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In Northern European countries, a great variety of Red cattle populations exists which can be broadly categorized in two groups: specialized dairy and dual-purpose breeds. Collaboration between these breeds (i.e. the exchange of sires across breeds) can be beneficial but is limited so far. The aim of this study was to demonstrate and evaluate consequences of collaboration between Red breeds using stochastic simulations. Two breeding lines (dairy type and dual purpose) were simulated. As a special aspect of this study, differences in genetic levels of breeding traits (milk production, beef production, mastitis resistance, fertility, feed efficiency) have been taken into account. Various scenarios were investigated where across-breed selection was either restricted or allowed and with different correlations between breeding goals in the two lines. The results of this study were influenced by the different genetic levels in breeding traits only in the first years of simulation. In the long run, the breed differences did not affect the degree of collaboration between lines. When the correlation between breeding goals was close to unity, the selection of external bulls was highly beneficial in terms of genetic gain and total monetary gain. Additionally, the lowest rate of inbreeding was found in that case. With decreasing correlations between environments, degree of cooperation between lines rapidly terminated and lines operated individually. In last years of simulation, cooperation was only found when the correlation between breeding goals was close to unity. From a long-term perspective, the exchange of breeding sires across lines also caused negative effects. In the dual-purpose line, deterioration of genetic gain in mastitis resistance and fertility was observed. Additionally, breeding lines genetically converged, which decreased genetic diversity. Collectively, short-term benefits and long-term negative effects have to be reconciled if collaboration between Red breeds in Northern Europe is to be pursued.

Genetic selection for reduced methane emission and BeefxDairy crossbreeding are strategies to lower the climate impact of beef. Combined they require knowledge of phenotypes on methane production for BeefxDairy offspring. Slaughter calves sired by Belgian Blue, Charolaise and Angus sires to Holstein dams were compared to purebred Holstein calves. Heritability for methane concentration (CH4c) were estimated for Belgian blue crosses. Raw phenotypic means showed that CH4c was lower for calves born after Charolaise and Angussires compared to Belgian Blue. The heritability of log transformed CH4c for Belgian blue crosses was estimated to be 0.44 (±0.08), and for log transformed CH4c adjusted for background CH4 it was 0.33 (±0.06). This is in line with heritabilities found for log transformed CH4c in Holstein cows, and will be the basis for further analysis in genetic architecture of methane traits in crossbred slaughter calves.

The objective of this study was to present a new methodology to predict selection response on resilience and feed efficiency (FE) in dairy cattle. This approach combines genetic and mechanistic modelling to describe the biological mechanisms underlying these traits. A dairy cattle breeding scheme was simulated considering a non-limiting nutritional environment and two different breeding goals focusing either on milk production or FE. Selection response was predicted within the non-limiting environment but also for a prospective low-input system (LS). Predictions obtained with conventional and mechanistic-based methods were consistent for milk production, body weight and FE within the non-limiting environment. However, genetic trends predicted for fertility were different. Selection response achieved on milk production was much smaller in the LS than in the breeding nucleus due to the increased nutritional constraint. The breeding goal with emphasis on FE enabled a better transfer of genetic gain to the LS environment.

ADAM software is a stochastic simulation tool intended to model a variety of selective breeding schemes for animals and plants. ADAM can be used to generate genetic data to test statistical tools and the implemented algorithms can evaluate breeding schemes by tracing genetic change under different selective breeding scenarios. In practice, crossbreeding has been used extensively in beef cattle, pig, and poultry production systems, and the use of crossbreeding isincreasing in dairy cattle breeding system due to changes in the dairy market. The aim of this paper was to present a new crossbreeding feature of the ADAM software. The software was updated to include multiple purebred populations and crossbred populations in animals with different genetic backgrounds considering both additive and dominance effects. Our simulated results showed that, by using the new features in ADAM, breeding organizations can optimizetheir design of crossbreeding schemes and, thereby, optimize profitability.

Farmers play a key role in conserving native livestock breeds, but without economic support, farms with native breeds may not be viable. We hypothesized that terminal crossbreeding can improve herd economy and decrease the economic support needed from society. Three scenarios were simulated using SimHerd Crossbred: a herd of purebred Swedish Polled Cattle, a herd of purebred Swedish Red, and a herd of 75% Swedish Polled Cattle and 25% F1 crossbreds. The results showed annual contribution margin per cow in the herd can be increased by €181 by crossbreeding compared with pure-breeding with the native breed, giving a 13.6% growth in contribution margin. However, the needed cost in subsidies paid by the government will remain unchanged if the population size of the native breed is to be maintained. Combining a crossbreeding strategy with the marketing of niche products may facilitate the conservation of native cattle.

Genotype by environment interaction (G×E) may exist for traits that are expressed in different environments. The G×E is often ignored in the genetic evaluation of selection candidates. We hypothesized that genetic gain in 2 environments is always higher when the true value of the genetic correlation (rg) between traits expressed in different environments is considered in the genetic evaluation. We tested this hypothesis by stochastic simulation of dairy cattle breeding programs in a mainstream and a niche environment. The rg was varied from 0 to 1 in steps of 0.1. We simulated the following 3 scenarios: 1Trait_1Index, 2Traits_1Index, and 2Traits_2Indices. The G×E was ignored in the genetic evaluation in the scenario with 1Trait and included in scenarios with 2Traits. Selection was based on the mainstream selection index in both environments in scenarios with 1Index. Selection in the mainstream environment was based on the mainstream selection index and selection in the niche environment was based on the niche selection index in the scenario with 2Indices. With moderate G×E (rg between 0.6 and 0.9), the highest genetic gain was achieved in the niche environment by selecting for the mainstream selection index and ignoring G×E. At lower rg, the highest genetic gain was achieved when considering G×E and selecting for the niche selection index. For the mainstream environment, it was never an advantage to ignore G×E. Therefore, although our hypothesis was confirmed in most cases, there were cases where ignoring G×E was the better option, and using the correct evaluation led to inferior genetic gain. The results of the current study can be used in animal breeding programs that encompass multiple environments.

