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1 Posgrado Regional en Ciencias Veterinarias Tropicales, Universidad Nacional de Costa Rica, Heredia, Costa Rica
2 Animal Breeding and Genetics Group, Wageningen University, 6700 AH Wageningen, The Netherlands
Corresponding author: J. Van Arendonk; E-mail: Johan.vanarendonk{at}wur.nl.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Key Words: breeding scheme • genetic comparison • dairy cattle
Abbreviation key: CN = closed nucleus, CR = correlated response, ER = economic response, G x E = genotype x environment interaction, PT = progeny testing, SI = semen importation, TPI = total production index
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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An efficient progeny testing (PT) scheme within a country is built on participation of a large group of farmers in AI and performance recording. Not all countries can afford the implementation of such a functional but costly breed improvement organization. Open nucleus breeding schemes may provide an alternative to PT schemes (Smith, 1988; Mpofu et al., 1993; Peters, 1993). Some advantages that have been mentioned for this scheme are that the entire breeding program is operated as a single herd with a high degree of operational control over the determinants of genetic progress (Meuwissen, 1990). In addition, generation intervals are shorter, and important characters can be measured at a relatively low cost under the same conditions. Potential disadvantages that have been mentioned for this scheme are possible increases of inbreeding, major risk for spreading diseases, high initial investment and operating costs, and organizational considerations (Hodges, 1990; Meuwissen, 1990).
As an alternative to having their own breeding scheme, countries could decide to rely entirely on importation of semen, embryos, or both from other countries. Performance testing on a relatively small number of farms is required to evaluate the merit of genetic material from different exporting countries. Both genetic as well as economic issues are involved in choosing the most appropriate improvement strategy for a country.
For example, the dairy cattle population in Costa Rica consists of approximately 200,000 cows located on 6400 farms (MAG-CORFOGA, 2001). Although these farms are technologically advanced, no official milk recording scheme is carried out, and <20% of the farmers perform some kind of milk recording. There is a need to explore the opportunities of different breeding strategies to meet the needs of the Costa Rican dairy farmers. The main question is whether the current breeding practices, based on importation of semen, should be continued or whether there is room for a transition to a more local breeding scheme.
Livestock production systems vary in production intensity, access to infrastructure, and markets. Differences between countries in environmental or market conditions may lead to differences in breeding goals and genotype x environment interaction (G x E) between countries.
From a conceptual point of view, importation of semen to improve the local cattle population is advised only under the following circumstances (Smith, 1988): 1) breeding goals for the exporting and importing populations are similar, 2) exotic stocks are better than domestic stocks for traits in the breeding goal, or 3) G x E effects are not important.
No good framework is available for evaluating the importance of each of these factors. Such a framework is needed for a genetic and economic comparison of the different breeding alternatives for a population.
This paper presents a framework for the genetic comparison of schemes based on semen importation (SI) and local breeding schemes, i.e., PT and closed nucleus (CN) breeding. The study first addresses the consequences of differences in breeding goals between the local and exporting country. Subsequently, differences in genetic level and rates of genetic gain between the populations are evaluated in relation to the structure of the breeding scheme and the degree of G x E between countries. The framework is demonstrated for the Costa Rican Holstein population, which currently relies heavily on importation of semen from North America.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Genetic and phenotypic parameters used in this analysis are given in Table 1
. Parameters were taken from the literature (Groen, 1990; Visscher and Goddard, 1995) and assumed equal for both countries. In this way, we ensured that observed differences between countries are due to differences in breeding goals or breeding schemes and not due to differences in genetic parameters. Economic values for traits in the breeding goal for Holstein cattle in Costa Rica (Table 1) were calculated by Vargas et al. (2002) assuming a fixed milk-output evaluation base.
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) reflect the relative weights in the total production index (TPI) economic index used for selection of Holstein cattle in US (Holstein USA, 2003). The TPI index included production (fat, protein), type (type, udder, feet, and legs), and health traits (productive life, SCS) with relative weights of 4:2:1. In determining the economic values for production traits, the ratio of economic values for protein and fat in the exporting country was set equal to 5:2, and the total value (fat + protein) was assumed equal to the total value for Costa Rica. An earlier study (Vargas et al., 2002) demonstrated that the economic value for survival rate in Holstein cattle of Costa Rica was in the same range as in other countries. Therefore, survival rate was given the same economic value in the exporting country and Costa Rica. Rumen capacity was assumed to have an economic value of zero in the exporting country. Selection index coefficients (b) were derived using the following equation (Hazel, 1943):
 | ([1]) |
where P is the variance-covariance matrix between traits in the selection index, G is the variance-covariance matrix between traits in the index and traits in the breeding goal, and v is a vector with economic values for traits in the breeding goal.
