dm2 {gpbStat}

Analysis of Diallel Method 2 data containing only Crosses laid out in RCBD or Alpha Lattice design.

Description

Analysis of Diallel Method 2 data containing only Crosses laid out in RCBD or Alpha Lattice design.

Usage

dm2(data, rep, parent1, parent2, var, block)

Arguments

data

dataframe containing following variables

rep

replication

parent1

parent 1

parent2

parent 2

var

trait of interest

block

block (for alpha lattice only)

Details

Analyzing the Diallel Method 2 data containing only crosses which are evaluated in RCBD & Alpha lattice design. All the factors are considered as fixed.

Value

Means

Two way mean table.

ANOVA

ANOVA for the given variable.

Coefficient of Variation

Coefficient of Variation of the variable.

Diallel ANOVA

Diallel ANVOA for the given trait.

Genetic Variance

GCA & SCA varaince.

Combining ability effects

Two way table containing Combining ability effects of parents and crosses

Standard Error

Standard Errror for comining ability effects.

Critical Difference

Critical Difference at 5 pecent for combining ability effects.

Note

The blocks are mentioned at end of the function if the experimental design is Alpha Lattice. For RCBD no need mention the blocks.

Author(s)

Nandan Patil [e-mail]

References

Griffing, B. (1956) Concept of General and Specific Combining Ability in relation to Diallel Crossing Systems. Australian Journal of Biological Sciences, 9(4), 463-493.

Dabholkar, A. R. (1999). Elements of Bio Metrical Genetics. Concept Publishing Company, New Delhi.

Singh, R. K. and Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis. Kalyani Publishers, New Delhi.

See Also

ltcchk, ltc

Examples

## Not run: #Diallel Method 2 analysis containing only crosses in RCBD.
library(gpbStat)
data(dm2rcbd)
result1 =  dm2(dm2rcbd, rep, parent1, parent2, DTP)
result1

#Diallel Method 2 analysis containing only crosses in Alpha Lattice
library(gpbStat)
data(dm2alpha)
result2 =  dm2(dm2alpha, replication, parent1, parent2, TW, block)
result2

# Save results to csv file
lapply(result2, function(x) write.table(data.frame(x), 'result2.csv'  , append= T, sep=','))

## End(Not run)