Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes-Reference-Cited by-同舟云学术

Predictive approach to optimize the number of visual graders for indirect selection of high-yielding Urochloa ruziziensis genotypes

Published:2020 Issue:3 Volume:20 Page:
ISSN:1984-7033
Container-title:Crop Breeding and Applied Biotechnology
language:
Short-container-title:Crop Breed. Appl. Biotechnol.

Author:

Fonseca Jales Mendes Oliveira¹,Nunes José Airton Rodrigues²^ORCID,Gonçalves Flavia Maria Avelar²,Souza Sobrinho Fausto de³,Benites Flávio Rodrigo Gandolfi³,Lima Teixeira Davi Henrique⁴

Affiliation:

1. Texas A&M University, USA

2. Universidade Federal de Lavras, Brazil

3. Embrapa Gado de Leite, Brazil

4. Universidade Federal Rural da Amazonia, Brazil

Publisher

FapUNIFESP (SciELO)

Subject

Agronomy and Crop Science,Biotechnology,General Medicine

Link

http://www.scielo.br/pdf/cbab/v20n3/1984-7033-cbab-20-03-e329220314.pdf

Reference30 articles.

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3. Fitting linear mixed-effects models using {lme4};Bates D;Journal of Statistical Software,2015

4. Comparison of selection methods among and within full-sibling progenies in Urochloa humidicola;Berchembrock YV;Grass Forage Science,2020

5. Visual selection for yield in cotton breeding programs;Bowman DT;Journal of Cotton Science,2004

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