DETERMINE SOME MORPHOLOGICAL CHARACTERISTICS OF CRAYFISH (Astacus leptodactylus ESCHSCHOLTZ, 1823) WITH TRADIONAL METHODS AND ARTIFICIAL NEURAL NETWORKS IN DIKILITAS POND, ANKARA, TURKEY


BENZER S. , Benzer R.

FRESENIUS ENVIRONMENTAL BULLETIN, cilt.24, ss.3727-3735, 2015 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 24
  • Basım Tarihi: 2015
  • Dergi Adı: FRESENIUS ENVIRONMENTAL BULLETIN
  • Sayfa Sayıları: ss.3727-3735

Özet

This study aimed to determine some morphological characteristics of freshwater crayfish (Astacus leptodactylus Eschscholtz 1823) populations 2014, in Dikilitas Pond. We present the relationships between total length (TL), total weight (TW); carapace length (CL), total weight (TW); carapace length (CL), total length (TL); abdomen length (AL), total weight (TW); chelea length (ChL), total weight (TW) for Astacus leptodactylus from Dikilitas Pond. The research was used 260 (105 female, 155 male). The research was found as 40.38 % male, 59.62% female of crayfish thought investigation female and male ratios was of determined as to 0.68 / 1.00. Results of the research can be seemed as follows; average total length 110.60 mm for female 113.50 mm for male, average total weight 38.52 g for female 50.08 g for male. Length-weight relation equation was found for females W = 0.031 x L (2.97), for males W = 0.059 x L (2.75) and for all gender W = 0.024 x L (3.01). The results obtained by artificial neural networks and length-weight relation equation are compared to those obtained by the growth rate of the crayfish caught from the natural environment. Length-weight relation and artificial neural network MAPE results were examined. It was found MAPE value of the forecast of ANNs as a 0.46 and 1.30, while MAPE value of relationship results as a 6.07 and 2.98 for length weight of all gender. Artificial neural networks gives better results than length-weight relation. Artificial neural networks can be alternative as a evaluated for growth estimation.