Derivation of sustainable breeding goals for dairy cattle using selection index theory

The objective was to present 2 methods for the derivation of nonmarket values for functional traits in dairy cattle using deterministic simulation and selection index theory. A nonmarket value can be a value representing animal welfare and societal influences for animal production, which can be added to market economic values in the breeding goal to define sustainable breeding goals. The first method was restricted indices. A consequence of adding a nonmarket value to a market economic value for a given functional trait is less selection emphasis on milk yield. In the second method, the loss in selection response in milk resulting from greater emphasis on functional traits was quantified. The 2 methods were demonstrated using a breeding goal for dairy cattle with 4 traits (milk yield, mastitis resistance, conception rate, and stillbirth). Nonmarket values derived separately using restricted indices were 0.4 and 2.6 times the value of market economic values for mastitis resistance and conception rate, respectively. Nonmarket values for mastitis resistance and conception rate were both lower when derived simultaneously than when derived separately. This was due to the positive genetic correlation between mastitis resistance and conception rate, and because both traits are negatively correlated with milk yield. Using the second method and accepting a 5% loss in selection response for milk yield, nonmarket values for mastitis, conception rate, and stillbirth were 0.3, 1.4, and 2.9 times the market economic values. It was concluded that the 2 methods could be used to derive nonmarket values for functional traits in dairy cattle.     

A method to define breeding goals for sustainable dairy cattle production

The objective of this study was to present a method to define breeding goals for sustainable dairy cattle production by adding nonmarket values to market economic values for functional traits in the breeding goal. A nonmarket value can represent the value of improved animal welfare or societal influences for animal production. The nonmarket value for mastitis resistance, conception rate, and stillbirth were derived based on how much farmers or breeding companies were willing to lose in selection response for milk yield to improve functional traits. The desired response for milk yield corresponding to a given percent loss was obtained using desired gain indices. By allowing a 5% loss in the selection response for milk yield, the nonmarket value was found to be €40.4 for mastitis resistance, €16.1 for conception rate, and €−9.7 for stillbirth. The nonmarket value increased proportionally with increasing loss in the selection response for milk yield, but the selection response was lower for conception rate than for mastitis resistance because of differences in market economic value and heritability. To increase the response for conception rate, the nonmarket value was also derived for 2 situations, in which the desired responses for milk yield, mastitis resistance, and conception rate were specified. The method can be used to define breeding goals for sustainable production and to increase the response for traits that are at critically low levels. When defining breeding goals for sustainable production, breeding organizations should predict the selection response based on market economic value and add non-market value for traits with unacceptable selection responses.     

Strategies for implementing genomic selection for feed efficiency in dairy cattle breeding schemes

Alternative genomic selection and traditional BLUP breeding schemes were compared for the genetic improvement of feed efficiency in simulated Norwegian Red dairy cattle populations. The change in genetic gain over time and achievable selection accuracy were studied for milk yield and residual feed intake, as a measure of feed efficiency. When including feed efficiency in genomic BLUP schemes, it was possible to achieve high selection accuracies for genomic selection, and all genomic BLUP schemes gave better genetic gain for feed efficiency than BLUP using a pedigree relationship matrix. However, introducing a second trait in the breeding goal caused a reduction in the genetic gain for milk yield. When using contracted test herds with genotyped and feed efficiency recorded cows as a reference population, adding an additional 4,000 new heifers per year to the reference population gave accuracies that were comparable to a male reference population that used progeny testing with 250 daughters per sire. When the test herd consisted of 500 or 1,000 cows, lower genetic gain was found than using progeny test records to update the reference population. It was concluded that to improve difficult to record traits, the use of contracted test herds that had additional recording (e.g., measurements required to calculate feed efficiency) is a viable option, possibly through international collaborations.     

