International Genetic Evaluation for Milkability

International Genetic Evaluation for Milkability D. Sprengel 1, J. Dodenhoff 1, K-U. Götz 1, J. Duda 2 and L. Dempfle 3 1 Bavarian Institute of Animal Production, 85586 Grub, Germany 2 Landeskuratorium der Erzeugerringe für tierische Veredelung in Bayern, 80336 München, Germany 3 Department of Animal Science, TU München, 85350 Freising-Weihenstephan, Germany Abstract Average milk flow rate (AFR) for Simmental from Austria and two German states (Bavaria and Baden-Wuerttemberg) was analysed. Definition of AFR and collection of data were slightly different across countries and states, respectively. For each pair five sample data sets were created. A two-trait animal model was applied to obtain estimates by REML, using an average information approach. Heritability estimates ranged from.282 to.369. Estimates of genetic correlations were large, ranging from.841 between Baden-Wuerttemberg and Bavaria to.933 between Austria and Baden-Wuerttemberg. Based on these results, AFR from Austria and Baden-Wuerttemberg were considered the same trait. Therefore, application of a two-trait model was proposed for a joint genetic evaluation for AFR from Austria and Germany with AFR from Bavaria being the second trait. In both Austria and Germany only breeding values for average flow rate from Austria and Baden-Wuerttemberg will be published. 1. Introduction Currently, Austria and Germany are in the process of implementing joint genetic evaluations for all traits in Simmental and Brown Swiss. The joint evaluation started with conformation traits in Simmental in August 2000. Other traits will follow successively, e.g., functional longevity, growth and carcass traits, fertility, and milk yield. Population sizes for Simmental differ considerably with the German population being approximately four times the size of the Austrian population. Within Germany, two major subpopulations can be distinguished. The Bavarian population is approximately 6 times the size of the population in Baden-Wuerttemberg. In total, Austria and Germany have about 1.2 million Simmental cows under milk recording. Genetic ties between these countries can be considered sufficient, and breeding goals are similar, making an international evaluation useful. Selection across populations can considerably increase the rate of genetic response (Lohuis and Dekkers, 1998). Several Austrian and German AI stations are co-operating, and a number of young bulls are tested in both countries. Especially for these bulls accuracy of breeding values will increase when data from Austria and Germany are combined. Analyses for conformation traits (results not presented) have shown the genetic correlation between Austria and Germany to be close to unity. Therefore, conformation scores from both countries can be considered the same trait. Similar results can be expected for most of the other traits, since definition of traits and data recording are almost identical in Austria and Germany. Singletrait models are computationally easier to handle. The biggest advantage, however, is that there will be one breeding value per animal, equally valid for Austria and Germany. Other procedures would result in two breeding values on an Austrian and on a German scale, respectively. However, application of a single-trait model may not be possible for milkability where definition of the trait and data collection are not standardised across Austria and Germany, and not even across regions in Germany. Milkability is the only trait where a joint evaluation for the states of Baden-Wuerttemberg and Bavaria was not implemented. For all other traits a joint genetic evaluation is in place since 1995. In Austria average flow rate (AFR) is recorded once in first lactation cows between 30 and 200 days in milk. Personnel of the dairy recording organisations measure time of milking during the official milk 35

recording, and then AFR is calculated. Because of regional differences in data collection, AFR is recorded in approximately 50% of the Simmental cows. In Baden-Wuerttemberg collection of AFR is similar, only that it is not connected with the official milk recording. Cows are supposed to be at least 50 days and no more than 180 days in milk but are also tested outside these limits. AFR is recorded in approximately 25% of the Simmental cows in Baden-Wuerttemberg. In Bavaria this collection system was applied until 1998 but only daughters of young bulls were tested. AFR was no longer recorded when a new milk recording device was introduced in 1998. The LactoCorder (FossElectric), a mobile milk meter, is used for routine dairy recording in herds participating in dairy recording test plan AT (a.m.