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

Benzer S., Benzer R.

THALASSAS, vol.36, no.1, pp.149-156, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 36 Issue: 1
  • Publication Date: 2020
  • Doi Number: 10.1007/s41208-020-00192-1
  • Journal Name: THALASSAS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, BIOSIS, DIALNET
  • Page Numbers: pp.149-156
  • Gazi University Affiliated: Yes

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 Sureyyabey 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.