CN103604778A - Method for accurately grouping and processing tobacco leaves in loosening and moisture regaining procedures - Google Patents
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- 241000208125 Nicotiana Species 0.000 title claims abstract description 77
- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 77
- 238000012545 processing Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 10
- 230000003595 spectral effect Effects 0.000 claims abstract description 6
- 238000012360 testing method Methods 0.000 claims description 13
- 238000001228 spectrum Methods 0.000 claims description 11
- 238000012937 correction Methods 0.000 claims description 3
- 238000001035 drying Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000010298 pulverizing process Methods 0.000 claims description 3
- 238000007789 sealing Methods 0.000 claims description 3
- 238000004611 spectroscopical analysis Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 8
- 238000000513 principal component analysis Methods 0.000 abstract description 3
- 230000000694 effects Effects 0.000 abstract description 2
- 235000019504 cigarettes Nutrition 0.000 description 19
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- 230000000391 smoking effect Effects 0.000 description 13
- 239000000203 mixture Substances 0.000 description 12
- 239000000463 material Substances 0.000 description 10
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- 238000001303 quality assessment method Methods 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 239000000243 solution Substances 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- 206010010071 Coma Diseases 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
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Abstract
The invention discloses a method for accurately grouping and processing tobacco leaves in a loosening and moisture regaining process. The method combines a Fourier transform near infrared spectrum FT-NIR analysis technology with a principal component analysis Mahalanobis distance PCA-MD classification method, is applied to analysis of tobacco leaves after loosening and moisture regaining processing, reasonably classifies analysis results of spectral data, and fully combines processing characteristics of the tobacco leaves to group the tobacco leaves. The method is simple and quick in operation, remarkable in effect and good in practical prospect.
Description
Technical field
The invention belongs to production of cigarettes technical field, be specifically related to a kind ofly in cigarette primary processing stage loosening and gaining moisture operation, utilize near-infrared spectrum technique tobacco leaf to be carried out to the method for accurate grouping Processing.
Background technology
In production of cigarettes process, tobacco leaf is carried out to scientific and reasonable grouping and can effectively improve each tobacco leaf formulation characteristic, significant for the quality of stabilizing and increasing cigarette product.Traditional tobacco leaf group technology is mainly to divide into groups according to the organoleptic attribute of raw tobacco material, throwing several raw tobacco materials with identical or close style characteristic in leaf group of filling a prescription are combined to form to tobacco leaf formulation module, and this method Chang Yin is subject to the subjective factor that sensory evaluating smoking itself exists and affects accuracy and the reliability of group result.Then there is scholar to propose on sensory evaluating smoking's basis, for the chemical characteristic of raw tobacco material, set up tobacco leaf group technology, the method has been considered the quality characteristic of different raw tobacco materials, effectively brought into play the similarity between different qualities raw tobacco material, there is objectivity to a certain degree, yet, raw tobacco material lives through series of temperature in follow-up process, after humidity changes, there is change in various degree in its inner material, cause quality of tobacco that variation has occurred, this group technology does not take into full account the processing characteristics of different raw tobacco materials, also cannot meet Cigarette processing " flexibility, become more meticulous " technological requirement.
Loosening and gaining moisture operation is one of important procedure in cigarette primary processing production run, also be one of raw tobacco material master operation of being heated, different raw tobacco materials is after the processing of loosening and gaining moisture operation, show processing characteristics separately, change except physical quality, the chemical substance of tobacco leaf inside also can change, and between this variation and the aesthetic quality of tobacco leaf, has contiguity, and product quality is impacted.How in loosening and gaining moisture operation, to take into full account the processing characteristics of tobacco leaf, and tobacco leaf is rationally divided into groups, for the personalization of different tobacco leaves, process scientific basis is provided, effectively promote the aesthetic quality of tobacco leaf, just report not yet has good solution at present.
Summary of the invention
The object of the invention is to for the deficiencies in the prior art, a kind of easy, accurate method is provided, use near infrared spectrum (FT-NIR) analytical technology and in conjunction with principal component analysis (PCA) mahalanobis distance (PCA-MD) method, tobacco sample after the processing of loosening and gaining moisture operation is set up to class model, by mahalanobis distance, characterize the difference of sample classification qualitative characteristics, thereby define this sample applicable tobacco leaf grouping Processing method in loosening and gaining moisture operation, take into full account the processing characteristics of tobacco leaf, for the similar tobacco leaf of following process provides the grouping foundation of science.
