predict: Spatial QUEFTS model predictions

In Rquefts: Quantitative Evaluation of the Native Fertility of Tropical Soils

Spatial QUEFTS model predictions

Description

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.

Usage

## 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

Value

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)

Rquefts documentation built on Oct. 24, 2023, 5:07 p.m.