Quantitative analysis of routine chemical constituents in tobacco by near-infrared spectroscopy and support vector machine

Zhang, Yong; Cong, Qian; Xie, Yunfei; JingxiuYang,; Zhao, Bing

doi:10.1016/j.saa.2008.04.020

Cited by 102 publications

(41 citation statements)

References 17 publications

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“…These routine chemical components, such as total sugar, are often used as indices to evaluate tobacco qualities (Zhang et al 2008). However, their detections are, in most cases, laborious and time-consuming, requiring harmful reagents and involving expensive equipment with high operation and=or maintenance costs.…”

Section: Introductionmentioning

confidence: 99%

Determination of Total Sugar in Tobacco by Near-Infrared Spectroscopy and Wavelet Transformation-Based Calibration

Tan

Chen

et al. 2013

Analytical Letters

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Based on wavelet transformation (WT) and mutual information (MI), a simple and effective procedure is proposed for multivariate calibration of near-infrared spectroscopy. In such a procedure, the original spectra of the training set are first transformed into a set of wavelet representations by wavelet prism transform. Then, the MI value between each wavelet coefficient variable and the dependent variable is calculated, resulting in a MI spectrum; by retaining a subset set of coefficients with higher MI, an update training set consisting of wavelet coefficients is obtained and reconstructed/converted back to the original domain. Based on this, a partial least square (PLS) model can be constructed and optimized. The optimal wavelet and decomposition level are determined by experiment. A NIR quantitative problem involving the determination of total sugar in tobacco is used to demonstrate the overall performance of the proposed procedure, named RPLS, meaning PLS in reconstructed original domain coupled with MI-induced variable selection in wavelet domain (RPLS). Three kinds of procedures, that is, conventional full-spectrum PLS in original domain (FPLS), PLS in original domain coupled with MI-induced variable selection (OPLS), and direct PLS in MI-based wavelet coefficients (WPLS), are used as reference. The result confirms that it can build more accurate and robust calibration models without increasing the complexity.

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Section: Introductionmentioning

confidence: 99%

Determination of Total Sugar in Tobacco by Near-Infrared Spectroscopy and Wavelet Transformation-Based Calibration

Tan

Chen

et al. 2013

Analytical Letters

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“…For cigarette brand discrimination, most of research works combined NIR technique and pattern recognition approaches [12], [13]. Zhang et al [14] applied partial least squares regression (PLSR), ANN, and support vector machine (SVM) to determine routine chemical of constituents of tobacco. SVM, originally proposed by Vapnik [15], is a powerful technique for pattern recognition, classification and regression.…”

Section: Introductionmentioning

confidence: 99%

A support vector machine discriminator for tobacco growing areas based on near-infrared spectrum

Xie

Panwenjie

Yang

2012

2012 IEEE International Conference on Automation and Logistics

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The tobacco growing area is of great importance in the quality control of cigarette, because the fragrance of tobacco leaves would be divergent for different climates planting environments. Currently, most of discrimination processes are manually operated, which are time-consuming and inevitably limited by the subjective evaluation. In this paper, an automatic growing area discrimination method is presented based on tobacco nearinfrared (NIR) spectrum using support vector machine (SVM). The Savitzky-Golay smoothing method and principle component analysis are used for tobacco NIR spectra preprocessing. A SVM model is established to investigate the characteristics of growing areas. The developed SVM classifier produces the best prediction accuracy of 80.3% in testing subset with 14 principle components as the inputs. It is 6% and 2% higher than that of artificial neuron network and Mahalanobia distance model respectively, which were developed for comparison. It demonstrates the effectiveness and robustness of SVM for growing area discrimination. The prediction ability for each growing region is further analyzed by the measurements derived from confusion matrix, such as true positive rate, true negative rate, positive predictive value and F1 score. The SVM setting is also discussed with respect to prediction accuracy of validation.

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“…Depending on the available samples and the intended application a satisfactory discrimination of various tobacco samples has 0304-3894/$ -see front matter © 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.jhazmat.2010.08.126 been reported [8][9][10][11][12], especially with regards to the identification of cultivation areas [8,10], tobacco varieties [13] or different commercial tobacco brands [9,14,15].…”

Section: Introductionmentioning

confidence: 99%

“…Although this problem could be amortized by transferring the calibrations from the master instrument to several slaves, no specific methodology has yet gained widespread acceptance due to optical differences between the instruments [17]. As a result different calibration procedures are required depending on the available training data set and the intended application [8][9][10][11][12][13][14][15]. Although these procedures are efficient, they significantly increase the computational effort and in several occasions require too sophisticated statistical techniques which are not always available in commercial statistical software.…”

Section: Introductionmentioning

confidence: 99%

Multivariate chemometric discrimination of cigarette tobacco blends based on the UV–Vis spectrum of their hydrophilic extracts

Giokas¹,

Thanasoulias²,

Vlessidis³

2011

Journal of Hazardous Materials

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Quantitative analysis of routine chemical constituents in tobacco by near-infrared spectroscopy and support vector machine

Cited by 102 publications

References 17 publications

Determination of Total Sugar in Tobacco by Near-Infrared Spectroscopy and Wavelet Transformation-Based Calibration

Determination of Total Sugar in Tobacco by Near-Infrared Spectroscopy and Wavelet Transformation-Based Calibration

A support vector machine discriminator for tobacco growing areas based on near-infrared spectrum

Multivariate chemometric discrimination of cigarette tobacco blends based on the UV–Vis spectrum of their hydrophilic extracts

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