Estimation of genetic parameters for milk and fertility traits within and between low, medium and high dairy production systems in Kenya to account for genotype‐by‐environment interaction

Abstract

Dairy records from the Dairy Recording Service of Kenya were classified into low, medium and high production systems based on mean 305‐day milk yield using the K‐means clustering method. Milk and fertility records were then analysed to develop genetic evaluation systems accounting for genotype‐by‐environment interaction between the production systems. Data comprised 26,638 lactation yield, 3,505 fat yield, 9,235 age at first calving and 17,870 calving interval records from 12,631 cows which were descendants of 2,554 sires and 8,433 dams. An animal model was used to estimate variance components, genetic correlations and breeding values for the production systems. Variance components increased with production means, apart from genetic group variances, which decreased from the low to the high production system. Moderate heritabilities were estimated for milk traits (0.21–0.27) and fat traits (0.11–0.38). Low heritabilities were estimated for lactation length (0.04–0.10) and calving interval (0.03–0.06). Moderate heritabilities (0.25–0.26) were estimated for age at first calving, except under the high production system (0.05). Within production systems, lactation milk yield, 305‐day milk yield and lactation length had high positive genetic correlations (0.52–0.96), while lactation milk yield and lactation length with age at first calving had negative genetic correlations. Milk yield and calving interval were positively correlated except under the low production system. The genetic correlations for lactation milk yield and 305‐day milk yield between low and medium (0.48 ± 0.20 and 0.46 ± 0.21) and low and high production systems’ (0.74 ± 0.15 and 0.62 ± 0.17) were significantly lower than one. Milk yield in the low production system is, therefore, a genetically different trait. The low genetic correlations between the three production systems for most milk production and fertility traits suggested that sires should be selected based on progeny performance in the targeted production system.

Genetic parameters for test-day milk yield, lactation persistency, and fertility in low-, medium-, and high-production systems in Kenya

“…Test-day milk yield records from multiple-breed cow populations in Kenya were analyzed in this study to estimate genetic parameters. Herds were grouped into low-, medium-, and high-production systems based on mean production level (Wahinya et al, 2020). Multivariate random regression models were then used to estimate (co)variance components for test-day milk yield and lactation persistency in the first 4 lactations.…”

“…Herds were classified into low-, medium-, and highproduction systems based on their mean 305-d milk yield (Wahinya et al, 2020). Herd effects were predicted for 305-d milk yield in a linear mixed model, with calving year, parity, and breed group as fixed effects and herd and residual as random effects.…”

“…A dairy performance recording scheme using test-day milk yield has been implemented by the Dairy Recording Services of Kenya in Naivasha. The participating herds represent quite diverse production environments and have been grouped into low-, medium-, and highproduction systems based on their level of production (Wahinya et al, 2020). Holstein-Friesian and Ayrshire are the dominant breeds, with crosses making up 50% of the total herd (Muriuki, 2011).…”

Economic values for sustainable dairy cattle breeding in the tropics: A focus on climate change responsive traits

“…This could explain Bebe et al (2003)'s recommendation that smallholder dairy farmers raise smaller breeds such as Guernsey, Jersey, and their crosses. This premise is supported by the existence of low genetic correlations between smallholder and large scale farms, which are the primary sources of breeding stock for milk and fertility traits [42] . Since climate change poses the biggest risk to developing countries, this problem is anticipated to get worse [37] .…”

“…However, inflation rate, alteration of production systems and farmers' preferences to breeds and traits [28] in the face of climate change would also affect economic values. It has therefore been recommended that, economic values should be reviewed over time to account for production dynamics [42] . Therefore, inflation and inclusion of climate change responsive traits makes it important to update the current economic values in the breeding goal.…”