Total Merit Research Articles

Multiple-trait breeding values for parental selection in self-pollinating crops

Using breeding values in parental selection of self-pollinating crops seems to be superior to conventional selection strategies, where selection is often based on several traits which are correlated among each other. However, analysing each trait separately can bias estimates of breeding values. This study examined responses to selection for total merit indices based on breeding values resulting from single- and multiple-trait best linear unbiased prediction (BLUP). We generated data for a multi-environment trial of a "virtual" parental population in which the phenotypic value of inbred lines was influenced by additive, additive-by-additive epistatic, year, location, block and genotype-by-environment interaction effects. Two traits with heritabilities of 0.7 and 0.3 and nine different correlation scenarios between traits (estimated phenotypic correlation ranging from -0.39 to +0.36) were simulated. Gain in selection response was greater for multiple-trait than for single-trait breeding values, especially if traits were negatively correlated. For all correlation scenarios, the overall standard errors of difference of multiple-trait predictors were lower than those of single-trait analysis.

Proposed economic selection indices for the Simmentaler breed in South Africa

The development of economic selection indices for an integrated Simmentaler production system was described. The breeding objective was defined in terms of production-, functional- and product quality traits. Criteria included in the total index were birth- and weaning weight (direct and maternal), final weight, mature cow weight, days-to-calving, backfat thickness, tenderness and marbling. The total merit index was termed as IT = – 1.60 BWD – 1.95 BWM + 2.23 WWD + 1.75 WWM – 0.54 FW – 2.01 MCW – 13.21 CD + 4.97 BF – 2.36 T + 12.66 M. The correlation between this index and the aggregate breeding objective was 0.988. The economic superiority of the progeny from the top 40% of animals selected on their ranking in the total index, relative to the average progeny, is expected to be R 119.51. South African Journal of Animal Science Vol. 37 (2) 2007: pp. 122-131

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication)

In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends

In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.

A Stochastic Simulation Study on Validation of an Approximate Multitrait Model Using Preadjusted Data for Prediction of Breeding Values

Three different models for prediction of breeding values were compared in a stochastic simulation study of a dairy cattle population of 100,000 cows. The simulation was done in 2 steps. The first step involved 15 yr of selection using breeding values obtained in a univariate model for production and a trivariate model for mastitis occurrence, udder depth, and somatic cell score, in which production and mastitis occurrence were included in the breeding goal. This was done to create an initial population that had already been under selection. The second step consisted of 20 replicates of 4 different scenarios set up to make it possible to compare the different models. Two scenarios were based on univariate evaluations and one for udder health traits on trivariate evaluations, with 2 different breeding goals. In another scenario, an approximate multitrait model using preadjusted data in a 2-step procedure was used and in the last scenario, a complete linear multitrait model was carried out. Differences in genetic response in total merit over the last 15 yr of selection were compared and used to rank the models. The linear multitrait model gave the highest regression coefficient of true genetic values on year (3.073±0.069 in economic units), and this was significantly better than for the approximate multitrait model (2.819±0.047), which again was significantly better than for the univariate approach (2.672±0.060). The linear multitrait model cannot be applied to nearly the same number of traits as the approximate model. Therefore, the approximate model with developments handling breeding values from more complex models than presented in this paper is an option of choice in countries providing total merit indices that combine many traits because it does not neglect correlations between these traits.

