Gompertz函数
氨基酸
营养物
生物
生物系统
生物技术
肉鸡
生化工程
数学
必需氨基酸
析因实验
异速滴定
必需营养素
经验模型
功能(生物学)
产量(工程)
主成分分析
能量平衡
能源
生物化学
持续性
数学模型
丝氨酸
预测建模
体重
环境科学
计算机科学
发酵
能量需求
食品科学
作者
Nilva Sakomura,Matheus P. Reis,Gabriel S. Viana,Rony [UNESP] Riveros
标识
DOI:10.1016/j.aninu.2025.12.016
摘要
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.
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