CN101140226B - Method for detecting arsenic in scenting agent with AOTF near-infrared spectrometer - Google Patents
Method for detecting arsenic in scenting agent with AOTF near-infrared spectrometer Download PDFInfo
- Publication number
- CN101140226B CN101140226B CN 200710017124 CN200710017124A CN101140226B CN 101140226 B CN101140226 B CN 101140226B CN 200710017124 CN200710017124 CN 200710017124 CN 200710017124 A CN200710017124 A CN 200710017124A CN 101140226 B CN101140226 B CN 101140226B
- Authority
- CN
- China
- Prior art keywords
- spices
- near infrared
- arsenic
- sample
- spectrum data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Abstract
The present invention discloses a method to detect arsenic in spice with an AOTF near infrared spectrograph, which comprises procedures below: A. Calibrating samples are prepared according to actual situations of tested spice solution and a specific arsenic content grade; B. The AOTF near infrared spectrograph collects near infrared spectrum data of the calibrating sample; C. A rated calibrating model is created based on relevant data of the near infrared spectrum data corresponding to the arsenic content; D. Near infrared spectrum data of the spice sample to be tested are collected; E. Arsenic content of the spice sample to be tested is analyzed in light of the calibrating model above to measure arsenic content in the spice sample to be tested. The present invention has the advantages ofunnecessary sample preprocessing, quick detection (second-level), no reagent consumption, pollution-free and environment-friendly analysis and high accuracy, etc.
Description
Technical field
The present invention relates to a kind of detection method of arsenic, relate in particular to a kind of method of utilizing the acousto-optic filter near infrared spectral instrument to detect arsenic in the spices.
Background technology
Arsenic is the native element in the environment, but also is a kind of extremely toxic substance and is threatening human health.Modal arsenide is arsenic trioxide, is commonly called as arsenic, white arsenic etc., and the semifinished product of using on the agricultural is blush, is commonly called as arsenic, and other arsenide has arsenate and arsenite etc.It is extremely toxic substance that arsenic is clearly regarded as, and to be confirmed to be one of chief-criminal of lung cancer and cutaneum carcinoma.The arsenide of every water soluble or diluted acid all is extremely toxic substance, sneaks in the food to work the mischief to human body.After arsenide enters human body, draining slowly, mainly is combine with the sulfydryl of zymoprotein and accumulate in organizing, and enzyme is lost activity, and various dystrophias and malaise symptoms occur.There is burn feeling in acute arsenic poisoning patient throat, occurs tormina then, symptom such as suffer from vomiting and diarrhoea, and weight person loses one's senses, paralysis and dead.The dosis toxica of arsenic trioxide is 0.005～0.05g, and lethal quantity is 0.1～0.3g.
The food additives particularly restriction of the arsenic content in the essence are often out in the cold, and along with the revision of country to arsenic limit standard in the food, the detection of arsenic content also more and more is much accounted of in the essence.
Arsenic Determination on content method in the spices, national standard method is GB8450-87: lignocaine two bamic acids silver colourimetry.Its principle is: in the presence of potassium iodide and stannous chloride, high price arsenic in the sample liquid is reduced to trivalent arsenic, the hydrogen in statu nascendi effect that trivalent arsenic and zinc granule and acid produce, generate arsine gas, after lead acetate cotton is removed the sulfuretted hydrogen interference, the lignocaine two bamic acids silver solution that will be dissolved in triethanolamine-methenyl choloride or in the pyridine absorbs and effect, generates aubergine network and thing, and is more quantitative with standard.In this The whole analytical process, use nearly 13 kinds of chemical reagent, and comprise strong acid and strong bases such as nitric acid, sulfuric acid, hydrochloric acid, NaOH, operate the careless slightly experiment accident that will cause, have a strong impact on the chemical examination health of operators.And operating process is more loaded down with trivial details, and is technical stronger, and non-technical personnel is difficult to grasp.The detection of this index also just requires just detect once every half a year on actual analysis.Therefore, the method for setting up the arsenic content in the fast detecting essence becomes the task of top priority.
