Is heat stress a growing problem for dairy cattle husbandry in the temperate regions? A case study of Baden-Württemberg in Germany.

Heat stress with measurable effects in dairy cattle is a growing concern in temperate regions. Heat stress in temperate regions differs between environments with different geophysical characteristics. Microclimates specific to each environment were found to greatly impact at what level heat stress occurs and will occur in the future. The landlocked state of Baden-Württemberg, Germany, provides several different environments, hence, a good case-study. Temperature Humidity Index (THI) from 17 weather stations for the years 2003-2022 was calculated and milking yields from 22 farms for the years 2017-2022 were collected. The occurrences and evolving patterns of heat stress were analysed with use of a Temperature Humidity Index (THI), and the effect of heat stress on milk yield was analysed based on milking records from Automated Milking Systems (AMS). Daily average THI was calculated using hourly readings of relative humidity and ambient temperature, disregarding solar radiation and wind, as all animals were permanently stabled. Based on studies conducted in Baden-Württemberg and neighbouring regions, cited ahead in the section of Temperature Humidity Index, THI = 60 was the threshold for heat stress occurrence. Findings show that the heat stress period varied between stations from 64 to 120 days with THI ≥ 60 in a year. This aligns with yearly and summer averages, also steadily increasing from May to September. Length of heat stress period was found to increase 1 extra day every year. Extreme weather events such as heat waves did not increase the heat stress period of that year in length but increased the average THI. Milk yield was found to be significantly (α = 0.05) different between counties grouped into different zones according to heat stress severity and rate of increase in daily average THI. Future attempts at managing heat stress on dairy cattle farms in the temperate regions should account for microclimate, as geographical proximity does not mean that the increase in heat stress severity will be the same in the two neighbouring areas.

Genomic rotational crossbreeding with advanced optimum contribution selection methods applied to simulated German Angler and German Holstein dairy cattle populations.

Many local dairy cattle breeds are facing genetic extinction due to a large proportion of foreign genes, which have been introgressed in the past. In addition, the performance gap to popular high-yielding breeds is increasing, resulting in a risk of numeric extinction. In the present simulation study, a genomic rotational crossbreeding scheme with the high-yielding German Holstein breed and the numerically small German Angler breed was analysed with the aim to utilize heterosis effects in the crossbred animals. Simultaneously inbreeding was controlled, and the amount of Holstein introgression observed in the Angler breed was reduced. Different scenarios of implementing OCS methods for Angler individuals were evaluated, which differed in their restrictions regarding kinship, native kinship, as well as the amount of genetic contributions from German Holstein. The results showed that rotational crossbreeding can result in superior crossbred offspring compared to the purebred parental lines, whereby OCS methods can simultaneously restrict the increase in inbreeding and keep the Holstein contributions at their current level. However, reducing the amount of migrant contributions while restricting the increase in the native kinship in Angler turned out to be a costly restriction. The reason was that Angler with low genetic contributions from Holsteins tended to have similar Angler ancestors. Consequently, reducing Holstein contributions would considerably increase the native kinship in Angler if it were not constrained. The constraint on the native kinship made a constraint on the conventional kinship superfluous and caused it to increase at a much lower rate than envisaged. This led to both, a high genetic diversity and a low genetic gain. The high genetic diversity in Angler also resulted in lower and oscillating heterosis effects in the crossbred animals. Thus, the reduction of migrant contribution did not increase heterosis effects in the crossbred offspring, and did not result in superior crossbred offspring in general.

Improving the Accuracy of Multi-Breed Prediction in Admixed Populations by Accounting for the Breed Origin of Haplotype Segments.

Numerically small breeds have often been upgraded with mainstream breeds. This historic introgression predisposes the breeds for joint genomic evaluations with mainstream breeds. The linkage disequilibrium structure differs between breeds. The marker effects of a haplotype segment may, therefore, depend on the breed from which the haplotype segment originates. An appropriate method for genomic evaluation would account for this dependency. This study proposes a method for the computation of genomic breeding values for small admixed breeds that incorporate phenotypic and genomic information from large introgressed breeds by considering the breed origin of alleles (BOA) in the evaluation. The proposed BOA model classifies haplotype segments according to their origins and assumes different but correlated SNP effects for the different origins. The BOA model was compared in a simulation study to conventional within-breed genomic best linear unbiased prediction (GBLUP) and conventional multi-breed GBLUP models. The BOA model outperformed within-breed GBLUP as well as multi-breed GBLUP in most cases.

A Review of Genomic Models for the Analysis of Livestock Crossbred Data.

Livestock breeding has shifted during the past decade toward genomic selection. For the estimation of breeding values in purebred breeding schemes, genomic best linear unbiased prediction has become the method of choice. Systematic crossbreeding with the aim to utilize heterosis and breed complementary effects is widely used in livestock breeding, especially in pig and poultry breeding. The goal is to improve the performance of the crossbred animals. Due to genotype-by-environment interactions, imperfect linkage disequilibrium, and the existence of dominance and imprinting, purebred and crossbred performances are not perfectly correlated. Hence, more complex genomic models are required for crossbred populations. This study reviews and compares such models. Compared to purebred genomic models, the reviewed models were of much higher complexity due to the inclusion of dominance effects, breed-specific effects, imprinting effects, and the joint evaluation of purebred and crossbred performance data. With the model assessment work conducted until now, it is not possible to come to a clear recommendation as to which existing method is most suitable for a specific breeding program and a specific genetic trait architecture. Since it is expected that a superior method includes all the different genetic effects in a single model, a dominance model with imprinting and breed-specific SNP effects is proposed. Further progress could be made by assuming realistic covariance structures between the genetic effects of the different breeding lines, and by using larger marker panels and mixture distributions for the SNP effects.