Total Merit Index Research Articles

The economic benefit of herd genotyping and using sexed semen for pure and beef-on-dairy breeding in dairy herds.

The cost benefits of herd genotyping and the benefits of using sexed semen have been affected by recent improvements in sexing technologies, the incorporation of direct health traits in the German total merit index for Holstein cattle, the deteriorating prices for purebred heifer calves and bull calves, and the introduction of herd genotyping programs. Inseminating the genetically superior dams with female-sexed Holstein semen increases the mean breeding value of the heifer calves and can produce more Holstein heifer calves than are needed for replacement. This provides an opportunity to increase the selection response in health and production traits at the farm level. A deterministic model is introduced that predicts the increase or decrease in net profit when a farmer takes part in a herd genotyping program and follows a certain insemination strategy. The types of semen that are allocated to cows and heifers are sexed semen or unsexed semen and Holstein semen or beef breed semen. The genetically superior heifers and cows are inseminated with female-sexed Holstein semen, intermediate dams with unsexed Holstein semen, and genetically inferior dams with unsexed or male-sexed beef breed semen. In general, participating in a herd genotyping program is beneficial for German Holstein breeders. The optimum proportions of cows and heifers that should be inseminated with a certain type of semen are sensitive to farm-specific peculiarities. A small price difference between crossbred bull calves and crossbred heifer calves often makes the use of male-sexed beef breed semen uneconomic. Under the conditions considered, it was found to be advantageous to inseminate approximately 50% of the heifers and 10% of the cows with the highest genetic merit with female-sexed Holstein semen. The optimum proportion of cows that should be inseminated with unsexed beef breed semen was found to be approximately 40%. In a herd with a low replacement rate, the selected heifers can exhibit their genetic superiority over a longer period of time, and a larger proportion of cows can be inseminated with beef breed semen. Participation in a herd genotyping program is, therefore, particularly beneficial for herds with low replacement rates.

Optimization Strategies to Adapt Sheep Breeding Programs to Pasture-Based Production Environments: A Simulation Study.

Strong differences between the selection (indoor fattening) and production environment (pasture fattening) are expected to reduce genetic gain due to possible genotype-by-environment interactions (G × E). To investigate how to adapt a sheep breeding program to a pasture-based production environment, different scenarios were simulated for the German Merino sheep population using the R package Modular Breeding Program Simulator (MoBPS). All relevant selection steps and a multivariate pedigree-based BLUP breeding value estimation were included. The reference scenario included progeny testing at stations to evaluate the fattening performance and carcass traits. It was compared to alternative scenarios varying in the progeny testing scheme for fattening traits (station and/or field). The total merit index (TMI) set pasture-based lamb fattening as a breeding goal, i.e., field fattening traits were weighted. Regarding the TMI, the scenario with progeny testing both in the field and on station led to a significant increase in genetic gain compared with the reference scenario. Regarding fattening traits, genetic gain was significantly increased in the alternative scenarios in which field progeny testing was performed. In the presence of G × E, the study showed that the selection environment should match the production environment (pasture) to avoid losses in genetic gain. As most breeding goals also contain traits not recordable in field testing, the combination of both field and station testing is required to maximize genetic gain.

Farmers' preferences for breeding goal traits and selection indexes for Slovenian dairy cattle

The aim of the study was to determine the role played by farmers' sociodemographic factors in the characteristics of dairy farmers' breeding goals and how they are clustered in Slovenia. Understanding how farmers formulate their breeding objectives is crucial because their perspectives may diverge from those of the stakeholders engaged in selection and breeding. Involving farmers in the process of setting breeding goals can improve the use of selection tools and confidence in the selection process. For a more complete picture of how farmers view breeding work, their expectations, and the changes they would prefer to see in the future in terms of new traits and a total merit index, a mixed methods approach was used. Initially, 3 focus groups with 30 participants were conducted on the following main topics: farmers' needs and attitudes regarding genomic selection, the main barriers and advantages to adopting genomic selection, the design of a total merit index, and preferences for breeding goals. To generalize the results to the whole population, an additional online questionnaire was sent to dairy farmers affiliated with Slovenian breeding associations, with 212 farmers responding. Based on how the farmers distributed weights across the trait categories in the total merit index, a cluster analysis identifies 3 distinct groups of farmers. Milk production proved to be an important common factor for all farmers, especially production-focused ones. Functionality-focused farmers expressed the strongest preference for fertility (22%), longevity (18%), and animal health (18%), whereas resilience-focused farmers concentrated on fertility (13%), health (13%), longevity (11%), and workability (11%). Yet, the results also showed that dairy farmers hold quite similar preferences for breeding goal traits, with animal health and welfare, reproductive traits, dominating across the sample and environmental and meat traits being the least important. The quantitative analysis of the preference for new environmental traits showed that farmers express less importance to them due to pressure and negative public opinion about the environmental impact of dairy farming. The focus group participants, although acknowledging that adaptation to climate change and heat stress will be essential, were even more negative about traits related to greenhouse gas emissions, which can be attributed to negative public opinion and constraints on agricultural activity.

