KAUR, RAJBIR and DUA, ANISH and KAUR, SATINDER (2022) MULTIVARIATE APPROACHES TO CLUB LARGE WATER QUALITY DATA FROM AQUATIC TOXICITY STUDIES: A REVIEW STUDY. UTTAR PRADESH JOURNAL OF ZOOLOGY. pp. 500-509. ISSN 0256-971X
Full text not available from this repository.Abstract
Water is the most valuable, widespread resource, major constituent of all living creatures and extremely essential for the sustenance & existence of life. This is exemplified by its multiple uses such as drinking, cooking, washing, irrigation, farming, industrial activities and many more. Quality of surface waters are getting deteriorated as water resources are polluted due to the discharge of industrial effluents, agricultural run-off having insecticides, pesticides, heavy metals, fertilizers, chemicals, sewage and other domestic wastes. This review strongly recommends the incorporation of regular monitoring programmes for reliable estimation of water quality, effective pollution control and water resource management. The practice of conducting physicochemical studies is even essential/mandatory before conducting any toxicity study using fishes or any other sentinel organism both for in-vivo and in-vitro studies. Frequent sampling at many sites with a lot of water quality parameters generates a large & complex data matrix that needs data interpretation. The use of different multivariate approaches provide a rapid solution by identifications of factors that are mainly influencing water quality, clustering many parameters to identify the parameters mainly responsible for spatial and temporal variations linked to seasonality. In this way, reliable management of water resources as well as rapid solutions to pollution problems and effective environmental impact assessment can be approached.
Item Type: | Article |
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Subjects: | GO for STM > Biological Science |
Depositing User: | Unnamed user with email support@goforstm.com |
Date Deposited: | 30 Oct 2023 11:44 |
Last Modified: | 30 Oct 2023 11:44 |
URI: | http://archive.article4submit.com/id/eprint/1948 |