Analysis method of key differential flavor components influencing tobacco sensory quality and analysis method of tobacco sensory quality influence factors

Abstract

The invention relates to a method for analyzing key differential flavor components influencing the sensory quality of tobacco and a method for analyzing influence factors of the sensory quality of the tobacco, and belongs to the technical field of tobacco chemistry. According to the method, the sensory omics and the metabonomics are combined, the tobacco characteristic components are analyzed with the sense organ as the guide, key differential flavor components are screened in combination with the OAV value and difference analysis, the factors influencing the tobacco sensory quality are explored from the perspective of metabonomics pathway analysis, and a theoretical basis is provided for directional regulation and control of the tobacco sensory quality.

Description

Technical Field

[0001] The invention relates to an analysis method for key difference aroma components affecting tobacco sensory quality and an analysis method for factors affecting tobacco sensory quality, belonging to the technical field of tobacco chemistry. Background Art

[0002] Tobacco (Nicotiana tabacum L.) is an annual herbaceous plant of the genus Nicotiana in the Solanaceae family. It is native to South America and is widely cultivated in provinces and regions in the north and south of China. Tobacco has medicinal, agricultural and industrial uses and is one of the important economic crops in the world. With the improvement of people's living standards and the advancement of science and technology, the quality requirements for tobacco are getting higher and higher. The chemical composition of tobacco is the material basis for the formation of tobacco quality, and the sensory quality of tobacco is the final judgment of tobacco quality. Among them, the aroma components are crucial to the aroma level and richness of tobacco during the smoking process. Therefore, from the perspective of aroma components, studying the factors that affect the sensory quality of tobacco is conducive to further understanding and mastering the influence of aroma components on the sensory quality of tobacco.

[0003] At present, the methods for studying the factors affecting the sensory quality of tobacco mainly focus on the qualitative analysis of all components of tobacco, and then screen the aroma components that may affect its sensory quality. The Chinese invention patent application with the publication date of August 9, 2019 and the publication number of CN110108817A discloses an analysis method for volatile metabolic markers of tobacco with characteristic aroma mutants based on GC-MS. The method first performs solid phase microextraction of volatile metabolites of living tobacco, and then uses gas chromatography-mass spectrometry to identify the volatile metabolites of tobacco plants in full scan mode, and finally performs data processing and pattern recognition analysis to obtain volatile metabolic markers. This method can solve the problems of collection, identification and semi-quantitative detection of unstable and easily degradable active volatiles, and can distinguish and identify different aroma mutant flue-cured tobacco. However, when the material matrix is ​​complex and there are many types of system components, it is difficult to quickly obtain key components that have a direct causal relationship with sensory effects. Therefore, component analysis of characteristic components screened out based on sensory omics is helpful to find sensory active components in complex systems. Moreover, most current studies focus on the screening of differential substances, and few explore the factors that affect sensory quality from the perspective of anabolic molecular mechanisms. Summary of the invention

[0004] The first object of the present invention is to provide a method for analyzing key differential aroma components that affect the sensory quality of tobacco, and to provide a method for analyzing key differential aroma components that reflect the characteristic aroma of tobacco products and affect the sensory quality.

[0005] The second object of the present invention is to provide a method for analyzing factors affecting tobacco sensory quality, and to provide a new method for analyzing factors affecting tobacco sensory quality that effectively integrates the cooperation between sensory quality and compounds.

[0006] In order to achieve the above object, the technical scheme of a method for analyzing key difference aroma components affecting tobacco sensory quality in the present invention is:

[0007] A method for analyzing key differential aroma components that affect tobacco sensory quality comprises the following steps:

[0008] S1. Extracting and dividing different tobacco samples of the same type into fractions, performing sensory evaluation on each collected fraction, combining the fractions that can reflect the aroma characteristics of the tobacco sample extract, and obtaining characteristic components;

[0009] S2. Perform qualitative and quantitative analysis on the characteristic components obtained in S1, evaluate the sensory contribution of each aroma component based on the OAV value, and obtain the key differential aroma components through differential analysis.

