Annual Monetary Genetic Gain Research Articles

Genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies

Both small dairy cattle populations and dairy cattle populations with a low level of linkage disequilibrium (LD) suffer from low reliability of genomic prediction. In this study, we investigated whether adding more genotyped cows to the reference population influences the rate of genetic gain and rate of inbreeding by affecting the reliability. A standard breeding program with a large reference population and high LD, which mimicked a breeding program for Danish Holstein population, was simulated as a reference. A Danish Jersey population with a small reference population and high LD and a Red Dairy Cattle population with a large reference population and low LD were also simulated. Two additional breeding programs were simulated for Danish Jersey and Red Dairy Cattle populations, where 2,000 additional genotyped cows were included in the population for genomic selection. All 5 simulated breeding programs were initiated by a founder population to generate LD resembling the real LD pattern, followed by a 20-yr conventional progeny-testing scheme with 1,000 or 10,000 genotyped progeny-tested bulls and a 10-yr genomic selection scheme with or without 2,000 additional genotyped cows. Evaluation criteria were annual monetary genetic gain and rate of true inbreeding. Our results showed that adding more genotyped cows to the reference in dairy cattle populations has the potential to increase genetic gain and reduce the rate of inbreeding, regardless of reference population size and level of LD. However, it is still not possible to reach the same genetic gain as in the simulated Danish Holstein population with either a small reference population or low LD. Our results also showed that in a small reference population with high LD, it is difficult to manage inbreeding because of lower accuracy compared with the simulated Danish Holstein population and a smaller number of relevant families to select from. Therefore, breeding strategies need to be chosen to match population size and structure. The rate of true inbreeding is always underestimated by pedigree inbreeding and even more in genomic breeding programs, indicating that some forms of genome-wide inbreeding, instead of pedigree-based inbreeding, should be used to monitor inbreeding when genomic selection is implemented.

Optimization of Swine Breeding Programs Using Genomic Selection with ZPLAN.

The objective of this study was to evaluate the present conventional selection program of a swine nucleus farm and compare it with a new selection strategy employing genomic enhanced breeding value (GEBV) as the selection criteria. The ZPLAN+ software was employed to calculate and compare the genetic gain, total cost, return and profit of each selection strategy. The first strategy reflected the current conventional breeding program, which was a progeny test system (CS). The second strategy was a selection scheme based strictly on genomic information (GS1). The third scenario was the same as GS1, but the selection by GEBV was further supplemented by the performance test (GS2). The last scenario was a mixture of genomic information and progeny tests (GS3). The results showed that the accuracy of the selection index of young boars of GS1 was 26% higher than that of CS. On the other hand, both GS2 and GS3 gave 31% higher accuracy than CS for young boars. The annual monetary genetic gain of GS1, GS2 and GS3 was 10%, 12%, and 11% higher, respectively, than that of CS. As expected, the discounted costs of genomic selection strategies were higher than those of CS. The costs of GS1, GS2 and GS3 were 35%, 73%, and 89% higher than those of CS, respectively, assuming a genotyping cost of $120. As a result, the discounted profit per animal of GS1 and GS2 was 8% and 2% higher, respectively, than that of CS while GS3 was 6% lower. Comparison among genomic breeding scenarios revealed that GS1 was more profitable than GS2 and GS3. The genomic selection schemes, especially GS1 and GS2, were clearly superior to the conventional scheme in terms of monetary genetic gain and profit.

Economic evaluation of genomic selection in small ruminants: a sheep meat breeding program

