A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators

The main goal of this study was to develop a model for organic pollution assessment. Seven sampling sites in six rivers in the Rawang sub-basin, Selangor River, Malaysia, were selected with one reference site. The sampling sites near the fish farm were used to develop the model. SR2 was used for the...

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Main Authors: Hettige, Nadeesha Dilani, Hashim, Rohasliney, Kutty, Ahmad Abas, Ashaari, Zulfa Hanan
Format: Article
Published: Central Fisheries Research Institute 2023
Online Access:http://psasir.upm.edu.my/id/eprint/106561/
https://www.trjfas.org/abstract.php?id=14966
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.1065612024-10-03T04:47:08Z http://psasir.upm.edu.my/id/eprint/106561/ A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators Hettige, Nadeesha Dilani Hashim, Rohasliney Kutty, Ahmad Abas Ashaari, Zulfa Hanan The main goal of this study was to develop a model for organic pollution assessment. Seven sampling sites in six rivers in the Rawang sub-basin, Selangor River, Malaysia, were selected with one reference site. The sampling sites near the fish farm were used to develop the model. SR2 was used for the validation of the developed model. Benthic macroinvertebrates and water sampling were conducted from April 2019 to March 2020. The Principal Components Analysis (PCA) and regression were conducted to select the most representing benthic macroinvertebrates family. Based on the score value (variance coefficient) of each benthic macroinvertebrates family, the cumulative score value of each sampling site was calculated (i.e., 18=6 sampling sites x 3 replicates). The nine benthic macroinvertebrate families (Baetidae, Libellulidae, Protoneuridae Chironomidae, Curbicullidae Hydropchysidae, Tubificidae, Lumbriculiade, and Naididae) were identified using PCA and regression. The cluster analysis and mean confidence intervals were used to classify water quality classes precisely. Finally, three different value scales were produced to represent the level of contamination (i.e., 0.87 as clean status). The newly developed model was validated. The results produced after validation were better than the water quality status from other studies based on the BMWP/BMWP score. This study concludes that the developed model can evaluate river organic contamination successfully. Central Fisheries Research Institute 2023-02-15 Article PeerReviewed Hettige, Nadeesha Dilani and Hashim, Rohasliney and Kutty, Ahmad Abas and Ashaari, Zulfa Hanan (2023) A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators. Turkish Journal of Fisheries and Aquatic Sciences, 23 (8). pp. 1-15. ISSN 1303-2712; eISSN: 2149-181X https://www.trjfas.org/abstract.php?id=14966 10.4194/trjfas22423
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The main goal of this study was to develop a model for organic pollution assessment. Seven sampling sites in six rivers in the Rawang sub-basin, Selangor River, Malaysia, were selected with one reference site. The sampling sites near the fish farm were used to develop the model. SR2 was used for the validation of the developed model. Benthic macroinvertebrates and water sampling were conducted from April 2019 to March 2020. The Principal Components Analysis (PCA) and regression were conducted to select the most representing benthic macroinvertebrates family. Based on the score value (variance coefficient) of each benthic macroinvertebrates family, the cumulative score value of each sampling site was calculated (i.e., 18=6 sampling sites x 3 replicates). The nine benthic macroinvertebrate families (Baetidae, Libellulidae, Protoneuridae Chironomidae, Curbicullidae Hydropchysidae, Tubificidae, Lumbriculiade, and Naididae) were identified using PCA and regression. The cluster analysis and mean confidence intervals were used to classify water quality classes precisely. Finally, three different value scales were produced to represent the level of contamination (i.e., 0.87 as clean status). The newly developed model was validated. The results produced after validation were better than the water quality status from other studies based on the BMWP/BMWP score. This study concludes that the developed model can evaluate river organic contamination successfully.
format Article
author Hettige, Nadeesha Dilani
Hashim, Rohasliney
Kutty, Ahmad Abas
Ashaari, Zulfa Hanan
spellingShingle Hettige, Nadeesha Dilani
Hashim, Rohasliney
Kutty, Ahmad Abas
Ashaari, Zulfa Hanan
A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
author_facet Hettige, Nadeesha Dilani
Hashim, Rohasliney
Kutty, Ahmad Abas
Ashaari, Zulfa Hanan
author_sort Hettige, Nadeesha Dilani
title A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
title_short A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
title_full A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
title_fullStr A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
title_full_unstemmed A new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
title_sort new model for organic contamination assessments using benthic macroinvertebrates as biological indicators
publisher Central Fisheries Research Institute
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/106561/
https://www.trjfas.org/abstract.php?id=14966
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