CN111044638A - Method for classifying and identifying different varieties of flue-cured tobacco leaves - Google Patents
Method for classifying and identifying different varieties of flue-cured tobacco leaves Download PDFInfo
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Abstract
The invention discloses a method for classifying and identifying different varieties of flue-cured tobacco leaves, which mainly comprises the following steps: and (3) performing headspace analysis and gas chromatography-ion mobility spectrometry on the flue-cured tobacco leaf sample to be detected to obtain a three-dimensional spectrogram, comparing characteristic analysis areas in the three-dimensional spectrogram, and identifying the type of the flue-cured tobacco leaf. The method uses a headspace-gas chromatography-ion mobility spectrometry combined technology for rapid classification and identification of different varieties of flue-cured tobacco leaves, has the advantages of high resolution and sensitivity, short analysis time, no damage, no sample pretreatment, environmental friendliness, less consumable materials used in experiments, low detection cost, intuitive result and suitability for batch classification and identification of tobacco leaf samples, and can obtain signal peaks enough for distinguishing different varieties of tobacco leaves by adopting lower incubation temperature and longer incubation time, effectively reduce background interference by adopting lower temperature and reduce pollution to instruments.
Description
Technical Field
The invention relates to the field of rapid analysis and detection, in particular to a method for classifying and identifying different varieties of flue-cured tobacco leaves.
Background
When the quality of the tobacco leaves is inspected, the essential differences among different types of tobacco leaves such as flue-cured tobacco, burley tobacco, aromatic tobacco and the like can be clarified only by gradually distinguishing the tobacco leaves according to the principle of classification, grouping and grading, so that reasonable grouping and grading are realized. If the tobacco leaves are not classified, the tobacco leaves in the same type can have different types of tobacco leaves, so that the difficulty of identifying the quality of the tobacco leaves is easily caused, and the quality of the tobacco leaves cannot be correctly distinguished. Therefore, classification plays a decisive role in the classification of tobacco leaves.
Ion Mobility Spectrometry (IMS) is a trace chemical species analysis and detection technique, which is an analysis technique for characterizing chemical ion species based on the difference in the migration velocity of different gas phase ions in a gas phase in an electric field. The IMS has high detection sensitivity and high response speed, has outstanding advantages in trace detection of volatile organic compounds, is suitable for field rapid detection or analysis, and has detection time of millisecond level. However, the IMS only separates the compounds by the drift tube, the separation effect is poor, and the method cannot effectively classify and identify the flue-cured tobacco leaves of different varieties.
Disclosure of Invention
The invention aims to solve the problem that flue-cured tobacco leaves of different varieties cannot be effectively classified and identified in the prior art.
In order to solve the technical problem, the embodiment of the invention discloses a method for classifying and identifying different varieties of flue-cured tobacco leaves, which comprises the following steps:
step S1, adopting a headspace mode to sample, respectively carrying out headspace analysis treatment on the cured tobacco leaves to be detected, and obtaining volatile compounds and semi-volatile compounds volatilized from the cured tobacco leaves to be detected, wherein headspace analysis conditions are set as follows: incubation temperature is 60 ℃, incubation time is 8min, sample injection volume is 200 mu l, and sample injection needle temperature is 80 ℃;
step S2, analyzing the flue-cured tobacco leaves to be detected after headspace analysis processing by using gas chromatography-ion mobility spectrometry to obtain a three-dimensional spectrogram corresponding to the flue-cured tobacco leaves to be detected, wherein the analysis conditions of the gas chromatography-ion mobility spectrometry are set as follows: the chromatographic column is a multi-capillary separation column, the stationary phase is OV-5, the temperature of the chromatographic column is 34 ℃, the temperature of an injection port is 80 ℃, the carrier gas is high-purity nitrogen, the flow rate of the carrier gas adopts a programmed gas rising mode, the initial flow rate is 8ml/min, after 3min of retention, the carrier gas rises to 150ml/min at 8min, 150ml/min is kept for 10min, and the flow rate is reduced to 8ml/min at 10.5 min; the flow rate of a mobility spectrum drift gas is 150ml/min, and the temperature of a mobility spectrum drift tube is 45 ℃;
and step S3, analyzing the three-dimensional spectrogram to obtain a characteristic analysis area, and classifying and identifying the to-be-detected flue-cured tobacco leaves.
