Accurately determining nutrient requirements based on animal performance and environmental conditions is essential to developing feeding strategies that optimize resource utilization, enhance productivity, and improve sustainability in poultry production. Traditional empirical dose-response approaches, while practical, are constrained by their experimental conditions. These static models are limited in their applications under variable conditions such as genetic strain, environmental factors, and age. This review aims to promote the use of dynamic factorial models for predicting energy and amino acid requirements in poultry. These models integrate key biological parameters, such as growth and tissue deposition, into nutrient utilization models for implementation in feeding programs. This review presents models for the principal poultry categories (broiler chickens, laying hens, and broiler breeders), based on biological assays developed over two decades of research at the Poultry Science Laboratory of the São Paulo State University (UNESP-Jaboticabal). The principle of the model is based on the growth potential described by the Gompertz function for protein growth, as well as allometric relationships between body protein and the other components (lipid, ash, and water) to predict tissue deposition rates. Body composition was estimated using in vivo measurements such as dual-energy X-ray absorptiometry and indirect calorimetry. Factorial models integrated dynamic growth (whole-body mass or protein growth) and product yield rates body weight gain, egg mass, protein, and lipid deposition) as inputs to partition the energy and amino acids into maintenance, growth, and reproduction. Energy models were further adjusted for environmental temperature, while amino acid models account for the utilization efficiency determined for each amino acid. The models presented here are effective for estimating energy and amino acid requirements, which can help nutritionists define feeding programs adapted to each production condition, improving productivity and sustainability.
Building similarity graph...
Analyzing shared references across papers
Loading...
Nilva Sakomura
Matheus P. Reis
Gabriel S. Viana
Animal nutrition
Universidade Estadual Paulista (Unesp)
Núcleo de Pesquisas Aplicadas (Brazil)
Building similarity graph...
Analyzing shared references across papers
Loading...
Sakomura et al. (Fri,) studied this question.
synapsesocial.com/papers/6a002126c8f74e3340f9bf4e — DOI: https://doi.org/10.1016/j.aninu.2025.12.016