Analysis of the influence of the Norwegian Red bull-sires with different breeding value on milk productivity, health, exterior and reproductive traits of daughters

An analysis of the influence of breeding bulls of the Norwegian Red (NR) breeds with different breeding values (BV) on the milk productivity of daughters, their health, reproductive characteristics, udder characteristics, exterior, and indices of productive use. The study material was the data from the electronic catalog of breeding bulls of the NR breed as of April 4, 2023. The sample was formed from the data of only those breeders recommended for reproduction in 2023 by Geno SA. The animals were grouped according to the Total Merit Index (TMI). Breeding bulls with the highest TMI – 53-35 (n = 24) were assigned to the I group, to the II group – with an average TMI – 34-25 (n = 25), and to the III group – bulls with the lowest TMI – 24-10 (n = 22). As a result of the research, it was established that the most significant influence on the indices of productive use of daughters was observed in breeding bulls of the NR breed of the I group (High production index (HPI) – 118.13 % (Р < 0.001), Grazing index (GI) – 110.88 % (Р < 0.05)). According to the TMI index, bulls of the I and II groups prevailed over the sires of the III group, according to their improving effect, on such signs of milk productivity of daughters as milk yield (Р < 0.01), amount of milk fat (Р < 0.05; Р < 0.01) and protein (Р < 0.01; Р < 0.001) and milk productivity index (Р < 0.001 and Р < 0.01) in daughter cows. The greatest improving effect on the udder health of the daughter cows was observed in breeding bulls of the NR breed with TMI 53-35. Bull-sires of groups I and II reduced the number of somatic cells count in the milk of daughter cows by 15.58 and 9.16 %, and bulls of III – only by 3.82 %. Breeder bulls of groups I and III increased milking speed in daughter cows by 4.25 and 1.68 %, and breeders of group II decreased it by 1.96 %. However, the difference was significant only between groups I and II (P < 0.05). Studied breeding sires increased daughters' stature (height) in all groups. Group I sires had the most significant influence on daughters' stature – 114.88, and III group sires had the most minor influence – 102.00. However, the difference was significant between the I and II and I and III groups (Р < 0.05; Р < 0.001). Bull-sires of the I group of the NR breed increased the feet and legs index in daughter cows, as well as the foot angle by 7.58 and 7.38 %, II breeders by 3.48 and 2.48 %, and bulls III reduced these traits in daughters by 0.41 and 0.14 %. The difference between the I and III groups was significant (P < 0.05). Breeder bulls of the NR breed with TMI 53–35 were leaders in improving the udder index of daughters, as well as in reducing its udder depth, strengthening the fore udder attachment, increasing the rear udder width and rear udder height. Therefore, the most significant impact on most of the studied traits was observed in breeding bulls of the NR breed with the highest BV – TMI 53-35. The influence of sires with TMI 53-35 and 34-25 on daughters' milk production was almost the same and improving. However, in terms of the effect on the reproductive characteristics of daughter cows, no significant difference was found between all experimental groups of breeding bulls.

Correlation between breeding values for milk fatty acids and Nordic Total Merit index traits for Danish Holstein and Danish Jersey

Milk fatty acid composition is gaining interest in the Danish dairy industry both to develop new dairy products and as a management tool. To be able to implement milk fatty acid (FA) composition in the breeding program, it is important to know the correlations with the traits in the breeding goal. To estimate these correlations, we measured milk fat composition in Danish Holstein (DH) and Danish Jersey (DJ) cattle breeds using mid-infrared spectroscopy. Breeding values were estimated for specific FA and for groups of FA. Correlations with the estimated breeding values (EBV) underlying the Nordic Total Merit index (NTM) were calculated within breed. For both DH and DJ, we showed that FA EBV had moderate correlations with the NTM and production traits. For both DH and DJ, the correlation of FA EBV and NTM were in the same direction, except for C16:0 (0 in DH, 0.23 in DJ). A few correlations differed between DH and DJ. The correlation between claw health index and C18:0 was negative in DH (-0.09) but positive in DJ (0.12). In addition, some correlations were not significant in DH but were significant in DJ. The correlations between udder health index and long-chain FA, trans FA, C16:0, and C18:0 were not significant in DH (-0.05 to 0.02), but were significant in DJ (-0.17, -0.15, 0.14, and -0.16, respectively). For both DH and DJ, the correlations between FA EBV and nonproduction traits were low. This implies that it is possible to breed for a different fat composition in the milk without affecting the nonproduction traits in the breeding goal.