In the Nordic countries of Denmark, Finland, and Sweden, a breeding value for Saved feed is targeted. Saved feed consists of two sub-traits, maintenance and metabolic efficiency, which are evaluated as residual feed intake. This study evaluated residual feed intake in relation to calculated economic values to set breeding goal. Residual feed intake typically is derived using phenotypic or genetic regression. However, when calculating economic value (EV) for residual feed intake, phenotypic and genetic residual feed intake save feed, and so are not relevant; yet, EV is important for the genetic progress of such traits. Thus, phenotypic regression coefficients were used to obtain the economic value of residual feed intake in the current simulation. The SimHerd model was used in this study to quantify the EV of RFI. The economic value of phenotypic residual feed intake ranged from 0.16 to 0.18 €/kg dry matter, corresponding to 0.16 to 0.18 €/Scandinavian feed unit (SFU – 1 SFU corresponds to 0.97 kg dry matter and 6.7 mega joule net energy) in the SimHerd simulation. Thus, the economic value of feed efficiency corresponded to the applied feed price in the simulations (0.18 €/SFU). By splitting phenotypic residual feed intake into two periods (before and after 84 days in milk), we showed that the simulation of biological changes during early lactation showed that the economic value was not dependent on (P > 0.05) residual feed intake being modelled as one or two periods. However, profit per annual cow differed significantly between simulations using one or two residual feed intake periods (P < 0.001). In conclusion, it is very important to select the appropriate the method to estimate breeding values for residual feed intake.

To assess the economic importance of breeding traits, economic values (EV) were derived for 3 German dairy cattle breeds: German Holstein (HOL), Angler (ANG), and Red and White Dual-Purpose (RDN). For that purpose, the stochastic bio-economic model SimHerd (SimHerd A/S, Viborg, Denmark) was used, which simulates the expected monetary gain in dairy herds. The EV was calculated as the alteration in average net return of the herd responding to a marginal change in the trait of interest. When deriving EV using SimHerd, economic consequences resulting from changes in the age structure of a dairy herd (i.e., structural herd effects) are considered. However, this requires the simulation of relationships between traits in the bio-economic model. To avoid double counting, the EV of a trait was corrected for effects from alterations in correlated traits using multiple regression analysis. The EV were derived for 23 traits in terms of production, conformation and workability, dairy health, calf survival, and reproduction performance. Furthermore, the relative economic importance of the breeding traits was calculated. Relative emphasis on production was between 39.9 and 44.4% in the breeds studied. Total costs per case of ketosis and metritis ranged from €167 to €196 and €173 to €182, respectively. Highest marginal EV of direct health traits were found for mastitis (€257 to €271 per case) and lameness (€270 to €310 per case). Consequently, relative emphasis on direct health traits was between 15.7 and 17.9%. The EV of reproduction performance showed largest differences among the cattle breeds. Overall relative emphasis on reproduction was 10.5% in HOL, 10.8% in ANG, and 6.5% in RDN. The relative economic importance of cow mortality ranged from 15.5 to 16.0% across the breeds. Collectively, the study showed the high economic importance of functional traits in the cattle breeds studied.

Numerous Red cattle breeds exist all throughout Europe. Some Red cattle breeds are only used locally in certain regions and are smaller in population size, whereas other Red cattle breeds are used in multiple countries in mainstream production environments. Conservation of local Red breeds is necessary to maintain genetic diversity. Collaboration between local and mainstream Red cattle breeds can increase the genetic potential of the local breed and thereby the success of survival. The aim of this paper was to explore possibilities to increase the genetic potential of local Red cattle breeds by collaboration with a mainstream Red cattle breed, while at the same time conserve the local Red cattle breeds. Three breeds were included in this study; the mainstream Red dairy cattle breed from Denmark, Finland and Sweden (RDC) and two local Red cattle breeds, German Red and White dual-purpose cattle (RDN), and Lithuanian Red (LIR). Each simulation included the RDC breeding program and one local Red breeding program. Simulated time was 30 years, in which the first 20 years were used to build up reference populations and the last 10 years were used to run a genomic selection scheme with varying levels of collaboration between the local and the mainstream breeding program in the different scenarios. The maximum percentage of breeding bulls selected for breeding to the cows in the local breeding program that could originate from the RDC breeding program differed between scenarios, and could be either 0, 20, 50 or 100%. Results show that the maximum rate of genetic gain in the local breeds was reached in the scenarios where maximum 20, 50 or 100% of the breeding bulls could originate from the RDC breeding program. The highest rate of inbreeding was found in the scenario where no RDC bulls were selected in the local breeding programs. However, even with very restricted selection, the breed proportion of the local breeds dropped significantly after ten years of genomic selection. To really conserve a local breed such as RDN or LIR, a different selection strategy is needed.

Organic dairy production differs from conventional dairy production in many aspects. However, breeding programs for the 2 production systems are the same in most countries. Breeding goals (BG) might be different for the 2 production systems and genotype × environment interaction may exist between organic and conventional dairy production, both of which have an effect on genetic gain in different breeding strategies. Other aspects also need to be considered, such as the application of multiple ovulation and embryo transfer (MOET), which is not allowed in organic dairy production. The general aim of this research was to assess different environment-specific breeding strategies for organic dairy production. The specific aim was to study differences in BG weights and include the effect of genotype × environment interaction, MOET, and the selection of breeding bulls from the conventional environment. Different scenarios were simulated. In the current scenario, the present-day situation for dairy production in Denmark was emulated as much as possible. The BG was based on a conventional dairy production system, MOET was applied in both environments, and conventional bulls could be selected as breeding bulls in the organic environment. Four alternative scenarios were simulated, all with a specific organic BG in the organic breeding program but differences in the usage of MOET and the selection of conventional bulls as breeding bulls. Implementation of a specific BG in organic dairy production slightly increased genetic gain in the aggregate genotype compared with the breeding program that is currently implemented in organic dairy production. Not using embryo transfer or only selecting breeding bulls from the organic environment decreased genetic gain in the aggregate genotype by as much as 24%. However, the use of embryo transfer is debatable because this is not allowed according to current regulations for organic dairy production. Assessing genetic gain on trait levels showed that a significant increase for functional traits was possible compared with the current breeding program in the organic environment without a decrease in genetic gain in the aggregate genotype. This difference on trait level was even more present when selection of conventional bulls as breeding bulls in the organic environment was not possible. This finding is very relevant when breeding for the desired cow in organic dairy production.

