CN112345654A - Method for identifying oil stain smoke pollution source based on chromatographic fingerprint spectrum - Google Patents
Method for identifying oil stain smoke pollution source based on chromatographic fingerprint spectrum Download PDFInfo
- Publication number
- CN112345654A CN112345654A CN201910720414.4A CN201910720414A CN112345654A CN 112345654 A CN112345654 A CN 112345654A CN 201910720414 A CN201910720414 A CN 201910720414A CN 112345654 A CN112345654 A CN 112345654A
- Authority
- CN
- China
- Prior art keywords
- pollution source
- peak
- oil
- identifying
- fingerprint spectrum
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000001228 spectrum Methods 0.000 title claims abstract description 50
- 239000000779 smoke Substances 0.000 title claims abstract description 19
- 235000019504 cigarettes Nutrition 0.000 claims abstract description 37
- 239000000126 substance Substances 0.000 claims abstract description 21
- 238000010586 diagram Methods 0.000 claims abstract description 15
- 238000004519 manufacturing process Methods 0.000 claims abstract description 10
- 239000003517 fume Substances 0.000 claims abstract description 8
- 239000003921 oil Substances 0.000 claims description 52
- 238000004458 analytical method Methods 0.000 claims description 30
- 230000014759 maintenance of location Effects 0.000 claims description 26
- 230000003068 static effect Effects 0.000 claims description 17
- 238000003988 headspace gas chromatography Methods 0.000 claims description 16
- 239000010687 lubricating oil Substances 0.000 claims description 10
- 238000000926 separation method Methods 0.000 claims description 9
- 238000011156 evaluation Methods 0.000 claims description 5
- 230000006698 induction Effects 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 3
- 239000005662 Paraffin oil Substances 0.000 claims description 2
- 238000005520 cutting process Methods 0.000 claims description 2
- 239000004519 grease Substances 0.000 claims description 2
- 238000012795 verification Methods 0.000 claims description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 2
- 238000002290 gas chromatography-mass spectrometry Methods 0.000 description 33
- 239000003344 environmental pollutant Substances 0.000 description 21
- 231100000719 pollutant Toxicity 0.000 description 21
- 239000012159 carrier gas Substances 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 5
- 238000011160 research Methods 0.000 description 5
- 241001177117 Lasioderma serricorne Species 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 4
- 239000006233 lamp black Substances 0.000 description 4
- 238000004949 mass spectrometry Methods 0.000 description 4
- 230000000630 rising effect Effects 0.000 description 4
- 241000208125 Nicotiana Species 0.000 description 3
- 235000002637 Nicotiana tabacum Nutrition 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000011067 equilibration Methods 0.000 description 3
- 239000003205 fragrance Substances 0.000 description 3
- 238000005303 weighing Methods 0.000 description 3
- 238000010923 batch production Methods 0.000 description 2
- 238000004587 chromatography analysis Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- VLKZOEOYAKHREP-UHFFFAOYSA-N n-Hexane Chemical compound CCCCCC VLKZOEOYAKHREP-UHFFFAOYSA-N 0.000 description 2
- URAYPUMNDPQOKB-UHFFFAOYSA-N triacetin Chemical compound CC(=O)OCC(OC(C)=O)COC(C)=O URAYPUMNDPQOKB-UHFFFAOYSA-N 0.000 description 2
- 238000003965 capillary gas chromatography Methods 0.000 description 1
- 238000012790 confirmation Methods 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000001125 extrusion Methods 0.000 description 1
- 235000013773 glyceryl triacetate Nutrition 0.000 description 1
- 239000001087 glyceryl triacetate Substances 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 238000001819 mass spectrum Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012067 mathematical method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000002203 pretreatment Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 239000002904 solvent Substances 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 229960002622 triacetin Drugs 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/04—Preparation or injection of sample to be analysed
- G01N30/06—Preparation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/26—Conditioning of the fluid carrier; Flow patterns
- G01N30/28—Control of physical parameters of the fluid carrier
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/86—Signal analysis
- G01N30/8675—Evaluation, i.e. decoding of the signal into analytical information
- G01N30/8679—Target compound analysis, i.e. whereby a limited number of peaks is analysed
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
- Library & Information Science (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The invention provides a method for identifying a fume pollution source based on a chromatographic fingerprint, which comprises the following steps: step 1: acquiring a total ion flow graph of a pollution source sample; step 2: confirming common peaks of the samples, and constructing a common peak database and a standard fingerprint of the pollution source sample; and step 3: acquiring a total ion flow diagram of an oil spot part of the oil spot cigarette paper, and extracting a characteristic peak from the total ion flow diagram; and 4, step 4: and (3) calling the common peak database in the step (2), and comparing the characteristic peak obtained in the step (3) with the standard fingerprint spectrum in the step (2) to identify the pollution source of the oily fume. The method for identifying the oil stain cigarette pollution source can quickly and accurately determine the nature of the oil stain cigarette pollution substances, further determine the specific production link and reason for generating the oil smoke, and provide support for improving the quality of cigarette products.
