CN104596982A - Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology - Google Patents
Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology Download PDFInfo
- Publication number
- CN104596982A CN104596982A CN201510050141.9A CN201510050141A CN104596982A CN 104596982 A CN104596982 A CN 104596982A CN 201510050141 A CN201510050141 A CN 201510050141A CN 104596982 A CN104596982 A CN 104596982A
- Authority
- CN
- China
- Prior art keywords
- sample
- pectin
- reconstituted tobacco
- paper
- spectrum
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 67
- 238000001228 spectrum Methods 0.000 title claims abstract description 60
- 235000010987 pectin Nutrition 0.000 title claims abstract description 58
- 229920001277 pectin Polymers 0.000 title claims abstract description 58
- 239000001814 pectin Substances 0.000 title claims abstract description 58
- 241000208125 Nicotiana Species 0.000 title claims abstract description 45
- 235000002637 Nicotiana tabacum Nutrition 0.000 title claims abstract description 45
- 238000005516 engineering process Methods 0.000 title claims abstract description 18
- 238000012795 verification Methods 0.000 claims abstract description 20
- 235000019505 tobacco product Nutrition 0.000 claims abstract description 19
- 238000001514 detection method Methods 0.000 claims abstract description 10
- 239000011159 matrix material Substances 0.000 claims description 22
- 238000012937 correction Methods 0.000 claims description 18
- 238000007781 pre-processing Methods 0.000 claims description 14
- 230000003595 spectral effect Effects 0.000 claims description 14
- 230000002159 abnormal effect Effects 0.000 claims description 9
- 238000002329 infrared spectrum Methods 0.000 claims description 9
- 239000000843 powder Substances 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 9
- 238000010561 standard procedure Methods 0.000 claims description 6
- 238000012353 t test Methods 0.000 claims description 4
- 238000012935 Averaging Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000002156 mixing Methods 0.000 claims description 3
- 238000003825 pressing Methods 0.000 claims description 3
- 238000000692 Student's t-test Methods 0.000 claims description 2
- 238000001055 reflectance spectroscopy Methods 0.000 claims 5
- 235000019504 cigarettes Nutrition 0.000 abstract description 9
- 230000000391 smoking effect Effects 0.000 abstract description 3
- 238000011160 research Methods 0.000 abstract description 2
- 238000010200 validation analysis Methods 0.000 abstract 1
- 238000004458 analytical method Methods 0.000 description 15
- 238000005259 measurement Methods 0.000 description 6
- 230000009286 beneficial effect Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 3
- 238000002790 cross-validation Methods 0.000 description 3
- 238000000354 decomposition reaction Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 238000012628 principal component regression Methods 0.000 description 3
- 238000000611 regression analysis Methods 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- UJOBWOGCFQCDNV-UHFFFAOYSA-N 9H-carbazole Chemical compound C1=CC=C2C3=CC=CC=C3NC2=C1 UJOBWOGCFQCDNV-UHFFFAOYSA-N 0.000 description 2
- AEMOLEFTQBMNLQ-YMDCURPLSA-N D-galactopyranuronic acid Chemical compound OC1O[C@H](C(O)=O)[C@H](O)[C@H](O)[C@H]1O AEMOLEFTQBMNLQ-YMDCURPLSA-N 0.000 description 2
- IAJILQKETJEXLJ-UHFFFAOYSA-N Galacturonsaeure Natural products O=CC(O)C(O)C(O)C(O)C(O)=O IAJILQKETJEXLJ-UHFFFAOYSA-N 0.000 description 2
- 108010059820 Polygalacturonase Proteins 0.000 description 2
- 239000003153 chemical reaction reagent Substances 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 108010093305 exopolygalacturonase Proteins 0.000 description 2
- 238000004817 gas chromatography Methods 0.000 description 2
- 238000004255 ion exchange chromatography Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000009659 non-destructive testing Methods 0.000 description 2
- 238000010238 partial least squares regression Methods 0.000 description 2
- 238000011002 quantification Methods 0.000 description 2
- 238000007493 shaping process Methods 0.000 description 2
- LWFUFLREGJMOIZ-UHFFFAOYSA-N 3,5-dinitrosalicylic acid Chemical compound OC(=O)C1=CC([N+]([O-])=O)=CC([N+]([O-])=O)=C1O LWFUFLREGJMOIZ-UHFFFAOYSA-N 0.000 description 1
- 240000002635 Dendrocalamus asper Species 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- -1 aldehyde ketone Chemical class 0.000 description 1
- 238000009835 boiling Methods 0.000 description 1
- 238000004737 colorimetric analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000593 degrading effect Effects 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000007071 enzymatic hydrolysis Effects 0.000 description 1
- 238000006047 enzymatic hydrolysis reaction Methods 0.000 description 1
- 238000005206 flow analysis Methods 0.000 description 1
- 238000000227 grinding Methods 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000004128 high performance liquid chromatography Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007794 irritation Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000003918 potentiometric titration Methods 0.000 description 1