By adopting the technical scheme, the acquired three-dimensional spectrogram of the analysis sample is more reliable and qualitative analysis can be more accurately realized by optimally setting the headspace analysis conditions and the gas chromatography-ion mobility spectrometry analysis conditions so as to accurately and rapidly classify different varieties of to-be-detected flue-cured tobacco leaves. In addition, the analysis method does not need sample pretreatment, is environment-friendly, short in detection time, high in sensitivity and good in reproducibility, the separation time of the rapid gas chromatography equipped with the multi-capillary chromatographic column is greatly shortened compared with that of the conventional chromatography, the requirement of on-site rapid analysis can be met, the scheme adopts lower incubation temperature and longer incubation time, signal peaks which can sufficiently distinguish different varieties of tobacco leaves can be obtained, background interference can be effectively reduced at lower temperature, pollution to instruments is reduced, and the flow of drift gas is only selected to be 150ml/min because the incubation temperature adopted by the scheme is lower and volatilized compounds are relatively few.
Optionally, step S3 specifically includes:
step S31, carrying out optimization analysis on the three-dimensional spectrogram to obtain characteristic analysis areas of the volatile compounds and the semi-volatile compounds, wherein the characteristic analysis areas can represent varieties of the cured tobacco leaves to be detected;
step S32, generating a view library which takes the characteristic analysis area as a horizontal axis and the sample number of the cured tobacco leaf to be detected as a vertical axis by using a Gallery plug-in;
and step S33, classifying and identifying the to-be-detected flue-cured tobacco leaves by comparing the characteristic analysis areas.
Optionally, classifying and identifying the to-be-detected flue-cured tobacco leaves specifically comprises:
setting a matching degree threshold value;
analyzing the result of the characteristic analysis area of the three-dimensional spectrogram of the flue-cured tobacco leaves to be detected to obtain the overall matching degree of the characteristic analysis areas among all the flue-cured tobacco leaves to be detected;
and comparing the overall matching degree value with a matching degree threshold value, and identifying the variety of the flue-cured tobacco leaves to be detected.
Optionally, identifying the variety of the flue-cured tobacco leaf to be tested specifically comprises:
if the integral matching degree value is greater than or equal to the matching degree threshold value, the flue-cured tobacco leaves to be detected are of the same variety;
and if the overall matching degree value is smaller than the matching degree threshold value, the flue-cured tobacco leaves to be detected are of different varieties.
Optionally, comparing the overall match value to the match threshold is performed using a chemometric evaluation method.
Optionally, the chemometric evaluation method is principal component analysis and/or orthogonal partial least squares-discriminant analysis.
Optionally, the classification and identification of the flue-cured tobacco leaves to be detected specifically comprises:
identifying the tobacco variety by comparing the peak appearance condition of the characteristic analysis area; wherein,
if the peak appearance conditions of the characteristic analysis areas of the flue-cured tobacco leaves to be detected are obviously different, the flue-cured tobacco leaves to be detected are of different varieties;
otherwise, the flue-cured tobacco leaves to be detected are of the same variety.
Alternatively, headspace analysis was performed using a gas chromatography-ion mobility spectrometry apparatus of type FlavourSpec.
Optionally, the information in the three-dimensional spectra comprises drift time, chromatographic retention time and particle response signal intensity.
