Modeling heat tolerance for production traits in Canadian Holstein cattle

Area of Science:

• Animal Genetics
• Dairy Science
• Environmental Stress Biology

Background:

• Heat stress significantly impacts dairy cattle productivity and welfare.
• Current methods for assessing heat tolerance often use a common temperature-humidity index (THI) threshold, overlooking individual variations.
• Reaction norm models with linear heat stress functions (HSf) are standard but may not capture nuanced individual responses.

Purpose of the Study:

• To estimate genetic parameters and breeding values for heat tolerance using Legendre polynomials (LP) models that account for individual THI threshold variations.
• To compare these LP model estimates with those from a traditional HSf model.
• To evaluate the impact of different modeling approaches on the genetic evaluation of heat tolerance in Canadian Holstein cows.

Main Methods:

• Utilized test-day records from 300,791 first-parity Holstein cows across Canada, linked with local meteorological data.
• Compared linear, quadratic, and cubic Legendre polynomial (LP) models against a standard heat stress function (HSf) model.
• Assessed model performance using mean squared error (MSE) and analyzed parameter estimates across the THI gradient.
• Correlated breeding values (EBVs) for heat tolerance and milk production traits between LP and HSf models using Spearman rank correlation.

Main Results:

• The quadratic LP model showed good performance across the THI gradient.
• Spearman rank correlations for bull EBVs between LP and HSf models were high (greater than 0.97) for overall heat tolerance.
• Rank correlations for fat, protein, and milk yields under heat stress were substantial (0.97, 0.95, and 0.86, respectively) even when comparing the top 10% of bulls.

Conclusions:

• Both Legendre polynomial and traditional HSf models can effectively identify bulls with superior genetic merit for heat tolerance.
• The choice of model does not substantially alter the ranking of bulls for genetic evaluations.
• The findings support the continued use of these models in Canadian dairy genetic evaluations for heat tolerance.