PSXII-22 Genomic prediction accuracy for feed efficiency related traits using different pseudo-phenotypes, prediction and validation methods in Nellore cattle | Zendy

C. de U. Magnabosco | Zendy; Fernando Lopes | Zendy; Valentina Magnabosco | Zendy; Raysildo Barbosa Lôbo | Zendy; Letícia Silva Pereira | Zendy; Rafael Espigolan | Zendy; L. C. Brunes | Zendy

Open Access

PSXII-22 Genomic prediction accuracy for feed efficiency related traits using different pseudo-phenotypes, prediction and validation methods in Nellore cattle

Author(s) -

C. de U. Magnabosco,

Fernando Lopes,

Valentina Magnabosco,

Raysildo Barbosa Lôbo,

Letícia Silva Pereira,

Rafael Espigolan,

L. C. Brunes

Publication year - 2020

Publication title -

journal of animal science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.928

H-Index - 156

eISSN - 1525-3015

pISSN - 0021-8812

DOI - 10.1093/jas/skaa278.446

Subject(s) - residual feed intake , heritability , statistics , population , cross validation , residual , best linear unbiased prediction , genetic gain , mathematics , genomic selection , biology , feed conversion ratio , regression , zoology , body weight , selection (genetic algorithm) , genetic variation , computer science , genotype , genetics , artificial intelligence , medicine , single nucleotide polymorphism , algorithm , environmental health , gene , endocrinology

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