Compare the beneficial effect in prior art:
according to the method for classifying and identifying the different varieties of flue-cured tobacco leaves, the headspace analysis conditions and the gas chromatography-ion mobility spectrometry analysis conditions are set in an optimized mode, so that the obtained three-dimensional spectrogram of the analysis sample is more reliable, qualitative analysis can be achieved more accurately, and the different varieties of flue-cured tobacco leaves to be detected can be classified accurately and rapidly. In addition, the analysis method does not need sample pretreatment, is environment-friendly, has short detection time, high sensitivity and good reproducibility, and the rapid gas chromatography separation time equipped with the multi-capillary chromatographic column is greatly shortened compared with the conventional chromatography, so that the requirements of on-site rapid analysis can be met.
Drawings
FIG. 1 is a flowchart of a method for classifying and identifying different varieties of flue-cured tobacco leaves according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a gas chromatography-ion mobility spectrometry (GC-IMS) structure;
FIG. 3 is a GC-IMS three-dimensional spectrogram of A, B, C tobacco leaves of three varieties;
FIG. 4 is a library of views of selected analysis areas for 6 batches of A tobacco leaves, 4 batches of B tobacco leaves, and 12 batches of C tobacco leaves;
FIG. 5 is a 1 st and 2 nd principal component score chart of OPLS-DA model of characteristic analysis region of D, E tobacco leaf sample.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure. While the invention will be described in conjunction with the preferred embodiments, it is not intended that features of the invention be limited to these embodiments. On the contrary, the invention is described in connection with the embodiments for the purpose of covering alternatives or modifications that may be extended based on the claims of the present invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be practiced without these particulars. Moreover, some of the specific details have been left out of the description in order to avoid obscuring or obscuring the focus of the present invention. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
It should be noted that in this specification, like reference numerals and letters refer to like items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The tobacco leaf aroma component is one of the main contents of the tobacco leaf internal quality, the volatile and semi-volatile components in the tobacco leaf are closely related to the aroma quality, and the tobacco leaf aroma quality is mainly influenced by genetic factors and environmental factors. Under the condition that environmental factors are the same or similar, the genetic factors determine the types, the contents and the composition proportion of the tobacco leaf aroma components. Different varieties of flue-cured tobacco leaves have unique aroma and volatile components, i.e. the chemical composition of one variety of tobacco leaves is different from that of another, which form their respective fingerprint characteristics and variety characteristics.
Fig. 1 is a flowchart of a method for classifying and identifying different varieties of flue-cured tobacco leaves according to an embodiment of the present invention.
The embodiment of the invention provides a method for classifying and identifying different varieties of flue-cured tobacco leaves, which comprises the following steps:
step S1, adopting a headspace method for sample injection, respectively carrying out headspace analysis treatment on each flue-cured tobacco leaf sample, and obtaining volatile compounds and semi-volatile compounds volatilized from the flue-cured tobacco leaf sample, wherein the headspace analysis conditions are set as follows: incubation temperature is 60 ℃, incubation time is 8min, sample injection volume is 200 mu l, and sample injection needle temperature is 80 ℃;
step S2, analyzing the flue-cured tobacco leaf sample subjected to headspace analysis by using gas chromatography-ion mobility spectrometry to obtain a three-dimensional spectrogram corresponding to the flue-cured tobacco leaf sample, wherein the analysis conditions of the gas chromatography-ion mobility spectrometry are set as follows: the chromatographic column is a multi-capillary separation column, the stationary phase is OV-5, the temperature of the chromatographic column is 34 ℃, the temperature of an injection port is 80 ℃, the carrier gas is high-purity nitrogen, the flow rate of the carrier gas adopts a programmed gas rising mode, the initial flow rate is 8ml/min, after 3min of retention, the carrier gas rises to 150ml/min at 8min, 150ml/min is kept for 10min, and the flow rate is reduced to 8ml/min at 10.5 min; the flow rate of a mobility spectrum drift gas is 150ml/min, and the temperature of a mobility spectrum drift tube is 45 ℃;
and step S3, analyzing the three-dimensional spectrogram to obtain a characteristic analysis area, and classifying and identifying the to-be-detected flue-cured tobacco leaves.
