CN112557528A - Identification method of smoking liquid - Google Patents

Identification method of smoking liquid Download PDF

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Publication number
CN112557528A
CN112557528A CN202011297006.1A CN202011297006A CN112557528A CN 112557528 A CN112557528 A CN 112557528A CN 202011297006 A CN202011297006 A CN 202011297006A CN 112557528 A CN112557528 A CN 112557528A
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Prior art keywords
sample
density
smoking
bottle
detected
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Chinese (zh)
Inventor
韩敏义
侯钰柯
何伟俊
叶俊杰
邓绍林
徐幸莲
周光宏
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Nanjing Agricultural University
Wens Foodstuff Group Co Ltd
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Nanjing Agricultural University
Wens Foodstuff Group Co Ltd
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    • 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
    • G01N30/04—Preparation or injection of sample to be analysed
    • G01N30/24—Automatic injection systems
    • 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
    • G01N30/62—Detectors specially adapted therefor
    • G01N30/72—Mass spectrometers
    • 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
    • G01N30/8686—Fingerprinting, e.g. without prior knowledge of the sample components
    • 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
    • G01N30/8696—Details of Software
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/02—Food
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N9/00—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity
    • G01N9/02—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity by measuring weight of a known volume
    • G01N9/04—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity by measuring weight of a known volume of fluids

Abstract

The invention relates to the technical field of food detection, in particular to an identification method of smoking liquid. The authentication method comprises the following steps: (1) preparing different smoking solution samples to be tested; (2) detecting a smoking fluid sample to be detected by using GC-IMS to obtain a GC-IMS fingerprint; (3) selecting a characteristic analysis area, and comparing the overall matching degree of the characteristic analysis area of the sample to be detected by using a Gallery plug-in to obtain a matching degree value; (4) testing the density and pH of a smoking solution sample to be tested; (5) and (4) introducing a signal peak in the fingerprint and the measured pH and density into R software, and performing comparative analysis by adopting a principal component analysis method. The method for identifying the liquid smoke is simple to operate and high in sensitivity, and indexes of the identification method comprise a fingerprint, the density and the pH value of a sample, so that the method has higher identification accuracy.

