光谱学与光谱分析 |
|
|
|
|
|
Study on the Method for the Determination of Soil Available B by ICP-MS |
WANG Yan-ze1,SHI Yan-zhi1*,ZHANG Hua1,WANG Ying-feng1, CHEN Yu-hong2 |
1. The Analysis Test Center, Capital Normal University,Beijing 100037, China 2. Agilent Technologies Co. Ltd., Beijing 100022, China |
|
|
Abstract A method was established for the determination of soil available B by inductively coupled plasma mass spectrometry(ICP-MS). Compared to the traditional method for B analysis, the recommended method does not need filtration, so it escapes the contamination. The method not only proved simple and rapid, but also showed satisfying precision and accuracy. The detection limit of this method is 0.009 ng·g-1. The relative standard deviation is 2.66%, and the recovery is 93.0%-102.0%.
|
Received: 2005-01-28
Accepted: 2005-04-20
|
|
Corresponding Authors:
SHI Yan-zhi
|
|
Cite this article: |
WANG Yan-ze,SHI Yan-zhi,ZHANG Hua, et al. Study on the Method for the Determination of Soil Available B by ICP-MS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(07): 1334-1335.
|
|
|
|
URL: |
https://www.gpxygpfx.com/EN/Y2006/V26/I07/1334 |
[1] XIONG Cai-hua, XIONG Yu-xiang, YANG Bo-yong, et al(熊采华,熊玉祥,杨波涌, 等). Hubei Geology and Mineral Resources(湖北地矿), 2001, 15(4): 125. [2] LIU Yong-ming,GONG Ben-ling,XU Yu-li, et al(刘永铭,宫本玲,徐毓丽, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 1995, 15(1): 75. [3] TAO Xiao-qiu, HUANG Mei(陶晓秋, 黄 玫). Tobacco Science and Technology/Tobacco Chemistry(烟草科技/烟草化学), 2003, (7): 30. [4] MA Man-zhuang, SUN Ying-bo(马曼庄, 孙映波). Journal of Guangdong Agricultural Sciences(广东农业科学) , 1998, (3): 30. [5] WANG Zhao-min, WANG Nen-liang, WU Long-gao, et al(王赵民, 王嫩良, 吴隆高, 等). Forest Research(林业科学研究), 1995, 8(6): 634. [6] SHEN Yun-he, ZHAO Wei, SUN Yu-wen(沈运河, 赵 伟, 孙玉文). Journal of Anhui Agricultural Sciences(安徽农业科学), 1995, 23(4): 365. [7] ZHU Duan-wei,PI Mei-mei,LIU Wu-ding, et al(朱端卫, 皮美美, 刘武定, 等). Journal of Huazhong Agricultural University(华中农业大学学报),1994, 13(3): 262.
|
[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 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. |
[3] |
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. |
[4] |
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. |
[5] |
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. |
[6] |
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. |
[7] |
ZHANG Yu-hui1, 2, DING Yong-kang3, PEI Jing-cheng1, 2*, GU Yi-lu1, 2, YU Min-da1, 2. Chemical Constituents and Spectra Characterization of Monocrystal
Rhodonite From Brazil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3504-3508. |
[8] |
XIE Peng, WANG Zheng-hai*, XIAO Bei, CAO Hai-ling, HUANG Yi, SU Wen-lin. Hyperspectral Quantitative Inversion of Soil Selenium Content Based on sCARS-PSO-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3599-3606. |
[9] |
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. |
[10] |
AN Bai-song1, 2, WANG Xue-mei1, 2*, HUANG Xiao-yu1, 2, KAWUQIATI Bai-shan1, 2. Hyperspectral Estimation of Soil Lead Content Based on Random Frog Band Selection Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3302-3309. |
[11] |
DENG Yun1, 2, NIU Zhao-wen1, 2, FENG Qi-yao1, 2, WANG Yu1, 2*. A Novel Hyperspectral Prediction Model of Organic Matter in Red Soil Based on Improved Temporal Convolutional Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2942-2951. |
[12] |
CAI Hai-hui1, ZHOU Ling2, SHI Zhou3, JI Wen-jun4, LUO De-fang1, PENG Jie1, FENG Chun-hui5*. Hyperspectral Inversion of Soil Organic Matter in Jujube Orchard
in Southern Xinjiang Using CARS-BPNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2568-2573. |
[13] |
XIA Chen-zhen1, 2, 3, JIANG Yan-yan4, ZHANG Xing-yu1, 2, 3, SHA Ye5, CUI Shuai1, 2, 3, MI Guo-hua5, GAO Qiang1, 2, 3, ZHANG Yue1, 2, 3*. Estimation of Soil Organic Matter in Maize Field of Black Soil Area Based on UAV Hyperspectral Image[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2617-2626. |
[14] |
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. |
[15] |
ZHANG Xia1, WANG Wei-hao1, 2*, SUN Wei-chao1, DING Song-tao1, 2, WANG Yi-bo1, 2. Soil Zn Content Inversion by Hyperspectral Remote Sensing Data and Considering Soil Types[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2019-2026. |
|
|
|
|