-p.m. recording). Producers are also offered a new test plan that mixes supervised and unsupervised testing. In this test plan (ATM), at one milking per test day the LactoCorder is operated by the producer himself. Recently the LactoCorder has also been approved for ownersampler test plans. As of July 2001, approximately 72% of the cows were in test plans where the LactoCorder is used. In addition to recording milk yield and taking component samples the LactoCorder calculates milk flow rate during milking. For details see Worstorff et al. (1992). Based on flow rate thresholds, the milking is partitioned in several periods, e.g., period of main milking and period of machine stripping. Several traits can be derived (Dodenhoff et al., 1999), among others: Maximum flow rate (MFR) is the largest milk flow rate during the milking over a time span of approximately 22 seconds. 2MY: Milk yield in the first 2 minutes of the main milking. Machine stripping yield (MSY): Milk yield during the machine stripping period. Average flow rate during main milking and machine stripping (AFR) is calculated from main milking period and machine stripping period, and the milk yield in these periods. Bimodality of the milk flow curve (B) (with codes 0 and 1) is defined as a sudden and heavy drop of the flow rate shortly after milking begins. A bimodal milk flow curve usually indicates an inadequate stimulus resulting in a delayed let-down. In former studies (Sprengel et al., 2000) milk flow parameters like MFR and 2MY proved to be suited best to describe milkability. However, the trait chosen in Bavaria for a joint evaluation with Austria and Baden-Wuerttemberg was AFR. There was a strong concern that farmers would not accept maximum flow rate because in their opinion selection on maximum flow rate would almost automatically lead to higher cell counts and to a higher risk for mastitis. The unfavourable genetic relationship between milk flow rate and udder health traits is well-known (see Mrode and Swanson (1996) for an overview) but it may be overestimated by farmers. AFR as recorded in Bavaria is not quite comparable to AFR as recorded in Austria and Baden-Wuerttemberg because the period of overmilking, if it occurs, is omitted from the calculation. Structure of data is also different between Bavaria and the other countries. In Austria and Baden-Wuerttemberg only one AFR observation per cow is available while in Bavaria AFR is available from all milkings and all lactations (if cows are tested with the LactoCorder) because it is measured during the routine milk recording. No AFR observations are available from cows on farms that do not take part in test plans involving the LactoCorder. Objectives of this study were to estimate genetic parameters for milkability in Simmental from Austria, Baden-Wuerttemberg and Bavaria, and to implement a joint genetic evaluation. 2. Materials and Methods For these analyses data from Bavaria were from the routine dairy recording with the LactoCorder and were provided by the Bavarian dairy recording organisation, LKV Bayern. Test-day records were from first lactation Simmental cows tested from January 1999 to December 2000. Traits included were milk yield during main milking and during machine stripping and the times for the respective periods, and bimodality. MSY was recorded in 39% of the records. Cows in test plan ATM had two records per test day, one supervised and one unsupervised. Average flow rate (AFR_BY) was calculated as described above. 36

Data from Austria and Baden-Wuerttemberg, that were used in the respective routine evaluation in February 2001, were available for this study. First lactation average flow rate records from Austria (AFR_AU) were from 1985 to 2000, and average flow rate records from Baden- Wuerttemberg (AFR_BW) were from 1981-2000. Records were selected from cows that had calved at an age of 600 to 1260 days and had been tested between 5 and 275 days in milk. Characteristics of the data are given in Table 1. AFR_AU was larger than AFR_BW because cows were tested at an earlier stage of lactation. In Bavaria, days in milk was larger because AFR_BY is measured repeatedly during lactation while in Austria and Baden-Wuerttemberg AFR is measured only once relatively early in lactation. AFR_BY cannot be compared to AFR_AU and AFR_BW because definition of traits is slightly different and because AFR_BY is only from recent years. Sufficient genetic ties between countries are required for a useful joint genetic evaluation as well as for the estimation of genetic parameters. Amount of genetic ties was assessed by the number of common bulls between countries (Table 2). Numbers of bulls with progeny in the data did not reflect the differences in population size because percentages of cows tested for AFR are different across populations and because data were not from the same time span. Number of common bulls between Austria and Bavaria was larger than number of common bulls between Baden-Wuerttemberg and Bavaria. This