Literature DB >> 30954253

Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships.

J M K Ojango1, R Mrode2, J E O Rege3, D Mujibi4, E M Strucken5, J Gibson5, O Mwai6.   

Abstract

Efforts to improve dairy production in smallholder farming systems of East Africa over the past decade have had limited impact because of the lack of records on performance to guide targeted breeding programs. Estimates of genetic parameters in these systems are lacking. Using data generated through a project ("Germplasm for Dairy Development in East Africa") in Kenya and a genomic relationship matrix from genotypic records, we examined the potential impact of different models handling contemporary groups or herd effects on estimates of genetic parameters using a fixed regression model (FRM) for test-day (TD) milk yields, and the covariance structure for TD milk yield at various stages of lactation for animals using a random regression model (RRM). Models in which herd groups were defined using production levels derived from the data fitted the data better than those in which herds were grouped depending on management practices or were random. Lactation curves obtained for animals under different production categories did not display the typical peak yield characteristic of improved dairy systems in developed countries. Heritability estimates for TD milk yields using the FRM varied greatly with the definition of contemporary herd groups, ranging from 0.05 ± 0.03 to 0.27 ± 0.05 (mean ± standard error). The analysis using the RRM fitted the data better than the FRM. The heritability estimates for specific TD yields obtained by the RRM were higher than those obtained by the FRM. Genetic correlations between TD yields were high and positive for measures within short consecutive intervals but decreased as the intervals between TD increased beyond 60 d and became negative with intervals of more than 5 mo. The magnitude of the genetic correlation estimates among TD records indicates that using TD milk records beyond a 60-d interval as repeated measures of the same trait for genetic evaluation of animals on smallholder farms would not be optimal. Although each individual smallholder farmer retains only a few animals, using the genomic relationship between animals to link the large number of farmers operating under specified environments provides a sufficiently large herd-group for which a breeding program could be developed. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Entities:  

Keywords:  dairy production; genomic relationship; random regression analyses; smallholder farm

Mesh:

Year:  2019        PMID: 30954253      PMCID: PMC7753894          DOI: 10.3168/jds.2018-15807

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


  14 in total

1.  Modeling lactation curves and estimation of genetic parameters for first lactation test-day records of French Holstein cows.

Authors:  T Druet; F Jaffrézic; D Boichard; V Ducrocq
Journal:  J Dairy Sci       Date:  2003-07       Impact factor: 4.034

2.  Genetic parameters for test day milk yields of first lactation Holstein cows by random regression models.

Authors:  C M R de Melo; I U Packer; C N Costa; P F Machado
Journal:  Animal       Date:  2007-03       Impact factor: 3.240

3.  Efficient methods to compute genomic predictions.

Authors:  P M VanRaden
Journal:  J Dairy Sci       Date:  2008-11       Impact factor: 4.034

4.  Fast model-based estimation of ancestry in unrelated individuals.

Authors:  David H Alexander; John Novembre; Kenneth Lange
Journal:  Genome Res       Date:  2009-07-31       Impact factor: 9.043

5.  adegenet 1.3-1: new tools for the analysis of genome-wide SNP data.

Authors:  Thibaut Jombart; Ismaïl Ahmed
Journal:  Bioinformatics       Date:  2011-09-16       Impact factor: 6.937

6.  Modelling of lactation curves of dairy cows based on monthly test day milk yield records under inconsistent milk recording scenarios.

Authors:  C B Wasike; A K Kahi; K J Peters
Journal:  Animal       Date:  2011-09       Impact factor: 3.240

7.  Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian in central Ethiopia: milk production traits.

Authors:  A Haile; B K Joshi; W Ayalew; A Tegegne; A Singh
Journal:  Animal       Date:  2009-04       Impact factor: 3.240

8.  Genetics of milk yield and fertility traits in Holstein-Friesian cattle on large-scale Kenyan farms.

Authors:  J M Ojango; G E Pollott
Journal:  J Anim Sci       Date:  2001-07       Impact factor: 3.159

9.  Estimation of milk production from smallholder dairy cattle in the coastal lowlands of Kenya.

Authors:  G R Muraguri; A McLeod; N Taylor
Journal:  Trop Anim Health Prod       Date:  2004-10       Impact factor: 1.559

10.  Genetic tests for estimating dairy breed proportion and parentage assignment in East African crossbred cattle.

Authors:  Eva M Strucken; Hawlader A Al-Mamun; Cecilia Esquivelzeta-Rabell; Cedric Gondro; Okeyo A Mwai; John P Gibson
Journal:  Genet Sel Evol       Date:  2017-09-12       Impact factor: 4.297

View more
  3 in total

1.  Genetic Parameter Estimation and Genome-Wide Association Study-Based Loci Identification of Milk-Related Traits in Chinese Holstein.

Authors:  Xubin Lu; Abdelaziz Adam Idriss Arbab; Ismail Mohamed Abdalla; Dingding Liu; Zhipeng Zhang; Tianle Xu; Guosheng Su; Zhangping Yang
Journal:  Front Genet       Date:  2022-01-28       Impact factor: 4.599

2.  A multi-breed GWAS for morphometric traits in four Beninese indigenous cattle breeds reveals loci associated with conformation, carcass and adaptive traits.

Authors:  Sèyi Fridaïus Ulrich Vanvanhossou; Carsten Scheper; Luc Hippolyte Dossa; Tong Yin; Kerstin Brügemann; Sven König
Journal:  BMC Genomics       Date:  2020-11-11       Impact factor: 3.969

3.  Spatial modelling improves genetic evaluation in smallholder breeding programs.

Authors:  Maria L Selle; Ingelin Steinsland; Owen Powell; John M Hickey; Gregor Gorjanc
Journal:  Genet Sel Evol       Date:  2020-11-16       Impact factor: 4.297

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.