Quantitative Evaluation of the Native Fertility of Tropical Soils

Description

This package provides implments the QUEFTS model.

QUEFTS (Quantitative Evaluation of the Native Fertility of Tropical Soils) model (1) estimates native nutrient (N, P, K) supply of soils from a few soil chemical properties; and (2) computes crop yield given that supply, fertilizer application and crop parameters. See Janssen et al. (1990) <doi:10.1016/0016-7061(90)90021-Z> for the technical details and Sattari et al. (2014) <doi:10.1016/j.fcr.2013.12.005> for a recent evaluation and improvements.

The package is particularly useful if you want to make spatial predictions with QUEFTS.

There are also a few functions that can help with computing the amount of nutriets supplied with fertilizer (blends) and compute the optimal use of fertilizer given a goal in nutrients, available products, and their prices.

Helper functions to go from fertilizers to nutrients

Description

Computes the amount of nutrients given a rate of fertilizer.

Usage

fertilizers()
nutrientRates(supply, treatment) 

Arguments

Examples

# fertilizer product list
fert <- fertilizers()
# shortening some of the names for display
fert[,2] = substr(fert[,2], 1, 20)
# contents are expressed as a percentage.
fert

myferts <- fert[c(8,15), ] 
nutrientRates(myferts, c(100,50))

Batch QUEFTS model predictions

Description

Make many predictions with a QUEFTS model.

Usage

## S4 method for signature 'Rcpp_QueftsModel'
batch(x, supply, fert, yatt, leaf_ratio, stem_ratio, var="yield")

Arguments

Value

numeric or matrix (if var="gap")

Examples

potato <- quefts_crop("potato")
q <- quefts(crop=potato)
fert=cbind(c(0,100), c(0,200), c(0,30))
supply=cbind(50,50,25)
yatt <- 10000
batch(q, supply, fert, yatt, 0.45, 0.4)

batch(q, supply, fert, yatt, 0.45, 0.4, var="gap")

Optimal fertilizer application

Description

Compute the optimal fertilizer application rates given a target nutrient application and the available products (fertilizer blends) and their prices.

Usage

fertApp(nutrients, fertilizers, price, exact=TRUE, retCost=FALSE)

Arguments

Examples

# fertilizer product list
fert <- fertilizers()
# shortening some of the names for display
fert[,2] = substr(fert[,2], 1, 20)
# contents are expressed as a percentage.
ferts <- fert[c(8,15:17), 2:5] 
ferts

x <- fertApp(data.frame(N=100, P=50, K=50), ferts, c(1, 1.5, 1.25, 1))
# show that it is correct
nutrientRates(ferts, x[,2])

fertApp(data.frame(N=seq(0,200,50), P=50, K=50), ferts, c(1, 1.5, 1.25, 0.75))
fertApp(data.frame(N=seq(0,200,50), P=50), ferts[,-3], c(1, 1.5, 1.25, 0.75))
fertApp(data.frame(N=seq(0,200,50), P=50), ferts[,-3], c(1, 1.5, 1.25, 5.75))

Soil nutrients supply for QUEFTS model

Description

nutSupply1 computes the base (unfertilized) soil supply of N, P and K according to Janssen et al. (1990), Table 2. For use with the QUEFTS model.

nutSupply2 is a modified version following Sattari et al. (2014). It has an additional variable "temperature", and P-total is required. Sattari et al suggest that, for soils that have not been fertilized with P, you can estimate P-total as 95 * P-Olsen. Using AfSIS data I found 55 * P-Olsen.

Usage

nutSupply1(pH, SOC, Kex, Polsen, Ptotal=NA)
nutSupply2(temp, pH, SOC, Kex, Polsen, Ptotal)

Arguments

Value

Matrix with three columns: Nsup, Psup and Ksup. These are the potential supply of N, P and K of the unfertilized soil (kg/ha).

References

Janssen B.H., F.C.T. Guiking, D. van der Eijk, E.M.A. Smaling, J. Wolf and H. van Reuler, 1990. A system for the quantitative evaluation of the fertility of tropical soils (QUEFTS). Geoderma 46: 299-318

Sattari, S.Z., M.K. van Ittersum, A.F. Bouwman, A.L. Smit, and B.H. Janssen, 2014. Crop yield response to soil fertility and N, P, K inputs in different environments: Testing and improving the QUEFTS model. Field Crops Research 157: 35-46

Examples

s1 <- nutSupply1(6, c(23, 11, 35), 15, c(1.6, 2.6, 2.4))
s1
s2 <- nutSupply2(20, 6, c(23, 11, 35), 15, c(1.6, 2.6, 2.4), 225)
s2

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

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)

QUEFTS model

Description

Create a QUEFTS model, set parameters, and run it to compute nutrient requirements and nutrient limited yield.