Mating allocations in Holstein combining genomic information and linear programming optimization at the herd level

In this study, we explored mating allocation in Holstein using genomic information for 24,333 Holstein females born in Denmark, Finland, and Sweden. We used 2 data sets of bulls: the top 50 genotyped bulls and the top 25 polled genotyped bulls on the Nordic total merit scale. We used linear programming to optimize economic scores within each herd, considering genetic level, genetic relationship, semen cost, the economic impact of genetic defects, polledness, and β-casein. We found that it was possible to reduce genetic relationships and eliminate expression of genetic defects with minimal effect on the genetic level in total merit index. Compared with maximizing only Nordic total merit index, the relative frequency of polled offspring increased from 13.5 to 22.5%, and that of offspring homozygous for β-casein (A2A2) from 66.7 to 75.0% in one generation, without any substantial negative impact on other comparison criteria. Using only semen from polled bulls, which might become necessary if dehorning is banned, considerably reduced the genetic level. We also found that animals carrying the polled allele were less likely to be homozygous for β-casein (A2A2) and more likely to be carriers of the genetic defect HH1. Hence, adding economic value to a monogenic trait in the economic score used for mating allocation sometimes negatively affected another monogenetic trait. We recommend that the comparison criteria used in this study be monitored in a modern genomic mating program.

Genomic dominance variance analysis of health and milk production traits in German Holstein cattle.

Genomic analyses commonly explore the additive genetic variance of traits. The non-additive variance, however, is usually small but often significant in dairy cattle. This study aimed at dissecting the genetic variance of eight health traits that recently entered the total merit index in Germany and the somatic cell score (SCS), as well as four milk production traits by analysing additive and dominance variance components. The heritabilities were low for all health traits (between 0.033 for mastitis and 0.099 for SCS), and moderate for the milk production traits (between 0.261 for milk energy yield and 0.351 for milk yield). For all traits, the contribution of dominance variance to the phenotypic variance was low, varying between 0.018 for ovarian cysts and 0.078 for milk yield. Inbreeding depression, inferred from the SNP-based observed homozygosity, was significant only for the milk production traits. The contribution of dominance variance to the genetic variance was larger for the health traits, ranging from 0.233 for ovarian cysts to 0.551 for mastitis, encouraging further studies that aim at discovering QTLs based on their additive and dominance effects.

Selecting the ‘Sustainable’ Cow Using a Customized Breeding Index: Case Study on a Commercial UK Dairy Herd

The aim of the current study was to investigate using a customized profit and carbon total merit index to identify sustainable milking cows and herd replacements within a commercial dairy herd. Balancing the economic, social and environmental aspects of milk production has gained interest given the increasing global demand for milk products. Furthermore, a farm-level customized breeding index with farm-derived weightings for biological traits would incorporate the effect of the farm environment. This study used a Markov chain approach to model a commercial dairy herd in the UK between the years 2017 and 2022. Production, financial, genetic and nutritional data for the herd were used as input data. The model derived the economic (GBP per unit) and carbon values (kilograms CO2-eq. emissions per unit) for a single phenotypic increase in milk volume, milk fat yield, milk protein yield, somatic cell count, calving interval and lifespan, which were used in a profit and carbon index. The study proposed a methodology for selecting individual milking cows and herd replacements based on their potential to increase herd profitability and reduce carbon emissions as a means to identify more sustainable animals for a given farm environment. Of the 370 cows and herd replacements studied, 76% were classified as sustainable with a desirable increase in profit and reduction in carbon emissions. Customized breeding indices with trait weightings derived from the farm environment and selecting individual animals on economic and carbon metrics will bring permanent and cumulative improvements to the sustainability of milk production with appropriate nutrition and management. The approach used can be applied to any commercial farm to select animals that are more sustainable.

New insights into the genetic resistance to paratuberculosis in Holstein cattle via single-step genomic evaluation

