Meta-Regression to Develop Predictive Equations for Urinary Nitrogen Excretion of Lactating Dairy Cows

Area of Science:

• Animal Science
• Environmental Science
• Agricultural Science

Background:

• Dairy cows excrete significant urinary nitrogen (UN), contributing to environmental pollution.
• Existing models inadequately predict UN from total mixed ration (TMR) and fresh forage (FF) diets.
• Accurate UN prediction is crucial for mitigating environmental impacts.

Purpose of the Study:

• Evaluate existing models for predicting dairy cow UN.
• Develop new predictive equations for UN using animal and dietary factors.
• Improve the accuracy of UN prediction models for dairy cows.

Main Methods:

• Meta-analysis of 51 experiments (174 treatment means).
• Evaluation of three existing UN prediction models for bias and accuracy.
• Development and validation of new UN prediction models using training and test datasets.
• Inclusion of animal factors (milk urea nitrogen, body weight) and dietary factors (diet type, DMI, NDF, CP).

Main Results:

• Existing models showed significant biases and poor predictive capabilities (high RPE).
• Initial models using only animal factors had poor agreement (CCC=0.50) and high RPE (24.7%).
• Models incorporating both animal and dietary factors demonstrated excellent agreement (CCC ≥ 0.86) and low RPE (≤13.1%).

Conclusions:

• Existing UN prediction models are inadequate for dairy cows.
• Integrating animal and dietary factors significantly improves UN prediction accuracy.
• New, precise equations were developed for predicting UN in dairy cows across different feeding systems.