Recent genomic evaluation studies using real data and predicting genetic gain by modeling breeding programs have reported moderate expected benefits from the replacement of classic selection schemes by genomic selection (GS) in small ruminants. The objectives of this study were to compare the cost, monetary genetic gain and economic efficiency of classic selection and GS schemes in the meat sheep industry. Deterministic methods were used to model selection based on multi-trait indices from a sheep meat breeding program. Decisional variables related to male selection candidates and progeny testing were optimized to maximize the annual monetary genetic gain (AMGG), that is, a weighted sum of meat and maternal traits annual genetic gains. For GS, a reference population of 2000 individuals was assumed and genomic information was available for evaluation of male candidates only. In the classic selection scheme, males breeding values were estimated from own and offspring phenotypes. In GS, different scenarios were considered, differing by the information used to select males (genomic only, genomic+own performance, genomic+offspring phenotypes). The results showed that all GS scenarios were associated with higher total variable costs than classic selection (if the cost of genotyping was 123 euros/animal). In terms of AMGG and economic returns, GS scenarios were found to be superior to classic selection only if genomic information was combined with their own meat phenotypes (GS-Pheno) or with their progeny test information. The predicted economic efficiency, defined as returns (proportional to number of expressions of AMGG in the nucleus and commercial flocks) minus total variable costs, showed that the best GS scenario (GS-Pheno) was up to 15% more efficient than classic selection. For all selection scenarios, optimization increased the overall AMGG, returns and economic efficiency. As a conclusion, our study shows that some forms of GS strategies are more advantageous than classic selection, provided that GS is already initiated (i.e. the initial reference population is available). Optimizing decisional variables of the classic selection scheme could be of greater benefit than including genomic information in optimized designs.

Reproductive technologies combine well with genomic selection in dairy breeding programs

The objective of the present study was to examine whether genomic selection of females interacts with the use of reproductive technologies (RT) to increase annual monetary genetic gain (AMGG). This was tested using a factorial design with 3 factors: genomic selection of females (0 or 2,000 genotyped heifers per year), RT (0 or 50 donors selected at 14mo of age for producing 10 offspring), and 2 reliabilities of genomic prediction. In addition, different strategies for use of RT and how strategies interact with the reliability of genomic prediction were investigated using stochastic simulation by varying (1) number of donors (25, 50, 100, 200), (2) number of calves born per donor (10 or 20), (3) age of donor (2 or 14mo), and (4) number of sires (25, 50, 100, 200). In total, 72 different breeding schemes were investigated. The profitability of the different breeding strategies was evaluated by deterministic simulation by varying the costs of a born calf with reproductive technologies at levels of €500, €1,000, and €1,500. The results confirm our hypothesis that combining genomic selection of females with use of RT increases AMGG more than in a reference scheme without genomic selection in females. When the reliability of genomic prediction is high, the effect on rate of inbreeding (ΔF) is small. The study also demonstrates favorable interaction effects between the components of the breeder’s equation (selection intensity, selection accuracy, generation interval) for the bull dam donor path, leading to higher AMGG. Increasing the donor program and number of born calves to achieve higher AMGG is associated with the undesirable effect of increased ΔF. This can be alleviated, however, by increasing the numbers of sires without compromising AMGG remarkably. For the major part of the investigated donor schemes, the investment in RT is profitable in dairy cattle populations, even at high levels of costs for RT.

Breakeven prices for recording of indicator traits to reduce the environmental impact of milk production.

A breeding scheme using genomic selection and an indicator trait for environmental impact (EI) was studied to find the most effective recording strategy in terms of annual monetary genetic gain and breakeven price for the recording of indicator traits. The breakeven price shows the investment space for developing a recording system for an indicator trait. The breeding goal consisted of three traits – milk production, functional trait and environmental impact – with economic values of €83, €82 and €-83, respectively. The first scenario included only breeding goal traits and no indicator traits (NoIT). The other scenarios included all three breeding goal traits and one indicator trait (IT) for EI. The indicator traits were recorded on a large scale (stayability after first lactation and stature), medium scale (live weight and greenhouse gases (GHG) measured in the breath of the cow during milking) or small scale (residual feed intake and total enteric methane measured in a respiration chamber). In the scenario with stayability, the genetic gain in EI was over 11% higher than it was in NoIT. The breakeven price of recording stayability was €8 per record. Stayability is easy to record in the national milk recording system, and its use as an indicator trait for EI would not generate any additional recording costs. Therefore, stayability would be a good indicator trait to use to mitigate EI. The highest genetic gain in EI (23% higher compared to NoIT) was achieved when the GHG measured in the breath of the cow was used as indicator trait. The breakeven price for this indicator trait was €29 per record in the reference population. Ideally the recording of a specific indicator trait for EI would take place when: (i) the genetic correlation between the IT and EI is high; and (ii) the number of phenotypic records for the indicator trait is high enough to achieve a moderately high reliability of direct genomic values.

