CN102901779B - Discrimination method for caramel sweet taste characteristics of tobacco leaf based on flavor components - Google Patents
Discrimination method for caramel sweet taste characteristics of tobacco leaf based on flavor components Download PDFInfo
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- CN102901779B CN102901779B CN201210337233.1A CN201210337233A CN102901779B CN 102901779 B CN102901779 B CN 102901779B CN 201210337233 A CN201210337233 A CN 201210337233A CN 102901779 B CN102901779 B CN 102901779B
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Abstract
The invention provides a discrimination method for caramel sweet taste characteristics of a tobacco leaf based on flavor components. The discrimination method is characterized by comprising the following steps: (1) establishment of a sample database of tobacco leaves with caramel sweet taste characteristics; (2) artificial discrimination of the caramel sweet taste characteristics; (3) establishment of a flavor component database of the tobacco leaves with the caramel sweet taste characteristics; (4) screening of flavor component characterization indexes of the tobacco leaves with the caramel sweet taste characteristics; (5) establishment of a model for discrimination of the caramel sweet taste characteristics by using the flavor components of the tobacco leaves; (6) testing of the model; (7) determination of flavor components of an unknown sample; and (8) discrimination of caramel sweet taste characteristics of the unknown sample. The invention has the following advantages: the model for discrimination of caramel sweet taste characteristics based on flavor components is established, the problems of subjectivity and nondeterminacy of determination which is carried out mainly through subjective recognition of a smoke panel in the prior art are overcome, and scientificalness, objectivity and accuracy of determination of taste characteristics are improved.
Description
Technical field
The present invention relates to the composition measurement of tobacco leaf fragrance, specifically the method for discrimination of the burnt sweet sense mouthfeel feature of a kind of tobacco leaf based on flavor component.
Background technology
The style characteristic of the burnt sweet sense mouthfeel feature centering type cigarette of tobacco leaf plays an important role.Mainly rely on sensory evaluating smoking expert to smoke panel test manually to judge to tobacco sample to the method for the burnt sweet sense mouthfeel feature of raw tobacco material at present, this method depends on the personnel's that smoke panel test Subjective, inevitably have certain subjectivity and uncertainty, the processing scheme of formulating differentiation according to raw tobacco material characteristic to cigarette enterprise brings certain difficulty.
Form because the sweet sense mouthfeel of Jiao feature of tobacco leaf has multiple fragrance composition synergy, this provides theoretical foundation for utilizing flavor component to differentiate tobacco leaf odor type type.A kind of mathematical model of utilizing flavor component to build that the present invention sets up based on this mechanism is just judged the method for the burnt sweet sense mouthfeel feature of tobacco leaf.
Summary of the invention
The method of discrimination of the burnt sweet sense mouthfeel feature of a kind of tobacco leaf based on flavor component that object of the present invention provides in order to overcome the subjective impairment of the burnt sweet sense feature assessment method existence of above-mentioned existing tobacco leaf just.
The object of the invention is to be achieved through the following technical solutions:
The method of discrimination of the burnt sweet sense mouthfeel feature of the tobacco leaf based on flavor component of the present invention comprises the following steps:
1.the foundation in burnt sweet sense mouthfeel feature tobacco sample storehouse.Choose 60 of C3F grade Luzhou-flavor tobacco samples, roll, set up burnt sweet sense mouthfeel feature tobacco sample storehouse.
2.the artificial cognition of burnt sweet sense mouthfeel feature.Sample in the tobacco sample storehouse that step 1 is formed, organizes the expert that smokes panel test, and utilizes scaling law to differentiate its burnt sweet sense mouthfeel feature, completes the artificial cognition of the burnt sweet sense mouthfeel feature of these samples.
3.the foundation in burnt sweet sense mouthfeel feature tobacco leaf fragrance compositional data storehouse.The tobacco sample storehouse that step 1 is formed, adopts distillation extraction method simultaneously.Take offal 20.0g and be placed in 1000ml flat bottom flask, add 350ml distilled water, 90g sodium chloride, flask is placed in to the left side of distillation extraction instrument simultaneously, then in 100ml flat bottom flask, add 45ml methylene chloride, be placed in the right side of distillation extraction instrument simultaneously, after water boiling to be distilled, carry out while distillation extraction 2h, dichloromethane extraction to experiment gained adds 9g anhydrous sodium sulfate in mutually, and dried overnight.Dried extract is transferred in concentrated bottle and is concentrated into 1ml, add mark phenethyl acetate in 10 μ l, be GC/MS analytic liquid.Adopt gas chromatography-mass spectrum (GC/MS) combined instrument to measure.Gas chromatograph is AT-7890A type, and mass spectrometer is AT-5975C type.GC condition: capillary column is that (50m × 0.2mm × 0.33 μ m) for HP-ULTRA2; 280 DEG C of injector temperatures; Split ratio 10:1; Sample size 1.0 μ l; Heating schedule: 60 DEG C of initial temperature, keep 1min, 2 DEG C/min is warmed up to 280 DEG C, and 280 DEG C keep 20min.MS condition: 230 DEG C of ion source temperatures; 150 DEG C of quadrupole rod temperature, select ion detection.Flavor matter is qualitative: qualitative by GC/MS qualification result and Wiley library searching.Flavor matter is quantitative: adopt inner mark method ration.Utilize GC-MS to its Main Fragrance (furfural, furfuryl alcohol, 5 methyl furfural, benzaldehyde, 6-methyl-5-hepten-2-one, phenmethylol, phenylacetaldehyde, linalool, bata-phenethyl alcohol, isophorone, oxidation isophorone, dorinone, β-damascone, farnesyl acetone, geranyl acetone, alpha, beta-lonone, 2-acetyl furan, solanone, dihydroactinidiolide, Megastigmatrienone A, Megastigmatrienone B, Megastigmatrienone C, Megastigmatrienone D, 6, 10, 14-trimethyl-2-15 ketone) measure, set up burnt sweet sense mouthfeel feature tobacco leaf fragrance compositional data storehouse.
