Comprehensive growth modeling of Adana dewlap pigeons' chicks using adaptive Kalman filter techniques

Adana Dewlap pigeons are a unique breed native to the Adana region of Turkey, recognized for their distinctive flight characteristics. The current study investigates the growth dynamics of these pigeons using both traditional and advanced modeling techniques, aiming to identify the most accurate approach. Due to their limited reproductive cycle (typically two or three clutches per year), only a few offspring can be reared annually from a single pair, and many hatchlings do not reach sexual maturity. A dataset comprising 43-day body weight measurements from 88 pigeons collected over seven years was used. The average daily weight was modeled using well-established growth functions, including the Richards, Logistic, and Gompertz models. MATLAB scripts were developed for parameter estimation, and the reliability of model predictions was evaluated using metrics such as Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and R². In addition to static models, this study emphasizes the importance of capturing the temporal dynamics of growth in avian species like the Adana Dewlap pigeon. The Adaptive Kalman Filter (AKF) was employed to decompose the growth process into position, velocity, and acceleration for a more detailed analysis. The velocity curve shows a rapid increase in weight gain during the first two weeks, consistent with a critical post-hatch developmental phase. This is followed by gradual deceleration, suggesting that the pigeons reach a physiological threshold at which weight gain slows due to metabolic adaptation or genetic constraints. Acceleration analysis further substantiates this trend, with positive values during early development and negative values during later stages, characteristic of the asymptotic phase of sigmoidal growth curves, as described by the Logistic, Gompertz, and Richards models. These results demonstrate that AKF not only fits observed data accurately but also reveals latent transitions in growth behavior, offering a robust tool for real-time monitoring and analysis in biological development studies.