| 光谱学与光谱分析 |
|
|
|
|
|
| Quality Anlysis of the before Redrying Raw Tobacco & after Redrying Sheet Tobacco by Using Online Near Infrared Spectroscopy |
| TANG Zhao-qi1, LIU Ying2, SHU Ru-xin1, YANG Kai1, ZHAO Long-lian2, ZHANG Lu-da3, ZHANG Ye-hui2, LI Jun-hui2* |
1. Technology Center of Shanghai Tobacco (Group) Corporation, Shanghai 200081, China
2. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
3. College of Science, China Agricultural University, Beijing 100083, China |
|
|
|
|
Abstract In this paper, the 7 different origin before redrying raw tobacco & after redrying sheet tobacco’s online near infrared spectroscopy were collected from sorting & redrying production line specifically for “ZHONGHUA” brand. By using the projection model bulit by different origin tobacco’s online spectroscopy and the method of variance and correlation analysis, we studied the uniformity and similarity quality characteristics change before and after the redrying of tobacco, which can provide support for understanding the quality of the tobacco material and cigarette product formulations. This study show that selecting about 10 000 by equally spaced sampling time from a huge number of online near infrared spectroscopy, for modeling are feasible, and representative. After manual sorting, threshing, and redrying, the uiformity of each origin tobacco near-infrared spectroscopy can be increased by 10%～35%，homogeneity of the tobacco leaf has been significantly improved. After redrying, the similar relationship embodied in the origin also have significant changes, overall it reduce significantly, that shows the quality differences embodied by origin significantly improve, which can provide greater space for formulations, it shows the need for high-quality Chinese cigarette production requires large amounts of financial and human resources to implement cured tobacco processing. The traditional means of chemical analysis, it takes a lot of time and effort, it is difficult to control the entire processing chain, Near Infrared Spectroscopy with its rapid, non-destructive advantage, not only can achieve real-time detection and quality control, but also can take full advantage of near-infrared spectroscopy information created in the production process, which is a very promising online analytical detection technology in many industries especially in the agricultural and food processing industries.
|
|
Received: 2013-12-17
Accepted: 2014-04-05
|
|
|
|
Corresponding Authors:
LI Jun-hui
E-mail: caunir@cau.edu.cn
|
|
[1] Kari Aaljoki. Journal of Automated Methods & Management in Chemistry, 2005, (2): 44.
[2] Aernouts B, Polshin E, Lammertyn J, et al. American Dairy Science Association, 2011, 94(11): 5315.
[3] YAN Yan-lu, ZHAO Long-lian, HAN Dong-hai, et al(严衍禄, 赵龙莲，韩东海，等). Basis and Application of Near Infrared Spectroscopy(近红外光谱分析基础与应用). Beijing：China Light Industry Press(北京：中国轻工业出版社), 2005.
[4] Liu Jingjing, Ma Xiang, Wen Yadong, et al. Industrial & Engineering Chemistry Research, 2011, 50(12): 7677.
[5] YANG Kai, LIU Peng, WANG Wei-miao, et al(杨 凯，刘 鹏，王维妙). Acta Tabacaria Sinica(中国烟草学报) , 2012, 18(6)：27.
[6] WANG Bao-xing, ZOU Zhen-min, LIU Wei-juan, et al(王保兴，邹振民，刘伟娟，等). Tobacco Science & Technology(烟草科技)，2011, (1): 48.
[7] MA Xiang, WEN Ya-dong, WANG Yi，et al(马 翔，温亚东，王 毅，等). Tobacco Science & Technology(烟草科技), 2006, (1): 22.
[8] Duan Jia，Huang Yue，Li Zuhong, et al. Industrial Crops and Products，2012, 40(11): 21.
[9] Jing Ming, Cai Wensheng, Shao Xueguang. Analytical Letters, 2010, 43: 1910.
