agridat (version 1.12)

ortiz.tomato: Tomato weight/yield and environmental covariates in Latin America

Description

Tomato weight/yield and environmental covariates in Latin America

Format

A list of three matrices, yield, weight, and covs. See details below.

Details

The yield matrix contains average marketable fruit yield (t / ha) for 8 open-pollinated and 7 hybrid tomatos in 18 environments. The weight matrix contains average fruit weight (g).

The environment locations and codes are: Estanzuela, Guatemala (E04), Baja Verapaz, Guatemala, (E05), Cogutepeque, El Salvador (E06), San Andres, El Salvador (E07), Comayagua, Honduras (E11), Valle de Sabaco, Nicaragua (E14), San Antonio de Belen, Costa Rica (E15), San Cristobal, Dominican Republic (E20), Constanza, Dominican Republic (E21), Palmira, Colombia (E27), La Molina, Peru (E40), Santiago, Chile (E41), Chillan, Chile (E42), Curacavi, Chile (E43), Colina, Chile (44), Belem, Brazil (E50), Caacupe, Paraguay (E51), Centeno, Trinidad Tobago (E53).

The covs matrix contains 16 environmental covariates.

Lat	Latitude
Long	Longitude
MxT	Max temperature (C)
MnT	Min temperature (C)
MeT	Mean temperature (C)
Prec	Precipitation (mm)
Day	Degree days (base 10)
pH	Soil pH
OM	Organic matter (percent)
P	Phosphorous (ppm)
K	Potassium (me/100 g)
ExN	Extra nitrogen (kg / ha)
ExP	Extra phosphorous (kg / ha)
ExK	Extra potassium (kg / ha)
Trim	Trimming (0/1)
Driv	Drivings (0/1)
Irr	Irrigation (0/1)
Dha	Days to harvest

Examples

# NOT RUN {
data(ortiz.tomato)
# Double-centered yield matrix
Y <- ortiz.tomato$yield
Y <- sweep(Y, 1, rowMeans(Y, na.rm=TRUE))
Y <- sweep(Y, 2, colMeans(Y, na.rm=TRUE))

# Standardized covariates
X <- ortiz.tomato$covs
X <- X[,c("MxT", "MnT", "MeT", "Prec", "Day", "pH", "OM", "P", "K",
          "ExN", "ExP", "ExK", "Trim", "Driv", "Irr", "Dha")]
X <- scale(X)

# Now, PLS relating the two matrices.
# Note: plsr deletes observations with missing values
if(require(pls)){
m1 <- plsr(Y~X)
# Inner-product relationships similar to Ortiz figure 1.
biplot(m1, which="x", var.axes=TRUE, main="ortiz.tomato - env*cov biplot")
#biplot(m1, which="y", var.axes=TRUE)
}

# }