Screening method for key factors of sensory quality of tobacco leaves and application of screening method

Abstract

The invention relates to a screening method and application of key factors of sensory quality of tobacco leaves, and the screening method comprises the following steps: carrying out sensory effect evaluation on the tobacco leaves of the same variety in the same production area to obtain high-quality tobacco leaves and low-quality tobacco leaves; respectively extracting and separating to obtain a plurality of separated fractions of the high-quality tobacco leaves and the low-quality tobacco leaves; carrying out sensory effect evaluation on the plurality of separation fractions, dividing the fractions with the same function into one group to obtain components A1-An of high-quality tobacco leaves and components B1-Bn of inferior tobacco leaves, and screening to obtain components Ax and Bx with the best sensory quality and components Ay and By with the worst sensory quality; and carrying out chemical analysis on Ax, Bx, Ay and By, carrying out difference analysis on Ax and Bx and Ay and By based on chemical analysis data, and screening chemical components with obvious differences to obtain key factors of the sensory quality of the tobacco leaves. The screening method provided by the invention can effectively determine the chemical components influencing the sensory quality of the tobacco leaves, and provides guidance for tobacco leaf planting, conditioning, tobacco flavor blending and the like.

Description

Technical Field

[0001] This invention relates to the field of tobacco analysis technology, and in particular to a method for screening key factors of tobacco leaf sensory quality and its application. Background Technology

[0002] In the food and daily chemical industries, sensory omics research elucidates the formation of complex flavor systems and their key material basis through component groups sharing common flavor characteristics. In recent years, based on sensory omics research, groups influencing important flavor characteristics of cigarette smoke, such as smoky, spicy, caramel-sweet, milky, bean-like, sour, floral, nutty, and fruity aromas, have become increasingly clear. Furthermore, applying sensory omics research to the refined processing of natural flavorings can yield "functionally focused and component-diverse" characteristic flavor groups of natural flavorings, fully highlighting their stylistic features (202211130793.X; CN202211132136.9; CN202211130817.1). Methodologically, membrane separation and gel column chromatography are commonly used to separate particulate matter or natural flavorings from cigarette smoke, combined with aroma evaluation to identify characteristic components, and GC / MS analysis to further clarify the material basis of these characteristic groups.

[0003] Due to factors such as climate, soil, and genetic characteristics, the yield and quality of tobacco leaves vary significantly among different varieties and from different producing areas. In recent years, to explore the influencing factors on tobacco leaf quality, numerous reports have been published on the sensory quality, conventional chemical components, and volatile / semi-volatile aroma components of tobacco leaves of different types and from different producing areas. However, no studies have been reported that use sensoryomics to explore the differences in sensory quality of tobacco leaves of the same variety from the same main producing area. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a method for screening key factors affecting the sensory quality of tobacco leaves and its application. Based on the research approach of sensory omics, this invention analyzes the reasons for quality differences in tobacco leaves of the same variety from the same production area, effectively identifying the chemical components affecting the sensory quality of tobacco leaves, and providing guidance for tobacco cultivation, processing, and flavoring.

[0005] To achieve this objective, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a method for screening key factors of the sensory quality of tobacco leaves, the screening method comprising the following steps:

[0007] (1) Sensory evaluation of tobacco leaves of the same variety from the same production area was conducted to identify high-quality and low-quality tobacco leaves;

[0008] (2) Extract and separate high-quality tobacco leaves and low-quality tobacco leaves respectively to obtain several separated fractions of high-quality tobacco leaves and low-quality tobacco leaves;

[0009] (3) Sensory evaluation of several separated fractions of high-quality and low-quality tobacco leaves was conducted, and fractions with the same function were grouped together to obtain the components A1-A of high-quality tobacco leaves. n Component B1-B of inferior tobacco leaves n Component A with the best sensory quality was selected through screening. x and B x The worst component A y and B y ;

[0010] (4) For A x B x A y and B y Chemical analysis was performed, and the chemical analysis data was used to analyze A. x With B x A y With B y Differential analysis was conducted to screen for chemically significant differences, thereby identifying key factors affecting the sensory quality of tobacco leaves.

