A multi-dimensional real-time monitoring system and method for the fermentation process of tobacco leaves

Abstract

The present invention relates to the field of tobacco fermentation technology, in particular to a multi-dimensional real-time monitoring system and method for the fermentation process of core tobacco leaves, wherein the monitoring method comprises: collecting core tobacco leaves before, during and after agricultural fermentation samples, using electronic nose, GC-IMS, LC-MS / MS to quickly detect volatile aroma components and related metabolite components of the core tobacco leaves; according to the characteristics of volatile aroma components and metabolite components in different periods of agricultural fermentation, differentiating the core tobacco leaves at different fermentation times and screening the differential markers of the core tobacco leaves at different fermentation stages. The present invention monitors the agricultural fermentation process of core tobacco leaves in real time by electronic nose smelling of volatile aroma components and image features of rapid detection, and further screens differential compounds by Lasso regression, and the obtained differential markers are reliable, which can provide reference for the research of core tobacco leaf fermentation mechanism, quality control and preparation of intelligent monitoring equipment for real-time monitoring of the agricultural fermentation process of core tobacco leaves.

Description

Technical Field

[0001] The present invention relates to the technical field of tobacco leaf fermentation, and specifically relates to a multi-dimensional real-time monitoring method for a fermentation process of cigar core tobacco leaves. Background Art

[0002] During the agricultural fermentation of cigar core tobacco leaves, although the content of most volatile aroma components is observed to increase, these volatile aroma components generated during the fermentation process are usually thermally unstable, highly active and low in content, which increases the difficulty of accurately evaluating the agricultural fermentation process of cigar core tobacco leaves. At present, the detection of volatile aroma components in cigar tobacco mainly adopts single technical detection methods such as gas chromatography-mass spectrometry (GC-MS), gas chromatography-olfaction detection (GC-O) and electronic nose technology. Although GC-MS and GC-O can provide more reliable qualitative and quantitative information and detect more volatile aroma components, these technologies cannot realize real-time monitoring of the fermentation process, and have disadvantages such as long sample pretreatment cycle and slow analysis speed.

[0003] Electronic nose technology uses a series of selective electrochemical sensors and appropriate recognition algorithms to convert chemical signals into electrical signals. It is suitable for the identification of complex volatile aroma components, including quality inspection of food, tobacco and flavors and fragrances, medical diagnosis and explosives detection. This technology can realize real-time monitoring of the fermentation process, but the electronic nose cannot accurately quantify the changes in various specific volatile chemical components and is greatly affected by the ambient temperature and humidity. GC-IMS technology has high sensitivity and high resolution, can quickly and accurately detect trace amounts of volatile organic compounds, and can monitor the fermentation process in real time. In addition, GC-IMS can perform multiple sampling and detection without affecting the fermentation process, maintaining the integrity and natural fermentation state of the sample. At the same time, its test results are intuitively presented in the form of fingerprint imaging, which is convenient for direct observation.

[0004] Key metabolites such as amino acids and organic acids are important precursors for the formation of volatile aroma components during the fermentation of cigar core tobacco leaves, and are also key factors affecting the quality of tobacco leaf fermentation. Although there are many detection methods for markers of the fermentation process of cigar core tobacco leaves, there is no method that can achieve real-time monitoring of samples, visualize the image change characteristics of volatile compounds, and achieve satisfactory detection results. Moreover, due to the wide variety of metabolites, how to screen characteristic markers and achieve targeted monitoring is a gap in current research.

[0005] Therefore, how to develop a technology that can realize rapid sample detection with good signal response, high sensitivity, fast detection speed and good repeatability, and combine it with chemometric analysis to target monitoring of characteristic markers to achieve rapid and accurate identification of the agricultural fermentation process of citrus tobacco leaves is one of the problems that urgently need to be solved in this field. Summary of the invention

[0006] The purpose of the present invention is to provide a multi-dimensional real-time monitoring system and method for the fermentation process of cigar core tobacco leaves, which can monitor and analyze the volatile aroma and metabolic components of cigar tobacco leaves at different stages of agricultural fermentation in real time, and perform chemometric analysis based on the volatile aroma and metabolic component data to achieve rapid targeted monitoring of differential markers of different processes of agricultural fermentation of cigar core tobacco leaves.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A multi-dimensional real-time monitoring method for the fermentation process of cigar core tobacco leaves: samples of cigar core tobacco leaves are collected on the 0-10th day (early fermentation), 11-31st day (middle fermentation), and 32-45th day (late fermentation) of agricultural fermentation, and volatile aroma components and related metabolite components of the cigar core tobacco leaves are quickly detected by electronic nose (E-Nose), gas chromatography-ion mobility spectrometry (GC-IMS), full-automatic amino acid analyzer and liquid chromatography-mass spectrometry (LC-MS / MS); according to the characteristics of volatile aroma components and metabolites in different periods of agricultural fermentation, chemometric analysis is combined to distinguish cigar core tobacco leaves at different fermentation times and screen differential markers of cigar core tobacco leaves at different fermentation stages.

