HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Corrected Table 1 Interpretive Summary An erratum has been published Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Miglior, F. Articles by Van Doormaal, B. J. Search for Related Content PubMed PubMed Citation Articles by Miglior, F. Articles by Van Doormaal, B. J.

Selection Indices in Holstein Cattle of Various Countries

¹ Agriculture and Agri-Food Canada – Dairy and Swine Research and Development Centre Lennoxville, QC, Canada
² Canadian Dairy Network, Guelph, ON, Canada

Corresponding author: Filippo Miglior; e-mail: miglior{at}cdn.ca.

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

 
Fifteen countries, based on geographical representation, Interbull membership, and size of progeny testing programs, provided a brief description of national selection index and top bull listings from August 2003. Individual traits included in each selection index were grouped into 3 components as they related to production, durability, and health and reproduction. The relative emphasis for each component within the selection index, as well as the number of common bulls among top listings were compared across countries. Average relative emphasis for production, durability, and health and reproduction, across all countries, was 59.5, 28, and 12.5%, respectively. The main difference between selection indices in various countries was the relative emphasis on production. Overall, the Danish S-Index had the most balanced emphasis across the 3 components, with 34% on production, 29% on durability, and 37% on health and reproduction. Broadening of breeding goals through recent changes to selection indices decreased the similarities of top bull listings across the various countries, with a slightly greater commonality among sires of top bulls.

Key Words: selection index • bull ranking • international dairy

Abbreviation key: Interbull = International Bull Evaluation Service

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

 
For many years, most selection indices worldwide focused on increasing milk production. National selection indices were based on improving milk yield and gradually shifted toward improving protein yield and, outside North America, toward increasing fat and especially protein content. This was true for most countries with the exception of the Scandinavian countries, whose selection indices also included health and reproduction, and North American countries, whose selection indices included conformation together with production. In the last 5 yr, there has been a growing interest in broadening selection indices to include functional traits such as reproduction and health. Main reasons for this shift were quota-based milk marketing systems, price constraints, or both, together with increasing producer and consumer concerns associated with the observed deterioration of the health and reproduction of dairy cows. Labor costs have increased relatively more than milk price in some countries. Several studies have shown that selection for production alone causes negative effects on udder health (Heringstad et al., 2003) and reproductive performance (Veerkamp et al., 2001; Haile-Mariam et al., 2003; Kadarmideen et al., 2003).

A decade ago, Leitch (1994) reported the relative emphasis on traits in selection indices from various countries. VanRaden (2002) reported the relative emphasis on traits in the US Net Merit formula in 1994 for comparison. Six selection indices placed 100% emphasis on production (Germany, France, Great Britain, Israel, the Netherlands, and New Zealand) and 4 indices placed approximately one-third emphasis on longevity and conformation traits in addition to production (US TPI and Net Merit, Canada, and Italy). The Danish S-Index (28%) and the US Net Merit (6%) were the only national selection indices that placed some emphasis on health and reproduction. Denmark placed relatively little emphasis on production (30%) compared with other countries, but also placed emphasis on durability (42%) and health and reproduction (28%), for a balanced selection index. Since 1994, several changes to national selection indices have been implemented and it is therefore of interest to assess changes in breeding goals in various countries over time.

Inbreeding levels have increased in Holstein populations worldwide and annual rate of inbreeding accelerated until the year 2000, especially in North American populations (Miglior, 2000). In the last 5 yr, inbreeding rates have slowed in North America (AIPL, 2004; CDN, 2004), France (S. Mattalia, personal communication, 2004), and Italy (S. Biffani, personal communication, 2004), whereas annual rates have not changed in Great Britain (Kearney et al., 2004). Lower rates of inbreeding are expected over the long term, because a broader range of traits is considered in different selection indices. Differences among national top bull rankings may help explain the likelihood that different bulls are being selected worldwide.

second aim was to quantify differences in top bull listings worldwide, as well as the commonality of their sires.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

 
Fifteen countries provided data for this study. Countries were chosen based on geographical representation, International Bull Evaluation Service (Interbull) membership, and size of progeny testing programs. Each national genetic evaluation center provided a brief description of their national selection index, including the relative emphasis of each trait in the overall index. Relative emphasis was expressed as a percentage and was computed as the economic weight divided by the breeding value standard deviation.

