Research Note: Analysis of Growth Curve Patterns for Muscovy Ducks Using Gompertz and Logistic Models

This study aimed to estimate the growth parameters of Muscovy ducks. The superiority of the study offers insightful information on the Muscovy duck growth curve, makes quantitative comparisons easier, allows for predictive capacities, and quickly finds problems. A total of 40 Muscovy ducks called “R...

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Bibliographic Details
Published in:Poultry science journal (Online) Vol. 12; no. 2; pp. 161 - 167
Main Authors: Sifa Ussyarif, Edy Kurnianto, Asep Setiaji
Format: Journal Article
Language:English
Published: Gorgan University of Agricultural Sciences and Natural Resources 01-09-2024
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Summary:This study aimed to estimate the growth parameters of Muscovy ducks. The superiority of the study offers insightful information on the Muscovy duck growth curve, makes quantitative comparisons easier, allows for predictive capacities, and quickly finds problems. A total of 40 Muscovy ducks called “Rambon” were used in the study, consisting of 12 males and 28 females. Body weight was weighed periodically every two days from the day-old ducks (DOD) until 60 days of age. The data was analyzed by using Gompertz and Logistic models. The growth curves were analyzed, and parameters such as adult body weight (A), integral constant (B), and growth rate (K) were determined. Inflection points were also identified. Body weight (Wi) and age at the inflection (Ai) point using Gompertz were 1060.95 g and 46.34 d; 613.41 g and 30.52 d; 712.56 g and 36.81 d, respectively for males, females, and the unsexed. By using Logistic model, the Wi and Ai for males were 934.60 g and 41.46 d, females were 670.52 g and 32.96 d, and unsexed were 739.11 g and 36.56 d. Results showed that the Gompertz model generally outperformed the Logistic model, with lower AIC, BIC, MSE values and slightly higher R2 for all sex groups, indicating superior fit and predictive accuracy. These findings offer valuable insights into Rambon Muscovy duck growth dynamics, aiding in breeding and production strategies to enhance economic efficiency and sustainability. Farmers can utilize these models to optimize feeding schedules and make informed decisions about slaughtering, ultimately improving Muscovy duck production.
ISSN:2345-6604
2345-6566
DOI:10.22069/psj.2024.21840.1991