[0009] The specific steps include:

[0010] (1) Real-time collection of sample information: Collect samples of tobacco leaves from the 0th to the 10th day, the 11th to the 31st day, and the 32nd to the 45th day of agricultural fermentation. All samples are tobacco leaves from the middle of the tobacco leaves from the same origin, the same variety, and the same original tobacco grade;

[0011] (2) Electronic nose sniffing: using an E-Nose PEN3 detector to detect the tobacco leaf samples of different fermentation periods in step (1), to obtain the difference information of the samples, and to screen the high response parameters according to the response values ​​of the 10 sensors of the electronic nose;

[0012] (3) Fingerprint imaging: using HS-GC-IMS detection and analysis technology to detect the tobacco leaf samples of different agricultural fermentation periods in step (1) to obtain fingerprint characteristic information of the samples;

[0013] (4) Establishing a fingerprint database: Selecting the sample fingerprint characteristic information obtained in step (3), using the analysis software supporting the instrument to perform statistical analysis on the sample data, and establishing a GC-IMS spectrum database of tobacco leaf samples at different fermentation stages;

[0014] (5) Metabolite analysis: The tobacco leaf samples of the tobacco leaves at different stages of agricultural fermentation in step (1) were tested using an automatic amino acid analyzer and LC-MS / MS detection and analysis technology to obtain characteristic information on changes in free amino acid and organic acid content of the samples;

[0015] (6) Establishing a metabolite database: Select the characteristic information of the free amino acid and organic acid content changes obtained in step (5), perform statistical analysis on the sample data using the analysis software supporting the instrument, and establish a key metabolite database of tobacco leaf samples at different fermentation stages;

[0016] (7) Construction of chemometric analysis data matrix: Select the spectra and metabolite data obtained in step (4) and step (6) to process missing values ​​and outliers, and construct the complete data matrix required for chemometric analysis;

[0017] (8) Screening of differential markers of different fermentation stages of filler tobacco leaves: The data matrix obtained in step (7) is screened for characteristic compounds using a chemometric method, wherein the chemometric method is an OPLS-DA discriminant analysis method, a calculation and screening of tolerance and variance expansion factor values, and a Lasso regression analysis method;

[0018] (9) Verification of differential markers: A data set is constructed using the characteristic compounds screened in step (7), and the accuracy and reliability of the differential markers are verified by combining the ROC curve and AUC value.

[0019] Among them, the 10 sensors of the electronic nose include: W1C, which is sensitive to aromatic compounds; W5S, which is sensitive to nitrogen oxides; W3C, which is sensitive to ammonia and aromatic compounds; W6S, which is sensitive to hydrogen substances; W5C, which is sensitive to alkanes and aromatic compounds; W1S, which is sensitive to methyls; W1W, which is sensitive to inorganic sulfides and terpenes; W2S, which is sensitive to alcohols and some aromatic compounds; W2W, which is sensitive to aromatic compounds and organic sulfides; and W3S, which is sensitive to alkanes.

[0020] Among them, an electronic nose was used to quickly smell the changes in volatile aroma components of fermented cigar core tobacco leaf samples. Cigar core tobacco leaf samples of different fermentation stages were accurately weighed and placed in 20mL sampling bottles, which were tightly sealed with sampling bottle caps and placed in a 60°C water bath for heating for 10 minutes. During the detection, the zero gas needle and the electronic nose sampling needle were simultaneously inserted into the headspace sampling bottle for sampling, and the volatile gas was inhaled into the electronic nose sensor system for detection. The sensor compartment flow rate of the electronic nose was 400mL / min, the initial injection flow rate was 400mL / min, the sampling interval was 1.0s, the cleaning time was 90s, the zeroing time was 5s, the pre-injection time was 5s, and the measurement time was 150s.

[0021] Among them, the volatile aroma components of the cigar core tobacco leaf sample were quickly detected by gas chromatography-ion mobility spectrometry. The specific method was as follows: 0.5 g of the fermented cigar tobacco leaf sample was accurately weighed and placed in a 20 mL headspace bottle, and the sample was injected after incubation at 80-100°C for 10-15 minutes, with an injection volume of 100-200 μL and no split injection; the incubation speed was 500 r / min, and the injection needle temperature was 80-85°C. The chromatographic column temperature was 60°C, and the carrier gas was high-purity helium (purity ≥ 99.999%);

[0022] The pressure increase program is as follows: initial flow rate 2.00 mL / min, maintained for 2 min, linearly increased to 10.00 mL / min within 8 min, linearly increased to 100.00 mL / min within 10 min, maintained for 10-20 min; chromatographic running time: 30-40 min; injection port temperature: 80°C; ionization source is tritium source (3H), migration tube length is 53 mm, electric field strength is 500 V / cm, migration tube temperature is 45°C, drift gas is high-purity nitrogen (purity ≥ 99.999%); flow rate is 150 mL / min, positive ion mode;

[0023] Obtain three-dimensional information spectra and obtain image features of volatile compounds;

[0024] Data analysis was performed on the image features of the three-dimensional information spectrum: a mixed standard of 6 ketones was detected, a calibration curve of retention time and retention index was established, and then the retention index of the substance was calculated through the retention time of the target object. The GC retention index (NIST 2020) database and IMS migration time database built into the VOCal software were used for retrieval and comparison, and the image features of the obtained three-dimensional information spectrum were analyzed to obtain the composition of volatile aroma components at different fermentation stages of the cigar core tobacco leaf samples.