[0011] The method for screening key factors of tobacco leaf sensory quality provided by this invention obtains high-quality and low-quality tobacco leaves through sensory evaluation, extracts and separates the two types of tobacco leaves to obtain separate fractions, and then screens to obtain component A with the best sensory quality. x and B x The worst component A y and B y Based on this, chemical analysis and differential analysis were conducted to screen for chemically significantly different components, thus identifying key factors affecting the sensory quality of tobacco leaves. The screening method provided by this invention is based on sensory omics research, which can accurately identify key groups affecting the smoking quality of tobacco leaves, thereby effectively determining the chemical components affecting the sensory quality of tobacco leaves and providing guidance for tobacco cultivation, processing, and flavoring.

[0012] Preferably, the type of tobacco leaves in step (1) includes flue-cured tobacco, aromatic tobacco, burley tobacco, or sun-cured tobacco.

[0013] Preferably, the high-quality tobacco leaves in step (1) are tobacco leaves that embody the typical style characteristics of the tobacco variety, and the low-quality tobacco leaves are tobacco leaves that embody the defects of the tobacco variety. The difference in the sensory evaluation index scores between the high-quality tobacco leaves and the low-quality tobacco leaves is the greatest.

[0014] Preferably, the extraction method in step (2) includes any one or a combination of at least two of solvent extraction, subcritical extraction, supercritical extraction, molecular distillation or steam distillation.

[0015] Preferably, the separation method in step (2) includes membrane separation and / or column chromatography.

[0016] Preferably, step (3) A x B x A y and B y The screening methods include: matching A1 with B1, A2 with B2, A3 with B3…A n With B n Comparative evaluation was conducted to identify component A, which represents the style characteristics of tobacco leaves from this production area. x1 and B x1 And component A, which has the worst sensory quality. y1 and B y1 Then, through component substitution and deletion experiments, the component A with the best sensory quality was determined. x and B x The worst component A y and B y .

[0017] Preferably, the component substitution and deletion experiment includes: recombining the components of inferior tobacco leaves and removing B. y1 To verify whether B has a negative effect on sensory quality y1 ; after removing B y1 Based on this, use A x1 Replace B x1 To verify A x1 Whether it is the component with the best sensory quality in tobacco leaves.

[0018] Preferably, the chemical analysis method in step (4) includes any one or a combination of at least two of the following: non-targeted or targeted gas chromatography-mass spectrometry (GC / MS), solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC / MS), or liquid chromatography-mass spectrometry (LC / MS).

[0019] Preferably, the chemical analysis data in step (4) includes any one or a combination of at least two of the following: mass-to-nucleus ratio, retention time, or peak area.

[0020] Preferably, the method for difference analysis in step (4) includes single-index comparison method and / or multivariate statistical method, preferably any one or a combination of at least two of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), one-factor correlation analysis or two-factor correlation analysis.

[0021] Preferably, the screening method for key factors of tobacco leaf sensory quality in step (4) includes: screening A... x With B x A y With B yPerform discriminant analysis to extract variables with VIP>1 in the two groups, and screen for common variables between the two groups; calculate the common variables in A. x With B x The ratio of the relative contents (FC) in the samples was used to screen common variables with FC ≥ 10, thereby obtaining the key factors of the sensory quality of tobacco leaves; the group discriminant analysis method included partial least squares discriminant analysis or orthogonal partial least squares discriminant analysis.

[0022] Secondly, the present invention provides a method for screening key factors of tobacco sensory quality according to the first aspect, which is applied in tobacco cultivation, processing, or tobacco flavoring.

[0023] Compared with the prior art, the present invention has at least the following beneficial effects:

[0024] The method for screening key factors of tobacco sensory quality provided by this invention is based on the research idea of ​​sensory omics. It can accurately identify key groups that affect the smoking quality of tobacco leaves, and thus effectively determine the chemical components that affect the sensory quality of tobacco leaves, providing guidance for tobacco planting, processing, and flavoring. Attached Figure Description

[0025] Figure 1 This is a bar chart showing the sensory evaluation of the recombinant samples. Detailed Implementation

[0026] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments. However, the following examples are merely simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention is determined by the claims.

