Ma H.,Chongqing Tobacco Quality Supervision & Test Station |
Wang Z.,Chongqing Tobacco Quality Supervision & Test Station |
Yuan T.,Yunnan COMTESTOR Co. |
Zhao K.,Chongqing Tobacco Quality Supervision & Test Station |
And 5 more authors.
Tobacco Science and Technology | Year: 2015
In order to improve the prediction precision of calibration model, the near infrared spectroscopy (NIR) calibration model for the starch in tobacco was studied. Spectral variables were chosen by means of full spectrum (FS) and variance spectrum (VS), spectral wavelength by means of genetic algorithm (GA), via partial least squares, the calibration models, FS+PLS, VS+PLS and GA+PLS, were established, and the starch contents in 100 flue-cured tobacco samples were predicted. The results showed that: 1) Rc2 and root mean squares error of cross validation (RMSECV) of the three models, FS+PLS (1 557 variables), VS+PLS (781 variables) and GA+PLS (72 variables) were 0.976 4 and 0.433, 0.987 1 and 0.332, 0.988 5 and 0.314, respectively. 2) Comparing with FS+PLS and VS+PLS, the number of variables in GA+PLS was 4.62% and 9.22% of that in FS and VS, its main factor number reduced from 15 to 12, Rc2 increased from 0.976 4 to 0.988 5, and RMSECV decreased from 0.433 to 0.314. 3) The predicted results of starch contents in 100 tobacco samples indicated that, Rp2 and RMSEP of FS+PLS, VS+PLS and GA+PLS models were 0.965 2 and 0.780, 0.984 3 and 0.501, 0.985 3 and 0.496, respectively. The paired T test between the prediction values and the test values was performed, the Sig. value, T value and average relative error (%) were 0.271, 1.107 and 17.48% for FS+PLS, 0.973, 0.034 and 13.13% for VS+PLS, 0.722, 0.357 and 13.12% for GA + PLS, respectively. There were no significant differences between the results predicted by the three methods and the corresponding test values. The RSD values of FS + PLS, VS + PLS and GA + PLS were 10.34%, 6.98% and 4.76%, respectively. The prediction precision of GA+PLS model was better than that of FS+PLS and VS+PLS models. This method provides a reference for improving the precision of prediction model for a complex chemical system. ©, 2015, Editorial Office of Tobacco Science and Technology. All right reserved.
Li W.,Yunnan Comtestor Co. |
Qian Q.,HongyunHonghe Tobacco Group Co. |
Yang P.,Yunnan Comtestor Co. |
Yang Y.,Yunnan Comtestor Co.
Tobacco Science and Technology | Year: 2014
To effectively monitor the quality of blend modules during cigarette manufacturing via near infrared spectroscopy combined with chemometrics, Hotelling T2 statistics were derived from the established categorized models for principal components of blend modules and used to monitor the samples before and after blend modifying. The Hotelling T2 statistics of 150 samples before blend modification were of 95% confidence interval (Hotelling T2=22.70), the 50 samples of modified blends were of 99% confidence interval (Hotelling T2=28.16). The contents of nicotine, total nitrogen and total sugar in samples before and after blend modification were predicted with the established calibration model, the results indicated that the contents of nicotine, total nitrogen and total sugar in the 150 samples of unmodified blends were within the quality control limits of M±3S, while those in the 50 samples of modified blends all exceeded the limits of M±3S. The method is capable of monitoring the quality consistency and uniformity of blend modules and predicting the variation of chemical component contents in blend modules.
Yang L.,Kunming University of Science and Technology |
Yang L.,Yunnan Comtestor Co. |
Yang Q.-X.,China Tobacco Yunnan Industrial Co. |
Yang S.-H.,Yunnan Comtestor Co. |
And 5 more authors.
Journal of Near Infrared Spectroscopy | Year: 2015
Mould infection is a significant postharvest issue for processors of tobacco, which can cause direct product loss and value reduction of product as well as serious economic losses. However, mould mostly is undetectable at the early stages using traditional sorting techniques. In this study, near infrared (NIR) spectroscopy was used to detect mould infection in flue-cured tobacco samples. Based on visual analysis grading a good to bad (GBA) algorithm for feature selection of NIR spectra and linear discriminant analysis routines were applied to detect mould contamination. The optimal wavelengths of NIR spectra included bands at 1066 nm, 1130 nm, 1832 nm and 1474 nm which were applied to establish a classification model which achieved a low classification error rate (2.92% with a Wilks's l of 0.216 at P < 0.001). The classification accuracies of unmould and mould were 94.6% and 96.9%, respectively (100.0% for slight mould, 100.0% for low mould, 95.0% for medium mould and 92.9% for high mould). A sorting system was developed based on multispectral NIR bands. This showed rapid, accurate and effective detection, and identification of mould-contaminated tobacco was possible at early stages of mould contamination, making it possible to remove mould-contaminated tobacco found in tobacco lots. © IM Publications LLP 2015.