The correlation between the breeding goal for Costa Rica (Hcr) and the breeding goal in the exporting country (Hexp) was derived as follows (Gibson and van Arendonk, 1998):
 | ([2]) |
where C is the variance-covariance matrix between traits in the 2 breeding goals and v is as defined in Eq. [1]. Note that matrix C is the same within and between countries because of the assumption that the same parameters apply in both countries and that there is no genotype x country interaction. Equation [2] can be modified in situations where there are differences in parameters between countries or when G x E is present (Gibson and van Arendonk, 1998).
The correlation between the selection index of sires obtained for Costa Rica (Icr) and the selection index in the exporting country (Iexp) is equal to:
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where P is as defined in Eq. [1] and bcr and bexp are the vectors with selection index coefficients for proven sires in Costa Rica and the exporting country, respectively. The expressions in the denominator of Eq. [3] are the products of the standard deviation of the index (
I) in both countries.
Alternative Breeding Schemes
General concept.
The objective of the following analysis was to determine the relative efficiency of alternative breeding schemes for the current Holstein population in Costa Rica using deterministic simulation. Three strategies were analyzed: SI, PT, and CN breeding schemes.
Information sources for the selection indexes were defined according to breeding scheme and selection path. The assumptions made for the different breeding schemes are described in the following sections.
SI.
For this strategy, it was assumed that genetic improvement of the local Holstein cattle population relies entirely on the importation of semen from the exporting country. This strategy has been suggested for situations in which the exotic stock suits the local production and marketing conditions, and there are no major effects of G x E (Smith, 1988). Genetic resources available worldwide can be used locally at a reasonable price because of the increasing number of competitors for this market (Meuwissen, 1990). In the present study, it was assumed that all imported semen was purchased from a single country. This country has a long-standing PT scheme operating on a large dairy cow population. Cattle population parameters assumed for Costa Rica and the exporting country are given in Table 2. Figures for the exporting country were based on data for the Holstein cattle population in the US (Wiggans, 1997), which is currently the major provider of germplasm for Costa Rica. Selection intensities for the different selection paths were derived from these figures, considering restrictions in size of population for PT-Costa Rica and CN. It was also assumed that all cows in the population were inseminated using imported semen. No selection was performed within the local population; therefore, genetic improvement for this strategy relied exclusively on the genetic progress generated in the exporting country. Traits included in the selection index are given in Table 3. Genetic evaluation of sires was based on daughter performance for production traits and survival, with no measurements on rumen capacity.
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PT.
For this strategy, it was assumed that a PT scheme was initiated within the local population. Table 2 summarizes assumptions made about the size of the local population and the structure of the PT scheme. Given the small population size, it is obvious that the number of bulls needed to sire all cows in the base population could be very low. Therefore, a minimum of 4 sires to breed sons and 8 sires to breed dams was used to avoid rates of inbreeding that were too high. Traits in the selection index and information sources for this strategy are specified in Table 3. It was assumed that all cows under milk recording were sired by bulls selected from the local PT scheme. It was also assumed that production traits and survival rate were measured on the entire cow population participating in the breeding program; rumen capacity information was only available on performance of sires.
CN.
This strategy assumed that a nucleus breeding herd was established in Costa Rica. The nucleus herd used multiple ovulation and embryo transfer. In our analysis, we considered multiple ovulation and embryo transfer on adult cows within a closed nucleus. Potential donors were selected on the basis of performance during first lactation and on information on first lactation performance of full-sibs and half-sibs. Selection of sires and dams was performed only within the CN herd. Genetic gain in the base population was, therefore, entirely determined by the genetic gain within the nucleus. Data on structure and efficiency parameters assumed for the nucleus are given in Table 4 and were based on field data (Meuwissen, 1990). Traits included in the selection index and information sources are given in Table 3. Note that for this strategy we assumed that rumen capacity was measured not only on males, but also on females.
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Comparison criteria and sensitivity.
Total genetic response (R) expressed in US dollars per year was used as the criteria for comparison. This result was obtained from the following equation (Rendel and Robertson, 1950):
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where ERs and Ls are, respectively, the economic response (ER) in the breeding goal and the average generation interval for selection path s. Details on calculation of ERs are given in Table 5. The change in genetic (co–)variance caused by selection (Bulmer, 1971) and effects of family structure and population size on selection intensity were ignored, which lead to an over-prediction of genetic gain in particular for the CN scheme (McGuirk, 1989). Inbreeding effects were only taken into account by setting a minimum number of sires to select in the PT scheme and by setting a restriction of one bull selected per family in the CN scheme. The main objective of the present analysis was to provide a framework for comparing the results of alternative breeding schemes.
