Cross relationships between growth performance, growth composition and feed composition in broiler chickens,...

Area of Science:

• Animal Science
• Poultry Nutrition
• Nutritional Modeling

Background:

• Accurate prediction of daily feed intake (DFI) is crucial for broiler nutrition management.
• Existing models may not fully capture the complex relationships between feed composition, growth, and intake.
• Data from 42 articles (1980-2015) involving 12,277 broilers were analyzed.

Purpose of the Study:

• To develop and validate a system of equations to predict DFI in broilers.
• To establish cross-relationships between key growth and nutritional parameters.
• To provide a framework for future broiler nutritional modeling systems.

Main Methods:

• Regression analysis was used to establish equations for heat production, AME intake (MEI), and body composition.
• A system of 6 interconnected equations was formulated.
• The system integrates equations for MEI, protein gain (PCG), fat gain (FCG), protein efficiency (PE), AME, and DFI.

Main Results:

• The 6-equation system accurately predicted DFI, showing a high correlation (R²=0.880) with measured values.
• Predicted values for DFI, PE, PCG, and FCG aligned with established nutritional principles.
• Regressions for feed efficiency also showed strong predictive power (R²=0.767 and R²=0.747).

Conclusions:

• The developed 6-equation system offers a robust framework for predicting broiler DFI.
• This model can be a valuable tool for optimizing broiler nutrition and feeding strategies.
• The findings support the potential for advanced nutritional modeling in poultry production.