aug.rowcol: Analysis of Augmented row and column design

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

Description

The function implements analysis of augmented random row and column design.

Usage

aug.rowcol(dataframe, rows, columns, genotypes, yield)

Arguments

dataframe	dataframe object with at least columns with information of rows, columns, genotypes / entries/ varieties / or treatments and yield (yvariable)
rows	name of numbericnumeric variable with rows number
columns	name of numeric variable with column number
genotypes	name of column with with treatments / genotypes (factor)
yield	name of column with yield or any y variable

Value

ANOVA	Analysis of Variance Table
Adjustment	Original and Adjusted Phenotypic value
se_check	Difference between check means
se_within	Difference adjusted yield of two genotypes / varitiesvarieties / entries in same row or column
se_diff	Difference between two genotypes / varieties / entries in different rows or blocks
se_geno_check	Difference between two genotypes / varieties / entries and a check mean

Author(s)

Umesh Rosyara

Examples

# example 1
data(rowcoldata)
outp <- aug.rowcol(dataframe = rowcoldata, rows = "rows", columns = "columns", 
genotypes = "genotypes", yield = "yield")

outp$ANOVA # analysis of variance 
outp$Adjustment # adjusted values 

# calculation of means
stab <- aggregate( yield ~ genotypes, data=rowcoldata, FUN= mean)

hist(stab$yield, col = "cadetblue", xlab = "Grain Yield", 
main = "Mean yields from Augmented Yield Trial")

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