[0025] Among them, the free amino acid content of tobacco leaf samples of different fermentation stages was detected by using an amino acid automatic analyzer: 0.4g of tobacco leaf samples of different fermentation stages were accurately weighed into a 50mL centrifuge tube, 8mL of 4% sulfosalicylic acid was added, and the samples were fully vortexed and mixed in a vortex machine and centrifuged at 10000rpm for 5min in a centrifuge, and then 1mL of supernatant was taken and filtered through a 0.22μm filter membrane into a 1.5mL injection bottle, and buffer A with a pH value of 3.45, buffer B with a pH value of 10.85, regeneration solution, potassium-sodium buffer solution, ninhydrin solution and cleaning solution were prepared, and then all the prepared solutions were ultrasonically treated for 30min, and filtered through 0.22μm aqueous and organic phase filter membranes, and then tested on the machine, and the amino acid mixed standard solution was used as the internal standard for quantification;

[0026] LC-MS / MS was used to detect the organic acid content of tobacco leaf samples at different fermentation stages: 0.5 g of freeze-dried tobacco leaf powder sample was accurately weighed, 5 mL of ultrapure water was added, and the mixture was fully homogenized using a homogenizer, and then ultrasonically extracted for 1 hour, and then 5 mL of chromatographic grade ethanol solution was added, and the mixture was centrifuged at 10,000 r / min for 3 minutes. The supernatant was filtered through a 0.45 μm organic filter membrane first, and then through a 0.22 μm organic filter membrane. 200 μL of the filtrate was placed in a liner tube, placed in a 1.5 mL injection bottle, and waited for injection for organic acid detection and analysis. A standard curve was constructed using six organic acid standards, including oxalic acid, tartaric acid, quinic acid, malic acid, lactic acid, and citric acid, to quantify the organic acid content in tobacco leaf.

[0027] The LC conditions were as follows: Eclipse Plus C18 column (4.6 mm × 250.0 mm, 5 μm), gradient elution with methanol and 0.1% formic acid aqueous solution as the mobile phase;

[0028] Mobile phase A was methanol solution: mobile phase B was 0.1% formic acid aqueous solution, the elution ratio was 3:97; the flow rate was 0.80 mL / min; the column temperature was 30°C; the injection volume was 5.0 μL;

[0029] The conditions of MC were as follows: electrospray ion source, negative ion detection mode, spray voltage of 3200 V, sheath gas flow rate of 50 arb, auxiliary gas flow rate of 20 arb, auxiliary gas temperature of 400 °C, ion transfer tube temperature of 500 °C, and scanning range of 50-750 m / z.

[0030] Among them, based on the data of volatile aroma components and metabolite content of cigar core tobacco samples at different fermentation stages, component analysis was performed to obtain grouping data of cigar core tobacco at different fermentation stages; according to the grouping data of cigar core tobacco at different fermentation stages, OPLS-DA discriminant analysis and Lasso regression analysis were combined to screen characteristic markers;

[0031] Based on the selected characteristic markers, a differential marker matrix is ​​constructed. Before the differential marker matrix is ​​used for chemometric analysis, data preprocessing is also performed, and the data preprocessing includes: deleting features with missing values ​​greater than 20%, using at least one missing value processing method; the missing value processing method includes: at least one of the non-filling method, mean filling method, regression filling method or missForest method; after the data processing is completed, the entire data matrix required for chemometric analysis is constructed;

[0032] ROC curve and AUC value were used to verify the reliability of real-time monitoring characteristic markers.

[0033] Preferably, the data preprocessing includes background subtraction, chromatographic peak extraction and peak alignment of the data.

[0034] Among them, in step (8), OPLS-DA analysis is used to analyze the flavor component spectrum information and amino acid and organic acid contents of the cigar core tobacco leaves at different stages of agricultural fermentation detected in steps (4) and (6), and metabolites with VIP values ​​> 1, difference multiple (FC) > 2 and p < 0.05 have better identification and differentiation characteristics. The top 10 volatile flavor compounds and related metabolites with VIP values ​​are screened for VIF calculation, and volatile flavor compounds and related metabolites with VIF < 10 are screened. Lasso regression analysis is further combined to screen differential markers, and the accuracy and reliability of the differential markers are verified using ROC curves and AUC values ​​to achieve effective identification of cigar tobacco leaves at different stages of agricultural fermentation.

[0035] The present invention also provides a multi-dimensional real-time monitoring system for the fermentation process of cigar core tobacco leaves, including a sample information real-time acquisition module, an electronic nose olfactory module, a fingerprint imaging module, and a metabolite analysis module. Based on the characteristic markers of different fermentation stages, through the characteristic compound acquisition and detection instrument, the characteristic compounds are targeted for detection, and the electronic nose olfactory module, the fingerprint imaging module, and the metabolite analysis module are combined to monitor the agricultural fermentation process of cigar core tobacco leaves in real time in multiple dimensions.