Application of Controlling Instruments for Improvements in Cow Sire Selection

National estimated breeding values of bulls from 1998 through 2006 from 12 different German artificial insemination (AI) organizations were used to determine the differences in expected and realized selection intensities for cow sire selection, considering the total merit index as well as subindexes for production, conformation, somatic cell count, fertility, and functional herd life. The expected selection intensity was derived from a Gaussian distribution and from the replacement rate describing the percentage of bulls graduated as cow sires from the total amount of progeny-tested young bulls within the AI organization and by birth year. Realized selection intensities for all indexes were derived from the selection differential of cow sires, defined as the deviation of the average index of selected cow sires from the average index of the total number of progeny-tested young bulls. A low replacement rate of cow sires was associated with relatively high realized selection intensities for the total merit, production, and conformation indexes, but was not related to the somatic cell count, fertility, and functional herd life indexes. The controlling value, defined as the ratio of realized to expected selection intensities, indicates the effectiveness of cow sire selection for different traits. Low controlling values (i.e., low realized selection intensities in combination with moderate or high expected selection intensities) suggest improvements in the step of cow sire selection, especially when discussing the total merit index. Analysis of variance revealed significant differences in expected selection intensities, realized selection intensities, and controlling values for the total merit, production, and conformation indexes between AI organizations and birth years of bulls. Artificial insemination organizations applying well-defined breeding policies (e.g., high controlling values for the total merit index) were successful in the national competition when evaluated according to the national top lists for the respective indexes, regardless of the active population size. The suggested method also allows for comparison of the importance of different indexes in selection decisions. Furthermore, controlling values can monitor additional potential in the improvement of cow sire selection with respect to improvement of the genetic level in the whole population. The development of appropriate selection tools or controlling instruments is of increasing concern for monitoring selection policies in the short term as well as for establishing sustainable breeding policies.

Derivation of economic values for dairy cattle in Iran and comparison to other countries

Index selection is the most effective selection strategy to improve total merit. Index selection requires the economic values (EVs) of the traits in the breeding goal and the genetic parameters of the traits in the breeding goal and in the index (Hazel and Lush, 1942). According to this theory, in most countries a national selection index has been developed for dairy cattle (Miglior et al., 2005). In Iran a national selection index has not yet been developed. The first objective of this study was, therefore, to estimate economic values for production traits (milk, fat and protein yield) and longevity for Holsteins in Iran. The second objective was to compare the proposed Iranian selection index with selection indices of other countries in the world.

A Total Merit Selection Index for Ontario Organic Dairy Farmers

Organic standards require changes in management practices so that health, fertility, and overall fitness are more important than on conventional dairy farms and require different selection objectives. A survey involving 18 (40%) Ontario organic dairy farms was carried out to collect data on their production systems, breeding policies, and concerns. Compared with conventional farms, organic farms had lower milk production, lower replacement rate, higher somatic cell count, and a much higher rate of crossbreeding. Actual culling rate was 21%, and the main causes were fertility, mastitis, feet and legs, production, and old age. The major areas of concern expressed by organic dairy farmers were related to grazing traits, fertility, health, and longevity. An organic total merit index was developed based on the subjective scores for traits with a genetic evaluation in Canada. The relative weights of production to fitness traits (28:72) were substantially different from those in the Canadian Lifetime Profit Index (54:46), but similar to those used in conventional indices in Sweden and Denmark and in the Swiss organic index. The overall weight on health traits was 2.5 times higher in the organic index and, among fitness traits, the emphasis was substantially higher for lactation persistency, somatic cell score, and body capacity. Correlations between the organic index and Lifetime Profit Index were 0.88 for all bulls proven in Canada, 0.70 for the top 1,000, and 0.65 for the top 100, indicating that a different group of bulls would rank at the top of these 2 indices. When the top 100 bulls for either index were compared, those selected for the organic index were about 0.5 standard deviations lower for all yield traits, but were much better for body capacity and somatic cell score, and 0.25 standard deviations higher for herd life, feet and legs, udder conformation, and lactation persistency. Given the small population size, a separate breeding program for an organic management system is not viable in the foreseeable future. However, the organic index would allow producers to rank proven bulls in accordance with their perceived needs.