Crossbreeding in dairy cattle has recently become of increased interest. However, farmers in Scandinavian countries are reluctant to implement crossbreeding in their herds, and one reason is the common opinion that only herds at a poor level of management can benefit from crossbreeding. The Danish Cattle Database (SEGES, Aarhus, Denmark) provided data on 14 traits regarding milk yield, udder health, fertility traits, stillbirth, and survival. The data were collected from 103,307 pure Holstein cows and 14,832 F1 crosses (Holstein dam and Nordic Red sire). The cows were born between 2008 and 2014 and originated from 424 herds that contributed data from at least 5 purebreds and 5 crossbreds across the years. We split the animals into 3 production levels: high, average, and low according to the herd's average production (kg) of 305-d fat plus protein in the given birth year of the cow. We estimated least squares means of breed group (purebred and crossbred) performance within each production level. Crossbred performance in 305-d fat yield in first-parity cows was greater than that of Holstein across all herd production levels; the gain was greater in high- (9 kg more than Holstein) and average-producing herds (7 kg more than Holstein) than in low-producing herds (3 kg more than Holstein). Regardless of production level or parity, crossbreds did not outperform Holstein in terms of 305-d protein yield (0 to 8 kg less). Crossbreds had relatively better udder health than Holstein in both first and second parity (up to 15% less mastitis) within any of the production levels. In terms of fertility, stillbirth, and survival, crossbreds performed better than purebreds, and improved performance was independent of herd production level. We conclude that differences in performance between F1 crossbreds and Holstein are independent of production level.

The Jutland Horse is an original Danish horse breed and is regarded as Denmark’s national draft horse. It was previously used as a draught horse in the farming industry. The studbook dates back to ...

Mineral and fatty acid composition in milk from two minor native dairy breeds in Denmark; Danish Red 1970 (RDM-1970) and Jutland cows were analyzed. Results showed that for most compositional traits breed only played a minor role, whereas management and feeding played a significant role. Biodynamic management and very low milk yield resulted in a very characteristic fatty acid composition and a strongly elevated n-3/n-6 ratio (ratio 0.9 compared to 0.3). For milk minerals, RDM-1970 had significantly higher contents of P, Mg, Mn, whereas milk from Jutland cows had significantly higher K content.

Prediction of detailed milk fatty acid (FA) composition by mid-infrared spectroscopy (MIRS) offers possibilities for high-throughput indirect measurements of detailed milk compositional parameters through the milk testing system, which can be used to differentiate the FA profile by genetics or specific management or on dairies for milk quality evaluation. Since 2015, milk samples from all Danish dairy cows under milk testing have been recorded using MIRS. The MIRS software from the FOSS Application Note 64 was used to predict contents of 7 FA groups and 4 individual FA. Data generated from the application note have been used to estimate breeding values for sires for percentage of saturated fat (SFA%) in milk. To investigate whether extreme SFA% breeding values of sires were reflected in the detailed milk FA profile from their daughters, milk samples from 194 cows in 7 organic herds were collected and the detailed FA composition measured by gas chromatography. From each cow, milk samples were collected twice to explore specific seasonal effects of pasture-based diets in relation to sires' estimated breeding value (EBV) for MIRS-predicted SFA% (MIRS-SFA%). The results showed a significant difference in SFA% measured from GC (GC-SFA%) in milk from daughters of sires having high SFA% EBV compared with daughters of sires having low SFA% EBV. The EBV group (low or high) also significantly affected most FA except C13:0, C15:0, C17:0, and C18:1 trans-11. Contents of SFA with even chain-lengths were all higher in the high EBV group, whereas C14:1, C16:1, and the other unsaturated C18 FA had a higher content in the low EBV group. All FA were significantly affected by season. The SFA% decreased from indoor spring feeding to summer pasture, as did FA with chain length ≤16 carbons, whereas long-chain FA (>C17) all increased during summer pasture. The results show that use of MIRS-predicted EBV for SFA% will most likely display a correlated response on the detailed FA composition in milk. In the current study, the combined action of feeding and genetics resulted in a 10 percentage-point difference on average when comparing milk SFA% from daughters of high SFA% EBV sires during indoor spring feeding from one farm to milk SFA% from daughters of low SFA% EBV sires during summer from another farm.

The aim of the study was to calculate economic values (EV) of breeding traits (production, reproduction, direct health, calving and survival traits) for the Polish dairy cattle breeds Polish Holstein (PH) and Polish Red (PR). EV are key elements in setting up economically based breeding goals for dairy cattle and they are crucial for optimizing breeding schemes. For deriving EV, a stochastic bio-economic model was used, which estimates EVs based on population-specific biological and economic characteristics. Because the bio-economic model considers correlations between different traits, a multiple regression approach was used to correct for any double counting of effects. The results showed that EVs for direct health traits and fertility differed between breeds. The biggest difference was observed for lameness (PH -1.44 €, PR -1.09 € per cow-year), ketosis (PH -0.94 €, PR -0.58 € per cow-year) and for cow conception rate (PH 1.94 €, PR 0.84 € per cow-year). The relative economic weights for production traits were estimated as 37.00 % (PH) and 34.30 % for (PR) and for fertility traits 15.10 % (PH and for 16.10 % (PR). Major economic differences between the relative weights were observed for cow mortality (22.70 % PH, 16.90 % PR). The results of our study showed that breeding the PH brings higher economic profit than breeding the PR. Total income per PR cow was equal to 1,623 € and for PH 2,970 €.

This study simulated the consequences of crossbreeding between Swedish Holstein and Swedish Red on herd dynamics and herd profitability under Swedish conditions. Two base herds were simulated using a stochastic herd simulation model, SimHerd Crossbred. The herds reflected average Swedish conventional and organic herds having purebred Swedish Holstein. For each base herd, 3 breeding strategies were simulated: purebreeding, 2-breed terminal crossbreeding, and 2-breed rotational crossbreeding. The terminal crossbreeding strategy implied having a nucleus of Swedish Holstein and a proportion of F-1 Swedish Red x Swedish Holstein crossbred cows within the same herd. The crossbreds in this herd did not produce replacement heifers but exclusively beef x dairy crass calves. Beef semen was also used in the pure-breeding (10-20% in cows) and the rotational crossbreeding (40% in cows) strategies to retain a limited surplus of replacement heifers. To ensure an adequate number of crossbreds in the terminal crossbreeding strategy, X-sorted sexed semen was used for insemination in all the purebred heifers. The outcome was 67% purebred and 31% F-1 crossbreds in the herd. In addition, 31% heterosis was expressed compared with 67% heterosis expressed using a 2-breed rotational crossbreeding strategy. Compared with the pure-breeding strategy, crossbreeding increased the annual contribution margin per cow by (sic)20 to (sic)59, with the rotational crossbreeding strategy creating the largest profitability. The increased profitability was mainly due to improved functional traits, especially fertility. For the conventional production system, the replacement rate was 39.3% in the pure-breeding strategy and decreased to 35.8 and 30.1% in the terminal and rotational crossbreeding strategy, respectively. Similar changes happened in the organic production system. Additionally, the crossbreeding strategies earned (sic)22 to (sic)42 more annually per cow from selling live calves for slaughter due to the extended use of beef semen. Milk production was similar between pure-breeding and terminal crossbreeding, and only decreased 1 to 2% in rotational crossbreeding. These results show that crossbreeding between Swedish Holstein and Swedish Red can be profitable in both conventional and organic Swedish herds using the strategies we have simulated. However, some aspects remain to be investigated, such as the economically optimal breeding strategy, genetic improvement, and transition strategies.