Description
Technical Field
The invention belongs to the field of cigarette production control, and particularly relates to a method for identifying a tobacco tar stain pollution source based on a chromatographic fingerprint spectrum.
Background
The fingerprint spectrum is a mode for identifying the authenticity and quality stability of the content, composition and the like of substances such as traditional Chinese medicinal materials, tobaccos and other complex chemical components by extracting and separating the components of the substances through a proper pretreatment method, analyzing and identifying the complex chemical components contained in the substances through chromatography or other various proper analysis methods, and identifying the content, composition and the like of the substances through other mathematical methods such as relevant data statistics, analysis and the like. The fingerprint spectrum technology has the characteristics of capability of performing macroscopic inference analysis and fuzzy fingerprint characteristic analysis and the like, and the technology has the advantages of quantification, good reproducibility, high efficiency and stability. The fingerprint spectrum technology has been successfully applied to the fields of traditional Chinese medicine extract, product quality control and the like, and is gradually applied to the field of tobacco in recent years.
Liu Bai war, etc. in "identification and source analysis of contaminated components of cigarette filters" strip the contaminated part of contaminated filters, which is sent by a cigarette factory, from cigarettes, and through n-hexane solvent extraction, capillary gas chromatography separation and chromatography/mass spectrometry combined identification, the main component of contamination appearing at the filter tip is triacetin. When Yangyeliang and the like are applied to oil fume analysis in GC-MS (gas chromatography-mass spectrometry) method, after factors of oil pollution for production equipment are eliminated, a GC-MS method is used for comparing a finished oil fume sample with oil stains obtained by extruding adult tobacco beetles and larvae thereof on cigarette paper, and the result shows that the spectrogram of the oil fume sample is consistent with the characteristic peak of the adult tobacco beetles, the characteristic peak does not appear in the adult tobacco beetles, and the oil fume is determined to be caused by the extrusion of the larvae of the tobacco beetles. Gu Shu Pi (Gu book Jing) in research on Rapid detection method of lampblack in cigarette rods respectively pretreats an oil sample for cigarette production and cigarette lampblack, firstly establishes a characteristic spectrum of the oil sample through GC-MS analysis, then determines a GC-MS spectrum of the lampblack under the same analysis conditions, and determines source substances causing the lampblack through comparison of the two.
The above documents only relate to a single method for identifying a certain pollutant, the method used is complicated and complex to operate, and the analysis result of the pollutant can be interfered by adding a solvent, so that the application of the above documents has limitations and the root cause of the production of the oil stain cigarettes cannot be traced fundamentally. The static headspace can reduce the complicated sampling preparation work of an indirect introduction method, avoid introducing new impurities, improve the speed of a gas chromatography-mass spectrometry technology for identifying and identifying substances, can simply analyze the characteristic components of various pollutant source substances by using a fingerprint, can quickly and accurately identify the pollutant substances qualitatively after establishing a database, and further quickly find out the specific production link and reason causing the generation of oil smoke, thereby providing support for improving the quality of cigarette products.
SUMMARY OF THE PATENT FOR INVENTION
The invention aims to overcome the defect that no method capable of quickly and accurately tracing the root cause of the oil stain smoke pollutants exists at present, and provides a method for establishing a fingerprint of the pollutants by using a static headspace-GC/MS analysis technology, quickly finding out the root cause of the oil stain smoke and improving the sensory quality and the appearance quality of cigarettes. The purpose of the invention is realized by the following technical scheme:
a method for identifying oil stain smoke pollution sources based on a chromatographic fingerprint spectrum is characterized by comprising the following steps:
step 1: acquiring a total ion flow graph of a pollution source sample;
step 2: confirming common peaks of the samples, and constructing a common peak database and a standard fingerprint of the pollution source sample;
and step 3: acquiring a total ion flow diagram of an oil stain part of the oil stain cigarette paper, and extracting a characteristic peak of the total ion flow diagram;
and 4, step 4: and (3) calling the common peak database in the step (2), and comparing the characteristic peak obtained in the step (3) with the standard fingerprint spectrum in the step (2) to identify the pollution source of the oily fume.
