ISSN 3156-3104
The present study addresses the need for more efficient, high‑quality, and cost‑effective poultry processing by focusing on the optimization of broiler de‑feathering operations. De‑feathering quality directly affects the broiler appearance, product value, and processing costs, yet settings are often chosen by trial‑and‑error which leads to incomplete feather removal, skin damage, and reduced efficiency. This study provides a data‑driven solution, Response Surface Methodology (RSM) with a three‑variable, five‑level Central Composite Design to optimize key process parameters, including scalding time, de‑feathering time, and bird weight, at constant scalding temperature of 85 °C. Twenty experimental runs were conducted using a fabricated de‑feathering machine, and plucking efficiency was calculated from measured feather mass removal, and the boilers’ weights. RSM produced a quadratic regression model with high predictive power, with coefficient of determination (R2) of 0.9845. This indicates that more than 98 % of the variation in plucking efficiency is explained by the selected variables. ANOVA confirmed the model’s overall significance (Model F = 70.53, p < 0.0001), with scalding time, de‑feathering time, bird weight, all interaction terms, and all quadratic terms showing statistically significant effects on plucking efficiency (p < 0.05). Optimization using desirability functions identified the best operating parameter as 57.14 s scalding time, 50.17 s de‑feathering time, 85 °C scalding temperature, and 6.77 kg bird weight which yielded a maximum plucking efficiency of 98.58 % and desirability of 1.0. The study demonstrates that informed control of de‑feathering parameters via RSM‑based modelling and optimization significantly enhances plucking efficiency, product quality, and process consistency.
Keywords: Response Surface Methodology, Process Optimization, Broiler De-feathering, Plucking Efficiency, Poultry Processing