光谱学与光谱分析 |
|
|
|
|
|
Study on DNA Fourier Infrared Spectroscopy of Three Kinds of Nicotiana Tabacum L. |
QIU Lu1, YANG Hai-yan1, YANG Chun-sheng1, LIU Peng2, FAN Shu-guo1, LIU Ren-ming3, ZHOU Lin-zong4 |
1. Department of Chemistry and Life Science, Chuxiong Normal University, Chuxiong 675000, China 2. Department of Mathematics, Chuxiong Normal University, Chuxiong 675000, China 3. Department of Physics and Electronics Science, Chuxiong Normal University, Chuxiong 675000, China 4. Department of Geography Science, Chuxiong Normal University, Chuxiong 675000, China |
|
|
Abstract The aim is analyzing genetic reLationship and identifying varieties by detecting DNA differences of three kinds of Nicotiana tabacum L. using Fourier infrared spectrum (FTIR). Results show that DNA FTIR of three kinds of Nicotiana tabacum L. is relatively similar. They all have four obvious characteristic peaks. 1 105 cm-1 beLongs to symmetrical stretching vibration of phosphodiester bond,1 250 cm-1 is unsymmetrical stretching vibration of phosphodiester bond, 1 400 cm-1 is contributed to glucosidic bond, and 1 622 cm-1 belongs to C4C5C6 stretching vibration of cytosine. DNA FTIR data was handled by smoothing, standardizing, second derivative, principal component analysis and Hierarchical cluster analysis. The standard model of Hierarchical cluster combined with principal component of the second derivative was set up. The correct rate of identification is 100%. Yunyan 87 and K326 were clustered into one by using the model. The distance coefficient is 0.003, and DNA similarity is 99.7%, Hongda was clustered into one by itself. The correct rate of cluster is 100%. The study provides a reference for Nicotiana tabacum L. variety identification and genetic breeding.
|
Received: 2013-09-16
Accepted: 2014-01-10
|
|
Corresponding Authors:
QIU Lu
E-mail: qiulu@cxtc.edu.cn
|
|
[1] WANG Yan-ting(王彦亭). Chinese Tobacco Science(中国烟草科学),2001, (4): 1. [2] LIANG Jing-xia, QI Jian-min, WU Wei-ren, et al(梁景霞,祁建民,吴为人,等). Acta Tabacaria Sinica(中国烟草学报),2005, 11(4): 33. [3] CHANG Ai-xia, JIA Xing-hua, FENG Quan-fu, et al(常爱霞,贾兴华,冯全福,等). Chinese Tobacco Science(中国烟草科学),2013, 34(1): 1. [4] FAN Xiao-yan(范晓燕). Life Science Research(生命科学研究), 2003, 7(2): 68. [5] WU Jian-hua, LUO Zong-ming, ZHENG Jian-guo, et al(吴建华, 罗宗铭, 郑建国, 等). Journal of Instrumental Analysis(分析测试学报), 2003, 22(3): 75. [6] WANG Xu-ming, WANG Jing-huai, WANG Xu-dong, et al(王绪明,王静怀,王旭东,等). Modern Instruments(现代仪器),2010, 16(4): 8. [7] PAN Xue-feng(潘学峰). Modern Molecular biology Course(现代分子生物学教程). Beijing: Science Press(北京:科学出版社),2009. 31. [8] ZHU Sheng-wei, SHI Zhi-wen, XU Shu-fen, et al(朱生伟,史芝文,徐淑芬,等). The Northeast Agricultural University(东北农业大学学报),1998, 29(3): 275. [9] Komarov V M. Journal of Biological Physics, 1999, 24: 167. [10] Galinal Dovbeshko, Nina Ya Gridina, Elena B Kruglova, et al. Talanta, 2000, 53: 233. [11] Donna R Whelan, Keith R Bambery, Philip Heraud, et al. Nucleic Acids Research, 2011, 39(13): 175. [12] CanhLe-Tien, Roxanne Lafortune, Francois Shareck, et al. Talanta, 2007, 71: 1969. [13] Martina Banyay, Astrid Graslund. J. Mol. Biol., 2002, 324: 667. [14] ZHANG Yan, ZHANG Zhen-hua, YAO Fu-qi, et al(张 燕, 张振华, 姚付启, 等). Agricultural System Science and Integrated Research(农业系统科学与综合研究), 2009, 25(1): 23. [15] GUO Jin-ping, ZHU Hui-li, ZHOU Yi-fei, et al(郭金平,朱慧丽, 周以飞, 等). Chinese Tobacco Science(中国烟草科学), 2009, (30): 15, 24. [16] XIAO Bing-guang, GAO Yu-long, WU Wei-ren(肖炳光, 高玉龙, 吴为人). Molecalar Plant Breeding(分子植物育种), 2011, 9(39): 1297.
