CN101701909A - Rapid detection method of trace pesticide - Google Patents
Rapid detection method of trace pesticide Download PDFInfo
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- CN101701909A CN101701909A CN 200910236834 CN200910236834A CN101701909A CN 101701909 A CN101701909 A CN 101701909A CN 200910236834 CN200910236834 CN 200910236834 CN 200910236834 A CN200910236834 A CN 200910236834A CN 101701909 A CN101701909 A CN 101701909A
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Abstract
The invention discloses a rapid detection method of trace pesticide. The method comprises the following steps: 1. preparation of samples: preparing a plurality of filter paper samples where pesticide solution is dropped, drying the samples; 2. collection of spectra data: obtaining NIR transmission spectrums of the dried filter paper samples; and 3. analysis of spectra data: correcting the curves of the NIR transmission spectrums, performing data normalization, then collecting the numbers of principal components for modeling and building the forecasting model. The technical scheme of the invention realizes the detection of the pesticide concentration through the NIR transmission technology and the spectral data analysis method and is simple, rapid, accurate and environmentally friendly.
Description
Technical field
The present invention relates to the Pesticides Testing technical field, relate in particular to a kind of method for quick of trace pesticide.
Background technology
Whole world agricultural annual average due to illness, the loss that causes of worm, crop smothering accounts for 37% of overall crop yield, year amount of loss is up to 1,260 hundred million dollars.Agricultural chemicals is prevented and treated use in the process at the disease pest and weed of crops, can contaminated soil, water source and atmosphere.The fruit of the residues of pesticides of ingesting for a long time, vegetables can cause the human body pesticide poisoning, and the lighter shows as headache, giddy, feels sick, burnout, stomachache etc., and spasm, expiratory dyspnea, stupor, gatism then can appear in weight person, even death.In recent years, the residues of pesticides poisoning takes place repeatedly.
According to FAO (Food and Agriculture Organization of the United Nation) (FAO) statistics, China's sowing of vegetable area and output account for 43%, 49% of the world respectively, all rank first in the world.China's sowing of vegetable area reached 2.6 hundred million mu in 2007,5.65 hundred million tons of total productions, more than 420 kilogram of occupancy volume per person.Residues of pesticides are main factors of harm fruits and vegetables edible safety, some hypertoxic organophosphorus pesticide is the disabled or restriction use in each national capital in the whole world, but because China fruits and vegetables quality monitoring market standard not enough, especially some peasant households are for reaching high yield, volume increase purpose, ignore correct, the use rationally of agricultural chemicals, excessive use agricultural chemicals causes the pollution by pesticides problem often to take place, persticide residue exceeds standard seriously, and the trend of aggravation is year by year arranged.181 kinds of vegetable samples had detected 23 big and medium-sized cities in State General Administration for Quality Supervision in 2004, wherein 86 kinds of residues of pesticides surpass the national standard value of limiting the quantity of, exceeding standard rate reaches 47.5%, country prohibites the multiple organophosphorus pesticide of use, remain incessant after repeated prohibition in some places at home, also higher as the recall rate of acephatemet etc.
At present, the conventional sense method of residues of pesticides has: thin-layered chromatography, vapor-phase chromatography, high performance liquid chromatography, supercritical fluid chromatography, chromatograph-mass spectrometer coupling method, capillary electrophoresis, enzyme suppress method, immunoassay, biology sensor method, spectroscopic methodology etc.In above these detection methods, instrumental analysis detection method (various chromatographys and the mass spectroscopy mentioned above comprising) precision is the highest, but its drawback is that testing process is comparatively complicated, detection time is longer, can be used for the Accurate Analysis and the legal detection of laboratory residues of pesticides.Biochemistry detection technology (enzyme of being mentioned above comprising suppresses method, immunoassay, biology sensor method etc.) developed than very fast in recent years, but also had some defectives, and was big as early investment, requirement for experiment condition is harsh, and reagent is single etc.