[0036] The sample information real-time collection module includes a connecting tube, which is connected to the inside of the cigar core tobacco fermentation pile to monitor the agricultural fermentation process of the cigar core tobacco in real time and accurately determine the fermentation period;

[0037] The connecting pipe is a PE pipe, a PB pipe or a stainless steel pipe, and has an inner diameter of 2-4 mm.

[0038] Among them, the carrier gas and drift gas used in the fingerprint imaging module are both high-purity nitrogen, the capillary column of the analyzer is a DB-WAX capillary column, the capillary column temperature is 60°C, the drift tube temperature of the ion mobility spectrometry is 45°C, and the injection volume of each fermentation gas sampling analysis is 0.1-0.5mL.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] (1) The multi-dimensional real-time monitoring method of the fermentation process of cigar core tobacco leaves of the present invention effectively combines the electronic nose olfactory module, the fingerprint imaging module, the metabolite analysis module and the chemometric analysis to comprehensively and multi-dimensionally analyze the changing characteristics of cigar core tobacco leaves at different fermentation stages.

[0041] (2) The fermented cigar tobacco leaf samples in the electronic nose olfactory module and the fingerprint imaging module do not require any pretreatment process, avoiding interference from external solvents, and can achieve real-time monitoring of the fermented tobacco leaves.

[0042] (3) The present invention combines the high-efficiency separation of gas chromatography with the trace rapid analysis advantages of ion mobility spectrometry to achieve secondary separation and effectively distinguish the characteristic flavor components of cigar tobacco leaves at different stages of agricultural fermentation.

[0043] (4) The present invention uses OPLS-DA discriminant analysis and Lasso regression analysis to analyze the flavor components and metabolites of tobacco leaves at different stages of agricultural fermentation, and screens the differential markers of tobacco leaves at different fermentation stages.

[0044] (5) The present invention verifies the accuracy and reliability of the characteristic compounds based on the screened characteristic compounds by combining the ROC curve and AUC value.

[0045] (6) The multi-dimensional real-time monitoring system for the fermentation process of cigar core tobacco leaves of the present invention can quickly and accurately monitor the agricultural fermentation process of cigar tobacco leaves in real time, has the advantages of simple operation and intuitive results, and provides a new technical method for the mechanized and intelligent control of the agricultural production stage of cigar tobacco leaves. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the process of the multi-dimensional real-time monitoring method of the fermentation process of filler tobacco leaves of the present invention;

[0047] Figure 2 Schematic diagram of a multi-dimensional real-time monitoring system for the fermentation process of filler tobacco leaves of the present invention;

[0048] Figure 3 The PCA graph and radar graph of the electronic nose olfactory module E-Nose for samples of filler tobacco leaves at different fermentation stages;

[0049] Figure 4 It is a two-dimensional top view and fingerprint comparison diagram of the fingerprint imaging module GC-IMS of tobacco samples of filler leaves at different fermentation stages;

[0050] Figure 5 The PCA diagram and Heatmap diagram of the metabolite analysis module of filler tobacco samples at different fermentation stages;

[0051] Figure 6 HCA cluster diagram of flavor components and metabolites in filler tobacco samples at different fermentation stages;

[0052] Figure 7 OPLS-DA diagram of filler tobacco samples at different fermentation stages;

[0053] Figure 8 This is the permutation test diagram of the OPLS-DA model for filler tobacco samples at different fermentation stages;

[0054] Fig. 9 This is the VIP value screening diagram based on OPLS-DA;

[0055] Fig.10 This is the Lasso regression analysis diagram of filler tobacco samples at different fermentation stages;

[0056] Fig.11 The content distribution diagram of the screened characteristic compounds in the filler tobacco samples at different fermentation stages;

[0057] Fig.12 Shown are the ROC curves and AUC values ​​of differential markers. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] like Figure 2 As shown, a multi-dimensional real-time monitoring system for the fermentation process of filler tobacco leaves includes a sample information real-time acquisition module, an electronic nose olfactory module, a fingerprint imaging module and a metabolite analysis module.

[0060] Among them, the sample information real-time collection module includes a connecting tube, which is connected to the inside of the cigar core tobacco leaf fermentation pile to monitor the agricultural fermentation process of the cigar core tobacco leaves in real time and accurately determine the fermentation period; the connecting tube is a PE tube or PB tube or stainless steel tube with an inner diameter of 2-4mm.

[0061] The carrier gas and drift gas used in the fingerprint imaging module are both high-purity nitrogen. The capillary column of the analyzer is a DB-WAX capillary column with a capillary column temperature of 60°C. The drift tube temperature of the ion mobility spectrometer is 45°C. The injection volume of each fermentation gas sampling analysis is 0.1-0.5mL.

[0062] like Figure 1 As shown, a multi-dimensional real-time monitoring method for the fermentation process of filler tobacco leaves comprises the following steps:

[0063] (1) Sample information real-time collection module: Collect cigar tobacco leaf samples at different stages of agricultural fermentation. All samples are from the same origin (Pu'er Jiangcheng), the same variety (Yunxue No. 39), and the same original tobacco grade (FiC3).