- 238000000197 pyrolysis Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000007430 reference method Methods 0.000 description 1
- 230000000087 stabilizing effect Effects 0.000 description 1
- 238000001429 visible spectrum Methods 0.000 description 1
- 239000002023 wood Substances 0.000 description 1
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention relates to a method for measuring the pectin content of paper-making reconstituted tobacco by a near-infrared diffuse reflection spectrum technology, belonging to the technical field of paper-making reconstituted tobacco. The method mainly comprises the following steps: (1) collecting a sample; (2) acquiring the original spectrum; (3) measuring the reference value of the sample; (4) selecting and pretreating a calibration sample set and a verification sample set; (5) establishing a point-line-surface (PLS) conceptual model; and (6) carrying out model validation. According to the method, the PLS conceptual model for measuring the pectin content of the paper-making reconstituted tobacco products is established by the near-infrared technology; the method has the advantages of being rapid in detection speed, high in accuracy, good in reproducibility and the like, and has an important assisting function for the researches such as reducing the tar and harmful components of cigarette products, improving smoking quality, etc.
Description
Technical Field
The invention belongs to the field of paper-making reconstituted tobacco, and particularly relates to a method for measuring pectin of paper-making reconstituted tobacco by a near-infrared diffuse reflection spectrum technology.
Background
The paper-making reconstituted tobacco is an important raw material in cigarette production, and a proper amount of reconstituted tobacco is added into tobacco shreds, so that the physical properties and chemical components of cigarettes can be improved, the smoking safety of the cigarettes is improved, tobacco resources can be fully utilized, and the cost is reduced. The problems of high irritation, heavy wood smell and the like of the existing paper-making method reconstituted tobacco influence the addition amount and the use effect of the existing paper-making method reconstituted tobacco in cigarette products. The pectin accounts for about 10-13% of the total mass of the reconstituted tobacco, aldehyde ketone substances with low boiling points can be generated during pyrolysis, and irritating choking can be generated during smoking, which is one of the main reasons for the defects of the reconstituted tobacco. Therefore, the method has important significance in accurately and quickly measuring the pectin content in the reconstituted tobacco.
At present, the methods for measuring pectin in tobacco which are adopted internationally mainly comprise a gravimetric method, a carbazole colorimetric method, a 3, 5-dinitrosalicylic acid method (DNS), a High Performance Liquid Chromatography (HPLC), an enzymatic hydrolysis method, a flow analysis method and a Gas Chromatography (GC). The tobacco industry standard YC/T346-2010 ion chromatography for measuring pectin in tobacco and tobacco products is characterized in that according to the characteristic that pectinase has strong specificity, the pectinase is used for pretreating a sample to generate galacturonic acid, the pretreatment process of the sample is simplified, and meanwhile, according to the characteristic that the galacturonic acid has reducibility, a potentiometric titration method is used for measuring the pectin content in the tobacco. The methods all take longer time, the longer determination time not only reduces the efficiency, but also is difficult to satisfy the development of research work of improving the quality of the reconstituted tobacco by degrading the pectin content in the reconstituted tobacco by detection personnel. In view of this, it is necessary to develop a new method for rapidly determining the pectin content, so as to provide a certain reference for analyzing and evaluating the pectin content of the reconstituted tobacco.
After the near infrared light irradiates a substance, several interaction forms such as absorption, transmission, total reflection, diffuse reflection and the like can occur. The near infrared spectrum is mainly collected in three ways: transmissive, diffusely reflective, and diffusely transmissive.
For a liquid sample with good light permeability, near infrared light can penetrate through the whole sample, spectral scanning is performed in a transmission mode, and the measured data is accurate. The near infrared light can not completely penetrate through the paper-making reconstituted tobacco, so the diffuse reflection mode is adopted for spectrum scanning. After entering the inside of a sample, the near-infrared diffuse reflection light is reflected, refracted, diffracted and absorbed for countless times and then returns to the light of an incident surface, the analysis light loads the structure and composition information of the sample, and is a rapid and environment-friendly detection technology.
