In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding ...social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows.
This study investigated the possibility of increasing the reliability of direct genomic values (DGV) by combining reference populations. The data were from 3,735 bulls from Danish, Swedish, and ...Finnish Red dairy cattle populations. Single nucleotide polymorphism markers were fitted as random variables in a Bayesian model, using published estimated breeding values as response variables. In total, 17 index traits were analyzed. Reliabilities were estimated using a 5-fold cross validation, and calculated as the within-year squared correlation between estimated breeding values and DGV. Marker effects were estimated using reference populations from individual countries, as well as using a combined reference population from all 3 countries. Single-country reference populations gave mean reliabilities across 17 traits of 0.19 to 0.23, whereas the combined reference gave mean reliabilities of 0.26 for all populations. Using marker effects from 1 population to predict the other 2 gave a loss in mean reliability of 0.14 to 0.21 when predicting Swedish or Finnish animals with Danish marker effects, or vice versa. Using Swedish or Finnish marker effects to predict each other only showed a loss in mean reliability of 0.03 to 0.05. A combined Swedish-Finnish reference population led to an average reliability as high as that from the 3-country reference population, but somewhat different for individual traits. The results from this study show that it is possible to increase the reliability of DGV by combining reference populations from related populations.
In this study, we compared mating allocations in Nordic Red Dairy Cattle using genomic information. We used linear programming to optimize different economic scores within each herd, considering ...genetic level, semen cost, the economic impact of recessive genetic defects, and genetic relationships. We selected 9,841 genotyped females born in Denmark, Finland, or Sweden in 2019 for mating allocations. We used 2 different pedigree relationship coefficients, the first tracing the pedigree 3 generations back from the parents of the potential mating and the second based on all available pedigree information. We used 3 different genomic relationship coefficients, 1 SNP-by-SNP genomic relationship and 2 based on shared genomic segments. We found high correlations (≥0.83) between the pedigree and genomic relationship measures. The mating results showed that it was possible to reduce the different genetic relationships between parents with minimal effect on genetic level. Including the cost of known recessive genetic defects eliminated expression of genetic defects. It was possible to reduce genomic relationships between parents with pedigree measures, but it was best done with genomic measures. Linear programming maximized the economic score for all herds studied within seconds, which means that it is suitable for implementation in mating software to be used by advisors and farmers.
Because of an increasing interest in crossbreeding between dairy breeds in dairy cattle herds, farmers are requesting breeding values for crossbred animals. However, genomically enhanced breeding ...values are difficult to predict in crossbred populations because the genetic make-up of crossbred individuals is unlikely to follow the same pattern as for purebreds. Furthermore, sharing genotype and phenotype information between breed populations are not always possible, which means that genetic merit (GM) for crossbred animals may be predicted without the information needed from some pure breeds, resulting in low prediction accuracy. This simulation study investigated the consequences of using summary statistics from single-breed genomic predictions for some or all pure breeds in two- and three-breed rotational crosses, rather than their raw data. A genomic prediction model taking into account the breed-origin of alleles (BOA) was considered. Because of a high genomic correlation between the breeds simulated (0.62-0.87), the prediction accuracies using the BOA approach were similar to a joint model, assuming homogeneous SNP effects for these breeds. Having a reference population with summary statistics available from all pure breeds and full phenotype and genotype information from crossbreds yielded almost as high prediction accuracies (0.720-0.768) as having a reference population with full information from all pure breeds and crossbreds (0.753-0.789). Lacking information from the pure breeds yielded much lower prediction accuracies (0.590-0.676). Furthermore, including crossbred animals in a combined reference population also benefitted prediction accuracies in the purebred animals, especially for the smallest breed population.