Further, a static headspace GC/MS analysis method is adopted for acquiring the total ion flow graph in the step 1 and the step 3.
Further, when a static headspace GC/MS analysis method is adopted, the headspace sampling temperature is 100-.
Preferably, in step 1, the standard substance of the pollution source is weighed in a 20mL headspace bottle, and a total ion flow diagram is obtained by static headspace-GC/MS analysis:
chromatographic conditions: a chromatographic column: HP-5MS (30m x 250 μm x 0.25.25 μm); sample inlet temperature: 280 ℃; the split ratio is as follows: 1: 1; carrier gas: he, flow rate 1.0 mL/min; temperature rising procedure: the temperature is kept at 40 ℃ for 5min, and the temperature is increased to 240 ℃ at the speed of 4 ℃/min and kept for 10 min.
Mass spectrum conditions: EI source electron energy: 70 eV; mass scan range: 30-550 amu; ion source temperature: 230 ℃; temperature of the quadrupole rods: the temperature of the transmission line is 280 ℃ at 150 ℃; gain factor: 1.00.
further, the confirmation of the common peak in step 2 is based on the retention time, the peak shape and the peak area.
Further, when the step 3 is implemented, the oil spot part on the oil spot cigarette paper collected on the actual production line is peeled off from the cigarette, and the total ion flow diagram of the oil spot part is obtained according to the analysis condition of the total ion flow diagram of the pollution source sample obtained in the step 1.
Further, the diameter of the oil stain of the cigarette is about 0.01-1.00 cm.
Further, about 20 to 100 cigarette papers with oil spots are provided.
Further, before use, the fingerprint in step 2 is subjected to similarity evaluation by a correlation coefficient method and an included angle cosine method, and the fingerprint is put into use when the similarity evaluation result is not less than 90%, and preferably more than 95%. In the implementation process of the invention, 8 batches of total ion flow graphs are selected for each pollutant source substance, and the total peak area of each sample accounts for more than 90% of the total peak area through statistics. Similarity of 8 batches of fingerprints and standard fingerprints is calculated by adopting a correlation coefficient method and an included angle cosine method respectively, and the similarity is calculated to be more than 94%, so that the established fingerprints completely accord with technical specifications.
Further, when the standard fingerprint of the sample is constructed in the step 2, at least 5 batches of samples are selected for each pollutant substance to be counted, and preferably 8-15 batches of samples are adopted for counting.
Preferably, when the GC/MS standard fingerprint is constructed in the step 2, common chromatographic peak identification is carried out on the GC-MS total ion graphs of 8 batches of samples. And finally determining the number of the common peaks through comparison of retention time, peak shape and peak area. And calculating the percentage of the total peak area occupied by the common peaks in 8 batches of analysis, ensuring that the common peaks meet the technical requirements of fingerprint spectrum research, and establishing a common peak database. And calculating the relative retention time and the relative peak area of all peaks by taking a peak with good separation degree and strong induction among all chromatographic peaks as a reference peak, and constructing a sample standard fingerprint according to two quantitative indexes of the relative retention time and the relative peak area.
Further, the pollutant source substances comprise one or more of essence, peduncle essence, sugar, lubricating oil, grease, paraffin oil, oil for cutter head/cutting disc of cigarette making machine, and condensed water.
Further, before step 1 is carried out, the method is subjected to reliability verification, and the method enters a formal implementation stage when the relative retention time and the Relative Standard Deviation (RSD) of the precision and reproducibility of the relative peak area are not higher than 2%. In order to verify the reliability of the method, in the implementation process of the step 2 of the invention, samples are continuously injected for 5 times, and the results of comparing the relative retention time and the precision and the reproducibility of the relative peak area show that the RSD is below 2%. And (3) respectively placing the samples for 0h, 8h, 1d, 3d and 5d, and then injecting a sample for stability detection, wherein the results show that the RSD of the detection results is less than 2%, which indicates that the method is very stable.
The method for establishing the static headspace-GC/MS fingerprint spectrum is an analysis means capable of well analyzing complex samples, has small workload and can reflect the integral information of the samples, and more importantly, the fingerprint spectrum has uniqueness, can quickly and accurately determine the nature of pollutants of the oil-spot cigarette, further determine the specific production link and reasons for generating oil smoke, and provide support for improving the quality of cigarette products.