|
[1] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
[2] |
WANG Cai-ling1,ZHANG Jing1,WANG Hong-wei2*, SONG Xiao-nan1, JI Tong3. A Hyperspectral Image Classification Model Based on Band Clustering and Multi-Scale Structure Feature Fusion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 258-265. |
[3] |
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. |
[4] |
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. |
[5] |
FANG Zheng, WANG Han-bo. Measurement of Plastic Film Thickness Based on X-Ray Absorption
Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3461-3468. |
[6] |
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. |
[7] |
JIA Zong-chao1, WANG Zi-jian1, LI Xue-ying1, 2*, QIU Hui-min1, HOU Guang-li1, FAN Ping-ping1*. Marine Sediment Particle Size Classification Based on the Fusion of
Principal Component Analysis and Continuous Projection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3075-3080. |
[8] |
CHEN Jia-wei1, 2, ZHOU De-qiang1, 2*, CUI Chen-hao3, REN Zhi-jun1, ZUO Wen-juan1. Prediction Model of Farinograph Characteristics of Wheat Flour Based on Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3089-3097. |
[9] |
XUE Fang-jia, YU Jie*, YIN Hang, XIA Qi-yu, SHI Jie-gen, HOU Di-bo, HUANG Ping-jie, ZHANG Guang-xin. A Time Series Double Threshold Method for Pollution Events Detection in Drinking Water Using Three-Dimensional Fluorescence Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3081-3088. |
[10] |
JIA Hao1, 3, 4, ZHANG Wei-fang1, 3, LEI Jing-wei1, 3*, LI Ying-ying1, 3, YANG Chun-jing2, 3*, XIE Cai-xia1, 3, GONG Hai-yan1, 3, DING Xin-yu1, YAO Tian-yi1. Study on Infrared Fingerprint of the Classical Famous
Prescription Yiguanjian[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3202-3210. |
[11] |
CAO Qian, MA Xiang-cai, BAI Chun-yan, SU Na, CUI Qing-bin. Research on Multispectral Dimension Reduction Method Based on Weight Function Composed of Spectral Color Difference[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2679-2686. |
[12] |
ZHANG Zi-hao1, GUO Fei3, 4, WU Kun-ze1, YANG Xin-yu2, XU Zhen1*. Performance Evaluation of the Deep Forest 2021 (DF21) Model in
Retrieving Soil Cadmium Concentration Using Hyperspectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2638-2643. |
[13] |
CHEN Wan-jun1, XU Yuan-jie2, LU Zhi-yun3, QI Jin-hua3, WANG Yi-zhi1*. Discriminating Leaf Litters of Six Dominant Tree Species in the Mts. Ailaoshan Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2119-2123. |
[14] |
WANG Yu-hao1, 2, LIU Jian-guo1, 2, XU Liang2*, DENG Ya-song2, SHEN Xian-chun2, SUN Yong-feng2, XU Han-yang2. Application of Principal Component Analysis in Processing of Time-Resolved Infrared Spectra of Greenhouse Gases[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2313-2318. |
[15] |
HU Hui-qiang1, WEI Yun-peng1, XU Hua-xing1, ZHANG Lei2, MAO Xiao-bo1*, ZHAO Yun-ping2*. Identification of the Age of Puerariae Thomsonii Radix Based on Hyperspectral Imaging and Principal Component Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1953-1960. |
|
|
|
|