During the last decade, the use of systematic crossbreeding in dairy cattle herds has increased in several countries of the world. The aim of this study was to estimate the effect of breed proportion and heterosis on milk production traits and udder health traits in dairy cattle. The study was based on records on milk yield (MY), protein yield (PY), fat yield (FY), somatic cell score (SCS), and mastitis (MAST) from 73,695 first-lactation dairy cows in 130 Danish herds applying systematic crossbreeding programs. Around 45% of the cows were crosses between Danish Holstein (DH), Danish Red (DR), or Danish Jersey (DJ), and the remaining were purebred DH, DR, or DJ. The statistical model included the fixed effects of herd-year, calving month, and calving age and an effect representing the lactation status of the cow. In addition, the model included a regression on calving interval from first to second lactation, a regression on the proportion of DH, DR, and DJ genes, and a regression on the degree of heterozygosity between DH and DR, DH and DJ, and DR and DJ. Random effects were the genetic effect of the cow and a residual. The effect of breed proportions was estimated relatively to DH. For MY, a pure DR yielded 461 kg milk less than DH, whereas a pure DJ yielded 2,259 kg milk less than a pure DH. Compared with DH, PY was 41.7 kg less for DJ, whereas PY for DR was 4.0 kg less than for DH. For FY, a DR yielded 10.6 kg less than DH, whereas there was no significant effect of breed proportion between DJ and DH. A DR cow had lower SCS (0.13) than DH, whereas DJ had higher SCS (0.14) than DH. There was no significant effect of breed proportion on MAST between the 3 breeds. Heterosis was significant in all combinations of breeds for MY, FY, and PY. Heterosis for crosses between DH and DR was 257 kg (3.2%), 11.9 kg (3.2%), and 8.9 kg (3.2%) for MY, PY, and FY, respectively. Corresponding figures for crosses between DH and DJ were 314 kg (4.4%), 14.3 kg (4.4%), and 10.4 kg (4.0%), whereas heterosis between DR and DJ was 462 kg (6.7%), 19.6 kg (6.7%), and 13.9 kg (5.4%) for MY, PY, and FY, respectively. Heterosis was only significant for SCS in the crosses between DH and DR. Heterosis effects for MAST were nonsignificant for all the crosses. The results obtained in this study demonstrate that in first lactation cows, there is a positive effect of heterosis on milk production traits, but limited effect on udder health traits.

One joint breeding program (BP) for different dairy cattle environments can be advantageous for genetic gain depending on the genetic correlation between environments (rg). The break-even correlation (rb) refers to the specific rg where genetic gain with 1 joint BP is equal to the genetic gain of 2 environment-specific BP. One joint BP has the highest genetic gain if rg is higher than rb, whereas 2 environment-specific BP have higher genetic gain if rg is lower than rb. Genetic gain in this context is evaluated from a breeding company's perspective that aims to improve genetic gain in both environments. With the implementation of genomic selection, 2 types of collaboration can be identified: exchanging breeding animals and exchanging genomic information. The aim of this study was to study genetic gain in multiple environments with different breeding strategies with genomic selection. The specific aims were (1) to find rb when applying genomic selection; (2) to assess how much genetic gain is lost when applying a suboptimal breeding strategy; (3) to study the effect of the reliability of direct genomic values, number of genotyped animals, and environments of different size on rb and genetic gain; and (4) to find rb from each environment's point of view. Three breeding strategies were simulated: 1 joint BP for both environments, 2 environment-specific BP with selection of bulls across environments, and 2 environment-specific BP with selection of bulls within environments. The rb was 0.65 and not different from rb with progeny-testing breeding programs when compared at the same selection intensity. The maximum loss in genetic gain in a suboptimal breeding strategy was 24%. A higher direct genomic value reliability and an increased number of genotyped selection candidates increased genetic gain, and the effect on rb was not large. A different size in 2 environments decreased rb by, at most, 0.10 points. From a large environment's point of view, 1 joint BP was the optimal breeding strategy in most scenarios. From a small environment's point of view, 1 joint BP was only the optimal breeding strategy at high rg. When the exchange of breeding animals between environments was restricted, genetic gain could still increase in each environment. This was due to the exchange of genomic information between environments, even when rg between environments were as low as 0.4. Thus, genomic selection improves the possibility of applying environment-specific BP.

The aims of this study were to investigate variation and clustering in breeding goal trait preferences among Norwegian dairy farmers and to identify factors with a systematic influence on their preferences. An internet-based questionnaire was sent out to dairy farmers connected to the Norwegian co-operative breeding organization Geno (N = 8222), of which 10.8% answered (N = 888). Of the 15 suggested traits fertility had the highest overall ranking, while parasite resistance and methane emission had the lowest. Four distinct preference clusters were identified by the means of cluster analysis, of which two had a high preference for milk production. Differences in terms of farm and herd characteristics between clusters suggests a mixture of systematic and intrinsic effects on breeding goal trait priorities. This study shows that Norwegian dairy farmers' preferences for breeding goal traits fall into four distinct clusters, both affected by herd and farm characteristics along with intrinsic values.

