TY  - JOUR
T1  - Testing the relationship between otolith morphometric and growth patterns in the deep-sea fish Chlorophthalmus agassizi Bonaparte, 1840 (North Aegean Sea): A comparison of classical and ANN approaches
TT  - Derin deniz balığı Chlorophthalmus agassizi Bonaparte, 1840’da (Kuzey Ege Denizi) otolit morfometrik özellikleri ile büyüme örüntüleri arasındaki ilişkinin incelenmesi: Klasik ve ANN yaklaşımlarının karşılaştırılması
AU  - Arslan İhsanoğlu, Mukadder
AU  - İşmen, Ali
AU  - Yığın, Cahide Çiğdem
AU  - Öz, Melike İdil
PY  - 2026
DA  - July
Y2  - 2026
DO  - 10.12714/egejfas.43.3.11
JF  - Ege Journal of Fisheries and Aquatic Sciences
JO  - EgeJFAS
PB  - Ege Üniversitesi
WT  - DergiPark
SN  - 2148-3140
SP  - 273
EP  - 280
VL  - 43
IS  - 3
LA  - en
AB  - This study evaluates whether otolith morphometric descriptors can reliably reflect growth patterns in the deep-sea fish Chlorophthalmus agassizi (Bonaparte, 1840) and assesses the additional explanatory value of artificial neural network (ANN) models compared with classical approaches. A total of 95 specimens were collected monthly between September 2006 and September 2008 by trawling at depths of 100–500 m in Saros Bay (North Aegean Sea). Mean total length and weight were 11.43±0.22 cm (range:7.2–17.1 cm) and 11.07±0.66 g (range:1.88–33.42 g), respectively. Otolith weight ranged from 0.0016 to 0.0067 g, while otolith length varied between 2.73 and 4.37 mm. Relationships among total length (TL), total weight (TW), otolith length (OL), and otolith weight (OW) were examined using both classical regression analyses and ANN-based predictions. Strong relationships were observed for TL–TW (R²=0.95), TL–OL (R²=0.90), TL–OW (R²=0.88), and OL–OW (R²=0.86), whereas the TW–OW relationship showed lower explanatory power (R²=0.65). These findings indicate that otolith morphometrics provide reliable proxies for growth patterns in C. agassizi, while ANN models offer complementary insights into potential nonlinear relationships.
KW  - Shortnose greeneye
KW  - deep sea fishes
KW  - morphometric analysis
KW  - otolith structure
KW  - machine learning
N2  - Bu çalışma, otolit morfometrik tanımlayıcılarının derin deniz balığı Chlorophthalmus agassizi (Bonaparte, 1840)’da büyüme desenlerini güvenilir şekilde yansıtıp yansıtamayacağını ve yapay sinir ağı (ANN) modellerinin klasik yaklaşımlara kıyasla sağladığı ek açıklayıcı değeri değerlendirmektedir. Toplam 95 birey, Eylül 2006 ile Eylül 2008 tarihleri arasında Saros Körfezi’nde (Kuzey Ege Denizi) 100–500 m derinliklerde trol ile aylık olarak örneklenmiştir. Ortalama toplam boy ve ağırlık sırasıyla 11.43±0.22 cm (aralık:7.2–17.1 cm) ve 11.07±0.66 g (aralık:1.88–33.42 g) olarak belirlenmiştir. Otolit ağırlığı 0.0016–0.0067 g arasında değişirken, otolit uzunluğu 2.73–4.37 mm aralığında bulunmuştur. Toplam boy (TL), toplam ağırlık (TW), otolit uzunluğu (OL) ve otolit ağırlığı (OW) arasındaki ilişkiler hem klasik regresyon analizleri hem de ANN tabanlı tahminler kullanılarak incelenmiştir. TL–TW (R²=0.95), TL–OL (R²=0.90), TL–OW (R²=0.88) ve OL–OW (R²=0.86) ilişkileri güçlü bulunurken, TW–OW ilişkisi daha düşük açıklayıcılık göstermiştir (R²=0.65). Bu bulgular, otolit morfometrisinin C. agassizi’de büyüme desenleri için güvenilir bir gösterge olduğunu ortaya koyarken, ANN modellerinin olası doğrusal olmayan ilişkiler hakkında tamamlayıcı bilgiler sunduğunu göstermektedir.
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UR  - https://doi.org/10.12714/egejfas.43.3.11
L1  - https://dergipark.org.tr/tr/download/article-file/5954281
ER  -