[0027] Example 1

[0028] Sensory evaluations were conducted on C3F tobacco leaves 220 and 218 from the central part of Lushi County, Sanmenxia City, western Henan Province, referring to YC / T497-2014. The sensory evaluation results of the two tobacco leaves are shown in Table 1. The evaluation results show that, in terms of quality characteristics, sample 220 is superior to sample 218 in terms of aroma quality, aroma intensity, off-odors, irritation, and aftertaste, while sample 218 has a stronger flavor than sample 220. In terms of industrial usability, sample 220 scored 8 points, while sample 218 scored 6.5 points. In terms of aroma characteristics, sample 220 has stronger hay, caramel, and mellow sweet aromas than sample 218, while sample 218 has a significantly stronger caramel aroma than sample 220.

[0029] Table 1

[0030]

[0031] Solvent extraction: 20 g of tobacco leaves 220 and 218 were crushed and transferred to round-bottom flasks. Water was added at a material-to-liquid ratio of 1:10, and the mixture was heated to 80°C for 3 h. After the experiment, the residue and extract were separated by filtration. The extract was concentrated under reduced pressure to a paste to obtain two tobacco extracts (L220-2 and L218-2).

[0032] Gel column chromatography: 5g of tobacco extract was separated by gel permeation chromatography, and the starting and ending points of the collected fractions were monitored using a UV detector. The separation conditions were: mobile phase: ethanol; packing material: Sephadex LH-20 dextran gel; flow rate: 3mL / min; one fraction was collected every 8mL using a collector, for a total of 90 fractions. The fractions were combined and compared. Referring to YC / T 497-2014, the sensory evaluation results of the gel-separated components are shown in Table 2.

[0033] Table 2

[0034]

[0035] After preliminary evaluation, the components with the best sensory quality (L220-2-⑨ and L218-2-⑩, L220-2-⑥ and L218-2-⑦) and the worst sensory quality (L220-2-② and L218-2-③, L218-2-⑧ and L220-2-⑦, L218-2-) were selected. and L220-2- ).

[0036] The recombined components of L218-2 are designated as component A. Based on component A, L218-2-③ is removed to form component B. Based on component B, L220-2-⑨ replaces L218-2-⑩ to form component C. The sensory evaluation bar chart of the recombined samples of the three components is shown below. Figure 1 As shown. Through deletion and substitution experiments, the components with the best sensory quality were identified as L220-2-⑨ and L218-2-⑩, while the components with the worst sensory quality were identified as L220-2-② and L218-2-③.

[0037] Two groups of samples (L220-2-⑨ and L218-2-⑩, L220-2-② and L218-2-③) were analyzed by HPLC / MS. Peak identification, peak filtering, and peak alignment were performed on the raw data to obtain a data matrix containing information such as mass-to-mass ratio, retention time, and peak area. A total of 16,939 data points were obtained from the four samples. Partial least squares discriminant analysis (PLS-DA) was used to group and discriminate between L220-2-⑨ and L218-2-⑩, and L220-2-⑨ and L218-2-③, respectively. Important variables with VIP>1 were extracted under the two models, yielding 4,476 and 4,650 variables respectively, for a total of 3,766 variables. Further, based on the relative content ratio (FC) of 3766 variables in L220-2-⑨ and L218-2-⑩, 58 variables with FC>10 were screened. The relevant information of key sensory quality factors is shown in Table 3 ("-" indicates that they were not detected in L218-2-⑩).

[0038] Table 3

[0039]

[0040] Using some of the substances listed in Table 3 as representatives for verification, the key factors affecting the sensory quality of tobacco leaves were further identified through comparison with standard samples and quantitative analysis. The results of the content analysis of key sensory quality factors in the two types of tobacco leaves are shown in Table 4. The content of six substances, including dihydro-β-ionone, was higher in the 220 tobacco leaf than in the 218 tobacco leaf. The above research process shows that this method can accurately identify the key factors of tobacco leaf sensory quality, which is helpful for the objective evaluation of tobacco leaf quality.

[0041] Table 4

[0042]

[0043] The applicant declares that the above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the protection and disclosure scope of the present invention.

