Introducing a new method to determining the capacity of heavy metal absorption by macro algae on the coast of Persian Gulf based on Kullback-Leibler cumulative information

IF 2.3 3区 地球科学 Q2 OCEANOGRAPHY Deep-sea Research Part Ii-topical Studies in Oceanography Pub Date : 2025-02-19 DOI:10.1016/j.dsr2.2025.105466
Mehdi Bibak , Saeid Tahmasebi , Eisa Safavi , Najmaldin Ezaldin Hassan
{"title":"Introducing a new method to determining the capacity of heavy metal absorption by macro algae on the coast of Persian Gulf based on Kullback-Leibler cumulative information","authors":"Mehdi Bibak ,&nbsp;Saeid Tahmasebi ,&nbsp;Eisa Safavi ,&nbsp;Najmaldin Ezaldin Hassan","doi":"10.1016/j.dsr2.2025.105466","DOIUrl":null,"url":null,"abstract":"<div><div>Researchers have continuously sought effective and affordable ways to address contamination. Application of both live and deceased algae biomass has emerged as a highly effective and promising approach for remediation. In this study, the efficacy of macroalgal species (<em>Padina gymnospora</em>, <em>Cladophoropsis membranacea</em>, and <em>Hypnea hamulosa</em>) harvested from the northern coast of the Persian Gulf was evaluated for their capacity to biosorb heavy metals, with a focus on nickel, lead, cadmium, and mercury. The study encompassed two key components. Firstlythe experimental methodology was meticulously design using Design-Expert software. Secondly, a novel approach involving – the analysis of scanning electron microscope (SEM) images of the algae was introduced, employing a measure known as cumulative Kullback–Leibler information. The results showed that <em>P. gymnospora</em> is capable of removing 50% of Pb. The highest percentage of Cd removal was observed in <em>H. hamulosa</em> (86.44%), while the highest percentage of Hg removal was recorded in <em>C. membranacea</em> (50%). Both, the experimental and analysis of image methods yielded consistent findings, corroborating their reliability. Based on the findings of this study, image analysis employing cumulative Kullback–Leibler information presents a novel and cost effective means of assessment, contributing to the arsenal methods available for contamination treatment.</div></div>","PeriodicalId":11120,"journal":{"name":"Deep-sea Research Part Ii-topical Studies in Oceanography","volume":"221 ","pages":"Article 105466"},"PeriodicalIF":2.3000,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Deep-sea Research Part Ii-topical Studies in Oceanography","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967064525000153","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
引用次数: 0

Abstract

Researchers have continuously sought effective and affordable ways to address contamination. Application of both live and deceased algae biomass has emerged as a highly effective and promising approach for remediation. In this study, the efficacy of macroalgal species (Padina gymnospora, Cladophoropsis membranacea, and Hypnea hamulosa) harvested from the northern coast of the Persian Gulf was evaluated for their capacity to biosorb heavy metals, with a focus on nickel, lead, cadmium, and mercury. The study encompassed two key components. Firstlythe experimental methodology was meticulously design using Design-Expert software. Secondly, a novel approach involving – the analysis of scanning electron microscope (SEM) images of the algae was introduced, employing a measure known as cumulative Kullback–Leibler information. The results showed that P. gymnospora is capable of removing 50% of Pb. The highest percentage of Cd removal was observed in H. hamulosa (86.44%), while the highest percentage of Hg removal was recorded in C. membranacea (50%). Both, the experimental and analysis of image methods yielded consistent findings, corroborating their reliability. Based on the findings of this study, image analysis employing cumulative Kullback–Leibler information presents a novel and cost effective means of assessment, contributing to the arsenal methods available for contamination treatment.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
6.40
自引率
16.70%
发文量
115
审稿时长
3 months
期刊介绍: Deep-Sea Research Part II: Topical Studies in Oceanography publishes topical issues from the many international and interdisciplinary projects which are undertaken in oceanography. Besides these special issues from projects, the journal publishes collections of papers presented at conferences. The special issues regularly have electronic annexes of non-text material (numerical data, images, images, video, etc.) which are published with the special issues in ScienceDirect. Deep-Sea Research Part II was split off as a separate journal devoted to topical issues in 1993. Its companion journal Deep-Sea Research Part I: Oceanographic Research Papers, publishes the regular research papers in this area.
期刊最新文献
Variability of bottom dissolved oxygen on the southern Senegalese shelf at intraseasonal to interannual time scales using a modelling approach Impact of desalination plant brine discharge on macrobenthic communities in the Persian Gulf Introducing a new method to determining the capacity of heavy metal absorption by macro algae on the coast of Persian Gulf based on Kullback-Leibler cumulative information Uncovering the hidden amphipod biodiversity and its drivers in the Persian Gulf Diet of deep-sea octocorals from the Emperor Seamount Chain inferred by fatty acid trophic markers
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1