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Predicting intake and digestibility using mathematical models of ruminal function.

D R Mertens

    Journal of Animal Science
    |May 1, 1987
    PubMed
    Summary
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    Mathematical models integrating feed, animal, and feeding factors improve ruminant diet formulation. These models predict feed intake and digestibility, crucial for optimizing animal nutrition and production efficiency.

    Area of Science:

    • Ruminant nutrition and feed science
    • Mathematical modeling in animal agriculture

    Background:

    • Ruminant feed intake and digestibility are complex, influenced by feed, animal, and feeding conditions.
    • Accurate forage evaluation and diet formulation require integrating these factors into predictive models.

    Purpose of the Study:

    • To develop and present mathematical models for predicting ruminant feed intake and digestibility.
    • To integrate physiological, physical, and psychogenic factors into intake regulation models.
    • To refine digestibility predictions using ideal nutritive entities and steady-state kinetics.

    Main Methods:

    • Developed theoretical equations based on physiological and physical intake regulation theories.
    • Incorporated animal characteristics (body weight, production level) and feed characteristics (neutral detergent fiber, energy content).

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  • Utilized steady-state models to define nutritive entities and predict digestibility based on digestion and passage rates.

    • Main Results:

    • Intake is modeled as a linear function of animal traits and a reciprocal function of feed traits.
    • Models predict maximum intake for specific production levels by intersecting intake regulation equations.
    • Digestibility prediction incorporates ideal nutritive entities, endogenous losses, and digestible fiber, accounting for passage rate effects.

    Conclusions:

    • Mathematical modeling provides a robust framework for understanding and predicting ruminant feed intake and digestibility.
    • These models are essential tools for advancing forage evaluation and optimizing ruminant diet formulation.
    • Understanding the interplay of physiological, physical, and psychogenic factors enhances nutritional management strategies.