Object of the present invention is achieved by the following technical programs.
Except as otherwise noted, percentage of the present invention is mass percent.
A method of tobacco leaf in loosening and gaining moisture operation being carried out to accurate grouping Processing, comprises the following steps:
(1) sample collection: module tobacco leaf is fed intake successively by feeding sequence, gather respectively in loosening and gaining moisture operation the tobacco leaf after hot blast temperature is 50～55 ℃, 60～65 ℃ and 70～75 ℃ of processing; Wherein, under each temperature conditions, gather 30 times, gather 300g at every turn;
(2) sample preparation: be under 20～30 ℃ of conditions to be 11%～13% by drying tobacco to water percentage in temperature, cross 60 mesh sieves after pulverizing, be placed in sealing bag, normal temperature lucifuge is stored standby;
(3) spectral scan: use the start preheating near infrared spectrometer of 2 hours to carry out respectively near infrared spectrum scanning to each testing sample, gather its diffuse reflection spectrum data, the near infrared spectrum scanning scope of each sample is 10000～4000cm
-1, resolution is 8cm
-1, scanning times is 72 times;
(4) spectrum pre-service: the diffuse reflection spectrum data that spectral scan obtains obtains the pre-processed spectrum data of each testing sample after polynary scatter correction, the filtering of second order local derviation+Norris derivative;
(5) tobacco leaf grouping: application PCA-MD method is analyzed pretreated spectroscopic data, by the mahalanobis distance between class, weigh the qualitative characteristics similarity degree of sample, distance is larger, similarity degree is lower, otherwise similarity degree is larger, the larger sample of similarity degree is classified as and is divided into groups, thereby determine tobacco leaf grouping information.
Compared with prior art, the present invention has following beneficial effect:
1, tobacco sample after operation processing analyzed and then divided into groups, having taken into full account the processing characteristics of tobacco leaf, the personalized process requirements while meeting subsequent treatment tobacco leaf of the same type.
2, adopt PCA-MD classification, can carry out directviewing description to the chemical composition otherness of tobacco leaf after the processing of loosening and gaining moisture operation, made up to a certain extent the limitation of spot measurement, for the grouping Processing of this operation tobacco leaf provides scientific basis.
3, utilize FT-NIR diffuse reflection, in conjunction with PCA-MD, tobacco leaf is carried out to grouping Processing, the subjectivity impact of having avoided simple dependence sensory evaluating smoking to classify, has improved accuracy and the reliability of grouping.
4, method of operating of the present invention is simple and quick, and effect is remarkable, has good practical prospect.
Accompanying drawing explanation
Fig. 1 is sample classification figure when return air temperature is 50～55 ℃ in the embodiment of the present invention 1;
Fig. 2 is sample classification figure when return air temperature is 60～65 ℃ in the embodiment of the present invention 1;
Fig. 3 is sample classification figure when return air temperature is 70～75 ℃ in the embodiment of the present invention 1;
Fig. 4 is sample classification figure when return air temperature is 50～55 ℃ in the embodiment of the present invention 2;
Fig. 5 is sample classification figure when return air temperature is 60～65 ℃ in the embodiment of the present invention 2;
Fig. 6 is sample classification figure when return air temperature is 70～75 ℃ in the embodiment of the present invention 2.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail, but embodiment and accompanying drawing are not limited to the technical solution.
Except as otherwise noted, 2003 editions < < cigarette process standard > > that related technical term is all write with reference to State Tobacco Monopoly Bureau.
The experimental apparatus adopting in embodiment and application software: Nicolet Antaris
tMfT-NIR spectrometer (U.S. ThemoNicolet company), Cycbtec1093 cyclone type sample mill (Sweden FOSS company), FED hot blast circulation able to programme baking oven (German Binder company); RESULT
tMintegrated software, SPSS statistical analysis software.
Embodiment selects tobacco sample as modeling standard specimen, and application offset minimum binary mathematical method is carried out modeling to the basic data of the near infrared spectrum collecting and Flow Injection Analysis mensuration, by model optimization, finally obtains comparatively ideal mathematical model.
Select certain brand module cigarette to test, the tobacco leaf of module cigarette comprises a plurality of grades, refers in Table 1.
