3 Overview of Poultry Modeling Evolution

Abstract

Abstract This presentation aims to review advances in mathematical models used in poultry nutrition and production in the past decades and present an overview of the current status. Models have been developed to improve understanding of growth, voluntary feed intake, nutrient utilization, body composition, responses to nutrient supply, environmental changes, and stressors. Growth models for broilers, turkeys, ducks, layers, and breeders are available mainly based on the Gompertz curve, but a few other mathematical functions are also used. A few models can simulate egg production in layers and breeders. The EFG and Avinesp models, tools from feed additive and genetic companies, among others, will be described or mentioned. These models can describe genetic differences and estimate energy, amino acids, calcium, and phosphorus requirements or multiple biological responses to specific nutrient levels. Most models use the concept of ideal protein or balanced protein to describe responses to amino acid levels. However, very few models can describe responses to modifications of one or two specific amino acids. Compartmental models are mainly based on main chemical components such as water, body and feather protein, fat, and ash. Poultry models seldom consider variability due to feeding ingredient quality, fiber, fat, other mineral composition, or variation in nutrient digestibility. However, some models can predict responses to exogenous enzymes. Most applications can predict body weights and yields at a specific age, and some can estimate nitrogen, calcium, and phosphorus excretion. These models can be integrated with feed formulation software, economic data, and optimizers to simulate multiple conditions and estimate biological, economic, and environmental optimums. Poultry enterprise models can describe the whole production system, estimate the optimum combination of resources, aid in planning and scheduling, and determine strategies for growth. Currently, no official recommendations from academic or private groups are based only on models to estimate nutrient levels. Combinations of empirical data and model results are frequently used for nutritional decision-making. A few tools are available for specialized personnel to decide the energy and amino acid levels to use. The application of electronics and telecommunications triggered the fast production of enormous volumes of data from diverse poultry production sectors. This big data avalanche is starting to help modelers to integrate more accurate information and incorporate natural variability. However, integration between current models and significant data results is still under development. Despite increasing international collaboration in modeling, poultry model developments keep great independence and fundamental differences. One critical issue needed for faster development of poultry modeling is to increase education in modeling. The lack of academic programs offering modeling classes related to poultry caused the low current application of models. However, awareness about the benefits of modeling has increased in the past few years, and efforts are under development.