In this study, we aimed to estimate and compare the genetic parameters of dry matter intake (DMI), energy-corrected milk (ECM), and body weight (BW) as 3 feed efficiency–related traits across ...lactation in 3 dairy cattle breeds (Holstein, Nordic Red, and Jersey). The analyses were based on weekly records of DMI, ECM, and BW per cow across lactation for 842 primiparous Holstein cows, 746 primiparous Nordic Red cows, and 378 primiparous Jersey cows. A random regression model was applied to estimate variance components and genetic parameters for DMI, ECM, and BW in each lactation week within each breed. Phenotypic means of DMI, ECM, and BW observations across lactation showed to be in very similar patterns between breeds, whereas breed differences lay in the average level of DMI, ECM, and BW. Generally, for all studied breeds, the heritability for DMI ranged from 0.2 to 0.4 across lactation and was in a range similar to the heritability for ECM. The heritability for BW ranged from 0.4 to 0.6 across lactation, higher than the heritability for DMI or ECM. Among the studied breeds, the heritability estimates for DMI shared a very similar range between breeds, whereas the heritability estimates for ECM tended to be different between breeds. For BW, the heritability estimates also tended to follow a similar range between breeds. Among the studied traits, the genetic variance and heritability for DMI varied across lactation, and the genetic correlations between DMI at different lactation stages were less than unity, indicating a genetic heterogeneity of feed intake across lactation in dairy cattle. In contrast, BW was the most genetically consistent trait across lactation, where BW among all lactation weeks was highly correlated. Genetic correlations between DMI, ECM, and BW changed across lactation, especially in early lactation. Energy-corrected milk had a low genetic correlation with both DMI and BW at the beginning of lactation, whereas ECM was highly correlated with DMI in mid and late lactation. Based on our results, genetic heterogeneity of DMI, ECM, and BW across lactation generally was observed in all studied dairy breeds, especially for DMI, which should be carefully considered for the recording strategy of these traits. The genetic correlations between DMI, ECM, and BW changed across lactation and followed similar patterns between breeds.
Residual feed intake (RFI) is a candidate trait for feed efficiency in dairy cattle. We investigated the influence of lactation stage on the effect of energy sinks in defining RFI and the genetic ...parameters for RFI across lactation stages for primiparous dairy cattle. Our analysis included 747 primiparous Holstein cows, each with recordings on dry matter intake (DMI), milk yield, milk composition, and body weight (BW) over 44 lactation weeks. For each individual cow, energy-corrected milk (ECM), metabolic BW (MBW), and change in BW (ΔBW) were calculated in each week of lactation and were taken as energy sinks when defining RFI. Two RFI models were considered in the analyses; RFI model 1 was a 1-step RFI model with constant partial regression coefficients of DMI on energy sinks (ECM, MBW, and ΔBW) over lactation. In RFI model 2, data from 44 lactation weeks were divided into 11 consecutive lactation periods of 4 wk in length. The RFI model 2 was identical to model 1 except that period-specific partial regressions of DMI on ECM, MBW, and ΔBW in each lactation period were allowed across lactation. We estimated genetic parameters for RFI across lactation by both models using a random regression method. Using RFI model 2, we estimated the period-specific effects of ECM, MBW, and ΔBW on DMI in all lactation periods. Based on results from RFI model 2, the partial regression coefficients of DMI on ECM, MBW, and ΔBW differed across lactation in RFI. Constant partial regression coefficients of DMI on energy sinks over lactation was not always sufficient to account for the effects across lactation and tended to give roughly average information from all period-specific effects. Heritability for RFI over 44 lactation weeks ranged from 0.10 to 0.29 in model 1 and from 0.10 to 0.23 in model 2. Genetic variance and heritability estimates for RFI from model 2 tended to be slightly lower and more stable across lactation than those from model 1. In both models, RFI was genetically different over lactation, especially between early and later lactation stages. Genetic correlation estimates for RFI between early and later lactation tended to be higher when using model 2 compared with model 1. In conclusion, partial regression coefficients of DMI on energy sinks differed across lactation when modeling RFI. Neglect of lactation stage when defining RFI could affect the assessment of RFI and the estimation of genetic parameters for RFI across lactation.