Traits from national selection indices were separated into 3 components. The first, production, was to recognize its contribution to higher revenue. Durability, the second component, was meant to include traits that contributed to increased profit due to longer herd life of cows. The third component, health and reproduction, was meant to include traits that reduce the cost of production, which are mainly traits related to health and reproductive performance. Therefore, the 3 components included the following traits: (i) production (milk, fat, and protein yield, fat and protein percentage); (ii) durability (longevity, body size, overall udder, feet and legs, final score, other conformation traits, milking temperament, and meat quality); and (iii) health and reproduction (udder health, calving ease, and milking speed). The durability component encompassed all remaining traits in each national selection index that were not directly related to dairy production or to health and reproduction. All conformation traits and conformation composites in national selection indices were included in the durability component. As an exception, specific linear conformation traits were included in the health and reproduction component because Canada, the Netherlands, and Denmark placed direct emphasis on udder health using a combination of these linear conformation traits, as well as milking speed and SCS. All other countries evaluated udder health as SCS only. Other conformation traits in the durability component included overall rump and dairy character.

Each country provided its August 2003 official top-100 bull listing based on their national selection index. If this list was compiled based on minimum requirements of reliability or number of daughters, a second list was provided without such constraints. The United States and Great Britain each provided 2 national selection indices. All other countries provided a single index. Top-100 bull listings for national selection indices were based on bull breeding values originating from 3 different sources depending on number of local daughters or reliability level and availability of Interbull evaluations for a given trait: 1) domestic breeding values are used for all traits for bulls with a sufficient number of local daughters or sufficient degree of reliability; 2) Interbull breeding values are used for bulls without local daughters or with an insufficient number of local daughters, degree of reliability, or both; and 3) breeding values for traits not included in Interbull evaluations are based on conversion formulas, prediction equations, pedigree index, or breed average for bulls without local daughters. Conversion formulas were linear regressions to convert national evaluations from one country to the base and scale of another country. Prediction equations were multiple regressions to predict a trait not included in Interbull evaluations using national complete data. National policies regarding use of international breeding values are summarized on the Interbull Web site (Interbull, 2004) and each country is responsible for deciding which conversion strategy to adopt in all 3 options. However, most countries do not provide information about which conversion strategy they use for those traits that are not included in Interbull evaluations.

Top-100 bull listings for national selection indices were compared to determine the number of common bulls present in various country pairs. Sires of top bulls were also identified and compared across countries. Differences in selection indices across countries would be expected to lower the number of top bulls in common or the number of sires of top bulls in common.

In a second analysis, breeding values computed by Interbull in August 2003 were used to determine the top-100 bull list for protein yield, overall udder conformation, and SCS in each country. Again, bull listings were compared to determine the number of common bulls present in various countries. A summary of genetic correlations between countries used in the Interbull November 2003 routine evaluations for protein yield, overall udder, and SCS were reported to assist with interpretation of results.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

 
National Selection Indices
Table 1 shows the relative emphasis on traits in national selection indices in August 2003. Based on information from Table 1, differences among countries are shown in Figure 1. Average relative emphasis for production, durability, and health and reproduction, across all countries, was 59.5, 27.9, and 12.6%, respectively.

View larger version (38K): [in this window] [in a new window]   Figure 1. Relative emphasis on production (gray), durability (white), and health and reproduction (black) components in selection indices of countries in August 2003.

The TOP index, one of 2 indices used in Great Britain, placed the largest relative emphasis on durability (42%), followed closely by the US TPI (41%), the German RZG (40%), the Canadian LPI (38%), and the Spanish ICO (38%). Israel did not place any direct emphasis on the durability component. Other indices with a low relative emphasis on durability were the Australian APR (16.5%) and the British PLI (20%).

The Danish S-Index placed the largest relative emphasis on the health and reproduction component (37%), followed by the French ISU (25%). The US Net Merit and the Israeli PD01 both placed 20% emphasis on this component. The Japanese NTP did not have any direct emphasis on the health and reproduction component, and Spain placed only 3% emphasis on this component. Overall, the Danish S-Index had the most balanced emphasis across the 3 components, with 34% on production, 29% on durability, and 37% on health and reproduction.

Within the production component, the Japanese NTP had the largest emphasis on protein yield with 55%, followed by the Israeli PD01 (51%), and the British PLI (49%). Lowest emphasis for protein yield was observed for the Danish S-Index (20.4%), followed by the German RZG (26%), and the Swiss ISEL (27%). The US Net Merit index had the largest emphasis for fat yield (22%), whereas the British TOP had the lowest (6%). North America and Japan did not put any direct emphasis on fat or protein percentages and did not emphasize greater fat or protein percentages indirectly through negative emphasis on milk volume. All other indices had a positive relative emphasis on the components either directly (ISEL, RZG, PFT, and ISU) or through a negative weight on milk yield (8 remaining indices). The Spanish ICO was an exception as it had positive weight on both milk yield and protein percentage.