Description

Identification method of smoking liquid
Technical Field
The invention relates to the technical field of food detection, in particular to an identification method of smoking liquid.
Background
The smoking liquid is a liquid smoking spice which is processed by dry distillation and a special purification process by taking wood and the like as raw materials and can be added into food to be smoked by methods of adding, spraying, dipping and the like. The main components of the liquid smoke include compounds such as phenols, carbonyls, organic acids, alcohols and esters, and the interaction among the components changes the sensory characteristics of food, such as taste, texture, color and the like. At present, the brand and the variety of the smoking liquid in the market are complex and various, and the composition and the content of the components are different, so that the method for identifying the smoking liquid is provided, different smoking liquids are distinguished, and technicians can select proper smoking liquid from different food matrixes, thereby having important significance.
In the prior art, the method for analyzing the liquid smoke comprises an electronic nose and an electronic tongue technology, but the technology has larger identification errors. Related researchers also adopt a chromatographic detection method to identify the smoking liquid, but the method has long detection time and complex detection mode and is difficult to be widely applied.
Therefore, it is desirable to provide a method for identifying liquid smoke, which can accurately and rapidly identify the type of liquid smoke.
Disclosure of Invention
In view of the above, it is necessary to provide a method for identifying liquid smoke, which can accurately and rapidly identify the type of liquid smoke.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for identifying liquid smoke comprises the following steps:
(1) preparing different smoking solution samples to be tested;
(2) detecting a smoking fluid sample to be detected by using GC-IMS to obtain a GC-IMS fingerprint;
(3) selecting a characteristic analysis area, and comparing the overall matching degree of the characteristic analysis area of the sample to be detected by using a Gallery plug-in to obtain a matching degree value;
(4) testing the density and pH of a smoking solution sample to be tested;
(5) and (4) introducing a signal peak in the fingerprint and the measured pH and density into R software, and performing comparative analysis by adopting a principal component analysis method.
Further, in the method for identifying liquid smoke, the step (2) comprises the following specific steps:
s1: diluting the smoking solution sample to be tested by 105～109Doubling;
s2: taking 0.2-1 mL of diluted sample to be detected and putting the sample into a headspace bottle;
s3: and (3) putting the headspace bottle filled with the sample into an automatic sample applicator, incubating for 20-30 min at 45-80 ℃, and performing calibration through an injector of the automatic calibration applicator to obtain a calibration volume of 0.4-0.6 mL.
Further, in the above method for discriminating a liquid smoke, the pH of a sample to be measured is measured using a pH meter.
Further, in the above method for discriminating a liquid smoke, the method for measuring the density comprises:
1) weighing a density bottle with the mass of m 0;
2) filling the density bottle with a sample to be detected, sealing the cover, soaking in water bath at 20 ℃, wiping the density bottle dry and weighing the density bottle with the mass of m1 after the temperature in the bottle reaches 20 ℃;
3) filling the density bottle with distilled water, sealing the cover, soaking in a water bath at 20 ℃, wiping the density bottle dry and weighing the density bottle with the mass of m2 after the temperature in the bottle reaches 20 ℃;
4) and the density of the sample to be detected is (m1-m0)/(m2-m0) x 0.9982 g/mL.
Further, in the method for identifying liquid smoke, a preset matching degree threshold value is set according to the matching degree value, and the matching degree value is compared with the preset matching degree threshold value; if the matching degree value is larger than the preset matching degree threshold value, judging that the sample to be detected is smoking liquid; and if the matching degree value is smaller than the preset matching degree threshold value, judging that the sample to be detected is another smoking liquid.
The invention has the beneficial effects that: the invention overcomes the problems of larger error and complex detection of artificial sensory auxiliary identification in the prior art, and provides the smoking liquid identification method which has the advantages of no need of pretreatment of samples, simple operation, short detection time and high sensitivity of the detection method.
Drawings
FIG. 1 is a fingerprint of example 1;
FIG. 2 is a graph of the PCA analysis of example 1.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be further clearly and completely described below with reference to the embodiments of the present invention. It should be noted that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
The identification method of the liquid smoke comprises the following steps:
(1) preparing two different smoking solution samples to be detected; wherein sample A is from food products of Jinan Hualu, Inc., and sample B is from food flavor factory of Jinnishan in Alexant city of Jinan; 9 samples each;
(2) the GC-IMS is used for detecting two smoking liquid samples, and the detection method comprises the following steps:
s1: samples A and B were each diluted to 105～109Doubling;
s2: respectively taking 0.2-1 mL of diluted samples A and B to be detected, and putting the samples A and B into different headspace bottles;
