgpr) of standard to suppress water peak-to-peak signal.
4 collection of illustrative plates process and collecting methods
The each sample obtained will be measured
1h-NMR free damping (FID) signal imports MestReNova software, carry out phase place and baseline adjustment respectively, and calibration graph chemical displacement value is (with DMSO-d
6chemical displacement value δ 2.50 is chemical displacement value benchmark).
By δ 0 ~ 7.5 interval (removing solvent peak δ 2.40 ~ 2.60) of often opening collection of illustrative plates after the calibration of acquisition, carry out subsection integral by 0.04 chemical displacement value unit, obtain integrated value corresponding to chemical displacement value section.By data importing in Excel, integrated value is carried out to the standardization of area normalization, obtain the data matrix of sample number × integration section; PLS-DA pattern analysis is carried out by these data importings to soft sim CA-P.56 × 184 data matrixes obtained using the specification product of A company coconut milk as training set, coconut milk (Y57-64,8 × 184 of other companies; Y65-70,6 × 184; Y71-78,8 × 184; Y79-90,12 × 184) and the data matrix that obtains of additive test sample (Y90-94,4 × 184) distinguish respectively as different test sets separately.
The investigation of 5 detection methods
In conjunction with the actual conditions of this experiment, the repeatability of sample drawing spectrum processing method and sample-pretreating method is investigated.This test adopts included angle cosine as judge index.
Figure spectrum processing method repeatability is investigated: get for examination A brand coconut milk (lot number: 20100701) prepare 1 part, coconut milk sample, record
1h-NMR collection of illustrative plates is a, with above-mentioned collection of illustrative plates disposal route re-treatment 5 times, obtains the relative peak area integrated value of corresponding collection of illustrative plates.To process the data that obtain for the first time for contrast, the included angle cosine value calculated between these 5 groups of data is 1.000 respectively, illustrates that this repeatability of testing figure spectrum processing method used is very good.
Sample-pretreating method repeatability is investigated: get for examination A brand coconut milk (lot number: 20110519) prepare 5 parts, coconut milk sample, mensuration
1h-NMR collection of illustrative plates, collection of illustrative plates obtains 5 groups of integrated value data after treatment.At random with the data of a sample for contrast, the included angle cosine value calculated between 5 increment product is respectively: 1.000,0.9996,0.9998,0.9996,0.9989.Calculated value, all more than 0.99, illustrates that this sample preparation methods has good repeatability.
6 Analysis of test results
Coconut milk sample analysis between 6.1 different companys
Using the data of the coconut milk sample (Y1-56) of A company as training set, respectively the data of the coconut milk sample (Y57-64, Y65-70, Y70-78, Y79-90) of other four companies are carried out PLS-DA analysis as test set.
The analysis of A company sample and B company sample: first analyze and extract major component, first three major component accumulation contribution rate, to 87.54%, meets and analyzes requirement, can analyze.Transverse and longitudinal coordinate drafting score scatter diagram (Figure 1A) is respectively with the score value (t [2]) of the score value of its major component 1 (t [1]) and major component 2.Can visually see from Fig. 1, the coconut milk sample of A company mainly concentrates on t [1] (-5 ~ 10) and t [2] (-15 ~ 15) interval, it is interval that B company coconut milk sample is then distributed in t [1] (-25 ~-5) and t [2] (-15 ~ 5), has clear and definite difference between the two.
The analysis of A company sample and C company sample: first analyze and extract major component, first three major component accumulation contribution rate, to 89.11%, meets and analyzes requirement, can analyze.Transverse and longitudinal coordinate drafting score scatter diagram (Fig. 1) is respectively with the score value (t [2]) of the score value of its major component 1 (t [1]) and major component 2.Can visually see from Fig. 1, the coconut milk sample of A company mainly concentrates on t [1] (-5 ~ 10) and t [2] (-15 ~ 15) interval, it is interval that C company coconut milk sample is then distributed in t [1] (-3 ~-20) and t [2] (-20 ~ 0), has clear and definite difference between the two.
The analysis of A company sample and D company sample: first analyze and extract major component, first three major component accumulation contribution rate, to 86.42%, meets and analyzes requirement, can analyze.Transverse and longitudinal coordinate drafting score scatter diagram (Fig. 1) is respectively with the score value (t [2]) of the score value of its major component 1 (t [1]) and major component 2.Can visually see from Fig. 1, the coconut milk sample of A company mainly concentrates on t [1] (-5 ~ 10) and t [2] (-10 ~ 15) interval, it is interval that D company coconut milk sample is then distributed in t [1] (-5 ~-30) and t [2] (-15 ~ 5), has clear and definite difference between the two.
The analysis of A company sample and E company sample: first analyze and extract major component, first three major component accumulation contribution rate, to 93.81%, meets and analyzes requirement, can analyze.Transverse and longitudinal coordinate drafting score scatter diagram (Fig. 1 D) is respectively with the score value (t [2]) of the score value of its major component 1 (t [1]) and major component 2.Can visually see from Fig. 1 D, the coconut milk sample of A company mainly concentrates on t [1] (-5 ~ 10) and t [2] (-15 ~ 15) interval, it is interval that E company coconut milk sample is then distributed in t [1] (-5 ~-35) and t [2] (-20 ~ 15), has clear and definite difference between the two.