Drawings
FIG. 1: the schematic representation of GC-MS total ion of Yuxi (soft) essence obtained by static headspace GC/MS analysis in example 1;
FIG. 2: schematic diagrams of 8 batches of GC-MS fingerprints of Yuxi (soft) essence constructed in example 1;
FIG. 3: the fingerprint comparison of the unknown pollutant oil stain cigarette a and the Yuxi (soft) essence in the example 1 is shown schematically;
FIG. 4: the comparison of fingerprint spectra of the unknown pollutant oil stain cigarette b and the Yuxi (soft) peduncle fragrance in the example 2 is shown schematically;
FIG. 5: the comparison of the fingerprint spectrum of the unknown pollutant oil stain smoke c and the lubricating oil in the example 3 is shown schematically.
Detailed Description
The invention will be further explained by means of specific embodiments in conjunction with the attached drawings.
Example 1
The invention relates to a method for establishing a static headspace-GC/MS fingerprint of a pollutant source substance, which is realized by the following steps:
1) and acquiring a total ion flow diagram: weighing 0.3g of Yuxi (soft) essence sample, and analyzing in a 20mL headspace bottle by adopting static headspace-GC/MS (gas chromatography-Mass Spectrometry), wherein the headspace conditions are as follows: equilibrium temperature: 140 ℃, equilibration time: 30 min; carrier gas: and (e) He. Chromatographic conditions: a chromatographic column: HP-5MS (30m x 250 μm 0.25 μm); sample inlet temperature: 280 ℃; the split ratio is as follows: 1: 1; carrier gas: he, flow rate 1.0 mL/min; temperature rising procedure: the temperature is kept at 40 ℃ for 5min, and the temperature is increased to 240 ℃ at the speed of 4 ℃/min and kept for 10 min. ③ Mass Spectrometry conditions: EI source electron energy: 70 eV; mass scan range: 30-550 amu; ion source temperature: 230 ℃; temperature of the quadrupole rods: the temperature of the transmission line is 280 ℃ at 150 ℃; gain factor: 1.00; the obtained GC/MS total ion flow chart has stable baseline, multiple response peaks and good separation degree, as shown in figure 1.
2) Establishing a fingerprint spectrum: and (3) carrying out common chromatographic peak identification on GC/MS total ion flow graphs of 8 different batches of Yuxi (soft) essence in the step 1). 16 peaks are separated from 8 batches of samples through analysis, and 13 total peaks are finally determined through comparison of retention time, peak shape and peak area. The percentage of the total peak area occupied by the common peak in 8 analyses is calculated, so that the minimum sum of the 13 common peak areas is 95.52 percent, the technical requirements of fingerprint spectrum research are met, and a Yuxi (soft) essence common peak database is constructed, as shown in figure 2. And (3) calculating the relative retention time and the relative peak area of all peaks by taking the peak with good separation degree and strong induction retention time of 22.90min as a reference peak (S), and constructing the Yuxi (soft) essence standard fingerprint according to two quantitative indexes of the relative retention time and the relative peak area. And respectively evaluating the similarity between the fingerprint spectrums of different batches of samples and the standard fingerprint spectrum by adopting a correlation coefficient method and an included angle cosine method so as to evaluate the reliability of the standard fingerprint spectrum. The results show that: the similarity of the correlation coefficient method and the included angle cosine method between each batch of characteristic peaks of the Yuxi (soft) essence and the standard fingerprint spectrum is more than 99 percent.
3) Determination of oil stain pollutant source: stripping oil stain parts of 20 pieces of oil stain cigarettes collected on a first production line sent by a Yuxi cigarette factory, carrying out static headspace-GC/MS analysis according to the analysis conditions in the step 1), comparing the obtained spectrum with a common peak database, wherein the spectrum has 9 characteristic peaks: the retention time of the common characteristic peaks of the No. 1 peak, the No. 2 peak, the No. 4 peak, the No. 8 peak, the No. 9 peak, the No. 10 peak, the No. 11 peak, the No. 12 peak and the No. 13 peak is consistent with that of the Yuxi (soft) essence, and the pollution substance of the batch of the cigarette is judged to be the Yuxi (soft) essence, as shown in figure 3.
