| 光谱学与光谱分析 |
|
|
|
|
|
| The FTIR Spectral Characteristics and Comparison Study of Astragalus Menbranceus Soil |
| LIU Bi-wang1, ZHAO Hui-hui2*, ZHAO Ping3, WANG Wei2, XUE Hui-qing1, WANG Yong-hui1, ZHOU Ran1, LIU Yang-qing1 |
1. Shanxi College of Traditional Chinese Medicine, Taiyuan 030024, China
2. Beijing University of Chinese Medicine, Beijing 100029, China
3. Wuxi AppTec (Tianjin) Co. Ltd., Tianjin 300457, China |
|
|
|
|
Abstract To study the genuine soil of Astragalus menbranceus grows, FTIR spectrometry was used, which is accurate, simple and efficient and has high resolution. The genuine soils include six areas in Hunyuan of Shanxi province, three areas in Yingxian of Shanxi province, Fansi of Shanxi province, and Guyang of Inner Mongolia. Different growth years of two to five for each area were also studied. The results show that there are significant differences between Astragalus menbranceus soil FTIR spectrometry and general soil’s, between soil of Astragalus menbranceus growth and radix codonopsitis growth, between different soil of Astragalus menbranceus growth, providing useful information for the area chose of Chinese herb cultural and transplantation.
|
|
Received: 2012-03-08
Accepted: 2012-05-20
|
|
|
|
Corresponding Authors:
ZHAO Hui-hui
E-mail: hh686@126.com
|
|
[1] LI Gui-lan, ZHAO Hui-hui, ZHAO Ping, et al(李桂兰，赵慧辉，赵 平，等). China Journal of Traditional Chinese Medicine and Pharmacy(中华中医药杂志), 2011, 26(1): 84.
[2] LIU Yang-qing, ZHAO Guo-feng, HAN Xue, et al(刘养清，赵国峰，韩 雪). China Pharmacy(中国药房)，2009, 20(24): 1879.
[3] Pharmacopoeia Committee of the Ministry of Public Health of the People’s Republic of China(中华人民共和国卫生部药典委员会). Pharmacopoeia of the Ministry of Public Health of the People’s Republic of China，Ⅰ(中华人民共和国卫生部药典, 第1部). Beijing: Chemical Industry Press(北京: 化学工业出版社), 2005. 28.
|
| [1] |
XU Tian1, 2, LI Jing1, 2, LIU Zhen-hua1, 2*. Remote Sensing Inversion of Soil Manganese in Nanchuan District, Chongqing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 69-75. |
| [2] |
LI Xin-ting, ZHANG Feng, FENG Jie*. Convolutional Neural Network Combined With Improved Spectral
Processing Method for Potato Disease Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 215-224. |
| [3] |
LIANG Ye-heng1, DENG Ru-ru1, 2*, LIANG Yu-jie1, LIU Yong-ming3, WU Yi4, YUAN Yu-heng5, AI Xian-jun6. Spectral Characteristics of Sediment Reflectance Under the Background of Heavy Metal Polluted Water and Analysis of Its Contribution to
Water-Leaving Reflectance[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 111-117. |
| [4] |
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. |
| [5] |
LI Hu1, ZHONG Yun1, 2, FENG Ya-ting1, LIN Zhen1, ZHU Shi-jiang1, 2*. Multi-Vegetation Index Soil Moisture Inversion Model Based on UAV
Remote Sensing[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 207-214. |
| [6] |
ZHU Wen-jing1, 2，FENG Zhan-kang1, 2，DAI Shi-yuan1, 2，ZHANG Ping-ping3，JI Wen4，WANG Ai-chen1, 2，WEI Xin-hua1, 2*. Multi-Feature Fusion Detection of Wheat Lodging Information Based on UAV Multispectral Images[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 197-206. |
| [7] |
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. |
| [8] |
HAN Xue1, 2, LIU Hai1, 2, LIU Jia-wei3, WU Ming-kai1, 2*. Rapid Identification of Inorganic Elements in Understory Soils in
Different Regions of Guizhou Province by X-Ray
Fluorescence Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 225-229. |
| [9] |
WU Hu-lin1, DENG Xian-ming1*, ZHANG Tian-cai1, LI Zhong-sheng1, CEN Yi2, WANG Jia-hui1, XIONG Jie1, CHEN Zhi-hua1, LIN Mu-chun1. A Revised Target Detection Algorithm Based on Feature Separation Model of Target and Background for Hyperspectral Imagery[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 283-291. |
| [10] |
HE Yan1, TAO Ran1, YANG Ming-xing1, 2*. The Spectral and Technology Studies of Faience Beads Unearthed in Hubei Province During Warring States Period[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3700-3709. |
| [11] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
| [12] |
LI Wei1, TAN Feng2*, ZHANG Wei1, GAO Lu-si3, LI Jin-shan4. Application of Improved Random Frog Algorithm in Fast Identification of Soybean Varieties[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3763-3769. |
| [13] |
MENG Shan1, 2, LI Xin-guo1, 2*. Estimation of Surface Soil Organic Carbon Content in Lakeside Oasis Based on Hyperspectral Wavelet Energy Feature Vector[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3853-3861. |
| [14] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
| [15] |
CUI Xiang-yu1, 3, CHENG Lu1, 2, 3*, YANG Yue-ru1, WU Yan-feng1, XIA Xin1, 3, LI Yong-gui2. Color Mechanism Analysis During Blended Spinning of Viscose Fibers Based on Spectral Characteristics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3916-3923. |
|
|
|
|
