Literature DB >> 18487672

Prediction of dairy bull fertility from field data: use of multiple services and identification and utilization of factors affecting bull fertility.

M T Kuhn1, J L Hutchison.   

Abstract

The objectives of this research were to assess the utility of multiple services, rather than first service only, and an expanded service sire term for prediction of bull conception rate (CR) by artificial insemination in the United States. The intent with the expanded service sire term was to determine whether accuracy could be improved by estimating factors affecting the bull's CR explicitly in the model and then formulating the bull's prediction as the sum of his own service sire solution along with the solutions for the other factors. Factors considered for the expanded service sire term included age of the bull at the time of mating, stud, inbreeding of the service sire, inbreeding of the mating (potential embryo), and an additive genetic effect. Both simulated and field data were used to study the objectives. In simulation, predictions were compared with true values, whereas with real data, predictions were compared with the bulls' average CR in set-aside data. Field data, using lactations 1 to 5, included 3,312,998 breedings of 737,626 Holstein cows in 1,419 herds distributed over 43 states and across 12 yr (1995 to 2006). The use of both multiple services and an expanded service sire term improved the accuracy of predictions. Multiple services contributed a 7 to 9% increase in accuracy, whereas the expanded service sire term improved accuracy by an estimated 12%. The amount of improvement in accuracy depends on the number of services available, but even for bulls with at least 500 matings, the combination of multiple services and an expanded service sire term can be expected to result in an overall increase in accuracy of at least 20%. Mean differences between predictions and bulls' average CR in set-aside data indicated that this improvement in accuracy can be brought about without introducing bias into the evaluations. Heritability estimates for artificial-insemination bull CR were essentially zero. Thus, use of an additive genetic effect for the service sire will not be of assistance in predicting bull fertility. All 4 of the other factors used in the expanded service sire term contributed to improved accuracy, although age of the bull at the time of mating was, by far, the major factor (correlation of 55.2% with future-year CR when included, 44.0% when not included). Allowing the stud effect to vary by year and using only the stud's most recent year solution in prediction were shown to be superior to using stud alone.

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Year:  2008        PMID: 18487672     DOI: 10.3168/jds.2007-0743

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  9 in total

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Journal:  Vet Sci       Date:  2022-05-06

2.  Unravelling the genomic architecture of bull fertility in Holstein cattle.

Authors:  Yi Han; Francisco Peñagaricano
Journal:  BMC Genet       Date:  2016-11-14       Impact factor: 2.797

3.  Whole-genome homozygosity mapping reveals candidate regions affecting bull fertility in US Holstein cattle.

Authors:  Juan Pablo Nani; Francisco Peñagaricano
Journal:  BMC Genomics       Date:  2020-05-04       Impact factor: 3.969

4.  Autosomal recessive loci contribute significantly to quantitative variation of male fertility in a dairy cattle population.

Authors:  Maya Hiltpold; Naveen Kumar Kadri; Fredi Janett; Ulrich Witschi; Fritz Schmitz-Hsu; Hubert Pausch
Journal:  BMC Genomics       Date:  2021-03-30       Impact factor: 3.969

5.  Identifying factors affecting age at first semen freezing and age at first semen use in Sahiwal bulls.

Authors:  B C Naha; A K Chakravarty; M A Mir; V Jamuna; A P Singh; D Maher
Journal:  Vet World       Date:  2015-07-29

6.  Optimizing age of bull at first use in relation to fertility of Murrah breeding bulls.

Authors:  M A Mir; A K Chakravarty; A K Gupta; B C Naha; V Jamuna; C S Patil; A P Singh
Journal:  Vet World       Date:  2015-04-21

7.  Whole-genome scan reveals significant non-additive effects for sire conception rate in Holstein cattle.

Authors:  Paula Nicolini; Rocío Amorín; Yi Han; Francisco Peñagaricano
Journal:  BMC Genet       Date:  2018-02-27       Impact factor: 2.797

8.  Genetic dissection of bull fertility in US Jersey dairy cattle.

Authors:  F M Rezende; G O Dietsch; F Peñagaricano
Journal:  Anim Genet       Date:  2018-08-14       Impact factor: 3.169

9.  Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes.

Authors:  Rostam Abdollahi-Arpanahi; Daniel Gianola; Francisco Peñagaricano
Journal:  Genet Sel Evol       Date:  2020-02-24       Impact factor: 4.297

  9 in total

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