CN110702482A - Preparation and application of tobacco chemical component off-line near-infrared detection monitoring sample - Google Patents
Preparation and application of tobacco chemical component off-line near-infrared detection monitoring sample Download PDFInfo
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- 241000208125 Nicotiana Species 0.000 title claims abstract description 46
- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 45
- 238000001514 detection method Methods 0.000 title claims abstract description 37
- 238000012544 monitoring process Methods 0.000 title claims abstract description 27
- 239000000126 substance Substances 0.000 title claims abstract description 23
- 238000002360 preparation method Methods 0.000 title claims abstract description 17
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims abstract description 20
- 239000000203 mixture Substances 0.000 claims abstract description 15
- ZAMOUSCENKQFHK-UHFFFAOYSA-N Chlorine atom Chemical compound [Cl] ZAMOUSCENKQFHK-UHFFFAOYSA-N 0.000 claims abstract description 11
- 239000000460 chlorine Substances 0.000 claims abstract description 11
- 229910052801 chlorine Inorganic materials 0.000 claims abstract description 11
- SNICXCGAKADSCV-JTQLQIEISA-N (-)-Nicotine Chemical compound CN1CCC[C@H]1C1=CC=CN=C1 SNICXCGAKADSCV-JTQLQIEISA-N 0.000 claims abstract description 10
- ZLMJMSJWJFRBEC-UHFFFAOYSA-N Potassium Chemical compound [K] ZLMJMSJWJFRBEC-UHFFFAOYSA-N 0.000 claims abstract description 10
- 229960002715 nicotine Drugs 0.000 claims abstract description 10
- SNICXCGAKADSCV-UHFFFAOYSA-N nicotine Natural products CN1CCCC1C1=CC=CN=C1 SNICXCGAKADSCV-UHFFFAOYSA-N 0.000 claims abstract description 10
- 229910052757 nitrogen Inorganic materials 0.000 claims abstract description 10
- 239000011591 potassium Substances 0.000 claims abstract description 10
- 229910052700 potassium Inorganic materials 0.000 claims abstract description 10
- 238000005070 sampling Methods 0.000 claims abstract description 9
- 238000007873 sieving Methods 0.000 claims abstract description 5
- 238000007789 sealing Methods 0.000 claims description 5
- 238000003756 stirring Methods 0.000 claims description 5
- 230000015556 catabolic process Effects 0.000 claims description 3
- 238000006731 degradation reaction Methods 0.000 claims description 3
- 239000012535 impurity Substances 0.000 claims description 3
- 238000002156 mixing Methods 0.000 claims description 3
- 239000000523 sample Substances 0.000 description 40
- 238000000034 method Methods 0.000 description 8
- 239000013062 quality control Sample Substances 0.000 description 5
- 238000001228 spectrum Methods 0.000 description 5
- 238000013461 design Methods 0.000 description 3
- 239000007788 liquid Substances 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 235000019504 cigarettes Nutrition 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000003908 quality control method Methods 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 1
- 241000208292 Solanaceae Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 239000013068 control sample Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000000502 dialysis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000003205 fragrance Substances 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000003333 near-infrared imaging Methods 0.000 description 1
- 230000002572 peristaltic effect Effects 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000002834 transmittance Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 239000012224 working solution Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
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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
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- 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)
- Manufacture Of Tobacco Products (AREA)
Abstract
The invention discloses a preparation method and application of a tobacco chemical composition off-line near-infrared detection monitoring sample, wherein sampling is carried out according to the detection range of a near-infrared model, crushing is carried out by a cyclone mill, sieving is carried out, moisture is balanced, the mixture is uniformly mixed, the mixture is collected and sealed in a sealed container, air is discharged, the mixture is stored in a dark place for a period of time, the sample is fully and uniformly mixed, a continuous flow analyzer is used for detecting the sample to obtain the content of nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen, the content is determined as standard content, the prepared sample is a monitoring sample, the monitoring sample is used for verifying the near-infrared model, the sample is detected by the continuous flow analyzer to obtain the standard content, and the usability of the near-infrared model is determined. The invention effectively standardizes and unifies the monitoring samples for the off-line near infrared detection of the tobacco in the industry, can be used for evaluating the accuracy of the off-line near infrared detection of the tobacco, and can generally improve the accuracy and the detection stability of the off-line near infrared detection of the tobacco in the industry.
