Proposed genetic improvement strategies for dairy cattle in Kenya

Title
Proposed genetic improvement strategies for dairy cattle in Kenya
Publication Date
2021
Author(s)
Wahinya, P K
( author )
OrcID: https://orcid.org/0000-0003-4268-6744
Email: pwahiny2@une.edu.au
UNE Id une-id:pwahiny2
Swan, A A
( author )
OrcID: https://orcid.org/0000-0001-8048-3169
Email: aswan@une.edu.au
UNE Id une-id:aswan
Jeyaruban, M G
( author )
OrcID: https://orcid.org/0000-0002-0231-0120
Email: gjeyarub@une.edu.au
UNE Id une-id:gjeyarub
Abstract
Paper presented by Peter Wahinya
Type of document
Conference Publication
Language
en
Entity Type
Publication
Publisher
Association for the Advancement of Animal Breeding and Genetics (AAABG)
Place of publication
Armidale, Australia
UNE publication id
une:1959.11/51599
Abstract

Genotype by environment interactions and heterogeneity of variance may influence the effectiveness of breeding programs in developing countries. This study investigated optimization of dairy cattle breeding programs within Kenya for low, medium and high input and output production systems in the presence of genotype by environment interactions. Multi-trait selection index theory was applied using the SelAction software package to determine the optimum strategy that would maximise genetic gain across the three production systems. The breeding goal was to maximise overall gain for a breeding objective containing three traits: lactation milk yield; lactation fat yield and calving interval. Three selection strategies based on: 1) sire evaluation and selection within the high production systems only (single); 2) independent sire evaluation and selection within each production system (independent) and 3) sire evaluation across all production systems (joint), were evaluated under scenarios using progeny test information and genomic information. The joint strategy maximised the overall economic gain (1583 Kes) while the single strategy generated the least overall gain (1311 Kes). The dairy industry in Kenya would therefore benefit from implementing production system specific breeding strategies for bull evaluation and selection. In addition, implementing genomic selection could speed up the rate of genetic gain compared to progeny testing due to reductions in generation interval and higher selection accuracy with a moderately large reference population.

Link
Citation
Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.24, p. 414-418
ISSN
1328-3227
Start page
414
End page
418

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