When crossbreeding with beef breeds in organic dairy herds, the use of non-sexed semen will results in both male and female offspring to be used for beef production. The objective of the present study was to compare growth and carcass characteristics of 15 Danish Holstein bull (HB) calves, 15 beef x Danish Holstein crossbred bull (CB) calves and 15 beef x Danish Holstein crossbred heifer (CH) calves reared under organic settings. As beef bred sire a high-merit bull of the Limousine breed was used. Furthermore, the study should generate knowledge which can support future organic beef production. Forty-five Spring-born calves were purchased at 10 private farms at approximately 20 days of age with an average initial body weight of 52.9, 58.2 and 56.1 (s.e.m. 2.6) kg for HB, CB and CH, respectively. Calves were housed indoors in groups of five until weaning off cows’ milk at 3 months of age. Calves were gradually introduced to a grass-silage based ration from 3 to 4 months of age. From 4 to 7 months calves were kept on mixed grass pasture of ryegrass and white clover. From 7 to 13.5 months calves were housed indoor in groups of 5 and fed a mixed ration with low-moderate energy content. From 13.5 months of age, the established groups of 5 animals grazed in a rotational paddock system until slaughter at 17 months. There was no difference between HB, CB and CH in average daily gain (ADG) from birth to weaning, from weaning until turn-out and during pasture from 4 to 7 months. The ADG indoor from 7 to 13.5 months, and during pasture from 13.5 to 17 months differed between treatment groups. The CB had greater ADG than CH for both periods with HB being intermediate (P < 0.02–0.001). The ADG indoor from 7 to 13.5 months were 1.06, 1.10 and 0.97 (s.e.m. 0.02) kg d − 1 , and ADG during pasture from 13.5 months until slaughter were 0.88, 1.11, and 0.64 (s.e.m. 0.07) kg d − 1 for HB, CB, and CH, respectively. Final body weights were heavier for CB, intermediate for HB, and lowest for CH (575, 534, and 480 (s.e.m. 12.1) kg, P < 0.01). Overall, ADG from arrival to slaughter was 21% higher for CB than CH (P < 0.001), and the average ADG of the combined heifer and bull crossbreds ((CB+CH)/2) was not different from that of HB. Crossbreeding improved EUROP conformation markedly in both CH (5.3) and CB (7.0) compared with HB (3.0) (P < 0.001), and carcass weight was 4% higher for crossbreds ((CB+CH)/2) compared with HB. There was no difference in EUROP fatness between HB and CB which was low (1.0–1.2), whereas CH had an acceptable fatness (2.9). Carcass lean:fat color (assessed using a Danish 1–5 scale) was high for the bulls (3.9–4.0) but acceptable for CH (3.3, P < 0.01). It is concluded that improvements in carcass conformation and carcass weight coupled with similar overall growth of the combined heifer and bull crossbreds support the efficiency of beef x Holstein crossbreds of both sexes compared with purebred Holstein bulls within an organic system with summer grazing. Furthermore, it proved difficult to finish intact bulls on pasture to fulfill a premium beef cut market that requires higher fatness and less dark meat color than obtained herein.

Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. The objectives of this study were to study G × E interactions for female fertility traits in the Danish Holstein dairy cattle population using a reaction norm model (RNM), and to detect the particular genomic regions contributing to the performance of these traits and the G × E interactions. In total 4534 bulls were genotyped by an Illumina BovineSNP50 BeadChip. An RNM with a pedigree-based relationship matrix and a pedigree-genomic combined relationship matrix was used to explore the existence of G × E interactions. In the RNM, the environmental gradient (EG) was defined as herd effect. Further, the genomic regions affecting interval from calving to first insemination (ICF) and interval from first to last insemination (IFL) were detected using single-step genome-wide association study (ssGWAS). The genetic correlations between extreme EGs indicated that G × E interactions were sizable for ICF and IFL. The genomic RNM (pedigree-genomic combined relationship matrix) had higher prediction accuracy than the conventional RNM (pedigree-based relationship matrix). The top genomic regions affecting the slope of the reaction norm included immunity-related genes (IL17, IL17F and LIF), and growth-related genes (MC4R and LEP), while the top regions influencing the intercept of the reaction norm included fertility-related genes such as EREG, AREG and SMAD4. In conclusion, our findings validated the G × E interactions for fertility traits across different herds and were helpful in understanding the genetic background of G × E interactions for these traits.

The overall aim of this research was to characterize the preferences of Danish dairy farmers for improvements in breeding goal traits. The specific aims were (1) to investigate the presence of heterogeneity in farmers’ preferences by means of cluster analysis, and (2) to associate these clusters with herd characteristics and production systems (organic or conventional). We established a web-based survey to characterize the preferences of farmers for improvements in 10 traits, by means of pairwise rankings. We also collected a considerable number of herd characteristics. Overall, 106 organic farmers and 290 conventional farmers answered the survey, all with Holstein cows. The most preferred trait improvement was cow fertility, and the least preferred was calving difficulty. By means of cluster analysis, we identified 4 distinct clusters of farmers and named them according to the trait improvements that were most preferred: Health and Fertility, Production and Udder Health, Survival, and Fertility and Production. Some herd characteristics differed between clusters; for example, farmers in the Survival cluster had twice the percentage of dead cows in their herds compared with the other clusters, and farmers that gave the highest ranking to cow and heifer fertility had the lowest conception rate in their herds. This finding suggests that farmers prefer to improve traits that are more problematic in their herd. The proportion of organic and conventional farmers also differed between clusters; we found a higher proportion of organic farmers in the production-based clusters. When we analyzed organic and conventional data separately, we found that organic farmers ranked production traits higher than conventional farmers. The herds of organic farmers had lower milk yields and lower disease incidences, which might explain the high ranking of milk production and the low ranking of disease traits. This study shows that heterogeneity exists in farmers’ preferences for improvements in breeding goal traits, that organic and conventional farmers differ in their preferences, and that herd characteristics can be linked to different farmer clusters. The results of this study could be used for the future development of breeding goals in Danish Holstein cows and for the development of customized total merit indices based on farmer preferences.

Most cows face energy deficits in early lactation during peak milk production, which is reflected in the milk fatty acid (FA) profile. These cows typically mobilize body reserves to maintain milk fat production, and synthetize less FA de novo in the mammary gland. Milk FA can be routinely predicted by Fourier-transform infrared spectroscopy (FT-IR). This rapid milk analysis offers therefore an opportunity to develop an early indicator for body weight (BW) change based on the milk FA profile. The objective of this study was to validate if the milk FA profile can be used to predict BW change in early lactating cows in commercial dairy farms. Data originated from 17,067 Danish Holstein cows at 7-35 days in milk across 166 herds in Denmark between March 2015 and March 2017 with BW records from floor scales in Lely automatic milking systems at each milking. Milk FA were predicted by FT-IR on FOSS instruments providing seven groups of FA and four individual FA. Data for BW change predictions included parity, stage of lactation, and test day data for milk production and components (fat, protein, somatic cell counts, and FA concentrations). Daily BW change (median ± standard deviation) was −0.32 ± 2.66 g/kg of BW (first parity), −0.46 ± 2.82 g/kg of BW (second parity) and −0.60 ± 5.53 g/kg of BW (third parity and longer). Predictions of BW change were based on a random forest model that can account for nonlinear and high dimensional interactions. The model was validated with ten-fold repeated cross-validation for which 20% of the herds were randomly withhold for validation such that data of a specific herd are used exclusively either to train or to cross-validate the model. The overall root mean square error of prediction after cross-validation was 1.66 g/kg of BW with the model explaining 89.6% of the variance. The five most important variables to develop the model were the short-chain FA group (C4:0–C10:0), oleic acid (C18:1), the medium-chain FA group (C12:0–C16:1), the saturated FA group, and palmitic acid (C16:0). The short-chain and some medium-chain FA are synthesized de novo in the mammary gland, oleic acid originates from body reserves (e.g., during energy deficits), and palmitic and palmitoleic acid (C16:1) originate either from the de novo FA pool or from body reserves. These results suggest that the FT-IR milk FA profile may be used as an early indicator of BW change in early lactation cows. Nonetheless, before this model can be used in commercial farms, the model needs to be validated for different herd management and feeding strategies, breeds and country- or region-specific conditions. Further work is needed to assess the impact of the level of BW change on milk production, reproductive performance and health. Future models may gain from the inclusion of other milk components such as milk beta-hydroxybutyrate known to be linked to BW loss in early lactation. An early warning system may be implemented for cows with a large BW loss in early lactation based on the FT-IR milk FA profile.