Within the durability component, the Dutch DPS had the largest emphasis on longevity with 26%, followed by the German RZG (25%), and the Irish EBI (23%). No direct emphasis for longevity was reported for the Israeli PD01 and the Japanese NTP. On average, conformation traits provided the largest contribution to the durability component. The British TOP had the largest emphasis (40%), with 18% on overall udder, 14% on feet and legs, and 8% on body size. Canada had the second largest emphasis on conformation traits with 30.4% (15.2% on overall udder, 11.4% on feet and legs, and 3.8% on body size). Five selection indices put positive emphasis on traits related to body size, and 4 other indices put a negative weight. The New Zealander BW placed the largest emphasis on body weight (–19%).

Udder health and female fertility dominated the health and reproduction component. In most indices, SCS (an indicator trait for mastitis resistance) was the only trait contributing to udder health, with 3 exceptions: Canada, the Netherlands, and Denmark. The Canadian udder health index was based on SCS (60%), udder depth (–30%), and milking speed (10%). The Dutch udder health index was a combination of SCS, udder depth, fore udder attachment, teat length, and milking speed. The Danish udder health index was based on clinical mastitis, SCS, udder depth, udder support, and dairy form, with a combined emphasis of 14% on the Danish S-Index. The Danish S-Index had also a 6% emphasis on milking speed and 2% on resistance to other diseases.

The French ISU had the largest emphasis on female fertility (12.5%), followed by the Danish S-Index and the Israeli PD01 (both 9%). Several indices (7) did not have any direct emphasis on female fertility. Only 3 indices put some weight on calving ease (8, 6, and 4% for the Dutch DPS, Danish S-Index, and US Net Merit, respectively). No index placed any emphasis on stillbirth, even though increasing stillbirth rates have been reported in some Holstein populations, namely the Netherlands (Harbers et al., 1999), United States (Meyer et al., 2001), and Denmark (Hansen et al., 2004).

Bull Rankings in Various Countries
Table 2 has averages and ranges of Interbull genetic correlations for protein yield, overall udder, and SCS among countries considered in this study (November 2003 evaluations, Interbull, 2003a,b,c). Ireland and Israel were not included in Interbull evaluations for overall udder; and Spain, Ireland, and New Zealand were not included in Interbull evaluations for SCS. Average genetic correlations between the concerned countries were 0.87, 0.82, and 0.86 for protein yield, overall udder, and SCS, respectively. Genetic correlations ranged from 0.77 to 0.95, 0.48 to 0.96, and 0.55 to 0.97 for protein yield, overall udder, and SCS, respectively. Genetic correlations significantly lower than unity yielded a low average number of common bulls in top-100 lists for all 3 traits (Table 2). For protein yield, the average number of common bulls was 60, ranging from 31 to 84. Australia and New Zealand had the lowest average number of common bulls with 43 and 48, respectively, mainly due to the low genetic correlations with other countries. Overall udder and SCS had similar numbers of common bulls.

Leitch (1994) reported a relatively high similarity among top bull listings across countries with a rank correlation greater than 0.88. At that time, Interbull evaluations were not yet available and most countries focused entirely on production. Bull comparisons were based on simple conversion formulas that did not properly account for genotype by environment interaction (Goddard, 1985; Wilmink et al., 1986). Conversion formula methodology did not allow for reranking across countries for the same traits, and differences in top bull listings were solely based on differences in selection indices. In 1995, the Interbull Center started using the MACE procedure (Schaeffer, 1994) to compute international evaluations with estimated genetic correlations across countries that were less than one (Sigurdsson et al., 1996). This indicated that differences in top-100 bull listings were expected, as Interbull evaluation became available for an increasing number of traits, and broader selection indices were developed in various countries.

Most countries use minimum requirements based on reliability, semen availability, and number of daughters and herds to exclude bulls from officially published top-100 bull rankings. Values above diagonal in Table 3 include number of common bulls among top-100 bull listings without restrictions for those countries that did use such requirements (Australia, France, Germany, Ireland, Italy, Japan, New Zealand, Spain, and the United States). Number of common bulls increased for most country pairs, especially involving Australia, Italy, Japan, and Spain without restrictions. Restrictions on top-100 bull lists might have an impact on realized genetic gain, as some high-ranking bulls may be excluded from official listings, thereby lowering the selection differential. However, this negative impact might be offset by use of higher reliability bulls with more accurate proofs than newly proven bulls, whose breeding values based on a small amount of daughters might be affected in some countries by the overestimated breeding values of their dam.