Disclosure of Invention
The invention aims to provide a method for simply, easily and quickly measuring pectin of reconstituted tobacco. The near infrared spectrum nondestructive testing technology is adopted, so that the analysis efficiency is improved, the cost is saved, the detection efficiency is improved and the product quality is objectively reflected for accurately testing the reconstituted tobacco pectin, and the method has obvious practicability. The method has obvious beneficial effects on stably controlling the internal quality of the paper-making reconstituted tobacco products, and playing the roles of stabilizing the cigarette product quality and shaping the cigarette style of the paper-making reconstituted tobacco.
The technical scheme adopted by the invention is as follows:
the method for measuring the pectin of the paper-making reconstituted tobacco by the near-infrared diffuse reflection spectrum technology comprises the following steps:
step (1), collecting a sample: collecting and preparing a representative batch of paper-making process reconstituted tobacco products;
step (2), collecting an original spectrum: taking the paper-making reconstituted tobacco products collected in the step (1), crushing each product into powder, uniformly mixing the powder, putting the powder into a sample cup, lightly pressing the sample cup to be flat, wherein the thickness of the sample is more than or equal to 10mm, taking 3 parallel samples for each product, scanning and collecting the spectrum by using a near infrared spectrum technology in a diffuse reflection mode, scanning the spectrum once for each parallel sample, enabling each product to correspond to 3 parallel spectra, averaging the 3 parallel spectra to obtain an original spectrum, and scanning and collecting the spectrum for each reconstituted tobacco product in sequence by adopting the same method to obtain the original spectrum corresponding to each product;
step (3), determining a sample reference value: measuring pectin of the paper-making reconstituted tobacco products collected in the step (1) one by using a standard method to obtain a sample reference value;
and (4) selecting and preprocessing a correction sample set and a verification sample set: selecting a correction sample set and a verification sample set from the original spectrum obtained in the step (2) by adopting a method of standard GB/T29858-2013; then, preprocessing the spectrums in the correction sample set and the verification sample set to eliminate the influence of noise and baseline drift;
step (5), establishing a PLS model: the corrected sample set processed in the step (4) is in one-to-one correspondence with the sample reference values obtained in the step (3), the spectral data and the corresponding pectin determination data are fitted by applying a partial least square method, a quantitative model is established, the abnormal values are detected and removed in the process, the residual spectral values after the abnormal values are removed are in one-to-one correspondence with the obtained sample reference values again, the spectral data and the corresponding pectin determination data are fitted by applying the partial least square method, and a quantitative model of pectin indexes is established;
step (6), model verification: and (5) carrying out external prediction on the pectin index quantitative model established in the step (6) by using the verification sample set processed in the step (4).
Further, the spectrum collection conditions in the step (2) are as follows: scanning range: 4000cm-1~10000cm-1(ii) a Resolution ratio: 8cm-1(ii) a The number of scans is not less than 72.
And (3) the sample reference value determination is to determine the pectin of the collected samples one by using a standard method, so as to obtain the reference value, wherein the standard method is the tobacco industry standard YC/T346-.
Further, the preprocessing in step (4) refers to performing multivariate scattering correction, first Derivative and Norris Derivative filtering preprocessing on the original spectrum, that is, performing MSC + first order + Norris preprocessing on the original spectrum.
In the above technical solution, the detecting and removing the abnormal value in the step (5) adopts a method for detecting a lever value, and specifically includes the following steps:
the sample lever value was calculated as follows:
wherein,H i the value of the lever of the sample is,t i is a sampleiThe vector of the factors of (a) is,T T Tto model the factor score matrix of the set,is composed oft i Transposing;
when the lever value of a sample is more than 3k/n, wherein k is the number of main components, n is the number of samples, the spectrum of the sample has obvious influence on regression, and the sample is rejected.
Further, the model verification of the step (6) is to determine whether the predicted value obtained by verifying the quantitative model of the sample set input step (6) is statistically deviated from the corresponding sample reference value measured in the step 4 by using a t-test method: namely, the predicted value of the quantitative model of the pectin index established in the step (6) and the sample reference value t and the degree of freedom d in the step (3) are comparedv-1Critical value t of(a,dv-1)Compared, the significance level a =0.05, when | t | is < t(a,dv-1)Probability P>And when the time is 0.05, the detection results of the two methods are not obviously different, the model is successfully verified, and the model can be used for measuring the pectin of the paper-making reconstituted tobacco.
And (3) measuring pectin: and (5) inputting the original spectrum of the paper-making reconstituted tobacco sample to be tested into the quantitative model of the pectin index established in the step (5), and determining to obtain the pectin.