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Traits with the highest contribution to the overall genetic gain were protein and fat (see ER, Table 5), but the relative importance differs between countries. Fat and protein account for 61.4 and 35.5% of the total response in Costa Rica, respectively. For the exporting country, the contributions are 32.5 and 63.6%, respectively. Rumen capacity contributes an additional 8.0% to the genetic response in Costa Rica, and the contribution of survival rate is <4% in both countries.
A comparison of the differences in breeding goals can also be based on the correlated response (CR), i.e., the economic response in Costa Rica resulting from selection of sires in the exporting country for the breeding goal of the exporting country (Table 5). In this case, the total genetic response includes the contribution of rumen capacity, which is the correlated response achieved for this trait when selecting for other traits in the breeding goal. The correlated response in Costa Rica from selection for the exporting country is 2.2% lower than the response from direct selection for the Costa Rican breeding goal. The relative contribution of traits to the total economic response is very similar for both alternatives.
In summary, the breeding goals between Costa Rica and the exporting country differed in the traits included as well as the economic weights of breeding goal traits. The results show that selection for the breeding goal for the Costa Rican Holstein population would lead to similar rates of genetic response as selection for the breeding goal in the exporting country. The differences between breeding objectives are not a major factor in evaluating importation of semen and breeding schemes based on the local Holstein population.
Breeding Schemes
Initial situation.
The genetic response achieved for each breeding strategy and selection path is shown in Table 6. This table also gives information on selection intensities and accuracy of selection. Note that the results shown for SI correspond to the correlated response in Costa Rica when selection is performed in the exporting country, assuming a genetic correlation of one (no G x E effect), but different economic values for traits in the breeding goal. Strategy SI resulted in the highest rate of economic response. The response was 5.0 and 33.2% higher compared with CN and PT (Table 6). Cumulative genetic responses are plotted in Figure 1, assuming a time horizon of 25 yr and no initial genetic differences between populations. The genetic distance between populations will increase over time because of the differences in rates of genetic gain.
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Progeny testing schemes have been successfully practiced for a long time in countries with a large dairy cattle population. Selection of sires and dams can be performed directly within the same population to be improved. On the other hand, this strategy requires a widespread milk recording scheme and extensive use of AI for the estimation of breeding values of selection candidates, which are not the norm in a developing country (Meuwissen, 1990). Genetic gain largely depends on the effective size of the population. In addition, the inclusion of additional traits in the selection requires the implementation of a recording scheme.
From Table 6, we can also see that the superiority of CN over PT mainly originates from the increased reproductive capacity of females and the shorter generation intervals (Tables 2 and 4). As observed, most of the genetic gain was obtained through the dam paths (54%); for SI and PT, these 2 paths only contributed 30 and 40% of the total ER, respectively. Especially, the contribution of the dams to breed dams pathway becomes important in CN. Superiority of CN over PT schemes has been reported before (Nicholas and Smith, 1983; McGuirk, 1989; Mpofu et al., 1993).
Effect of G x E.
The effect of G x E was evaluated by simulating different degrees of genetic correlation between traits in the exporting country and Costa Rica. Three levels of genetic correlations were analyzed: 0.50, 0.75, and 1.0. The genetic responses for these 3 levels were compared against the genetic response obtained for strategy PT. The results are shown in Figure 2. As observed, when the genetic correlation was 0.50, the rate of response achieved by SI was lower than that by PT. With a genetic correlation of one, the genetic response from PT was 75.1% of the response from SI. Consequently, the strategies SI and PT produced almost the same genetic response for a genetic correlation of 0.75 (Figure 2). Based on these results, importation of semen is justified from a genetic point of view when the genetic correlation between countries is >0.75, which is in agreement with results found in previous studies (Goddard, 1992; Mpofu et al., 1993).
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, the line for PT will start below SI and will intersect SI at some point in time because of the higher rate of genetic gain. The point of intersection will be determined by the initial difference in genetic merit and can be obtained as x = IGD/(RSI – RPT), where x is the time in years, IGD is the initial difference in genetic merit for the index ([1.25, 1.50, or 2.0] x H-PT) (Table 5), and RSI – RPT is the difference in annual genetic responses between SI and PT (162.93 – 122.36). For the cases illustrated in Figure 3, the point of intersection is located at 5.1, 6.2, and 8.2 yr for 1.25, 1.50, and 2.0, respectively.
Other genetic considerations.
The time between the start of a breeding program and the realization of genetic gain in the commercial cow population will differ between strategies. The SI scheme relies on the importation of semen from selected sires and has a direct effect on the commercial cow population. Genetic gain in CN will take longer to reach the commercial population compared with SI and PT. These differences in timing do not affect the rate of genetic gain. The consequences can be visualized by moving the respective lines of ER along the x-axis.