BackgroundBovine paratuberculosis, or Johne’s disease (JD), is a contagious and incurable disease caused by Mycobacterium avium subsp. paratuberculosis (MAP). It has adverse effects on animal welfare and is very difficult to control, leading to serious economic consequences. An important line of defense to this disease is host genetic resistance to MAP, which, when it will be more fully understood, could be improved through selective breeding. Using a large dataset of Holstein cows (161,253 animals including 56,766 cows with ELISA serological phenotypes and 12,431 animals with genotypes), we applied a single-step single nucleotide polymorphism (SNP) best linear unbiased prediction approach to investigate the genetic determinism underlying resistance to this disease (heritability estimate and identification of relevant genomic regions) and estimated genetic trends, reliability, and relative risk factors associated with genomic predictions.ResultsResistance to JD was moderately heritable (0.14) and 16 genomic regions were detected that accounted for at least 0.05% of the breeding values variance (GV) in resistance to JD, and were located on chromosomes 1, 3, 5, 6, 7, 19, 20, 21, 23, 25, and 27, with the highest percentage of variance explained by regions on chromosomes 23 (0.36% GV), 5 (0.22% GV), 1 (0.14% GV), and 3 (0.13% GV). When estimated for the whole chromosomes, the autosomes with the largest overall contributions were chromosomes 3 (5.3% GV), 10 (4.8%), 23 (4.7%), 1 (3.6%), 7 (3.4%), 5 (2.9%), 12 (2.5%), 11 (2.2%), and 13 (2%). We estimated a slightly favorable genetic trend in resistance to JD over the last two decades, which can be explained by a low positive genetic correlation between resistance to JD and total merit index (+ 0.06). Finally, in a validation population of 907 cows, relatively reliable genomic predictions (reliability = 0.55) were obtained, which allowed the identification of cows at high risk of infection.ConclusionsThis study provides new insights into the genetic determinism of resistance to JD and shows that this trait can be predicted from SNP genotypes. It has led to the implementation of a single-step genomic evaluation that should rapidly become an effective tool for controlling paratuberculosis on French Holstein farms.

Opportunities for genomic selection of cheese-making traits in Montbéliarde cows

As part of the From'MIR project, traits related to the composition and cheese-making properties (CMP) of milk were predicted from 6.6 million mid-infrared spectra taken from 410,622 Montbéliarde cows (19,862 with genotypes). Genome-wide association studies of imputed whole-genome sequences highlighted candidate SNPs that were then added to the EuroG10K BeadChip, which is routinely used in genomic selection. In the present study, we (1) assessed the reliability of single-step genomic BLUP breeding values (ssEBVs) for cheese yields, coagulation traits, and casein and calcium content generated from test-day records of the first 3 lactations, (2) estimated realized genetic trends for these traits over the last decade, and (3) simulated different cheese-making breeding objectives and estimated the responses for CMP as well as for other traits currently selected in the Montbéliarde breed. To estimate the reliability of ssEBVs, the available data were split into 2 independent training and validation sets that respectively contained cows with the oldest and the most recent lactation data. The training set included 155,961 cows (12,850 with genotypes) and was used to predict ssEBVs of 2,125 genotyped cows in the validation set. We first tested 4 models that included either lactation (LACT) or test-day (TD) records from the first (1) or the first 3 (3) lactations, giving equal weight to all 50K SNP effects. Mean reliabilities were 61%, 62%, 63%, and 64% for the LACT1, LACT3, TD1, and TD3 models, respectively. Using the most accurate model (TD3), we then compared the reliabilities of 3 scenarios with: SNPs from the Illumina BovineSNP50 BeadChip only, equally weighted (50K); 50K SNPs plus additional candidate SNPs, equally weighted (50K+); and 50K and candidate SNPs with additional weight given to 7 to 14 candidate SNPs, depending on the trait (CAND). The 50K+ and CAND scenarios led to similar mean reliabilities (67%) and both outperformed the 50K scenario (64%), whereas the CAND scenario generated the less biased ssEBVs. To assess genetic trends, SNP effects were estimated with a single-step GBLUP based on the TD3 model and the 50K scenario applied to the whole population (2.6 million performance records from 190,261 cows and 423,348 animals in the pedigree, of which 21,874 were genotyped) and then applied to 50K genotypes of 21,171 males and 311,761 females. We detected a positive genetic trend for all CMP during the last decade, probably due to selection for an increase in milk protein and fat content in Montbéliarde cows. Finally, we compared the selection responses to 3 different breeding objectives: the current Montbéliarde total merit index (TMI) and 2 alternative scenarios that gave a weight of 70% to TMI and the remaining 30% to either milk casein content (TMI-COMP) or a combination of 3 CMP (TMI-Cheese). The TMI-Cheese scenario yielded the best responses for all the CMP analyzed, whereas values in the TMI-COMP scenario were intermediate, with a slight effect on other traits currently included in TMI. Based on these results, a program of genomic evaluation for CMP predicted from mid-infrared spectra was designed and implemented for the Montbéliarde breed.

