Phenotypic and genetic parameter estimates for early growth, growth rate and growth efficiency-related traits of Fogera cattle in Ethiopia.

Animals Birth Weight / genetics Body Weight / genetics Cattle / genetics Ethiopia Phenotype Weaning
Fogera cattle Klieber ratio genetic parameter estimates growth efficiency growth performance

Journal

Veterinary medicine and science
ISSN: 2053-1095
Titre abrégé: Vet Med Sci
Pays: England
ID NLM: 101678837

Informations de publication

Date de publication:
01 2022
Historique:
pubmed: 5 9 2021
medline: 1 3 2022
entrez: 4 9 2021
Statut: ppublish

Résumé

Understanding the phenotypic and genetic parameter estimates of growth traits is important for an effective livestock genetic improvement programme. In this study, we evaluated the phenotypic performances and estimated genetic parameters for birthweight (BWT), weaning weight (WWT), pre-weaning average daily gain (PADG), pre-weaning Kleiber ratio (PKR), pre-weaning growth efficiency (PGE) and pre-weaning relative growth rate (PRGR) of Fogera cattle in Ethiopia. Growth data collected from 2000 to 2018 in Andassa Livestock Research Center were used for the study. General linear model of SAS 9.1 was used to estimate the least squares mean (LSM) ± standard error (SE) for phenotypic performances, and AI-REML of Wombat software combined with a series of five single-trait animal models to estimate phenotypic variance and its direct, maternal and residual components. Calf sex, calf birth season and calf birth year were the fixed effects considered. The overall LSM ± SE BWT, WWT, PADG, PKR, PGE and PRGR were 21.28 ± 0.05 kg, 97.99 ± 0.67 kg, 320.29 ± 2.79 g, 10.10 ± 0.04, 3.51 ± 0.35 and 1.95 ± 0.00, respectively. All the fixed effects considered significantly (p < 0.001) affected all the traits. The direct heritability estimates for BWT, WWT, PADG, PKR, PGE and PRGR were 0.21 ± 0.07, 0.26 ± 0.01, 0.55 ± 0.19, 0.53 ± 0.18, 0.33 ± 0.00 and 0.50 ± 0.00, respectively. The genetic correlations among the traits ranged from negative (-0.20 ± 0.04; BWT-PKR) to positive (0.99 ± 0.00; BW-PGE, BW-GR, WWT-PGE, WWT-PGR, ADG-PGR, PKR-PGR, PKR-PGE and PGE-PGR). Similarly, the phenotypic correlations ranged from -0.03 ± 0.20 to 0.99 ± 0.01; BWT-PGE, BWT-PRGR, WWT-PGE, WWT-PRGR, PKR-PGE, PKR-PRGR and PGE-PRGR). The positive and larger phenotypic and genetic correlations between most of the traits implied that selection based on one trait could improve the other traits. However, the negative phenotypic and genetic correlation between BWT-PKRA implies that selection of Fogera calves based on either of the traits has an adverse effect on the other. Therefore, caution should be taken when designing the selection criteria for growth improvement.

Sections du résumé

BACKGROUND
Understanding the phenotypic and genetic parameter estimates of growth traits is important for an effective livestock genetic improvement programme.
OBJECTIVES
In this study, we evaluated the phenotypic performances and estimated genetic parameters for birthweight (BWT), weaning weight (WWT), pre-weaning average daily gain (PADG), pre-weaning Kleiber ratio (PKR), pre-weaning growth efficiency (PGE) and pre-weaning relative growth rate (PRGR) of Fogera cattle in Ethiopia.
METHODS
Growth data collected from 2000 to 2018 in Andassa Livestock Research Center were used for the study. General linear model of SAS 9.1 was used to estimate the least squares mean (LSM) ± standard error (SE) for phenotypic performances, and AI-REML of Wombat software combined with a series of five single-trait animal models to estimate phenotypic variance and its direct, maternal and residual components. Calf sex, calf birth season and calf birth year were the fixed effects considered.
RESULTS
The overall LSM ± SE BWT, WWT, PADG, PKR, PGE and PRGR were 21.28 ± 0.05 kg, 97.99 ± 0.67 kg, 320.29 ± 2.79 g, 10.10 ± 0.04, 3.51 ± 0.35 and 1.95 ± 0.00, respectively. All the fixed effects considered significantly (p < 0.001) affected all the traits. The direct heritability estimates for BWT, WWT, PADG, PKR, PGE and PRGR were 0.21 ± 0.07, 0.26 ± 0.01, 0.55 ± 0.19, 0.53 ± 0.18, 0.33 ± 0.00 and 0.50 ± 0.00, respectively. The genetic correlations among the traits ranged from negative (-0.20 ± 0.04; BWT-PKR) to positive (0.99 ± 0.00; BW-PGE, BW-GR, WWT-PGE, WWT-PGR, ADG-PGR, PKR-PGR, PKR-PGE and PGE-PGR). Similarly, the phenotypic correlations ranged from -0.03 ± 0.20 to 0.99 ± 0.01; BWT-PGE, BWT-PRGR, WWT-PGE, WWT-PRGR, PKR-PGE, PKR-PRGR and PGE-PRGR).
CONCLUSION
The positive and larger phenotypic and genetic correlations between most of the traits implied that selection based on one trait could improve the other traits. However, the negative phenotypic and genetic correlation between BWT-PKRA implies that selection of Fogera calves based on either of the traits has an adverse effect on the other. Therefore, caution should be taken when designing the selection criteria for growth improvement.

Identifiants

DOI: 10.1002/vms3.628 PMID: 34480429 PMC: PMC8788963
pubmed: 34480429
doi: 10.1002/vms3.628
pmc: PMC8788963
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

387-397

Informations de copyright

© 2021 The Authors. Veterinary Medicine and Science published by John Wiley & Sons Ltd.

Références

J Anim Breed Genet. 2010 Feb;127(1):26-33
pubmed: 20074184
J Anim Breed Genet. 2011 Apr;128(2):133-40
pubmed: 21385228
Trop Anim Health Prod. 2017 Oct;49(7):1431-1438
pubmed: 28691136
Trop Anim Health Prod. 2016 Mar;48(3):667-72
pubmed: 26739342
Physiol Rev. 1947 Oct;27(4):511-41
pubmed: 20267758
Animal. 2017 Jun;11(6):991-999
pubmed: 27821224
J Mol Endocrinol. 1999 Oct;23(2):209-21
pubmed: 10514558
Vet Med Sci. 2022 Jan;8(1):387-397
pubmed: 34480429

Auteurs

Demelash Kassahun (D)

Animal Production and Technology Department, College of Agriculture and Environmental Sciences, Bahir Dar University, Bahir Dar, Ethiopia.
Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Mengistie Taye (M)

Animal Production and Technology Department, College of Agriculture and Environmental Sciences, Bahir Dar University, Bahir Dar, Ethiopia.
Biotechnolgy Research Institute, Bahir Dar University, Bahir Dar, Ethiopia.
ORCID: 0000-0001-6795-9943

Damitie Kebede (D)

Animal Production and Technology Department, College of Agriculture and Environmental Sciences, Bahir Dar University, Bahir Dar, Ethiopia.

Mekonen Tilahun (M)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Assemu Tesfa (A)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Addisu Bitew (A)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Adebabay Kebede (A)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Mulugeta Meseret (M)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Eyasu Lakew (E)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Tewodros Bimrow (T)

Andassa Livestock Research Center, Amhara Regional Agricultural Research Institute, Bahir Dar, Ethiopia.

Aynalem Haile (A)

International Center for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia.

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Classifications MeSH

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