According to the technical scheme, the analysis conditions of the flue-cured tobacco leaves are optimized particularly, the incubation temperature is set to be 60 ℃, the incubation time is 8min, the chromatographic column temperature is 34 ℃, volatile and semi-volatile compounds which distinguish varieties are volatilized from different varieties of tobacco leaves, the number of chemical combination peaks on a three-dimensional spectrogram is increased, the initial flow is set to be 8ml/min, after 3min is reserved, the flow is increased to 150ml/min when 8min is carried out, 150ml/min is kept for 10min all the time, and the flow is reduced to 8ml/min when 10.5min is carried out. In addition, in this embodiment, a GC-IMS (gas chromatography-ion mobility spectrometry) device with a FlavourSpec model can be selected for the headspace analysis.
Wherein, step S3 specifically includes:
step S31, carrying out optimization analysis on the three-dimensional spectrogram to obtain characteristic analysis areas of the volatile compounds and the semi-volatile compounds, wherein the characteristic analysis areas can represent varieties of flue-cured tobacco leaves;
step S32, generating a view library which takes the characteristic analysis area as a horizontal axis and the sample number of the flue-cured tobacco leaf sample as a vertical axis by using a Gallery plug-in;
and step S33, classifying and identifying the to-be-detected flue-cured tobacco leaves by comparing the characteristic analysis areas.
Wherein, the information in the three-dimensional spectrogram comprises drift time, chromatographic retention time and particle response signal intensity.
Further, classifying and identifying the to-be-detected flue-cured tobacco leaves specifically comprises:
setting a matching degree threshold value;
analyzing the result of the characteristic analysis area of the three-dimensional spectrogram of the flue-cured tobacco leaves to be detected to obtain the overall matching degree of the characteristic analysis areas among all the flue-cured tobacco leaves to be detected;
and comparing the overall matching degree value with a matching degree threshold value, and identifying the variety of the flue-cured tobacco leaves to be detected.
Further, obtaining the variety of the flue-cured tobacco leaf to be tested specifically comprises:
if the integral matching degree value is greater than or equal to the matching degree threshold value, the flue-cured tobacco leaves to be detected are of the same variety;
and if the overall matching degree value is smaller than the matching degree threshold value, the flue-cured tobacco leaves to be detected are of different varieties.
Further, in step S5, the overall matching degree value is compared with the matching degree threshold value by the chemometric evaluation method.
The chemometric evaluation method is a principal component analysis method and/or an orthogonal partial least squares-discriminant analysis method.
That is, the characteristic information area of each variety of tobacco leaves is selected from the acquired three-dimensional spectrogram, and a characteristic analysis area capable of representing the volatility and semi-volatility components of the variety of tobacco leaves is formed through optimization. And comparing the characteristic analysis areas of the flue-cured tobacco leaf samples of different varieties, generating a view library by using a Gallery plug-in module carried by software, wherein the characteristic analysis areas are used as a transverse axis, the sample numbers of the flue-cured tobacco leaf samples are used as a longitudinal axis, and rapidly identifying the tobacco leaves of different varieties by observing the peak appearance condition of the selected analysis areas. Furthermore, the whole matching degree comparison can be carried out on the tobacco leaf analysis area through the Gallery plug-in, and different varieties of tobacco leaves can be identified by setting a matching degree threshold value. Furthermore, chemometric evaluation such as principal component analysis, orthogonal partial least square-discriminant analysis and the like can be carried out on the selected analysis area of the tobacco leaves to carry out rapid classification and identification on the tobacco leaf samples of different varieties of flue-cured tobaccos.
In other embodiments of the present invention, the classification and identification of the flue-cured tobacco leaves to be tested specifically comprises:
identifying the tobacco variety by comparing the peak appearance condition of the characteristic analysis area; wherein,
if the peak appearance conditions of the characteristic analysis areas of the flue-cured tobacco leaves to be detected are obviously different, the flue-cured tobacco leaves to be detected are of different varieties;
otherwise, the flue-cured tobacco leaves to be detected are of the same variety.
