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Artificial neural network based analysis on the influence of different limnological parameters favouring coexistence of Lemna minor L. with microalgae in stagnant waterbodies of Malda District, West Bengal, India

Sudipta Kumar Sil,Santanu Gupta.



Abstract
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ABSTRACT
Aims/background: Lesser duckweeds are the most common type of aquatic macrophytes showing multidimensional application in the field of biology. The physico-chemical properties of the water bodies strongly influence their rapid propagation. Cohabitation at a particular habitat by two different plant groups is related to mutual sharing of resources in any given ecosystem. In a lentic water body, adaptive strategies are often associated with sharing habitat by aquatic flora and fauna.
Methods: For the study of algal association with fronds of L.minor L., 15 different collection sites (CS) were selected. Various biochemical parameters included in the list of independent variables like pH, total dissolved solids (TDS), nitrate and phosphate levels etc. were determined. Association between lesser duckweeds and microalgae has been observed to have been stably maintained in both collected sample as well as in-vitro grown coculture and was detected under microscope and identified using algal identification keys. Artificial Neural Network (ANN) explained the role of independently variable limnological parameters towards predicting most significant association between microalgae and lesser duckweeds and the threshold sample size using SPSS v 24.0 software for statistical analysis of the collected data.
Results: Microalgal members belonging to members of Bacillariophyceae and Cyanophyceae were found to be closely associated with the fronds of Lemna minor L. Different physico chemical parameters of the water bodies were found to be closely related with the cohabitation. Multivariate analysis done by the ANN software and link established with target variable in the form of significant and non-significant outcome with both cyanophyceae and diatoms Obtained results also signified the selection minimum number of sampling sites based on the ANN model corresponding to their chosen independent variables, therefore, it would be economical both in terms of resource and time applicable to new researches.
Conclusion: This paper emphasizes algae-lesser duckweed cohabitation in the different geographical locations of Malda, West Bengal, India and simulating physical and chemical parameters of such water bodies that support this type of natural association between two evolutionary distinct organisms with the help of ANN.

Key words: Duckweeds, Lemna minor L., Total dissolved Solutes (TDS) Central National Herbarium (CNH), Artificial Neural Networking (ANN), Collection Site (CS), Cyanobacteria







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