Adding cows to the reference population makes a small dairy population competitive

Small dairy breeds are challenged by low reliabilities of genomic prediction. Therefore, we evaluated the effect of including cows in the reference population for small dairy cattle populations with a limited number of sires in the reference population. Using detailed simulations, 2 types of scenarios for maintaining and updating the reference population over a period of 15yr were investigated: a turbo scheme exclusively using genotyped young bulls and a hybrid scheme with mixed use of genotyped young bulls and progeny-tested bulls. Two types of modifications were investigated: (1) number of progeny-tested bulls per year was tested at 6 levels: 15, 40, 60, 100, 250, and 500; and (2) each year, 2,000 first-lactation cows were randomly selected from the cow population for genotyping or, alternatively, an additional 2,000 first-lactation cows were randomly selected and typed in the first 2yr. The effects were evaluated in the 2 main breeding schemes. The breeding schemes were chosen to mimic options for the Danish Jersey cattle population. Evaluation criteria were annual monetary genetic gain, rate of inbreeding, reliability of genomic predictions, and variance of response. Inclusion of cows in the reference population increased monetary genetic gain and decreased the rate of inbreeding. The increase in genetic gain was larger for the turbo schemes with shorter generation intervals. The variance of response was generally higher in turbo schemes than in schemes using progeny-tested bulls. However, the risk was reduced by adding cows to the reference population. The annual genetic gain and the reliability of genomic predictions were slightly higher with more cows in the reference population. Inclusion of cows in the reference population is a rapid way to increase reliabilities of genomic predictions and hence increase genetic gain in a small population. An economic evaluation shows that genotyping of cows is a profitable investment.

Short communication: Genotyping of cows to speed up availability of genomic estimated breeding values for direct health traits in Austrian Fleckvieh (Simmental) cattle—Genetic and economic aspects

The aim of this study was to quantify the impact of genotyping cows with reliable phenotypes for direct health traits on annual monetary genetic gain (AMGG) and discounted profit. The calculations were based on a deterministic approach using ZPLAN software (University of Hohenheim, Stuttgart, Germany). It was assumed that increases in reliability of the total merit index (TMI) of 5, 15, and 25 percentage points were achieved through genotyping 5,000, 25,000, and 50,000 cows, respectively. Costs for phenotyping, genotyping, and genomic estimated breeding values vary between €150 and €20 per cow. The gain in genotyping cows for traits with medium to high heritability is more than for direct health traits with low heritability. The AMGG is increased by 1.5% if the reliability of TMI is 5 percentage points higher (i.e., 5,000 cows genotyped) and 6.53% higher AMGG can be expected when the reliability of TMI is increased by 25 percentage points (i.e., 50,000 cows genotyped). The discounted profit depends not only on the costs of genotyping but also on the population size. This study indicates that genotyping cows with reliable phenotypes is feasible to speed up the availability of genomic estimated breeding values for direct health traits. But, because of the huge amount of valid phenotypes and genotypes needed to establish an efficient genomic evaluation, it is likely that financial constraints will be the main limiting factor for implementation into breeding program such as Fleckvieh Austria.

Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit

The objective of this study was to evaluate a genomic breeding scheme in a small dairy cattle population that was intermediate in terms of using both young bulls (YB) and progeny-tested bulls (PB). This scheme was compared with a conventional progeny testing program without use of genomic information and, as the extreme case, a juvenile scheme with genomic information, where all bulls were used before progeny information was available. The population structure, cost, and breeding plan parameters were chosen to reflect the Danish Jersey cattle population, being representative for a small dairy cattle population. The population consisted of 68,000 registered cows. Annually, 1,500 bull dams were screened to produce the 500 genotyped bull calves from which 60 YB were selected to be progeny tested. Two unfavorably correlated traits were included in the breeding goal, a production trait (h2=0.30) and a functional trait (h2=0.04). An increase in reliability of 5 percentage points for each trait was used in the default genomic scenario. A deterministic approach was used to model the different breeding programs, where the primary evaluation criterion was annual monetary genetic gain (AMGG). Discounted profit was used as an indicator of the economic outcome. We investigated the effect of varying the following parameters: (1) increase in reliability due to genomic information, (2) number of genotyped bull calves, (3) proportion of bull dam sires that are young bulls, and (4) proportion of cow sires that are young bulls. The genomic breeding scheme was both genetically and economically superior to the conventional breeding scheme, even in a small dairy cattle population where genomic information causes a relatively low increase in reliability of breeding values. Assuming low reliabilities of genomic predictions, the optimal breeding scheme according to AMGG was characterized by mixed use of YB and PB as bull sires. Exclusive use of YB for production cows increased AMGG up to 3 percentage points. The results from this study supported our hypothesis that strong interaction effects exist. The strongest interaction effects were obtained between increased reliabilities of genomic estimated breeding values and more intensive use of YB. The juvenile scheme was genetically inferior when the increase in reliability was low (5 percentage points), but became genetically superior at higher reliabilities of genomic estimated breeding values. The juvenile scheme was always superior according to discounted profit because of the shorter generation interval and minimizing costs for housing and feeding waiting bulls.

Genomic selection using indicator traits to reduce the environmental impact of milk production

The aim of this simulation study was to test the hypothesis that phenotype information of specific indicator traits of environmental importance recorded on a small-scale can be implemented in breeding schemes with genomic selection to reduce the environmental impact of milk production. A stochastic simulation was undertaken to test alternative breeding strategies. The breeding goal consisted of milk production, a functional trait, and environmental impact (EI). The indicator traits (IT) for EI were categorized as large-, medium-, or small-scale, depending on how the traits were recorded. The large-scale traits were stayability and stature; the medium-scale traits were live weight and methane in the breath of the cow measured during milking; and the small-scale traits were residual feed intake and methane recorded in a respiration chamber. Simulated scenarios considered information for just one IT in addition to information for milk production and functional traits. The annual monetary genetic gain was highest in the large-scale scenario that included stayability as IT. The annual monetary gain in the scenarios with medium- or small-scale IT varied from €50.5 to 47.5. The genetic gain improvement in EI was, however, best in the scenarios where the genetic correlation between IT and EI was ≥0.30 and the accuracy of direct genomic value was ≥0.40. The genetic gain in EI was 26 to 34% higher when indicator traits such as greenhouse gases in the breath of the cow and methane recorded in respiration chamber were used compared with a scenario where no indicator trait was included. It is possible to achieve increased genetic gain in EI by using a highly correlated indicator trait, but it requires that the established reference population for the indicator trait is large enough so that the accuracy of direct genomic values will be reasonably high.

Hot topic: Effect of breeding strategies using genomic information on fitness and health

A complex deterministic approach was used to model the breeding goal and breeding structure for the Austrian Fleckvieh (dual-purpose Simmental) breed. The reference breeding goal corresponded to the current total merit index (TMI-R), where dairy traits have a relative weight of 37.9% and fitness traits of 43.7% (beef traits 16.5%; milkability 2%). The breeding program was characterized by 280,000 cows under performance recording, 3,200 bull dams, 100 test bulls with a test capacity of 25%, and 15 proven bulls and 8 bull sires per year. The annual monetary genetic gain (AMGG) was generated mainly by increases in milk fat and milk protein yield (80.6%) and only to a small extent by fitness traits (6.6%). The inclusion of direct health traits (early reproductive disorders, cystic ovaries, and mastitis) with their economic weights increased the relative AMGG for fitness traits from 6.6 to 11.2%. The presently slightly negative AMGG for fertility index and udder health changed in a positive direction. Increasing the weight on the direct health traits by 50% resulted in a further shift toward fitness and health. The effect of strategies using genomic information in a total merit index (TMI) with varying weights on fitness and health traits was also analyzed. The conventional progeny-testing scheme was defined as the reference breeding program. A breeding program was considered to be genomically enhanced (GS50) when 50% of inseminations of herdbook cows and of bull dams were from young bulls with a genomic TMI, and a second program (GS100) did not rely on progeny-tested bulls at all. For GS50, a clear shift of the relative gain in AMGG toward fitness and health traits was observed for all 3 TMI scenarios, as a result of larger progeny groups and a shorter generation interval. For GS100, where no gene flow from progeny-tested bulls was assumed, the genetic gain per generation was lower for the fertility and udder health index but higher per year. The results based on natural genetic gain per year showed that no positive genetic response for fertility and udder health index were achieved for TMI-R (without the inclusion of direct health traits) in GS50 and GS100. The direction of the genetic trend was determined by the weights given to fertility and udder health indices within the TMI. When appropriate weights generated a clear positive trend, GS50 and GS100 reinforced this trend.