s3: putting the headspace bottles filled with different samples into an automatic sample applicator, incubating for 20min at 45-80 ℃, and performing calibration through an injector of the automatic calibration applicator to obtain a calibration volume of 0.5 mL;
obtaining GC-IMS fingerprint spectrums of the samples A and B; the fingerprint is shown in figure 1;
(3) and selecting a characteristic analysis area, and performing overall matching degree comparison on the characteristic analysis area of the sample to be detected by using a Gallery plug-in to obtain a matching degree value, wherein the matching degree comparison of the two samples is shown in Table 1.
TABLE 1 comparison of the degree of matching of samples A and B
A1 A2 A3 A4 A5 A6 A7 A8 A9 B1 B2 B3 B4 B5 B6 B7 B8 B9
A1 100 91 92 89 89 87 90 84 89 48 50 45 42 51 49 51 49 43
A2 91 100 95 94 92 91 89 89 93 46 49 43 40 49 47 50 47 41
A3 92 95 100 93 95 93 92 90 94 48 51 45 42 51 49 52 49 43
A4 89 94 93 100 92 94 89 92 92 47 49 44 41 49 48 50 47 41
A5 89 92 95 92 100 93 93 92 92 52 55 49 46 55 53 56 53 47
A6 87 91 93 94 93 100 90 95 94 49 52 46 43 52 50 52 50 44
A7 90 89 92 89 93 90 100 88 91 54 57 51 47 57 55 58 55 49
A8 84 89 90 92 92 95 88 100 91 47 50 44 41 50 48 51 48 42
A9 89 93 94 92 92 94 91 91 100 48 51 45 42 51 49 51 49 43
B1 48 46 48 47 52 49 54 47 48 100 88 96 92 86 87 89 94 93
B2 50 49 51 49 55 52 57 50 51 88 100 89 85 95 95 94 88 87
B3 45 43 45 44 49 46 51 44 45 96 89 100 95 88 89 88 95 97
B4 42 40 42 41 46 43 47 41 42 92 85 95 100 85 87 86 90 96
B5 51 49 51 49 55 52 57 50 51 86 95 88 85 100 95 94 88 86
B6 49 47 49 48 53 50 55 48 49 87 95 89 87 95 100 96 88 88
B7 51 50 52 50 56 52 58 51 51 89 94 88 86 94 96 100 90 87
B8 49 47 49 47 53 50 55 48 49 94 88 95 90 88 88 90 100 93
B9 43 41 43 41 47 44 49 42 43 93 87 97 96 86 88 87 93 100
According to the matching degree values of the samples in the table 1, the matching degrees of the same sample are all over 80, the preset matching degree threshold value is set to be 80, and the samples belonging to the same type with the matching degrees over 80 are identified by the same type method. In order to further improve the accuracy of the detection, the density and pH indexes of the sample are tested.
(4) Testing the density and pH of the smoking fluid sample to be tested:
the pH of sample a and sample B measured using a pH meter is shown in table 2.
TABLE 2 pH of sample A and sample B
Group of pH
A 2.71±0.00b
B 2.93±0.01a
Note: the statistical analysis method in table 2 used one-way anova with a statistical significance level set at p < 0.01. Data are presented as mean ± sd of sample determinations, with significant differences (p <0.01) indicated by different letters in the same column.
Samples a and B were tested for density as follows:
1. weighing a density bottle with the mass of m 0;
2. filling a density bottle with a sample to be detected, sealing the cover, soaking in water bath at 20 ℃, wiping the density bottle dry and weighing the density bottle with the mass of m1 after the temperature in the bottle reaches 20 ℃;
3. filling the density bottle with distilled water, sealing the cover, soaking in water bath at 20 ℃, wiping the density bottle dry and weighing the density bottle with the mass of m2 after the temperature in the bottle reaches 20 ℃;
4. the density of the sample to be detected is (m1-m0)/(m2-m0) x 0.9982 g/mL;
the measurements for sample A and sample B are shown in Table 3.
TABLE 3 Density of samples A and B
Group of Density (. about.10)-4)
A 10100±0.29a
B 10100±0.91b
Note: the statistical analysis method in table 3 used one-way anova with a statistical significance level set at p < 0.01. Data are presented as mean ± sd of sample determinations, with significant differences indicated by different letters on the same column (p <0.01)
(5) The signal peaks in the GC-IMS fingerprints of the samples A and B, the measured pH and the measured density are introduced into R software, and the comparison analysis is carried out by adopting a principal component analysis method, as shown in figure 2.
As is clear from FIG. 1, the known substances having a larger smoke solution B than those of group A include cyclohexanone, 2, 3-dimethylglyoxime, 2, 3-pentanedione, n-propanol (1-propanol), 2, 3-pentanedione, pinene, heptanol, 2-ethyl-1-hexanol, 2, 5-dimethylpyrazine, 2-pentanone, and ethyl propionate. As can be seen from FIG. 2, principal component 1 explains the 86.9% variation of the original data set, principal component 2 explains the 4.8% variation of the original data set, and the total variation of the original data set explained by the first two principal components is more than 91.7%, which shows that the relative contents of the volatile flavor substances of the two smoking solutions have strong correlation, and the data analysis by using the first two principal components can generally reflect the variation of the data in the original data set. Therefore, the method for identifying the smoking liquid can effectively distinguish different types of smoking liquid.
Accuracy verification
Taking 4 parts of smoking fluid samples with the sample numbers of 1, 2,3 and 4, wherein the sample sampling personnel know the types of the smoking fluid samples corresponding to the sample numbers of 1, 2,3 and 4 and give the samples to a tester for testing, and the tester detects the samples according to the identification method. The results of the detection accuracy are shown in table 4.
TABLE 4 confusion matrix for test samples
Figure BDA0002785703440000061
As can be seen from Table 4, the accuracy of the smoke identification method provided by the present application is 100%.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (5)

