CN106248619A - A kind of identify compounding flavoring essence kind and the method for deviation of concentration - Google Patents
A kind of identify compounding flavoring essence kind and the method for deviation of concentration Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000013329 compounding Methods 0.000 title claims abstract description 37
- 235000019504 cigarettes Nutrition 0.000 claims abstract description 9
- 150000001875 compounds Chemical class 0.000 claims abstract description 9
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 claims description 56
- 235000002637 Nicotiana tabacum Nutrition 0.000 claims description 25
- 241000208125 Nicotiana Species 0.000 claims description 18
- 239000000203 mixture Substances 0.000 claims description 18
- 238000001514 detection method Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 238000004611 spectroscopical analysis Methods 0.000 claims description 9
- 239000002904 solvent Substances 0.000 claims description 6
- 239000004615 ingredient Substances 0.000 claims 2
- 239000002304 perfume Substances 0.000 claims 2
- 230000000694 effects Effects 0.000 abstract description 7
- 238000004519 manufacturing process Methods 0.000 abstract description 3
- 239000000686 essence Substances 0.000 description 94
- 239000000523 sample Substances 0.000 description 79
- 239000000796 flavoring agent Substances 0.000 description 16
- 235000019634 flavors Nutrition 0.000 description 15
- 235000009508 confectionery Nutrition 0.000 description 12
- 239000012470 diluted sample Substances 0.000 description 8
- 239000012488 sample solution Substances 0.000 description 8
- 238000012360 testing method Methods 0.000 description 8
- 244000061176 Nicotiana tabacum Species 0.000 description 7
- 238000001228 spectrum Methods 0.000 description 7
- 238000007689 inspection Methods 0.000 description 6
- 239000003814 drug Substances 0.000 description 4
- 239000000284 extract Substances 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000001035 drying Methods 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 230000035945 sensitivity Effects 0.000 description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 238000005303 weighing Methods 0.000 description 3
- 239000002253 acid Substances 0.000 description 2
- 239000003153 chemical reaction reagent Substances 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 239000006071 cream Substances 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 235000019990 fruit wine Nutrition 0.000 description 2
- 238000004454 trace mineral analysis Methods 0.000 description 2
- 244000099147 Ananas comosus Species 0.000 description 1
- 235000007119 Ananas comosus Nutrition 0.000 description 1
- 241000628997 Flos Species 0.000 description 1
- 235000016623 Fragaria vesca Nutrition 0.000 description 1
- 240000009088 Fragaria x ananassa Species 0.000 description 1
- 235000011363 Fragaria x ananassa Nutrition 0.000 description 1
- 235000015511 Liquidambar orientalis Nutrition 0.000 description 1
- 239000004870 Styrax Substances 0.000 description 1
- 244000028419 Styrax benzoin Species 0.000 description 1
- 235000000126 Styrax benzoin Nutrition 0.000 description 1
- 244000299461 Theobroma cacao Species 0.000 description 1
- 235000005764 Theobroma cacao ssp. cacao Nutrition 0.000 description 1
- 235000005767 Theobroma cacao ssp. sphaerocarpum Nutrition 0.000 description 1
- 150000007513 acids Chemical class 0.000 description 1
- 150000001298 alcohols Chemical class 0.000 description 1
- 235000001046 cacaotero Nutrition 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000011208 chromatographic data Methods 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000001976 improved effect Effects 0.000 description 1
- 150000002632 lipids Chemical class 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 150000002989 phenols Chemical class 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 210000000582 semen Anatomy 0.000 description 1
- 241000894007 species Species 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 238000002235 transmission spectroscopy Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing liquids, e.g. polluted water
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- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The present invention is a kind of identifies compounding flavoring essence kind and the method for deviation of concentration.Described method is capable of identify that the kind of compounding flavoring essence, the sensitive identification of energy simultaneously compounds the deviation of concentration degree of flavoring essence and standard sample, and for polytype compounding flavoring essence, all there is good prediction effect, quickly identifying and the degree of deviation of concentration compounding flavoring essence kind can be realized, production of cigarettes is significant.