A stochastic simulation study on using different models for prediction of breeding values while changing the breeding goal

In a stochastic simulation study the effect of simultaneously changing the model for prediction of breeding values and changing the breeding goal was studied. A population of 100 000 cows with registrations on seven traits was simulated in two steps. In the first step of 15 years the population was selected for production and mastitis occurrence using a univariate model for prediction of breeding values for production and a trivariate model using information on mastitis treatments, udder depth and somatic cell score for prediction of breeding values for mastitis occurrence. In the second step six different scenarios were set up and simulated for 15 years combining two different breeding goals and three different models for prediction of breeding values in 20 replicates. Breeding goal 1 had relative economic value per genetic standard deviation on production (19.4) and mastitis occurrence ( − 50) whereas breeding goal 2 had a economic value on production (19.4), udder depth (4.2), mastitis occurrence ( − 50), non return rate (13.0) and days open ( − 16.75). Model 1 was a model similar to the one used in the first 15 years. Model 2 was an approximate multitrait model where solutions for fixed effects from a model corresponding to model 1 were subtracted from the phenotypes and a multitrait model with an overall mean, a year effect, an additive genetic and a residual effect were applied. Model 3 was a full multitrait model. Average genetic trends for total merit and each individual trait over 20 replicates were compared for each scenario. With the number of replicates the genetic responses using model 2 and 3 were not significant different. With a broad breeding goal using, model 2 or model 3 gave a significantly higher response in total merit than using model 1. Using a narrow breeding goal there was no significant difference between models used for prediction of breeding values. Results showed that with a breeding goal with a lot of emphasis on low heritable traits with a high economic value using a multitrait methodology for prediction of breeding values will redistribute the genetic progress in the total merit index. More gain will come from the low heritable traits in the breeding goal and less from traits with higher heritability. With a broad breeding goal and exploiting the available information in the data the inbreeding coefficient increased though not significantly.

Selection for Female Fertility Using Censored Fertility Traits and Investigation of the Relationship with Milk Production

Bivariate models (censored linear-linear and censored threshold-linear) were used to estimate genetic parameters for production and fertility traits in the Spanish Holstein population. Records on 71,217 lactations from 41,515 cows were used: 30 and 36% of lactations were censored for days open (DO) and number of inseminations to conception (INS), respectively. Heritability estimates for production traits (milk, fat, protein) ranged between 0.18 and 0.25. Heritability of days to first service (DFS) and DO was 0.05; heritability of INS on the liability scale was 0.04. Genetic correlations between fertility traits were 0.41, 0.71, and 0.87 for DFS–INS, DO–INS, and DO–DFS, respectively. Days open had a larger genetic correlation (ranging from 0.63 to 0.76) with production traits than did DFS (0.47 to 0.59) or INS (0.16 to 0.23). Greater antagonism between production and DO may be due to voluntary management decisions for high-yielding cows, resulting in longer lactation lengths. Inseminations to conception appeared to be less correlated with milk production than were the other 2 female fertility traits. Including INS in a total merit index would be expected to increase genetic gain in terms of profit, but profit would decrease if either DO or DO and DFS were included in the index. Thus, INS is the trait to be preferred when selecting for female fertility. The genetic correlation between actual milk yield and 305-d standardized milk yield was 0.96 in the present study, suggesting that some reranking of sires could occur. Because the target of attaining a 12-mo calving interval, as implied by a 305-d standardized lactation length, is changing in the dairy industry, routine genetic evaluation of actual total lactation milk yield should be considered.

Experiences in selecting on a total merit index in the Austrian fleckvieh breed

Spotted cattle breed is the most common breed in Austria. Austrian Spotted cattle breed is bred as a dual purpose breed for more than 100 years. The breeding objective has changed over the time according to the different economic importance of the traits and according to the different possibilities in using estimated breeding values (EBVs) for selection. Since 1998 the breeding objective is defined as the aggregate genotype of production traits and functional traits. All economically important traits are combined according to their economic weights in the total merit index (TMI). The TMI is calculated by combining the EBVs of all traits using a selection index procedure. The index weights (b-values) are estimated depending on the reliabilities of the EBVs and are therefore different from animal to animal. Considering the intensive international exchange of semen from the best bulls, the cooperation in the breeding programs and the similar economic situation in agriculture the breeding organizations of Germany and Austria decided to make a joint across-country evaluation for all traits. Since November 2002 breeding values for all traits and as a logical conclusion the TMI are evaluated jointly. The result is a high acceptance of the EBVs and the TMI by the farmers because of smaller changes of the breeding values for national and foreign bulls between consecutive evaluations. The realized economic gain in the different traits is very close to the expected economic gain. In the last 10 years on average 88.2 % of the economic gain were realized in the milk traits, 4.2 % in the beef traits and 7.6 % were realized in the fitness traits.