Extended lactation has shown economic benefits in dairy herds, but this strategy may affect the genetic lag between the production cows at herd level and the semen bulls unfavorably. We hypothesize, that a breeding strategy using sexed semen (SS) will reduce this effect and that SS and extended lactation has synergetic effects on the total economic return. A base scenario reflected an average Danish Holstein herd with 13 months calving interval (CInt) (BASE). Additionally, six scenarios with extended lactations: two with only first parity cows managed for a CInt of 15 (FIRST15) and 17 months (FIRST17), two with only cows in second parity or higher managed for a CInt of 15 (OLDER15) and 17 months (OLDER17), and two with all cows managed for a CInt of 15 (ALL15) and 17 months (ALL17). These were combined with four breeding schemes illustrating different uses of SS within each of the scenarios: SS in 50% genetically best heifers (SS50), 75% genetically best heifers (SS75), all heifers (SS100) and 70% genetically best heifers and 30% first parity cows (SS7030). Beef semen was used when necessary to equalize the number of replacement heifers within extended lactation scenarios. The scenarios were simulated using two stochastic simulation models for estimation of operational returns (SimHerd) and for genetic returns (ADAM). The genetic returns support that extended lactation has an unfavorable effect on genetic lag in SS0, because the generation interval among breeding females increases when extended lactation is introduced. Compared to BASE/SS0 most combinations of SS and extended lactation, with the exception of ALL17 combinations increased genetic returns as a result of decreased generation interval. Across extended lactation scenarios, reductions in genetic return relative to BASE was between €1 (FIRST15) and €12 (ALL17) per cow year within each scenario of SS. With increased use of SS, the genetic returns increased from €4 (SS50) to €12 (SS7030) per cow year, compared to SS0 within each scenario of extended lactation. In total economic return, the use of SS had effects between +€5 and +€29 per cow year due to increased use of beef semen, thus more sales of slaughter calves. Except for OLDER15 and OLDER17, the extended lactation scenarios within each scenario of SS increased total economic returns as well. In conclusion, the genetic lag caused by extended lactation can be reduced using SS, although there was no synergetic effect between SS and extended lactation on the total economic return.

Conventional and organic production systems mainly differ in feeding strategies, outdoor and pasture access, and the use of antibiotic treatments. These environmental differences could lead to a genotype by environment interaction (G × E) and a requirement for including G × E in breeding decisions. The objectives of this study were to estimate variance components and heritabilities for conventional and organic production systems and investigate G × E under these 2 production systems for female fertility traits in Danish Holsteins. The analyzed traits included the interval from calving to first insemination (ICF), the interval from first to last insemination, number of inseminations per conception (NINS), and non-return rate within 56 d after the first insemination. Records of female fertility in heifers and the first 3 lactations in cows as well as grass ratio of feed at herd level were collected during the period from 2011 to 2016. The performances of a trait in heifers and cows (lactation 1 to 3) were considered as different traits. The (co)variance components and the resulting heritabilities and genetic correlations were estimated using 2 models. One was a bivariate model treating performances of a trait under organic and conventional production systems as 2 different traits using a reduced data set, and the other was a reaction norm model with random regression on the production system and the grass ratio of feed using a full data set. The full data set comprised records of 37,836 females from 112 organic herds and 513,599 females from 1,224 conventional herds, whereas the reduced data set comprised records from all these 112 organic herds and 92,696 females from 185 convention herds extracted from the full data set with grass ratio of feed lower than 0.20. All female fertility performances of the organic production system were superior to those of the conventional production system. Besides, heterogeneities in additive genetic variances and heritabilities were observed between conventional and organic production systems for all traits. Furthermore, genetic correlations between these 2 production systems ranged from 0.607 to 1.000 estimated from bivariate models and from 0.848 to 0.999 estimated from reaction norm models. Statistically significant G × E were observed for NINS in heifers, non-return rate within 56 d after the first insemination in heifers, and ICF from the bivariate model, and for ICF and NINS in cows from the reaction norm model.

The aim of this study was to estimate genetic parameters for estrus-related traits that could improve selection for increased fertility due to improved ability of the cow to return to cycling and go into heat after calving. We compared the time from calving to first insemination (CFI) to 3 physical activity traits: the interval from calving to first high activity (CFHA), estrus duration (ED), and estrus strength (ES). We calculated CFI based on data from commercial Holstein herds that included the insemination dates for 11,363 cows. The CFHA, ED, and ES traits were derived from electronic activity tags for 3,533 Holstein cows. Estimates of heritability were 0.07 for CFI, 0.16 for CFHA, 0.02 for ED, and 0.05 for ES. We found a strong genetic correlation between CFI and CFHA (0.96). Genetic correlations between ED and CFI and CFHA were −0.37 and −0.68, respectively. Genetic correlations between ES and CFI and CFHA were −0.50 and −0.58, respectively. The heritability of CFHA and its strong genetic correlation with CFI suggest that including CFHA in the genetic evaluation of female cow fertility could improve the effectiveness of selection, because CFHA reflects the ability to return to cyclicity and go into heat after calving.

In Denmark, Finland, and Sweden, the Nordic Total Merit index is used as the breeding selection tool for both organic and conventional dairy farmers based on common economic models for conventional dairy farming. Organic farming is based on the principles of organic agriculture (POA) defined by the International Federation of Organic Agriculture Movements. These principles are not set up with an economic point of view, and therefore it may be questionable to use a breeding goal (BG) for organic dairy production based on economic models. In addition to economics and the principles of organic agriculture, it is important to look at farmers' preferences for improving BG traits when setting up a BG for organic farming. The aim of this research was to set up, simulate, and compare long-term effects of different BG for organic and conventional dairy production systems based on economic models, farmers' preferences, and POA, with particular emphasis on disease resistance or on roughage consumption and feed efficiency. The BG based on economic models and on farmers' preferences were taken from previous studies. The other BG were desired gains indices, set up by means of a questionnaire about relatedness between the POA and BG traits. Each BG was simulated in the stochastic simulation program ADAM. The BG based on POA, with particular emphasis on disease resistance or on roughage consumption and feed efficiency, caused favorable genetic gain in all 12 traits included in this study compared with 6 traits for the other BG. The BG based on POA, with particular emphasis on disease resistance or on roughage consumption and feed efficiency, were very different from BG for organic and conventional production based on economic models and farmers' preferences in both simulated genetic change and correlations between BG. The BG that was created based on the principles of organic agriculture could be used as a specific index for organic dairy farming in Denmark, but this index was economically not very sustainable. Hence, an intermediate breeding goal could be developed by breeding companies to address both economics and the principles of organic agriculture.

