Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology
Sanghoon Shin
1
,
Dongmin Seo
2
,
Samir T. Kumar
1
,
Ahyeon Lee
1
,
Sujin Lee
3
,
Young-Ryun Kim
3
,
2
Ocean System Engineering Research Division, Korea Research Institute of Ships & Ocean Engineering (KRISO), Daejeon 34103, Republic of Korea
|
3
Marine Eco-Technology Institute, Busan 48520, Republic of Korea
|
Publication type: Journal Article
Publication date: 2023-02-01
scimago Q1
wos Q1
SJR: 3.843
CiteScore: 21.2
Impact factor: 12.4
ISSN: 00431354, 18792448
PubMed ID:
36638739
Environmental Engineering
Pollution
Civil and Structural Engineering
Waste Management and Disposal
Water Science and Technology
Ecological Modeling
Abstract
The accidental spill of hazardous and noxious substances (HNSs) in the ocean has serious environmental and human health consequences. Assessing the ecotoxicity of seawater exposed to various HNS is challenging due to the constant development of new HNS or mixtures, and assessment methods are also limited. Microalgae viability tests are often used among the various biological indicators for ecotoxicity testing, as they are the primary producers in aquatic ecosystems. However, since the conventional cell growth rate test measures cell viability over three to four days using manual inspection under a conventional optical microscope, it is labor- and time-intensive and prone to subjective errors. In this study, we propose a rapid and automated method to evaluate seawater ecotoxicity by quantification of the morphological changes of microalgae exposed to more than 30 HNSs. This method was further validated using conventional growth rate test results. Dunaliella tertiolecta, a microalgae species without rigid cell walls, was selected as the test organism. Its morphological changes in response to HNS exposure were measured at the single cell level using a custom-developed device that uses lens-free shadow imaging technology. The ecotoxicity evaluation induced by the morphological change could be available in as little as 5 min using the proposed method and device, and it could be effective for 20 HNSs out of 30 HNSs tested. Moreover, the test results of six selected HNSs with high marine transport volume and toxicity revealed that the sensitivity of the proposed method extends to half the maximum effective concentration (EC50) and even to the lowest observed effective concentration (LOEC). Furthermore, the average correlation index between the growth inhibition test (three to four days) and the proposed morphology changes test (5 min) for the six selected HNSs was 0.84, indicating great promise in the field of various point-of-care water quality monitoring. Thus, the proposed equipment and technology may provide a viable alternative to traditional on-site toxicity testing, and the potential of rapid morphological analysis may replace traditional growth inhibition testing.
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Total citations:
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Citations from 2024:
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(70%)
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GOST
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Shin S. et al. Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology // Water Research. 2023. Vol. 230. p. 119585.
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Shin S., Seo D., Kumar S. T., Lee A., Lee S., Kim Y., Seo S. Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology // Water Research. 2023. Vol. 230. p. 119585.
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RIS
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TY - JOUR
DO - 10.1016/j.watres.2023.119585
UR - https://doi.org/10.1016/j.watres.2023.119585
TI - Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology
T2 - Water Research
AU - Shin, Sanghoon
AU - Seo, Dongmin
AU - Kumar, Samir T.
AU - Lee, Ahyeon
AU - Lee, Sujin
AU - Kim, Young-Ryun
AU - Seo, Sungkyu
PY - 2023
DA - 2023/02/01
PB - Elsevier
SP - 119585
VL - 230
PMID - 36638739
SN - 0043-1354
SN - 1879-2448
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2023_Shin,
author = {Sanghoon Shin and Dongmin Seo and Samir T. Kumar and Ahyeon Lee and Sujin Lee and Young-Ryun Kim and Sungkyu Seo},
title = {Field-portable seawater toxicity monitoring platform using lens-free shadow imaging technology},
journal = {Water Research},
year = {2023},
volume = {230},
publisher = {Elsevier},
month = {feb},
url = {https://doi.org/10.1016/j.watres.2023.119585},
pages = {119585},
doi = {10.1016/j.watres.2023.119585}
}
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