gvc_herit {gvcR}

Heritability

Description

gvc_herit computes model based genetic heritability for given traits of different genotypes from replicated data using methodology explained by Burton, G. W. & Devane, E. H. (1953) (<doi:10.2134/agronj1953.00021962004500100005x>) and Allard, R.W. (2010, ISBN:8126524154).

Usage

gvc_herit(y, x = NULL, rep, geno, env, data)

Arguments

y

Response

x

Covariate by default NULL

rep

Repliction

geno

Genotypic Factor

env

Environmental Factor

data

data.frame

Value

Heritability

Author(s)

1. Sami Ullah ([e-mail])

2. Muhammad Yaseen ([e-mail])

References

1. Williams, E.R., Matheson, A.C. and Harwood, C.E. (2002).Experimental Design and Analysis for Tree Improvement. CSIRO Publishing.

Examples

set.seed(12345)
Response <- c(
               rnorm(48, mean = 15000, sd = 500)
             , rnorm(48, mean =  5000, sd = 500)
             , rnorm(48, mean =  1000, sd = 500)
             )
Rep      <- as.factor(rep(1:3, each = 48))
Variety  <- gl(n = 4, k =  4, length = 144, labels = letters[1:4])
Env      <- gl(n = 3, k = 16, length = 144, labels = letters[1:3])
df1      <- data.frame(Response, Rep, Variety, Env)

# Heritability
herit <-
  gvc_herit(
           y    = Response
         , rep  = Rep
         , geno = Variety
         , env  = Env
         , data = df1
         )
herit

library(eda4treeR)
data(DataExam6.2)
herit <-
  gvc_herit(
           y    = Dbh.mean
         , rep  = Replication
         , geno = Family
         , env  = Province
         , data = DataExam6.2
         )
herit