Claims

1. A method for screening key factors of tobacco leaf sensory quality, characterized in that, The screening method includes the following steps: (1) Sensory evaluation of tobacco leaves of the same variety from the same production area was conducted to identify high-quality and low-quality tobacco leaves; (2) Extract and separate high-quality tobacco leaves and low-quality tobacco leaves respectively to obtain several separated fractions of high-quality tobacco leaves and low-quality tobacco leaves; (3) Sensory evaluation of several separated fractions of high-quality and low-quality tobacco leaves was conducted, and fractions with the same function were grouped together to obtain the components A1-A of high-quality tobacco leaves. n Component B1-B of inferior tobacco leaves n Component A with the best sensory quality was selected through screening. x and B x The worst component A y and B y ; (4) For A x B x A y and B y Chemical analysis was performed, and the chemical analysis data was used to analyze A. x With B x A y With B y Differential analysis was conducted to screen for chemically significant differences, thereby identifying key factors affecting the sensory quality of tobacco leaves.

2. The screening method according to claim 1, characterized in that, The types of tobacco leaves mentioned in step (1) include flue-cured tobacco, aromatic tobacco, burley tobacco, or sun-cured tobacco.

3. The screening method according to claim 1 or 2, characterized in that, In step (1), the high-quality tobacco leaves refer to tobacco leaves that embody the typical style characteristics of the tobacco variety, while the low-quality tobacco leaves refer to tobacco leaves that embody the defects of the tobacco variety. The difference in the sensory evaluation index scores between the high-quality tobacco leaves and the low-quality tobacco leaves is the greatest.

4. The screening method according to any one of claims 1-3, characterized in that, The extraction method described in step (2) includes any one or a combination of at least two of the following: solvent extraction, subcritical extraction, supercritical extraction, molecular distillation, or steam distillation; Preferably, the separation method in step (2) includes membrane separation and / or column chromatography.

5. The screening method according to any one of claims 1-4, characterized in that, Step (3) A x B x A y and B y The screening methods include: matching A1 with B1, A2 with B2, A3 with B3…A n With B n Comparative evaluation was conducted to identify component A, which represents the style characteristics of tobacco leaves from this production area. x1 and B x1 And component A, which has the worst sensory quality. y1 and B y1 Then, through component substitution and deletion experiments, the component A with the best sensory quality was determined. x and B x The worst component A y and B y .

6. The screening method according to claim 5, characterized in that, The component substitution and deletion experiments included: recombining the components of inferior tobacco leaves and removing B. y1 To verify whether B has a negative effect on sensory quality y1 ; after removing B y1 Based on this, use A x1 Replace B x1 To verify A x1 Whether it is the component with the best sensory quality in tobacco leaves.

7. The screening method according to any one of claims 1-6, characterized in that, The chemical analysis method described in step (4) includes any one or a combination of at least two of the following: non-targeted or targeted gas chromatography-mass spectrometry, solid-phase microextraction-gas chromatography-mass spectrometry, or liquid chromatography-mass spectrometry. Preferably, the chemical analysis data in step (4) includes any one or a combination of at least two of the following: mass-to-nucleus ratio, retention time, or peak area.

8. The screening method according to any one of claims 1-7, characterized in that, The method for difference analysis in step (4) includes single-index comparison method and / or multivariate statistical method, preferably any one or a combination of at least two of principal component analysis, partial least squares discriminant analysis, orthogonal partial least squares discriminant analysis, single factor correlation analysis or two factor correlation analysis.

9. The screening method according to claim 8, characterized in that, The screening method for key factors of tobacco leaf sensory quality in step (4) includes: screening A... x With B x A y With B y Perform a group discriminant analysis, extract variables with VIP>1 under the two groups, and screen for common variables between the two groups; calculate the common variables in A. x With B x The ratio of the relative contents (FC) in the samples was used to screen common variables with FC ≥ 10, thereby obtaining the key factors of the sensory quality of tobacco leaves; the group discriminant analysis method included partial least squares discriminant analysis or orthogonal partial least squares discriminant analysis.

10. The application of a method for screening key factors of tobacco sensory quality according to any one of claims 1-9 in tobacco cultivation, processing, or flavoring.

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