Predicting Intake and Digestibility Using Mathematical Models of Ruminal Function

TLDR

Intake and digestibility in ruminants depend on feed, animal, and feeding factors, and can be modeled by simple equations that relate intake to animal traits, feed characteristics, and psychogenic multipliers. The study aims to integrate feed, animal, and feeding characteristics into mathematical models to improve forage evaluation and diet formulation for ruminants. The authors developed theoretical equations that predict intake from diet fiber and energy and animal requirements, determine maximum intake for a given production level, and estimate digestibility by summing ideal nutritive entities, adjusting for endogenous losses, and applying steady‑state digestion and passage rates. Steady‑state solutions effectively predict how increased passage rates at high intake depress digestibility.

Abstract

Intake and digestibility of feeds by ruminants are influenced by characteristics of the feed, animal and feeding situation. Integration of these characteristics in mathematical models is critical to future progress in forage evaluation and optimal formulation of diets for ruminants. The physiological and physical theories of intake regulation can be described by simple mathematical equations. These equations indicate that intake is a linear function of animal characteristics, such as body weight and production level, and a reciprocal function of feed characteristics, such as fill effect and energy content. Theoretical equations were developed to predict intake when the neutral detergent fiber and energy content of the diet and the energy requirements of the animal are known. The theoretical model also can be used to predict the maximum intake that will maintain a given level of animal production by solving the physiological and physical intake equations at their intersection. Psychogenic intake regulation, which is related to the animal's behavioral response to factors not related to physiological or physical characteristics, can be described mathematically as a multiplier. Digestibility can be predicted by summing the contents of ideal nutritive entities in feeds, which have true digestibilities near 100%, subtracting their associated endogenous losses and adding the variable digestible fiber content. Steady-state models indicate fractional rates of digestion and passage can be used to define ideal nutritive entities and predict digestibility over a range of kinetic characteristics. The steady-state solutions are particularly useful in understanding and predicting the depression in digestibility associated with changes in rates of passage at high levels of feed intake.