The PLS model is a development of the principal component regression correction method (PCR). In the principal component regression analysis, a spectral matrix is decomposed through a certain number of principal factors, so that the aim of reducing the dimension of data and eliminating useless information (noise) is fulfilled. In the PLS regression analysis, in addition to the decomposition of the spectral matrix, the decomposition and dimension reduction of the concentration matrix are also performed, and mutual information is introduced. The principle is as follows:
(1) the matrix decomposition model is:
Am×p=Tm×kPk×p+EA
Cm×n=Um×kQk×n+EC
wherein A is a spectrum matrix; c is a concentration or property matrix; t is a scoring matrix of the spectrum matrix; u is the moment of concentration matrixArraying; p is a load matrix-principal component matrix of the spectrum matrix; q is a load matrix-principal component matrix of the concentration matrix; eAA spectral error matrix introduced for regression analysis using PLS; eCA concentration error matrix introduced for regression analysis using PLS; m is the number of samples; p is the number of wavelengths; k is the number of principal components.
(2) Regression analysis of the score matrix T, U to obtain a correlation coefficient matrix B
Um×k=Tm×fBk×k
(3) In predictive analysis, according to Am×p=Tm×kPk×p+EAObtaining a scoring matrix T of the sample from the unknown spectrum matrix A of the sample and the decomposed load matrix PIs unknownIn accordance with CIs unknown=TIs unknownBQ determines the concentration of the unknown sample.
Compared with the prior art, the invention has the beneficial effects that:the method has the advantages of high detection speed, no pollution, environmental protection, high accuracy, good reproducibility and the like, and is suitable for realizing on-site analysis and rapid detection of the pectin of the reconstituted tobacco product and on-line monitoring of the product quality fluctuation. The method has obvious beneficial effects of stably controlling the internal quality of the paper-making reconstituted tobacco products, playing the quality of the paper-making reconstituted tobacco stable cigarette products and shaping the style of the cigarettes, and does not need to damage samples and carry out pretreatment such as sample grinding after collecting the products.
a. The analysis speed is fast: measuring a sample within 3min, rapidly determining the pectin of the reconstituted tobacco product through the established pectin model, and preliminarily judging the fluctuation condition of the quality of the sample;
b. belongs to a non-destructive analysis technology: the sample is not damaged in the near infrared spectrum measurement process, and the sample is not influenced from the appearance to the inside;
c. low analysis cost and no pollution: the sample is not consumed in the sample analysis process, any chemical reagent is not used, the cost is reduced, and the environment is not polluted;
d. the test reproducibility is as follows: the spectral measurement is less interfered by human factors, and the measurement has stability;
e. the online analysis is convenient to realize: the near infrared spectrum has good transmission characteristics in the optical fiber, and can realize on-line analysis and remote monitoring.
The method for measuring the pectin of the reconstituted tobacco by the paper-making process by adopting the near infrared diffuse reflection spectrum technology is simple, easy to implement and quick, can improve the analysis efficiency and save the cost by adopting the near infrared spectrum nondestructive testing technology, and has obvious practicability for accurately measuring the pectin of the reconstituted tobacco, improving the testing efficiency and objectively reacting the product quality.
Drawings
FIG. 1 is a data fitting graph of the quantitative model of pectin indicator established in step (5).
Detailed Description
The present invention will be described in further detail with reference to examples.
It will be appreciated by those skilled in the art that the following examples are illustrative of the invention only and should not be taken as limiting the scope of the invention. The examples do not specify particular techniques or conditions, and are performed according to the techniques or conditions described in the literature in the art or according to the product specifications. The reagents or instruments used are not indicated by the manufacturer, and are all conventional products available by purchase.
The method for measuring the pectin of the paper-making reconstituted tobacco by utilizing the near-infrared diffuse reflection spectrum comprises the following steps:
step (1), collecting a sample: collecting 250-300 representative paper-making method reconstituted tobacco samples;
step (2), crushing each product collected in the step (1) into powder, uniformly mixing the powder, putting the powder into a sample cup, lightly pressing the sample cup to be flat, wherein the thickness of the sample is more than or equal to 10mm, taking 3 parallel samples for each product, scanning the samples by using a near infrared spectrum technology in a diffuse reflection mode, collecting spectrums, scanning the spectrums once for each parallel sample, enabling each product to correspond to 3 parallel spectrums, averaging the 3 parallel spectrums to obtain an original spectrum, and scanning and collecting the spectrums for each reconstituted tobacco product in sequence by using the same method to obtain the original spectrum corresponding to each product; the spectrum acquisition conditions are as follows: scanning range: 4000cm-1~10000cm-1(ii) a Resolution ratio: 8cm-1(ii) a The number of scans is not less than 72.