is surprising considering that Baden-Wuerttemberg and Bavaria are in the same region (Southern Germany), and that there is a joint genetic evaluation for most traits since 1995. Most of the common bulls between these countries/ states are proven bulls that were used in the other countries after a successful test in one country. However, in recent years a considerable number of young sires were tested jointly by Austrian and Bavarian AI stations. Genetic parameters for AFR_AU, AFR_BW and AFR_BY were estimated in bivariate analyses. For each pair five data sets were created. Progeny of common bulls were selected from the data and then herd mates were added so that complete herds were included in the data sets. In order to create data sets of a size computationally feasible for the estimation of genetic parameters number of common bulls was restricted to 20 to 40, and number of daughters per bull was restricted to 50 per country/ state. For each animal in these data sets three additional generations of pedigree information, if available, were added from a joint pedigree file. AFR was transformed by taking the square root to achieve approximate normality. Table 3 gives an overview over the sample data sets. Two different models were applied. For AFR_BY fixed effects fitted were herd test-day, calving year calving month, time of milking (a.m., p.m.), and bimodality (codes 0, 1). DIM/c and ln(c/dim) were included as linear and quadratic covariates where DIM is days in milk and c = 380, and age at calving was included as linear covariate. To account for repeated measures of AFR_BY an additional uncorrelated random effect (permanent environmental effect) was fitted. For AFR_AU and AFR_BW a different model was applied where herd and calving year calving month were fixed effects, and DIM/c and age at calving were linear covariates. Components of variance were estimated by restricted maximum likelihood (REML) using an average information algorithm implemented in the DMU package (Jensen and Madsen, 1996). Convergence was assumed to have been reached if the Euclidian norm of the vector of first derivatives was less then 10-4. 3. Results and Discussion Estimates of genetic parameters and standard errors for average flow rate from Austria, Baden- Wuerttemberg and Bavaria are in Table 4. Variances and ratios of variances are arithmetic averages from ten data sets (five data sets for each pair). Estimates of genetic variances (σ 2 a) were similar for AFR_AU and AFR_BW. For AFR_BY, the estimate of σ 2 a was slightly smaller. Estimates of residual variances (σ 2 e) and phenotypic variances (σ 2 p), respectively, were slightly larger for AFR_AU than for AFR_BW. A similar estimate of σ 2 p was found for AFR_BY but the estimate of σ 2 e was considerably smaller because an additional uncorrelated random effect was included in the model for AFR_BY. Estimates of heritability (h 2 ) for average flow rate ranged from.282 to.369, and agreed with 37

heritabilities found for various measures for milking speed (Tomaszewski et al., 1975; Williams et al., 1984), but were larger than heritabilities reported for subjectively scored milking speed (Boettcher et al., 1998; Rupp and Boichard, 1999). In Table 5 estimates of genetic (r g ) and phenotypic correlations (r p ) which are arithmetic averages from five data sets for each pair are presented. The largest estimate of r g (.933) was found between AFR_AU and AFR_BW. This indicated, along with the similar estimates of σ 2 a, σ 2 e, σ 2 p, and h 2, that AFR_AU and AFR_BW are essentially the same trait. While definition of AFR is identical in Austria and Baden-Wuerttemberg, it is different for Bavaria. Therefore, it is surprising that the estimate of r g between AFR_AU and AFR_BY was only slightly smaller (.910). However, the estimate of r g between AFR_BW and AFR_BY was considerably smaller (.836). Differences in definition of the trait as well as differences in collecting AFR may be the reason for these differences in the estimates of r g between AFR_AU, AFR_BW and AFR_BY. Definition of AFR is different for Austria and Bavaria but it is recorded at the same time when milk yield is officially recorded. Definition of AFR is identical for Austria and Baden-Wuerttemberg but AFR_BW is recorded at a milking when milk yield is not officially recorded. For Baden- Wuerttemberg and Bavaria both definition of AFR and collection of AFR are different. 