Analysis of tobacco color and location features using visible-near infrared hyperspectral data.

In the present paper, six categories of standard industrial grading tobacco provided by Hongta Group are taken as experimental samples, including three different tobacco locations-upper (B), middle(C) and lower(X) parts, with each part containing two kinds of tobacco colors-orange (O) and lemon yellow (L). Two methods including projection model method based on principal component and Fisher criterion (PPF) and support vector machine (SVM) method are used to analyze color and location features of tobacco based on visible-near infrared hyperspectral data. The results of projection model method indicate that in the projection and similarity analysis of tobacco color, location and six tobacco groups classified by color and location, two kinds of color can be fully differentiated, of which the similarity value is -1.000 8. Tobacco from upper and lower parts can also be fully differentiated with similarity value 0.405 3, but they both have intersections with tobac- co from middle part. Six tobacco groups classified by color and location can be fully differentiated as well and their projection positions meet the actual external features of tobacco. The results of support vector machine method indicate that in the discriminant analysis of tobacco color, location and six tobacco groups classified by color and location, the average recognition rate of tobacco colors reaches 98%. The average recognition rate of tobacco location is 96%. The average recognition rate of six tobacco groups is 94%. Therefore, it's feasible to analyze color and location features of tobacco using visible-near infrared hyperspectral data, which can provide reference for tobacco quality evaluation, computer-aided grading and tobacco intelligent acquisition, and also offers a new approach to the analysis of exterior features of other agricultural products.

[Near infrared spectroscopy and multivariate statistical process analysis for real-time monitoring of production process].

Near infrared diffusive reflectance spectroscopy has been applied in on-site or on-line analysis due to its characteristics of fastness, non-destruction and the feasibility for real complex sample analysis. The present work reported a real-time monitoring method for industrial production by using near infrared spectroscopic technique and multivariate statistical process analysis. In the method, the real-time near infrared spectra of the materials are collected on the production line, and then the evaluation of the production process can be achieved by a statistic Hotelling T2 calculated with the established model. In this work, principal component analysis (PCA) is adopted for building the model, and the statistic is calculated by projecting the real-time spectra onto the PCA model. With an application of the method in a practical production, it was demonstrated that a real-time evaluation of the variations in the production can be realized by investigating the changes in the statistic, and the comparison of the products in different batches can be achieved by further statistics of the statistic. Therefore, the proposed method may provide a practical way for quality insurance of production processes.

[Tobacco quality analysis of producing areas of Yunnan tobacco using near-infrared (NIR) spectrum].

In the present study, tobacco quality analysis of different producing areas was carried out applying spectrum projection and correlation methods. The group of industrial classification data was near-infrared (NIR) spectrum in 2010 year of middle parts of tobacco plant from Hongta Tobacco (Group) Co., Ltd. Twelve hundred seventy six superior tobacco leaf samples were collected from four producing areas, in which three areas from Yuxi, Chuxiong and Zhaotong, in Yunnan province all belong to tobacco varieties of K326 and one area from Dali belongs to tobacco varieties of Hongda. The conclusion showed that when the samples were divided into two parts by the ratio of 2 : 1 randomly as analysis and verification sets, the verification set corresponded with the analysis set applying spectrum projection because their correlation coefficients by the first and second dimensional projection were all above 0.99. At the same time, The study discussed a method to get the quantitative similarity values of different producing areas samples. The similarity values were instructive in tobacco plant planning, quality management, acquisition of raw materials of tobacco and tobacco leaf blending.

[Study of selecting characteristic wavelengths in qualitative analysis of near infrared spectroscopy].

The present article proposed a method of stepwise selecting characteristic wavelengths based on minimum sum of correlation coefficients (SMCC). The maximization of the ratio of inter-class Euclidean distance to the sum of inner-class Euclidean distances was used as evaluation basis in qualitative analysis of near infrared spectroscopy. Seventeen kinds of grading tobacco leaf in 2012, provided by Hongta Group, were used as experimental samples to verify the effectiveness of this new method. CO1 was selected as the reference category and ten points were selected as characteristic wavelengths. The results indicated that the average value of inner-class Euclidean distance, calculated by characteristic wavelengths, was 1.69 times as large as that calculated by all wavelengths. The average value of inter-class Euclidean distance, calculated by characteristic wavelengths, was 3.70 times as large as that calculated by all wavelengths. The average value of the ratio of inter-class Euclidean distance to the sum of inner-class Euclidean distances, calculated by characteristic wavelength, was 2.21 times as large as that calculated by all wavelengths. The ratio of characteristic wavelengths was increased. The characteristic wavelengths can express the classical differences. It was showed that SMCC was an effective way to select characteristic wavelengths in qualitative analyses of near infrared spectroscopy.