Example 2
The invention relates to a method for establishing a static headspace-GC/MS fingerprint of a pollutant source substance, which is realized by the following steps:
1) and acquiring a total ion flow diagram: weighing 0.4g of Yuxi (soft) stem aroma sample, and analyzing in a 20mL headspace bottle by adopting static headspace-GC/MS (gas chromatography-Mass Spectrometry) under the headspace condition: equilibrium temperature: 100 ℃, equilibration time: 20 min; carrier gas: and (e) He. Chromatographic conditions: a chromatographic column: HP-5MS (30m x 250 μm 0.25 μm); sample inlet temperature: 280 ℃; the split ratio is as follows: 1: 1; carrier gas: he, flow rate 1.0 mL/min; temperature rising procedure: the temperature is kept at 40 ℃ for 5min, and the temperature is increased to 240 ℃ at the speed of 4 ℃/min and kept for 10 min. ③ Mass Spectrometry conditions: EI source electron energy: 70 eV; mass scan range: 30-550 amu; ion source temperature: 230 ℃; temperature of the quadrupole rods: the temperature of the transmission line is 280 ℃ at 150 ℃; gain factor: 1.00; the obtained GC/MS total ion flow graph has stable baseline, multiple response peaks and good separation degree;
2) establishing a fingerprint spectrum: and (3) carrying out common chromatographic peak identification on GC/MS total ion flow graphs of 8 Yuxi (soft) peduncles in different batches in the step 1). 10 peaks are totally separated out from 8 batches of samples through analysis, and 9 total peaks are finally determined through comparison of retention time, peak shape and peak area. Calculating the percentage of the total peak area occupied by the common peaks in 8 analyses, wherein the minimum sum of the 9 common peak areas is 97.79%, the technical requirements of fingerprint research are met, constructing a Yuxi (soft) peduncle fragrance common peak database, calculating the relative retention time and the relative peak area of all peaks by using a peak with good separation degree and strong induction retention time of 9.60min among all chromatographic peaks as a reference peak (S), and constructing a Yuxi (soft) peduncle fragrance standard fingerprint according to two quantitative indexes of the relative retention time and the relative peak area. And respectively evaluating the similarity between the fingerprint spectrums of different batches of samples and the standard fingerprint spectrum by adopting a correlation coefficient method and an included angle cosine method so as to evaluate the reliability of the standard fingerprint spectrum. The results show that: the similarity of the correlation coefficient method and the included angle cosine method between the characteristic peaks of each batch of Yuxi (soft) peduncle incense and the standard fingerprint spectrum is more than 94%.
3) Determination of oil stain pollutant source: stripping oil spots of 40 oil spot cigarettes collected on a fourth batch production line sent by Yuxi cigarette factory, carrying out static headspace-GC/MS analysis according to the analysis conditions in the step 1), comparing the obtained spectrum with a common peak database, wherein the number of the characteristic peaks is 7: the retention time of the No. 4 peak, the No. 5 peak, the No. 6 peak, the No. 7 peak, the No. 8 peak, the No. 9 peak and the No. 10 peak is consistent with the retention time of the common characteristic peak of the Yuxi (soft) peduncle incense, and the shape of the peaks is similar, so that the pollutant of the batch of the oil spot cigarette is judged to be the Yuxi (soft) peduncle incense, as shown in the figure 4.
Example 3
The invention relates to a method for establishing a static headspace-GC/MS fingerprint of a pollutant source substance, which is realized by the following steps:
1) and acquiring a total ion flow diagram: weighing 0.5g of lubricating oil sample in a 20mL headspace bottle, analyzing by static headspace-GC/MS (first headspace conditions): equilibrium temperature: 120 ℃, equilibration time: 10 min; carrier gas: and (e) He. Chromatographic conditions: a chromatographic column: HP-5MS (30m x 250 μm x 0.25.25 μm); sample inlet temperature: 280 ℃; the split ratio is as follows: 1: 1; carrier gas: he, flow rate 1.0 mL/min; temperature rising procedure: the temperature is kept at 40 ℃ for 5min, and the temperature is increased to 240 ℃ at the speed of 4 ℃/min and kept for 10 min. ③ Mass Spectrometry conditions: EI source electron energy: 70 eV; mass scan range: 30-550 amu; ion source temperature: 230 ℃; temperature of the quadrupole rods: the temperature of the transmission line is 280 ℃ at 150 ℃; gain factor: 1.00; the obtained GC/MS total ion flow graph has stable baseline, multiple response peaks and good separation degree;
2) establishing a fingerprint spectrum: and (3) carrying out common chromatographic peak identification on GC/MS total ion flow graphs of 8 different batches of lubricating oil in the step 1). And (3) totally separating 12 peaks from 8 batches of samples through analysis, and finally determining that the total peaks are 8 through comparison of retention time, peak shape and peak area. Calculating the percentage of the total peak area occupied by the common peak in 8 analyses, wherein the minimum sum of the 8 common peak areas is 95.04%, the technical requirements of fingerprint spectrum research are met, constructing a lubricating oil common peak database, calculating the relative retention time and the relative peak area of all peaks by using the peak with better separation degree and stronger induction among all chromatographic peaks and with the retention time of 26.99min as a reference peak (S), and constructing a lubricating oil standard fingerprint spectrum according to two quantitative indexes of the relative retention time and the relative peak area. And respectively evaluating the similarity between the fingerprint spectrums of different batches of samples and the standard fingerprint spectrum by adopting a correlation coefficient method and an included angle cosine method so as to evaluate the reliability of the standard fingerprint spectrum. The results show that: the similarity of a correlation coefficient method and an included angle cosine method between each batch of characteristic peaks of the lubricating oil and a standard fingerprint spectrum is more than 96%.
