# Genetic parameters for alternative resilience phenotypes in Holstein cows

## TL;DR

This study identifies that genetic selection for milk yield changes during disturbances can improve resilience in dairy cows without reducing productivity.

## Contribution

The study introduces ΔMY as a more heritable and informative resilience phenotype for genetic selection in Holstein cows.

## Key findings

- Resilience indicators calculated over the entire perturbation period had higher heritability than single-day metrics.
- ΔMY showed more desirable genetic correlations with 305-day milk yield compared to other resilience traits.
- Genetic selection for ΔMY can improve resilience while maintaining high milk production.

## Abstract

Summary: Resilience in dairy cattle refers to the ability to withstand or recover rapidly from environmental disturbances. With increasing climate and feed variability, labor shortages, and disease risks, improving animal resilience through genetic selection is critical. This study evaluated 7 alternative phenotypes of resilience for 34,044 US Holstein cows during a perturbation. Cows were grouped by their response to and recovery from the event, using measures of milk yield change (ΔMY) and milk yield residuals on specific days. Our results showed that resilience indicators calculated over the entire perturbation period, especially ΔMY, had higher heritability and more desirable genetic correlations with 305-day milk yield than single-day metrics. These findings suggest that ΔMY is a more informative phenotype for identifying genetically resilient cows. Selecting for this trait could help improve resilience in dairy herds while maintaining high productivity, making it a valuable tool for modern dairy farming.

Summary: Resilience in dairy cattle refers to the ability to withstand or recover rapidly from environmental disturbances. With increasing climate and feed variability, labor shortages, and disease risks, improving animal resilience through genetic selection is critical. This study evaluated 7 alternative phenotypes of resilience for 34,044 US Holstein cows during a perturbation. Cows were grouped by their response to and recovery from the event, using measures of milk yield change (ΔMY) and milk yield residuals on specific days. Our results showed that resilience indicators calculated over the entire perturbation period, especially ΔMY, had higher heritability and more desirable genetic correlations with 305-day milk yield than single-day metrics. These findings suggest that ΔMY is a more informative phenotype for identifying genetically resilient cows. Selecting for this trait could help improve resilience in dairy herds while maintaining high productivity, making it a valuable tool for modern dairy farming.

•Resilience in cows is defined after identifying that a perturbation has occurred.•Seven novel resilience traits were tested for 34,044 US Holsteins.•ΔMY over the full perturbation period had the highest heritability for resilience.•Single-day metrics were less informative for genetic selection.•Genetic selection for ?MY can improve resilience while maintaining milk production.

Resilience in cows is defined after identifying that a perturbation has occurred.

Seven novel resilience traits were tested for 34,044 US Holsteins.

ΔMY over the full perturbation period had the highest heritability for resilience.

Single-day metrics were less informative for genetic selection.

Genetic selection for ?MY can improve resilience while maintaining milk production.

The ability of an animal to be minimally affected by or bounce back rapidly from a disturbance is known as resilience. With increasing variability in climate conditions, along with skilled labor shortages and disease outbreaks, the value of genetic selection of animals for increased resilience has become important. The goal of this study was to assess alternative resilience phenotypes in lactating Holstein cows. Our data set included 34,044 US Holstein cows from parities 1, 2, or 3 that experienced a single perturbation lasting at least 5 d but up to 14 d, with a severity of at least 5% for the entire duration of the perturbation. Perturbations were identified by detecting runs of poor performance at the pen level as the percentage difference between mean expected and mean observed milk production levels. After identifying the date within a detected perturbation with the lowest mean daily milk production level (nadir), we investigated 7 different resilience phenotypes for individual cows, comprising 2 distinct groups. The first consisted of 4 resilience phenotypes calculated using change in milk yield (ΔMY) over numerous days relative to the pen nadir. These phenotypes include (1) ΔMY throughout the entire event, (2) ΔMY before the nadir, (3) ΔMY near the nadir (1 d before, on the nadir, and 1 d after the nadir), and (4) ΔMY after the nadir. The second group of resilience phenotypes were calculated using a single day during the perturbation and include (5) residual on d 1 of the perturbation, (6) residual at the nadir, and (7) residual on the last day of the perturbation. Heritabilities for resilience phenotypes were estimated using a univariate model, whereas genetic correlations between resilience phenotypes and with 305-d milk yield were estimated using a bivariate model. Heritability (SE) estimates ranged from 0.004 (0.004) to 0.04 (0.009) for resilience phenotypes. Resilience traits calculated over the entire or partial perturbation period tended to show higher heritability estimates than those calculated using a residual on a single day. Genetic correlations among resilience indicators ranged from 0.21 (0.01) to 0.99 (0.01) and with 305-d milk yield ranged from −0.02 (0.45) to −0.30 (0.38), indicating potential to select for increased resilience while simultaneously increasing milk production. Overall, our findings suggest that resilience indicators based on subsets of the perturbation period or on single-day measurements tend to have low heritability. In contrast, resilience indicators calculated across several days within the perturbation period, such as ΔMY, capture greater genetic variation in resilience and are therefore more appropriate for the genetic improvement of resilience in dairy cattle.