[Research on characteristic of tobaccos from different ecological environments base on near infrared spectroscopy].

Four hundred ninety five samples from 3 parts of tobacco were collected from 11 different ecological environments in 2010 to analyze the characteristics of tobaccos in different ecological environments with near infrared spectroscopy. The results indicate that the differences are remarkable both between lower and upper parts and between lower and middle parts of tobacco, while negligible between upper and middle parts of tobacco under the same ecological environment. Good stability and consistency were showed by the similarity of characteristics of tobaccos under different ecological environments, and the projection correlation coefficient of analysis set and validation set is over 98%. This article also proposes a method of measuring the similarity between characteristics of tobaccos from different ecological environments. The results can provide reference data to quantify tobacco's planting programming, production processing and quality management.

[Tobacco quality analysis of industrial classification of different years using near-infrared (NIR) spectrum].

In this study, tobacco quality analysis of main Industrial classification of different years was carried out applying spectrum projection and correlation methods. The group of data was near-infrared (NIR) spectrum from Hongta Tobacco (Group) Co., Ltd. 5730 tobacco leaf Industrial classification samples from Yuxi in Yunnan province from 2007 to 2010 year were collected using near infrared spectroscopy, which from different parts and colors and all belong to tobacco varieties of HONGDA. The conclusion showed that, when the samples were divided to two part by the ratio of 2:1 randomly as analysis and verification sets in the same year, the verification set corresponded with the analysis set applying spectrum projection because their correlation coefficients were above 0.98. The correlation coefficients between two different years applying spectrum projection were above 0.97. The highest correlation coefficient was the one between 2008 and 2009 year and the lowest correlation coefficient was the one between 2007 and 2010 year. At the same time, The study discussed a method to get the quantitative similarity values of different industrial classification samples. The similarity and consistency values were instructive in combination and replacement of tobacco leaf blending.

[Tobacco quality analysis of industrial classification of different producing area using near-infrared (NIR) spectrum].

In this study, tobacco quality analysis of industrial classification of different producing area was carried out applying spectrum projection and correlation methods. The group of industrial classification data was near-infrared (NIR) spectrum in 2010 year from different tobacco plant parts and colors of Hongta Tobacco (Group) Co., Ltd. 6 064 tobacco leaf samples of 17 classes from Yuxi, Chuxiong and Zhaotong, in Yunnan province and 6 industrial classifications were collected using near infrared spectroscopy, which from different parts and colors and all belong to tobacco varieties of K326. The conclusion showed that, the probability of the grading belonging by the first dimension was 84%, the probability of the producing area belonging by the second dimension was 71%. The study can explain the difference of tobacco quality of industrial classification and producing area by a projection method to get the quantitative similarity values. The quantitative similarity values were instructive in combination of tobacco leaf blending.

[The highest proportion of tobacco materials in the blend analysis using PPF projection method for the near-infrared spectrum and Monte Carlo method].

The present paper builds a model based on Monte Carlo method in the projection of the blending tobacco. This model is made up of two parts: the projecting points of tobacco materials, whose coordinates are calculated by means of the PPF (projection based on principal component and Fisher criterion) projection method for the tobacco near-infrared spectrum; and the point of tobacco blend, which is produced by linear additive to the projecting point coordinates of tobacco materials. In order to analyze the projection points deviation from initial state levels, Monte Carlo method is introduced to simulate the differences and changes of raw material projection. The results indicate that there are two major factors affecting the relative deviation: the highest proportion of tobacco materials in the blend, which is too high to make the deviation under control; and the quantity of materials, which is so small to control the deviation. The conclusion is close to the principle of actual formulating designing, particularly, the more in the quantity while the lower in proportion of each. Finally the paper figures out the upper limit of the proportions in the different quantity of materials by theory. It also has important reference value for other agricultural products blend.

[Tobacco plant parts similarity analysis based on near-infrared spectroscopy and SIMCA algorithm].