Further, headspace analysis was performed using a gas chromatography-ion mobility spectrometry apparatus of the type FlavourSpec. And the information in the three-dimensional spectrogram comprises drift time, chromatographic retention time and particle response signal intensity.
To better aid understanding, the above method is illustrated below by way of example.
The structure schematic diagram of the headspace gas chromatography-ion mobility spectrometry (GC-IMS) is shown in FIG. 2;
in the figure, Drift gas is Drift gas, Carrier gas is Carrier gas, T1 is mobility spectrometry Drift tube temperature, T2 is chromatographic column temperature, T3 is injection port temperature, IMS is ion mobility spectrometry, EPC1 is mobility spectrometry Drift gas flow, EPC2 is Carrier gas flow, and sample is flue-cured tobacco leaf sample.
The first embodiment is as follows:
1) preparation of tobacco leaf samples
Weighing 1 g of flue-cured tobacco leaf samples of different varieties to be analyzed, filling the samples into 20ml of headspace bottles, preparing 3 bottles of samples as parallel samples for one sample, and sealing the samples by a gland to be detected.
2) Analyzing tobacco leaf samples by adopting headspace-gas chromatography-ion mobility spectrometry
The analysis conditions were as follows:
headspace conditions: incubation temperature: 60 ℃; incubation time: 8 min; sample introduction volume: 200 mul; the temperature of a sample injection needle is 80 ℃;
gas chromatography-ion mobility spectrometry conditions: the chromatographic column is a multi-capillary separation column (MCC) and is a stationary phase OV-5, and the temperature of the chromatographic column is 34 ℃; the sample inlet temperature is 80 ℃; the carrier gas is high-purity nitrogen; carrier gas flow: and (3) adopting a programmed air-lift mode, keeping the initial flow rate at 8ml/min for 3min, then lifting to 150ml/min at 8min, keeping the flow rate at 150ml/min for 10min, and reducing the flow rate to 8ml/min at 10.5 min. The mobility spectrum drift gas flow rate is 150 ml/min; the mobility spectrum drift tube temperature was 45 ℃.
3) Sample analysis and spectrogram evaluation
And analyzing volatile and semi-volatile components of A, B, C tobacco leaf samples under the conditions to obtain a headspace-gas chromatography-ion mobility spectrometry three-dimensional spectrogram. Selecting a spectrogram marker of the analyzed tobacco leaves, namely a characteristic analysis area of the tobacco leaf sample, generating a view library by using a Gallery plug-in of software through the selected analysis area, and comparing the peak conditions of the analysis area to achieve the purpose of quickly classifying the different varieties of flue-cured tobacco leaves.
FIG. 3 is a GC-IMS three-dimensional spectrogram of A, B, C tobacco leaves of three varieties. Most of the peaks were concentrated in the first 4min and all peaks were essentially completed within 6 min.
Selecting 12 characteristic peaks capable of distinguishing flue-cured tobacco leaves of different varieties from three-dimensional spectrograms of the three varieties of tobacco leaves, generating a visual library map through a Gallery plug-in of instrument data processing software, and calculating the overall matching degree of all samples in a selected analysis area. Fig. 4 shows a view library of selected analysis areas of 6 batches of tobacco leaves a, 4 batches of tobacco leaves B and 12 batches of tobacco leaves C, wherein flue-cured tobacco leaves of different varieties have strong responses in different analysis areas, ion mobility spectrum peaks of tobacco leaves of the same variety are similar, differences between peak shapes and peak intensities are not large, and the peak shapes and the peak intensities of the varieties are obviously different. The whole matching degree of the analysis area between the same variety of tobacco leaves in batches is more than 85%, and the matching degree of the analysis area between different brands is less than 65%. The method is used for classifying and predicting the A, B, C three-variety tobacco blind samples, and the accuracy rate reaches 100%.