A number of default crop parameter sets are available from quefts_crop, and an example soil from quefts_soil. You need to provide attainable or target crop production (in this context that is the maximum production in the absence of nutrient limitation), expressed as dry-matter biomass for leaves, stems and the storage organ (e.g. grain, root or tuber). See quefts_biom. Some crops are grown for the stems/leaves, in which case there is no relevant storage organ (e.g. sugarcane, jute). production yield estimates can be obtained with a crop growth model.

Usage

quefts(soil, crop, fert, biom)
crop(x) <- value
soil(x) <- value
fert(x) <- value
biom(x) <- value
run(x, ...)

Arguments

Details

For input parameters see quefts_crop, quefts_soil, quefts_fert and quefts_biom

Value

vector with output variables as described in the Details

References

Janssen B.H., F.C.T. Guiking, D. van der Eijk, E.M.A. Smaling, J. Wolf and H. van Reuler, 1990. A system for the quantitative evaluation of the fertility of tropical soils (QUEFTS). Geoderma 46: 299-318

Sattari, S.Z., M.K. van Ittersum, A.F. Bouwman, A.L. Smit, and B.H. Janssen, 2014. Crop yield response to soil fertility and N, P, K inputs in different environments: Testing and improving the QUEFTS model. Field Crops Research 157: 35-46

Examples

# create a QUEFTS model
# 1. get parameters
soiltype <- quefts_soil()
barley <- quefts_crop("Barley")
fertilizer <- list(N=0, P=0, K=0)
att_yield <- list(leaf_att=2200, stem_att=2700, store_att=4800, SeasonLength=110)

# 2. create a model
q <- quefts(soiltype, barley, fertilizer, att_yield)

# 3. run the model
run(q)

# change some parameters
q$SeasonLength <- 162
q$leaf_att <- 2651
q$stem_att <- 5053
q$store_att <- 8208

q$N <- 100
q$P <- 50
q$K <- 50

run(q)


## note that Rquefts uses C++ reference classes. 
## This means that if you copy a quefts model, you do not create a 
## new instance of the model, but you point to the same one!
q <- quefts()
q["N"]
k <- q
k["N"] <- 150
k["N"]
# the value of q has also changed!
q["N"]

## different ways of subsetting / replacement
q <- quefts()
q$N
q$N <- 30
q["N"]
q["N"] <- 90
q["model", "N"]
q["model", "N"] <- 60
q$N

q$soil$N_recovery
q["soil$N_recovery"]
q["soil$N_recovery"] <- .6
q["soil", "N_recovery"]
q["soil", "N_recovery"] <- .4
q$soil$N_recovery

biomass parameters

Description

Crop biomass parameters

For a cereal crop you can generally assume that about 50% of the total biomass is grain, and about 30% is stem and 20% is leaf biomass.

Usage

quefts_biom()

Details

Value

list

Examples

b <- quefts_biom()
str(b)

Crop parameters

Description

A number of default crop parameter sets are provided

Usage

quefts_crop(name="")

Arguments

Details

Value

list with crop parameters. See Details

Examples

barley <- quefts_crop("Barley")
str(barley)

fertilizer parameters

Description

Get a list with the default fertilization parameters

Usage

quefts_fert()

Details

Value

list

Examples

f <- quefts_fert()
str(f)

soil parameters

Description

Example soil parameters.

Usage

quefts_soil()

Details

Value

list with soil parameters

Examples

soiltype <- quefts_soil()
str(soiltype)

Estimate soil nutrients supply

Description

Estimate the apparent base (unfertilized) soil supply of N, P and K based on nutrient omission trial data and a "reverse" QUEFTS approach. The apparent supply is found with optimization.

Usage

revSupply(obs, crop, soil, Ya, leaf_ratio, stem_ratio, SeasonLength = 120, ...)

Arguments

Value

numeric vector with the N, P, and K supply in kg/ha

References

?

Examples

set.seed(777)
trial_data <- data.frame(treat = c("CON", "NPK", "NPK", "PK", "NK", "NP"),
                  N = c(0, 120, 120, 0, 120, 120),
                  P = c(0, 30, 30, 30, 0, 30),
                  K = c(0, 60, 60, 60, 60, 0),
                  Y = c(2000, 6000, 6000, 2500, 4500, 5500) + rnorm(6, 0, 500))
Ya <- max(trial_data$Y) + 1000
crop <- quefts_crop("Potato")
soil <- quefts_soil()

revSupply(trial_data, crop, soil, Ya, leaf_ratio=.17, stem_ratio=.14)