It is simple that acousto-optic turnable filter near infrared detection technology has method, rapidly characteristics of high efficiency.Traditional near infrared viewpoint thinks that near-infrared spectrum technique can only detect organic component content, and can't detect trace materials.But along with the raising of light splitting technology and the upgrading of spectrometer, its signal to noise ratio (S/N ratio) of acousto-optic filter near infrared spectral instrument of employing latest generation light splitting technology is compared with the instrument that adopts the earlier generations light splitting technology and is wanted high a lot, so the sensing range of instrument has also obtained respective extension.Test discovery by the applicant, the acousto-optic filter near infrared spectral instrument can effectively detect the content of trace arsenic in the spices.By retrieval, relevant research and the patent of utilizing the acousto-optic filter near infrared spectral instrument to detect the method for arsenic in the spices do not see that report is arranged.
Summary of the invention
At above-mentioned the deficiencies in the prior art, the problem to be solved in the present invention provides a kind of sample pretreatment that do not need, and detection speed fast (second step velocity) does not consume reagent, pollution-free, the acousto-optic filter near infrared spectral instrument that utilizes that accuracy is high detects the method for arsenic in the spices.
The method of utilizing the acousto-optic filter near infrared spectral instrument to detect arsenic in the spices of the present invention may further comprise the steps:
A. prepare the correcting sample collection according to the actual conditions of tested spices propylene glycol solution according to certain arsenic concentration concentration gradients;
B. utilize the near infrared spectrum data of acousto-optic filter near infrared spectral instrument acquisition correction sample sets sample;
C. set up the quantitative correction model according near infrared spectrum data with the corresponding associated data of arsenic content;
D. gather the near infrared spectrum data of spices propylene glycol solution sample to be measured;
E. according to the above-mentioned calibration model of setting up the arsenic in the spices sample to be measured is carried out quantitative test, determine the content of arsenic in the spices sample to be measured;
Wherein: the actual conditions of the described tested spices propylene glycol solution of steps A are: the CONCENTRATION DISTRIBUTION situation of arsenic content in the actual spices propylene glycol solution that uses; Described correcting sample collection is meant that the sample that is used for setting up model can contain the scope that chemical analysis can bear, and can fully represent the sample of whole background informations of original sample again.The described near infrared spectrum data collection of step B or D is carried out in the test sample mode of transmission, and each Zhang Guangpu is the average result of 1～500 scanning, and wavelength coverage is 780nm～2500nm, and wavelength increment is 0.3～20nm; The method for building up of the described quantitative correction model of step C is: with the near infrared spectrum data of gathering through the single order differential handle 5～13 in odd point level and smooth, import analysis software, and it is spectroscopic data is corresponding one by one with the data of arsenic content, adopt partial least-squares regression method, validation-cross is set up and is formed fully; Described spices is that food or tobacco are used spices.
The described near infrared spectrum data collection of above-mentioned steps B or D, the liquid measure dedicated probe that preferably uses the Luminar of Brimrose company 5030 type near infrared spectrometers to install additional.
During the described spectra collection of above-mentioned steps B or D, each Zhang Guangpu all is preferably the average result of 80～200 scannings, the preferred 1100nm～2300nm of wavelength coverage, and wavelength increment is preferably 1～10nm.
Wherein: during the described spectra collection of step B or D, each Zhang Guangpu all most preferably is the average result of 100 scannings, and wavelength coverage is 1100nm～2300nm, and wavelength increment most preferably is 2nm.
The above-mentioned utilization in the method that the acousto-optic filter near infrared spectral instrument detects arsenic in the spices: described analysis software preferably adopts Norway CAMO company's T he Unscrambler analysis software.
Hardware device involved in the present invention and software and mathematics manipulation mode are existing routine techniques, and the concrete operations that relate to all can be implemented according to universal method.
The present invention utilizes the acousto-optic turnable filter NIR technology, near infrared light is produced the principle of characteristic absorption according to organism functional group, near infrared spectrum data by analytic sample, utilization partial least-squares regression method (PLS1) is set up Quantitative Analysis Model, has realized the fast quantification of arsenic in the spices sample to be measured is detected.
The outstanding effect of the inventive method is: this detection method does not need to consume any chemical reagent fully, only need the near infrared spectrum of test sample can in seconds obtain the very high quantitative analysis results of precision, and do not destroy detected sample and do not need sample is carried out pre-service, be a kind of analytical technology of environmental protection.In addition, acousto-optic filter near infrared spectral instrument volume is little, is easy to carry, and can carry out the scene easily and detect, and has improved work efficiency greatly.
The present invention utilizes acousto-optic turnable filter near infrared detection technology to analyze arsenic content in the spices, method is simple, efficient rapidly, compare with the national standard detection method, adopt the acousto-optic turnable filter near infrared technology to detect the method environmental protection of arsenic content, not consuming any reagent, do not destroy sample, is a kind of detection method rapidly and efficiently.