Gong X.,Yunnan University |
Ma G.,Yunnan University |
Ma G.,Yunnan Comtestor Co. |
Zhang K.-Q.,Yunnan University |
Yang J.,Yunnan University
World Journal of Microbiology and Biotechnology | Year: 2016
Nicotine in tobacco is harmful to health and the environment, so there is an environmental requirement to remove nicotine from tobacco and tobacco wastes. In this study, the biotransformation of nicotine by Rhodococcus sp. Y22 was investigated, and three metabolites (NIC1, NIC4 and NIC5) were isolated by column separation, preparative TLC and solid plate’s method, respectively. NIC1 was identified as 6-hydoxynicotine based on the results of NMR, MS, HPLC–UV and HRESIMS analysis; NIC4 was a novel compound and identified as 5-(3-methyl-[1,3]oxazinan-2-ylidene)-5H-pyridin-2-one based on the results of NMR, MS and UV analysis; NIC5 was identified as nicotine blue based on the results of NMR and MS analysis. Meanwhile, two metabolites NIC2 and NIC3 were identified as 6-hydroxy-N-methylmyosmine and 6-hydroxypseudooxynicotine by HRESIMS analysis, respectively. According to these metabolites, the possible pathway of nicotine degradation by Rhodococcus sp. Y22 was proposed. The nicotine can be transformed to nicotine blue through two pathways (A and B), and 6-hydroxy-N-methylmyosmine is the key compound, which can be converted to 6-hydroxypseudooxynicotine (pathway A) and 5-(3-methyl-[1,3]oxazinan-2-ylidene)-5H-pyridin-2-one (pathway B), respectively. Moreover, the encoding gene of nicotine dehydrogenase, ndh, was amplified from Rhodococcus sp. Y22, and its transcriptional level could be up-regulated obviously under nicotine induction. Our studies reported the key metabolites and possible biotransformation pathway of nicotine in Rhodococcus sp. Y22, and provided new insights into the microbial metabolism of nicotine. © 2016, Springer Science+Business Media Dordrecht.
Liu J.,Tobacco Company of Chongqing |
Ma G.,Yunnan Comtestor Co. |
Chen T.,Tobacco Company of Chongqing |
Hou Y.,Yunnan Comtestor Co. |
And 3 more authors.
Applied Microbiology and Biotechnology | Year: 2015
Nicotine-degrading microorganisms (NDMs) are a special microbial group which can use nicotine as the sole carbon and nitrogen source for growth. Since the 1950s, the bioconversion of nicotine by microbes has received increasing attention, and several NDMs have been identified, such as Arthrobacter nicotinovorans, Microsporum gypseum, Pellicularia filamentosa JTS-208, and Pseudomonas sp. 41. In recent years, increasing numbers of NDMs have been isolated and identified from tobacco plantation soil, leaf, and tobacco waste. Meanwhile, the metabolic pathway and degradation mechanism of nicotine have been elucidated in several NDMs, such as A. nicotinovorans, Agrobacterium tumefaciens S33, Aspergillus oryzae, and Pseudomonas putida S16. Moreover, several NDMs have been used in improving the quality of cigarettes, treating tobacco waste, and producing valuable intermediates of nicotine. Here, we summarize the diversity, phylogenetic analysis, and potential applications of NDMs. © 2015, Springer-Verlag Berlin Heidelberg.
Li W.,Yunnan Comtestor Co. |
Yuan T.J.,Yunnan Reascend Tobacco Technology Group Coltd |
Wang Y.,Yunnan Comtestor Co. |
Hou Y.,Yunnan Comtestor Co.
Advanced Materials Research | Year: 2013
Greedy algorithms represented by orthogonal matching pursuit (OMP) and subspace pursuit (SP) algorithms are practically used in image processing based upon compressed sensing theory. However, there are two disadvantages: 1)Relatively poor signal reconstruction accuracy; 2) High computation complexity and measurements time. This paper proposes a frame of greedy algorithms obtaining a novel fusion of matching pursuit (FMP), combining the OMP and SP algorithms. FMP unites the two support sets from OMP and SP selecting the most appropriate atoms to achieve secondary screening of the original two support sets, finally realizing the accurate signal reconstruction. Using same test conditions, image reconstruction experiments and stability of Frame, the proposed FMP algorithm can effectively improve signal-to-noise ratio (SNR) with improved reconstruction error. Reconstruction effects using proposed FMP are better than separately using other two greedy algorithms for both high and low resolution images. © (2013) Trans Tech Publications, Switzerland.