Evaluation of basic and alternative breeding programs for Sahiwal cattle genetic resources in Kenya

The Sahiwal cattle breeding program in Kenya has been operational on an interim basis for over 45 years. However, there have been no systematic efforts undertaken to evaluate its suitability, or to examine how competitive it is compared with other alternative programs in terms of genetic and economic merit. The objective of this study was therefore to evaluate the genetic and economic success of the current basic and alternative Sahiwal cattle breeding programs in Kenya. The breeding programs examined were the current closed nucleus with two breeding strategies: a purebreeding (CNPURE) and a crossbreeding system (CNCROSS) involving Sahiwal sires and East African Zebu dams. An open nucleus with a certain proportion of pastoral-born Sahiwal bulls introduced into the nucleus herds to produce cows was simulated as an alternative breeding program. In this program only a purebreeding strategy (ONPURE) was considered. The breeding strategies were evaluated under two breeding objective scenarios that addressed traditional markets where animals are sold on body size/weight basis and the Kenya Meat Commission where payment is based on carcass characteristics. Sensitivity analyses to changes in nucleus size and gene contribution were also performed. The annual monetary genetic gain and profit per cow for all investigated breeding programs varied within breeding objectives. Closed nucleus purebreeding program was the most attractive economically but less competitive in regard to genetic superiority compared with either CNCROSS or ONPURE. Returns and profits were generally higher for the carcass characteristic basis compared with the body size/weight basis for all evaluated breeding strategies. Expansion of the nucleus size was not attractive because of the associated reduction in genetic and economic benefits. However, gradual importation of pastoral-born sires into the nucleus farms at the current nucleus proportion of 14% was both genetically and economically beneficial. The CNCROSS plays a complimentary role of facilitating the exploitation of trade-offs that exist between the Sahiwal and the locally better adapted East African Zebu, it also represents an intermediate phase in the on-going upgrading program.

Evaluation of the efficiency of alternative two‐tier nucleus breeding systems designed to improve meat sheep in Kenya

A deterministic approach was used to genetically and economically evaluate the efficiency of five two-tier nucleus breeding systems for meat sheep in Kenya. The nucleus breeding systems differed in terms of whether the system was closed or open, in the type of animals that were involved in the movement of genetic superiority and in the number of selection pathways in each system. These systems were compared under four alternative breeding objectives based on monetary genetic gain and profit per ewe. The first objective simulated a situation where the flock size cannot be increased due to non-feed related constraints (FLOCK). The second specifically assumed that the flock size is restricted due to limited amount of feed resources (FEED). The third and fourth objectives assumed that sheep performed only tangible roles (TR) and both tangible and intangible roles (IR) in the production system respectively. Monetary genetic gains were highest for all objectives in an open nucleus system with a certain proportion of commercial-born ewes being introduced in the nucleus while at the same time utilizing young rams from the nucleus to breed sires and dams for the nucleus and commercial sector (ONyre). Utilizing young rams in a closed nucleus system for the dissemination of superior genes resulted in higher annual monetary genetic gain than utilization of old rams. Profit per ewe was significantly higher for FLOCK and IR in ONyre. In a closed system that allowed for downward movement of dams from the nucleus to the commercial sector to breed sires and dams, profit per ewe was highest for FEED and TR. The success of a nucleus breeding system should also focus on the profitability and logistics of establishing it. The implication of these results on the choice of two-tier nucleus breeding systems for the improvement of meat sheep is discussed.