Development of a routine genetic evaluation and a total merit index for sheep breeds with focus on meat production

• A routine genetic evaluation was developed for sheep with focus on meat production. • Breeding values for individual traits, a Meat and a Fitness index as well as a Total merit index are calculated weekly. • Traits are weighted in a way so that the theoretical selection response is positive for all traits. The introduction of a routine genetic evaluation for specialized meat sheep (Blackheaded meat, Suffolk, Texel, Ile de France, Dorper, and Berrichon du Cher) and land sheep with focus on meat production (Merinoland) is described. Even though performance recording has existed for several production and fitness related traits and years, breeding values have not been officially available for sheep in Austria until 2017. Meat performance traits, recorded for purebred animals of both sexes, include average daily gain, fat depth and eye muscle depth. Historic computer tomography performance recording results serve as auxiliary traits. Regarding functional traits, lambing interval, number of lambs born and number of lambs born alive are considered. The routine genetic evaluation is carried out twice a year, at the beginning of January and at the end of June. Additionally, breeding values and reliabilities are calculated at weekly intervals but only uploaded if the change in reliability exceeds 5%-points or a new individual performance recording result is available. All estimated breeding values are standardised to relative breeding values with a mean of 100 (rolling base including rams aged 5–15 years), and a genetic standard deviation of 12, higher values are favourable. Apart from breeding values for individual traits, subindices for meat and fitness traits as well as a Total merit index (TMI) are calculated. For the calculation of the Meat index, the relative weights (in %) for average daily gain (direct) : muscle depth : fat depth are 36 : 62 : 2 for Merinoland and 44 : 52 : 4 for meat sheep. For fat depth, the breeding values are transformed to an intermediate optimum in the index calculation. In the Fitness index, the relative weights (in %) for lambing interval : lambs born maternal : lambs born paternal: lambs born alive maternal : lambs born alive paternal are 35.0 : 33.3 : 8.3 : 18.3 : 5.0 (Merinoland) and 20.0 : 49.0 : 17.0 : 10.0 : 4.0 (Meat sheep). Including the trait average daily gain maternal in the meat complex, the relative weights (in %) of Meat : Fitness are 40 : 60 and 60 : 40 in Merinoland and Meat sheep, respectively. The TMI was defined in a way so that the calculated selection response is positive for all single traits in order to avoid an unfavourable development. Thus, it serves as a starting point for a breeding objective that is both, economically feasible and sustainable in the long-term. Further traits that may be considered in a future TMI are e.g. longevity and selected conformation traits.

Analysis of milk solids production and mid-lactation bodyweight to evaluate cow production efficiency on commercial dairy farms

The efficient production of milk is an important determinant of both, farm productivity and the environmental impact of intensive dairy systems. The objective of the present study was to use a large dataset of commercial dairy cows to determine the relationship among animal breed, Irish total merit index (Economic Breeding Index; EBI), parity, and production efficiency parameters, which included milk solids (MS) production per kg of mid-lactation bodyweight (MSperBW) and the estimated net energy requirement per kg of MS produced (ENperMS). Data from 80 different spring-calving commercial dairy herds located in southern Ireland comprising 20,051 cows across 34,002 lactations from Holstein-Friesian (HF) and Jersey × Holstein-Friesian crossbred (JFX) cows were accessible for the study across 4 years. The data available included individual cow EBI, 305-day MS production, which is kg fat yield plus kg protein yield, calving and dry-off dates, and a mid-lactation bodyweight (BW) at 143 ± 26 days in milk. To evaluate the productive efficiency in this study, firstly, individual cow MSperBW was calculated by dividing 305-day MS production by mid-lactation BW, with higher values being desirable (Prendiville et al., 2009; O'Sullivan et al., 2019a). Secondly, ENperMS was established by dividing the total net energy requirement (in Unité Fourragère Lait; UFL) for an animal for maintenance (from BW), milk production, and growth (for animals up to lactation 3) by the 305-day MS production (INRA, 2010; Faverdin et al., 2011), where lower values indicate increased efficiency due to lower energy requirement per unit output. Statistical analyses were undertaken using mixed models. Overall, average MSperBW was 0.94 ±0.16 kg MS/ kg BW with large variation between animals within herds (0.42 to 1.47 kg MS/ kg BW) and between herds (0.73 to 1.14 kg MS/ kg BW). Similarly, ENperMS on farm averaged 9.8 total UFL/ kg MS ranging from 9.0 to 10.9 total UFL/ kg MS between farms. The MSperBW was significantly greater for JFX (1.01 kg MS/ kg BW) compared to HF animals (0.92 kg MS/ kg BW), resulting in a reduction in total energy requirements per kg of MS produced (ENperMS) (9.5 vs. 9.8 total UFL/ kg MS for JFX and HF, respectively). Animals with increased MSperBW produced 140 kg/cow more MS per 305-day lactation and were 58 kg lighter than lower MSperBW contemporaries. These results corroborate the benefits of both, selection on EBI and crossbreeding to increase aforementioned production efficiency parameters within intensive grazing systems. The results also provide a further compelling basis for dairy farmers to routinely weigh and milk record their herds to identify more efficient animals on which to increase animal performance and profitability in future generations.

