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Prediction of metabolizable energy intake of laying hen strains using a mathematical model and its relation to energy requirements with varying bird cage space

Mohammad A Jalal, University of Nebraska - Lincoln

Abstract

In trial one, four models (Combs, 1968, Emmans, 1974; NRC; 1981, and NRC, 1994) were used to predict metabolizable energy intake (MEI) of laying hens (Babcock B300, Hy-Line, W-36, Shaver White and, Hy-Line W98) during thermoneutral and heat stress conditions. Hens were fed three diets (moderate ME, and low ME with and without enzyme) in a factorial arrangement. Under thermoneutral condition Combs model was the most accurate predictor while NRC models were least accurate for diet and strain. Heat stress data showed that all models overpredcited MEI. Modification improved prediction accuracy under thermoneutral conditions only. In trial two, the same models and our Jalal model were evaluated for three White Leghorn strains (Hy-Line W36, Hy-Line W-98, and Bovans) fed two diets (high ME, and low ME) in a factorial arrangement. Preliminary model evaluation resulted in omission of Combs model from further evaluation because of poor prediction accuracy. Modification of remaining models showed modified Emmans, NRC and Jalal to be better predictors of MEI for Hy-Line W-36, Emmans for Hy-W98, and Jalal for Bovans. Field-testing of strain-derived equations showed that Emmans, NRC and Jalal models predicted MEI accurately for all strains. In Trial 3, laying hens housed at four cage spaces (342, 413, 516, and 690 cm2/hen) were fed three diets (high, intermediate and low ME). Increasing cage space improved feed and MEI intakes, egg mass, egg production, eight gain, and ME dietary efficiency, while energy level improved ME digestibility.

Subject Area

Livestock

Recommended Citation

Jalal, Mohammad A, "Prediction of metabolizable energy intake of laying hen strains using a mathematical model and its relation to energy requirements with varying bird cage space" (2003). ETD collection for University of Nebraska-Lincoln. AAI3116580.
https://digitalcommons.unl.edu/dissertations/AAI3116580

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