Over time, the number of common bulls among top listings in various countries has decreased proportionally with changes in national selection indices and availability of Interbull evaluations. When selection indices were similar across countries and Interbull evaluations were not yet available (genetic correlations among countries equal to one), the average rank correlation among top bull listings from various countries was greater than 0.88 (Leitch, 2004). When Interbull evaluations became available, genetic correlations lower than unity decreased the average number of common bulls among top listings for single traits, as shown in Table 2, with an average of 60 bulls in common across all 3 traits (protein yield, overall udder, and SCS). It should be noted, however, that the advent of Interbull evaluations improved the accuracy of international comparisons allowing the bulls to rank differently across countries. A small number of common bulls in top listings for selection indices for countries having 2 national selection indices (69 between PLI and TOP for Great Britain, and 54 between Net Merit and TPI for US), can be solely attributed to differences between the 2 pairs of selection indices, because genetic correlations within country were equal to one. The average number of common bulls in top listings for various selection indices (average of below diagonal elements in Table 3) was drastically lower (25) than average number of top bulls for single traits (60). This average became even smaller (18, average of upper diagonal elements in Table 3) when only official top-100 listings were considered, based on restrictions applied on certain country top listings. Although farmers today have more and better information on which to base their selection decisions compared with previous decades, a low number of common bulls could create problems for AI organizations that are under pressure to have top bulls in many country rankings. Alternatively, a low number of common bulls could indicate that there are an increasing number of selected blood-lines, thus slowing down the increasing rate of inbreeding in the global Holstein population. A larger international gene pool would give dairy farmers a wider selection of top bulls that may be less related to the animals in their herd.

Although the number of bulls in common was quite low among top bull listings worldwide, a slightly greater similarity was found among the sires of those top bulls. This could be explained by the fact that bull sires partly represent historical selection decisions. The sires with the largest number of sons for each country’s official listing are in Table 4. New Zealand had the lowest number of total sires (32), whereas Great Britain (both PLI and TOP) had the highest number of different sires with an average of almost 2 sons per sire. Table 4 also shows the level of similarity of sire of sons across the various top-100 bull listings. The sire with the largest number of sons in the top-100 listings had 82 sons in 16 listings, present in every country listing with the exception of New Zealand.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

	ACKNOWLEDGEMENTS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

 
The cooperation of national genetic evaluation centers and breed associations that provided information and data is kindly acknowledged. The authors would like to thank the 2 anonymous reviewers for helpful suggestions to improve the manuscript.

Received for publication June 8, 2004. Accepted for publication November 18, 2004.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS ACKNOWLEDGEMENTS REFERENCES

 


Animal Improvement Programs Laboratory (AIPL). 2004. Subject: Inbreeding trends. Online. Available http://aipl.arsusda.gov/dynamic/inbrd/current/kindx.html. Accessed Nov. 9, 2004.

Canadian Dairy Network (CDN). 2004. Subject: Inbreeding trends. Online. Available http://www.cdn.ca/articles.htm. Accessed Nov, 9, 2004.

Goddard, M. E. 1985. A method of comparing sires evaluated in different countries. Livest. Prod. Sci. 13:321.

Haile-Mariam, M., P. J. Bowman, and M. E. Goddard. 2003. Genetic and environmental relationships among calving interval, survival, persistency of milk yield and somatic cell count in dairy cattle. Livest. Prod. Sci. 80:189–200.

Hansen, M., I. Misztal, M. S. Lund, J. Pedersen, and L. G. Christensen. 2004. Undesired phenotypic and genetic trend for stillbirth in Danish Holsteins. J. Dairy Sci. 87:1477–1486.[Abstract/Free Full Text]

Harbers, A., L. Segeren, and G. de Jong. 2000. Genetic parameters for stillbirth in The Netherlands. Interbull Bull. No. 25:117–122.

Heringstad, B., Y. M. Chang, D. Gianola, and G. Klemetsdal. 2003. Genetic analysis of longitudinal trajectory of clinical mastitis in first-lactation Norwegian Cattle. J. Dairy Sci. 86:2676–2683.[Abstract/Free Full Text]

International Bull Evaluation Service. 2003a. INTERBULL routine genetic evaluation for production traits, November 2003. Online. Available http://www-interbull.slu.se/eval/nov03.html. Accessed Dec. 9, 2003.

International Bull Evaluation Service. 2003b. INTERBULL routine genetic evaluation for conformation traits, November 2003. Online. Available http://www-interbull.slu.se/conform/cnov03.html. Accessed Dec. 9, 2003.

International Bull Evaluation Service. 2003c. INTERBULL routine genetic evaluation for udder health traits, November 2003. Online. Available http://www-interbull.slu.se/udder/unov03.html. Accessed Dec. 9, 2003.

International Bull Evaluation Service. 2004. Policies regarding national and Interbull evaluations. Online. Available http://www-interbull.slu.se/polic_release/table2-041.html. Accessed Nov. 11, 2004.