3) Determination of oil stain pollutant source: stripping oil spots of 80 oil spot cigarettes collected on a fifth batch production line sent by Yuxi cigarette factory, performing static headspace-GC/MS analysis according to the analysis conditions in the step 1), comparing the obtained spectrum with a common peak database, wherein the spectrum has 8 characteristic peaks: the No. 1 peak, the No. 2 peak, the No. 3 peak, the No. 4 peak, the No. 9 peak, the No. 10 peak, the No. 11 peak and the No. 12 peak are consistent with the retention time of the common characteristic peak of the lubricating oil and similar in peak shape, and the pollutant of the oil stain cigarette of the batch is judged to be the lubricating oil, as shown in figure 5.
Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present invention and not to limit the same; although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art will understand that: modifications to the specific embodiments of the invention or equivalent substitutions for parts of the technical features may be made; without departing from the spirit of the present invention, it is intended to cover all aspects of the invention as defined by the appended claims.
Claims (10)
1. A method for identifying oil stain smoke pollution sources based on a chromatographic fingerprint spectrum is characterized by comprising the following steps:
step 1: acquiring a total ion flow graph of a pollution source sample;
step 2: confirming common peaks of the samples, and constructing a common peak database and a standard fingerprint of the pollution source sample;
and step 3: acquiring a total ion flow diagram of an oil spot part of the oil spot cigarette paper, and extracting a characteristic peak from the total ion flow diagram;
and 4, step 4: and (3) calling the common peak database in the step (2), and comparing the characteristic peak obtained in the step (3) with the standard fingerprint spectrum in the step (2) to identify the pollution source of the oily fume.
2. The method for identifying the pollution source of the oil smoke based on the chromatographic fingerprint spectrum as claimed in claim 1, wherein the step 1 and the step 3 are obtained by a static headspace GC/MS analysis method.
3. The method as claimed in claim 2, wherein the headspace sampling temperature is 100-140 ℃, and the headspace equilibrium time is 10-40 min.
4. The method for identifying the pollution source of the oil smoke based on the chromatographic fingerprint spectrum as claimed in claim 2, wherein the identification of the common peak in the step 2 is based on retention time, peak shape and peak area.
5. The method for identifying the oil smoke pollution source based on the chromatographic fingerprint as claimed in claim 4, wherein when the standard fingerprint is constructed in the step 2, the peak with good separation degree and strong induction among all chromatographic peaks is taken as a reference peak, the relative retention time and the relative peak area of all peaks are calculated, and the sample standard fingerprint is constructed according to the two quantitative indexes of the relative retention time and the relative peak area.
6. The method for identifying the oil stain smoke pollution source based on the chromatographic fingerprint spectrum as claimed in claim 2, wherein the step 3 is implemented by peeling the oil stain part on the oil stain smoke paper collected on the actual production line from the cigarette and obtaining the total ion flow diagram of the oil stain part according to the analysis condition of the total ion flow diagram of the pollution source sample obtained in the step 1.
7. The method for identifying the pollution source of the oil smoke based on the chromatographic fingerprint spectrum according to any one of the claims 1 to 6, wherein the statistics on not less than 5 batches of samples of each pollution source substance are selected when the standard fingerprint spectrum of the samples is constructed in the step 2.
8. The method for identifying the pollution source of the oil smoke based on the chromatographic fingerprint spectrum as claimed in any one of claims 1 to 6, wherein the fingerprint spectrum in the step 2 is subjected to similarity evaluation by a correlation coefficient method and an included angle cosine method before use, and the similarity evaluation result is used when the similarity evaluation result is not less than 90 percent, preferably more than 95 percent.
9. The method for identifying the pollution source of the oil smoke based on the chromatographic fingerprint spectrum according to any one of claims 1 to 6, wherein the pollution source substances comprise one or more of essence, peduncle, sugar, lubricating oil, grease, paraffin oil, cigarette machine tool bit/cutting disc oil and condensed water.