Our aim was to investigate the genetic correlations between CH4 production and body conformation, fertility, and health traits in dairy cows. Data were collected from 10 commercial Holstein herds in Denmark, including 5,758 cows with records for body conformation traits, 7,390 for fertility traits, 7,439 for health traits, and 1,397 with individual CH4 measurements. Methane production was measured during milking in automatic milking systems, using a sniffer approach. Correlations between CH4 and several different traits were estimated. These traits were interval between calving and first insemination, interval between first and last insemination, number of inseminations, udder diseases, other diseases, height, body depth, chest width, dairy character, top line, and body condition score. Bivariate linear models were used to estimate the genetic parameters within and between CH4 and the other traits. In general, the genetic correlations between CH4 and the traits investigated were low. The heritability of CH4 was 0.25, and ranged from 0.02 to 0.07 for fertility and health traits, and from 0.17 to 0.74 for body conformation traits. Further research with a larger data set should be performed to more accurately establish how CH4 relates to fertility, health, and body conformation traits in dairy cattle. This will be useful in the design of future breeding goals that consider the production of CH4.

The objective of this study was to assess the genetic variability of the detailed fatty acid (FA) profiles of Danish Holstein (DH) and Danish Jersey (DJ) cattle populations. We estimated genetic parameters for 11 FA or groups of FA in milk samples from the Danish milk control system between May 2015 and October 2016. Concentrations of different FA and FA groups in milk samples were measured by mid-infrared spectroscopy. Data used for parameter estimation were from 132,732 first-parity DH cows and 21,966 first-parity DJ cows. We found the highest heritabilities for test day measurements in both populations for short-chain FA (DH = 0.16; DJ = 0.16) and C16:0 (DH = 0.14; DJ = 0.16). In DH, the highest heritabilities were also found for saturated FA and monounsaturated FA (both populations: 0.15). Genetic correlations between the fatty acid traits showed large differences between DH and DJ for especially short-chain FA with the other FA traits measured. Furthermore, genetic correlations of total fat with monounsaturated FA, polyunsaturated FA, short-chain FA, and C16:0 differed markedly between DH and DJ populations. In conclusion, we found genetic variation in the mid-infrared spectroscopy-predicted FA and FA groups of the DH and DJ cattle populations. This finding opens the possibility of using genetic selection to change the FA profiles of dairy cattle.

Dairy farmers can increase the number of dairy heifer calves born in their herd by using sexed semen. They can reduce the number of both dairy bull and heifer calves by using beef semen. Long before sexed semen became commercially available, it was believed that it would provide opportunities for increasing genetic level in both herds and populations. In this study, we studied the potential for increasing the genetic level of a herd by using beef semen in combination with sexed semen. We tested the hypothesis that the potential of increasing the genetic level and the overall net return would depend on herd management. To test this hypothesis, we simulated 7 scenarios using beef semen and sexed semen in 5 herds at different management levels. We combined the results of 2 stochastic simulation models, SimHerd and ADAM. SimHerd simulated the effects of the scenarios and management levels on economic outcomes (i.e., operational return) and on technical outcomes such as the parity distribution of the dams of heifer calves, but it disregarded genetic progress. The ADAM model quantified genetic level by using the dams' parity distributions and the frequency of sexed and beef semen to estimate genetic return per year. We calculated the annual net return per slot as the sum of the operational return and the genetic return, divided by the total number of slots. Net return increased up to €18 per slot when using sexed semen in 75% genetically superior heifers and beef semen in 70% genetically inferior, multiparous cows. The assumed reliability of selection was 0.84. These findings were for a herd with overall high management for reproductive performance, longevity, and calf survival. The same breeding strategy reduced net return by €55 per slot when management levels were average. The main reason for the large reduction in net return was the heifer shortage that arose in this scenario. Our hypothesis that the potential for beef semen to increase genetic level would be herd-specific was supported. None of the scenarios were profitable under Danish circumstances when the value of the increased genetic level was not included. A comparable improvement in genetic level could be realized by selectively selling dairy heifer calves rather than using beef semen.

Crossing of lines or strains within and between breeds has been demonstrated to be beneficial for dairy cattle performance. However, even within breed, differences between strains may also give rise to heterosis. A key question is whether an interaction exists between heterosis and environment (H x E) that is independent of genotype by environment (G x E) interactions. In this study, H x E and G x E interactions were estimated in a population of approximately 300,000 Danish Jersey cows. The cows were a mixture of pure Danish Jerseys and crosses of US and Danish Jerseys. The phenotype studied was protein yield. A reaction norm model where the unknown environmental covariates are inferred simultaneously with the other parameters in the model was used to analyze the data. When H x E, but not G x E, was included in the model, heterosis was estimated to be 3.8% for the intermediate environmental level. However, when both H x E and G x E were included in the model, heterosis was estimated to be 4.1% for the intermediate environmental level. Furthermore, when only H x E was included in the model, the regression on the unknown environmental covariate was estimated to be 0.15, interpreted as meaning that an increase of average herd-year protein yield by 1 kg of protein led to an increase in heterosis of 0.15 kg above the average heterosis for a first-cross cow. When both H x E and G x E were included in the model, the regression on the unknown environmental covariate was not significantly different from zero, meaning that heterosis was similar in all environments investigated. The genetic correlation of protein yields for different environmental levels ranged from 0.72 to 0.93, which was significantly different from unity, indicating that G x E exist for protein yield.

Our aim was to investigate whether four fertility traits were different in herds using the activity tag Heatime for reproduction management compared within other herds. The genetic parameters were estimated using animal models. The fertility traits were number of inseminations (NINS), interval from first to last insemination (IFL), age at first insemination (AFI), and age at first calving (AFC) in Danish Holstein heifers. The means of the traits were all significantly different between the two groups of herds. Heritabilities for NINS and IFL were lower than 1%, while heritabilities for AFI and AFC were 12–29%. Heritabilities were all lower in Heatime herds than in reference herds. The genetic correlations between traits in different environments were high for NINS, AFI, and AFC (>0.88), while the correlation for IFL was 0.68 but with a higher SE (0.313). Thus, IFL seems not to be the same trait in Heatime and reference herds.