Step (3), determining a sample reference value: measuring the pectin of the paper-making reconstituted tobacco products collected in the step (1) one by using a standard method (tobacco industry standard YC/T346-2010 ion chromatography for measuring pectin of tobacco and tobacco products) to obtain a sample reference value;
step (4), selecting a correction sample set and a verification sample set and preprocessing: selecting a correction sample set and a verification sample set from the original spectrum obtained in the step (2) by adopting a standard GB/T29858-2013 method; then, MSC + first order + Norris (3, 5) preprocessing is carried out on the spectrums of the correction sample set and the verification sample set, and the influence of noise and baseline drift is eliminated;
step (5), establishing a PLS model: and selecting a full spectrum range to perform PLS regression and full cross validation on the correction set samples, and selecting the most suitable principal component number of the model as 2 when the principal component number of the model reaches 2 and the root mean square cross validation error RMSECV of the model is the minimum.
The corrected sample set processed in the step (4) and the sample reference value obtained in the step (3) are in one-to-one correspondence, the partial least square method is applied to carry out statistical fitting on the spectral data and the corresponding pectin determination data, a quantitative model is established, abnormal values are detected and removed in the process,
the sample lever value was calculated as follows:
H i the value of the lever of the sample is,t i is a sampleiThe vector of the factors of (a) is,T T Tto model the factor score matrix of the set,is composed oft i The transposing of (1).
When the lever value of a sample is more than 3k/n, wherein k is the number of main components, n is the number of samples, the spectrum of the sample has obvious influence on regression, and the sample is rejected; calculating to obtain spectral lever values of all the correction sample sets and the verification sample sets in the step (3) which are smaller than 3k/n, and eliminating no abnormal sample;
the residual spectrum numerical values after the abnormal values are removed are in one-to-one correspondence with the obtained sample reference values again, the partial least square method is applied to fit the spectrum data with the corresponding pectin determination data, a quantitative model of pectin indexes (shown in figure 1) is established, the correlation coefficient of the quantitative model is 0.855, RMSECV is 0.924, and an obvious linear relation exists between the visible spectrum data and the index quantification of the sample, so that the near infrared spectrum of the sample contains information closely related to the index quantification;
step (6), model verification: and (5) carrying out external prediction on the quantitative model of the pectin index established in the step (5) by using 50 products in the verification sample set processed in the step (4), and calculating a root mean square prediction error RMSEP according to the following formula:
wherein D isifi=xi-yiFor the i-th sample near-infrared measurement value xiReference value y of the sample as the analysis referenceiThe difference between them. The root mean square prediction error RMSEP is calculated by a formula and is 0.5397, and a model established by PLS has high prediction accuracy and prediction stability. Table 1 shows the prediction results of the PLS model prediction set. And (3) determining whether the predicted value obtained by inputting the sample set into the quantitative model in the step (5) is statistically deviated from the corresponding sample reference value measured in the step (3) by adopting a t test method: namely, the predicted value of the quantitative model of the pectin index established in the step (5) and the sample reference value t and the degree of freedom d in the step (3) are comparedv-1Critical value t of(a,dv-1)For comparison, significant level a =0.05 was taken. In the embodiment, the sample result is predicted and verified through the established quantitative correction model, the sample result is matched with a standard determination method for t test, the t value is found out according to a 95% confidence interval, and t is0.05,49=2.009, quantitative model prediction result by PLS and standard reference method measurement value | t < t0.05,49And P is more than 0.05, the detection results of the two methods have no significant difference, and the result predicted by the quantitative correction model established by PLS is reliable.
TABLE 1 PLS model prediction set prediction results
And (3) measuring pectin: inputting 10 original spectra of the paper-making reconstituted tobacco samples to be tested into the quantitative model of the pectin indexes established in the step (5), and determining to obtain pectin; and (3) predicting each sample for 5 times, and simultaneously determining the pectin of the sample by using the standard method in the step (3), wherein the determination results are shown in the following table 2, and it can be seen from the table 2 that the quantitative detection of the reconstituted tobacco product by using the near-infrared diffuse reflection spectrum in the production practice is completely feasible.
TABLE 2 actual sample measurement results
The pectin of the reconstituted tobacco finished product can be quickly and accurately measured by using the model, and the model has important significance for realizing field analysis and monitoring the quality stability and quality fluctuation condition of the reconstituted tobacco product.