Description
Technical field
The present invention relates to Analysis of Tobacco Flavor field, compound flavoring essence kind and dense more particularly, to one identification
The method of degree deviation.
Background technology
In order to enrich the taste of Medicated cigarette, essence can added during production of cigarettes.Essence is according to the applying added
Technique is different, can be divided into two kinds, and the first kind is added in charging technology, and this kind of essence adds to after generally mixing with water
In Nicotiana tabacum L., blade absorbs rapidly feed liquid, improves leaf water content and also improves quality of tobacco, through putting down of leaf storing cabinet more than 2 hours
After weighing apparatus, carry out getting damp again, shredding and drying process, and reduce moisture content by cut tobacco drying, reach water balance;Equations of The Second Kind be
Perfuming process adds, and this kind of essence adds the tobacco shred through drying with volatile solvent (usually ethanol) to after generally mixing
In, and no longer carry out the removal process of solvent.In actual production, find that composition or the slight change of concentration all may
Tobacco shred taste is improved effect significantly affect, therefore it is required that strictly control the composition of every batch and the consistent of concentration
Property.But existing to composition and the control of concentration, or rely on and manually carry out being main, lack the quick knowledge of a kind of science
Other method;Having in prior art and detect from by indexs such as indexs of refraction, but the suitability of these indexs is limited, it is right to fail to realize
Kind and the concentration of essence accurately detect.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, it is provided that a kind of identification compounds flavoring essence kind and concentration
The method of deviation.Testing through great many of experiments, the method can identify rapidly compounding flavoring essence kind, and can differentiate multiple delicately
With addition of essence, concentration with standard sample deviates.
The above-mentioned purpose of the present invention is achieved by following technical solution:
A kind of identify compounding flavoring essence kind and the method for deviation of concentration, comprise the steps:
S1. compounding flavoring essence sample to be measured is carried out near infrared detection, it is thus achieved that near-infrared all band spectroscopic data;
S2. S1. gained all band spectroscopic data is carried out data process:
Choose 9000 ~ 7300cm-1Wavelength band data, and carry out second dervative process;
S3. the data after processing according to S2. compare with the data of the standard sample of setting, it determines treat that test sample compounds perfuming fragrant
The kind of fine work;And the compounding flavoring essence sample data to be measured mahalanobis distance with corresponding standard sample data that converts, it determines
The concentration of compounding flavoring essence sample to be measured and the difference degree of normal concentration sample concentration;
S2., in, light path type is fixing;
Described compounding flavoring essence includes that flavouring essence for tobacco composition and solvent composition, described solvent are ethanol.NIR transmittance spectroscopy
Owing to more data message can be gathered, have in the quality control having been reported for flavouring essence for tobacco.But existing method
For single flavouring essence for tobacco, and all band chromatographic data can only be used.But inventor finds, for compounding essence, by
In for multiple flavor compound, the more single essence of its aroma component is more complicated, if using full wave former establishment of spectrum model, and one
Aspect is due to the highly polar O-as contained by the materials such as alcohols, phenols, acids of the aroma component in O-H key and the essence of ethanol molecule
H key easily causes spectra overlapping, and the spectra overlapping that on the other hand complex system self causes makes the spectrum at these wavelength believe
The measurement selectivity of breath is poor.Therefore compound essence the more single essence of species detecting difficulty distinguish that difficulty is bigger.Further, right
For producing, the kind of the compounding essence used by the medicated cigarette of different brands may be different, it is therefore desirable to the method pair set up
Multiple different types of compounding essence all have the suitability.If but using full wave former establishment of spectrum model, variety classes
The principal component scores of compounding essence have the phenomenon of overlap, it is seen that use full wave former establishment of spectrum model distinguishes that effect is very
Undesirable, even if using derivative processing, variety classes can not be compounded essence and effectively distinguishing.
Extract and absorb less subband 9000 ~ 7300cm-1When being modeled, with kind cigarette with compounding flavoring essence
Principal component scores more disperses, and variety classes cigarette does not has obvious distance with compounding flavoring essence, it is impossible to by variety classes cigarette
Effectively distinguish with compounding flavoring essence.
