Using a computer-controlled simulated digestion system to predict the energetic value of corn for ducks

Area of Science:

• Animal Nutrition
• Digestive Physiology
• Feed Evaluation

Background:

• Accurate determination of metabolizable energy (ME) and gross energy (GE) in feed ingredients like corn is vital for optimizing poultry diets.
• Traditional in vivo digestibility studies are time-consuming and resource-intensive.
• Development of in vitro methods that accurately predict in vivo energetic values is highly desirable.

Purpose of the Study:

• To develop and validate a computer-controlled in vitro digestion system simulating duck digestion.
• To predict the metabolizable energy (ME) concentration and metabolizability of gross energy (GE) in corn for ducks.
• To establish reliable prediction models correlating in vitro digestible energy (IVDE) with in vivo energetic values.

Main Methods:

• Two experiments were conducted: a calibration experiment using 30 corn samples and a validation experiment using 6 corn samples.
• A computer-controlled digestion system was used to simulate duck digestion and determine in vitro digestible energy (IVDE).
• Linear regression models were established to correlate IVDE with in vivo ME and IVDE/GE with in vivo ME/GE.

Main Results:

• Strong positive correlations were observed between IVDE and various in vivo ME measurements (r > 0.94) and between IVDE/GE and in vivo ME/GE (r > 0.95) in calibration samples.
• Prediction models for ME concentration and ME/GE demonstrated high accuracy, with coefficients of determination > 0.88 and > 0.91, respectively.
• Both calibration and validation samples showed small differences (<100 kcal/kg DM for ME, <2.4% for ME/GE) between determined and predicted values.

Conclusions:

• The developed computer-controlled simulated digestion system accurately predicts the ME and ME/GE of corn for ducks.
• This in vitro system provides a viable and accurate alternative to in vivo methods for feed energy evaluation in poultry.
• The system's predictive capability supports efficient formulation of duck diets based on corn energy content.