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Record W4315880760 · doi:10.1111/jbg.12755

The effect of new and ancestral inbreeding on milk production traits in Iranian Holstein cattle

2023· article· en· W4315880760 on OpenAlexaff
Reza Tohidi, R.I. Cue, Behrouz Mohammad Nazari, Rostam Pahlavan

Bibliographic record

VenueJournal of Animal Breeding and Genetics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsMcGill University
Fundersnot available
KeywordsInbreedingInbreeding depressionBiologyAnimal sciencePopulation fragmentationDairy cattlePopulationGeneticsDemography

Abstract

fetched live from OpenAlex

Inbreeding depression, the reduction of fitness and performance, is due to an increase in the mating of related individuals. Based on the purge hypothesis, inbreeding and breeding over generations reduce the effect of deleterious alleles responsible for inbreeding depression. Thus, recent inbreeding is assumed to be more harmful than ancestral inbreeding. This study aimed at evaluating the effects of new and ancestral inbreeding on milk, fat and protein production in Iranian Holstein cattle. The secondary objective was to examine the changes in predicted breeding values when the inbreeding effect was included in the model's analysis. To this end, inbreeding coefficients were calculated using the pedigree of 2,394,517 Holstein cattle to achieve these goals. In addition, 419,132 records of milk, fat and protein yields of first parity cows were collected to assess inbreeding depression and breeding values. The average inbreeding coefficients were 0.83% and 1.68% for the whole population and the inbred animals, respectively. A 1% increase in classical pedigree-based inbreeding coefficient was associated with a decrease of 11.99 kg in milk, 0.39 kg in fat and 0.29 kg in protein. The effect of ancestral inbreeding was more detrimental to performance traits than the effect of new inbreeding. This result contradicted the hypothesis of purging. By including the inbreeding coefficient in the model, the rank of animals remained unchanged, but the average predicted breeding values increased. In general, inbreeding depression was observed in Iranian Holstein cows; however, no evidence of purging was observed. The average of inbreeding coefficients was not high in this population, although accounting for inbreeding coefficients in the analytical model did significantly increase the predicted breeding values. It is recommended that the analytical model incorporate the inbreeding coefficient to improve the accuracy of genetic evaluation. In future studies, inbreeding depression should be assessed using genomic data for performance and reproduction traits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.269
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2023
Admission routes1
Has abstractyes

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