Description
Technical Field
The invention relates to the technical field of tobacco chemical detection, in particular to manufacturing and application of a tobacco chemical component off-line near-infrared detection monitoring sample.
Background
Tobacco is a plant of genus Nicotiana of family Solanaceae, and contains chemical substances which can generate fragrance, aroma and certain pungent smell after being combusted, and can give people a pleasant feeling, and has certain effects of recovering physical strength and refreshing vigor. The quality of tobacco is determined by the inherent chemical substances of the tobacco, so that the final research foothold and the attention point of the tobacco chemistry are both in the tobacco agriculture and the cigarette technology at present. Therefore, the detection means and the evaluation means are more and more sound, and the continuous flow type analyzer is introduced in the domestic tobacco industry in the 80 s to measure several main chemical components in the tobacco and the products thereof. The continuous flow method is used as an effective tobacco industry standard measuring method, and the main principle of the continuous flow analyzer is that a standard working solution, a reagent and a sample are introduced into a pipeline of a module according to a peristaltic pump, and bubbles with the same size are fed in continuous inflow, so that a liquid flow separation system is formed in the pipeline, and the integrity of the sample is kept. The chemical reaction is generated through the steps of mixing, heating, dialysis and the like, the color of liquid flow is changed, the transmittance is finally detected through a colorimeter, the analysis result is expressed by a series of peak electric signals, and the data acquisition and processing system prints and outputs the result. The method has the disadvantages of large workload of pretreatment, certain influence of the generated waste liquid on the environment and high maintenance cost of the instrument. After the model is established, the near-infrared method can be used for rapidly determining the conventional chemical analysis of the tobacco, the sample does not need to be pretreated and does not consume the sample, the detection of different chemical indexes of the sample can be rapidly and efficiently completed simultaneously, the environment is protected, the detection process is pollution-free and reliable in performance, the structure of the instrument is simpler, the instrument is easy to maintain, the operation cost and the environment protection risk are reduced, a large amount of manpower, material resources and financial resources are saved, and the economic benefit is high. In each link of tobacco and cigarette production, participating personnel are thousands of people, in order to ensure that each link has a recognition of product quality, a monitoring sample is generated at the end, and in order to increase the recognition degree of the monitoring sample, a uniform preparation method and an application range are important.
Disclosure of Invention
In order to solve the problems and the defects in the prior art, the invention provides the preparation and the application of the tobacco chemical component off-line near infrared detection monitoring sample.
The following design structure and design scheme are specifically adopted:
the preparation and application of the off-line near infrared detection monitoring sample for the chemical components of the tobacco comprise the following steps,
step S1: preparing a monitoring sample, removing impurities from a tobacco sample, separating stems and leaves, removing tobacco stems, taking leaves, crushing the leaves by using a cyclone mill, sieving, placing the crushed leaves in a constant-temperature constant-humidity box for balancing moisture, pouring the sample into a sampling frame after uniformly mixing, uniformly stirring, storing the sample in a sealed container, exhausting air, and storing in a dark place.
Step S2: and detecting the monitored sample by using a continuous flow analyzer, respectively obtaining the nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen content in the sample, and determining the content as the standard content.
Step S3: and detecting the monitored sample by adopting a tobacco off-line near-infrared detection method with a built model to obtain the contents of nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen in the sample.
Step S4: and comparing the contents obtained in the two modes, and confirming the usability of the near infrared model.
Preferably, the screening is a 20 mesh screen.
Preferably, the temperature of the constant temperature and humidity box is 22 ℃, the humidity is 66% RH, and the moisture is balanced for 24 hours.
Preferably, the samples are poured into the sampling frame, a worker wears the disposable gloves, holds the samples from left to right layer by layer, spreads the samples in the sampling frame and uniformly stirs the samples, spreads the samples from right to left after one time, and spreads the samples for 5 times by analogy.
