Evidence map›Paper›PMID 42180162›Full record

ArticleVeterinary medicine international2026

Inbreeding Implications on Genetic Diversity and Population Evolution of South American Brown Swiss Cattle.

Luis F Cartuche-Macas, Miguel A Gutierrez-Reinoso, Manuel Garcia-Herreros

Abstract read
In one paragraph

Article in Veterinary medicine international, 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

3 authors.

Luis F Cartuche-MacasVeterinary Medicine Degree, Escuela Superior Politécnica Agropecuaria de Manabí Manuel Félix López (ESPAM), Calceta, 130602, Ecuador.ORCID https://orcid.org/0000-0003-3278-1238
Miguel A Gutierrez-ReinosoVeterinary Medicine Degree, Facultad de Ciencias Agropecuarias y Recursos Naturales, Universidad Técnica de Cotopaxi, (UTC), Latacunga, 050150, Ecuador.ORCID https://orcid.org/0000-0002-8418-3312
Manuel Garcia-HerrerosNational Institute for Agricultural and Veterinary Research (INIAV), Santarém, 2005-424, Portugal.ORCID https://orcid.org/0000-0002-0911-6689

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inbreeding is a critical issue in both conservation and animal breeding, as it can severely impact survival, reproductive success and genetic diversity (GD) in domestic species. The Brown Swiss cattle were introduced in South America around a century ago; however, the breeding scheme-derived consequences have been neglected by breeders for numerous generations. The present research aimed to elucidate the population evolution, inbreeding and GD in introduced South American Brown Swiss cattle using genealogical databases. The study was based on official registered records from 8686 animals across multiple generations (until 2023). Different estimates related to population structure, including pedigree completeness, inbreeding rate (F), effective population size (Ne) and generation interval (GI), among others, were evaluated. Moreover, the characterisation of the probabilities of gene origin (effective number of founders [fe] and ancestors [fa]) and the GD loss were assessed. The results revealed that in the last period, GMax was 12.33, while the GCom and GEqu were 2.37 and 5.43, respectively. The mean GI was 7.11 years, and the mean F of 1.27% in the historical and the most recent populations was 5.60 and 2.78, respectively. The F increased between 0.10% and 0.50% per chronological period, showing an increasing tendency of the inbreeding values throughout time. The average Ne-census, Ne- ΔF

Indexed as

Brown Swisscattlediversity lossgenetic variabilityinbreeding

Identifiers

PMID42180162
PMCPMC13198180

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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.