View in EDS HTML Full Text PDF Full Text

Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.

Saved in:
Bibliographic Details
Title: Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.
Authors: Aasim, Muhammad1 (AUTHOR) mshazim@gmail.com, Ali, Seyid Amjad2 (AUTHOR), Aydin, Senar3 (AUTHOR), Bakhsh, Allah4 (AUTHOR), Sogukpinar, Canan3 (AUTHOR), Karatas, Mehmet5 (AUTHOR), Khawar, Khalid Mahmood6 (AUTHOR), Aydin, Mehmet Emin7 (AUTHOR)
Source: Environmental Science & Pollution Research. Mar2023, Vol. 30 Issue 14, p40206-40217. 12p.
Database: Environment Complete
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: eih
DbLabel: Environment Complete
An: 162868933
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Aasim%2C+Muhammad%22">Aasim, Muhammad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> mshazim@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Ali%2C+Seyid+Amjad%22">Ali, Seyid Amjad</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aydin%2C+Senar%22">Aydin, Senar</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bakhsh%2C+Allah%22">Bakhsh, Allah</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sogukpinar%2C+Canan%22">Sogukpinar, Canan</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Karatas%2C+Mehmet%22">Karatas, Mehmet</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khawar%2C+Khalid+Mahmood%22">Khawar, Khalid Mahmood</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Aydin%2C+Mehmet+Emin%22">Aydin, Mehmet Emin</searchLink><relatesTo>7</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Environmental+Science+%26+Pollution+Research%22">Environmental Science & Pollution Research</searchLink>. Mar2023, Vol. 30 Issue 14, p40206-40217. 12p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=162868933
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11356-022-25081-3
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
        StartPage: 40206
    Titles:
      – TitleFull: Artificial intelligence–based approaches to evaluate and optimize phytoremediation potential of in vitro regenerated aquatic macrophyte Ceratophyllum demersum L.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Aasim, Muhammad
      – PersonEntity:
          Name:
            NameFull: Ali, Seyid Amjad
      – PersonEntity:
          Name:
            NameFull: Aydin, Senar
      – PersonEntity:
          Name:
            NameFull: Bakhsh, Allah
      – PersonEntity:
          Name:
            NameFull: Sogukpinar, Canan
      – PersonEntity:
          Name:
            NameFull: Karatas, Mehmet
      – PersonEntity:
          Name:
            NameFull: Khawar, Khalid Mahmood
      – PersonEntity:
          Name:
            NameFull: Aydin, Mehmet Emin
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 20
              M: 03
              Text: Mar2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 09441344
          Numbering:
            – Type: volume
              Value: 30
            – Type: issue
              Value: 14
          Titles:
            – TitleFull: Environmental Science & Pollution Research
              Type: main
ResultId 1