[0064] (2) Electronic nose olfactory module: The electronic nose PEN3 olfactometer is used to detect the tobacco leaf samples of different fermentation periods in step (1) to obtain the difference differentiation information of the samples by 10 different sensors of the electronic nose, such as Figure 3 shown.

[0065] Specifically, 0.5 g of tobacco leaf samples with different fermentation stages were placed in a 20 mL injection bottle, tightly sealed with a sampling bottle cap, and heated in a 60°C water bath for 10 min. During detection, the zero gas needle and the electronic nose injection needle were simultaneously inserted into the head space injection bottle for sampling, and the volatile gas was inhaled into the electronic nose sensor system for detection. The sensor chamber flow rate of the electronic nose was 400 mL / min, the initial injection flow rate was 400 mL / min, the sampling interval was 1.0 s, the cleaning time was 90 s, the zeroing time was 5 s, the pre-injection time was 5 s, the measurement time was 150 s, and each sample was measured in parallel 3 times.

[0066] (3) Fingerprint imaging module: gas chromatography-ion mobility spectrometry is used to detect the tobacco leaf samples of different fermentation periods in step (1) to obtain image feature information of the sample spectrum, such as Figure 4 shown.

[0067] Specifically, 0.5 g of cigar tobacco leaf samples from different periods of agricultural fermentation were placed in a 20 mL headspace injection bottle, and each sample was measured in parallel 3 times. Before injection, the sample was incubated for 15 min at a temperature of 80°C. The chromatographic column model used was a DB-WAX capillary column (15m×0.53mm, 1.0μm), the injection volume was 100μL, non-split injection, the incubation speed was 500r / min, and the injection needle temperature was 85°C. The chromatographic column temperature was 60°C, and the carrier gas was high-purity helium (purity ≥99.999%). The boost program was: the initial flow rate was 2.00 mL / min for 2 min, linearly increased to 10.00 mL / min within 8 min, linearly increased to 100.00 mL / min within 10 min, and maintained for 10 min. Chromatographic run time: 30 min; injection port temperature: 80°C. The ionization source is a tritium source (3H), the migration tube length is 53 mm, the electric field strength is 500 V / cm, the migration tube temperature is 45° C., the drift gas is high-purity nitrogen (purity ≥ 99.999%); the flow rate is 150 mL / min, and the positive ion mode.

[0068] (4) Establishment of volatile flavor database: Select the image feature information of the sample spectrum obtained in step (3), use the analysis software supporting the instrument to perform statistical analysis on the GC-IMS sample data, and establish the GC-IMS spectrum database of the filler tobacco leaf sample, such as Figure 4 According to the principle of two-dimensional difference spectrum, 55 characteristic peaks were selected for sorting and comparison to characterize the difference information between samples at different fermentation stages and to establish the GC-IMS spectrum database information of filler tobacco samples (Table 1).

[0069] Table 1 Relative peak volume and composition of volatile flavor compounds at different fermentation stages in filler tobacco leaves

[0070]

[0071]

[0072] (5) Metabolite analysis module: The amino acid automatic analyzer and LC / MS / MS detector were used to detect the tobacco samples of the cigar core leaves at different stages of agricultural fermentation in step (1). The composition and content of free amino acids and organic acids in the cigar core leaves were accurately quantified by combining the peak time and peak area of ​​the free amino acid mixed standard solution (Table 2) and the regression equation, linear range limit of quantification and detection limit of 6 organic acids (Table 3). The distribution differences of metabolites in samples at different fermentation stages were as follows: Figure 5 shown.

[0073] Table 2 Peak elution time and peak area of ​​free amino acid mixed standard solution

[0074]

[0075]

[0076] Table 3 Regression equation, linear range, quantification limit and detection limit of 6 organic acids

[0077]

[0078] Specifically, 0.4 g of tobacco leaf samples with different fermentation stages were placed in a 50 mL centrifuge tube, 8 mL of 4% sulfosalicylic acid was added, the mixture was thoroughly vortexed and mixed, and then centrifuged at 10,000 rpm in a centrifuge for 5 min. Then 1 mL of supernatant was taken, filtered through a 0.22 μm filter membrane into a 1.5 mL injection bottle, and buffer A with a pH value of 3.45, buffer B with a pH value of 10.85, regeneration solution, potassium-sodium buffer solution, ninhydrin solution and cleaning solution were prepared. Then all the prepared solutions were ultrasonically treated for 30 min, filtered through 0.22 μm aqueous and organic phase filter membranes, tested on the machine, and quantified using an amino acid mixed standard solution as an internal standard.