Economic basis for the Nordic Total Merit Index

Within a group of cooperating countries, all breeding animals are judged according to the same criteria if a joint breeding goal is applied in these countries. This makes it easier for dairy farmers to compare national and foreign elite bulls and may lead to more selection across borders. However, a joint breeding goal is only an advantage if the countries share the same production environment. In this study, we investigated whether the development of a joint breeding goal for each of the major dairy cattle breeds across Denmark, Finland, and Sweden would be an advantage compared with national breeding goals. For that purpose, economic values for all breeding goal traits in the 3 countries were derived, and estimated rank correlations between bulls selected for a national breeding goal and a joint breeding goal were compared. The economic values within country were derived by means of an objective bio-economic model, and the basic situation in each of the 3 production environments was based on an average dairy cattle herd with regard to production system, production level, and management strategy. The common Nordic economic values for each trait were calculated as the average of that specific trait in each of the 3 production environments. Balanced breeding goals were obtained in all situations because the derived economic values for traits related to health, fertility, milk production, and longevity were sizeable. For both Nordic Red Dairy Cattle and Nordic Holstein, the estimated rank correlations between bulls selected for a national breeding goal and a joint breeding goal were very high. Thus, a joint breeding goal within breed is feasible for Denmark, Finland, and Sweden.     

Development of a breeding program for improving the milk yield performance of Butana cattle under smallholder production conditions using a stochastic simulation approach

Butana is one of the local dairy cattle breeds of Sudan commonly kept by smallholder producers. This breed has been strongly promoted to advance the dairy production sector in the country. The main problem, however, is the lack of a systematic breeding program that involves smallholder producers. The aim of the current study was to identify the most promising design for a breeding program to improve the milk yield performance of Butana cattle under smallholder production conditions. In total, 3 breeding scenarios, including (1) the use of farm bulls, (2) the use of village bulls, and (3) the rotational use of village bulls within village groups, were simulated using a stochastic simulation approach. For each breeding scenario, 3 selection methods for bulls were considered, namely random mating, phenotypic selection, and selection based on estimated breeding value (EBV). The results showed that no genetic gain was realized with random mating in all breeding scenarios. In the farm bull breeding scenario, annual genetic gain (standard deviation units) ranged from 0.01 to 0.19 (phenotypic selection) and from 0.01 to 0.39 (selection based on EBV). In the village bull breeding scenarios, the annual genetic gain ranged from 0.01 to 0.21 (phenotypic selection) and 0.01 to 0.45 (selection based on EBV). The lowest genetic gain was realized for the rotational use of village bulls among villages within groups. Through the rotational use of village bulls, however, a higher genetic variance was maintained than in the farm and village bull breeding scenarios. We concluded that a village bull breeding program with selection based on EBV of young bulls was the most promising breeding design for achieving the breeding goal. Further studies are needed to assess the organizational feasibility of such a breeding program to ensure the participation of smallholder producers and its sustainability.     

Genomic-based genetic parameters for resilience across lactations in North American Holstein cattle based on variability in daily milk yield records

Considering the increasing challenges imposed by climate change and the need to improve animal welfare, breeding more resilient animals capable of better coping with environmental disturbances is of paramount importance. In dairy cattle, resilience can be evaluated by measuring the longitudinal occurrences of abnormal daily milk yield throughout lactation. Aiming to estimate genetic parameters for dairy cattle resilience, we collected 5,643,193 daily milk yield records on automatic milking systems (milking robots) and milking parlors across 21,350 lactations 1 to 3 of 11,787 North American Holstein cows. All cows were genotyped with 62,029 SNPs. After determining the best fitting models for each of the 3 lactations, daily milk yield residuals were used to derive 4 resilience indicators: weighted occurrence frequency of yield perturbations (wfPert), accumulated milk losses of yield perturbations (dPert), and log-transformed variance (LnVar) and lag-1 autocorrelation (r_auto) of daily yield residuals. The indicator LnVar presented the highest heritability estimates (±standard error), ranging from 0.13 ± 0.01 in lactation 1 to 0.15 ± 0.02 in lactation 2; the other 3 indicators had relatively lower heritabilities across the 3 lactations (0.01–0.06). Based on bivariate analyses of each resilience indicator across lactations, stronger genetic correlations were observed between lactations 2 and 3 (0.88–0.96) than between lactations 1 and 2 or 3 (0.34–0.88) for dPert, LnVar, and r_auto. For the pairwise comparisons of different resilience indicators within each lactation, dPert had the strongest genetic correlations with wfPert (0.64) and r_auto (0.53) in lactation 1, whereas the correlations in lactations 2 and 3 were more variable and showed relatively high standard errors. The genetic correlation results indicated that different resilience indicators across lactations might capture additional biological mechanisms and should be considered as different traits in genetic evaluations. We also observed favorable genetic correlations of these resilience indicators with longevity and Net Merit index, but further biological validation of these resilience indicators is needed. In conclusion, this study provided genetic parameter estimates for different resilience indicators derived from daily milk yields across the first 3 lactations in Holstein cattle, which will be useful when potentially incorporating these traits in dairy cattle breeding schemes.     

