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© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Simple Summary

One of the indigenous sheep breeds that is primarily produced in Kenya under an extensive production system is the Red Maasai sheep. It has a reputation for being able to thrive in arid and semi-arid environments. A common belief is that, when contrasted with the Dorper breed, it performs poorly in terms of growth traits. Therefore, to enhance their growth traits, the Red Maasai are randomly crossed with Dorper. In contrast, the Red Maasai sheep breed outperformed the Dorper sheep breed in this study in terms of post-weaning growth rate, once more demonstrating early resilience and adaptation to local environmental conditions independent of maternal influence.

Abstract

This comparative study aimed to evaluate genetic and environmental factors’ effects on the growth traits of lambs in Dorper and Red Maasai (RedM) sheep breeds. The data analyzed contained the following measurements: birth weight (Bwt), weaning weight (Wwt), yearling weight (Ywt), birth type (single or twins), and details on each lamb’s dam (dam ID and age) and sire. Except for the RedM, whose birth weight decreased with time, both breeds generally showed an increase in other growth weights across the study period, with yearly variations affecting both breeds. Additionally, analysis by a linear mixed model with restricted maximum likelihood (REML) showed that only breed as a factor significantly (p < 0.05) influenced birth weight; breed, sex, and birth type all significantly (p < 0.05) influenced weaning weight, whereas season, sex, and dam age significantly (p < 0.05) influenced yearling weight. The RedM breed outperformed the Dorper breed in post-weaning growth rate, demonstrating early resilience and adaptation to local environmental factors independent of maternal influence. Breed and non-genetic factors play a vital role in the growth of lambs, and the results of this study offer an opportunity for improved farm management under an extensive production system and selection for the conservation of the indigenous Red Maasai breed.

Details

Title
An On-Station Analysis of Factors Affecting Growth Traits of Pure Red Maasai and Dorper Sheep Breeds under an Extensive Production System
Author
Wanjala, George 1   VIAFID ORCID Logo  ; Kichamu, Nelly 2 ; Ludovic Toma Cziszter 3   VIAFID ORCID Logo  ; Putri Kusuma Astuti 4   VIAFID ORCID Logo  ; Kusza, Szilvia 5   VIAFID ORCID Logo 

 Centre for Agricultural Genomics and Biotechnology, H-4032 Egyetem tér 1, 4032 Debrecen, Hungary; Doctoral School of Animal Science, University of Debrecen, H-4032 Böszörményi út 138, 4032 Debrecen, Hungary; Ministry of Agriculture, Livestock, Fisheries, Cooperatives and Irrigation, Directorate of Livestock Production, Bungoma P.O. Box 437-50200, Kenya 
 Doctoral School of Animal Science, University of Debrecen, H-4032 Böszörményi út 138, 4032 Debrecen, Hungary; Ministry of Agriculture Livestock, Fisheries and Cooperatives, State Department of Livestock Development, Naivasha Sheep and Goats Breeding Station, Naivasha P.O. Box 2238-20117, Kenya 
 Bioengineering Faculty of Animal Resources, Banat’s University of Agricultural Sciences and Veterinary Medicine “King Michael I of Romania”, Calea Aradului 119, 300645 Timisoara, Romania 
 Centre for Agricultural Genomics and Biotechnology, H-4032 Egyetem tér 1, 4032 Debrecen, Hungary; Doctoral School of Animal Science, University of Debrecen, H-4032 Böszörményi út 138, 4032 Debrecen, Hungary 
 Centre for Agricultural Genomics and Biotechnology, H-4032 Egyetem tér 1, 4032 Debrecen, Hungary 
First page
300
Publication year
2023
Publication date
2023
Publisher
MDPI AG
e-ISSN
20762615
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2767127193
Copyright
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.