An iterative procedure for deriving selection indexes with constant restrictions1

The objective of this study was to present an iterative procedure for deriving selection indexes with constant restrictions. Constant restriction means that the genetic responses of the restricted traits are preset to actual amounts for a given selection intensity (ī). Results of this study show that an index with constant restriction alone or in combination with other types of restrictions possesses three distinctive characteristics: 1) the coefficient matrix of the index equations is not symmetric and is nonlinear; 2) the coefficient matrix contains unknown ī, indicating that the index coefficients (b) to be derived depends on the value of ī predetermined before selection; and 3) the coefficient matrix contains unknown b, thus requiring iterative methods to solve the index equations. As a result of these unique characteristics, the index coefficients, genetic responses of the index traits, and overall genetic gain in net merit change nonlinearly with varying levels of ī, which is in sharp contrast to both unrestricted and restricted indexes reported in the literature. The construction of a constant-restricted index requires predetermining the value of ī intended for a selection program to derive the corresponding b. An index with constant restrictions has no meaning unless it is associated with a specific value of ī. Numerical examples are given to illustrate the construction of the index with constant restrictions and to validate the theoretical development proposed. The derived equations have yielded an index that maximized the total merit and fulfilled constant restriction at the same time.

Heritabilities, Genetic Correlations, and Genetic Change for Female Fertility and Protein Yield in Norwegian Dairy Cattle

Data from 1,815,581 first insemination records from daughters of 2697 Norwegian Dairy Cattle (NRF) sires were analyzed. A multitrait model was used to estimate genetic parameters and genetic change for 56-d nonreturn rate in virgin heifers (NR56D0), for 56-d nonreturn rate in first lactation cows (NR56D1L), for interval from calving to first insemination (CFI1L), and for protein yield (PY3051L). The heritabilities for NR56D0, NR56D1L, CFI1L, and PY3051L were 1.08, 0.99, 3.01, and 20.80%, respectively. Genetic correlation between heifer and cow fertility was high and favorable between NR56D0 and NR56D1L (0.54) and moderate and unfavorable between NR56D0 and CFI1L (0.24). The genetic correlations between NR56D1L and CFI1L and between NR56D0 and PY3051L were 0.08 and 0.04, respectively. A small, unfavorable genetic correlation between NR56D1L and PY3051L (−0.18) was found, while the genetic correlation between PY3051L and CFI1L was strongly unfavorable (0.47). Since 1972, NRF sires have been selected for NR56D0 using breeding values estimated from large progeny groups and with considerable weight in the total merit index. A linear regression analysis of sire PTA on year of first insemination of daughters showed an annual genetic change of 0.14% units for NR56D0. Selection was able to stabilize the genetic change of NR56D1L (0.03%/yr) but an undesirable change for CFI1L (0.11 d/yr) was found. The change of sire PTA for PY3051L was 0.63 kg/yr.

Genetic Relationship between Ultrasonic and Carcass Measurements for Meat Qualities in Korean Steers

Real time ultrasonic measurements for 13th rib fat thickness (LBF), longissimus muscle area (LEMA) and marbling score (LMS) of live animal at pre-harvest and subsequent carcass measurements for fat thickness (BF), longissimus muscle area (EMA), marbling score (MS) as well as body weight of live animal, carcass weight (CW), dressing percentage (DP), and total merit index (TMI) on 755 Korean beef steers were analyzed to estimate genetic parameters. Data were analyzed using multivariate animal models with an EM-REML algorithm. Models included fixed effects for year-season of birth, location of birth, test station, age of dam, linear and quadratic covariates for age or body weight at slaughter and random animal and residual effects. The heritability estimates for LEMA, LBF and LMS on RTU scans were 0.17, 0.41 and 0.55 in the age-adjusted model (Model 1) and 0.20, 0.52 and 0.55 in the weight-adjusted model (Model 2), respectively. The Heritability estimates for subsequent traits on carcass measures were 0.20, 0.38 and 0.54 in Model 1 and 0.23, 0.46 and 0.55 in Model 2, respectively. Genetic correlation estimate between LEMA and EMA was 0.81 and 0.79 in Model 1 and Model 2, respectively. Genetic correlation estimate between LBF and BF were high as 0.97 in Model 1 and 0.98 in Model 2. Real time ultrasonic marbling score were highly genetically correlated to carcass MS of 0.89 in Model 1 and 0.92 in Model 2. These results indicate that RTU scans would be alterative to carcass measurement for genetic evaluation of meat quality in a designed progeny-testing program in Korean beef cattle.

