Evaluation of Non-Genetic Factors Affecting Birth Weight of Kalahari Red Goats in South Africa

This study investigates the effect of non-genetic factors on the birth weight of Kalahari Red goats, a critical economic parameter in livestock production. Analysing data from 1902 goat kids born between 2008 and 2017 in different regions of South Africa, including the Northern (Gauteng, Mpumalanga, Northwest, and Limpopo), Southern (Eastern Cape and the eastern part of Western Cape), and Eastern (KwaZulu-Natal and the eastern part of Eastern Cape), the research employs a least-squares analysis of variance (ANOVA) using the General Linear Model (GLM) procedure. The results highlight the significance of various factors in determining birth weight. Season of birth, sire age, doe age, sex of the kid, breeder, year of birth, and birth type emerge as influential sources of variation (p < 0.05). Notably, region and kidding interval show no significant effect on birth weight (p > 0.05). Male kids generally have a higher average birth weight compared to females. Single births result in higher weights than multiple births (twins, triplets, and quadruplets). The study underscores the importance of considering these factors in genetic evaluation models. It emphasises their relevance in enhancing the understanding of prenatal growth and postnatal development in Kalahari Red goats within the context of livestock production.

Authors

Institutions

Publication Details

Journal
Suid-Afrikaanse tydskrif vir landbouvoorligting/South African journal of agricultural extension
Published
2024-10-18
DOI
https://doi.org/10.17159/2413-3221/2024/v52n4a16077
Citations
2
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
1.10
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of Non-Genetic Factors Affecting Birth Weight of Kalahari Red Goats in South Africa

C.B. Banga, M Ramoroka, Obert Tada
2 citations
Suid-Afrikaanse tydskrif vir landbouvoorligting/South African journal of agricultural extension
Genetic and phenotypic traits in livestock
1.10
article

Evaluation of Non-Genetic Factors Affecting Birth Weight of Kalahari Red Goats in South Africa

C.B. Banga, M Ramoroka, Obert Tada
article en
2 citations

Abstract

This study investigates the effect of non-genetic factors on the birth weight of Kalahari Red goats, a critical economic parameter in livestock production. Analysing data from 1902 goat kids born between 2008 and 2017 in different regions of South Africa, including the Northern (Gauteng, Mpumalanga, Northwest, and Limpopo), Southern (Eastern Cape and the eastern part of Western Cape), and Eastern (KwaZulu-Natal and the eastern part of Eastern Cape), the research employs a least-squares analysis of variance (ANOVA) using the General Linear Model (GLM) procedure. The results highlight the significance of various factors in determining birth weight. Season of birth, sire age, doe age, sex of the kid, breeder, year of birth, and birth type emerge as influential sources of variation (p < 0.05). Notably, region and kidding interval show no significant effect on birth weight (p > 0.05). Male kids generally have a higher average birth weight compared to females. Single births result in higher weights than multiple births (twins, triplets, and quadruplets). The study underscores the importance of considering these factors in genetic evaluation models. It emphasises their relevance in enhancing the understanding of prenatal growth and postnatal development in Kalahari Red goats within the context of livestock production.

Suid-Afrikaanse tydskrif vir landbouvoorligting/South African journal of agricultural extensionVol. 52(4)
University of Botswana (BW), University of the Free State (ZA), Botswana University of Agriculture and Natural Resources (BW), University of Limpopo (ZA)
Zero hunger
Openalex Percentile: Top 23%
Genetic and phenotypic traits in livestock
1.10
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.