Inventor finds, when selecting to absorb less subband 9000 ~ 7300cm simultaneously-1And second dervative process
When spectrum is modeled, the principal component scores distribution Relatively centralized of sample of the same race, the principal component scores of different samples has substantially
Distance.Therefore, by spectroscopic data is reasonably processed, the model with higher recognition effect can be set up.If
These test sample data are carried out first derivative process, good recognition effect can not be obtained.
Recognition effect is had an impact by light path type, uses the light path type under fixed model, it is possible to obtain higher identification
Effect.
It addition, the method that prior art also has the mahalanobis distance judgement sample concentration change calculated by detection method,
It is the biggest that the intensity of variation of mahalanobis distance is affected change by sample type.For a certain sample, possible mahalanobis distance changes the most greatly,
And for another sample, mahalanobis distance varies less, i.e. for different samples, discrimination (sensitivity) there may be bright
Significant difference is different.And by some conventional compounding flavoring essence samples of this area are tested repeatedly, it is found that said method pair
In conventional compounding flavoring essence sample, all there is higher discrimination, i.e. sample concentration deviation is identified there is high sensitivity.
The condition of described near infrared detection is referred to the existing testing conditions to flavouring essence for tobacco.That is, described near-infrared inspection
The condition surveyed is: gather wave-number range 10000 ~ 4000cm-1, fixing light path, with the built-in background of instrument as reference, sample and reference
All use 32 scanning, resolution 8cm-1。
Described flavouring essence for tobacco composition is by mixed for two or more essence flavouring essence for tobacco composition.
Preferably, described flavouring essence for tobacco composition is by two kinds of essence mixed flavouring essence for tobacco compositions.
Normally, described flavouring essence for tobacco composition accounts for 8 ~ 15 % of compounding flavoring essence weight.
Compared with prior art, the invention have the advantages that
Method disclosed by the invention can quickly identify the kind of compounding flavoring essence, in addition to qualitative analysis, moreover it is possible to sensitive distinguishes
Do not compound the deviation of concentration degree of flavoring essence sample and standard sample, and the suitability is wide, to multiple compounding flavoring essence, all
There is good prediction effect, in realizing producing, compounding flavoring essence is accurately identified.
Accompanying drawing explanation
Fig. 1 embodiment 1 uses (10000 ~ 4000) cm-1Scope, the main constituent of the data modeling not carrying out derivative processing obtains
Component.
Fig. 2 embodiment 1 uses (10000 ~ 4000) cm-1Scope, the principal component scores of the data modeling that first derivative processes
Figure.
Fig. 3 embodiment 1 uses (10000 ~ 4000) cm-1Scope, the principal component scores of the data modeling that second dervative processes
Figure.
Fig. 4 embodiment 1 uses (6200 ~ 5500) cm-1Scope, does not carries out the principal component scores of the data modeling of derivative processing
Figure.
Fig. 5 embodiment 1 uses (6200 ~ 5500) cm-1Scope, the principal component scores of the data modeling that first derivative processes
Figure.
Fig. 6 embodiment 1 uses (6200 ~ 5500) cm-1Scope, the principal component scores of the data modeling that second dervative processes
Figure.
Fig. 7 embodiment 1 uses (9000 ~ 7200) cm-1Scope, does not carries out the principal component scores of the data modeling of derivative processing
Figure.
Fig. 8 embodiment 1 uses (9000 ~ 7200) cm-1Scope, the principal component scores of the data modeling that first derivative processes
Figure.
Fig. 9 embodiment 1 uses (9000 ~ 7200) cm-1Scope, the principal component scores of the data modeling that second dervative processes
Figure.
Detailed description of the invention
The present invention is further described below in conjunction with specific embodiment.Unless stated otherwise, the present invention use reagent,
Equipment and method are the art conventional commercial reagent, equipment and conventional use of method.Essence used in embodiment
It is commercially available essence.
Select conventional more representational 8 kinds of compounding flavoring essences as standard sample, specific as follows:
The standard sample of sample 1: fresh and sweet type essence, sour odor type essence and ethanol are by 2%, 8%, 90% part by weight mixing.Described clearly
Sweet type essence is that Cortex Cinnamomi extracts essence, and described sour odor type essence is the strawberry essence that meta-acid is fragrant.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 90.5%, 91%, 91.5%, 92% respectively.)
