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Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Estimates of genetic parameters, principal components and cluster analysis for milk yield and body weight in Guzera cattle

Manuela Pires Monteiro Gama A , Rodrigo Pelicioni Savegnago https://orcid.org/0000-0002-6551-2168 B * , Henrique Torres Ventura C , Mariana Alencar Pereira C , Luara Afonso Freitas A , Claudia Cristina Paro Paz A D and Lenira El Faro D
+ Author Affiliations
- Author Affiliations

A Departamento de Genética, FMRP/USP, Ribeirão Preto, São Paulo, Brazil.

B Department of Animal Science, Michigan State University, East Lansing, MI 48824, USA.

C Associação Brasileira de Criadores de Zebu, ABCZ, Uberaba, Minas Gerais, Brazil.

D Instituto de Zootecnia, Centro Avançado de Pesquisa de Bovinos de Corte, Sertãozinho, São Paulo, Brazil.

* Correspondence to: rodrigopsa@yahoo.com

Handling Editor: Kim Bunter

Animal Production Science 62(3) 225-233 https://doi.org/10.1071/AN20041
Submitted: 31 January 2020  Accepted: 27 October 2021   Published: 29 November 2021

© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing

Abstract

Context: The estimation of genetic parameters for traits related to the production of milk, beef or both may assist in defining the selection criteria and objectives of the breeding program, as well as in the identification and selection of genetically superior animals.

Aims: The objectives of this study were to estimate genetic parameters for body weight and 305-day milk yield of Guzera cattle and to perform cluster analysis on the basis of estimated breeding values for these traits, to identify groups of animals that could be selected for the production of beef, milk or dual purpose.

Methods: Body weights (N = 253 012) of males and females were ecorded at 120 days of age (BW120), at weaning (WW), at 365 days (BW365), at yearling stage (YW) and at 24 months (BW24), and 6237 complete lactations (MY305) of 4723 cows were used to estimate the genetic parameters. The bi-trait animal models included direct additive genetic, maternal permanent environmental and temporary random effects for body weights and additive genetic, permanent environmental and temporary environmental random effects for MY305. The fixed effects for all the traits were contemporary group and age of cow at calving.

Key results: The estimates of heritability ranged from 0.14 ± 0.01 for WW to 0.23 ± 0.01 for MY305. The genetic correlations between body weights at different ages and milk yield were positive and ranged from 0.27 ± 0.11 to 0.38 ± 0.19. Two principal components explained 86.74% of the total genetic variance among the traits.

Conclusions: Cluster analysis identified four different clusters and showed that the Guzera breed had bulls with different genetic patterns that permits genetic selection for beef, milk or dual purpose.

Implications: The genetic correlations of the present study suggest that selection to increase milk yield will lead to a slight genetic gain in the same direction for body weight at different ages, in contrast to reports from some other studies.

Keywords: beef cattle, breeding values, dual-purpose, genetic selection, heritability, milk production, multivariate analysis, principal component.


References

Albuquerque LG, Meyer K (2001) Estimates of direct and maternal genetic effects for weights from birth to 600 days of age in Nelore cattle. Journal of Animal Breeding and Genetics 118, 83–92.
Estimates of direct and maternal genetic effects for weights from birth to 600 days of age in Nelore cattle.Crossref | GoogleScholarGoogle Scholar |

Ayalew W, Aliy M, Negussie E (2017) Estimation of genetic parameters of the productive and reproductive traits in Ethiopian Holstein using multi-trait models. Asian-Australasian Journal of Animal Science 30, 1550–1556.
Estimation of genetic parameters of the productive and reproductive traits in Ethiopian Holstein using multi-trait models.Crossref | GoogleScholarGoogle Scholar |

Bainy AM, Savegnago RP, Freitas LA, Nunes BN, Rosa JO, Ledur MC, Munari DP (2017) Estimates of genetic parameters and cluster analyses for carcass and beef quality traits in birds. Pesquisa Agropecuária Brasileira 52, 205–213.
Estimates of genetic parameters and cluster analyses for carcass and beef quality traits in birds.Crossref | GoogleScholarGoogle Scholar |

Charrad M, Ghazzali N, Boiteau V, Niknafs A (2014) NbClust: an R package for determining the relevant number of clusters in a data set. Journal of Statistical Software 61, 1–36.
NbClust: an R package for determining the relevant number of clusters in a data set.Crossref | GoogleScholarGoogle Scholar |

Cruz DAC, Peixoto MGCD, Bruneli FAT, Bignardi AB, El Faro L (2015) Genetics parameters of test-day milk yield in Guzerá cattle under tropical conditions. Genetics and Molecular Research 14, 13618–13624.
Genetics parameters of test-day milk yield in Guzerá cattle under tropical conditions.Crossref | GoogleScholarGoogle Scholar |

Hair JF, Black WC, Babin BJ, Anderson RE (2009) ‘Multivariate data analysis.’, 7th edn. (Prentice Hall)

Hartigan JA (1975) ‘Clustering algorithms.’ (John Wiley & Sons)

Hartigan JA, Wong MA (1979) Algorithm AS 136: a k-means clustering algorithm. Journal of Applied Statistics 28, 100–108.
Algorithm AS 136: a k-means clustering algorithm.Crossref | GoogleScholarGoogle Scholar |