Example two:
1) preparation of tobacco leaf samples
Collecting tobacco leaf samples of D, E kinds of flue-cured tobacco leaves in different batches in nearly three years, filling the tobacco leaf samples into 20ml headspace bottles, preparing 3 bottles of samples as parallel samples, and sealing the samples by a gland to be tested.
2) Analyzing tobacco leaf samples by adopting headspace-gas chromatography-ion mobility spectrometry
The analysis conditions of the headspace-gas chromatography-ion mobility spectrometry in this embodiment are the same as those in the first embodiment, and therefore, the detailed description thereof is omitted here.
3) Sample analysis and spectrogram evaluation
Selecting 14 characteristic analysis areas of a gas chromatography-ion mobility spectrometry three-dimensional spectrogram of D, E tobacco leaf samples, and performing data analysis on the areas by adopting statistical analysis software. Collecting 58 batches of D tobacco leaves, collecting 43 batches of E tobacco leaves, respectively analyzing main components of the D tobacco leaves and the E tobacco leaves, checking whether abnormal points exist in a sample, and rejecting the abnormal points after finding reasons if the abnormal points exist; and then carrying out orthogonal partial least squares-discriminant method (OPLS-DA) analysis on the D and E samples, wherein each analysis area is independent variable X, the classification variable is Y, establishing a classification model of the tobacco gas chromatography-ion mobility spectrometry characteristic analysis area, and carrying out internal and external verification on the model to be used for classifying and predicting the samples. The method comprises the steps of establishing a classification model by using feature analysis regions of 70D and E tobacco leaf samples as a training set through an OPLS-DA method, enabling the cumulative interpretation capability [ R2X (CUM) ] of the extracted 3 main components to an original data matrix to reach 86.1%, obtaining the total interpretation variance [ R2(CUM) ] of classification variables through cross validation to be 98.8%, enabling the prediction capability [ Q2(CUM) ] of the model to reach 98.5%, and enabling the difference value between R2(CUM) and Q2(CUM) to be far smaller than 0.3, so that the model is an excellent classification prediction model. The OPLS-DA model score map in FIG. 5 can visually show the classification effect of the model, and the separation degree of two groups of samples in the map is large, which shows that the classification effect of the model is good. And (3) taking the characteristic analysis areas of 29D, E tobacco leaf samples as a verification set to carry out external verification on the OPLS-DA classification model, judging the prediction result according to a judgment rule, and finding that the 29 samples are correctly judged. The method is suitable for rapid classification and identification of tobacco leaves in large batches.
The method can be used for quickly and accurately classifying different varieties of flue-cured tobacco leaves, accurately and quickly classifying and identifying finished tobacco leaves of different brands by directly collecting headspace-gas chromatography-ion mobility spectrograms of tobacco leaf samples to be classified, comparing characteristic analysis areas of the tobacco leaf samples through software, generating a visual library map by using data processing software Gallery carried by an instrument, or comparing the overall matching degree of the analysis areas, or carrying out chemometric analysis on the characteristic analysis areas through statistical software, such as principal component analysis, orthogonal partial least square method-discriminant analysis and the like. The method uses the headspace-gas chromatography-ion mobility spectrometry combined technology for rapid classification and identification of different varieties of flue-cured tobacco leaves, has the advantages of high resolution and sensitivity, short analysis time, no damage, no sample pretreatment, environmental friendliness, less consumable materials used in experiments, low detection cost, visual results and suitability for batch classification and identification of tobacco leaf samples.