10. The method for identifying the pollution source of the oil smoke based on the chromatographic fingerprint spectrum according to any one of claims 1 to 6, wherein before the step 1 is carried out, the method is subjected to reliability verification, and a formal implementation stage is carried out when the Relative Standard Deviation (RSD) of the relative retention time and the precision and reproducibility of the relative peak area is not higher than 2%.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910720414.4A CN112345654A (en) | 2019-08-06 | 2019-08-06 | Method for identifying oil stain smoke pollution source based on chromatographic fingerprint spectrum |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910720414.4A CN112345654A (en) | 2019-08-06 | 2019-08-06 | Method for identifying oil stain smoke pollution source based on chromatographic fingerprint spectrum |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112345654A true CN112345654A (en) | 2021-02-09 |
Family
ID=74366393
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910720414.4A Pending CN112345654A (en) | 2019-08-06 | 2019-08-06 | Method for identifying oil stain smoke pollution source based on chromatographic fingerprint spectrum |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112345654A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115015410A (en) * | 2022-05-25 | 2022-09-06 | 河北中烟工业有限责任公司 | Method for auxiliary identification of oil stain smoke pollution source |
| CN115112814A (en) * | 2022-05-25 | 2022-09-27 | 河北中烟工业有限责任公司 | Method for identifying oil spot smoke pollution source |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050113282A1 (en) * | 2003-11-20 | 2005-05-26 | Parekh Prabodh P. | Melamine-formaldehyde microcapsule slurries for fabric article freshening |
| US20070062255A1 (en) * | 2002-01-29 | 2007-03-22 | Nanotherapeutics, Inc. | Apparatus for collecting and analyzing human breath |
| CN101398412A (en) * | 2008-11-04 | 2009-04-01 | 河北大学 | Gas-chromatography fingerprinting for rapidly identifying edible oil |
| EP2373154A2 (en) * | 2008-12-03 | 2011-10-12 | Carlsberg Breweries A/S | Barley and malt-derived beverages with low dimethyl sulfide level |
| CN102288718A (en) * | 2011-05-16 | 2011-12-21 | 中国烟草总公司山东省公司 | Method for identifying genuine and fake cigarettes by using headspace-gas chromatography-mass spectrum (HS-GC-MS) total ion current chromatogram map technique |
| CN102495163A (en) * | 2011-11-17 | 2012-06-13 | 云南省烟草烟叶公司 | Establishing method and use of flue-cured tobacco GC/MS fingerprint |
| CN105675785A (en) * | 2016-01-27 | 2016-06-15 | 云南中烟工业有限责任公司 | Method for fast gas chromatography identification of quality of tobacco flavors for invitation for bids |
| CN106248850A (en) * | 2016-08-08 | 2016-12-21 | 云南中烟工业有限责任公司 | A kind of method of Fast Evaluation quality of flavoring essence for tobacco |
| CN106404884A (en) * | 2016-11-22 | 2017-02-15 | 云南中烟工业有限责任公司 | Method for quickly evaluating quality consistency of flavors and fragrances of volatile cigarettes by HS-IMR-MS |
| CN109342629A (en) * | 2018-10-30 | 2019-02-15 | 浙江中烟工业有限责任公司 | Method is determined based on the cigarette style of cigarette cracking ingredient |
| CN109425679A (en) * | 2017-08-24 | 2019-03-05 | 湖南中烟工业有限责任公司 | A method of flavouring essence for tobacco fingerprint similarity is copied based on equal power similarity analysis |
-
2019
- 2019-08-06 CN CN201910720414.4A patent/CN112345654A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070062255A1 (en) * | 2002-01-29 | 2007-03-22 | Nanotherapeutics, Inc. | Apparatus for collecting and analyzing human breath |
| US20050113282A1 (en) * | 2003-11-20 | 2005-05-26 | Parekh Prabodh P. | Melamine-formaldehyde microcapsule slurries for fabric article freshening |
| CN101398412A (en) * | 2008-11-04 | 2009-04-01 | 河北大学 | Gas-chromatography fingerprinting for rapidly identifying edible oil |
| EP2373154A2 (en) * | 2008-12-03 | 2011-10-12 | Carlsberg Breweries A/S | Barley and malt-derived beverages with low dimethyl sulfide level |
| CN102288718A (en) * | 2011-05-16 | 2011-12-21 | 中国烟草总公司山东省公司 | Method for identifying genuine and fake cigarettes by using headspace-gas chromatography-mass spectrum (HS-GC-MS) total ion current chromatogram map technique |
| CN102495163A (en) * | 2011-11-17 | 2012-06-13 | 云南省烟草烟叶公司 | Establishing method and use of flue-cured tobacco GC/MS fingerprint |
