Description Usage Arguments Details Value Note Author(s) References See Also Examples
Analysis of Line x Tester data for multiple traits containing only Crosses laid out in RCBD or Alpha Lattice design.
1 
data 
dataframe containing following variables 
replication 
replication 
line 
line 
tester 
tester 
traits 
multiple traits of interest 
block 
block (for alpha lattice design only) 
Analyzing the line by tester data of multiple trais only using the data from crosses which are evaluated in RCBD and Alpha lattice design. All the factors are considered as fixed.

Table of means. 

ANOVA with all the factors. 

GCA effects of lines. 

GCA effects of testers. 

SCA effects of crosses. 

Coefficent of Variation. 

Genetic component Variance and covariance. 

Standard error for combining ability effects. 

Critical Difference at 5 pecent for combining ability effects. 

Additive and Dominance component of Variance. 

Contribution of Lines, Testers and Line x Tester towards total variation. 
The block variable is inserted at the last if the experimental design is Alpha Lattice. For RCBD no need to have block factor.
Nandan Patil tryanother609@gmail.com
Kempthorne, O. (1957), Introduction to Genetic Statistics. John Wiley and Sons, New York. , 468472. Singh, R. K. and Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis. Kalyani Publishers, New Delhi.
1 2 3 4 5 6 7 8 9 10 11 12 13  ## Not run: #Line Tester analysis data with only crosses in RCBD
library(gpbStat)
data(rcbdltcmt)
result1 = ltcmt(rcbdltcmt, replication, line, tester, rcbdltcmt[,4:5])
result1
#Line Tester analysis data with only crosses in Alpha Lattice
library(gpbStat)
data(alphaltcmt)
result2 = ltcmt(alphaltcmt, replication, line, tester, alphaltcmt[,5:7], block)
result2
## End(Not run)

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