Experimental precision of grain yield components and selection of superior common bean lines

Experimental precision of grain yield components and selection of superior common bean lines Genetically superior common bean lines will be efficiently selected with the use of more precise experimental statistics. The objectives of this study were to evaluate the experimental precision of grain yield and primary grain yield components in experiments to register common bean cultivars and identify more appropriate statistics for the selection of genetically superior common bean lines. For this purpose, 21 experiments were performed in a randomized block design in southern Brazil. A total of 156 common bean genotypes of the Mesoamerican and Andean gene pool were assessed between 1998 and 2015. Experimental precisions of grain yield and primary grain yield components were evaluated using 11 statistics. Grain yield, number of pods per plant, number of grains per pod, and mass of 100 grains were evaluated with greater experimental precision by the F-test value for genotype, heritability, coefficient of relative variation, and selective accuracy. Mass of 100 grains presented the highest experimental precision among the traits evaluated in this study. The F-test value for genotype, heritability, coefficient of relative variation, and selective accuracy allow the selection of common bean lines with genetic superiority for grain yield and primary grain yield components. Selective accuracy is the most appropriate statistic to select common bean lines with genetic superiority for grain yield and is recommended for breeding programs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Euphytica Springer Journals

Experimental precision of grain yield components and selection of superior common bean lines

Loading next page...
 
/lp/springer_journal/experimental-precision-of-grain-yield-components-and-selection-of-ohc0guXH3N
Publisher
Springer Netherlands
Copyright
Copyright © 2017 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Life Sciences; Plant Sciences; Plant Genetics and Genomics; Plant Pathology; Plant Physiology; Biotechnology
ISSN
0014-2336
eISSN
1573-5060
D.O.I.
10.1007/s10681-017-2078-y
Publisher site
See Article on Publisher Site

Abstract

Genetically superior common bean lines will be efficiently selected with the use of more precise experimental statistics. The objectives of this study were to evaluate the experimental precision of grain yield and primary grain yield components in experiments to register common bean cultivars and identify more appropriate statistics for the selection of genetically superior common bean lines. For this purpose, 21 experiments were performed in a randomized block design in southern Brazil. A total of 156 common bean genotypes of the Mesoamerican and Andean gene pool were assessed between 1998 and 2015. Experimental precisions of grain yield and primary grain yield components were evaluated using 11 statistics. Grain yield, number of pods per plant, number of grains per pod, and mass of 100 grains were evaluated with greater experimental precision by the F-test value for genotype, heritability, coefficient of relative variation, and selective accuracy. Mass of 100 grains presented the highest experimental precision among the traits evaluated in this study. The F-test value for genotype, heritability, coefficient of relative variation, and selective accuracy allow the selection of common bean lines with genetic superiority for grain yield and primary grain yield components. Selective accuracy is the most appropriate statistic to select common bean lines with genetic superiority for grain yield and is recommended for breeding programs.

Journal

EuphyticaSpringer Journals

Published: Nov 29, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off