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

Benzer S., Benzer R.

THALASSAS, cilt.36, sa.1, ss.149-156, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36 Sayı: 1
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s41208-020-00192-1
  • Dergi Adı: THALASSAS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, BIOSIS, DIALNET
  • Sayfa Sayıları: ss.149-156
  • Gazi Üniversitesi Adresli: Evet

Özet

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.