The PLS-DA of 6.2 qualified samples and illegal additive sample analyzes
With coconut milk sample (Y1-54) data of A company for training set, A coconut milk sample (Y91-94) data being added with coconut milk essence and sweetener are carried out PLS-DA analysis as training set.Extract major component, the accumulation contribution rate of front 7 major components, to 87.67%, can be analyzed, and draws score scatter diagram (Fig. 2) with major component 1 score value t [1] to major component 2 score value t [2].Can be learnt by Fig. 2, it is interval that the qualified sample number strong point of A company is mainly distributed in t [1] (-15 ~ 20) and t [2] (-10 ~ 8), it is interval that coconut milk sample (Y91-94) data point containing additive is then mainly distributed in t [1] (-15 ~-25) and t [2] (4 ~ 10), has difference clearly between the two.
The PLS-DA of 6.3 5 qualified samples of company's coconut milk analyzes
The coconut milk sample (Y1-56, Y57-64, Y65-70, Y70-78, Y79-90) of 5 companies is imported SIMCA-P software and carries out PLS-DA analysis.Extract major component by software analysis, the accumulation contribution rate of front 9 major components, to 87.29%, can be analyzed, and draws score scatter diagram (Fig. 3) with major component 1 score value t [1] to major component 2 score value t [2].
The distribution situation at each company's sample number strong point as can be seen from Figure 3: the data point distribution of A company sample is interval in t [1] (0 ~ 10) and t [2] (-15 ~ 5), the data point distribution of B company sample is interval in t [1] (-10 ~ 5) and t [2] (-5 ~ 10), the data point distribution of C company sample is interval in t [1] (-2 ~ 6) and t [2] (-2 ~ 6), the data point distribution of D company sample is interval in t [1] (-3 ~ 6) and t [2] (2 ~ 25), and the data point distribution of E company sample is interval in t [1] (-30 ~-8) and t [2] (-10 ~ 10).
Above-mentioned analysis result display, the sample data distribution of A, B, C, D tetra-companies is comparatively concentrated, but and have obvious difference between E company sample data, illustrate that the coconut milk of E company has very large difference at the coconut milk sample of raw material sources and process aspect and other four companies.And at A, B, C, D tetra-in company's sample data, the sample data of A company and C company intersects, but also there is some difference, illustrates that A company is consistent with technics comparing with the raw material sources of C company, but still show the small difference of different company's production.There are differences between the sample data of B, D company and the sample data of A company and C company.But the degree of difference is less, B, D company that illustrates existing similarity but have differentiation in raw material sources and production technology.
7 conclusions
The present embodiment successfully establishes the coconut milk sample data of employing hydrogen nuclear magnetic resonance-ginsenoside (PLS-DA) method to different company to carry out detecting the new method analyzed.The method is with a company (A company) coconut milk sample
1h-NMR data are training set, respectively with other company's coconut milk samples
1when H-NMR data carry out PLS-DA analysis, significantly can distinguish the coconut milk sample of different brands.
The present embodiment attempts the coconut milk sample of all companies to carry out simultaneously
1when H-NMR-PLS-DA analyzes, only have the sample of a company to have notable difference, the otherness of the sample room display of other companies is less.
The present embodiment has also carried out the analytical test of additive, after adding additive, then carries out in certified products
1h-NMR-PLS-DA analyzes, and result shows between the sample of additive and qualified samples exists notable difference, directly can judge that the sample containing additive is defective.Illustrate that the detection sensitivity of this method is higher, effectively can differentiate specification product.
Claims (3)
1. differentiate a detection method for coconut milk, its content comprises the steps:
(1) sample pre-treatments: accurate absorption coconut milk 0.1mL-5mL, 20 DEG C of-80 DEG C of evaporated under reduced pressure, residue adds 0.2mL-0.8mL DMSO-d
6dissolve in rearmounted 2mL centrifuge tube, be more than or equal to centrifugal 2min-30min under 5000r/min condition, get supernatant 0.5mL immigration 5mm nuclear magnetic tube to be measured;
(2) assay method is hydrogen nuclear magnetic resonance method; Nuclear magnetic resonance analyser refers to 300MHz, the instrument of 400MHz, 500MHz, 600MHz or more;
(3)
1the condition determination of H-NMR: constant temperature at 296K, with DMSO-d
6as internal lock, scan 16-128 time, sampling time territory is 64k, spectrum width is-1500Hz-13000Hz, and the sampling time is 2.66s, and recurrent interval D1 is 3.00s, the presaturation pulse train (zgpr) of employing standard suppresses water peak-to-peak signal, namely obtains each sample
1h-NMR composes;
(4) data processing and analysis: the principal component analysis (PCA) or the offset minimum binary-techniques of discriminant analysis that refer to mode identification technology;
(5) discriminatory analysis method: based on the data mainly obtained after above-mentioned sample preparation, mensuration, collection of illustrative plates and data processing by the qualified coconut milk sample of some, form qualified samples database and verify, with 95% credibility interval of this database data for benchmark, Qualitive test is carried out to coconut milk sample to be measured; The data that testing sample obtains by same procedure compared with database data, the data as testing sample drop in 95% credibility interval of database data, then differentiate that this sample is qualified, as dropped on outside 95% credibility interval, then differentiate as defective;
Coconut milk sample refers to coconut milk (slurry and meat) raw material or its beverage manufactured goods.
2. detection method according to claim 1, it is characterized in that accurate absorption coconut milk 0.5mL in step (1), 45 DEG C of evaporated under reduced pressure, residue adds 0.5mL DMSO-d
6dissolve in rearmounted 2mL centrifuge tube, centrifugal 5min under 15000r/min condition, get supernatant 0.5mL and move in 5mm nuclear magnetic tube.
3. detection method according to claim 1, it is characterized in that scanning 32 times in step (3), spectrum width is 8000.0Hz.
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| CN111965207A (en) * | 2020-06-29 | 2020-11-20 | 厦门大学 | Low-field nuclear magnetic resonance combined mode recognition technology olive oil adulteration detection method |
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Application publication date: 20150408 |