Tobacco leaf class information in table 1 the present embodiment
| Sequence number | Tobacco leaf grade | The time limit | Sequence number | Tobacco leaf grade | The |
| 1 | C4F | 2010 | 16 | B1F | 2009 |
| 2 | C4F | 2010 | 17 | B1F | 2009 |
| 3 | C3F | 2011 | 18 | B1F | 2009 |
| 4 | C3F | 2011 | 19 | BSF | 2010 |
| 5 | C3F | 2011 | 20 | BSF | 2010 |
| 6 | C3F | 2011 | 21 | BSF | 2010 |
| 7 | C3F | 2011 | 22 | BSF | 2010 |
| 8 | C3F | 2011 | 23 | BSF | 2010 |
| 9 | C2F | 2010 | 24 | B2F | 2011 |
| 10 | C2F | 2010 | 25 | B2F | 2011 |
| 11 | C2F | 2010 | 26 | B2F | 2011 |
| 12 | C2F | 2010 | 27 | B2F | 2011 |
| 13 | C1F | 2009 | 28 | B3F | 2010 |
| 14 | C1F | 2009 | 29 | B3F | 2010 |
| 15 | C1F | 2009 | 30 | B3F | 2010 |
The hot air conditioning cylinder that adopts Italian COMAS company to produce in loosening and gaining moisture operation, parameter arranges condition and is: flow: 3000kg/h; Drum rotation speed: 9rpm; Humidity discharging throttle opening: 50%; Cycle throttle aperture: 70%; Hot blast temperature is followed successively by: 50～55 ℃, 60～65 ℃, 70～75 ℃; Module tobacco leaf is fed intake successively by feeding sequence, gather respectively in loosening and gaining moisture operation each grade tobacco leaf after hot blast temperature is 50～55 ℃, 60～65 ℃ and 70～75 ℃ of processing; Wherein, under each temperature conditions, corresponding collection 30 times gathers 300g at every turn; In temperature, be under 20～30 ℃ of conditions by drying tobacco, to water percentage, to be 11%～13%, after pulverizing, cross 60 mesh sieves, be placed in sealing bag, normal temperature lucifuge is stored standby; Use the start preheating near infrared spectrometer of 2 hours to carry out respectively near infrared spectrum scanning to each testing sample, gather its diffuse reflection spectrum data, the near infrared spectrum scanning scope of each sample is 10000～4000cm
-1, resolution is 8cm
-1, scanning times is 72 times; The diffuse reflection spectrum data that spectral scan obtains obtains the pre-processed spectrum data of each testing sample after polynary scatter correction, the filtering of second order local derviation+Norris derivative; Application PCA-MD method is analyzed pretreated spectroscopic data, by the mahalanobis distance between class, weigh the qualitative characteristics similarity degree of sample, distance is larger, similarity degree is lower, otherwise similarity degree is larger, the larger sample of similarity degree is classified as and is divided into groups, thereby determine tobacco leaf grouping information.
Test class class in and between class distance in Table 2; Tobacco leaf group result as shown in Figures 1 to 3; Tobacco leaf after grouping is carried out to sensory quality assessment, and sensory evaluating smoking the results are shown in Table 3.
Mahalanobis distance mean value in the class of table 2 test class and between class
| Type | A1 | A2 | B1 | B2 | C1 | C2 |
| A1 | 0.9425 | 1.1033 | - | - | - | - |
| A2 | 1.1098 | 0.9563 | - | - | - | - |
| B1 | - | - | 0.8937 | 2.1137 | - | - |
| B2 | - | - | 2.0986 | 0.9021 | - | - |
| C1 | - | - | - | - | 0.9511 | 3.2961 |
| C2 | - | - | - | - | 3.2173 | 0.9739 |
Different classes of cigarette sensory quality assessment result of table 3
Interpretation of result:
As can be seen from Figure 1, when return air temperature is 50～55 ℃, sample is state of aggregation on distribution plan, in table 2 between the class of A1, A2 mahalanobis distance and inter-object distance comparatively approaching, distance less, illustrate that difference is not obvious; As can be seen from Figure 2, when return air temperature is 60～65 ℃, sample is divided into two classes on classification chart, between class, mahalanobis distance is respectively 2.1137,2.0986, contrast the numbering of two class components, first kind component is by 1st～No. 15 sample compositions, and Equations of The Second Kind component is by 16th～No. 30 sample compositions; As can be seen from Figure 3, when return air temperature is 70～75 ℃, sample is divided into two classes on classification chart, and between class, mahalanobis distance is respectively 3.2961,3.2173, is obviously greater than inter-object distance, and the numbering of two class components is consistent during with 60～65 ℃.Compare with sample after 60～65 ℃ of processing, between two class group categories, mahalanobis distance is larger.Comprehensive explanation, form the tobacco leaf of module cigarette at 60～65 ℃, 70～75 ℃ of return air temperatures, between the sample intrinsic chemical composition of the difference classification after processing, there are differences, 1st～No. 15 sample is substantially similar, 16th～No. 30 sample is substantially similar, divides respectively a class on distribution plan into.