The appearance features of tobacco reflect its inner quality. Many factors, such as different plant parts, variety and maturity, provide standard and foundation for tobacco production processing. According to the different position of tobacco plant parts, tobacco plants leaves can be divided into five parts as tip, upper-middle, middle, lower-middle and priming leaf respectively. Five hundred tobacco leaf samples (100 each for one of five tobacco plant parts) from Yunnan province in 2008 were collected using near infrared spectroscopy, which all belong to tobacco varieties of K326. The similarity analysis of tobacco plant parts was carried out using mathematical model of SIMCA similarity analysis. The conclusion showed that the tobacco plant parts similarity results based on near-infrared spectroscopy corresponded to the relative tobacco plant parts in Yunnan province. The farther two tobacco plant parts were away from each other, the lower the similarity of corresponding parts was. And the similarity results of adjacent tobacco plant parts were different. The study discussed a method of confirming PC numbers and realized the quantitative similarity analysis between classes. It is instructive in replacement or adjustment of tobacco leaf blending and evaluation of tobacco industrial grading.

[The application of near-infrared diffuse reflection spectra based on the principle of linear additive in tobacco redrying formula].

In the process of analyzing and designing tobacco redrying formula using near infrared spectroscopy, a great deal of spectra for different ratio mixed samples are badly needed. However these sample spectra are very hard to obtain in the actual production process. Furthermore, for the samples of different grades it is difficult to achieve the goal of even mixing, in consequence of introducing inevitable errors. In order to solve the above problems, the present paper proposes to use "theory of even mixed spectrum" produced by linear additive near infrared spectroscopy in place of the spectra of actual mixed samples. This way can not only eliminate the errors caused by uneven mixture, but also leave out the course of mixing samples and measuring spectra and save time, effort, and material simultaneously. This article analyzes the comparison between linear additive spectra and the spectra of actual mixed samples from the following four aspects: original spectra, derivative spectra, principal components, and the data of PPF projection, accordingly verifing the feasibility and superiority of the linear additive spectra.

[Study on the projection method based on principal component of tobacco near-infrared spectrum and application in redrying model].

The present paper briefly describes the application of near-infrared spectroscopy technology in tobacco. Two methods for solving projection vector based on the principal component of near-infrared spectrum are reported. They are named as projection of basing on principal component and Fisher criterion by principal component analysis method (PPF_PCA for short) and projection of basing on principal component and Fisher criterion by solving eigenvalue (PPF_Eig for short), and they are studied and compared in the application and evaluation of the redrying model. The result of the first-dimensional projection on 9 kinds of tobacco leaf grading samples shows that, the diversity of the first-dimensional projection values of inter-class and intra-class by the PPF_PCA method is both larger than that by the PPF_Eig method, and the mean absolute deviation of the mean projection values of inter-class by the PPF_PCA method is about 1.26 times that of the PPF_Eig method. At the same time, this result is interpreted by using the contribution rate of the first-dimensional projection values. That is, the contribution rate of first-dimensional projection values by the PPF_PCA method is 93%, while the contribution rate of first-dimensional projection values by the PPF_Eig method is 77%. The former is about 1.21 times the later. Therefore, the first-dimensional projection values by PPF PCA method include more information of diversity of both inter-class and intra-class. The similarity of samples inter-class and the diversity of samples intra-class can be evaluated more objectively from first-dimensional projection figure(on 9 kinds of tobacco leaf grading samples, 33 kinds of tobacco leaf grading samples and 6 redrying blending models), so it is more convenient to be used as a reference for the redrying model of tobacco, and it has a good application prospect in other formulation design of agricultural products (traditional Chinese medicine etc.).

[Determination of chemical components in tobacco leaves by FT-NIR spectroscopy: study of influence of spectral ranges on PLS modeling].

NIR spectra of tobacco leaves were measured in the range of 12000 to 4000 cm(-1) using a Bruker MPA FT-NIR spectrometer. PLS calibration models were developed and optimized for rapid quantitative analysis of nicotine alkaloids, total sugar and total nitrogen contents in tobacco leaves. It was found that the prediction errors of the same component were significantly different when different spectral regions were used for PLS modeling, and the best spectral range is also different for each component. The study demonstrated that wavelength range selection is one of the important keys to optimizing the NIR calibration model. In this study it was found that the optimized calibration ranges for nicotine alkaloids, total sugar and total nitrogen are 9500-4231.2 cm(-1), 7502.1-4246.7 cm(-1) and 7502.1-4597.7 cm(-1), respectively. The Root Mean Square Error of Cross Validation (RMSECV) of the three calibration models are 0.081 5, 0.808 and 0.056, respectively.