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...
| Main Authors: | , , , |
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| Format: | Article |
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Central Fisheries Research Institute
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/106561/ |
| _version_ | 1848864782907604992 |
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| author | Hettige, Nadeesha Dilani Hashim, Rohasliney Kutty, Ahmad Abas Ashaari, Zulfa Hanan |
| author_facet | Hettige, Nadeesha Dilani Hashim, Rohasliney Kutty, Ahmad Abas Ashaari, Zulfa Hanan |
| author_sort | Hettige, Nadeesha Dilani |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T13:54:17Z |
| format | Article |
| id | upm-106561 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:54:17Z |
| publishDate | 2023 |
| publisher | Central Fisheries Research Institute |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| 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 |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/106561/ http://psasir.upm.edu.my/id/eprint/106561/ http://psasir.upm.edu.my/id/eprint/106561/ |