As can be seen from Table 3, when return air temperature is 50～55 ℃, sensory evaluating smoking's result of sample does not have notable difference; When return air temperature is 60～65 ℃, there is notable difference in sensory evaluating smoking's result of sample, first kind sample is higher than Equations of The Second Kind sample in the score of fragrance matter, perfume quantity, and the score of Equations of The Second Kind sample on assorted gas, fine and smooth degree, pungency and dry sensation is higher than first kind sample; When return air temperature is 70～75 ℃, there is notable difference in sensory evaluating smoking's result of sample, and two class sample score variation tendencies are that 60～65 ℃ of samples after processing are consistent with return air temperature, and the score of two class samples is all lower than sample after 60～65 ℃ of processing.Comprehensive explanation, forms the tobacco leaf of module cigarette at 60～65 ℃, 70～75 ℃ of return air temperatures, according to the classification of Fig. 1～3, it is carried out to sensory evaluating smoking, and at two temperature, its aesthetic quality of sample of different classification there are differences.
Summary, the tobacco leaf of this module cigarette adds man-hour at 60～65 ℃, 70～75 ℃ of return air temperatures, its tobacco leaf should be divided into two groups to be processed respectively, and to guarantee giving full play to of its tobacco leaf processing characteristics, sensory evaluating smoking's result further illustrates the accuracy of this group technology.
Select certain brand module cigarette to test, the tobacco leaf of module cigarette comprises a plurality of grades, refers in Table 4.
Tobacco leaf class information in table 4 the present embodiment
| Sequence number | Tobacco leaf grade | The time limit | Sequence number | Tobacco leaf grade | The |
| 1 | X1F | 2009 | 16 | C3F | 2011 |
| 2 | X2F | 2009 | 17 | C3L | 2011 |
| 3 | X2F | 2009 | 18 | C3L | 2011 |
| 4 | X2F | 2009 | 19 | C4F | 2010 |
| 5 | XZF | 2009 | 20 | C4F | 2010 |
| 6 | XZF | 2009 | 21 | C4F | 2010 |
| 7 | MZF | 2011 | 22 | C4F | 2010 |
| 8 | MZF | 2011 | 23 | CSF | 2009 |
| 9 | XZF | 2011 | 24 | CSF | 2009 |
| 10 | XZF | 2011 | 25 | CSF | 2009 |
| 11 | CSL | 2010 | 26 | C3K | 2010 |
| 12 | CSL | 2010 | 27 | C3K | 2010 |
| 13 | CSL | 2010 | 28 | BSF | 2011 |
| 14 | C3F | 2011 | 29 | BSF | 2011 |
| 15 | C3F | 2011 | 30 | BSF | 2011 |
Test condition is identical with embodiment 1, test class class in and between class distance in Table 5; Tobacco leaf classification is as shown in Fig. 4～6; Sensory evaluating smoking the results are shown in Table 6.
