AUTHOR=Oloo Richard D. , Mrode Raphael , Bennewitz Jörn , Ekine-Dzivenu Chinyere C. , Ojango Julie M. K. , Gebreyohanes Gebregziabher , Mwai Okeyo A. , Chagunda Mizeck G. G. 

TITLE=Potential for quantifying general environmental resilience of dairy cattle in sub-Saharan Africa using deviations in milk yield

JOURNAL=Frontiers in Genetics

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2023.1208158

DOI=10.3389/fgene.2023.1208158

ISSN=1664-8021

ABSTRACT=Genetic improvement of general resilience of dairy cattle is deemed as a part of the solution to low dairy productivity and poor cattle adaptability in sub-Saharan Africa (SSA). Although indicators of general resilience have been proposed and tested elsewhere, they are yet to be tested in SSA. This study aimed to test the potential of using log-transformed variance (LnVar), autocorrelation (rauto), and skewness (skew) of deviations in milk yield in assessing the general resilience of dairy cows performing in the tropical environment of Kenya. To achieve this, we investigated the genetic parameters of resilience indicators derived from both actual and standardized deviations and their relationship with longevity and average test-day milk yield. Test-day milk yield records of 2,670 first-parity cows performing in three different agroecological zones of Kenya were used. Lactation curve was modeled for each cow using quantile regression method. Actual and standardized deviations from these curves were then used to calculate these indicators. All indicators were heritable except the two Skew indicators. The log-transformed variance of actual (LnVar1) and standardized (LnVar2) deviations had the highest heritabilities of 0.19 and 0.17, respectively. Auto-correlation of actual (rauto1) and standardized (rauto2) deviations had 0.05 and 0.07, respectively. Genetic correlations among resilience indicators were weak to moderate. Both rauto and Skew indicators had negligible genetic correlations with both longevity and average test-day milk yield, indicating that they might not be ideal indicators of resilience in these environments. LnVar1 and LnVar2 were genetically associated with better longevity (rg = 0.43 to 0.50). Whereas LnVar1 showed that resilient animals produce low average test-day milk yield, LnVar2 found resilience to be genetically associated with high average test-day milk yield. These findings demonstrate that LnVar of deviations has a strong potential to be utilized as a resilience indicator for dairy animals performing in SSA. Moreover, standardized as opposed to actual deviations should be used to calculate LnVar because the resultant indicator does not inaccurately conclude that low-producing animals are resilient. This study offers an opportunity to improve the productivity of dairy cattle performing in the tropical conditions of SSA by breeding for resilience to environmental stressors.