Nowadays, the developing direction of Detecting Pesticide is quicker, more accurate, safer.Food security has become the cardinal task that concerns people's livelihood problem, in order to ensure consumers in general's interests, press for quick, the testing result of a kind of testing process of research and development accurately, the Detecting Pesticide method of testing process safety.
Summary of the invention
The objective of the invention is at the deficiencies in the prior art, a kind of method that can detect trace pesticide be provided, this method is simple, fast, accurately, safety.
For achieving the above object, the invention provides a kind of method for quick of trace pesticide, may further comprise the steps:
S1, the preparation of sample: prepare a plurality of filter paper sample that pesticidal solutions is arranged, and it is carried out drying;
S2, the collection of spectroscopic data: the near-infrared transmission curve of spectrum that obtains dry back filter paper sample;
S3, the analysis of spectroscopic data: the described near-infrared transmission curve of spectrum is proofreaied and correct, and the number of principal components of modeling is chosen in the line data standardization of going forward side by side then, and sets up forecast model.
Wherein, described step S2 is specifically as follows: to 32 near-infrared transmission curves of spectrum of each sample collecting, and be averaged.
Wherein, in described step S3, (MultiplicativeScatter Correction, MSC) algorithm is proofreaied and correct the described near-infrared transmission curve of spectrum can to utilize polynary scatter correction.
Wherein, in described step S3, can utilize the internal chiasma proof method to choose the number of principal components of modeling.
Wherein, in described step S3, (Partial LeastSquares Regression, PLSR) method is set up described forecast model can to adopt partial least squares regression.
Wherein, can obtain the near-infrared transmission curve of spectrum of dry back filter paper sample with near infrared spectrometer.
Wherein, in described step S1, filter paper sample is carried out dry step be specifically as follows: described filter paper sample is supported with the nail that is fixed on the cystosepiment, put into vacuum drying chamber then and carry out drying.
Compared with prior art, technical scheme of the present invention has following advantage: the present invention realizes detection to pesticide concentration by near infrared spectral transmission technology and spectral data analysis method, simple, fast, accurately, environmental protection.
Description of drawings
Fig. 1 is the method flow diagram of the embodiment of the invention;
Fig. 2 is the selected filter paper placement platform synoptic diagram of the method for the embodiment of the invention;
Fig. 3 is the spectrum picture that utilizes the filter paper pesticide sample that the method for the embodiment of the invention gathers;
Fig. 4 is the spectrum picture that utilizes the filter paper pesticide sample that obtains after the MSC algorithm process in the method for the embodiment of the invention;
Fig. 5 chooses in the method for the embodiment of the invention in the process of best major component of filter paper pesticide sample, the synoptic diagram that concerns of the number of principal components of choosing and corresponding parameter of trying to achieve;
To be the method for utilizing the embodiment of the invention predict relation between resulting actual value and the predicted value to the filter paper pesticide sample to Fig. 6.
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples are used to illustrate the present invention, but are not used for limiting the scope of the invention.
As shown in Figure 1, the method for quick according to the trace pesticide of the embodiment of the invention may further comprise the steps:
S1, the preparation of sample
It is 2.5,5,10,20,40,80,160,200,320,400 (units: solution mg/kg) that the chlopyrifos pesticides of commercially available 40% concentration is configured to concentration respectively with distilled water, is that the die for cutting of 3.2cm becomes four parts with the filter paper of 9cm by diameter, gets certain density pesticidal solutions 200 μ l with pipettor and evenly drops in the circular filter paper surface that diameter is 3.2cm.4 filter paper sample of each concentration gradient preparation, wherein 3 as calibration set, and another one is as the checking collection.The filter paper that is adsorbed with certain pesticidal solutions is placed on the independently developed filter paper placement platform, put into vacuum drying chamber dry one hour, temperature is a room temperature.It is standby that dried filter paper sample is put into sealing bag.Wherein, the structure of filter paper placement platform as shown in Figure 2, the base of this platform is the high-density foam plate, every filter paper is fixed on three that tack supports on this cystosepiment.