Heifer Fertility in Norwegian Dairy Cattle: Variance Components and Genetic Change

Variance components and genetic change were estimated for 56-d nonreturn rate in virgin heifers using first insemination records of a total of 1,632,961 Norwegian Dairy Cattle daughters of 2945 sires. Six univariate mixed linear sire models were compared. The heritabilities varied from 1.2% to 1.4%. All models gave favorable, although different, estimates of genetic change of 56-d nonreturn rate. The method used to validate the genetic trend did not detect bias in any of the models. Goodness-of-fit and predictive ability were used to further validate the models. Three models included service sire, but this effect had little influence on the results. Models treating the herd-year effects as random showed smaller prediction error and higher correlation between observed and predicted values than the models treating herd-year effect as fixed. To avoid confounding of environmental and genetic effects, the model including fixed effect of month-year was preferred over a model with only month of first insemination to estimate the genetic change. Female fertility has been successfully included in the total merit index of Norwegian Dairy Cattle for 20 yr. This has resulted in genetic improvement and the chosen model showed annual genetic change of 0.04% for 56-d nonreturn rate in heifers between 1979 and 2000.

Experiences of including reproduction and health traits in Scandinavian dairy cattle breeding programmes

Reproduction and health traits are of significant economic importance for dairy production. Most of these traits are expressed in a categorical way and show heritabilities of 5% or less. Nevertheless, their additive genetic variation is considerable. For example, the incidence of clinical mastitis in the first lactation varies among daughter groups of Swedish Holstein bulls between 10 and 26%, stillbirth rate at first parity between 3 and 16%, and the number of inseminations per serviced cow between 1.6 and 1.9. Unfavourable genetic correlations of the order of 0.2–0.4 between production on one side, and mastitis and female fertility on the other, have generally been found. Well integrated recording schemes in the Scandinavian countries enabled early the adoption of total merit indexes (TMI), including reproduction and health traits, into their selection schemes. In practice, TMI selection has proven to be effective in maintaining functional efficiency of the cows simultaneously with a sharp increase in production. As bull selection nowadays takes place globally, sustainable breeding programmes require more extensive recording and genetic evaluations of reproduction and health traits internationally, a development that presently grows quickly. The Scandinavian experiences are reviewed in this paper in the light of this international development.

Optimization of a specialized beef breeding program with a crossbreeding component

Abstract. A complex deterministic approach (ZPLAN) was used to optimize the breeding programs for beef breeds. For the model population 1,000 beef cows and 60,000 dual purpose Simmental cows for crossbreeding were assumed. The percentage of AI was 25% within the beef breed and 93% within the Simmental cows. Domestic AI beef bulls were used for crossbreeding only. The total merit index included beef traits (birth weight, 200-day-weight direct and maternal, 365-day-weight, daily gain, dressing percentage, EUROP grading score) and functional traits (calving ease, stillbirth, fertility and functional longevity). The proportion of foreign proven and domestic AI bulls was varied as well as the number of bulls tested on stations and on contract farms. Annual monetary genetic gain and discounted profit were used to evaluate alternative breeding strategies. Extending the number of bulls tested on stations and establishing performance testing of natural service bulls on contract farms increased the annual monetary genetic gain and the discounted profit, especially when domestic AI bulls were also used in the beef cattle breeding population.