In addition, the preprocessing of step (4) is performed by MSC + first order + Norris (3, 5) preprocessing, and is the result of PLS model of the calibration sample set under different spectrum preprocessing, as shown in table 3, where table 3 is the result of PLS model of the calibration sample set under different spectrum preprocessing; as can be seen from Table 1, different spectrum preprocessing methods have different effects on the PLS modeling results, and MSC + first order + Norris (3, 5) has better effect.
TABLE 3 PLS model results under different spectral pretreatment
Note: k is the number of main components, RMSECV is the root mean square cross validation error, RMSEC is the root mean square correction error, MSC is the multivariate scattering correction, SNV is the vector normalization, Norris (a, b) is the Norris derivitive filtering, a is the segment length, b is the segment spacing, Savitzky-Golay (a, b) is the polynomial smoothing method, a is the number of smoothed data points, b is the polynomial power; the first order is the first derivative; the second order is the second derivative.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof 。
Claims (5)
1. The method for measuring pectin of paper-making reconstituted tobacco by using near-infrared diffuse reflection spectroscopy is characterized by comprising the following steps of:
step (1), collecting a sample: collecting and preparing a representative batch of paper-making process reconstituted tobacco products;
step (2), collecting an original spectrum: taking the paper-making reconstituted tobacco products collected in the step (1), crushing each product into powder, uniformly mixing the powder, putting the powder into a sample cup, lightly pressing the sample cup to be flat, wherein the thickness of the sample is more than or equal to 10mm, taking 3 parallel samples for each product, scanning and collecting the spectrum by using a near infrared spectrum technology in a diffuse reflection mode, scanning the spectrum once for each parallel sample, enabling each product to correspond to 3 parallel spectra, averaging the 3 parallel spectra to obtain an original spectrum, and scanning and collecting the spectrum for each reconstituted tobacco product in sequence by adopting the same method to obtain the original spectrum corresponding to each product;
step (3), determining a sample reference value: measuring pectin of the paper-making reconstituted tobacco products collected in the step (1) one by using a standard method to obtain a sample reference value;
and (4) selecting and preprocessing a correction sample set and a verification sample set: selecting a correction sample set and a verification sample set from the original spectrum obtained in the step (2) by adopting a method of standard GB/T29858-2013; then, preprocessing the spectrums in the correction sample set and the verification sample set to eliminate the influence of noise and baseline drift;
step (5), establishing a PLS model: the corrected sample set processed in the step (4) is in one-to-one correspondence with the sample reference values obtained in the step (3), the spectral data and the corresponding pectin determination data are fitted by applying a partial least square method, a quantitative model is established, the abnormal values are detected and removed in the process, the residual spectral values after the abnormal values are removed are in one-to-one correspondence with the obtained sample reference values again, the spectral data and the corresponding pectin determination data are fitted by applying the partial least square method, and a quantitative model of pectin indexes is established;
step (6), model verification: and (5) carrying out external prediction on the pectin index quantitative model established in the step (6) by using the verification sample set processed in the step (4).
2. The method for measuring pectin of paper-making reconstituted tobacco by using the near-infrared diffuse reflection spectroscopy technology according to claim 1, wherein the spectrum collection conditions in the step (2) are as follows: scanning range: 4000cm-1~10000cm-1(ii) a Resolution ratio: 8cm-1(ii) a The number of scans is not less than 72.
3. The method for measuring pectin in paper-making reconstituted tobacco by using a near-infrared diffuse reflection spectroscopy technology according to claim 1, wherein the pretreatment in the step (4) is to perform multivariate scattering correction, first Derivative and Norris derivitive filtering pretreatment on an original spectrum.
4. The method for measuring pectin of paper-making reconstituted tobacco by using the near-infrared diffuse reflection spectroscopy technology according to claim 1, which is characterized by comprising the following steps of: the step (5) of detecting and eliminating the abnormal value adopts a method of detecting a lever value, and specifically comprises the following steps:
the sample lever value was calculated as follows:
wherein,H i the value of the lever of the sample is,t i is a sampleiThe vector of the factors of (a) is,T T Tto model the factor score matrix of the set,is composed oft i Transposing;
when the lever value of a sample is more than 3k/n, wherein k is the number of main components, n is the number of samples, the spectrum of the sample has obvious influence on regression, and the sample is rejected.
