multienv: Multi- evironment data

In plantbreeding: Analysis and visualization of data from plant breeding and genetics experiments

Description

Simulated Multi- evironment data for stability and Additive Main Effects and Multiplicative Interaction (AMMI) analysis.

Usage

data(multienv)

Format

A data frame with 150 observations on the following 4 variables.

yield

yield - Y variable

replication

replication

genotypes

genotype: G1 G10 G2 G3 G4 G5 G6 G7 G8 G9

environments

environments: CA CB CC MN SD

References

Gauch H.G.(1992). Statistical analysis of regional yield trials:AMMI analysis of factorial designs. Elsevier, Amsterdam.

Gauch H.G. (2006). Statistical analysis of yield trials by AMMI and GGE. Crop Sci. 46:1488-1500.

Gauch, H.G., Zobel.R.W. (1996). AMMI analysis of yield trials. p.85-122. In M.S. Kang and H.G. Gauch, Jr. (ed.) Genotype x byenvironment interaction. CRC Press, Boca Raton, FL.

Eberhart S.A., Russell W.A. (1966) Stability parameters for comparing varieties. Crop Sci. 6: 36-40.

Singh R.K., Chaudhary B.D.(1985) Biometrical Methods in Quantitative Genetics Analysis, Kalyani Publishers

Kang M.S., Aggarwal V.D., Chirwa R.M.(2006) Adaptability and stability of bean cultivars as determined via yield-stability statistic and GGE biplot analysis. J. Crop Improv. 15:97-120

Examples

# stability analysis 
data(multienv)
out <- stability (dataframe = multienv , yvar = "yield", genotypes = "genotypes",
 environments = "environments", replication =  "replication")
out
# AMMI analysis 
results <- ammi.full(dataframe = multienv , environment = "environments",
 genotype = "genotypes", replication = "replication", yvar = "yield")
print(results)

plantbreeding documentation built on May 2, 2019, 4:54 p.m.