Description of drawings
The abosrption spectrogram of Fig. 1 .1 spices
The abosrption spectrogram of Fig. 2 .2 spices
The abosrption spectrogram of Fig. 3 .3 spices
The single order differential smoothing figure of Fig. 4 .1 spices
The single order differential smoothing figure of Fig. 5 .2 spices
The single order differential smoothing figure of Fig. 6 .3 spices
The spectroscopic data of sample is corresponding with the content data of As in Fig. 7 .The Unscrambler software
The PLS1 regression model of Fig. 8 .1 spices As
The PLS1 regression model of Fig. 9 .2 spices As
The PLS1 regression model of Figure 10 .3 spices As
Figure 11. predicted value as the one-level data after the model of No. 1 spices As
Embodiment
The present invention is further described below in conjunction with drawings and Examples.
Instrument condition and sample preparation:
Instrument: the portable acousto-optic tunable optical filter of the Luminar 5030 types technology near infrared spectrometer that U.S. BRIMROSE company produces, critical piece comprises: opticator, control section, power supply adaptor, fibre-optical probe, notebook computer.The instrument wavelength coverage be 1100nm to 2300nm, the wavelength increment of 2nm, scanning times is 100, adopts the InGaAs detecting device, test light path 15mm.Norway CAMO company's T he Unscrambler analysis software.
Sample: select the spices sample of the different purposes of commercially available 3 producers, numbering is respectively 1,2, No. 3, and all samples is propylene glycol solution spices.No. 1 sample size is 210ml, for showing spices; No. 2 sample size 200ml are sweet-smelling spices; 3 good sample size 230ml are bed material spices.Three samples all are diluted to 300ml with propylene glycol.No. 1, No. 2 color sample is more shallow, does not have viscosity; No. 3 sample compares thickness, and color is very dark.
Utilize the acousto-optic filter near infrared spectral instrument that trace arsenic (As) in the selected different spices is measured.
According to the proportioning of table 1 with As with each 25ml constant volume of three spices samples, preparation obtains shown in the table 1 content of As in the final solution.
The preparation table of table 1, As spices sample
Metering system:
This experiment amounts to 30,10 samples of each producer with the spices sample that the acousto-optic filter near infrared spectral instrument scans the As for preparing with the spices of 3 different manufacturers respectively.The concentration range of As is 0.2ppm～2.0ppm, every sample of 0.2ppm preparation.Use the Brimrose Luminar of company 5030 type near infrared spectrometers to install the liquid measure dedicated probe additional, the spectroscopic data of the mode collection liquid sample by transmission.
The spectra collection mode is for to reach probe in the test tube of contain fluid, and liquid will be full of the barbed portion of probe, rocks probe, and bubble is eliminated, and measures then.Each Zhang Guangpu is the average result of 100 scannings, and wavelength coverage is from 1100nm to 2300nm, and wavelength increment is 2nm.The equal continuous sweep of each sample ten times obtains ten spectrograms.
The spectroscopic data of all samples is handled (level and smooth) at 9 through the single order differential, import The Unscrambler analysis software, the spectroscopic data of each sample is corresponding one by one with the content data of As, utilize PLS1 (minimum partially square law) to calculate then to create Quantitative Analysis Model (to see Fig. 8～Figure 10).
From Fig. 8 to Figure 10 as can be seen: As has good correlativity, and related coefficient is more than 0.97.The As solution that No. 1 spices disposed is not accurate enough, and the dispersion degree of each data point is bigger, and related coefficient is relatively low.The As solution accuracy of No. 2, No. 3 spices configurations is higher, and very high related coefficient is all arranged, and the dispersion degree of data point is very little, but has other concentration preparation not accurate enough.
Prediction:
This experiment is built together and has been found 3 models, is respectively the As model of No. 1 spices; The As model of No. 2 spices; The As model of No. 3 spices.Because each sample has scanned 10 times, obtain 10 spectrum, with 1 spectrum of 10 spectrum average out to of each sample, obtain 30 spectrum of all samples so.Utilize above 3 models respectively 10 sample spectra of 1,2, No. 3 spices to be predicted that obtain the predicted value of As content, the deviation of predicted value and reference value the results are shown in Table 2.
Test accuracy and repeatability for verification model, in the test to No. 3 spices totally 10 samples, extract out at random and be numbered 303,307,310 3 samples and predict, each sample measurement 3 times, calling the As model of No. 3 spices predicts, well predicted the outcome and good repeatability, seen Table 3.