The development of breeding tools, such as genomic selection and sexed semen, has progressed rapidly in dairy cattle breeding during the past decades. In combination with beef semen, these tools are ...adopted increasingly at herd level. Dairy crossbreeding is emerging, but the economic and genetic consequences of combining it with the other breeding tools are relatively unknown. We investigated 5 different sexed semen schemes where 0, 50, and 90% of the heifers; 50% of the heifers + 25% of the first-parity cows; and 90% of the heifers + 45% of the first-parity cows were bred to sexed semen. The 5 schemes were combined in scenarios managing pure-breeding or terminal crossbreeding, including genomic testing of all newborn heifers or no testing, and keeping Swedish Red or Swedish Holstein as an initial breed. Thus, 40 scenarios were simulated, combining 2 stochastic simulation models: SimHerd Crossbred (operational returns) and ADAM (genetic returns). The sum of operational and genetic returns equaled the total economic return. Beef semen was used in all scenarios to limit the surplus of replacement heifers. Terminal crossbreeding implied having a nucleus of purebred females, where some were inseminated with semen of the opposite breed. The F1 crossbred females were inseminated with beef semen. The reproductive performance played a role in improving the benefit of any of the tools. The most considerable total economic returns were achieved when all 4 breeding tools were combined. For Swedish Holstein, the highest total economic return compared with a pure-breeding scenario, without sexed semen and genomic test, was achieved when 90% sexed semen was used in heifers and 45% sexed semen was used for first-parity cows combined with genomic test and crossbreeding (+€58, 33% crossbreds in the herd). The highest total economic return for Swedish Red compared with a pure-breeding scenario, without sexed semen and genomic test, was achieved when 90% sexed semen was used in heifers combined with genomic test and crossbreeding (+€94, 46% crossbreds in the herd). Terminal crossbreeding resulted in lower genetic returns across the herd compared with the corresponding pure-breeding scenarios but was compensated by a higher operational return.
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: pure-breeding, 2-breed terminal crossbreeding, and 2-breed rotational crossbreeding. The terminal crossbreeding strategy implied having a nucleus of Swedish Holstein and a proportion of F1 Swedish Red × Swedish Holstein crossbred cows within the same herd. The crossbreds in this herd did not produce replacement heifers but exclusively beef × dairy cross 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% F1 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 €20 to €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 €22 to €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.
•The effect of changed herd management on cow dairy cow longevity and herd dynamics.•Low replacement rate is key to increasing cow longevity, profits, and sustainability.•Good reproductive ...performance is a prerequisite for a low cow replacement rate.•Beef production from dairy herds can be increased by using beef semen on dairy cows.•Results can be implicated as herd management changes to increase cow longevity.
Sustainable dairy and beef production provides environmental, economic, and social values that can potentially be maximized by optimizing herd management strategies. The length of a dairy cow’s life is affected by, and affects, all three pillars of sustainability. Longevity in dairy cows is multifactorial and strongly dependent on herd management. Despite genetic improvements, the average time of culling for Swedish cows has barely changed and is currently at 2.6 lactations. This culling rate requires a high number of replacement heifers, generating high rearing costs for farmers. This study evaluated different herd management strategies to improve cow longevity and assessed the effects on enteric methane (CH4) emissions from the herd and the profitability of milk production and beef production from the dairy cows and their offspring. The base scenario, an average Swedish Holstein herd of 100 cows, was compared with seven scenarios simulated using a stochastic herd simulation model (SimHerd). Two of these scenarios involved improved health and survival of cows in the herd, three involved improved reproduction, one considered the consequences of keeping all surplus heifers in the herd, and one considered maximizing the use of X-sorted dairy semen and inseminating the rest of the herd with unsorted beef semen, to avoid surplus replacement heifers. Improved fertility had the greatest effect in increasing the productive life per cow, to 3.8 years compared with 2.8 in the base scenario, allowed for more use of beef semen, reduced the number of replacement heifers, and generated the highest herd profit (€98 per cow-year higher than base scenario). Keeping all surplus heifers instead of producing beef × dairy cross calves decreased the number of productive years by 0.8 and reduced profit by €22 per cow-year. The profit was highly associated with costs related to replacement heifers. The highest beef output (3 369 kg per year more than base scenario) was achieved by keeping all heifers and culling a high share of dairy cows, but this scenario also generated much higher enteric CH4 emissions (+1 257 kg per year). Improving health, survival, or fertility reduced enteric CH4 emissions by 90–255 kg per year, while total yearly beef production ranged from 59 kg less to 556 kg more than in the base scenario. Reducing the number of replacement heifers needed by improving cow reproductive performance is thus key to increasing cow longevity and profitability, while reducing enteric CH4 emissions from the herd without compromising milk and meat production.
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.
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