Preferably, the sample is subpackaged by clean and dry sample bags, sealed by special sealing bags, each bag is 100g, and placed in a dry shady place for preservation.
Preferably, the temperature after sealing is controlled to be 18-25 ℃, and the relative humidity is 45-65%.
Preferably, the continuous flow analyzer is a SKALAR flow analyzer in the netherlands.
Preferably, the near infrared is an Antaris Fourier transform near infrared spectrometer.
Preferably, the model content ranges are nicotine (1.26% -3.87%), water-soluble sugar (17.92% -38.34%), reducing sugar (17.05% -30.19%), chlorine (0.15% -0.61%), potassium (1.49% -2.81%), and total nitrogen (1.49% -3.1%).
Preferably, after the near infrared model is effectively put into use, the accuracy and precision of the model must be continuously monitored. At the same time, the performance of the instrument must be monitored to determine whether the model performance is degraded or the error caused by the degradation of the instrument performance.
Compared with the prior art, the invention has the following beneficial effects: the invention effectively standardizes and unifies the monitoring samples for the off-line near infrared detection of the tobacco in the industry, can be used for evaluating the accuracy of the off-line near infrared detection of the tobacco, and can generally improve the accuracy and the detection stability of the off-line near infrared detection of the tobacco in the industry.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a table of experimental data for the present invention;
FIG. 3 is a table of experimental data for the present invention;
Detailed Description
The following describes embodiments of the present invention in more detail with reference to the accompanying drawings and specific examples.
Example (b):
as shown in the attached figure 1 of the specification, the preparation and the application of the tobacco chemical composition off-line near infrared detection monitoring sample comprise the following steps,
s1: preparing a monitoring sample, removing impurities from a tobacco sample, separating stems and leaves, removing tobacco stems, taking leaves, crushing the leaves by a cyclone mill of FOSS-CT410 model, sieving by a 20-mesh sieve, placing in a constant temperature and humidity box for balancing moisture for 24 hours, the temperature of the constant temperature and humidity box is 22 ℃, the humidity is 66% RH, the samples are poured into a sampling frame after being uniformly mixed, the working personnel wears the disposable gloves, holds the samples by hands, spreads the samples layer by layer from left to right in the sampling frame and uniformly stirs the samples, spreads the samples from right to left after one time, and spreads the samples for 5 times by analogy, then subpackaging the sample with clean and dry sample bags, sealing with special sealing bags, each bag containing 100g of the sample, storing in dry shady place, controlling the temperature at 18-25 ℃ and the relative humidity at 45-65%, and carrying out sample coding on the prepared monitoring sample.
S2: and (3) detecting the monitored sample by using a Dutch SKALAR continuous flow analyzer, respectively obtaining the contents of nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen in the sample, and determining the contents as standard contents.
S3: and detecting the monitored sample by adopting a tobacco off-line Antaris Fourier transform near infrared detection method to obtain the contents of nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen in the sample.
S4: the contents obtained in the two ways are compared, and the usability of a near infrared model is confirmed, wherein the model contents range from nicotine (1.26% -3.87%), water-soluble sugar (17.92% -38.34%), reducing sugar (17.05% -30.19%), chlorine (0.15% -0.61%), potassium (1.49% -2.81%) and total nitrogen (1.49% -3.1%).
The "continuous flow detection data" and the "near infrared detection data" in the accompanying drawings 2 and 3 of the specification are comparison data of 20 monitored samples, wherein the "continuous flow detection data" is an average value of data obtained by detecting the same sample for 5 times and is determined as a standard value of the monitored sample, the "near infrared detection data" is comparison data for detecting whether a near infrared model can be detected, and after the comparison, the following steps are carried out: chlorine takes absolute error because its content is low, and even a small deviation will result in a large relative error. The error is less than 5%, and the model prediction capability is generally considered to be very good. Error is 5% -10%; generally we consider model prediction capability acceptable. The error is more than 10%; generally we consider the model prediction capability to be poor.