While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those skilled in the art that the foregoing is a more detailed description of the invention, taken in conjunction with the specific embodiments thereof, and that no limitation of the invention is intended thereby. Various changes in form and detail, including simple deductions or substitutions, may be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (9)
1. A method for classifying and identifying different varieties of flue-cured tobacco leaves is characterized by comprising the following steps:
step S1, adopting a headspace mode to sample, respectively carrying out headspace analysis treatment on the cured tobacco leaves to be detected, and obtaining volatile compounds and semi-volatile compounds volatilized from the cured tobacco leaves, wherein the headspace analysis conditions are set as follows: incubation temperature is 60 ℃, incubation time is 8min, sample injection volume is 200 mu l, and sample injection needle temperature is 80 ℃;
step S2, analyzing the flue-cured tobacco leaves to be detected after the headspace analysis processing by using a gas chromatography-ion mobility spectrometry to obtain a three-dimensional spectrogram corresponding to the flue-cured tobacco leaves to be detected, wherein the analysis conditions of the gas chromatography-ion mobility spectrometry are set as follows: the chromatographic column is a multi-capillary separation column, the stationary phase is OV-5, the temperature of the chromatographic column is 34 ℃, the temperature of an injection port is 80 ℃, the carrier gas is high-purity nitrogen, the flow rate of the carrier gas adopts a programmed gas rising mode, the initial flow rate is 8ml/min, the flow rate is increased after 3min is reserved, the flow rate is increased to 150ml/min when 8min is carried out, the flow rate is maintained for 10min all the time at 150ml/min, and the flow rate is reduced to 8ml/min when 10.5min is carried out; the flow rate of a mobility spectrum drift gas is 150ml/min, and the temperature of a mobility spectrum drift tube is 45 ℃;
and step S3, analyzing the three-dimensional spectrogram to obtain a characteristic analysis area, and classifying and identifying the to-be-detected flue-cured tobacco leaves.
2. The method according to claim 1, wherein the step S3 specifically includes:
step S31, carrying out optimization analysis on the three-dimensional spectrogram to obtain the characteristic analysis areas of the volatile compounds and the semi-volatile compounds, wherein the characteristic analysis areas can represent the varieties of the flue-cured tobacco leaves;
step S32, generating a view library which takes the characteristic analysis area as a horizontal axis and the sample number of the cured tobacco leaf to be detected as a vertical axis by using a Gallery plug-in;
and step S33, classifying and identifying the to-be-detected flue-cured tobacco leaves by comparing the characteristic analysis areas.
3. The method of claim 2, wherein the classifying and identifying the flue-cured tobacco leaves to be tested specifically comprises:
setting a matching degree threshold value;
analyzing the result of the characteristic analysis area of the three-dimensional spectrogram of the flue-cured tobacco leaves to be detected to obtain the overall matching degree value of the characteristic analysis area among all the flue-cured tobacco leaves to be detected;
and comparing the overall matching degree value with the matching degree threshold value, and identifying the variety of the flue-cured tobacco leaves to be detected.
4. The method of claim 3, wherein the identifying the variety of the cured tobacco leaf to be tested specifically comprises:
if the integral matching degree value is greater than or equal to the matching degree threshold value, the flue-cured tobacco leaves to be detected are of the same variety;
and if the overall matching degree value is smaller than the matching degree threshold value, the flue-cured tobacco leaves to be detected are of different varieties.
5. The method of claim 3, wherein said comparing said overall match value to said match threshold value is performed using a chemometric evaluation method.
6. The method of claim 5, wherein the chemometric evaluation method is principal component analysis and/or orthogonal partial least squares discriminant analysis.
7. The method of claim 2, wherein the classification and identification of the flue-cured tobacco leaves to be tested is specifically:
identifying the tobacco variety by comparing the peak appearance condition of the characteristic analysis area; wherein,
if the peak appearance conditions of the characteristic analysis areas of the flue-cured tobacco leaves to be detected are obviously different, the flue-cured tobacco leaves to be detected are of different varieties;
otherwise, the flue-cured tobacco leaves to be detected are of the same variety.
8. The method according to claim 1, wherein the headspace analysis process is performed using a gas chromatography-ion mobility spectrometry apparatus of the type FlavourSpec.
9. The method of claim 1, wherein the information in the three-dimensional spectrum includes drift time, chromatographic retention time, and ion response signal intensity.
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