Multi-trait selection in Holstein cows

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Published: Dec 1, 2020

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Arelis Hernández
Instituto de Ciencia Animal, Apartado Postal 24, San José de Las Lajas, Mayabeque, Cuba.
Raquel Ponce de León
Instituto de Ciencia Animal, Apartado Postal 24, San José de Las Lajas, Mayabeque, Cuba.

Abstract

The phenotypic and genealogical data of 1 571 Holstein cows located in three livestock enterprises during the years 1984 to 2016 were used. The purpose of this study was to carry out the multi-trait selection of dairy production, reproduction and longevity traits by means of the preparation of selection indexes (SI) through the analysis of main components (MC). Correlations and breeding values (BV) were estimated for the traits: cumulative milk production up to 305 days (BVL305), duration of lactation
(BVDL), age at first parturition (BVAP1), gestation parturition interval (BVGPI), accumulated milk per life (BVTML) and productive life (BVPL) by means of a multi-trait animal model. The SPSS statistical package was used to perform the MC analysis, for which the BV were standardized, and the Kaiser criterion was used to select the MC that explains the greatest genetic variation. The genetic correlations between L305, TML and DL showed mean values (0.55, 0.47 and 0.27), and between GPI and PL of 0.29. The first two main components (MC1, MC2) were those that obtained the Kaiser criterion and explained 53.7 % of the total variance of the BV. Linear correlations between BVs with each main component showed that
L305, DL and TML were related with the MC1, and GPI and PL to MC2. It is concluded that in Holstein cows it is possible to perform multi-trait selection by constructing selection indexes based on the first two MCs, since they showed considerable genetic variation.
Key words: main component analysis, dairy cattle, selection indexes

Article Details

How to Cite
Hernández, A., & Ponce de León, R. (2020). Multi-trait selection in Holstein cows. Cuban Journal of Agricultural Science, 54(4). Retrieved from https://cjascience.com/index.php/CJAS/article/view/994
Issue
Vol. 54 No. 4 (2020): Cuban Journal of Agricultural Science
Section
Genetics

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