data_ge

This dataset contain data on two variables assessed in 10 genotypes growing
in in 11 environments. The experimental design was a RCBD with 3
replicates(blocks). This data provide examples for several functions of
metan package.

data

Performs stability analysis of multi-environment
trial data using parametric and non-parametric methods. Parametric
methods includes Additive Main Effects and Multiplicative Interaction
(AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>,
Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang
(2003) <doi:10.1201/9781420040371>, joint Regression Analysis by
Eberhart & Russel (1966)
(<doi:10.2135/cropsci1966.0011183X000600010011x>), ecovalence by
Wricke (1965), genotypic confidence index by Annicchiarico (1992),
Murakami & Cruz's (2004) method <doi:10.12702/1984-7033.v04n01a02>,
stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>,
weighted average of absolute scores by Olivoto et al. (2019a)
<doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by
Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>.
Non-parametric methods includes superiority index by Lin & Binns
(1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic
stability by Huehn (1990)
<https://link.springer.com/article/10.1007/BF00024241>, TOP third
statistic by Fox et al. (1990) <doi:10.1007/BF00040364>, geometric
adaptability index described by Shahbazi (2019)
<doi:10.1016/j.scienta.2019.04.047>. Functions for computing
biometrical analysis such as path analysis, canonical correlation,
partial correlation, clustering analysis, and tools for inspecting,
manipulating, summarizing and plotting typical multi-environment
trial data are also provided.

Tiago Olivoto

metan

Multi Environment Trials Analysis

data_ge function

A tibble with 420 observations on the following 5 variables.<ul>
<li>ENV A factor with 14 levels; each level represents one cultivation
environment.</li>
<li>GEN A factor with 10 levels; each level represents one genotype.</li>
<li>REP A factor with 3 levels; each level represents one
replication/block.</li>
<li>GY A continuous variable (grain yield) observed in each plot.</li>
<li>HM A continuous variable (hectoliter mass) observed in each plot.</li>
</ul>

data_ge: Multi-environment trial of oat

Description

Arguments

Format