Kadarmideen, H. N., R. Thompson, M. P. Coffey, and M. A. Kossaibati. 2003. Genetic parameters and evaluations from single- and multiple-trait analysis of dairy cow fertility and milk production. Livest. Prod. Sci. 81:183–195.

Kearney, J. F., E. Wall, B. Villaneuva, and M. P. Coffey. 2004. Inbreeding trends and application of optimized selection in the UK Holstein population. J. Dairy Sci. 87:3503–3509.[Abstract/Free Full Text]

Klei, B., K. Weigel, and T. Lawlor. 1999. MACE: the relative importance of information source. Interbull Bull. No. 22:9–13.

Leitch, H. W. 1994. Comparison of international selection indices for dairy cattle breeding. Interbull Bull. No. 10.

Meyer, C. L., P. J. Berger, K. J. Koehler, J. R. Thompson, and C. G. Sattler. 2000. Interactions among factors affecting stillbirths in Holstein Cattle in the United States. J. Dairy Sci. 83:2657–2663.[Abstract]

Miglior, F. 2000. Impact of inbreeding: Managing a declining Holstein gene pool. Pages 108–113 in Proc. 10th World Holstein-Friesian Conf., Sydney, Australia.

Schaeffer, L. R. 1994. Multiple-country comparison of dairy sires. J. Dairy Sci. 77:2671–2678.[Abstract]

Sigurdsson, A., G. Banos, and J. Philipsson. 1996. Estimation and genetic (co)variance components for international evaluation of dairy bulls. Acta Agric. Scand. 46:129–136.

VanRaden, P. M. 2002. Selection of dairy cattle for lifetime profit. Pages 127–130 in Proc. 7th World Congr. Genet. Appl. Livest. Prod., Montpellier, France.

Veerkamp, R. F., E. P. C. Koenen, and G. De Jong. 2001. Genetic correlations among body condition score, yield, and fertility in first-parity cows estimated by random regression models. J. Dairy Sci. 84:2327–2335.[Abstract]

Wilmink, J. B. M., A. Meijering, and B. Engel. 1986. Conversion of breeding values for foreign populations. Livest. Prod. Sci. 14:223.

This article has been cited by other articles:

				J. R. Roche, N. C. Friggens, J. K. Kay, M. W. Fisher, K. J. Stafford, and D. P. Berry Invited review: Body condition score and its association with dairy cow productivity, health, and welfare J Dairy Sci, December 1, 2009; 92(12): 5769 - 5801. [Abstract] [Full Text] [PDF]

				R. Prendiville, K. M. Pierce, and F. Buckley An evaluation of production efficiencies among lactating Holstein-Friesian, Jersey, and Jersey x Holstein-Friesian cows at pasture J Dairy Sci, December 1, 2009; 92(12): 6176 - 6185. [Abstract] [Full Text] [PDF]

				E. P. Cunningham and H. Tauebert Measuring the effect of change in selection indices J Dairy Sci, December 1, 2009; 92(12): 6192 - 6196. [Abstract] [Full Text] [PDF]

				M. J. M. Rutten, H. Bovenhuis, K. A. Hettinga, H. J. F. van Valenberg, and J. A. M. van Arendonk Predicting bovine milk fat composition using infrared spectroscopy based on milk samples collected in winter and summer J Dairy Sci, December 1, 2009; 92(12): 6202 - 6209. [Abstract] [Full Text] [PDF]

				J. Coleman, K. M. Pierce, D. P. Berry, A. Brennan, and B. Horan The influence of genetic selection and feed system on the reproductive performance of spring-calving dairy cows within future pasture-based production systems J Dairy Sci, October 1, 2009; 92(10): 5258 - 5269. [Abstract] [Full Text] [PDF]

				S. Konig and H. H. Swalve Application of selection index calculations to determine selection strategies in genomic breeding programs J Dairy Sci, October 1, 2009; 92(10): 5292 - 5303. [Abstract] [Full Text] [PDF]

				B. Griesbeck-Zilch, M. Osman, Ch. Kuhn, M. Schwerin, R. H. Bruckmaier, M. W. Pfaffl, A. Hammerle-Fickinger, H. H. D. Meyer, and O. Wellnitz Analysis of key molecules of the innate immune system in mammary epithelial cells isolated from marker-assisted and conventionally selected cattle J Dairy Sci, September 1, 2009; 92(9): 4621 - 4633. [Abstract] [Full Text] [PDF]

				P. Lovendahl and M. G. G. Chagunda Short communication: Genetic variation in estrus activity traits J Dairy Sci, September 1, 2009; 92(9): 4683 - 4688. [Abstract] [Full Text] [PDF]