[0010] The beneficial effect of the above technical solution is that the method for analyzing key differential aroma components that affect the sensory quality of tobacco is a pioneering invention. The present invention combines sensory omics, analyzes tobacco characteristic components with sensory orientation, and screens key differential aroma components by combining OAV value and differential analysis, providing a theoretical basis for the directional regulation of tobacco sensory quality.

[0011] Specifically, the OAV value (detection threshold) described in the present invention is the detection threshold of the aroma component in the same medium, and the medium may be air, water or ethanol.

[0012] Preferably, the extraction process of the tobacco sample in S1 is: the tobacco sample is subjected to treatments such as cutting, crushing, grinding, and baking, and then the tobacco sample extract is obtained by using extraction methods such as ultrasonic extraction, reflux extraction, continuous extraction, and microwave extraction.

[0013] Preferably, the qualitative analysis in S2 includes qualitative analysis of the matching degree of the NIST spectral library and the Wiley spectral library, qualitative analysis of standard substances, and qualitative analysis of RI; and the quantitative analysis includes semi-quantitative analysis and accurate quantitative analysis.

[0014] As a further improvement, the fraction segmentation method in S1 includes gel permeation chromatography, forward chromatography, reverse chromatography, and ion exchange chromatography.

[0015] As a further improvement, the analysis method described in S2 includes non-targeted or targeted GC-MS, SPME-GC-MS, and LC-MS.

[0016] As a further improvement, the difference analysis in S2 includes univariate statistical analysis and multivariate statistical analysis.

[0017] As a further improvement, the multivariate statistical analysis includes PCA, PLS-DA, OPLS-DA, and correlation analysis.

[0018] As a further improvement, the difference analysis is a t-test combined with OPLS-DA.

[0019] As a further improvement, the conditions for the difference analysis are that VIP is greater than 1 and P is less than 0.05.

[0020] The beneficial effect of the above technical solution is that the key difference aroma components are screened by using t-test combined with multivariate statistical analysis OPLS-DA, with strict VIP greater than 1 and P less than 0.05 as screening indicators. Combining univariate statistical analysis with multivariate statistical analysis can more accurately and comprehensively screen out difference information, and the tester can adjust it according to the actual situation, which has a wide range of applications.

[0021] As a further improvement, the tobacco samples include flue-cured tobacco, burley tobacco, air-cured tobacco, and oriental tobacco.

[0022] In order to achieve the above object, the technical scheme of a method for analyzing factors affecting tobacco sensory quality in the present invention is:

[0023] A method for analyzing factors affecting tobacco sensory quality, comprising the following steps:

[0024] S1. Obtaining key difference aroma components by using the analysis method of key difference aroma components affecting tobacco sensory quality;

[0025] S2. Use the KEGG database to match the key differential aroma components obtained in S1, and enrich the metabolic pathways of the matching metabolites to obtain the metabolic pathways of the key components.

[0026] The beneficial effect of the above technical solution is that: from the perspective of metabolomics pathway analysis of the present invention, metabolic pathways that may have a certain impact on the sensory quality of tobacco can be screened, and factors that may affect the sensory quality of tobacco can be explored from the molecular metabolic mechanism level. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is the OPLS-DA score diagram of filler tobacco leaves from different producing areas in Example 1 of the present invention;

[0028] Figure 2 This is a metabolic network diagram of the key difference aroma components in Example 2 of the present invention. DETAILED DESCRIPTION

[0029] The existing methods for studying factors affecting tobacco sensory quality mainly focus on characterizing all tobacco components and then screening out aroma components that may affect its sensory quality. However, the sensory quality of tobacco is not a simple sum of the effects of a single compound, but a common result of mutual cooperation, and is ultimately reflected in the smoking experience. This method may miss components that have indirect effects on the senses, and most studies only stop at obtaining screening results, and rarely explore the impact of sensory quality from the perspective of anabolic molecular mechanisms.

[0030] Acquiring characteristic components guided by the sense organs, conducting component analysis, and screening the components in combination with the odor contribution can accurately obtain the aroma components that affect the sensory quality. Using metabolomics pathway analysis to trace the key differential aroma components, enriching the important synthetic pathways, and finding the main metabolic pathways that affect the sensory quality of tobacco can provide solutions for tobacco sensory quality regulation and provide a basis for tobacco production enterprises to manage tobacco sensory quality. Based on this, the present invention provides an analysis method for key differential aroma components that affect tobacco sensory quality and an analysis method for factors affecting tobacco sensory quality.

