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
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.
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).
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")
Or
You can just click on Import dataset and select your excel file.
![](https://raw.githubusercontent.com/nandp1/Line-Tester-Analysis/master/dataimport.png)
Viewing Imported data
View(ltdata)
- 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))
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)
- Saving the results
ltresult = capture.output(print(result3), "ltresult.txt")
All the script can be found on Github
This is an open source webpage make your contribution and help us to improve.
Contact me for any query.
Author
Nandan L. Patil
Special thanks to LAKSHMI