Chemometric assessment of water quality of a river using a major biochemical constituent

被引:2
|
作者
Suryakumari, Sumathyamma [1 ]
Saritha, Sarala [2 ]
Padma, Parameswaran [3 ]
Sheela, Vattathara Sivaramamenon [4 ]
Gopinath, Anu [5 ]
Jayalakshmy, Koovelimadom Veeraraghavaiyer [6 ]
Kumar, Narayanannair Chandramohana [2 ]
Nair, Sukumarannair Muraleedharan [2 ]
机构
[1] SD Coll, Dept Chem, Alappuzha, India
[2] Cochin Univ Sci & Technol, Sch Marine Sci, Dept Chem Oceanog, Cochin, Kerala, India
[3] SSV Coll, Dept Chem, Perumbavoor, India
[4] NSS Coll, Dept Chem, Cherthala, India
[5] St Teresas Coll, Dept Chem, Cochin, Kerala, India
[6] Natl Inst Oceanog, Cochin, Kerala, India
关键词
River-estuary; biochemical constituent; protein; chemometrics; trellis diagram;
D O I
10.1080/15715124.2015.1012205
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The use of biochemical methods is emerging as an important and valuable tool in the environmental impact assessment. This is a systematic study on the monitoring of a major labile biochemical component, protein along a tropical river-estuary, Chalakudy River, south India to identify the different riverine inputs and also about the pollution factors. The National Bureau of Fish Genetic Resources report indicates Chalakudy River with its riparian zone as the richest river in fish diversity perhaps in India. Chemometrics was applied in assessing the highly complex environmental data to picture the prevailing condition of the river-estuary, and to show how the biochemical component varies spatio-temporally with respect to the changes in hydrological and sediment characteristics. The protein contents are probably related to the natural fluctuations in the productivity due to monsoon/non-monsoon seasons or to the geographical variations due to organic pollution gradient. The three-way analysis of variance and Trellis diagram were used to obtain seasonal and spatial variation. The canonical discriminant analysis characterized the hypertrophic, eutrophic and meso-oligotrophic areas with 68.8% precision for correct classification of cross-validated grouped cases using sediment texture and different forms of protein data from different sites.
引用
收藏
页码:229 / 241
页数:13
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