Reliabilities of Genomic Prediction for Young Stock Survival Traits Using 54K SNP Chip Augmented With Additional Single-Nucleotide Polymorphisms Selected From Imputed Whole-Genome Sequencing Data.

This study investigated effects of integrating single-nucleotide polymorphisms (SNPs) selected based on previous genome-wide association studies (GWASs), from imputed whole-genome sequencing (WGS) data, in the conventional 54K chip on genomic prediction reliability of young stock survival (YSS) traits in dairy cattle. The WGS SNPs included two groups of SNP sets that were selected based on GWAS in the Danish Holstein for YSS index (YSS_SNPs, n = 98) and SNPs chosen as peaks of quantitative trait loci for the traits of Nordic total merit index in Denmark–Finland–Sweden dairy cattle populations (DFS_SNPs, n = 1,541). Additionally, the study also investigated the possibility of improving genomic prediction reliability for survival traits by modeling the SNPs within recessive lethal haplotypes (LET_SNP, n = 130) detected from the 54K chip in the Nordic Holstein. De-regressed proofs (DRPs) were obtained from 6,558 Danish Holstein bulls genotyped with either 54K chip or customized LD chip that includes SNPs in the standard LD chip and some of the selected WGS SNPs. The chip data were subsequently imputed to 54K SNP together with the selected WGS SNPs. Genomic best linear unbiased prediction (GBLUP) models were implemented to predict breeding values through either pooling the 54K and selected WGS SNPs together as one genetic component (a one-component model) or considering 54K SNPs and selected WGS SNPs as two separate genetic components (a two-component model). Across all the traits, inclusion of each of the selected WGS SNP sets led to negligible improvements in prediction accuracies (0.17 percentage points on average) compared to prediction using only 54K. Similarly, marginal improvement in prediction reliability was obtained when all the selected WGS SNPs were included (0.22 percentage points). No further improvement in prediction reliability was observed when considering random regression on genotype code of recessive lethal alleles in the model including both groups of the WGS SNPs. Additionally, there was no difference in prediction reliability from integrating the selected WGS SNP sets through the two-component model compared to the one-component GBLUP.

Cross-sectional analyses of a national database to determine if superior genetic merit translates to superior dairy cow performance

Various studies have validated that genetic divergence in dairy cattle translates to phenotypic differences; nonetheless, many studies that consider the breeding goal, or associated traits, have generally been small scale, often undertaken in controlled environments, and they lack consideration for the entire suite of traits included in the breeding goal. Therefore, the objective of the present study was to fill this void, and in doing so, provide producers with confidence that the estimated breeding values (EBV) included in the breeding goal do (or otherwise) translate to desired changes in performance among commercial cattle; an additional outcome of such an approach is the identification of potential areas for improvements. Performance data on 536,923 Irish dairy cows (and their progeny) from 13,399 commercial spring-calving herds were used. Association analyses between the cow's EBV of each trait included in the Irish total merit index for dairy cows (which was derived before her own performance data accumulated) and her subsequent performance were undertaken using linear mixed models; milk production, fertility, calving, maintenance (i.e., liveweight), beef, health, and management traits were all considered in the analyses. Results confirm that excelling in EBV for individual traits, as well as on the total merit index, generally delivers superior phenotypic performance; examples of the improved performance for genetically elite animals include a greater yield and concentration of both milk fat and milk protein, despite a lower milk volume, superior reproductive performance, better survival, improved udder and hoof health, lighter cows, and fewer calving complications; all these gains were achieved with minimal to no effect on the beef merit of the dairy cow's progeny. The associated phenotypic change in each performance trait per unit change in its respective EBV was largely in line with the direction and magnitude of expectation, the exception being for calving interval. Per unit change in calving interval EBV, the direction of phenotypic response was as anticipated but the magnitude of the response was only half of what was expected. Despite the deviation from expectation between the calving interval EBV and its associated phenotype, a superior total merit index or a superior fertility EBV was indeed associated with an improvement in all detailed fertility performance phenotypes investigated. Results substantiate that breeding is a sustainable strategy of improving phenotypic performance in commercial dairy cattle and, by extension, profit.