[10] WEN Ya-dong, WANG Yi, WANG Neng-ru, et al(温亚东，王 毅，王能如，等). Acta Tabacaria Sinica(中国烟草学报), 2009, 15(5)：6.
[11] WANG Yi, MA Xiang, WEN Ya-dong, et al(王 毅，马 翔，温亚东，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2012, 32(11)：3014. |
| [1] |
GAO Feng1, 2, XING Ya-ge3, 4, LUO Hua-ping1, 2, ZHANG Yuan-hua3, 4, GUO Ling3, 4*. Nondestructive Identification of Apricot Varieties Based on Visible/Near Infrared Spectroscopy and Chemometrics Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 44-51. |
| [2] |
LIU Jia, ZHENG Ya-long, WANG Cheng-bo, YIN Zuo-wei*, PAN Shao-kui. Spectra Characterization of Diaspore-Sapphire From Hotan, Xinjiang[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 176-180. |
| [3] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [4] |
HE Qing-yuan1, 2, REN Yi1, 2, LIU Jing-hua1, 2, LIU Li1, 2, YANG Hao1, 2, LI Zheng-peng1, 2, ZHAN Qiu-wen1, 2*. Study on Rapid Determination of Qualities of Alfalfa Hay Based on NIRS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3753-3757. |
| [5] |
HU Cai-ping1, HE Cheng-yu2, KONG Li-wei3, ZHU You-you3*, WU Bin4, ZHOU Hao-xiang3, SUN Jun2. Identification of Tea Based on Near-Infrared Spectra and Fuzzy Linear Discriminant QR Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3802-3805. |
| [6] |
LIU Xin-peng1, SUN Xiang-hong2, QIN Yu-hua1*, ZHANG Min1, GONG Hui-li3. Research on t-SNE Similarity Measurement Method Based on Wasserstein Divergence[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3806-3812. |
| [7] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [8] |
WANG Qi-biao1, HE Yu-kai1, LUO Yu-shi1, WANG Shu-jun1, XIE Bo2, DENG Chao2*, LIU Yong3, TUO Xian-guo3. Study on Analysis Method of Distiller's Grains Acidity Based on
Convolutional Neural Network and Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3726-3731. |
| [9] |
LUO Li, WANG Jing-yi, XU Zhao-jun, NA Bin*. Geographic Origin Discrimination of Wood Using NIR Spectroscopy
Combined With Machine Learning Techniques[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3372-3379. |
| [10] |
ZHANG Shu-fang1, LEI Lei2, LEI Shun-xin2, TAN Xue-cai1, LIU Shao-gang1, YAN Jun1*. Traceability of Geographical Origin of Jasmine Based on Near
Infrared Diffuse Reflectance Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3389-3395. |
| [11] |
YANG Qun1, 2, LING Qi-han1, WEI Yong1, NING Qiang1, 2, KONG Fa-ming1, ZHOU Yi-fan1, 2, ZHANG Hai-lin1, WANG Jie1, 2*. Non-Destructive Monitoring Model of Functional Nitrogen Content in
Citrus Leaves Based on Visible-Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3396-3403. |
| [12] |
ZHU Hua-dong1, 2, 3, ZHANG Si-qi1, 2, 3, TANG Chun-jie1, 2, 3. Research and Application of On-Line Analysis of CO2 and H2S in Natural Gas Feed Gas by Laser Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3551-3558. |
| [13] |
HUANG Meng-qiang1, KUANG Wen-jian2, 3*, LIU Xiang1, HE Liang4. Quantitative Analysis of Cotton/Polyester/Wool Blended Fiber Content by Near-Infrared Spectroscopy Based on 1D-CNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3565-3570. |
| [14] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [15] |
KANG Ming-yue1, 3, WANG Cheng1, SUN Hong-yan3, LI Zuo-lin2, LUO Bin1*. Research on Internal Quality Detection Method of Cherry Tomatoes Based on Improved WOA-LSSVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3541-3550. |
|
|
|
|