5. The method for measuring pectin of paper-making reconstituted tobacco by using the near-infrared diffuse reflection spectroscopy technology according to claim 1, which is characterized by comprising the following steps of: the model verification in the step (6) is to adopt a t-test method to determine whether the predicted value obtained by the quantitative model input in the step (6) of the verification sample set has a statistical deviation with the corresponding sample reference value measured in the step (4): namely, the predicted value of the quantitative model of the pectin index established in the step (6) and the sample reference value t and the degree of freedom d in the step (3) are comparedv-1Critical value t of(a,dv-1)Comparing to obtain the significanceLevel a =0.05, when | t | is < t(a,dv-1)Probability P>And when the time is 0.05, the detection results of the two methods are not obviously different, the model is successfully verified, and the model can be used for measuring the pectin of the paper-making reconstituted tobacco.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510050141.9A CN104596982A (en) | 2015-01-30 | 2015-01-30 | Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510050141.9A CN104596982A (en) | 2015-01-30 | 2015-01-30 | Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104596982A true CN104596982A (en) | 2015-05-06 |
Family
ID=53122903
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510050141.9A Pending CN104596982A (en) | 2015-01-30 | 2015-01-30 | Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104596982A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105021564A (en) * | 2015-08-06 | 2015-11-04 | 云南同创检测技术股份有限公司 | Method for determining content of ergosterol in tobacco based on near infrared spectroscopic analysis technology |
| CN105842190A (en) * | 2016-03-17 | 2016-08-10 | 浙江中烟工业有限责任公司 | Near-infrared model transfer method based on spectral regression |
| CN106644958A (en) * | 2016-11-14 | 2017-05-10 | 浙江大学 | Method for imaging spatial distribution of pectin content in peach fruit |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1828271A (en) * | 2006-03-30 | 2006-09-06 | 将军烟草集团有限公司 | Method for detecting chemical ingredient of tobacco adopting near infrared light |
| US20080094625A1 (en) * | 2006-09-21 | 2008-04-24 | Philip Morris Usa Inc. | Detection of nitrates from tobacco for correlation with the amount of tobacco-specific nitrosamines within the tobacco |
| CN201066339Y (en) * | 2007-07-27 | 2008-05-28 | 浙江大学 | A portable near infrared spectrum instrument for identifying tobacco identity |
| CN101393118A (en) * | 2008-10-30 | 2009-03-25 | 中国烟草总公司郑州烟草研究院 | Method for detecting tobacco tension by utilizing near-infrared spectrum technology |
| CN101393101A (en) * | 2008-10-30 | 2009-03-25 | 中国烟草总公司郑州烟草研究院 | Method for detecting tobacco surface density by near-infrared spectrum |
| CN101710073A (en) * | 2009-12-10 | 2010-05-19 | 云南瑞升烟草技术（集团）有限公司 | Method for detecting physical and chemical indexes of reconstituted tobacco by near infrared spectrum detection paper making method |
| WO2012128281A1 (en) * | 2011-03-22 | 2012-09-27 | 日本たばこ産業株式会社 | Apparent density measuring method |
| CN102706811A (en) * | 2012-05-27 | 2012-10-03 | 红云红河烟草(集团)有限责任公司 | Method for identifying quality of sugar material of cigarette by applying near infrared spectrum analysis technology |
-
2015
- 2015-01-30 CN CN201510050141.9A patent/CN104596982A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1828271A (en) * | 2006-03-30 | 2006-09-06 | 将军烟草集团有限公司 | Method for detecting chemical ingredient of tobacco adopting near infrared light |
| US20080094625A1 (en) * | 2006-09-21 | 2008-04-24 | Philip Morris Usa Inc. | Detection of nitrates from tobacco for correlation with the amount of tobacco-specific nitrosamines within the tobacco |
| CN201066339Y (en) * | 2007-07-27 | 2008-05-28 | 浙江大学 | A portable near infrared spectrum instrument for identifying tobacco identity |
| CN101393118A (en) * | 2008-10-30 | 2009-03-25 | 中国烟草总公司郑州烟草研究院 | Method for detecting tobacco tension by utilizing near-infrared spectrum technology |
| CN101393101A (en) * | 2008-10-30 | 2009-03-25 | 中国烟草总公司郑州烟草研究院 | Method for detecting tobacco surface density by near-infrared spectrum |
| CN101710073A (en) * | 2009-12-10 | 2010-05-19 | 云南瑞升烟草技术（集团）有限公司 | Method for detecting physical and chemical indexes of reconstituted tobacco by near infrared spectrum detection paper making method |
| WO2012128281A1 (en) * | 2011-03-22 | 2012-09-27 | 日本たばこ産業株式会社 | Apparent density measuring method |
