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

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...

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Autores principales: Ojango, J. M. K., Mrode, R., Rege, J. E. O., Mujibi, D., Strucken, E. M., Gibson, J., Mwai, O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: FASS and Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7753894/
https://www.ncbi.nlm.nih.gov/pubmed/30954253
http://dx.doi.org/10.3168/jds.2018-15807
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author Ojango, J. M. K.
Mrode, R.
Rege, J. E. O.
Mujibi, D.
Strucken, E. M.
Gibson, J.
Mwai, O.
author_facet Ojango, J. M. K.
Mrode, R.
Rege, J. E. O.
Mujibi, D.
Strucken, E. M.
Gibson, J.
Mwai, O.
author_sort Ojango, J. M. K.
collection PubMed
description 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.
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spelling pubmed-77538942020-12-28 Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships Ojango, J. M. K. Mrode, R. Rege, J. E. O. Mujibi, D. Strucken, E. M. Gibson, J. Mwai, O. J Dairy Sci Research 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. FASS and Elsevier 2019-04-03 /pmc/articles/PMC7753894/ /pubmed/30954253 http://dx.doi.org/10.3168/jds.2018-15807 Text en © 2019, The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research
Ojango, J. M. K.
Mrode, R.
Rege, J. E. O.
Mujibi, D.
Strucken, E. M.
Gibson, J.
Mwai, O.
Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships
title Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships
title_full Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships
title_fullStr Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships
title_full_unstemmed Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships
title_short Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships
title_sort genetic evaluation of test-day milk yields from smallholder dairy production systems in kenya using genomic relationships
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7753894/
https://www.ncbi.nlm.nih.gov/pubmed/30954253
http://dx.doi.org/10.3168/jds.2018-15807
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