4.the screening of the flavor component characteristic index of burnt sweet sense mouthfeel feature tobacco leaf.Flavor component index and burnt sweet sense mouthfeel feature are carried out successive Regression, introduce according to the principle of p<0.05, and selected flavor component is respectively furfural, 5 methyl furfural, 2-acetyl furan, geranyl acetone.
5.utilize tobacco leaf flavor component to differentiate the foundation of burnt sweet sense mouthfeel feature.Choose at random 40 tobacco sample data as modeling data collection, utilize support vector machine regression model to simulate the quantitative relationship of four kinds of characteristic indexs and the burnt sweet sense mouthfeel feature of tobacco leaf, set up the discrimination model of the burnt sweet sense mouthfeel feature of tobacco leaf based on flavor component, model parameter is as follows: the type that support vector machine returns is EPSILON-SVR, kernel function type is RBF, Degree=3, Gamma=0.5, Coef0=0.001, Eps=0.001, C=1, nu=0.5, shrinking=1, p=0.01, probability=1.
6.the inspection of model.20 tobacco sample data definitions outside modeling data is integrated are as check data collection.Utilize the sweet sense mouthfeel of Jiao feature discrimination model of setting up in step 2 to predict the sweet sense mouthfeel of Jiao feature of check data collection (n=20), draw the scatter diagram of measured value and predicted value, and related coefficient, the coefficient of determination and the average relative error of predicted value and measured value are calculated.Hence one can see that, and between the predicted value of model and measured value, related coefficient is 0.9048, and the coefficient of determination is 0.8996, average relative error 9.01%.
7.the mensuration of unknown sample flavor component.Utilize describing method in step 3 to measure the flavor component of unknown sample.
8.the differentiation of the burnt sweet sense mouthfeel feature of unknown sample.To in step 7, obtain unknown sample flavor component substitution model, Output rusults, completes the differentiation of the sweet sense mouthfeel of Jiao feature of unknown sample.
The invention has the advantages that: the discrimination model of having set up the burnt sweet sense mouthfeel feature of tobacco leaf based on flavor component, for the judgement of the burnt sweet sense mouthfeel feature of tobacco leaf provides objective, means accurately, overcome the Subjective that mainly depends on the personnel that smoke panel test in prior art and judged existing subjectivity and uncertainty, improved science, objectivity and accuracy that mouthfeel feature is judged.
Embodiment
Below in conjunction with instantiation, the present invention will be further described:
Embodiment 1
1 part of C3F grade tobacco sample, detects through GC-MS, and its furfural, 5 methyl furfural, 2-acetyl furan, geranyl acetone content are respectively 36.13 μ g/g, 5.06 μ g/g, 3.30 μ g/g, 30.65 μ g/g, bring model into, show that its burnt sweet sense mouthfeel feature must be divided into 59.Smoke panel test through expert, its actual burnt sweet sense mouthfeel feature must be divided into 52, and relative error rate is 13.46%.
Embodiment 2
1 part of C3F grade tobacco sample, detects through GC-MS, and its furfural, 5 methyl furfural, 2-acetyl furan, geranyl acetone content are respectively 61.55 μ g/g, 3.05 μ g/g, 5.76 μ g/g, 14.38 μ g/g, bring model into, show that its burnt sweet sense mouthfeel feature must be divided into 76.Smoke panel test through expert, its actual burnt sweet sense mouthfeel feature must be divided into 70, and relative error rate is 8.57%.
Embodiment 3
1 part of C3F grade tobacco sample, detects through GC-MS, and its furfural, 5 methyl furfural, 2-acetyl furan, geranyl acetone content are respectively 65.03 μ g/g, 4.92 μ g/g, 6.87 μ g/g, 12.07 μ g/g, bring model into, show that its burnt sweet sense mouthfeel feature must be divided into 79.Smoke panel test through expert, its actual burnt sweet sense mouthfeel feature highlights degree and must be divided into 85, and relative error rate is 7.06%.