[0079] 0.5g freeze-dried tobacco powder sample was added with 5mL ultrapure water, fully homogenized with a homogenizer, and ultrasonically extracted for 1 hour, and then 5mL chromatographic grade ethanol solution was added, centrifuged at 10000r / min for 3min, and the supernatant was filtered through a 0.45μm organic filter membrane first, and then through a 0.22μm organic filter membrane. 200μL of the filtrate was placed in a liner tube and placed in a 1.5mL injection bottle, waiting for injection, and organic acid detection and analysis were performed. A standard curve was constructed with oxalic acid, tartaric acid, quinic acid, malic acid, lactic acid and citric acid, and the organic acid content in the core tobacco was quantified. The LC conditions were: Eclipse Plus C18 column (4.6 mm × 250.0 mm, 5 μm), gradient elution with methanol and 0.1% formic acid aqueous solution as the mobile phase, elution ratio of 3:97, flow rate of 0.80 mL / min, column temperature of 30 ° C, injection volume of 5.0 μ L. The MC conditions were: electrospray ion source, negative ion detection mode, spray voltage of 3200 V, sheath gas flow rate of 50 arb, auxiliary gas flow rate of 20 arb, auxiliary gas temperature of 400 ° C, ion transfer tube temperature of 500 ° C, scanning range of 50-750 m / z.

[0080] (6) Establishment of amino acid and organic acid metabolite database: The composition and content data of free amino acids and organic acids obtained in step (5) were selected for statistical analysis to establish the amino acid and organic acid metabolite database information of the filler tobacco leaf samples (Tables 4 and 5).

[0081] Table 4 Content and composition of free amino acids at different fermentation stages in filler tobacco leaves (mg / g)

[0082]

[0083] Table 5 Content and composition of organic acids at different fermentation stages in filler tobacco leaves (μg / mL)

[0084]

[0085]

[0086] (7) Chemometric analysis: The volatile flavor database and amino acid organic acid metabolite database obtained in step (4) and step (6) were respectively screened for differential marker compounds using OPLS-DA discriminant analysis, VIF value calculation screening and Lasso regression analysis. HCA cluster analysis and OPLS-DA discriminant analysis divided the agricultural fermentation process of tobacco leaves into three periods: early fermentation period (0-10 days), middle fermentation period (11-31 days) and late fermentation period (32-45 days). The HCA clustering results are shown in Figure 2. Figure 6As shown in Figure 2, the volatile flavor compounds and amino acid organic acid metabolites of the three fermentation periods were clustered separately, with obvious discrimination effects. Figure 7 As shown in the figure, the main areas of the early, middle and late fermentation stages of the tobacco leaves are relatively independent and do not overlap. The dependent variable fitting index (R2y) in the OPLS-DA discriminant analysis is 0.987 and 0.968, and the model prediction index (Q2) is 0.952 and 0.929. R2 and Q2 are both over 0.5, indicating that the model fitting results are reliable. After 200 permutation tests, Figure 8 As shown, the intersection points of the Q2 regression line and the vertical axis are all less than zero, indicating that the model does not have overfitting. The model validation is effective and it is believed that the results can be used for identification analysis of tobacco leaves at different stages of agricultural fermentation. Metabolites with VIP values ​​> 1, FC > 2, and p < 0.05 have better identification and differentiation characteristics. The top 10 VIP value volatile flavor compounds and related metabolites were screened out. The results are shown in Fig. 9 shown.

[0087] To further improve the accuracy of differential markers, all variables were further tested for cointegration. When there was a cointegration relationship between the independent variables, the variance of the regression coefficient estimated using the least squares method increased by a multiple of the variance of the estimated regression coefficient when there was no cointegration relationship between the independent variables. The larger the VIF value, the stronger the multicollinearity between the variables. A VIF value <10 was considered acceptable. The VIF calculation values ​​are shown in Table 6. A total of 16 variables with VIF values ​​>10 were deleted. The remaining variables were used as responses, and Lasso regression analysis was performed based on the Gaussian kernel function. The optimal value of the regularization parameter Lambda was determined through cross-validation, and the stability and prediction performance of the model selection were further explored. As Lambda increased, the mean square error (MSE) of the cross-validation showed a U-shaped curve, indicating that there was an optimal Lambda value at which the MSE was the smallest. The model corresponding to this optimal Lambda value covered 2 characteristic variables, which was the result of avoiding overfitting while ensuring prediction accuracy. In addition, the coefficient paths of each variable showed different trends with the increase of L1 Norm. It can be seen that some coefficients approach zero when the L1 Norm is relatively small, which means that these variables have limited contribution to the model. At the same time, the coefficients of other variables remain non-zero and even remain stable when the Lambda value increases, indicating that they are important for the prediction model. Therefore, tartaric acid and 1-hexanol were finally selected as differential characteristic markers of different fermentation stages of filler tobacco leaves ( Fig.10 The distribution of tartaric acid and 1-hexanol in tobacco leaves at different fermentation stages is shown in Figure 2. Fig.11 shown.

