carolina1: Analysis of North Carolina Design I

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

Description

The function performs analysis of North Carolina I design (Comstock and Rosbinson 1952).

Usage

carolina1(dataframe, set, male, female, progeny, replication, yvar)

Arguments

dataframe	Dataframe sould consist of variables set, male, female, progeny and replication along with at least one y variable (yvar)
set	name of numeric variable for set
male	name of numeric variable with male
female	name of numeric variable with female
progeny	name of numeric variable with progeny
replication	name of numeric variable with replication
yvar	name of name of y variable to be analyzed

Value

The following values as list are returned -

model	model - use anova (model) to see analysis of variables
'variance male'	Male variance
'BULP estimates'	BLUP estimates
'variance female'	Female variance
'additive variance'	Additive variance
'dominance variance'	Dominance variance
'female:male:set:replication'	female:male:set:replication
'female:male:set'	female:male:set
'male:set'	male:set
'set:replication'	set:replication

Author(s)

Umesh R. Rosyara

References

Comstock R.F., Rosbinson F.F (1952). Estimation of average dominance of genes. In Heterosis, Iowa State College Press, Iowa City, Iowa, chapter 30.

Singh R.K., Chaudhary B.D.(1985) Biometrical Methods in Quantitative Genetics Analysis, Kalyani Publishers

Mather K., Jinks J.L. (1971). Biometrical Genetics. Chapman & Hall, London.

Saxton A. (2004) Genetic Analysis of Complex Traits Using SAS. SAS Institute, Inc.

Examples

data(northcaro1)
# using general linear model
p1 <- carolina1(dataframe = northcaro1, set = "set", male = "male", female = "female", 
progeny = "progeny", replication = "replication", yvar = "yield")
print(p1)

anova(p1[[1]]) # anova 

p1[[1]]$coefficients  ## coefficients  

p1$var.m # male variance 
p1$ var.f # femal variance 
p1$ var.A # variance additive 
p1$ var.D # variance dominance 

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