Preferences of European dairy stakeholders in breeding for resilient and efficient cattle: A best-worst scaling approach

Including resilience in the breeding objective of dairy cattle is gaining increasing attention, primarily as anticipated challenges to production systems, such as climate change, may make some perturbations more difficult to moderate at the farm level. Consequently, the underlying biological mechanisms by which resilience is achieved are likely to become an important part of the system itself, increasing value on the animal's ability to be unperturbed by variable production circumstances, or to quickly return to pre-perturbed levels of productivity and health. However, because the value of improving genetic traits to a system is usually based on known profit functions or bioeconomic models linked to current production conditions, it can be difficult to define longer-term value, especially under uncertain future production circumstances and where nonmonetary values may be progressively more important. We present the novel application of a discrete choice experiment, used to investigate potential antagonisms in the values of genetic improvements for 8 traits to dairy cattle system stakeholders in Europe when the production goal was either efficiency or resilience. A latent class model was used to identify heterogeneous preferences within each production goal, and postestimation was used to identify associations between these preferences and sociodemographic characteristics of respondents. Results suggested 3 distinct latent preference classes for each production goal. For the efficiency goal, yield and feed efficiency traits were generally highly valued, whereas for the resilience goal, health and robustness traits were generally highly valued. In both cases, these traits generally carried a low value in the other production scenario. Overall, in both scenarios, longevity was highly valued; however, the value of this trait in terms of resilience will depend on phenotyping across diverse environments to sufficiently capture performance under various anticipated system challenges. Additionally, results showed significant associations between membership of latent preference classes with education level and profession. In conclusion, as resilience becomes increasingly important, it is likely that a continued reliance on the short-term economic value of traits alone will lead decision makers to misrepresent the importance of some traits, including those with substantial contextual values in terms of resilience.     

Invited review: Phenotypes to genetically reduce greenhouse gas emissions in dairying

Phenotypes have been reviewed to select for lower-emitting animals in order to decrease the environmental footprint of dairy cattle products. This includes direct selection for breath measurements, as well as indirect selection via indicator traits such as feed intake, milk spectral data, and rumen microbial communities. Many of these traits are expensive or difficult to record, or both, but with genomic selection, inclusion of methane emission as a breeding goal trait is feasible, even with a limited number of registrations. At present, methane emission is not included among breeding goals for dairy cattle worldwide. There is no incentive to include enteric methane in breeding goals, although global warming and the release of greenhouse gases is a much-debated political topic. However, if selection for reduced methane emission became a reality, there would be limited consensus as to which phenotype to select for: methane in liters per day or grams per day, methane in liters per kilogram of energy-corrected milk or dry matter intake, or a residual methane phenotype, where methane production is corrected for milk production and the weight of the cow. We have reviewed the advantages and disadvantages of these traits, and discuss the methods for selection and consequences for these phenotypes.     

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.     