Claims (3)
1. a method of discrimination for the burnt sweet sense mouthfeel feature of the tobacco leaf based on flavor component, is characterized in that: this method of discrimination comprises the following steps:
(1) foundation in burnt sweet sense mouthfeel feature tobacco sample storehouse, chooses 60 of C3F grade Luzhou-flavor tobacco samples, rolls, and sets up burnt sweet sense mouthfeel feature tobacco sample storehouse;
(2) artificial cognition of burnt sweet sense mouthfeel feature, sample in the tobacco sample storehouse that step 1 is formed, organizes the expert that smokes panel test, with reference to tobacco and tobacco product sensory evaluation method YC/T138-1998, carry out the sensory evaluation of burnt sweet sense mouthfeel feature, standards of grading are: the most typical 100～76; Typical case 75～51; Inferior typical 50～26; Be not true to type 25～1, complete the artificial cognition of the burnt sweet sense mouthfeel feature of these samples;
(3) foundation in burnt sweet sense mouthfeel feature tobacco leaf fragrance compositional data storehouse, the tobacco sample storehouse that step (1) is formed, adopts distillation extraction method simultaneously to extract each sample, adopts GC/MS to analyze mensuration to each sample extract, flavor matter is qualitative: qualitative by GC/MS qualification result and Wiley library searching, flavor matter is quantitative: adopt inner mark method ration, utilize GC/MS to its Main Fragrance: furfural, furfuryl alcohol, 5 methyl furfural, benzaldehyde, 6-methyl-5-hepten-2-one, phenmethylol, phenylacetaldehyde, linalool, bata-phenethyl alcohol, isophorone, oxidation isophorone, dorinone, β-damascone, farnesyl acetone, geranyl acetone, alpha, beta-lonone, 2-acetyl furan, solanone, dihydroactinidiolide, Megastigmatrienone A, Megastigmatrienone B, Megastigmatrienone C, Megastigmatrienone D, 6, 10, 14-trimethyl-2-15 ketone, measure, set up burnt sweet sense mouthfeel feature tobacco leaf fragrance compositional data storehouse,
(4) burnt sweet sense mouthfeel feature tobacco leaf fragrance component list is levied the screening of index, flavor component index and burnt sweet sense mouthfeel feature are carried out successive Regression, principle according to p<0.05 is introduced, and selected flavor component is respectively furfural, 5 methyl furfural, 2-acetyl furan, geranyl acetone;
(5) utilize tobacco leaf flavor component to differentiate the foundation of burnt sweet sense mouthfeel characteristic model, choose at random 40 tobacco sample data as modeling data collection, utilize support vector machine regression model to simulate the quantitative relationship of four kinds of characteristic indexs and the burnt sweet sense mouthfeel feature of tobacco leaf, set up the discrimination model of the burnt sweet sense mouthfeel feature of tobacco leaf based on flavor component, model parameter is as follows: the type that support vector machine returns is EPSILON-SVR, kernel function type is RBF, Degree=3, Gamma=0.5, Coef0=0.001, Eps=0.001, C=1, nu=0.5, shrinking=1, p=0.01, probability=1,
?
(6) inspection of model, 20 tobacco sample data definitions outside modeling data is integrated are as check data collection, utilize the sweet sense mouthfeel of Jiao feature discrimination model of setting up in step (5) to predict the sweet sense mouthfeel of Jiao feature of check data collection n=20, calculate predicted value average relative error, average relative error 9.01%;
(7) mensuration of unknown sample flavor component, utilizes describing method in step (3) to measure the flavor component of unknown sample;
(8) differentiation of the burnt sweet sense mouthfeel feature of unknown sample, will obtain unknown sample flavor component substitution model in step (7), and Output rusults, completes the differentiation of the sweet sense mouthfeel of Jiao feature of unknown sample.
2. the method for discrimination of the burnt sweet sense mouthfeel feature of the tobacco leaf based on flavor component according to claim 1, it is characterized in that: in step (3), adopt the concrete grammar that distillation extraction method extracts each sample to be simultaneously: to take offal 20.0g and be placed in 1000ml flat bottom flask, add 350ml distilled water, 90g sodium chloride, flask is placed in to the left side of distillation extraction instrument simultaneously, then in 100ml flat bottom flask, add 45ml methylene chloride, be placed in the right side of distillation extraction instrument simultaneously, after water boiling to be distilled, carry out while distillation extraction 2h, dichloromethane extraction to experiment gained adds 9g anhydrous sodium sulfate in mutually, and dried overnight, dried extract is transferred in concentrated bottle and is concentrated into 1ml, add mark phenethyl acetate in 10 μ l, be GC/MS sample extraction liquid.
3. the method for discrimination of the burnt sweet sense mouthfeel feature of the tobacco leaf based on flavor component according to claim 1, is characterized in that: in step (3), gas chromatograph used is AT-7890A type, and mass spectrometer is AT-5975C type; GC condition: capillary column is HP-ULTRA2 specification 50m × 0.2mm × 0.33 μ m; 280 DEG C of injector temperatures; Split ratio 10:1; Sample size 1.0 μ l; Heating schedule: 60 DEG C of initial temperature, keep 1min, 2 DEG C/min is warmed up to 280 DEG C, and 280 DEG C keep 20min; MS condition: 230 DEG C of ion source temperatures; 150 DEG C of quadrupole rod temperature, select ion monitoring.
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