Skip to content
RDL
Network
Ekosistem
Uygulama değiştir
EN
Hakkımızda
SSS
Giriş yap
Başla
Modeling phytoremediation of heavy metal contaminated soils through machine learning — Liang Shi (2022) | RDL Network
Back
Cite
Save
Save for later
Share
Home
Publications
Modeling phytoremediation of heavy metal contaminated soils through machine learning
Shared by
Yong Sik Ok
Modeling phytoremediation of heavy metal contaminated soils through machine learning
Article
2022
en
Authors
+6 more
LS
Liang Shi
JL
Jie Li
KP
Kumuduni Niroshika Palansooriya
Discussion
(0)
Sign in
to like and join the discussion.
No comments yet. Be the first to comment.
Related publications
Article
2003
Phytoremediation of heavy metal contaminated soils: mechanisms and feasibility
Fang-jie Zhao
,
S. P. McGrath
Article
2001
Phytoremediation of Heavy Metal–Contaminated Soils: Natural Hyperaccumulation versus Chemically Enhanced Phytoextraction
Enzo Lombi
,
Fang-jie Zhao
,
S. J. Dunham
,
S. P. McGrath
Journal of Environmental Quality
Article
2008
Phytoremediation of arsenic contaminated soils
S. P. McGrath
,
Fang-jie Zhao
Chapter in a book
2002
Plant and rhizosphere processes involved in phytoremediation of metal-contaminated soils
S. P. McGrath
,
Fang-jie Zhao
,
Enzo Lombi
Article
2017
Remediation of heavy metal contaminated soils by using Solanum nigrum : A review
Muhammad Zia‐ur‐Rehman
,
Muhammad Rizwan
,
Shafaqat Ali
,
Yong Sik Ok
,
Wajid Ishaque
,
Saif Ullah
,
Muhammad Nawaz
,
Fatima Akmal
,
Maqsooda Waqar
Discussion(0)
No comments yet. Be the first to comment.