The G x E can also be present in the CN, where the performance recorded on cows may not be the same in the nucleus herds as in the commercial population. In this case, the same reasoning would apply as for SI.
Differences between schemes with respect to inbreeding have been ignored in the present study. A way to consider this could be to adjust the genetic response achieved under different strategies by the expected rate of inbreeding (Goddard, 1992). Higher predicted rates of inbreeding are reported for the CN scheme; however, a previous study (Leitch et al., 1994) demonstrated that inbreeding within CN might be reduced effectively by using restrictive mating strategies and with little effect on genetic responses. In addition, the most likely local scheme will continue to import some genetic material to overcome the bottlenecks of a small population and to provide an international benchmark for the local population.
Final considerations.
The present results have clear implications for the design of a breeding program for dairy cattle in a small country such as Costa Rica. For this specific case, it seems that the choice between a local vs. externally based breeding program depends largely on the level of G x E, because no major differences in breeding objectives were found. In a preliminary study (Vargas and Solano, 1995), a correlation of 0.62 was found between breeding values for milk yield of Holstein sires in the US and Costa Rica. Other studies performed on AI Holstein sires from the US used in Latin America showed even lower estimates (Powell et al., 1990; Stanton et al., 1991; Houri Neto et al., 1996). Powell et al. (1990) reported a correlation between PTA of 0.42 for Holstein sires evaluated in the US and Ecuador. A similar study in Brazil found genetic correlations in the range of 0.50 to 0.68 (Houri Neto et al., 1996). Other studies, however, report correlations >0.90 (Powell and Wiggans, 1991). If the estimate of 0.62 found for Costa Rica is close to reality, there is a clear prospect to establish a local breeding scheme.
Our findings on the impact of G x E are in agreement with earlier results (Banos and Smith, 1991; Goddard, 1992). Banos and Smith (1991) found that when the genetic correlation between objectives in both countries was 0.7, each country stopped selecting bulls from the other country after a few generations. Goddard (1992), however, pointed out that inbreeding effects and the large size of the world population work to prevent complete isolation. He concluded that a possible future course is one in which, following the global bottleneck resulting from the introduction of American Holstein in the global Black and White populations, some differences between local populations re-emerge, but these local populations continue to exchange genes and do not become isolated strains. His latter conclusion, however, depends heavily on the degree of G x E between countries. The degree of G x E should be evaluated for total genetic merit and not just milk production (Goddard, 1992). When differences in production environments increased (e.g., feeding regimen, temperature, disease pressure), the importance of functional traits for the overall genetic merit is likely to be larger in the poor environment. Consequently, the degree of G x E will increase.
The implementation of a PT scheme requires the participation of a large number of farmers in milk recording and AI. This might be difficult to realize given the relatively low participation of farms in milk recording schemes. A small-scale milk performance recording scheme is also required in the case of SI. The results are needed to judge the value of genetic material from different exporting countries. Strategies based on nucleus herds rely less on the collection of information in the commercial cow population. However, establishing an effective nucleus breeding scheme puts high demands on technical skills and management conditions (Meuwissen, 1990). Such conditions are rarely attained in developing countries. A few studies reported on the results of implementation of multiple ovulation and embryo transfer programs in developing countries (Wagner, 1987; Niemann, 1992). Results showed large variation between countries with low efficiency levels in general.
Apart from the technical comparison of schemes discussed thus far, operating costs and general economic developments need to be taken into account when considering the future of dairy breeding in a country such as Costa Rica. Current trends in dairy breeding seem to converge toward the globalization of breeding programs. Under these circumstances, it is highly probable that international breeding companies will continue to play an important role on genetic improvement of the cattle population in developing countries. Several countries are already participating in a project for international evaluation of sires under the guidance of INTERBULL. Access to information on genetic evaluations performed worldwide can now be easily gained through the Internet. These transformations will also have an effect on breeding of dairy cattle in developing countries, because these countries represent a potential market for international breeding programs. However, these programs will have to meet the requirements of the new markets, i.e., future generations of sires will have to satisfy the specific demands of specific countries and productive sectors.
Collective efforts among similar countries in a regional breeding program, rather than several programs at the national level, may be a more sound option for small developing countries with similar production conditions. Breeding companies may play a role in setting up these programs and providing the necessary expertise to run them efficiently, while still making profit by fulfilling the requirements of a broader market.
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ACKNOWLEDGEMENTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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Received for publication September 12, 2003. Accepted for publication December 20, 2003.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONACKNOWLEDGEMENTSREFERENCES |
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| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
), semen importation (
), and closed nucleus (
) breeding schemes assuming no genotype x environment interaction effect and no initial difference in genetic merit between populations.
) between traits in the breeding goals in the exporting country and Costa Rica.