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

Influence of different environmental challenges on the expression of reproductive traits in Holstein cattle in Southern Brazil

The aim of this study was to assess the impact of genotype-environment interaction (GEI) on the manifestation of traits such as age at first calving (AFC), age at first service (AFS), and calving interval (CI) through the application of the reaction norm model in Holstein cattle raised in Paraná state, Brazil. Utilizing data from the milk testing service of the Paraná Association of Holstein Cattle Breeders (APCBRH), this study analyzed records from 179,492 animals undergoing their first, second, and third lactations from the years 2012 to 2022. These animals were part of 513 herds spread across 72 municipalities in Paraná. The environmental gradient was established by normalizing contemporary group solutions, derived from the animal model, with the 305-day-corrected milk yield serving as the dependent variable. Subsequently, reaction norms were determined utilizing a Random Regression Model. Spearman's correlation was then applied to compare the estimates of breeding values across different environmental gradients for the studied traits. The highest EG (+ 4) indicates the least challenging environments, where animals experience better environmental conditions. Conversely, lower EG (-4) values represent the most challenging environments, where animals endure worse conditions. The only trait that exhibited a moderate heritability magnitude was AFC (0.23) in the least challenging environmental condition. The other traits were classified as having low heritability magnitudes regardless of the evaluated environmental gradient. While minimal evidence was found for the influence of GEI on CI, a clear GEI effect was observed for AFC and AFS across all environmental gradients examined. A reversal in genotype ranking occurred under extreme environmental conditions. The findings suggest that the best-performing genotype under one environmental gradient may not necessarily excel under another.

Economic viability of using OvSynch and fixed timed artificial insemination protocol in breeding improvement of pastoral herds in the rangelands

Though using Assisted Reproductive Technologies (ARTs) can improve oestrus detection, conception and pregnancy success, thus benefit breeding program implementation, empirical evidence of their economic viability is lacking to inform investment decisions in pastoral herds. This study assessed economic viability of using OvSynch and fixed Timed Artificial Insemination (TAI) protocol in Sahiwal upgrading breeding program under two hypothetical cases of best and worst in activity-based money allocations when pastoral herds deploy either optimal or low input husbandry practices. From herd owners' assessment of milk production, best-case scenarios attain on average 10 L/cow/day with optimal husbandry and 5 L/cow/day with low input husbandry. The worst-case scenarios attain 5 L/cow/day with optimal husbandry and 1 L/cow/day with low input husbandry. Benefit- Cost Analysis (BCA) estimated Net Present Value (NPV), Benefit-Cost ratio (BCR) and Internal Rate of Return (IRR) to establish economic viability of using OvSynch and TAI Protocol in pastoral breeding programs. Both best-case scenarios retuned positive NPVs (82,028 and 6,912), BCR values (1.68 and 1.08) and IRR (27.46% and 8.08%) while worst-case scenarios returned negative NPVs (-135,855 and -141,025), BCR values of below 1 (0.87 and 0.66) and IRR values below the minimum rate of returns. These economic parameters were sensitive to price changes in inputs and outputs, under both optimal and low input husbandry practices. Results indicate that using OvSynch and TAI Protocol is a profitable and economically viable investment under optimal husbandry practices but not under low input husbandry practices. By implications, use of OvSynch and TAI Protocol in Sahiwal upgrading breeding programs need be accompanied with improved husbandry practices and de-risking pastoral herd owners from price changes in input and output markets.

Heterogeneity of variance and genetic parameters for milk production in cattle, using Bayesian inference

The goal of this study was to verify the effect of heterogeneity of variance (HV) on milk production in up to 305 days of lactation (L305) of daughters of Girolando, Gir and Holstein sires, as well as in the genetic evaluation of these sires and their progenies. in Brazil. The model included contemporary groups (consisting of herd, year and calving season) as a fixed effect, cow age at calving (linear and quadratic effects) and heterozygosity (linear effect) as covariates, in addition to the random effects of direct additive genetic and environmental, permanent and residual. The first analysis consisted of the single-trait animal model, with L305 records (disregarding HV). The second considered classes of standard deviations (SD): two-trait model including low and high classes (considering HV), according to the standardized means of L305 for herd-year of calving. The low SD class was composed of herds with SD equal to or less than zero and the high class with positive SD values. Estimates of (co)variance components and breeding values were obtained separately for each scenario using Bayesian inference via Gibbs sampling. Different heritability was estimated. Higher for the high DP class in the Gir (0.20) and Holstein (0.15) breeds, not occurring the same in the Girolando breed, with a lower value among the classes for the high DP (0.10). High values of genetic correlations were also found between low and high SD classes (0.88; 0.85 and 0.79) for the Girolando, Gir and Holstein breeds, respectively. Like the order correlations (Spearman) which were also high for the three breeds analyzed (equal to or above 0.92). Thus, the presence of HV had a smaller impact for L305 and did not affect the genetic evaluation of sires.