				L. H. Buch, A. C. Sorensen, J. Lassen, P. Berg, L. G. Christensen, and M. K. Sorensen Factors affecting the exchange of genetic material between Nordic and US Holstein populations J Dairy Sci, August 1, 2009; 92(8): 4023 - 4034. [Abstract] [Full Text] [PDF]

				M. A. Perez-Cabal, G. de los Campos, A. I. Vazquez, D. Gianola, G. J. M. Rosa, K. A. Weigel, and R. Alenda Genetic evaluation of susceptibility to clinical mastitis in Spanish Holstein cows J Dairy Sci, July 1, 2009; 92(7): 3472 - 3480. [Abstract] [Full Text] [PDF]

				K. Togashi and C. Y. Lin Economic weights for genetic improvement of lactation persistency and milk yield J Dairy Sci, June 1, 2009; 92(6): 2915 - 2921. [Abstract] [Full Text] [PDF]

				Y. Terawaki and V. Ducrocq Nongenetic effects and genetic parameters for length of productive life of Holstein cows in Hokkaido, Japan J Dairy Sci, May 1, 2009; 92(5): 2144 - 2150. [Abstract] [Full Text] [PDF]

				R. T. Garmo, E. Ropstad, O. Havrevoll, E. Thuen, H. Steinshamn, A. Waldmann, and O. Reksen Commencement of luteal activity in three different selection lines for milk yield and fertility in Norwegian Red cows J Dairy Sci, May 1, 2009; 92(5): 2159 - 2165. [Abstract] [Full Text] [PDF]

				H. Khatib, W. Huang, X. Wang, A. H. Tran, A. B. Bindrim, V. Schutzkus, R. L. Monson, and B. S. Yandell Single gene and gene interaction effects on fertilization and embryonic survival rates in cattle J Dairy Sci, May 1, 2009; 92(5): 2238 - 2247. [Abstract] [Full Text] [PDF]

				F. Forabosco, J. H. Jakobsen, and W. F. Fikse International genetic evaluation for direct longevity in dairy bulls J Dairy Sci, May 1, 2009; 92(5): 2338 - 2347. [Abstract] [Full Text] [PDF]

				J. A. D. R. N. Appuhamy, B. G. Cassell, and J. B. Cole Phenotypic and genetic relationships of common health disorders with milk and fat yield persistencies from producer-recorded health data and test-day yields J Dairy Sci, April 1, 2009; 92(4): 1785 - 1795. [Abstract] [Full Text] [PDF]

				R. Rupp, D. Bergonier, S. Dion, M. C. Hygonenq, M. R. Aurel, C. Robert-Granie, and G. Foucras Response to somatic cell count-based selection for mastitis resistance in a divergent selection experiment in sheep J Dairy Sci, March 1, 2009; 92(3): 1203 - 1219. [Abstract] [Full Text] [PDF]

				N. Begley, F. Buckley, K. M. Pierce, A. G. Fahey, and B. A. Mallard Differences in udder health and immune response traits of Holstein-Friesians, Norwegian Reds, and their crosses in second lactation J Dairy Sci, February 1, 2009; 92(2): 749 - 757. [Abstract] [Full Text] [PDF]

				L. M. Chagas, M. C. Lucy, P. J. Back, D. Blache, J. M. Lee, P. J. S. Gore, A. J. Sheahan, and J. R. Roche Insulin resistance in divergent strains of Holstein-Friesian dairy cows offered fresh pasture and increasing amounts of concentrate in early lactation J Dairy Sci, January 1, 2009; 92(1): 216 - 222. [Abstract] [Full Text] [PDF]

				M. K. Sorensen, E. Norberg, J. Pedersen, and L. G. Christensen Invited Review: Crossbreeding in Dairy Cattle: A Danish Perspective J Dairy Sci, November 1, 2008; 91(11): 4116 - 4128. [Abstract] [Full Text] [PDF]

				S. Walsh, F. Buckley, K. Pierce, N. Byrne, J. Patton, and P. Dillon Effects of Breed and Feeding System on Milk Production, Body Weight, Body Condition Score, Reproductive Performance, and Postpartum Ovarian Function J Dairy Sci, November 1, 2008; 91(11): 4401 - 4413. [Abstract] [Full Text] [PDF]

				O. M. Onyiro, L. J. Andrews, and S. Brotherstone Genetic Parameters for Digital Dermatitis and Correlations with Locomotion, Production, Fertility Traits, and Longevity in Holstein-Friesian Dairy Cows J Dairy Sci, October 1, 2008; 91(10): 4037 - 4046. [Abstract] [Full Text] [PDF]