Table 2, call 3 models predicting the outcome to all As samples
Predicting the outcome of table 3, No. 33 samples of spices
Analyze:
As can be seen from Table 2: predicting the outcome of the As content in No. 3 spices is best, and reference value that provides and predicted value are the most approaching, and predicting the outcome of No. 2 spices taken second place, and No. 1 spices is poor slightly.Analyzing reason, may be that the concentration of No. 1 spices preparation is not accurate enough, provides promptly that to set up the one-level data that model uses not accurate enough, and the one-level data are accurate may set up a good model, can not set up a good model certainly but data are inaccurate.From Fig. 8 also as can be seen: because data is not accurate enough, the dispersion degree of each data place's point is very big.Though model has good related coefficient, accuracy for predicting is relatively poor.
Not accurate enough for the one-level data that illustrate No. 1 spices provided, the present invention verifies by following method.Near infrared spectral analysis is by adopting multivariate calibration methods to set up quantitative relationship between near infrared spectrum and the tested character, and the establishment of this relation is based upon on the basis of statistical regression and theory of errors.The near-infrared spectrum analysis model is a regression results, and it predicts the outcome and more approach " true value " on statistical significance.According to above theoretical foundation, we can be with the near infrared predicted value of As in the table 2 as " true value ", and are corresponding with the spectrum of sample, rebulid the verification model of As, and 10 samples of No. 1 spices are predicted, the results are shown in Table 4, table 5.
By table 4 as can be seen: the related coefficient of verification model is well more a lot of than master mould.The comparison that predicts the outcome of table 5, also as can be seen, the prediction mean deviation of verification model is more much smaller than the prediction mean deviation of master mould.Thereby proved that the one-level data that provided in No. 1 spices are not accurate enough.
Table 4: front and back model related coefficient relatively
| Related coefficient | Master mould | Verification model |
| As | 0.9739 | 0.9949 |
Table 5: the front and back model As comparison that predicts the outcome
Conclusion:
Through selecting the experimental result explanation of a plurality of spices of different manufacturers, utilize the acousto-optic filter near infrared spectral instrument effectively to detect to other trace of ppm level As in the spices.Though the process of experiment is the spice solution that obtains the As content of certain gradient by preparation As in the solution of spices, but there has not been too big difference with the spices of reality, therefore, can conclude that the present invention can detect the As content of ppm rank concentration effectively in the spices test of reality.
Claims (4)
1. method of utilizing the acousto-optic filter near infrared spectral instrument to detect arsenic in the spices may further comprise the steps:
A. prepare the correcting sample collection according to the actual conditions of tested spices propylene glycol solution according to certain arsenic concentration concentration gradients;
B. utilize the near infrared spectrum data of acousto-optic filter near infrared spectral instrument acquisition correction sample sets sample;
C. set up the quantitative correction model according near infrared spectrum data with the corresponding associated data of arsenic content;
D. gather the near infrared spectrum data of spices to be measured the third two glycol solution samples;
E. according to the above-mentioned calibration model of setting up the arsenic in the spices sample to be measured is carried out quantitative test, determine the content of arsenic in the spices sample to be measured;
Wherein: the actual conditions of the described tested spices propylene glycol solution of steps A are: the CONCENTRATION DISTRIBUTION situation of arsenic content in the actual spices propylene glycol solution that uses; The described near infrared spectrum data collection of step B or D is carried out in the test sample mode of transmission, and each Zhang Guangpu is the average result of 1～500 scanning, and wavelength coverage is 780nm～2500nm, and wavelength increment is 0.3～20nm; The method for building up of the described quantitative correction model of step C is: with the near infrared spectrum data of gathering through the single order differential handle 5～13 in odd point level and smooth, import analysis software, and it is spectroscopic data is corresponding one by one with the data of arsenic content, adopt partial least-squares regression method, validation-cross is set up and is formed fully; Described spices is that food or tobacco are used spices.
2. the method for utilizing the acousto-optic filter near infrared spectral instrument to detect arsenic in the spices according to claim 1, it is characterized in that: the described near infrared spectrum data collection of step B or D, the liquid measure dedicated probe that uses the Brimrose Luminar of company 5030 type near infrared spectrometers to install additional.