Johnson RA, Wichern DW (2007) ‘Applied multivariate statistical analysis.’, 6th edn. (Pearson Prentice Hall)

Kaiser HF (1960) The application of electronic computers to factor analysis. Educational and Psychological Measurement 20, 141–151.
The application of electronic computers to factor analysis.Crossref | GoogleScholarGoogle Scholar |

Lin CY, McAllister AJ, Lee AJ (1985) Multitrait estimation of relationships of first-lactation yields to body weight changes in Holstein heifers. Journal of Dairy Science 68, 2954–2963.
Multitrait estimation of relationships of first-lactation yields to body weight changes in Holstein heifers.Crossref | GoogleScholarGoogle Scholar | 4078123PubMed |

Madalena FE (2012) Animal breeding and development – South American perspective. Journal of Animal Breeding and Genetics 129, 171–172.
Animal breeding and development – South American perspective.Crossref | GoogleScholarGoogle Scholar | 22583321PubMed |

Meyer K (1992) Variance components due to direct and maternal effects for growth traits of Australian beef cattle. Livestock Production Science 31, 179–204.
Variance components due to direct and maternal effects for growth traits of Australian beef cattle.Crossref | GoogleScholarGoogle Scholar |

Meyer K (2007) Wombat – a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML). Journal of Zhejiang University Science B 8, 815–821.
Wombat – a tool for mixed model analyses in quantitative genetics by restricted maximum likelihood (REML).Crossref | GoogleScholarGoogle Scholar | 17973343PubMed |

Peixoto MGCD, Verneque RS, Teodoro RL, Penna VM, Martinez ML (2006) Genetic trend for milk yield in Guzerat herds participating in progeny testing and MOET nucleus schemes. Genetic and Molecular Research 5, 454–465.

Pelicioni LC, Albuquerque LG, Queiroz SA (2009) Estimates of covariance components for body weights from birth to 365 days of age in Guzera cattle, using random regression models. Revista Brasileira de Zootecnia 38, 50–60.
Estimates of covariance components for body weights from birth to 365 days of age in Guzera cattle, using random regression models.Crossref | GoogleScholarGoogle Scholar |

Pelicioni LC, Queiroz SA, Albuquerque LG (2003) Estimates of genetic parameters for birth and monthly weights till 450 days in Guzerá cattle. Archivos Latinoamericanos de Producción Animal 11, 34–39.

Penasa M, Cecchinato A, Dal Zotto R, Blair HT, López-Villalobos N, Bittante G (2012) Direct and maternal genetic effects for body weight and price of calves sold for veal production. Journal of Animal Science 90, 3385–3391.
Direct and maternal genetic effects for body weight and price of calves sold for veal production.Crossref | GoogleScholarGoogle Scholar | 22585805PubMed |

Pimenta Filho EC, Martins GA, Sarmento JLR, Ribeiro MN, Martins Filho R (2001) Heritability of maternal and direct effects of growth traits in Guzera herds at Paraiba State, Brazil. Revista Brasileira de Zootecnia 30, 1220–1223.
Heritability of maternal and direct effects of growth traits in Guzera herds at Paraiba State, Brazil.Crossref | GoogleScholarGoogle Scholar |

Rencher AC (2002) ‘Methods of multivariate analysis.’ (Wiley-Interscience)

Santos DJA, Peixoto MGCD, Aspilcueta Borquis RR, Panetto JCC, El Faro L, Tonhati H (2014) Predicting breeding values for milk yield of Guzerá (Bos indicus) cows using random regression models. Livestock Science 167, 41–50.
Predicting breeding values for milk yield of Guzerá (Bos indicus) cows using random regression models.Crossref | GoogleScholarGoogle Scholar |

Santos DJA, Peixoto MGCD, Borquis RRA, Verneque RS, Panetto JCC, Tonhati H (2013) Genetic parameters for test-day milk yield, 305-day milk yield and lactation length in Guzerat cows. Livestock Science 152, 114–119.
Genetic parameters for test-day milk yield, 305-day milk yield and lactation length in Guzerat cows.Crossref | GoogleScholarGoogle Scholar |

SAS (2008) Statistical Analysis Systems Institute. Version 9.1 (SAS Institute Inc.: Cary, NC, USA)

Savegnago RP, Nascimento GB, Rosa GJM, Carneiro RLR, Sesana RC, El Faro L, Munari DP (2016) Cluster analyses to explore the genetic curve pattern for milk yield of Holstein. Livestock Science 183, 28–32.
Cluster analyses to explore the genetic curve pattern for milk yield of Holstein.Crossref | GoogleScholarGoogle Scholar |

Tosh JJ, Kemp RA, Ward DR (1999) Estimates of direct and maternal genetic parameters for weight traits and backfat thickness in a multibreed population of beef cattle. Canadian Journal of Animal Science 79, 433–439.
Estimates of direct and maternal genetic parameters for weight traits and backfat thickness in a multibreed population of beef cattle.Crossref | GoogleScholarGoogle Scholar |

Ward JH (1963) Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58, 236–244.
Hierarchical grouping to optimize an objective function.Crossref | GoogleScholarGoogle Scholar |

Wolfinger R (1993) Covariance structure in general mixed models. Communications in Statistics – Simulation and Computation 22, 1079–1106.
Covariance structure in general mixed models.Crossref | GoogleScholarGoogle Scholar |