Economic values of production and functional traits,including residual feed intake,in Finnish milk production

Improving the feed efficiency of dairy cattle has a substantial effect on the economic efficiency and on the reduction of harmful environmental effects of dairy production through lower feeding costs and emissions from dairy farming. To assess the economic importance of feed efficiency in the breeding goal for dairy cattle, the economic values for the current breeding goal traits and the additional feed efficiency traits for Finnish Ayrshire cattle under production circumstances in 2011 were determined. The derivation of economic values was based on a bioeconomic model in which the profit of the production system was calculated, using the generated steady state herd structure. Considering beef production from dairy farms, 2 marketing strategies for surplus calves were investigated: (A) surplus calves were sold at a young age and (B) surplus calves were fattened on dairy farms. Both marketing strategies were unprofitable when subsidies were not included in the revenues. When subsidies were taken into account, a positive profitability was observed in both marketing strategies. The marginal economic values for residual feed intake (RFI) of breeding heifers and cows were −25.5 and −55.8 €/kg of dry matter per day per cow and year, respectively. The marginal economic value for RFI of animals in fattening was −29.5 €/kg of dry matter per day per cow and year. To compare the economic importance among traits, the standardized economic weight of each trait was calculated as the product of the marginal economic value and the genetic standard deviation; the standardized economic weight expressed as a percentage of the sum of all standardized economic weights was called relative economic weight. When not accounting for subsidies, the highest relative economic weight was found for 305-d milk yield (34% in strategy A and 29% in strategy B), which was followed by protein percentage (13% in strategy A and 11% in strategy B). The third most important traits were calving interval (9%) and mature weight of cows (11%) in strategy A and B, respectively. The sums of the relative economic weights over categories for RFI were 6 and 7% in strategy A and B, respectively. Under production conditions in 2011, the relative economic weights for the studied feed efficiency traits were low. However, it is possible that the relative importance of feed efficiency traits in the breeding goal will increase in the future due to increasing requirements to mitigate the environmental impact of milk production.     

Combining selection for carcass quality, body weight, and milk traits in dairy cattle

Alternative selection strategies were evaluated for breeding for carcass quality, body weight, and milk traits in dairy cattle. The efficiency of different alternatives was evaluated by comparing predicted genetic responses in individual traits as well as in the aggregate genotype. Particular interest was paid to the loss of response with indices that partially or totally ignored genetic correlations between traits, reflecting selection on single-trait evaluations. Simplified indices gave almost the same total response as a full multiple-trait index, but relative responses in carcass and milk traits differed between indices. Also studied were the consequences of restricting increase in body weight of dairy cows, while selecting for carcass and milk production traits. Restriction of body weight of cows resulted in considerable loss of predicted total response.     

Genetic parameters for body condition score and its relationship with type and production traits in Swiss Holsteins

The objectives of this study were to estimate the genetic and environmental parameters between body condition score (BCS) and 27 conformation and 3 production traits in Swiss Holstein cattle. The dataset consisted of 31,500 first-lactation cows, which were daughters of 545 sires in 1867 herds. Bivariate sire models with relationships among sires were used to estimate parameters. Least squares means for BCS by lactation stage show that cows lose BCS up to 5 mo after calving and gain BCS prior to the next calving. Regression models showed that an increase in age and percentage of Holstein genes results in an increase and decrease in BCS, respectively. Heritability (h2) was 0.24 for BCS score, which indicates good potential for selection. Sire estimated breeding values for BCS ranged from -0.46 to +0.51 units. Heritabilities ranged from 0.08 (heel depth) to 0.46 (rump width) for type traits and 0.23 to 0.29 for yield traits. Genetic correlations of BCS with 8 conformation traits were significant; stature (0.28), heart girth (0.21), strength (0.17), loin (-0.39), body capacity (0.19), dairy character (-0.35), udder quality (-0.42), and teat position rear (-0.33). Milk production and body condition have an unfavorable genetic correlation (-0.12 to -0.17). These results show that selection for good body condition, body conformation, and optimal milk production is possible and their genetic associations reported here will be useful for designing Swiss breeding goals.     