[0088] Table 6 VI F calculated values

[0089]

[0090] Based on the content of tartaric acid and 1-hexanol in tobacco leaf samples at different stages of agricultural fermentation, a data set was constructed, and the accuracy and reliability of the ROC curve and AUC value as differential marker compounds of different fermentation stages were verified. Generally speaking, the closer the AUC value is to 1, the higher the accuracy of the algorithm. In the present invention, the AUC values ​​of three different fermentation stages were calculated, and only a subset of the curves were displayed. The average AUC value was 0.864 in the early fermentation stage VS the middle fermentation stage, 1.000 in the early fermentation stage VS the late fermentation stage, and 0.7354 in the middle fermentation stage VS the late fermentation stage ( Fig.12 ). It is generally believed that an AUC value > 0.7 indicates the reliability of the screened characteristic compound. These indicate that tartaric acid and 1-hexanol can be used as key differential marker compounds for different fermentation stages. This example shows that the key differential markers screened by the present invention can be used as effective indicators for distinguishing different fermentation stages during the fermentation of filler tobacco leaves, and have high stability and good accuracy.

[0091] like Figure 2 As shown, the differential marker compounds screened in step (7) are used as rapid targeted monitoring indicators and built into a computer system to construct a multi-dimensional real-time monitoring system for the fermentation process of cigar core tobacco leaves, thereby realizing multi-dimensional real-time monitoring of the agricultural fermentation process of cigar core tobacco leaves.

[0092] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-dimensional real-time monitoring method for the fermentation process of filler tobacco leaves, characterized in that: Samples of filler tobacco leaves were collected before, during and after agricultural fermentation, and the volatile aroma components and related metabolite components of the filler tobacco leaves were quickly detected using an electronic nose, gas chromatography-ion mobility spectrometry, fully automatic amino acid analyzer and liquid chromatography-mass spectrometry. According to the characteristics of volatile aroma components and metabolites at different stages of agricultural fermentation, chemometric analysis was combined to distinguish the filler tobacco leaves at different fermentation times and screen the differential markers of the filler tobacco leaves at different fermentation stages. The following steps are involved: (1) Real-time collection of sample information: Collect samples of tobacco leaves from the 0th to the 10th day, the 11th to the 31st day, and the 32nd to the 45th day of agricultural fermentation. All samples are from the middle part of the tobacco leaves of the same origin, the same variety, and the same original tobacco grade; (2) Electronic nose sniffing: Using the E-Nose PEN3 detector to detect the tobacco leaf samples at different stages of agricultural fermentation in step (1), the difference information of the samples was obtained, and the high response parameters were screened according to the response values ​​of the 10 sensors of the electronic nose; (3) Fingerprint imaging: HS-GC-IMS detection and analysis technology is used to detect the tobacco leaf samples of the filler leaves at different stages of agricultural fermentation in step (1) to obtain the fingerprint characteristic information of the samples; GC-IMS was used to rapidly detect the volatile aroma components of cigar filler tobacco samples. Specifically, 0.5 g of fermented cigar tobacco samples were accurately weighed and placed in a 20 mL headspace bottle. The samples were incubated at 80-100 °C for 10-15 min and then injected with an injection volume of 100-200 µL without split flow. The incubation speed was 500 r / min, the injection needle temperature was 80-85 °C, the chromatographic column temperature was 60 °C, and the carrier gas was high-purity helium. The pressure increase program was as follows: initial flow rate 2.00 mL / min for 2 min, linearly increased to 10.00 mL / min within 8 min, linearly increased to 100.00 mL / min within 10 min, and maintained for 10-20 min; chromatographic running time: 30-40 min; injection port temperature: 80 °C; ionization source was tritium source, migration tube length was 53 mm, electric field strength was 500 V / cm, migration tube temperature was 45 °C, drift gas was high-purity nitrogen; flow rate was 150 mL / min, positive ion mode; three-dimensional information spectra were obtained to obtain image features of volatile compounds; Data analysis was performed on the image features of the three-dimensional information spectrum: a mixed standard of six ketones was detected, and a calibration curve of retention time and retention index was established. The retention index of the substance was then calculated by the retention time of the target substance. The GC retention index database and IMS migration time database built into the VOCal software were used for retrieval and comparison, and the image features of the obtained three-dimensional information spectrum were analyzed to obtain the composition of volatile aroma components at different fermentation stages of the cigar core tobacco leaf samples. (4) Establishing a fingerprint database: Select the sample fingerprint characteristic information obtained in step (3), use the analysis software provided with the instrument to perform statistical analysis on the sample data, and establish a GC-IMS spectrum database of tobacco leaf samples at different fermentation stages; wherein the chromatographic column model is a DB-WAX capillary chromatographic column; (5) Metabolite analysis: The full-automatic amino acid analyzer and LC-MS / MS detection and analysis technology are used to detect the tobacco leaf samples at different stages of agricultural fermentation in step (1) to obtain the characteristic information of the changes in the free amino acid and organic acid content of the samples; LC-MS / MS was used to detect the organic acid content of tobacco leaf samples at different fermentation stages: 0.5 g of freeze-dried tobacco leaf powder sample was accurately weighed, 5 mL of ultrapure water was added, and the mixture was fully homogenized using a homogenizer. Ultrasonic extraction was performed for 1 hour, and then 5 mL of chromatographic grade ethanol solution was added. The mixture was centrifuged at 10,000 r / min for 3 min. The supernatant was filtered through a 0.45 μm organic filter membrane and then a 0.22 μm organic filter membrane. 200 μL of the filtrate was placed in a liner tube and placed in a 1.5 mL injection bottle, waiting for injection. Organic acid detection and analysis were performed, and a standard curve was constructed using six organic acid standards, namely oxalic acid, tartaric acid, quinic acid, malic acid, lactic acid and citric acid, to quantify the organic acid content in tobacco leaf samples. The LC conditions were as follows: Eclipse Plus C18 column, methanol and 0.1% formic acid aqueous solution as mobile phase, elution ratio of 3:97; flow rate of 0.80 mL / min; column temperature of 30 °C; injection volume of 5.0 μL; The MS conditions were as follows: electrospray ion source, negative ion detection mode, spray voltage of 3200 V, sheath gas flow rate of 50 arb, auxiliary gas flow rate of 20 arb, auxiliary gas temperature of 400 °C, ion transfer tube temperature of 500 °C, and scan range of 50–750 m / z; (6) Establishment of metabolite database: Select the characteristic information of free amino acid and organic acid content changes obtained in step (5), use the analysis software supporting the instrument to perform statistical analysis on the sample data, and establish a key metabolite database of tobacco leaf samples at different fermentation stages; (7) Construction of the chemometric analysis data matrix: Select the spectra and metabolite data obtained in steps (4) and (6) to process missing values ​​and outliers, and construct the complete data matrix required for chemometric analysis; (8) Screening of differential markers of different fermentation stages of cigar core tobacco leaves: The data matrix obtained in step (7) is screened for characteristic compounds using a chemometric method, wherein the chemometric method is an OPLS-DA discriminant analysis method, a calculation and screening of tolerance and variance expansion factor values, and a Lasso regression analysis method; tartaric acid and 1-hexanol are used as differential characteristic markers of different fermentation stages of cigar core tobacco leaves; (9) Verification of differential markers: Construct a data set using the characteristic compounds screened in step (8), and verify the accuracy and reliability of the differential markers using ROC curves and AUC values.