Crossbreeding has been shown to improve the longevity of dairy cattle in countries across the world. The aim of this study was to estimate heterosis, breed effects, and genetic parameters for longevity in crossbred dairy cattle among Danish Holstein (DH), Danish Red (DR), and Danish Jersey (DJ) breeds. Data were provided from 119 Danish commercial herds that use systematic crossbreeding (i.e., rotational crossbreeding). Additional data from 11 mixed-breed herds with DH and DJ were included to estimate reliable breed effects for DJ. Survival information on 73,741 cows was analyzed with a linear animal model using the artificial insemination–REML algorithm in the DMU package. Five longevity (L) traits were defined: days from first calving until the end of first lactation or culling (L1), days from first calving until the end of second lactation or culling (L2), days from first calving until the end of third lactation or culling (L3), days from first calving until the end of fourth lactation or culling (L4), and days from first calving until the end of fifth lactation or culling (L5). Heritabilities ranged between 0.022 and 0.090. Additive breed effects in units of days were estimated relative to DH for DR as −0.5 (L1), +10.5 (L2), +18.5 (L3), +11.9 (L4), and +28.6 (L5), and corresponding figures for DJ were +2.0, +0.5, +14.2, +27.7, and +44.0. Heterosis effects in L1 were low (1.2%) but favorable in crosses between DH and DR, whereas negative heterosis effects were estimated for crosses between DH and DJ (−2.5%) and DR and DJ (−1.2%). The largest heterosis effects for L2, L3, L4, and L5 were found in DH × DR and were favorable (+3.3, +5.7, +7.7, and +8.5%, respectively). Corresponding figures for heterosis effects in DH × DJ and DR × DJ were favorable as well: +2.3, +4.1, +5.6, and +6.2% in DH × DJ and +3.1, +7.3, +6.9, and +7.2% in DR × DJ. The favorable heterosis effects show that crossbreeding is an efficient tool for improving longevity in Danish dairy cattle.

The objective of this study was to investigate whether genotype by environment interaction exists for female fertility traits and production of energy-corrected milk at 70 d in milk (ECM70). Fertility traits considered were the activity-based estrus traits interval from calving to first high activity (CFHA), duration of high activity episode (DHA), as an indicator for first estrus duration, and strength of high activity episode (SHA), as an indicator for first estrus strength. The physical activity traits were derived from electronic activity tags for 11,522 first-parity cows housed in 125 commercial dairy herds. Data were analyzed using a univariate random regression animal model (URRM), by regressing the phenotypic performance on the average herd ECM70 as an environmental gradient. Furthermore, the genetic correlations between CFHA and ECM70 as a function of production level were estimated using a bivariate random regression animal model (BRRM). For all traits, heterogeneity of additive genetic variances and heritability estimates was observed. The heritability estimate for CFHA decreased from 0.25 to 0.10 with increasing production level and the heritability estimate for ECM70 decreased from 0.35 to 0.15 with increasing production level using URRM. The genetic correlation of the same trait in low and high production levels was around 0.74 for CFHA and 0.80 for ECM70 using URRM, but when data were analyzed using the multiple-trait analysis (MT), genetic correlation estimates between low and high production levels were not significantly different from unity. Furthermore, the genetic correlation of SHA between low and high production level was 0.22 using URRM, but the corresponding correlation estimate had large standard error when data were analyzed using MT. The genetic correlation between CFHA and ECM70 as a function of production environment was weak but unfavorable and decreased slightly from 0.09 to 0.04 with increasing production level using BRRM. Moreover, the same trend was observed when the data were analyzed using MT where the genetic correlation between CFHA and ECM70 in the low production environment was 0.29 compared with −0.13 in the high production environment, but these estimates had large standard errors. In conclusion, regardless of the trait used, in relation to average herd ECM70 production, the results indicated no clear evidence of strong genotype by environment interaction that would cause significant re-ranking of sires between low and high production environments.

It has been a challenge to avoid double counting when economic values (EV) of traits are derived for breeding goal traits when using stochastic herd simulation models. In this study multiple regression and model building with mediator variables representing other traits in the breeding goal were evaluated to avoid double counting. EV were derived from data simulated with the SimHerd dairy herd simulation model. Scenarios were simulated to represent dairy herds with low and high levels of metritis and cow mortality. The simulated data was analyzed statistically with the economic net return per cow-year as the dependent variable and either the incidences of metritis or the incidence of cow mortality as the independent variables. In the model with metritis we corrected for mediator variables representing the direct effects of metritis on milk yield, fertility and occurrence of other diseases. The EV was estimated as the marginal change in economic net return in response to a change in the trait of interest. To avoid the multiple regression models to correct the EV for structural herd effects (changes in distribution of parities and lactation stages) we used a single animal based indicator variable for each trait of interest, such as incidence rate of cow mortality 1–100 DIM in multiparous cows. The EV value of improving the trait ‘incidence rate of metritis 1–100 DIM in multiparous cows’ by 0.01 was estimated to be €0.93. The importance of avoiding double counting was demonstrated as the EV of metritis was overestimated by 82% when no mediator variables were included in the multiple regression analysis. And by ignoring structural herd effects for the EV of metritis we demonstrated an underestimation in the order of 9%. Further pitfall of underestimation was demonstrated for EV of cow mortality. The EV of improving the trait ‘incidence rate of cow mortality 1–100 DIM in multiparous cows’ by 0.01 was estimated to be €46.4. Correcting for the independent variation in mortality between simulation replicates within the individual scenarios was found to be important. The results of this study suggests a new method for designing simulation experiments and analyzing simulated herd effects for estimation of EV of traits in a breeding goal. This deals with a number of previous and new concerns of how to correct for double counting and at the same time still include the structural herd effects.

Following the recent years' increase in herd size, the awareness of a group of cows with a generally lowered health and production level, the “loser cows,” has arisen in Denmark. The aim of this study was to estimate genetic correlations between the loser cow score, 305d protein yield and realized productive life (RPL) and inbreeding depression for the loser cow score. Estimation of genetic correlations and inbreeding depression was performed on 2644 first-lactation cows and 4914 multiple-lactation cows, respectively. We found no significant genetic correlation between the loser cow score and the inbreeding level or between the loser cow score and protein yield. However, the loser cow score was favorably correlated with RPL (−0.53). This implies that the prevalence of loser cows is neither a result of inbreeding depression nor an undesirable side effect of selecting for increased production.