The standard sample of sample 2: burnt sweet type essence, Soysauce-like essence and ethanol are by 3%, 6%, 91% part by weight mixing.Described Jiao
Sweet type essence is partially to bakee fragrant cacao essence, and described Soysauce-like essence is paste flavor essence.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 91.45%, 91.9%, 92.35%, 92.8% respectively.)
The standard sample of sample 3: the sweetest type essence, bouquet type composition and ethanol are by 10%, 5%, 85% part by weight mixing.Described
The sweetest type essence is flavoring pineapple essence, and described bouquet type composition is Flos Rosae Rugosae orange blossom essence.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 85.75%, 86.5%, 87.25%, 88% respectively.)
The standard sample of sample 4: cream sweet type essence, Nicotiana tabacum L. flavor essence and ethanol are by 4%, 6%, 90% part by weight mixing.Described
Cream sweet type essence is Styrax lipid essence, and described Nicotiana tabacum L. flavor essence is Zimbabwe's tobacco extract.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 90.5%, 91%, 91.5%, 92% respectively.)
The standard sample of sample 5: burnt sweet type essence, nut flavor essence and ethanol are by 6%, 2%, 92% part by weight mixing.Described
Burnt sweet type essence is the Fructus Hordei Germinatus essence that defocusing is fragrant and sweet, and described nut flavor essence is the Semen coryli heterophyllae essence that baking is fragrant partially.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 92.4%, 92.8%, 93.2%, 93.6% respectively.)
The standard sample of sample 6: medicine flavor essence, spicy essence and ethanol are by 2%, 8%, 90% part by weight mixing.Described medicine
Flavor essence is Ilicis Purpureae flavor essence, and described spicy essence is Oleum Ocimi Gratissimi.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 90.5%, 91%, 91.5%, 92% respectively.)
The standard sample of sample 7: Nicotiana tabacum L. flavor essence, sweet flavor essence and ethanol are by 9%, 6%, 85% part by weight mixing.Described
Nicotiana tabacum L. flavor essence is Zimbabwe's tobacco extract, and described sweet flavor essence is Radix Glycyrrhizae extractum.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 85.75%, 86.5%, 87.25%, 88% respectively.)
The standard sample of sample 8: medicine sweet type essence, fruit wine flavor essence and ethanol are by 5%, 3%, 92% part by weight mixing.Described
Medicine sweet type essence is Herba thymi vulgaris extractum, and described fruit wine flavor essence is the tropical fruit (tree) essence of inclined aroma.
It addition, add ethanol in above-mentioned standard sample again, it is original 95%, 90%, 85%, 80% by above-mentioned diluted sample
Concentration (i.e. correspond to prepare the deviation sample solution that ethanol weight ratio is 92.4%, 92.8%, 93.2%, 93.6% respectively.)
Embodiment a kind differentiates
S1. the standard sample of preparation said sample 1 ~ 8 each 5 respectively, each tension metrics sample uses index of refraction detection to confirm all
For qualified standard sample, carry out near infrared detection respectively, it is thus achieved that near-infrared all band spectroscopic data;
The condition of described near infrared detection is: gather wave-number range 10000 ~ 4000cm-1, fixing light path, with the built-in background of instrument
32 scanning, resolution 8cm is all used for reference, sample and reference-1。
S2. S1. gained all band spectroscopic data is carried out data process: set light path type as SNV, respectively to use
10000~4000 cm-1、9000~7300cm-1、6200~5500cm-1Wavelength band, and do not carry out derivative processing, carry out single order or
Second dervative processes;Being respectively established, and carry out internal inspection, modeling sample is continued to use in internal inspection.Totally 40 samples.Inspection
Result is as shown in table 1.
Fig. 1 ~ 9 reflect different-waveband scope respectively and whether carry out derivative processing, the impact on model construction.Fig. 1, figure
2 it can be seen that for use all band (10000 ~ 4000 cm-1) scope, regardless of whether carry out derivative processing, between balance sample
Score more disperse, therefore detection time, error rate is higher.