				H. Hammami, B. Rekik, H. Soyeurt, C. Bastin, J. Stoll, and N. Gengler Genotype x Environment Interaction for Milk Yield in Holsteins Using Luxembourg and Tunisian Populations J Dairy Sci, September 1, 2008; 91(9): 3661 - 3671. [Abstract] [Full Text] [PDF]

				Y. de Haas, W. Ouweltjes, J. t. Napel, J. J. Windig, and G. de Jong Alternative Somatic Cell Count Traits as Mastitis Indicators for Genetic Selection J Dairy Sci, June 1, 2008; 91(6): 2501 - 2511. [Abstract] [Full Text] [PDF]

				A. Sewalem, F. Miglior, G. J. Kistemaker, P. Sullivan, and B. J. Van Doormaal Relationship Between Reproduction Traits and Functional Longevity in Canadian Dairy Cattle J Dairy Sci, April 1, 2008; 91(4): 1660 - 1668. [Abstract] [Full Text] [PDF]

				K. A. Macdonald, G. A. Verkerk, B. S. Thorrold, J. E. Pryce, J. W. Penno, L. R. McNaughton, L. J. Burton, J. A. S. Lancaster, J. H. Williamson, and C. W. Holmes A Comparison of Three Strains of Holstein-Friesian Grazed on Pasture and Managed Under Different Feed Allowances J Dairy Sci, April 1, 2008; 91(4): 1693 - 1707. [Abstract] [Full Text] [PDF]

				P. Smith, D. Martino, Z. Cai, D. Gwary, H. Janzen, P. Kumar, B. McCarl, S. Ogle, F. O'Mara, C. Rice, et al. Greenhouse gas mitigation in agriculture Phil Trans R Soc B, February 27, 2008; 363(1492): 789 - 813. [Abstract] [Full Text] [PDF]

				O. M. Onyiro and S. Brotherstone Genetic Analysis of Locomotion and Associated Conformation Traits of Holstein-Friesian Dairy Cows Managed in Different Housing Systems J Dairy Sci, January 1, 2008; 91(1): 322 - 328. [Abstract] [Full Text] [PDF]

				S. Konig, X. L. Wu, D. Gianola, B. Heringstad, and H. Simianer Exploration of Relationships Between Claw Disorders and Milk Yield in Holstein Cows via Recursive Linear and Threshold Models J Dairy Sci, January 1, 2008; 91(1): 395 - 406. [Abstract] [Full Text] [PDF]

				O. Gonzalez-Recio, E. Lopez de Maturana, and J. P. Gutierrez Inbreeding Depression on Female Fertility and Calving Ease in Spanish Dairy Cattle J Dairy Sci, December 1, 2007; 90(12): 5744 - 5752. [Abstract] [Full Text] [PDF]

				S. Walsh, F. Buckley, D. P. Berry, M. Rath, K. Pierce, N. Byrne, and P. Dillon Effects of Breed, Feeding System, and Parity on Udder Health and Milking Characteristics J Dairy Sci, December 1, 2007; 90(12): 5767 - 5779. [Abstract] [Full Text] [PDF]

				D. P. Berry, B. Horan, M. O'Donovan, F. Buckley, E. Kennedy, M. McEvoy, and P. Dillon Genetics of Grass Dry Matter Intake, Energy Balance, and Digestibility in Grazing Irish Dairy Cows J Dairy Sci, October 1, 2007; 90(10): 4835 - 4845. [Abstract] [Full Text] [PDF]

				J. R. Roche, J. M. Lee, K. A. Macdonald, and D. P. Berry Relationships Among Body Condition Score, Body Weight, and Milk Production Variables in Pasture-Based Dairy Cows J Dairy Sci, August 1, 2007; 90(8): 3802 - 3815. [Abstract] [Full Text] [PDF]

				C. Hayhurst, M. K. Sorensen, M. D. Royal, and P. Lovendahl Metabolic Regulation in Danish Bull Calves and the Relationship to the Fertility of Their Female Offspring J Dairy Sci, August 1, 2007; 90(8): 3909 - 3916. [Abstract] [Full Text] [PDF]

				S. Konig, F. Bosselmann, U. U. von Borstel, and H. Simianer Genetic Analysis of Traits Affecting the Success of Embryo Transfer in Dairy Cattle J Dairy Sci, August 1, 2007; 90(8): 3945 - 3954. [Abstract] [Full Text] [PDF]

				H. Hammami, C. Croquet, J. Stoll, B. Rekik, and N. Gengler Genetic Diversity and Joint-Pedigree Analysis of Two Importing Holstein Populations J Dairy Sci, July 1, 2007; 90(7): 3530 - 3541. [Abstract] [Full Text] [PDF]

