中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 合肥物质科学研究院
  3. 中国科学院合肥物质科学研究院
Polluted soil-plant interaction analysis and soil classification based on laser-induced breakdown spectroscopy and machine learning

文献类型：期刊论文

作者Cai, Yuyao1,2; Yu, Wei1,2; Gao, Wenhan1,2; Zhai, Ruoyu1,2; Zhang, Xinglong1,2; Yu, Wenjie1,2; Wang, Liusan3; Liu, Yuzhu1,2,4
刊名ANALYTICAL METHODS
出版日期2024-09-04
ISSN号1759-9660
DOI10.1039/d4ay00875h
通讯作者Wang, Liusan(lswang@iim.ac.cn) ; Liu, Yuzhu(yuzhu.liu@gmail.com)
英文摘要A new method is introduced for the swift and precise detection of soil pollution and its effects on crops. Soil quality is essential for human well-being, with heavy metal pollution presenting considerable risks to both the ecological environment and human health. In crops, heavy metal contamination primarily occurs through mediums such as soil and water sources. This study introduces a system combining Laser-Induced Breakdown Spectroscopy (LIBS) with machine learning (ML) to analyze garlic contaminated by soil and the soil used for its cultivation. The simulation conducted in this study focuses on the impact of heavy metal-contaminated soil on garlic. Detection results indicate a significant influence of soil on garlic, resulting in heavy metal accumulation. Further analysis shows that metals from contaminated soil accumulate differently in various garlic plant parts, as per spectral data, underscoring the need for targeted detection methods to assess crop contamination. Conducting LIBS analysis on various soil samples enables the classification of different soil types. This indicates that tracing the origin of contaminated garlic through its residual soil is feasible. These findings imply the feasibility of tracing contaminated garlic's origin through its residual soil. This study presents a novel method combining Laser-Induced Breakdown Spectroscopy (LIBS) and machine learning for fast, effective analysis of soil pollution, highlighting the impact of heavy metals on garlic crops under contaminated soil conditions.
WOS关键词TOXIC ELEMENTS ; METALS
资助项目National Natural Science Foundation of China[2023YFD1701801] ; National Key R&D Program of China[62375136] ; National Natural Science Foundation of China[202410300221Y] ; Provincial College Students' Innovation and Entrepreneurship Training Program[XJDC202410300299] ; NUIST Students' Platform for Innovation and Entrepreneurship Training Program
WOS研究方向Chemistry ; Food Science & Technology ; Spectroscopy
语种英语
WOS记录号WOS:001308726500001
出版者ROYAL SOC CHEMISTRY
资助机构National Natural Science Foundation of China ; National Key R&D Program of China ; National Natural Science Foundation of China ; Provincial College Students' Innovation and Entrepreneurship Training Program ; NUIST Students' Platform for Innovation and Entrepreneurship Training Program
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/135173]  
专题中国科学院合肥物质科学研究院
通讯作者Wang, Liusan; Liu, Yuzhu
作者单位1.Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Detect Atmosphere & Ocean, Nanjing 210044, Jiangsu, Peoples R China
2.Nanjing Univ Informat Sci & Technol, Jiangsu Int Joint Lab Meteorol Photon & Optoelect, Nanjing 210044, Jiangsu, Peoples R China
3.Chinese Acad Sci, Inst Intelligent Machines, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
4.Jiangsu Collaborat Innovat Ctr Atmosphere Environm, Nanjing 210044, Jiangsu, Peoples R China
推荐引用方式
GB/T 7714		 Cai, Yuyao,Yu, Wei,Gao, Wenhan,et al. Polluted soil-plant interaction analysis and soil classification based on laser-induced breakdown spectroscopy and machine learning[J]. ANALYTICAL METHODS,2024.
APA Cai, Yuyao.,Yu, Wei.,Gao, Wenhan.,Zhai, Ruoyu.,Zhang, Xinglong.,...&Liu, Yuzhu.(2024).Polluted soil-plant interaction analysis and soil classification based on laser-induced breakdown spectroscopy and machine learning.ANALYTICAL METHODS.
MLA Cai, Yuyao,et al."Polluted soil-plant interaction analysis and soil classification based on laser-induced breakdown spectroscopy and machine learning".ANALYTICAL METHODS (2024).

入库方式： OAI收割

来源：合肥物质科学研究院

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。