2. The multi-dimensional real-time monitoring method of the fermentation process of filler tobacco leaves according to claim 1, characterized in that: The 10 sensors of the electronic nose include: W1C, which is sensitive to aromatic compounds; W5S, which is sensitive to nitrogen oxides; W3C, which is sensitive to ammonia and aromatic compounds; W6S, which is sensitive to hydrogen substances; W5C, which is sensitive to alkanes and aromatic compounds; W1S, which is sensitive to methyls; W1W, which is sensitive to inorganic sulfides and terpenes; W2S, which is sensitive to alcohols and some aromatic compounds; W2W, which is sensitive to aromatic compounds and organic sulfides; and W3S, which is sensitive to alkanes.

3. The multi-dimensional real-time monitoring method of the fermentation process of filler tobacco leaves according to claim 2, characterized in that: The free amino acid content of tobacco leaf samples with different fermentation stages was detected by amino acid automatic analyzer: 0.4 g of tobacco leaf samples with different fermentation stages were accurately weighed into a 50 mL centrifuge tube, 8 mL of 4% sulfosalicylic acid was added, the samples were thoroughly vortexed and centrifuged at 10000 rpm in a centrifuge for 5 min, 1 mL of supernatant was taken, filtered through a 0.22 μm filter membrane into a 1.5 mL injection bottle, buffer A with a pH value of 3.45, buffer B with a pH value of 10.85, regeneration solution, potassium-sodium buffer solution, ninhydrin solution and cleaning solution were prepared, all the prepared solutions were ultrasonicated for 30 min, filtered through 0.22 μm aqueous and organic phase filter membranes, tested on the analyzer, and quantified using the amino acid mixed standard solution as the internal standard.

4. The multi-dimensional real-time monitoring method of the fermentation process of filler tobacco leaves according to claim 3, characterized in that: Based on the data of volatile aroma components and metabolite content of core tobacco samples at different fermentation stages, component analysis was performed to obtain grouping data of core tobacco leaves at different fermentation stages; based on the grouping data of core tobacco leaves at different fermentation stages, OPLS-DA discriminant analysis and Lasso regression analysis were combined to screen characteristic markers; According to the screened characteristic markers, a differential marker matrix is ​​constructed; Before the differential marker matrix is ​​used for chemometric analysis, data preprocessing is also performed, and the data preprocessing includes: deleting features with missing values ​​greater than 20%, using at least one missing value processing method; the missing value processing method includes at least one of the non-filling method, the mean filling method, the regression filling method or the missForest method; after the data processing is completed, the entire data matrix required for chemometric analysis is constructed.

5. A multi-dimensional real-time monitoring system for the fermentation process of filler tobacco leaves using the monitoring method according to any one of claims 1 to 4, characterized in that: It includes a sample information real-time acquisition module, an electronic nose olfactory module, a fingerprint imaging module and a metabolite analysis module; the sample information real-time acquisition module includes a connecting tube, which is connected to the inside of the cigar core tobacco fermentation pile to monitor the agricultural fermentation process of the cigar core tobacco in real time and accurately determine the fermentation period; The connecting pipe is a PE pipe, a PB pipe or a stainless steel pipe, and has an inner diameter of 2-4 mm.

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