1. The identification method of the liquid smoke is characterized by comprising the following steps:
(1) preparing different smoking solution samples to be tested;
(2) detecting a smoking fluid sample to be detected by using GC-IMS to obtain a GC-IMS fingerprint;
(3) selecting a characteristic analysis area, and comparing the overall matching degree of the characteristic analysis area of the sample to be detected by using a Gallery plug-in to obtain a matching degree value;
(4) testing the density and pH of a smoking solution sample to be tested;
(5) and (4) introducing a signal peak in the fingerprint and the measured pH and density into R software, and performing comparative analysis by adopting a principal component analysis method.
2. The method for identifying liquid smoke of claim 1, wherein the step (2) comprises the following steps:
s1: diluting the smoking solution sample to be tested by 105～109Doubling;
s2: taking 0.2-1 mL of diluted sample to be detected and putting the sample into a headspace bottle;
s3: and (3) putting the headspace bottle filled with the sample into an automatic sample applicator, incubating for 20-30 min at 45-80 ℃, and performing calibration through an injector of the automatic calibration applicator to obtain a calibration volume of 0.4-0.6 mL.
3. The method for identifying liquid smoke according to claim 1, wherein the pH of the sample to be tested is measured using a pH meter.
4. The method of claim 1, wherein the density is determined by:
1) weighing a density bottle with the mass of m 0;
2) filling the density bottle with a sample to be detected, sealing the cover, soaking in water bath at 20 ℃, wiping the density bottle dry and weighing the density bottle with the mass of m1 after the temperature in the bottle reaches 20 ℃;
3) filling the density bottle with distilled water, sealing the cover, soaking in a water bath at 20 ℃, wiping the density bottle dry and weighing the density bottle with the mass of m2 after the temperature in the bottle reaches 20 ℃;
4) and the density of the sample to be detected is (m1-m0)/(m2-m0) x 0.9982 g/mL.
5. The method of claim 1, wherein a predetermined threshold value of the degree of matching is set based on the degree of matching, and the degree of matching is compared to the predetermined threshold value of the degree of matching; if the matching degree value is larger than the preset matching degree threshold value, judging that the sample to be detected is smoking liquid; and if the matching degree value is smaller than the preset matching degree threshold value, judging that the sample to be detected is another smoking liquid.
CN202011297006.1A 2020-11-18 2020-11-18 Identification method of smoking liquid Pending CN112557528A (en)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102645502A (en) * 2012-04-23 2012-08-22 上海应用技术学院 Method for detecting age of yellow rice wine by using high-speed gas chromatography type electronic nose fingerprint analysis system
CN107245376A (en) * 2017-07-12 2017-10-13 广州城市职业学院 Wooden sootiness spices of a kind of lichee and preparation method thereof
CN107624860A (en) * 2017-10-13 2018-01-26 江苏省中国科学院植物研究所 It is a kind of to prepare the application of the method and smoke solution of smoke solution in bacon is prepared using walnut shell

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102645502A (en) * 2012-04-23 2012-08-22 上海应用技术学院 Method for detecting age of yellow rice wine by using high-speed gas chromatography type electronic nose fingerprint analysis system
CN107245376A (en) * 2017-07-12 2017-10-13 广州城市职业学院 Wooden sootiness spices of a kind of lichee and preparation method thereof
CN107624860A (en) * 2017-10-13 2018-01-26 江苏省中国科学院植物研究所 It is a kind of to prepare the application of the method and smoke solution of smoke solution in bacon is prepared using walnut shell

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
NATALIE GERHARDT 等: "Volatile-Compound Fingerprinting by Headspace-Gas-Chromatography Ion-Mobility Spectrometry (HS-GC-IMS) as a Benchtop Alternative to 1H NMR Profiling for Assessment of the Authenticity of Honey", 《ANALYTICAL CHEMISTRY》 *
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