Fig. 4 ~ 5 it can be seen that for use (6200 ~ 5500 cm-1) scope, regardless of whether carry out derivative processing, balance sample
Between score the most more disperse, and overlap occurs between different sample, discrimination is little, therefore when detection, mistake
Rate is higher.From fig. 6, it can be seen that use (6200 ~ 5500 cm-1) scope, carry out second dervative process and have relatively good knot
Really, but for sample segment, balance sample score or not concentration, there is misjudgement risk.
Even if from figure 7 it can be seen that using (9000 ~ 7300 cm-1) scope, if not carrying out derivative processing, it balances sample
Between score the most more disperse.There is the risk of misjudgement.
From figure 8, it is seen that use (9000 ~ 7300 cm-1) scope, and process through first derivative, putting down of each sample
The score of weighing apparatus sample is concentrated very much, and differing greatly between various sample accurate may can carry out anticipation.
From fig. 9, it can be seen that use (9000 ~ 7300 cm-1) scope, and process through second dervative, putting down of each sample
The score of weighing apparatus sample is concentrated very much, and differ greatly (diversity ratio first derivative processes and becomes apparent from) between various sample, possibility can be relatively
Carry out anticipation accurately.
Table 1
Although from the point of view of internal inspection, (9000 ~ 7300cm-1) scope and (6200 ~ 5500cm-1) scope first derivative process
Process with second dervative and can pass through interior survey inspection, but from the point of view of the figure of model construction, the mould built under different condition
Type diversity is relatively big, therefore also needs to the accuracy combining actual prediction to verify model.
Embodiment 2
S1. 4 concentration of said sample 1 ~ 8 are carried out near infrared detection respectively, it is thus achieved that near-infrared all band spectroscopic data;
The condition of described near infrared detection is: gather wave-number range 10000 ~ 4000cm-1, fixing light path, with the built-in background of instrument
32 scanning, resolution 8cm is all used for reference, sample and reference-1。
S2. S1. gained all band spectroscopic data is carried out data process:
Choose 9000 ~ 7300cm-1Wavelength band data, set light path type as fixing, and carry out second dervative process;
S3. the data after processing according to S2. compare with the data of the standard sample of setting, it determines the kind of testing sample;
And the testing sample data mahalanobis distance with corresponding standard sample data that converts, it determines the concentration of testing sample and normal concentration
The difference degree of sample concentration;And calculate discrimination.The calculation of discrimination is:
Discrimination==80% dilute sample is from mahalanobis distance away from standard sample of mahalanobis distance/95% dilute sample of standard sample.
The testing result of deviation of concentration:
When selecting condition process described in embodiment 2, the discrimination of each deviation sample is as shown in table 2:
Table 2
Comparative example
Choose 6200 ~ 5500cm-1Wavelength band when using second dervative data to process, the discrimination of each deviation sample such as table 3
Shown in:
Table 3
From table 2 it can be seen that the compounding flavoring essence being re-dubbed for multiple different formulations, described recognition methods is respectively provided with good
Good discrimination.Even and if essence concentration occurs trickle change (about 0.5%), the most still can reflect that concentration is inclined delicately
From.From table 3 it can be seen that when the wavelength band chosen is not in scope of the present invention, declining substantially occurs in sensitivity.
Application examples:
Utilizing the near-infrared analysis model set up, trace analysis produces totally 62, the compounding flavoring essence sample of preparation, fortune
Carrying out double happiness brand with qualitative discrimination model and compound the specification identification of flavoring essence, the judgement of specification matching degree, each sample is passed through
Refractive power Density Detection value all confirms as qualified samples (actual preparation qualified samples tolerance 1%, i.e. such as the concentration of standard sample
It is 100%, then in the range of the 99 ~ 101% of this concentration, all can determine that as qualified samples), the model that different methods builds
Result of determination is as shown in table 4.From table 4, it can be seen that only at (9000 ~ 7300cm-1) scope, and data are carried out at second dervative
The model that reason is set up, can be only achieved the predictablity rate of 100%.The near-infrared analysis model demonstrating present invention structure can be in reality
Border is persistently applied in producing, and supplementing as conventional refractive power Density Detection means.
