Predicting growth and performance of Holstein steers

Area of Science:

• Animal Science
• Agricultural Engineering
• Nutritional Physiology

Background:

• Predictive models are crucial for optimizing cattle growth and feed efficiency.
• Previous models require updates to reflect current feeding practices and genetic advancements.
• Accurate prediction of dry matter intake (DMI), average daily gain (ADG), and feed per gain (FPG) is essential for livestock management.

Purpose of the Study:

• To refine and validate an existing cattle growth model for Holstein steers.
• To improve the accuracy of predicting DMI, ADG, and FPG in growing Holstein steers.
• To assess the model's performance across diverse feeding trials and conditions.

Main Methods:

• Modification of the Fox et al. (1988) cattle growth model.
• Testing the modified model on a database of 299 feeding periods from Holstein steers.
• Data collected over 15 years from Cornell University, University of Minnesota, and University of Wisconsin.

Main Results:

• The modified model explained 93% of variation in DMI, 56% in ADG, and 68% in FPG.
• Average prediction errors were 1% for DMI, 4% for ADG, and 2% for FPG.
• Model accuracy was not influenced by metabolizable energy (ME) levels but showed overprediction of DMI for heavier cattle (>318 kg).

Conclusions:

• The refined model accurately predicts the performance of Holstein steers.
• The model's predictions for DMI, ADG, and FPG are reliable for Holstein steers, particularly those slaughtered under 15 months.
• The study highlights the need to adjust DMI predictions for heavier cattle based on specific breed and management factors.