Efficiency of alternative schemes breeding for resistance to gastrointestinal helminths in meat sheep

Genetic and economic efficiency of alternative schemes breeding for resistance to gastrointestinal (GI) helminths in meat sheep was evaluated using deterministic simulation. Four breeding objectives and schemes were assessed. The first breeding objective simulated a situation where the flock size cannot be increased due to non-feed related constraints (FLOCK). The second specifically assumed that the flock size is restricted due to limited amount of feed resources (FEED). The third and fourth objectives assumed that sheep performed only tangible roles (TR) and both tangible and intangible roles (IR) in the production system, respectively. Within these breeding objectives, four breeding schemes that differed in the measures available for use as selection criteria were compared. The schemes ranged from one that utilised birth weight, weaning weight, yearling weight, litter size and lambing interval (scheme 1) to one that included two measurements of faecal egg count (FEC, eggs/g) in young rams immediately after weaning (scheme 4). For scheme 1, resistance to GI helminths was not included in the breeding objectives. A two-stage selection process was assumed in the selection of rams to be used in the nucleus. The annual monetary genetic gain and profit per ewe for all schemes varied within breeding objectives but were highest in TR. Within each breeding objective, the annual monetary genetic gain and profit per ewe was highest for the breeding scheme with the highest level of recording (scheme 4). In all objectives, the difference in the profit per ewe between a scheme that included records on FEC measured once in rams immediately after weaning (scheme 3) and scheme 4 was small (1.3–3.7%) indicating that there is little benefit taking a second measurement of FEC. The optimal size of the nucleus was determined by the breeding objective. In schemes 3 and 4, profit per ewe was optimal when the top 5%, 5%, 10% and 10% of rams were selected in the first selection stage for FEC measurement in FLOCK, FEED, TR and IR, respectively. The practical implications of these results are discussed.

Developing breeding schemes for pasture based dairy production systems in Kenya: II. Evaluation of alternative objectives and schemes using a two-tier open nucleus and young bull system

A deterministic approach was used to evaluate alternative breeding objectives and schemes in a dairy cattle breed in Kenya. A two-tier open nucleus breeding scheme and a young bull system (YBS) were assumed with intensive recording and 100% artificial insemination (AI) in the nucleus and 35% AI in the commercial sector. The breeding objectives differed in the marketing scenario that each described and whether pasture feed for the cows was limited or not. Two marketing scenarios were distinguished; current (payment of milk is based on volume) and future (payment of milk would be based on volume and fat content). Therefore, four breeding objectives were considered: current no limitation (CUNL), current with limitation (CUWL), future no limitation (FUNL) and future with limitation (FUWL). The breeding schemes differed in the records available for use as selection criteria. The schemes ranged from one that only utilised fertility criteria (scheme 1) to one that incorporated fertility, weights, milk and fat yield (FY) criteria (scheme 5). The annual monetary genetic gain and profit per cow for all schemes varied within breeding objectives but were highest in CUNL. Within each marketing scenario, the annual monetary genetic gain and profit per cow was higher in a no limitation situation than in a situation with limitation on pastures. Within each breeding objective, the annual monetary genetic gain and profit per cow was highest for the breeding scheme with the highest level of investments. In all objectives, the difference in the profit per cow between a scheme that incorporated fertility, weights and milk yield (MY) criteria (scheme 4) and scheme 5 was small (0.4–1.2%) indicating that there is little benefit including FY as a selection criterion. Therefore, a breeding scheme that requires records on FY seems not to be reasonable from an economic point of view. This study showed that a well-organised breeding programme utilising an open nucleus, YBS and the smallholder farms as the commercial sector could sustain itself. The practical implications of the results and how sustainable breeding programmes can be established are discussed.

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.

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.