				J. Lassen, M. K. Sorensen, P. Madsen, and V. Ducrocq A Stochastic Simulation Study on Validation of an Approximate Multitrait Model Using Preadjusted Data for Prediction of Breeding Values J Dairy Sci, June 1, 2007; 90(6): 3002 - 3011. [Abstract] [Full Text] [PDF]

				M. Wolfova, J. Wolf, J. Kvapilik, and J. Kica Selection for Profit in Cattle: I. Economic Weights for Purebred Dairy Cattle in the Czech Republic J Dairy Sci, May 1, 2007; 90(5): 2442 - 2455. [Abstract] [Full Text] [PDF]

				S. Konig, S. Lessner, and H. Simianer Application of Controlling Instruments for Improvements in Cow Sire Selection J Dairy Sci, April 1, 2007; 90(4): 1967 - 1980. [Abstract] [Full Text] [PDF]

				W. M. Stoop, H. Bovenhuis, and J. A. M. van Arendonk Genetic Parameters for Milk Urea Nitrogen in Relation to Milk Production Traits J Dairy Sci, April 1, 2007; 90(4): 1981 - 1986. [Abstract] [Full Text] [PDF]

				E. Wall, M. P. Coffey, and S. Brotherstone The Relationship Between Body Energy Traits and Production and Fitness Traits in First-Lactation Dairy Cows J Dairy Sci, March 1, 2007; 90(3): 1527 - 1537. [Abstract] [Full Text] [PDF]

				P. Rozzi, F. Miglior, and K. J. Hand A Total Merit Selection Index for Ontario Organic Dairy Farmers J Dairy Sci, March 1, 2007; 90(3): 1584 - 1593. [Abstract] [Full Text] [PDF]

				D. P. Berry, J. M. Lee, K. A. Macdonald, K. Stafford, L. Matthews, and J. R. Roche Associations Among Body Condition Score, Body Weight, Somatic Cell Count, and Clinical Mastitis in Seasonally Calving Dairy Cattle J Dairy Sci, February 1, 2007; 90(2): 637 - 648. [Abstract] [Full Text] [PDF]

				B. Beerda, W. Ouweltjes, L. B. J. Sebek, J. J. Windig, and R. F. Veerkamp Effects of Genotype by Environment Interactions on Milk Yield, Energy Balance, and Protein Balance J Dairy Sci, January 1, 2007; 90(1): 219 - 228. [Abstract] [Full Text] [PDF]

				S. Brotherstone, M. P. Coffey, and G. Banos Genetic Parameters of Growth in Dairy Cattle and Associations Between Growth and Health Traits J Dairy Sci, January 1, 2007; 90(1): 444 - 450. [Abstract] [Full Text] [PDF]

				M. Ron, M. Cohen-Zinder, C. Peter, J. I. Weller, and G. Erhardt Short Communication: A Polymorphism in ABCG2 in Bos indicus and Bos taurus Cattle Breeds J Dairy Sci, December 1, 2006; 89(12): 4921 - 4923. [Abstract] [Full Text] [PDF]

				J. R. Roche, D. P. Berry, and E. S. Kolver Holstein-friesian strain and feed effects on milk production, body weight, and body condition score profiles in grazing dairy cows. J Dairy Sci, September 1, 2006; 89(9): 3532 - 3543. [Abstract] [Full Text] [PDF]

				H. M. Nielsen, L. G. Christensen, and J. Odegard A method to define breeding goals for sustainable dairy cattle production. J Dairy Sci, September 1, 2006; 89(9): 3615 - 3625. [Abstract] [Full Text] [PDF]

				H. A. Mulder and P. Bijma Benefits of Cooperation Between Breeding Programs in the Presence of Genotype by Environment Interaction J Dairy Sci, May 1, 2006; 89(5): 1727 - 1739. [Abstract] [Full Text] [PDF]

				H. A. Mulder, R. F. Veerkamp, B. J. Ducro, J. A. M. van Arendonk, and P. Bijma Optimization of Dairy Cattle Breeding Programs for Different Environments with Genotype by Environment Interaction J Dairy Sci, May 1, 2006; 89(5): 1740 - 1752. [Abstract] [Full Text] [PDF]

				J. F. Kearney, P. R. Amer, and B. Villanueva Cumulative Discounted Expressions of Sire Genotypes for the Complex Vertebral Malformation and {beta}-Casein Loci in Commercial Dairy Herds J Dairy Sci, December 1, 2005; 88(12): 4426 - 4433. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Corrected Table 1 Interpretive Summary An erratum has been published Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Miglior, F. Articles by Van Doormaal, B. J. Search for Related Content PubMed PubMed Citation Articles by Miglior, F. Articles by Van Doormaal, B. J.