[0031] The present invention combines sensory omics and metabolomics, and can quickly analyze the aroma components in tobacco products, effectively determine the aroma components in tobacco that have important contributions to the sensory quality, and screen out their main influencing metabolic pathways, providing theoretical guidance at the molecular metabolic level for improving the sensory quality of tobacco.

[0032] The present invention is further described below in conjunction with specific implementation methods, but the protection scope of the present invention is not limited thereto; unless otherwise specified, various reagents, instruments, etc. used in the examples are commercially available products.

[0033] Specific embodiments of the method for analyzing key difference aroma components affecting tobacco sensory quality and the method for analyzing factors affecting tobacco sensory quality of the present invention:

[0034] Example 1 Analysis of differences in sensory quality of cigar tobacco leaves at home and abroad

[0035] This example analyzes the sensory quality differences of filler tobacco leaves from domestic and foreign production areas, and the specific implementation operations are as follows:

[0036] 1. Sample collection and sample pretreatment

[0037] Cigar core tobacco samples from 4 production areas at home and abroad were selected, including 2 foreign cigars from Indonesia and the Dominican Republic, and 5 domestic cigars from Hubei and Yunnan, China. The tobacco samples were crushed and sieved, and placed in a constant temperature and humidity chamber (temperature 22°C, humidity 60%) for 24 hours for equilibration.

[0038] Preparation of the extract: Take 100 g of balanced tobacco powder and reflux extract it in 500 mL of ethanol aqueous solution (75% by volume) for 2 h. After filtering, evaporate the solvent by rotary evaporation (40° C., system pressure 5 kPa) to obtain a crude tobacco extract.

[0039] Separation of extracts: Take 6g of the above tobacco leaf extract and dissolve it in 15mL of distilled water. After filtering through an ultrafiltration membrane, use distilled water as the mobile phase, Sephadex LH-20 as the filler, and perform gel chromatography separation at a flow rate of 3mL / min. Collect one fraction every 10 minutes through the collector, and collect a total of 10 fractions; monitor with an ultraviolet detector to determine the starting and end points of the collected fractions. The sensory evaluation team used the aroma profile method to olfactory evaluate the collected fractions one by one. After removing the fractions without obvious aroma characteristics, the fractions with similar aroma characteristics were combined to obtain 5 aroma components. Among them, 3 groups of aroma components are closest to the aroma characteristics of cigar tobacco leaf extracts. These 3 groups of components are selected and combined as the characteristic components of cigar core tobacco leaves.

[0040] Note: The same operation was adopted for the filler tobacco samples from different producing areas to obtain the characteristic components of the filler tobacco.

[0041] 2. Analysis methods

[0042] (1) Analysis of characteristic aroma components:

[0043] The characteristic components of the cigar core tobacco leaves from different producing areas obtained in step 1 were dissolved in methanol respectively, filtered with a 0.22μm nylon filter head and then analyzed by GC-MS. The GC-MS conditions are: DB-5MS chromatographic column (60m×0.25mm×0.25μm); the injection port temperature is 270℃, the ion source temperature is 230℃, and the transfer line temperature is 280℃. The program temperature is increased to 260℃ at a rate of 3℃ / min, and then to 280℃ at a rate of 5℃ / min. The injection is carried out in a splitless manner at 270℃, and the injection volume is 1μL. The ionization voltage is 70eV, and the scanning range is 33~455amu. The GC-MS results are searched using the NIST17 spectral library, and compounds with a matching degree higher than 85% are selected for identification. And the standard material comparison verification is carried out to determine the aroma components that contribute to the characteristics of the cigar core tobacco leaves.

[0044] Through qualitative analysis, 99 compounds were identified in the characteristic components. The aroma characteristics of each substance were clarified through literature review, and the compounds were classified according to the aroma characteristics. At the same time, based on the characteristic components of cigar tobacco leaves reported in the literature, 56 characteristic aroma components were screened out in combination with the aroma characteristics of the compounds, mainly including 19 ketones, 6 alcohols, 4 esters, 9 acids, 3 aldehydes, 9 heterocyclics, 3 terpenes, 2 phenols and 1 ether. Some of the compounds are shown in Table 1.