| CN105675785A (en) * | 2016-01-27 | 2016-06-15 | 云南中烟工业有限责任公司 | Method for fast gas chromatography identification of quality of tobacco flavors for invitation for bids |
| CN106248850A (en) * | 2016-08-08 | 2016-12-21 | 云南中烟工业有限责任公司 | A kind of method of Fast Evaluation quality of flavoring essence for tobacco |
| CN106404884A (en) * | 2016-11-22 | 2017-02-15 | 云南中烟工业有限责任公司 | Method for quickly evaluating quality consistency of flavors and fragrances of volatile cigarettes by HS-IMR-MS |
| CN109425679A (en) * | 2017-08-24 | 2019-03-05 | 湖南中烟工业有限责任公司 | A method of flavouring essence for tobacco fingerprint similarity is copied based on equal power similarity analysis |
| CN109342629A (en) * | 2018-10-30 | 2019-02-15 | 浙江中烟工业有限责任公司 | Method is determined based on the cigarette style of cigarette cracking ingredient |
Non-Patent Citations (4)
| Title |
|---|
| 惠非琼等: "顶空-气相色谱-质谱指纹图谱应用于烟用香精中主成分测定", 《理化检验(化学分册)》 * |
| 梁现蕊等: "静态顶空-气相色谱法用于柳叶蜡梅挥发油指纹图谱研究", 《浙江工业大学学报》 * |
| 生态环境部，《土壤环境监测分析方法》编委会: "《土壤环境监测分析方法》", 28 February 2019, 中国环境出版集团 * |
| 郭书裴: "卷烟烟支油烟的快速检测方法研究", 《轻工科技》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115015410A (en) * | 2022-05-25 | 2022-09-06 | 河北中烟工业有限责任公司 | Method for auxiliary identification of oil stain smoke pollution source |
| CN115112814A (en) * | 2022-05-25 | 2022-09-27 | 河北中烟工业有限责任公司 | Method for identifying oil spot smoke pollution source |
| CN115015410B (en) * | 2022-05-25 | 2024-04-19 | 河北中烟工业有限责任公司 | Method for auxiliary identification of oil spot smoke pollution source |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108133313B (en) | Artificial intelligent sensory evaluation food flavor system and construction method thereof | |
| US6936814B2 (en) | Median filter for liquid chromatography-mass spectrometry data | |
| CN107941978B (en) | Method for evaluating internal quality stability of bead blasting for cigarettes | |
| CN109781908B (en) | Method for analyzing odor substances in tobacco material | |
| CN110687240B (en) | Method for rapidly identifying production place of ham | |
| CN106353419B (en) | Method for measuring flavor components in cigarette mainstream smoke | |
| CN104122358A (en) | Method for measuring volatile fragrance components of electronic cigarette | |
| CN111707745A (en) | Method for evaluating cigarette perfuming uniformity | |
| CN112345654A (en) | Method for identifying oil stain smoke pollution source based on chromatographic fingerprint spectrum | |
| CN113138248B (en) | Characteristic spectrum extraction method and detection method for feed liquid preparation quality stability | |
| CN108645940A (en) | A kind of tobacco flavor ingredient extracting process | |
| CN111505174A (en) | Method for identifying true and false cigarettes | |
| CN112034084A (en) | Detection method of volatile components in blumea oil and application thereof | |
| WO2004040258A2 (en) | Method and apparatus for automated detection of peaks in spectroscopic data | |
| US20230400441A1 (en) | Identification method of volatile flavor compound in meat and use thereof | |
| CN112578069A (en) | Analysis method for simultaneously measuring 11 components in electronic smoke sol | |
| Teonata et al. | An Introduction to Different Types of Gas Chromatography | |
| CN112285263A (en) | Method for quantitatively analyzing non-volatile organic acid in tobacco essence and feed liquid | |
| CN115097021B (en) | Method for researching chemical composition difference of cigarette smoke based on gas chromatography-quadrupole electrostatic field orbit trap high-resolution mass spectrum | |
| CN115792022A (en) | Sensory effect-based model for flavor substances in tobacco and construction method and application thereof | |
| CN111679009B (en) | GC-MS/MS method for simultaneously detecting volatile and semi-volatile acids, alcohols and phenols in tobacco flavor and fragrance | |
| CN111272906B (en) | Method for determining flower fragrance components in main stream smoke of cigarette | |
| CN113607850A (en) | Method for analyzing and identifying wheat varieties by utilizing volatile organic compounds | |
| CN114441679B (en) | Method for detecting tobacco tar component of electronic cigarette | |
| CN109725098B (en) | Method for measuring rhynchophylline transfer rate and rhynchophylline retention rate of filter tip of smoke |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210209 |
|
| RJ01 | Rejection of invention patent application after publication |