Height of Eucalyptus trees in southern Brazil

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Description

Height of Eucalyptus trees in southern Brazil

Format

A data frame with 490 observations on the following 4 variables.

gen

Genotype (progeny) factor

origin

Origin of progeny

loc

Location factor

height

Height, meters

Details

The genotypes originated from three different locations in Queensland, Australia, and were tested in southern Brazil. The experiment was conducted as a randomized complete block design with 6 plants per plot and 10 blocks. Mean tree height is reported.

The testing locations are described in the following table:

Loc City Lat (S) Long (W) Altitude Avg min temp Avg max temp Avg temp (C) Precip (mm)
L1 Barra Ribeiro, RS 30.33 51.23 30 9 25 19 1400
L2 Telemaco Borba, PR 24.25 20.48 850 11 26 19 1480
L3 Boa Experanca de Sul, SP 21.95 48.53 540 15 23 21 1300
L4 Guanhaes, MG 18.66 43 900 14 24 19 1600
L5 Ipatinga, MG 19.25 42.33 250 15 24 22 1250
L6 Aracruz, ES 19.8 40.28 50 15 26 24 1360
L7 Cacapva, SP 23.05 45.76 650 14 24 20 1260

Arciniegas-Alarcon (2010) used the 'Ravenshoe' subset of the data to illustrate imputation of missing values.

Source

O J Lavoranti (2003). Estabilidade e adaptabilidade fenotipica atraves da reamostragem bootstrap no modelo AMMI, PhD thesis, University of Sao Paulo, Brazil.

References

Arciniegas-Alarcon, S. and Garcia-Pena, M. and dos Santos Dias, C.T. and Krzanowski, W.J. (2010). An alternative methodology for imputing missing data in trials with genotype-by-environment interaction, Biometrical Letters, 47, 1–14.

Examples

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# Arciniegas-Alarcon et al use SVD and regression to estimate missing values.
# Partition the matrix X as a missing value xm, row vector xr1, column
# vector xc1, and submatrix X11
# X = [ xm  xr1 ]
#     [ xc1 X11 ] and let X11 = UDV'.
# Estimate the missing value xm = xr1 V D^{-1} U' xc1

data(lavoranti.eucalyptus)
dat <- lavoranti.eucalyptus

require(lattice)
levelplot(height~loc*gen, dat, main="lavoranti.eucalyptus - GxE heatmap")

dat <- droplevels(subset(dat, origin=="Ravenshoe"))
require(reshape2)
dat <- acast(dat, gen~loc, value.var='height')

dat[1,1] <- NA
x11 <- dat[-1,][,-1]
X11.svd <- svd(x11)
xc1 <- dat[-1,][,1]
xr1 <- dat[,-1][1,]
xm <- xr1 
xm # = 18.29, Original value was 17.4

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