[0045] (2) Quantitative analysis of aroma components:

[0046] The characteristic components of the tobacco leaves from different production areas obtained in step 1 were prepared into solutions with ethanol containing internal standard phenylethyl acetate (0.92 μg / mL), and the aroma components were determined by GC-MS. The mass spectrometry scanning mode was selected ion scanning (SIM), and other analysis conditions were the same as qualitative analysis. The target components were quantified by the standard curve internal standard method.

[0047] 3. Screening of aroma active ingredients

[0048] The olfactory threshold (OAV) of the aroma component is based on the detection threshold of the substance in water, using the formula OAV i =C i / T i (C i is the mass concentration of the compound; T i The aroma activity value was calculated by using the detection threshold of the compound in water, and 36 compounds with OAV greater than 1 were screened out from 56 characteristic aroma components as aroma active components. The specific results are shown in Table 1.

[0049] Table 1 OAV of 36 flavor active ingredients

[0050]

[0051]

[0052] 4. Difference Analysis

[0053] SPSS software was used to conduct a one-way ANOVA on the contents of 36 flavor active ingredients in tobacco leaves from different production areas, and the P value was obtained. SIMCA 14.1 software was used to combine the production area grouping with the results of the content of flavor active ingredients in tobacco leaves, and an orthogonal partial least squares discriminant analysis was performed. The results are as follows: Figure 1 As shown. Figure 1 It can be seen that the tobacco samples from domestic and foreign production areas are well separated. 2 The intercept of the regression line and the Y axis is less than 0, indicating that the model is not overfitted and can be used for subsequent screening of key differential aroma components. Combined with VIP>1, P<0.05, it can be seen that sclareol, indole, phenylacetic acid, furfuryl alcohol, 5-methylfurfural, γ-butyrolactone, (-)-ambrox, megatrienone II and megatrienone IV are key differential aroma components.

[0054] 5. Sensory effect verification

[0055] In order to verify the influence of the key difference components screened out in step 4 on the sensory quality of filler tobacco leaves, two tobacco leaves, Yunxue No. 6 (Yunnan) and Olor (Dominican Republic), were selected for flavoring comparison experiments. Among the key difference components, the OAVs of 5-methylfurfural, furfuryl alcohol, (-)-ambrox, indole, megastigmatrienone II, megastigmatrienone IV, and phenylacetic acid were different between the two (as shown in Table 2).

[0056] Table 2 Odor contribution of key differential components

[0057]

[0058] From the sensory results (as shown in Table 3), Yunxue No. 6 has obvious hay aroma compared with Olor, and slightly insufficient nutty aroma, woody aroma, honey sweet aroma, and baking aroma. Yunxue No. 6 was selected to add 5-methylfurfural, furfuryl alcohol, (-)-ambrox and phenylacetic acid to make its content the same as Olor to obtain Yunxue No. 6# comparative example, and then sensory evaluation was performed. From the results in Table 3, it can be seen that compared with Yunxue No. 6, Yunxue No. 6# has improved nutty aroma, woody aroma, honey sweet aroma and baking aroma, indicating that the selected key difference components have an important influence on the aroma characteristics of the sensory quality of the cigar filler tobacco leaves.

[0059] Table 3 Sensory evaluation data

[0060] Nutty aroma Bean Fragrance Woody Sweet and caramel Honey sweet fragrance Resin Fragrance Baking aroma Hay aroma Yunxue No.6 1 2 - 2 1 2 0 2 Olor 2 2 1 2 3 2 2 1 Cloud Snow No.6# 2 2 1 2 2 2 1 2

[0061] Example 2 Metabolomics Pathway Analysis

[0062] The CAS number of the key difference aroma component screened out in Example 1 was searched in the KEGG database, and the corresponding KEGG ID was matched to obtain the biological pathway information of the matching metabolite. In the pathway enrichment analysis, the metabolic pathway impact value was calculated by topological analysis, and the metabolic pathway with a P value less than 0.05 was screened as the main influencing pathway for the biosynthesis of the key difference aroma component. The metabolic network of the key difference aroma component was formed by drawing.