Mahalanobis distance mean value in the class of table 5 test class and between class
| Type | A1 | A2 | A3 | B1 | B2 | B3 | C1 | C2 | C3 |
| A1 | 0.8934 | 2.5528 | 2.5411 | - | - | - | - | - | - |
| A2 | 2.5979 | 0.9247 | 1.0257 | - | - | - | - | - | - |
| A3 | 2.5368 | 0.9971 | 0.9238 | - | - | - | - | - | - |
| B1 | - | - | - | 0.8743 | 3.5127 | 2.1798 | - | - | - |
| B2 | - | - | - | 3.4925 | 0.8983 | 2.4935 | - | - | - |
| B3 | - | - | - | 2.0914 | 2.5348 | 0.9536 | - | - | - |
| C1 | - | - | - | - | - | - | 0.8537 | 2.9831 | 3.2035 |
| C2 | - | - | - | - | - | - | 2.8913 | 0.9368 | 1.0739 |
| C3 | - | - | - | - | - | - | 3.3124 | 1.1942 | 0.9545 |
Different classes of cigarette sensory quality assessment result of table 6
Interpretation of result:
As can be seen from Figure 4, when return air temperature is 50～55 ℃, it is two classes that sample gathers on classification chart, and it is a class that A1 gathers, and A2 and A3 are overlapping is a class, in table 5, the between class distance of A1 and A2, A3 is larger, and the between class distance of A2 and A3 and inter-object distance approach, and contrasts the numbering of two class components, first kind component is by 1st～No. 10 sample compositions, and Equations of The Second Kind component is by 11st～No. 30 sample compositions; As can be seen from Figure 5, when return air temperature is 60～65 ℃, it is three classes that sample gathers on classification chart, as known from Table 5, the between class distance of sample is obviously greater than inter-object distance, and between interpret sample, difference is obvious, contrast the numbering of three class components, first kind component is by 1st～No. 10 sample compositions, and Equations of The Second Kind component is by 11st～No. 20 sample compositions, and the 3rd class component is by 21st～No. 30 sample compositions; As can be seen from Figure 6, when return air temperature is 70～75 ℃, sample is divided into two classes at distribution plan, it is a class that C1 gathers, C2 and C3 are overlapping is a class, and in table 5, the between class distance of C1 and C2, C3 is larger, the between class distance of C2 and C3 and inter-object distance approach, and the numbering of two class components is consistent during with 50～55 ℃.Comprehensive explanation, forms the tobacco leaf of module cigarette at 50～55 ℃, 60～65 ℃, 70～75 ℃ of return air temperatures, after processing, between the sample intrinsic chemical composition of different classification, there are differences.
As can be seen from Table 6, when return air temperature is 50～55 ℃, score and all the other sample of first kind sample on aroma characteristic and mouthfeel characteristic there are differences; When return air temperature is 60～65 ℃, there is notable difference in sensory evaluating smoking's result of three class samples, on aroma characteristic, flue gas characteristic, mouthfeel characteristic, all have different performances, integrate score situation sees, the 3rd class sample score is the highest, Equations of The Second Kind sample takes second place, the 3rd class sample is minimum; When return air temperature is 70～75 ℃, two class sample score variation tendencies are that 50～55 ℃ of samples after processing are consistent with return air temperature, and the score of two class samples is respectively higher than sample after 50～55 ℃ of processing.Comprehensive explanation, forms the tobacco leaf of module cigarette at 50～55 ℃, 60～65 ℃, 70～75 ℃ of return air temperatures, according to the classification of Fig. 4～6, it is carried out to sensory evaluating smoking, and at three temperature, its aesthetic quality of sample of different classification there are differences.
To sum up, module cigarette tobacco leaf is processed at 50～55 ℃, 70～75 ℃ of return air temperatures, its tobacco leaf should be divided into two groups and process respectively, at 60～65 ℃ of return air temperatures, should be divided into three groups and process respectively, to guarantee giving full play to of its tobacco leaf processing characteristics, sensory evaluating smoking's result further illustrates the accuracy of this group technology.
Claims (1)
1. tobacco leaf in loosening and gaining moisture operation is carried out to a method for accurate grouping Processing, comprises the following steps:
(1) sample collection: module tobacco leaf is fed intake successively by feeding sequence, gather respectively in loosening and gaining moisture operation the tobacco leaf after hot blast temperature is 50～55 ℃, 60～65 ℃ and 70～75 ℃ of processing; Wherein, under each temperature conditions, gather 30 times, gather 300g at every turn;
(2) sample preparation: be under 20～30 ℃ of conditions to be 11%～13% by drying tobacco to water percentage in temperature, cross 60 mesh sieves after pulverizing, be placed in sealing bag, normal temperature lucifuge is stored standby;
(3) spectral scan: use the start preheating near infrared spectrometer of 2 hours to carry out respectively near infrared spectrum scanning to each testing sample, gather its diffuse reflection spectrum data, the near infrared spectrum scanning scope of each sample is 10000～4000cm
-1, resolution is 8cm
-1, scanning times is 72 times;
(4) spectrum pre-service: the diffuse reflection spectrum data that spectral scan obtains obtains the pre-processed spectrum data of each testing sample after polynary scatter correction, the filtering of second order local derviation+Norris derivative;
(5) tobacco leaf grouping: application PCA-MD method is analyzed pretreated spectroscopic data, by the mahalanobis distance between class, weigh the qualitative characteristics similarity degree of sample, distance is larger, similarity degree is lower, otherwise similarity degree is larger, the sample that similarity degree is larger divides into groups, thereby determines tobacco leaf grouping information.
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