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Growth Properties of Pseudorasbora parva in Süreyyabey Reservoir: Traditional and Artificial Intelligent Methods

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Abstract

Pseudorasbora parva (Temminck and Schlegel, 1846) is a small nan-native Cyprinidae species which lives in shallow lakes, pools, irrigation canals, and rivers. Samples (550 specimens: 233 females and 317 males) were collected in 2016 from Süreyyabey Reservoir. Length and weight values were measured and then compared with traditional (Length-Weight Relationship and von Bertalanfy) and Artificial Intelligent (Artificial Neural Networks) methods for growth assessment. The results of the study were examined by the artificial neural networks approach and traditional estimation method. This approach would be useful for sustainable fisheries management.

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Acknowledgments

We would like to express our gratitude to the referees for their help and support to our research with their reviews and recommendations. This study has been accepted for oral presentation at International Conference on Civil and Environmental Engineering in 2018 (ICOCEE 2018, İzmir, Çeşme Turkey).

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Correspondence to Semra Benzer.

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Benzer, S., Benzer, R. Growth Properties of Pseudorasbora parva in Süreyyabey Reservoir: Traditional and Artificial Intelligent Methods. Thalassas (2020) doi:10.1007/s41208-020-00192-1

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Keywords

  • Pseudorasbora parva
  • Stone moroko
  • Growth properties
  • Artificial neural networks