Breeding objectives for dairy cattle under low, medium and high production systems in the tropics

A deterministic bio-economic model was developed to estimate economic weights for genetic improvement of lactation milk yield, fat yield, age at first calving, calving interval, mature weight and survival under low, medium and high production systems in the Tropics. Input parameters were obtained from dairy production systems in Kenya which has a tropical environment. The highest proportion of revenue is from the sale of milk followed by sale of heifers, cull cows and sale of male calves under all production systems. On the other hand, feed cost is the most important production cost followed by labour, marketing, reproduction and health costs, respectively. Economic values for the six traits were derived from a profit equation using revenue and production costs per cow per year. The economic values were then discounted using diffusion coefficients which account for differences between traits in the time when the improvement is expressed. Economic weights were robust to changes in input and output prices, changes in feeding strategies, and changes in milk and surplus heifer marketing strategies. Genetic standard deviations were multiplied by economic values to standardise the economic value of traits and to compare their potential for economic response. When expressed as proportion of their sum, these relative economic weights under the low, medium and high production systems for lactation milk yield were 51.36, 59.79 and 63.98%; for fat yield 4.50, 10.69 and 9.05%; for age at first calving 3.16, 2.66 and 0.55%; for calving interval 33.59, 19.88 and 20.05%; for mature weight 1.55, 1.34 and 1.19% and for survival rate 5.84, 5.64 and 5.18%, respectively. The predicted responses followed the same pattern as the relative economic weights. This shows that milk yield and calving interval were most important in all production systems but the value of response for traits differed between production systems with more emphasis on milk yield and less on calving interval in the high production systems. Moderate correlations were estimated between the breeding objective for the low, medium and high production systems. To maximise response in the overall breeding objective, different selection criteria are required for the three production systems.

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

Genetic parameters for test-day milk yield, lactation persistency, and age at first calving (as a fertility trait) were estimated for the first 4 lactations in multiple-breed dairy cows in low-, medium-, and high-production systems in Kenya. Data included 223,285 test-day milk yield records from 11,450 cows calving from 1990 to 2015 in 148 herds. A multivariate random regression model was used to estimate variance and covariance components. The fixed effects in the model included herd, year, and test month, and age as a covariate. The lactation profile over days in milk (DIM) was fitted as a cubic smoothing spline. Random effects included herd, year, and test month interaction effects, genetic group effects, and additive genetic and permanent environmental effects modeled with a cubic Legendre polynomial function. The residual variance was heterogeneous with 11 classes. Consequently, the variance components were varied over the lactation and with the production system. The estimated heritability for milk yield was lower in the low-production system (0.04-0.48) than in the medium- (0.22-0.59) and high-production (0.21-0 60) systems. The genetic correlations estimated between different DIM within lactations decreased as the time interval increased, becoming negative between the ends of the lactations in the low- and medium-production systems. Low (0.05) to medium (0.60) genetic correlations were estimated among first lactation test-day milk yields across the 3 production systems. Genetic correlations between the first lactation test-day milk yield and age at first calving ranged from 0.27 to 0.49, 0 to 0.81, and -0.08 to 0.27 in the low-, medium-, and high-production systems, respectively. Medium to high heritabilities (0.17-0.44) were estimated for persistency, with moderate to high (0.30-0.87) genetic correlations between 305-d milk yield and persistency. This indicates that genetic improvement in persistency would lead to increased milk yield. The low to medium genetic correlations between test-day milk yield between production systems indicate that sires may be re-ranked between production systems. Therefore, we conclude that sires should be selected based on a genetic evaluation within the target production system.