Analysis of Egg Production Curves Using Three Mathematical Models and the Variation in Egg Quality between Commercial (Hy-Line Brown) Layer Hens and Sentul Hens

Subject Areas :

S.A. Santosa ¹ , I. Ismoyowati ^{2 *} , D. Purwantini ³ , A. Susanto ⁴ , M.Y. Abare ^{5 *}

1 - Department of Animal Husbandry, Faculty of Animal Science, University of Jenderal Soedirman, Purwokerto, Central Java, Indonesia
2 - Department of Animal Husbandry, Faculty of Animal Science, University of Jenderal Soedirman, Purwokerto, Central Java, Indonesia
3 - Department of Animal Husbandry, Faculty of Animal Science, University of Jenderal Soedirman, Purwokerto, Central Java, Indonesia
4 - Department of Animal Husbandry, Faculty of Animal Science, University of Jenderal Soedirman, Purwokerto, Central Java, Indonesia
5 - Department of Agricultural Biotechnology, Faculty of Postgraduate, University of Jenderal Soedirman, Purwokerto, Central Java, Indonesia

Received: 2024-06-22 Accepted : 2024-11-15 Published : 2024-12-01

Keywords: egg production and quality, genetic variation, Hy-Line Brown hens, mathematical models, selective breeding, Sentul Hens,

Abstract :

Egg production is a crucial economic trait in poultry, with heritability challenges. The study investigated egg production and quality in commercial (Hy-Line Brown) and local (Sentul) chicken strains through mathematical modeling and detailed egg quality assessments. Utilizing 100 hens from each strain for up to 80 weeks, mathematical models: Gamma Wood, Quadratic, and Quartic, were applied to analyze egg pro-duction curves. The Quartic model exhibited outstanding accuracy, surpassing other models with signifi-cantly higher coefficients of determination (R2) for both Hy-Line Brown (R2=89.67%) and Sentul (R2=89.92%) hens showing the Quartic model's superior ability to precisely represent the persistence in egg production curves over time. Correlation analysis identified multiple linkages shaping egg quality, notably positive relationships of egg weight with shell strength, yolk color, yolk weight, albumen weight and shell weight as well as a trade-off between egg weight and Haugh units. Egg quality parameters were systemati-cally compared. Commercial hens demonstrated significantly (P<0.005) higher values in several quality parameters, including egg weight (62.35±5.02 g), shell strength (0.42±0.10), albumen weight (32.5±2.71 g), Haugh Unit (95.99±7.94), and shell weight (8.16±0.86 g), compared to local hens. Positive correlations were identified between egg weight and shell strength (0.224**), yolk color (0.033), yolk weight (0.968**), albumen weight (0.993**), and shell weight (0.488**). Conversely, a negative correlation is noted between egg weight and Haugh Unit (-0.040), indicating a trade-off between egg size and freshness. The Identified correlations between egg weight and quality parameters showed the multifaceted nature of egg characteris-tics, shaped by genetic and management factors. These findings provide comprehensive insights into the genetic and environmental influences on egg production and quality, offering a foundation for selective breeding strategies and management practices permitting productive strategies to ensure animal welfare in diverse chicken populations. This research notably illuminates untapped potential of the Quartic model for forecasting laying persistence amidst environmental fluctuations, while also suggesting hybridization op-portunities to infuse specialized commercial vigor and consistency into local gene pools. With global de-mand for affordable, quality nutrition expanding amidst climate change, these unified insights to bolstering egg quantity and quality through predictive modeling and strategic breeding carry far-reaching implications for sustaining poultry production.

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