Literature DB >> 27706593

Number of repetitions for evaluating technological traits in cotton genotypes.

L P Carvalho1, F J C Farias1, C L Morello1, J I S Rodrigues1, P E Teodoro2.   

Abstract

With the changes in spinning technology, technological cotton traits, such as fiber length, fiber uniformity, fiber strength, fineness, fiber maturity, percentage of fibers, and short fiber index, are of great importance for selecting cotton genotypes. However, for accurate discrimination of genotypes, it is important that these traits are evaluated with the best possible accuracy. The aim of this study was to determine the number of measurements (repetitions) needed to accurately assess technological traits of cotton genotypes. Seven experiments were conducted in four Brazilian States (Ceará, Rio Grande do Norte, Goiás, and Mato Grosso do Sul). We used nine brown and two white colored fiber lines in a randomized block design with four replications. After verifying the assumptions of residual normality and homogeneity of variances, analysis of variance was performed to estimate the repeatability coefficient and calculating the number of repetitions. Trials with four replications were found to be sufficient to identify superior cotton genotypes for all measured traits except short fiber index with a selective accuracy >90% and at least 81% accuracy in predicting their actual value. These results allow more accurate and reliable results in future researches with evaluating technological traits in cotton genotypes.

Mesh:

Year:  2016        PMID: 27706593     DOI: 10.4238/gmr.15038557

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  1 in total

1.  The number of measurements needed to obtain high reliability for traits related to enzymatic activities and photosynthetic compounds in soybean plants infected with Phakopsora pachyrhizi.

Authors:  Tássia Boeno de Oliveira; Leonardo de Azevedo Peixoto; Paulo Eduardo Teodoro; Amauri Alves de Alvarenga; Leonardo Lopes Bhering; Clara Beatriz Hoffmann-Campo
Journal:  PLoS One       Date:  2018-02-13       Impact factor: 3.240

  1 in total

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