S2, the collection of spectroscopic data
After the specimen preparation for the treatment of all concentration finished, (it used InGaAs detecting device, spectral range 3800-12000cm can to use the ANTARIS Fourier transform near infrared spectrometer of being produced by U.S. Thermo Nicolet company
-1, minimum resolution is 2cm
-1, instrument configuration Dell P4 computer) and the acquisition of transmission curve of spectrum.To each sample collecting 32 times, be averaged then, it is standby that spectroscopic data is saved as the .csv form.Employed this spectrometer adopts 8cm in the present embodiment
-1Resolution.
S3, the analysis of spectroscopic data
At first adopt the standardization of MSC algorithm binding data to the spectroscopic data pre-service.Fig. 4 is the spectrum picture of the filter paper pesticide sample after the MSC algorithm process, with after original spectrum picture Fig. 3 contrast as can be seen, after MSC handles, can eliminate the baseline wander of spectrum preferably.
When adopting partial least square method to set up the quantitative correction model,, at first to reasonably select number of principal components, avoid occurring " owing match " and " over-fitting " phenomenon in order to utilize spectral information more all sidedly.Adopt the internal chiasma proof method to determine best number of principal components in the present embodiment, the determining as shown in Figure 5 of the best number of principal components of model.After Fig. 5 shows that filter paper agricultural chemicals dry sample adds the data standardization through polynary scatter correction, determine the process of best major component.At first, extract 1 major component of variable, use major component to set up model, model is carried out full cross validation, checking coefficient R cv when obtaining this major component and cross validation mean square deviation RMSEcv; Rcv and RMSEcv when then asking 2 major components; Rcv and RMSEcv when by that analogy, asking the individual major component of N (N=wave band number) always.Contrast the Rcv and the RMSEcv result of all major components, if the model that x major component of use set up has maximum Rcv and minimum RMSEcv, then x is the required best number of principal components that gets.As can be seen from Figure 5, when from variable, extracting 14 major components, the Rcv maximum of model (being 0.924), and RMSEcv minimum (being 0.399), therefore after filter paper agricultural chemicals dry sample was handled through data normalization, when adopting the PLSR method to set up forecast model, the variable number of principal components that is extracted was 14.
Behind the selected number of principal components, adopt the PLSR method to set up forecast model, then the precision of prediction of valuation prediction models.It is as shown in table 1 to predict the outcome, and the result shows: extracted 14 major components, the prediction related coefficient R that sets up the PLSR model has reached 0.989, and prediction standard deviation RMSEP is 0.153.Fig. 6 has shown the correlativity between chlopyrifos concentration actual value and the predicted value.
Table 1
As can be seen from the above embodiments, embodiments of the invention can be realized detection by quantitative to pesticide concentration by near infrared spectral transmission technology and spectral data analysis method, simple, fast, accurately, environmental protection.In addition, method of the present invention also can be used to detect other chemical solution.
The above only is a preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the technology of the present invention principle; can also make some improvement and modification, these improve and modification also should be considered as protection scope of the present invention.
Claims (7)
1. the method for quick of a trace pesticide may further comprise the steps:
S1, the preparation of sample: prepare a plurality of filter paper sample that pesticidal solutions is arranged, and it is carried out drying;
S2, the collection of spectroscopic data: the near-infrared transmission curve of spectrum that obtains dry back filter paper sample;
S3, the analysis of spectroscopic data: the described near-infrared transmission curve of spectrum is proofreaied and correct, and the number of principal components of modeling is chosen in the line data standardization of going forward side by side then, and sets up forecast model.
2. the method for quick of trace pesticide as claimed in claim 1 is characterized in that, described step S2 is specially: to 32 near-infrared transmission curves of spectrum of each sample collecting, and be averaged.