Age at puberty, cyclicity, clinical response to PGF2α, hCG and GnRH and embryo recovery rate in yearling mares

This study investigated some aspects of breeding management in the Italian Heavy Draught Horse breed, aiming at improving its efficiency at stud farm level. A first aim was to evaluate the risk of unsuccessful reproduction in mares after an early (3 years) or normal (4 years) age at first foaling, in interaction with different stud rearing systems. A second objective was the examination of the mean time length in which young 2-year-old stallions maintain a genetic superiority on older proven stallions, identifying a ‘genetic lifespan’ in which young stallions can be safely used for reducing the cost of services. Reproductive performance at first and second foaling of 1513 mares were used. Mares had a normal first foal at 3 (n = 745) or 4 years of age (n = 768) in stud farms on the basis of stable (n = 488), feral (n = 345) or semi-feral (n = 680) rearing systems. Logistic regression analysis was performed by modeling the risk of unsuccessful reproduction in the subsequent season (i.e., results at second foaling), as affected by the interaction of age at first foaling × rearing system (six classes). Genetic lifespan of young stallions was estimated by regressing the least square means from a mixed model analysis for repeated measures of individual differences in ‘total merit’ estimated breeding values (EBVs) between young stallions (mean no. of 45/year) and the mean EBV of all proven stallions in a given year of genetic evaluation (mean no. of 483/year). Young stallions born between 1999 and 2005 were used, following each generation (i.e., birth year) from 2 to 7 subsequent yearly genetic evaluations. In comparison with the best reproductive success of second foaling at 4 years in stable systems, the greatest risk of unsuccessful reproduction was at 3 years in feral (+167%) and 3 years in semi-feral conditions (+91%). Young stallions showed a 0.50 s.d. greater EBV at the first evaluation than proven stallions, with a mean annual decrease in EBV of 0.07 s.d./year on proven stallions. Optimal breeding management could be obtained in stud farms by limiting foaling at 3 years, particularly in feral and semi-feral rearing systems, and using young stallions for 3 to 4 years to maintain a perceptible selection differential with older proven stallions and to reduce cost of services. Later, the selection differential with proven stallions become less consistent and genetic improvement could be slowed down.

Optimization of progeny testing schemes when functional traits play an important role in the total merit index

The inclusion of functional traits in a total merit index is expected to have some consequences on the design of progeny testing schemes in dairy cattle. Due to the usually low heritabilities of functional traits more daughter records per sire seem to be necessary to improve the accuracy of the breeding values of these traits. A complex deterministic approach was used to optimize the design of progeny testing schemes for Austrian Simmental and Brown Swiss cattle. The total merit index for Simmental included dairy traits (fat and protein yield), beef traits (daily gain, dressing percentage, EUROP grading score) and functional traits (functional longevity, persistency, fertility, calving ease, stillbirth and somatic cell count); the Brown Swiss total merit index consisted of dairy and functional traits only. The proportion of recorded cows mated with test bulls (test capacity) and the number of test bulls were varied. Annual monetary genetic gain and discounted profit were used to evaluate the different progeny testing schemes. The inclusion of functional traits in a total merit index has a positive effect on the annual monetary genetic gain. The annual genetic gains of functional traits are either positive or at least the negative trend can be reduced. Extending the number of daughter records per test bull from 60 (current situation) up to around 100 leads to a small increase of annual monetary genetic gain for Simmental, whereas no positive effect can be found for Brown Swiss. Discounted profit can be considerably improved, especially for Brown Swiss.

Ecological total merit index for an Austrian dual purpose cattle breed

Abstract. Organic farming plays a considerable role in Austrian agriculture. Therefore it seems to be worthwhile to make suggestions about a more ecological breeding goal for cattle breeds. Because of the fact that Simmental is the most frequent dual purpose cattle breed in Austria, this breed is chosen to show the impact of selection under an ecological total merit index. With model calculations the effect on selection response in milk production beef production and functional traits under selection with the current economic total merit index and more ecological index variants, e.g. with higher economic values for fitness and functional traits, is shown. As a basis for future decisions the efficiency of more or less ecological indices is compared. The results indicate that an increase of the current economic values of functional traits of about 50 percent does not present a great risk, expected selection responses for milk production traits are still high.