predict function

Spatial QUEFTS model predictions

Make spatial predictions with a QUEFTS model. First create a model, then use the model with a SpatRaster of soil properties to make spatial predictions.

## S4 method for signature 'Rcpp_QueftsModel'
predict(object, supply, yatt, leaf_ratio, stem_ratio, 
                var="yield", filename="", overwrite=FALSE, ...)

Arguments

• object: QUEFTSModel
• supply: SpatRaster with nutrient supply data (Ns, Ps, Ks)
• yatt: SpatRaster with attainable yield
• leaf_ratio: positive numeric (typically between 0 and 1) indicating the leaf weight relative to the storage organ weight. For example: 0.46 for maize, 0.17 for potato, and 0.18 for rice
• stem_ratio: positive numeric (typically between 0 and 1) indicating the stem weight relative to the storage organ weight, For example: 0.56 for maize, 0.14 for potato, and 0.67 for rice
• var: character. Output variable name. Either "yield" or "gap"
• filename: character. Output filename. Optional
• overwrite: logical. If TRUE, filename is overwritten
• ...: list. Options for writing files as in writeRaster

Returns

SpatRaster

Examples

library(terra)

ff <- list.files(system.file("sp", package="Rquefts"), full.names=TRUE)
r <- rast(ff)

soil <- r[[c("Tavg", "pH", "SOC", "Kex", "Pex", "Ptot")]]
supply <- lapp(soil, nutSupply2)
plot(supply)

yatt <- rast(system.file("sp/Ya.tif", package="Rquefts"))

maize <- quefts_crop("Maize")
fertilizer <- list(N=0, P=0, K=0)
q <- quefts(crop=maize, fert=fertilizer)

p <- predict(q, supply, yatt, 0.46, 0.56)
plot(p)

g <- predict(q, supply, yatt, 0.46, 0.56, "gap")
plot(g)