Consequences of selection for yield traits on calving ease performance

The impact of different breeding goals on the genetic response for calving ease (CE) and yield traits was studied in the Basque Holstein cattle population. The economic value for CE was estimated with a bioeconomic model, using Basque production and market circumstances and taking into account the categorical nature of CE. The economic value for CE was −€18.03/cow per calving interval per liability unit. This value was relatively insensitive to changes in the market price of animals but was more sensitive to changes in the incidence of dystocia. Records from parities between 1995 and 2002 were used for the estimation of genetic parameters for yield (actual milk, fat, and protein yield) and CE using a multivariate model. Linear sire models for yield traits and a threshold sire-maternal grandsire model for CE were used. A Holstein population was simulated to determine the consequences of including CE in the breeding goal. Three selection strategies were considered: 1) selection only on yield traits, 2) selection on yield and direct CE (DCE), and 3) selection on yield, DCE, and maternal CE (MCE). Selection on yield traits only resulted in a slight reduction of dystocia. Selection strategies in which DCE or DCE and MCE were included in the breeding goal did not improve the genetic response for DCE and MCE obtained with the first selection strategy. Genetic responses were also calculated using the 2.5th, 50th, and 97.5th percentiles of posterior densities of genetic correlations between DCE and MCE and yield traits. Because responses in CE were sensitive to deviations in estimates of genetic parameters, the inclusion of CE in the monitoring scheme is recommended. Genetic evaluation of bulls for CE is of considerable value because it provides farmers with the opportunity to use assortative matings of sires with favorable estimated breeding values for DCE to primiparous cows.     

The genetic relationship between calving interval, body condition score and linear type and management traits in registered Holsteins

The trend to poorer fertility in dairy cattle with rising genetic merit for production over the last decade suggests that breeding goals need to be broadened to include fertility. This requires reliable estimates of genetic (co)variances for fertility and other traits of economic importance. In the United Kingdom at present, reliable information on calving dates and hence calving intervals are available for most dairy cows. Data in this study consisted of 44,672 records from first lactation heifers on condition score, linear type score, and management traits in addition to 19,042 calving interval records. Animal model REML was used to estimate (co)variance components. Genetic correlations of body condition score (BCS) and angularity with calving interval were -0.40 and 0.47, respectively, thus cows that are thinner and more angular have longer calving intervals. Genetic correlations between calving interval and milk, fat, and protein yields were between 0.56 and 0.61. Records of phenotypic calving interval were regressed on sire breeding values for BCS estimated from records taken at different months of lactation and breeding values for BCS change. Genetic correlations inferred from these regressions showed that BCS recorded 1 mo after calving had the largest genetic correlation with calving interval in first lactation cows. It may be possible to combine information on calving interval, BCS, and angularity into an index to predict genetic merit for fertility.     

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.     

Simulating consequences of choosing a breeding goal for organic dairy production

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.     

Genetic parameters for rectal temperature,respiration rate,and drooling score in Holstein cattle and their relationships with various fertility,production, body conformation,and health traits

Genetic selection for improved climatic resilience is paramount to increase the long-term sustainability of high-producing dairy cattle, especially in face of climate change. Various physiological indicators, such as rectal temperature (RT), respiration rate score (RR), and drooling score (DS), can be used to genetically identify animals with more effective coping mechanisms in response to heat stress events. In this study, we investigated genetic parameters for RT, RR (score from 1–3), and DS (score from 1–3). Furthermore, we assessed the genetic relationship among these indicators and other economically important traits for the dairy cattle industry. After data editing, 59,265 (RT), 30,290 (RR), and 30,421 (DS) records from 13,592 lactating Holstein cows were used for the analyses. Variance components were estimated based on a multiple-trait repeatability animal model. The heritability ± standard error estimate for RT, RR, and DS was 0.06 ± 0.01, 0.04 ± 0.01, and 0.02 ± 0.01, respectively, whereas their repeatability was 0.19, 0.14, and 0.14, respectively. Moderate genetic correlations of RR with RT and DS (0.26 ± 0.11 and 0.25 ± 0.16) and nonsignificant correlation between RT and DS (?0.11 ± 0.14) were observed. Furthermore, the approximate genetic correlations between RT, RR, and DS with 12 production, 29 conformation, 5 fertility and reproduction, 5 health, and 9 longevity-indicator traits were assessed. In general, the approximate genetic correlations calculated were low to moderate. In summary, 3 physiological indicators of heat stress response were measured in a large number of animals and shown to be lowly heritable. There is a value in developing a selection index including all the 3 indicators to improve heat tolerance in dairy cattle. All the unfavorable genetic relationships observed between heat tolerance and other economically important traits can be accounted for in a selection index to enable improved climatic resilience while also maintaining or increasing productivity in Holstein cattle.     