3. the method for utilizing the acousto-optic filter near infrared spectral instrument to detect arsenic in the spices according to claim 1, it is characterized in that: during the described spectra collection of step B or D, each Zhang Guangpu is the average result of 80～200 scannings, wavelength coverage is 1100nm～2300nm, and wavelength increment is 1～10nm.
4. the method for utilizing the acousto-optic filter near infrared spectral instrument to detect arsenic in the spices according to claim 3, it is characterized in that: during the described spectra collection of step B or D, each Zhang Guangpu is the average result of 100 scannings, and wavelength coverage is 1100nm～2300nm, and wavelength increment is 2nm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200710017124 CN101140226B (en) | 2007-09-04 | 2007-09-04 | Method for detecting arsenic in scenting agent with AOTF near-infrared spectrometer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200710017124 CN101140226B (en) | 2007-09-04 | 2007-09-04 | Method for detecting arsenic in scenting agent with AOTF near-infrared spectrometer |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN101140226A CN101140226A (en) | 2008-03-12 |
| CN101140226B true CN101140226B (en) | 2010-11-03 |
Family
ID=39192264
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 200710017124 Active CN101140226B (en) | 2007-09-04 | 2007-09-04 | Method for detecting arsenic in scenting agent with AOTF near-infrared spectrometer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101140226B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102213674A (en) * | 2011-04-08 | 2011-10-12 | 北京市农林科学院 | Method for detecting lime substances in flour by near infrared spectroscopy |
| CN102998288A (en) * | 2012-09-26 | 2013-03-27 | 广西师范大学 | Aptamer-nanometer gold syntony Rayleigh scattering spectra method for measuring As (III) in water |
-
2007
- 2007-09-04 CN CN 200710017124 patent/CN101140226B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN101140226A (en) | 2008-03-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102252992B (en) | Method for performing near-infrared on-line detection in process of extracting Chinese medicines | |
| CN103018195B (en) | Method for determination of PCTFE content in PBX explosive by near infrared spectrum | |
| CN102636454A (en) | Method for quickly measuring content of low carbon number fatty acid in edible oil by near infrared spectrum | |
| CN101413885A (en) | Near-infrared spectrum method for rapidly quantifying honey quality | |
| CN101221125A (en) | Method for measuring eutrophication water body characteristic parameter by spectrum technology | |
| CN104048941A (en) | Method for quickly measuring content of multiple index components in radix ophiopogonis through near infrared spectroscopy | |
| CN105486655A (en) | Rapid detection method for organic matters in soil based on infrared spectroscopic intelligent identification model | |
| CN102128807B (en) | Method for quickly detecting concentration of droplet on crop leaf | |
| CN104849232A (en) | Method for rapid detection of contents of water and protein in royal jelly | |
| CN105486662A (en) | Cottonseed gossypol content non-destructive measurement method based on near-infrared spectrum technology | |
| CN106525761A (en) | Nitrite detection method based on terahertz spectroscopy scanning | |
| CN105352913A (en) | Method for detecting polysaccharide content of ganoderma lucidum extract through near-infrared spectroscopy | |
| Nespeca et al. | Multivariate filters combined with interval partial least square method: A strategy for optimizing PLS models developed with near infrared data of multicomponent solutions | |
| CN104596976A (en) | Method for determining protein of paper-making reconstituted tobacco through ear infrared reflectance spectroscopy technique | |
| CN104865322A (en) | Rapid detection method for concentration process of Fructus Gardeniae extract liquor | |
| CN104849234A (en) | Assay method for analyzing contents of principal components of imidacloprid based on near-infrared spectrum | |
| CN101140225B (en) | Method for detecting lead in scenting agent with AOTF near-infrared spectrometer | |
| CN104266998A (en) | Near-infrared spectrum detection method for isocyanate group content in spandex prepolymer | |
| CN101140226B (en) | Method for detecting arsenic in scenting agent with AOTF near-infrared spectrometer | |
| CN107300535A (en) | The method of near-infrared quick detection organic fertilizer active constituent content | |
| CN103592256A (en) | Mid-infrared spectroscopic method for distinguishing normal edible vegetable oil from refined hogwash oil based on Fourier transform | |
| CN102759515A (en) | Method for rapidly determining oil contents of agricultural products by using mid-infrared spectrometer based on horizontal attenuated total reflection (ATR) | |
| CN104596982A (en) | Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology | |
| Liu et al. | Rapid detection of hydrolyzed leather protein adulteration in infant formula by near-infrared spectroscopy | |
| CN101650306A (en) | Method for quickly testing and analyzing quality of sericite |
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 |