In a more specific step of the method, after the near-infrared model is effectively put into use, the accuracy and precision of the model must be continuously monitored. At the same time, the performance of the instrument must be monitored to determine whether the model performance is degraded or the error caused by the degradation of the instrument performance. To meet such tests, one or more quality control samples are typically required. However, it is very difficult to store tobacco samples for a long period (e.g., 1 year) to ensure that the components of the samples do not change. Therefore, in selecting a quality control sample of tobacco, it is required that the spectrum of the quality control sample matches the model, as similar as possible to the spectrum of the calibration sample, as long as the control sample is analyzed by model interpolation, and can be applied to monitor the predictive performance of the model. In a simple way, a representative batch of interpolated samples (at least 30, preferably not less than 10, and the sample component content should cover the range of content variation when the model is built, and the sample component content should be distributed as uniformly as possible over the whole range) can be collected as quality control samples, the corresponding component content data is determined by using a continuous flow method, and then statistical comparison is performed with the result determined by the calibration model to evaluate whether the calibration model can pass effective verification. In the measurement and prediction of the quality control sample spectrum, the spectrum of the quality control sample should be collected using exactly the same procedure as the collection of the corrected sample spectrum. The basic data of the quality control sample is determined, and the same method as that for determining the basic data of the calibration sample is also used.
The scope of the present invention is not limited to the above-described embodiments, which are intended to help explain and illustrate the present invention, but not to limit the scope of the present invention, if it is designed to be the same as or substituted by the equivalent design of the present invention, and fall within the scope of the present invention as claimed.
Claims (10)
1. The preparation and the application of the tobacco chemical composition off-line near infrared detection monitoring sample are characterized in that: comprises the following steps of (a) carrying out,
step S1: preparing a monitoring sample, removing impurities from a tobacco sample, separating stems and leaves, removing tobacco stems, taking leaves, crushing the leaves by using a cyclone mill, sieving, placing the crushed leaves in a constant-temperature constant-humidity box for balancing moisture, pouring the sample into a sampling frame after uniformly mixing, uniformly stirring, storing the sample in a sealed container, exhausting air, and storing in a dark place.
Step S2: and detecting the monitored sample by using a continuous flow analyzer, respectively obtaining the nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen content in the sample, and determining the content as the standard content.
Step S3: and detecting the monitored sample by adopting a tobacco off-line near-infrared detection method with a built model to obtain the contents of nicotine, water-soluble sugar, reducing sugar, chlorine, potassium and total nitrogen in the sample.
Step S4: and comparing the contents obtained in the two modes, and confirming the usability of the near infrared model.
2. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 1, characterized in that: the sieving is a sieve with the aperture of 20 meshes.
3. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 1, characterized in that: the temperature of the constant temperature and humidity box is 22 ℃, the humidity is 66% RH, and the moisture is balanced for 24 hours.
4. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 3, characterized in that: the sample is poured into the sampling frame, the worker wears the disposable gloves, holds the sample and spreads the sample in the sampling frame layer by layer from the left to the right, evenly stirs the sample, spreads the sample from the right to the left after spreading once, and spreads 5 times by analogy.
5. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 4, characterized in that: the samples are subpackaged by clean and dry sample bags, sealed by special sealing bags, each bag is 100g, and placed in a dry shady place for storage.
6. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 1, characterized in that: the temperature of the sealed storage environment is controlled to be 18-25 ℃, and the relative humidity is 45-65%.
7. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 1, characterized in that: the continuous flow analyzer is a SKALAR flow analyzer in the Netherlands.
8. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 1, characterized in that: the near infrared is an Antaris Fourier transform near infrared spectrometer.
9. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 1, characterized in that: the content range of the model is nicotine (1.26% -3.87%), water-soluble sugar (17.92% -38.34%), reducing sugar (17.05% -30.19%), chlorine (0.15% -0.61%), potassium (1.49% -2.81%) and total nitrogen (1.49% -3.1%).
10. The preparation and application of the tobacco chemical composition off-line near infrared detection monitoring sample according to claim 7, characterized in that: after the near-infrared model is effectively put into use, the accuracy and precision of the model must be continuously monitored. At the same time, the performance of the instrument must be monitored to determine whether the model performance is degraded or the error caused by the degradation of the instrument performance.
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