Implementation of an Economic Lifetime Net Merit for the Dual-Purpose German Black Pied Cattle Breed

Recently, a Total Merit Index (RZ€) has been developed for German Holstein dairy cattle on the basis of margin in Euro. Our aim was to adjust this lifetime net merit for the dual-purpose German Black Pied cattle breed (DSN) accounting for beef production in addition to milk performance and fitness traits. We used the estimated breeding values of DSN sires and developed a breeding value for carcass weight and quality. Furthermore, we adjusted the German Holstein marginal profits per standard deviation, which are used to calculate the estimated breeding values, to DSN-specific values. The DSN Net Merit is the sum of the three sub-indices DSN Net Milk, DSN Net Fitness, and DSN Net Beef, which contribute to the DSN Net Merit with 52.84%, 43.43%, and 3.73%, respectively. The DSN Net Merit that was calculated for 33 DSN sires ranged between EUR −1114 and +709. The DSN Net Merit strongly correlates with the Total Merit Index. The implementation of the DSN Net Merit is useful for selection and mating decisions. Especially, the sub-index DSN Net Beef, which does not correlate with existing breeding values, can be used to maintain the dual-purpose character of DSN while modestly improving milk yield. The approach can be easily adapted to other dual-purpose breeds.

Genotype-by-environment interactions at the trait level and total merit index level for milk production and functional traits in Brown Swiss cattle

The production environments of the German–Austrian Brown Swiss population show a wide range due to differences in topography, landscapes, local climates, and different farm management systems. Extensive production systems such as organic farming have become increasingly popular in recent decades because of interest in sustainability and consumer preferences. Compared with conventional farmers, organic farmers put more weight on fitness traits. Besides the official total merit index (TMI), a selection index applying relative economic weights (REWs) suitable for organic production systems is provided for Brown Swiss cattle in Germany. The aim of the study was to investigate genotype-by-environment interactions (GxE) for milk production traits and functional traits (including longevity, fertility traits, and calving traits) in a sample of the German–Austrian Brown Swiss population housed in Baden-Wuerttemberg (southern Germany) by applying bivariate and random regression sire models. For bivariate analyses, the production environment was binary classified by farm management system (organic and conventional) and altitude of farm location (above or below 800 m above sea level (ASL)). Milk energy yields (MEY) obtained from herd effects were used as continuously scaled environmental descriptor in the reaction norm approach. The TMIs for sires were calculated based on breeding values estimated with different models and environment-specific REWs to determine possible GxE at TMI levels and rerankings of sires. In bivariate analyses, genetic correlations at the trait level were high and ranged from rg = 0.99 (calving to first insemination, cystic ovaries, and maternal stillbirth rate) to rg = 0.79 (first insemination to conception for altitude). Except for the latter, no severe GxE were found at the trait level using the bivariate models. Fat yield was the only trait showing minor GxE in the reaction norm model approach. Investigating the environmental sensitivity at the TMI level revealed rank correlations between the different environment-specific TMIs that were close to unity, implying no severe reranking effects. The results show no need to account for different environments in Brown Swiss cattle breeding programs.

Validation of a beef cattle maternal breeding objective based on a cross-sectional analysis of a large national cattle database.

Despite the importance of validating any technology prior to recommendation for use, few studies exist in the scientific literature which have demonstrated the superior performance of high-ranking animals in a given total merit index; this is especially true for maternal cattle selection indexes. The objective of the present study was to demonstrate the impact of the Irish total merit maternal-based index and provide the benefits of using the Irish total merit maternal-based beef index as part of a breeding policy. The validation exercise was undertaken using 269,407 records (which included the cow's own records and her progeny records) from 92,300 females differing in a total merit index for maternal value; a comparison was also made with the Irish terminal index. Association analyses were undertaken within the framework of linear and threshold mixed models; the traits analyzed were fertility (e.g., calving interval), slaughter (e.g., harvest weight), live weight (e.g., weaning weight), and producer-recorded traits (e.g., docility). All traits were analyzed with the maternal index and terminal index fitted as covariate(s) separately. Depending on the independent variable analyzed, the other fixed effects included: parity of cow, heterosis and recombination loss of cow and/or progeny, gender of progeny, and the estimated breeding value of the sire; contemporary group was included as a random effect. The results demonstrate the effectiveness of using total merit indexes to improve performance in a whole range of different traits, despite the often antagonistic genetic correlations among traits that underpin the index. Cows excelling on the maternal index had less calving difficulty, superior fertility performance, lighter carcasses, and live weight, as well as being more easily managed. Additionally, progeny of higher maternal index cows were lighter at birth and more docile albeit with a small impact on slaughter traits. In contrast, higher terminal index cows had more calving difficulty, compromised fertility and had heavier carcasses themselves as well as their progeny. While the differences in phenotypic performance between groups on maternal index was, in most instances, relatively small, the benefits are: (1) expected to be greater when more genetically extreme groups of animals are evaluated and (2) expected to accumulate over time given the cumulative and permanent properties of breeding schemes.

Feed and production efficiency of young crossbred beef cattle stratified on a terminal total merit index.