[0063] The key differential aroma components were searched in the KEGG database, and 7 compounds were matched. MetaboAnalyst analysis was used to analyze the biological pathways involved in the 7 matching metabolites. The results showed that the key differential aroma components were mainly involved in 3 pathways, namely phenylalanine metabolism, biosynthesis of phenylalanine, tyrosine and tryptophan, and biosynthesis of carotenoids. The metabolic pathway impact value was calculated by topological analysis, and 2 metabolic pathways with P < 0.05 were screened as the main influencing pathways for the biosynthesis of key differential aroma components. The results are shown in Table 4. Afterwards, the metabolic network was constructed for the 2 pathways with higher impact values, such as Figure 2From the above analysis, it can be concluded that the metabolic pathways that affect the sensory quality differences of filler tobacco leaves from different production areas may be phenylalanine metabolism and the biosynthesis of phenylalanine, tyrosine and tryptophan, which involve compounds such as phenylalanine, lutein, tryptophan and pyruvate.

[0064] Related studies have shown that most alkaloids in tobacco are produced by the metabolism of aromatic amino acids (phenylalanine, tyrosine and tryptophan) (Chinese Tobacco Science, 2005, (04): 23-26). Although alkaloids do not have aroma themselves, they are directly related to the aroma quality of tobacco leaves (Chinese Tobacco Journal, 2013, 19 (05): 16-21). In addition, aromatic amino acids themselves are indirect precursors of tobacco aroma precursors. For example, the degradation of phenylalanine can produce benzaldehyde, phenylacetaldehyde, benzyl alcohol, phenylethanol and other substances, which can contribute to the characteristic aroma of almond, rose and honey sweet aroma to tobacco (Chinese Tobacco Science, 2008, (05): 6-10), and have a significant impact on the formation of cigar aroma style. Therefore, the two metabolic pathways screened can significantly affect the sensory quality of cigar tobacco leaves.

[0065] Table 4 Metabolic pathway enrichment results

[0066]

[0067] Finally, it is noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing key difference aroma components that affect tobacco sensory quality, characterized in that: The steps include: S1. Extracting and dividing different tobacco samples of the same type into fractions, performing sensory evaluation on each collected fraction, combining the fractions that can reflect the aroma characteristics of the tobacco sample extract, and obtaining characteristic components; S2. Perform qualitative and quantitative analysis on the characteristic components obtained in S1, evaluate the sensory contribution of each aroma component based on the OAV value, and obtain the key differential aroma components through differential analysis.

2. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to claim 1, characterized in that: The fraction splitting methods described in S1 include gel permeation chromatography, forward chromatography, reverse chromatography, and ion exchange chromatography.

3. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to claim 1, characterized in that: The methods of analysis described in S2 include non-targeted or targeted GC-MS, SPME-GC-MS, and LC-MS.

4. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to claim 1, characterized in that: The difference analysis described in S2 includes univariate statistical analysis and multivariate statistical analysis.

5. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to claim 4, characterized in that: The multivariate statistical analysis includes PCA, PLS-DA, OPLS-DA, and correlation analysis.

6. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to claim 4 or 5, characterized in that: The difference analysis was performed by combining t-test with OPLS-DA.

7. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to claim 6, characterized in that: The conditions for the difference analysis were that VIP was greater than 1 and P was less than 0.

05.

8. The method for analyzing the key difference aroma components affecting tobacco sensory quality according to any one of claims 1 to 5, characterized in that: The tobacco samples include flue-cured tobacco, burley tobacco, sun-cured tobacco and oriental tobacco.

9. A method for analyzing factors affecting tobacco sensory quality, characterized in that: The steps include: S1. Obtaining key difference aroma components by using the analysis method for key difference aroma components affecting tobacco sensory quality according to any one of claims 1 to 8; S2. Use the KEGG database to match the key differential aroma components obtained in S1, and enrich the metabolic pathways of the matching metabolites to obtain the metabolic pathways of the key components.

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