Non-Destructive ANN Model for Epinephelus costae in Syria (2026)

# Non-Destructive ANN Model for *Epinephelus costae* in Syria (2025) **Author**: Nader Iskandar Hamwi **Affiliation**: Department of Animal Production, Latakia University, Syria **Contact**: [e-mail] **Manuscript**: Published in *PeerJ* (2026) 🔗 https://peerj.com/articles/21243 🆔 DOI: 10.7717/peerj.21243 ## 📖 DescriptionThis repository contains:- Original biological data (n=150) of *Epinephelus costae* from Syrian coastal waters (2024–2025)- Trained Artificial Neural Network (MLP 1–10–2) parameters for non-destructive age and maturity estimation- Minimal Python script for field prediction using only total length (cm) ## 📌 Citation RequirementIf you use this model, data, or code in any form, you **must cite** the final published article:> Hamwi, N. I. (2026). An ANN-based non-destructive model for age and maturity estimation in the data-deficient Goldblotch Grouper (*Epinephelus costae*). *PeerJ*, 14, e21243. https://doi.org/10.7717/peerj.21243 ## ⚠️ Usage Conditions- **Non-commercial academic research only**.- Field deployment, mobile app development, or policy integration requires prior collaboration with the author to ensure biological validity, ethical use, and co-ownership of adaptations.- The model is trained on **Syrian *E. costae* data** (Lₘ = 30 cm, max age = 12 years). Performance may degrade in other regions without recalibration. ## 📂 Files- `Dataset_Syria_Ecostae.csv`: Original field data (length, age, maturity)- `ANN_weights_biases_Ecostae_Syria.txt`: Full model parameters