Welcome to Line by Tester Analysis

Here we learn on how to conduct Line by Tester analysis which is the most common design used by Plant Breeders to estimate Combining ability and Genetic variances.

Contents

Data Arrangement and Structure

Method 1

Method 2

Setup R for your Computer

R is a programming language and free software used for Statistical computation.

Download and Install the R base package
Next download and install the free version of R Studio which is user friendly interface for R.

Data Arrangement and Structure

To begin the analysis first arrange the data into four columns namely replication, line, tester and yield in an excel file.

Note that an additional coloumn of blocks has to be added if its Incomplete Block Design (IBD).

Importing data in R

After you have created your data file, paste it in your Working Directory. By default your working directory is Documents folder. We import the excel data file (Example: ltdata) by,

ltdata = read_excel("ltdata.xlsx")

You can just click on Import dataset and select your excel file.

Viewing Imported data

View(ltdata)

Method 1

By agricolae package

Install package agricolae

install.packages('agricolae', dependencies=True)

Loading the installed package

library(agricolae)

Understanding the struture of dataset.

str(ltdata)

Note: There are two example Line x Tester dataset in agricole package named as heterosis and LxT. You can load them by,

data(heterosis)

data(LxT)

Now using the function lineXtester of the agricolae package we perform Line x Tester analysis.

result = with(ltdata,lineXtester(replication, line, tester, yield))

Results are displayed which can be copied and saved.

Analysing heterosis dataset.

result2 = with(heterosis,lineXtester(Replication, Female, Male, v1))

Method 2

By plantbreeding package

Line x Tester analysis by plantbreeding package

Install package plantbreeding

install.packages("plantbreeding", repos="http://R-Forge.R-project.org", dependencies= T)

Loading the installed package

library(plantbreeding)

linetester is an example dataset in the package. Loading and view the dataset. data(linetester)

View(linetester)

Note that dataset has two addtional coloumns genotypes and gclass. genotypes is the name of the cross or parent. Ex: 1x2, 2x3, 2, 3. gclass metions whether the genotypes is cross or a parent. Thus, we have to add two addtional coloumns to ltdata.

Analysing the ltdata by line.tester function.

result3 <- line.tester(dataframe = linetester, yvar = "trait1", genotypes = "genotypes", replication = "replication", Lines = "Lines", Testers = "Tester", gclass = "gclass" ) print(result3)