bond.diallel.Rd
Diallel cross of winter beans
A data frame with 36 observations on the following 3 variables.
female
female parent
male
male parent
yield
yield, grams/plot
stems
stems per plot
nodes
podded nodes per stem
pods
pods per podded node
seeds
seeds per pod
weight
weight (g) per 100 seeds
height
height (cm) in April
width
width (cm) in April
flower
mean flowering date in May
Yield in grams/plot for full diallel cross between 6 inbred lines of winter beans. Values are means over two years.
D. A. Bond (1966). Yield and components of yield in diallel crosses between inbred lines of winter beans (Viciafaba). The Journal of Agricultural Science, 67, 325--336. https://doi.org/10.1017/S0021859600017329
Peter John, Statistical Design and Analysis of Experiments, p. 85.
# \dontrun{
library(agridat)
data(bond.diallel)
dat <- bond.diallel
# Because these data are means, we will not be able to reproduce
# the anova table in Bond. More useful as a multivariate example.
libs(corrgram)
#>
#> Attaching package: 'corrgram'
#> The following object is masked from 'package:lattice':
#>
#> panel.fill
corrgram(dat[ , 3:11], main="bond.diallel",
lower=panel.pts)
# Multivariate example from sommer package
corrgram(dat[,c("stems","pods","seeds")],
lower=panel.pts, upper=panel.conf, main="bond.diallel")
libs(sommer)
#> Loading required package: MASS
#>
#> Attaching package: 'MASS'
#> The following object is masked from 'package:asreml':
#>
#> oats
#> The following object is masked from 'package:dplyr':
#>
#> select
#> Loading required package: crayon
#>
#> Attaching package: 'sommer'
#> The following object is masked from 'package:asreml':
#>
#> vpredict
m1 <- mmer(cbind(stems,pods,seeds) ~ 1,
random= ~ vs(female)+vs(male),
rcov= ~ vs(units),
dat)
#> Version out of date. Please update sommer to the newest version using:
#> install.packages('sommer') in a new session
#> Use the 'date.warning' argument to disable the warning message.iteration LogLik wall cpu(sec) restrained
#> 1 -63.6729 15:16:51 0 0
#> 2 -40.8016 15:16:51 0 0
#> 3 -27.2147 15:16:51 0 0
#> 4 -24.2403 15:16:51 0 0
#> 5 -24.1945 15:16:51 0 0
#> 6 -24.194 15:16:51 0 0
#### genetic variance covariance
cov2cor(m1$sigma$`u:female`)
#> stems pods seeds
#> stems 1.0000000 0.5745963 -0.8714338
#> pods 0.5745963 1.0000000 -0.7946327
#> seeds -0.8714338 -0.7946327 1.0000000
cov2cor(m1$sigma$`u:male`)
#> stems pods seeds
#> stems 1.0000000 0.3173646 -0.6610472
#> pods 0.3173646 1.0000000 -0.4276277
#> seeds -0.6610472 -0.4276277 1.0000000
cov2cor(m1$sigma$`u:units`)
#> stems pods seeds
#> stems 1.0000000 -0.3354943 0.2294149
#> pods -0.3354943 1.0000000 0.1294200
#> seeds 0.2294149 0.1294200 1.0000000
# }