3. the method for quick of trace pesticide as claimed in claim 1 is characterized in that, in described step S3, utilizes polynary scatter correction algorithm that the described near-infrared transmission curve of spectrum is proofreaied and correct.
4. the method for quick of trace pesticide as claimed in claim 1 is characterized in that, in described step S3, utilizes the internal chiasma proof method to choose the number of principal components of modeling.
5. the method for quick of trace pesticide as claimed in claim 1 is characterized in that, in described step S3, adopts partial least-squares regression method to set up described forecast model.
6. the method for quick of trace pesticide as claimed in claim 1 is characterized in that, in described step S2, obtains the near-infrared transmission curve of spectrum of dry back filter paper sample with near infrared spectrometer.
7. the method for quick of trace pesticide as claimed in claim 1, it is characterized in that, in described step S1, filter paper sample is carried out dry step be specially: described filter paper sample is supported with the nail that is fixed on the cystosepiment, put into vacuum drying chamber then and carry out drying.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102636482A (en) * | 2012-03-19 | 2012-08-15 | 中国农业大学 | Rapid Dursban pesticide residue detection method combining reagent colorimetry and spectrum detection |
| CN103499530A (en) * | 2013-10-14 | 2014-01-08 | 无锡艾科瑞思产品设计与研究有限公司 | Method for rapidly detecting pesticide residues in fruits and vegetables |
| CN104237200A (en) * | 2014-09-12 | 2014-12-24 | 浙江大学 | Glyphosate concentration detection method based on Raman signals of chlorella pyrenoidosa |
| CN107300528A (en) * | 2017-07-05 | 2017-10-27 | 中科谱光科技（北京）有限公司 | A kind of vegetable pesticide residue detection method and system |
| CN108444946A (en) * | 2018-05-10 | 2018-08-24 | 苏州农业职业技术学院 | A kind of Practice for Pesticide Residue in Agricultural Products detection method and device |
| CN108776116A (en) * | 2018-08-15 | 2018-11-09 | 山东五洲检测有限公司 | A method of detection pesticide residues in fruits |
| CN114137122A (en) * | 2021-12-01 | 2022-03-04 | 青岛海关技术中心 | Method for rapidly identifying component content of full-sucrose syrup on customs inspection site |
-
2009
- 2009-11-02 CN CN 200910236834 patent/CN101701909A/en active Pending
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102636482A (en) * | 2012-03-19 | 2012-08-15 | 中国农业大学 | Rapid Dursban pesticide residue detection method combining reagent colorimetry and spectrum detection |
| CN103499530A (en) * | 2013-10-14 | 2014-01-08 | 无锡艾科瑞思产品设计与研究有限公司 | Method for rapidly detecting pesticide residues in fruits and vegetables |
| CN103499530B (en) * | 2013-10-14 | 2015-12-09 | 无锡艾科瑞思产品设计与研究有限公司 | A kind of method for quick of vegetable and fruit Pesticide Residues thing |
| CN104237200A (en) * | 2014-09-12 | 2014-12-24 | 浙江大学 | Glyphosate concentration detection method based on Raman signals of chlorella pyrenoidosa |
| CN107300528A (en) * | 2017-07-05 | 2017-10-27 | 中科谱光科技（北京）有限公司 | A kind of vegetable pesticide residue detection method and system |
| CN107300528B (en) * | 2017-07-05 | 2019-12-06 | 中科谱光科技（北京）有限公司 | vegetable pesticide residue detection method and system |
| CN108444946A (en) * | 2018-05-10 | 2018-08-24 | 苏州农业职业技术学院 | A kind of Practice for Pesticide Residue in Agricultural Products detection method and device |
| CN108776116A (en) * | 2018-08-15 | 2018-11-09 | 山东五洲检测有限公司 | A method of detection pesticide residues in fruits |
| CN114137122A (en) * | 2021-12-01 | 2022-03-04 | 青岛海关技术中心 | Method for rapidly identifying component content of full-sucrose syrup on customs inspection site |
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