| CN102706811A (en) * | 2012-05-27 | 2012-10-03 | 红云红河烟草(集团)有限责任公司 | Method for identifying quality of sugar material of cigarette by applying near infrared spectrum analysis technology |
Non-Patent Citations (2)
| Title |
|---|
| ZI TENG,QIN WANG: "Extraction, identification and characterization of the water-insoluble proteins from tobacco biomass", 《JOURNAL OF SCIENCE OF FOOD AND AGRICULTURE》 * |
| 付秋娟等: "烤烟烟叶平衡含水率的近红外模型", 《江苏农业科学》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105021564A (en) * | 2015-08-06 | 2015-11-04 | 云南同创检测技术股份有限公司 | Method for determining content of ergosterol in tobacco based on near infrared spectroscopic analysis technology |
| CN105842190A (en) * | 2016-03-17 | 2016-08-10 | 浙江中烟工业有限责任公司 | Near-infrared model transfer method based on spectral regression |
| CN105842190B (en) * | 2016-03-17 | 2018-12-11 | 浙江中烟工业有限责任公司 | A kind of method for transferring near infrared model returned based on spectrum |
| CN106644958A (en) * | 2016-11-14 | 2017-05-10 | 浙江大学 | Method for imaging spatial distribution of pectin content in peach fruit |
| CN106644958B (en) * | 2016-11-14 | 2019-04-05 | 浙江大学 | A kind of method of Peach fruits inside pectin content spatial distribution imaging |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101915744B (en) | Near infrared spectrum nondestructive testing method and device for material component content | |
| CN103018195B (en) | Method for determination of PCTFE content in PBX explosive by near infrared spectrum | |
| CN104596975A (en) | Method for measuring lignin of reconstituted tobacco by paper-making process by virtue of near infrared reflectance spectroscopy technique | |
| CN104596979A (en) | Method for measuring cellulose of reconstituted tobacco by virtue of near infrared reflectance spectroscopy technique | |
| CN107703097B (en) | Method for constructing model for rapidly predicting crude oil property by using near-infrared spectrometer | |
| CN109085136B (en) | Method for measuring content of oxide components in cement raw material by near-infrared diffuse reflection spectrum | |
| CN101413885A (en) | Near-infrared spectrum method for rapidly quantifying honey quality | |
| CN104020127A (en) | Method for rapidly measuring inorganic element in tobacco by near infrared spectrum | |
| CN104749132A (en) | Method for measuring content of azodicarbonamide in flour | |
| CN104596976A (en) | Method for determining protein of paper-making reconstituted tobacco through ear infrared reflectance spectroscopy technique | |
| CN102937575B (en) | Watermelon sugar degree rapid modeling method based on secondary spectrum recombination | |
| CN104596980A (en) | Method for measuring hot water solvends of reconstituted tobacco by paper-making process by virtue of near infrared reflectance spectroscopy technique | |
| CN110749565A (en) | Method for rapidly identifying storage years of Pu' er tea | |
| CN114088661A (en) | Online prediction method for chemical components in tobacco leaf curing process based on transfer learning and near infrared spectrum | |
| CN104568828A (en) | Method for determining tensile strength of reproduced tobacco leaves of papermaking method by near-infrared diffuse reflection spectrum | |
| CN104596982A (en) | Method for measuring pectin of paper-making reconstituted tobacco by near-infrared diffuse reflection spectrum technology | |
| CN105738311A (en) | Apple sweetness non-damage quick detection method based on near-infrared spectrum technology | |
| CN107991265A (en) | A kind of wheat flour Rubus biflorus Buch quick determination method based on information fusion | |
| CN105954228A (en) | Method for measuring content of sodium metal in oil sand based on near infrared spectrum | |
| CN110210005A (en) | A kind of spectrum wave number selection method of no reference value | |
| CN111141809B (en) | Soil nutrient ion content detection method based on non-contact type conductivity signal | |
| CN104596978A (en) | Method for determining quantitative physical indexes of paper-making tobacco sheet by virtue of near-infrared reflectance spectroscopy | |
| CN104596974A (en) | Method for measuring paper process reconstituted tobacco filling value via near infrared diffuse reflection spectroscopy | |
| CN107238557A (en) | A kind of method of utilization near infrared spectroscopy quick detection calcium carbonate particle diameter distribution | |
| CN115436315A (en) | Near infrared spectrum-based cement additive detection method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150506 |
|
| RJ01 | Rejection of invention patent application after publication |