In CIP-RIU/hidap: High Interactive Data Analysis Platform for Plant breeding

r i = {{i}}

{{i}}. Analysis for trait `r traits[i]`

model <- aov.lxt(traits[i], line, tester, rep, dfr)

GCA effects for lines plot

barplot(model$GCA.le[, 1], col = "lightblue", las = 2, cex.names = 0.8, ylab = "GCA effects")

Mid parent heterosis increment plot

# Means

means <- docomp('mean', traits[i], c(line, tester), dfr = dfr)
hhh <- means[!is.na(means[, line]) & !is.na(means[, tester]), ]
line.means <- means[!is.na(means[, line]) & is.na(means[, tester]), ]
test.means <- means[is.na(means[, line]) & !is.na(means[, tester]), ]

# Colnames

colnames(line.means)[3] <- paste(line, 'means', sep = "_")
colnames(test.means)[3] <- paste(tester, 'means', sep = "_")

# Merge data frames

hhh <- merge(hhh, line.means[, -2], by = line)
hhh <- merge(hhh, test.means[, -1], by = tester)
hhh$het <- hhh[, 3] / (hhh[, 4] + hhh[, 5]) * 200 - 100

# Graph

barplot(hhh$het, col = "lightblue", las = 2, cex.names = 0.8,
        ylab = "Heterosis increment (%)",
        names.arg = paste(hhh[, line], hhh[, tester], sep = "-"))