Table 4 near-infrared trace analysis compounds flavoring essence
Claims (4)
1. one kind identifies compounding flavoring essence kind and the method for deviation of concentration, it is characterised in that comprise the steps:
S1. compounding flavoring essence sample to be measured is carried out near infrared detection, it is thus achieved that near-infrared all band spectroscopic data;
S2. S1. gained all band spectroscopic data is carried out data process:
Choose 9000 ~ 7300cm-1Wavelength band data, and carry out second dervative process;
S3. the data after processing according to S2. compare with the data of the standard sample of setting, it determines compounding flavoring essence to be measured
The kind of sample;And the compounding flavoring essence sample data to be measured mahalanobis distance with corresponding standard sample data that converts, it determines
The concentration of compounding flavoring essence sample to be measured and the difference degree of normal concentration sample concentration;
S2., in, light path type is fixing;
Described compounding flavoring essence includes that flavouring essence for tobacco composition and solvent composition, described solvent are ethanol.
Identify compounding flavoring essence kind and the method for deviation of concentration the most according to claim 1, it is characterised in that described cigarette
It is by mixed for two or more essence flavouring essence for tobacco composition with perfume ingredient.
Identification the most according to claim 1 or claim 2 compounds the method for flavoring essence kind and deviation of concentration, it is characterised in that institute
State flavouring essence for tobacco composition for by two kinds of essence mixed flavouring essence for tobacco compositions.
Identify compounding flavoring essence kind and the method for deviation of concentration the most according to claim 1, it is characterised in that described cigarette
8 ~ 15 % of compounding flavoring essence weight are accounted for perfume ingredient.
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CN113281291A (en) * | 2021-05-14 | 2021-08-20 | 深圳市八六三新材料技术有限责任公司 | Method and device for analyzing components of essence and computer readable storage medium |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101393114A (en) * | 2008-10-21 | 2009-03-25 | 龙岩烟草工业有限责任公司 | Rapid measuring method for physical property of flavouring essences for tobacco |
CN101929950A (en) * | 2010-08-24 | 2010-12-29 | 聚光科技(杭州)股份有限公司 | Method and device for monitoring glycolonitrile preparation technology in real time |
CN102566533A (en) * | 2011-11-25 | 2012-07-11 | 福建中烟工业有限责任公司 | On-line monitoring device and method for preparing tobacco essence perfume |
CN102778442A (en) * | 2012-08-08 | 2012-11-14 | 福建中烟工业有限责任公司 | Method for rapidly identifying type of balsam material liquid for cigarette |
CN103091282A (en) * | 2013-02-06 | 2013-05-08 | 吉林烟草工业有限责任公司 | Method for detecting quality of tobacco essence perfume |
-
2016
- 2016-08-17 CN CN201610679176.3A patent/CN106248619A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101393114A (en) * | 2008-10-21 | 2009-03-25 | 龙岩烟草工业有限责任公司 | Rapid measuring method for physical property of flavouring essences for tobacco |
CN101929950A (en) * | 2010-08-24 | 2010-12-29 | 聚光科技(杭州)股份有限公司 | Method and device for monitoring glycolonitrile preparation technology in real time |
CN102566533A (en) * | 2011-11-25 | 2012-07-11 | 福建中烟工业有限责任公司 | On-line monitoring device and method for preparing tobacco essence perfume |
CN102778442A (en) * | 2012-08-08 | 2012-11-14 | 福建中烟工业有限责任公司 | Method for rapidly identifying type of balsam material liquid for cigarette |
CN103091282A (en) * | 2013-02-06 | 2013-05-08 | 吉林烟草工业有限责任公司 | Method for detecting quality of tobacco essence perfume |
Non-Patent Citations (2)
Title |
---|
张峰 等: "近红外透射光谱技术用于烟用香精的品质控制", 《中国烟草学报》 * |
张峰: "近红外光谱技术用于二次调配烟用香精的品质控制", 《全国第四届近红外光谱学术会议论文集》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113281291A (en) * | 2021-05-14 | 2021-08-20 | 深圳市八六三新材料技术有限责任公司 | Method and device for analyzing components of essence and computer readable storage medium |
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