The Evaluation for Recent Growth Performance of Bali Cattle using Non-linear Models

Growth curve modeling is essential for understanding livestock development, productivity, and efficiency. This study evaluated the growth patterns of Bali cattle, a resilient and economically significant breed in Indonesia, using five non-linear growth models: Brody, Gompertz, Logistic, Von Bertalanffy, and Modified Von Bertalanffy. Body weight data were collected from 256 males and 279 females at key growth stages from birth to 730 days. Goodness-of-fit criteria including Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), coefficient of determination (R²), and correlation coefficient (r) were applied to identify the most suitable model for describing growth curves. The Gompertz model exhibited the best fit for males, with the lowest AIC (29.76) and BIC (28.58) and highest R² (0.9913) and r (0.9956). For females, the Modified Von Bertalanffy model performed best, with superior goodness-of-fit metrics. Growth parameter analysis revealed that males achieved higher mature weights (A) and slower growth rates (K), whereas females exhibited faster growth rates but matured at smaller sizes. These findings indicate distinct growth dynamics between sexes, influenced by genetic and physiological factors. This research emphasizes the importance of selecting appropriate models to understand critical growth stages, optimize nutrition, and enhance management and breeding strategies. The results offering valuable insights for breeders, farmers, and policymakers aiming to bolster beef production.

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Journal
Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi
Published
2025-06-20
DOI
https://doi.org/10.29133/yyutbd.1646048
Primary Topic
Livestock Farming and Management
Type
article
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article

The Evaluation for Recent Growth Performance of Bali Cattle using Non-linear Models

S. Sutopo, Fariz Zharfan Haris, Firda Tasya Kamila, Asep Setiaji et al.
Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi
Livestock Farming and Management
article

The Evaluation for Recent Growth Performance of Bali Cattle using Non-linear Models

S. Sutopo, Fariz Zharfan Haris, Firda Tasya Kamila, Asep Setiaji, Dinda Ayu Lestari, Putu Novia Gariri, Miaofei Dai, Pupus Galau Prahara, Syaddad Verahry Philco
article en

Abstract

Growth curve modeling is essential for understanding livestock development, productivity, and efficiency. This study evaluated the growth patterns of Bali cattle, a resilient and economically significant breed in Indonesia, using five non-linear growth models: Brody, Gompertz, Logistic, Von Bertalanffy, and Modified Von Bertalanffy. Body weight data were collected from 256 males and 279 females at key growth stages from birth to 730 days. Goodness-of-fit criteria including Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), coefficient of determination (R²), and correlation coefficient (r) were applied to identify the most suitable model for describing growth curves. The Gompertz model exhibited the best fit for males, with the lowest AIC (29.76) and BIC (28.58) and highest R² (0.9913) and r (0.9956). For females, the Modified Von Bertalanffy model performed best, with superior goodness-of-fit metrics. Growth parameter analysis revealed that males achieved higher mature weights (A) and slower growth rates (K), whereas females exhibited faster growth rates but matured at smaller sizes. These findings indicate distinct growth dynamics between sexes, influenced by genetic and physiological factors. This research emphasizes the importance of selecting appropriate models to understand critical growth stages, optimize nutrition, and enhance management and breeding strategies. The results offering valuable insights for breeders, farmers, and policymakers aiming to bolster beef production.

Yüzüncü Yıl Üniversitesi Tarım Bilimleri DergisiVol. 35(2)
Diponegoro University (ID)
Openalex Percentile: Top 80%
Livestock Farming and Management
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The Evaluation for Recent Growth Performance of Bali Cattle using Non-linear Models — S. Sutopo, Fariz Zharfan Haris, et al. · Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi (2025) | TGRS Research Map | TGRS