Few studies have attempted to quantify the association between a terminal total merit index with phenotypic feed and production efficiency in beef cattle, particularly when feed efficiency is itself explicitly absent as a goal trait in the index. The objective of the present study was to quantify the differences in phenotypic performance for feed intake, feed efficiency, and carcass traits of crossbred bulls, steers, and heifers differing in a terminal total merit index. A validation population of 614 bulls, steers, and heifers that were evaluated for feed intake and efficiency in the same feedlot and subsequently slaughtered at the end of their test period was constructed. The Irish national genetic evaluations for a terminal index of calving performance, docility, feed intake, and carcass traits were undertaken with the phenotypic records of animals present in the validation population masked. The validation population animals were subsequently stratified into four groups, within sex, according to their terminal index value. Mixed models were used to quantify the association between terminal genetic merit and phenotypic performance; whether the associations differed by sex were also investigated. The regression coefficient of phenotypic feed intake, carcass weight, carcass conformation, or carcass fat on its respective estimated breeding values was 0.86 kg dry matter 0.91 kg, 1.01 units, and 1.29 units, respectively, which are close to the expectation of one. On average, cattle in the very high terminal index stratum had a 0.63 kg DM/d lower feed intake, a 25.05 kg heavier carcass, a 1.82 unit better carcass conformation (scale 1 to 15), and a 1.24 unit less carcass fat score (scale 1 to 15), relative to cattle in the very low terminal index stratum. Cattle of superior total genetic merit were also more feed efficient (i.e., had a lower energy conversion ratio, lower residual feed intake, and greater residual gain), had a greater proportion of their live-weight as carcass weight (i.e., better dressing percentage) and were slaughtered at a younger age relative to their inferior total genetic merit counterparts. This study provides validation of an all-encompassing total merit index and demonstrates the benefits of selection on a total merit index for feed and production efficiency, which should impart confidence among stakeholders in the contribution of genetic selection to simultaneous improvements in individual animal performance and efficiency.

SELECTION OF RED MOTLEY HOLSTEIN BULLS BY GENOTYPE AND THEIR EXTENSIVE USE IN BREEDING

The article describes the selection of red motley Holstein bulls by genotype imported from Germany to the state enterprise "Uznaslchilik" and their use in breeding practices, which are also characterized by breeding and productivity qualities typical of black motley types. In the study of world breeding practices, new high-yielding herds are being formed by crossing dairy red breeds with red motley Holstein breed bull-improvers. The red motley Holstein breed is also recognized in our country as an improver and is being used in artificial insemination. KEYWORDS: Red motley Holstein breed, breeding and productivity, artificial insemination, crossbreeding, selection and pairing, fertile, individual, genotype, breeding, total merit index, farm useful traits.

Farmers’ stated selection preferences differ from revealed AI bull selection in Finnish dairy herds

Traditionally, in dairy production, traits included in total merit indices (TMI) are weighted based on their economic importance in the production system in which they are meant to be used. In the Nordic countries, Nordic Total Merit (NTM) is used. Farmers may, however, have herd-specific breeding goals, which can differ greatly from TMI. Recently, surveys have been conducted among dairy farmers to determine their selection preferences with the aim of complementing the development of the breeding objectives deduced purely from economic data. The aim of this study was 1) to investigate the stated selection preferences for AI (artificial insemination) bull traits of Finnish dairy farmers when selecting AI bulls for both of the main dairy breeds in Finland: Ayrshire (AY) and Holstein (HOL), and 2) to analyse how the stated preferences match the revealed preferences in dairy bull selection. An online survey was conducted to determine farmers’ stated preferences using Analytic hierarchy process (AHP). Altogether 657 farmers responded to the survey, yielding a response rate of 17.2%. Based on farm characteristics and background information, the respondents can be said to represent also the future Finnish dairy farmer. The AHP results were compared with respondents’ revealed bull selection, which was determined by the mean of traits’ estimated breeding values (EBVs) of bulls used weighted by the number of inseminations in each herd. Large differences emerged between stated and revealed preferences in both dairy breeds. Longevity was the most important trait in revealed preferences in HOL herds and the second most important trait in AY herds. In stated preferences longevity was the second most important trait on both breeds. Yield was the most important trait in AY herds and the second most important trait in HOL herds in revealed preferences, but very little favoured in stated selection preferences. In addition, conformation was more favoured in the revealed selection than in the stated preferences. Health was quite poorly favoured in revealed selection, given that it ranked highest in the stated preferences. Revealed preference of different traits followed relatively well NTM-based selection in both breeds. Most farmers seem to trust NTM in their AI bull selection, but it is not the only criterion for choosing AI bulls. The information regarding farmers’ stated preferences and earlier AI bull selection could be used to customize the NTM at the farm level, better considering individual farmers' perspectives.