Evidence map›Paper›PMID 42381685›Full record

ArticleJDS communications2026

Different goals, common ground: A global perspective on dairy breeding objectives.

D P Berry, F Miglior, C Schmidtmann, K Byskov, H Splittorff, M Rocland, R Finocchiaro, G De Jong, J Cole, J Graham and 20 more

Abstract read
In one paragraph

Article in JDS communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

30 authors.

D P BerryTeagasc, Animal & Grassland Research and Innovation Centre, Moorepark, Fermoy, Co. Cork, P61 P302, Ireland.
F MigliorCentre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada.
C SchmidtmannVereinigte Informationssysteme Tierhaltung w.V. (vit), 27283 Verden, Germany.
K ByskovThe Nordic Cattle Genetic Evaluation, DK-8200 Århus N, Denmark.
H SplittorffThe Nordic Cattle Genetic Evaluation, DK-8200 Århus N, Denmark.
M RoclandIdele, Institut de l'Élevage, 75012 Paris, France.
R FinocchiaroAssociazione Nazionale Allevatori della Razza Frisona, Bruna e Jersey Italiana, Via Bergamo, 292 26100 Cremona, Italy.
G De JongCooperative CRV u.a., 6842 BD Arnhem, the Netherlands.
J ColeCouncil on Dairy Cattle Breeding, Bowie, MD 20716.
J GrahamHolstein Association USA, Brattleboro, VT 05302-0808.
A BarencoSwissherdbook, CH-3052 Zollikofen, Switzerland.
T F O NeuenschwanderHolstein Switzerland, 1730 Posieux, Switzerland.
M WintersAgriculture and Horticulture Development Board, Coventry, CV3 4PE, United Kingdom.
P AmerAbacusBio Ltd., Cargill House, Dunedin 9016, New Zealand.
M AxfordDataGene, Bundoora, VIC 3083, Australia.
K WijnrocxTERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.
N GenglerTERRA Teaching and Research Center, University of Liège, Gembloux Agro-Bio Tech (ULiège-GxABT), 5030 Gembloux, Belgium.
B E MostertSA Stud Book, Bloemfontein, 9300, South Africa.
M KelleherIrish Cattle Breeding Federation, Ballincollig, County Cork, P31 D452, Ireland.
J A Jiménez-MonteroConafe, 28320 Pinto, Madrid, Spain.
O Gonzalez-RecioThe Roslin Institute and Royal (Dick) School of Veterinary Studies, Easter Bush Campus, Midlothian EH25 9RG, United Kingdom.
K PotočnikDepartment of Animal Science, University of Ljubljana, 1000 Ljubljana, Slovenia.
E EzraIsrael Cattle Breeders' Association, Caesarea Industrial Park, 3079820, Israel.
J WellerIsrael Cattle Breeders' Association, Caesarea Industrial Park, 3079820, Israel.
L BognárNational Association of Hungarian Holstein Friesian Breeders, H-1134 Budapest, Hungary.
K RzewuskaCentre for Genetics, Polish Federation of Cattle Breeders and Dairy Farmers, 00-515 Warsaw, Poland.
M PszczolaCentre for Genetics, Polish Federation of Cattle Breeders and Dairy Farmers, 00-515 Warsaw, Poland.
T OsawaNational Livestock Breeding Center, Nishigo-mura, Fukushima, 961-8511, Japan.
I AguilarInstituto Nacional de Investigación Agropecuaria, 90100 Montevideo, Uruguay.
R D López-CorreaFacultad de Agronomía, Universidad de la República, 12900 Montevideo, Uruguay.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A global comparison of dairy cow breeding objectives provides valuable insight into areas of convergence and divergence, helping identify populations with compatible breeding goals for sourcing germplasm to strengthen domestic genetic improvement programs. The objective of this study was primarily to compare the rankings of Holstein-Friesian artificial insemination sires across countries on the total merit index value of each country. The study also examined how different countries present estimates of genetic merit and how frequently they update their base populations; Denmark, Finland, and Sweden (DFS) were treated as a single group. The partial correlation among 22 indexes (i.e., 21 national indexes plus the Holstein Association USA Total Performance Index) was estimated for 49,450 Holstein(-Friesian) sires born post-2000 with a reliability >70%, after adjustment for genetic trends. The partial correlations among the ranking of sires on different indexes varied from 0.24 to 0.87 with 41% of the pairwise correlations being stronger than 0.70 but just 11% being stronger than 0.80. Notably, indexes designed for indoor confinement-based systems had, on average, weaker correlations with grazing-focused indexes from Ireland and New Zealand (0.48 to 0.50). Stronger average correlations (0.69) were observed among the ranking of sires on confinement-based indexes; the correlation between the Irish Economic Breeding Index and New Zealand Breeding Worth was 0.56. When limited to just the milk production components of the different indexes, the partial correlations among the ranking of sires on subindexes were, on average, 0.78, varying from 0.29 (Uruguay with Poland) to 0.96 (Japan with Spain). Countries differ in their approach to trait weighting. Across the 21 countries examined in this study, 38% derived the weights assigned to traits solely from economic models or functions, whereas an additional 29% of the countries adopted only a desired-gains approach. The remainder of countries adopted a hybrid strategy, applying economic values to certain traits, typically the production traits, while using desired gains for others (e.g., the Netherlands, DFS). In some cases, initial weights were derived from economic principles but subsequently adjusted to achieve specific desired gains (e.g., Canada, Australia, Uruguay). Of the 21 milk production subindexes compared, 8 had a negative weight on milk yield (i.e., Canada, DFS, United Kingdom, New Zealand, Australia, Belgium, Ireland, Uruguay), 4 had a positive value (i.e., United States, Poland, Spain, South Africa), whereas Germany, the Netherlands, Japan, France, Slovenia, Italy, Israel, Switzerland, and Hungary did not consider milk yield in their total merit indexes. With the exception of Ireland, United Kingdom, United States, Israel, and Uruguay who presented genetic evaluations of individual animals as PTA, genetic evaluations of milk production traits are presented as EBVs by all other countries. Of the 21 countries, 10% update their genetic evaluation base population more than once per year, 38% update it annually, 38% update it every 5 yr, and the remaining 14% update it periodically. Health traits are increasingly being considered for inclusion in future breeding objectives as are traits associated with both environmental impact and feed efficiency. The findings underscore how economic, biological, genetic, and policy factors shape national breeding objectives, helping interpret international differences in genetic trends and performance outcomes.

Identifiers

PMID42381685
PMCPMC13316385

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.