A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle

Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.     

Economic evaluation of the breeding goal for Norwegian Red dairy cattle

In this paper, a translog profit function was applied to estimate the economic values of the traits included in the breeding goal for Norwegian Red dairy cattle. The following 10 traits are included in the breeding goal: milk, meat, mastitis resistance, fertility, calving difficulties, stillbirths, other diseases, udder, temperament, and legs. An empirical implementation that locally approximates the unknown true profit function was suggested and estimated, taking farm heterogeneity into account. The model was applied to a panel data set of 3,259 Norwegian dairy farms over the period 1999 to 2003. Panel data, also called longitudinal or cross-sectional time-series data, are multiple cases (cows, farms, countries, etc.) observed over 2 or more time periods. The data set consisted of farm-level data, including production and economic data from the farm and the estimated breeding values for each cow's sire. The estimated economic values make it possible to test whether genetic selection has been profitable for the farmer, and the extent to which the currently used economic values were optimal during the period 1999 to 2003. Although the translog profit function is quite flexible, it is rather complex, and a simplified version of the model, a Cobb-Douglas profit function, was also estimated. However, the hypothesis that this simpler function adequately describes the data compared with the full translog model was rejected. Further, the hypothesis that the estimated breeding values are profit neutral was rejected (i.e., the hypothesis that there are no interactions between input and output prices on one hand and estimated breeding values on the other). These results indicated that selection not only leads to a parallel shift in profits, but also to changes in input use. Seven of the 10 traits had a significant effect on the farmers’ profit. The 3 traits that were not significant were calving difficulty, stillbirth, and other diseases. The results showed that the breeding program for Norwegian Red cattle has been fairly successful in improving farmers’ profits. However, a slight modification of the breeding goal, such as a reduction in the weights for stillbirths and other diseases and an increase in the weights for meat and temperament, would increase farm profits.     

Selection for profit in cattle: I. Economic weights for purebred dairy cattle in the Czech Republic

A bioeconomic model for dairy cattle production was used to estimate economic values of 18 traits for dairy sires in purebred Holstein and Czech Fleckvieh populations. Economic values were defined as partial derivatives of the profit function with respect to each trait in a closed production system with dairy cow herds and integrated fattening of bulls. All revenues and costs associated with cows calving in the herds within one year and with their progeny were discounted at 5% per annum back to the date of calving. Calculations were carried out for the situation in the Czech Republic in 2005 (scenario 1: market quotas for milk yield and fat percentage) and for the expected situation in 2015 (scenario 2: free market). The relative economic importance of each trait was expressed as a ratio of the standardized economic value of that trait (its marginal economic value multiplied by its genetic standard deviation) to the standardized economic value of 305-d milk yield, with average fat and protein percentages. In addition to milk yield, somatic cell score was the second most important trait, achieving 32% to 43% of the value for milk yield in both scenarios. The relative importance of milk components differed notably between scenarios. The relative importance was approximately zero for protein and from −14 to −23% for fat percentage in scenario 1, but changed to 38% for protein and 27 to 31% for fat percentage in scenario 2. In both scenarios and for both breeds, the relative economic values for somatic cell score and length of productive life of cows were similar to those for fat and protein percentages in scenario 2. The smallest relative economic values (less than 4% of the relative importance of milk yield) were for birth weight, conception rate of heifers, and carcass traits. In conclusion, relative emphasis among traits in the breeding objective for Czech dairy cattle should be reassessed according to the expected situation after shifting to a free market economy in 2015.