4. Conclusions In this study genetic parameters necessary to implement a joint genetic evaluation for average flow rate from Austria and Germany (Bavaria, Baden-Wuerttemberg) were obtained. Estimates of heritability were moderate, and estimates of genetic correlations were large. The results indicate that average flow rate from Austria and Baden-Wuerttemberg can be considered the same trait in a genetic evaluation. Since genetic correlations between AFR_BY and AFR_AU and especially between AFR_BY and AFR_BW were not quite as large as the corresponding correlation between AFR_AU and AFR_BW, and the h 2 estimate for AFR_BY was smaller a two-trait model seems to be appropriate for a joint genetic evaluation. Average flow rates from Austria and Baden-Wuerttemberg would be the first trait and average flow rate from Bavaria would be the second trait. The main objective of a joint evaluation is to obtain breeding values that are identical across countries. Therefore, only breeding values for average flow rate from Austria and Baden- Wuerttemberg will be published in both Austria and Germany. This might be a disadvantage for bulls from Bavaria but it will most likely be offset by the larger amount of data available from Bavaria. References Boettcher, P.J., Dekkers, J.C.M. & Kolstad, B.W. 1998. Development of an udder health index for sire selection based on somatic cell score, udder conformation, and milking speed. J. Dairy Sci. 81, 1157-1168. Dodenhoff, J., Sprengel, D., Duda, J. & Dempfle, L. 1999. Potential use of parameters of the milk flow curve for genetic evaluation of milkability. In: Proc. Int. Workshop Genet. Improvement of Functional Traits in Cattle. Interbull Bulletin 23, 131-141. Int. Committee Anim. Recording, Uppsala, Sweden. Jensen, J. & Madsen, P. 1996. A user s guide to DMU, a package for analyzing multivariate mixed models. Natl. Inst. Anim. Sci., Tjele, Denmark. Lohuis, M.M. & Dekkers, J.C.M. 1998. Merits of borderless evaluations. Proc. 6 th World Congr. Genet. Appl. Livest. Prod., Armidale, Australia XXVI, 169-172. Mrode, R.A. & Swanson, G.J.T. 1996. Genetic and statistical properties of somatic cell count and its suitability as an indirect means of reducing the incidence of mastitis in dairy cattle. Anim. Breed. Abstr. 64, 847-856. Rupp, R. & Boichard, D. 1999. Genetic parameters for clinical mastitis, somatic cell score, production, udder type traits, and milking ease in first lactation Holsteins. J. Dairy Sci. 82, 2198-2204. Sprengel, D., Dodenhoff, J., Duda, J. & Dempfle, L. 2000. Genetic parameters for milkability traits in Fleckvieh. 51 st EAAP Annual Meeting, Den Haag, The Netherlands. Tomaszewski, M.A., Hargrove, G.L. & Legates, J.E. 1975. An assessment of field measures of milking rate. J. Dairy Sci. 58, 545. 38

Williams, C.B., Burnside, E.B. & Schaeffer, L.R. 1984. Genetic and environmental parameters for two field measures of milking speed. J. Dairy Sci. 67, 1273-1280. Worstorff, H., Göft, H. & Zierer, E. 1992. Milchflusskurven in der Leistungsprüfung. In: Proc. Symp. Int. Komitee f. Leistungsprüfungen in der Tierproduktion (IKTL/ICAR), Neustift, Austria. EAAP Publication No. 61, 63-71. Table 1. Characteristics of the data a Country /State No. of cows No. of observations Days in milk Average flow rate Mean SD Mean SD Austria 155,586 155,586 35.7 24.8 1.98.56 Baden-Wuerttemberg 157,394 157,394 87.7 38.8 1.77.53 Bavaria 331,390 2,449,250 138.3 76.6 1.74 a.49 a Definition of AFR in Bavaria slightly different from AFR in Austria and Baden-Wuerttemberg Table 2. Number of bulls with progeny and number of common bulls Country/ State Austria Baden-Wuerttemberg Bavaria Austria 5,323 225 439 Baden-Wuerttemberg 5,410 257 Bavaria 7,897 Table 3. Characteristics of the sample data sets a Country/ State Parameter Austria Baden-Wuerttemberg Bavaria Cows 15,498 26,751 6,573 Pedigree animals 86,301 95,681 75,481 Observations 15,498 26,751 35,555 Mean b 1.41 1.38 1.31 Herds/ Test-days 722 517 2631 Calving year month effects 183 236 28 a Values given are means from ten sample data sets b Average flow rate was transformed by taking the square root in order to achieve approximate normality 39

Table 4. Estimates of genetic parameters ab and standard errors b (in parentheses) for average flow rate Country/ State Parameter Austria Baden-Wuerttemberg Bavaria σ 2 a.011.011.009 σ 2 c.013 σ 2 e.021.018.008 c σ 2 p.032.029.030 h 2.337 (.002).369.282 (.004) c 2.442 (.004) e 2.663 (.002).631.276 a σ 2 a = variance of additive genetic effects; σ 2 c = variance due to permanent environmental effects of cows; σ 2 e = residual variance; σ 2 p = phenotypic variance; h 2 = heritability; c 2 = fraction of variance due to permanent environmental effects of cows; e 2 = fraction of variance due to residual effects b Values given are means from ten sample data sets c Standard error not available Table 5. Estimates of heritabilities a, genetic correlations a (above the diagonal), phenotypic correlations a (below the diagonal, and standard errors a (in parentheses) for average flow rate Country/ State Austria Baden-Wuerttemberg Bavaria Austria.337 (.002).933 (.006).910 (.005) Baden-Wuerttemberg.346.369.841 (.009) Bavaria.281.256.282 (.004) a Values given are means from ten (heritabilities) and five (correlations) sample data sets, respectively 40