TE1: Mixed model analysis of individuals trials

In gcostaneto/YieldTrial: Phenotypic analysis and diagnosis over multienvironment trials in plant breeding

Description

Perform a mixed model analysis of each individual trial within a MET dataset.

Usage

TE1(df, y, rep, gen, trials, accuracy)

Arguments

df	dataframe object
y	numeric, column associated to evaluated trait within df object
rep	factor, column associated to replication or blocks levels within df object
gen	factor, column associated to genotype levels within df object
trials	factor, column associated to environment levels within df object
accuracy	numeric, a single value (from 0 to 1) indicating the expected threshold accuracy (we recommend the use of 0.7)

Author(s)

Germano Martins F. Costa Neto <[e-mail]>

References

1. Colombari Filho JM, de Resende MDV, de Morais OP, de Castro AP, Guimarães ÉP, Pereira JA, et al. Upland rice breeding in Brazil: A simultaneous genotypic evaluation of stability, adaptability and grain yield. Euphytica. 2013;192(1):117–29.

2. Resende MDV, Duarte JB. Precisão e controle de qualidade em experimentos de avaliação de cultivares. Pesquisa Agropecuária Tropical. 2007;37(3):182–94.

Examples

data(MET_maize)
trial.evalut-trialEvalut(y = "YIELD", trials = "ENV", accuracy=0.7,
                         gen = "GEN", rep = "REP", df = MET.maize)
head(trial.evalut)

gcostaneto/YieldTrial documentation built on June 10, 2019, 5:45 a.m.