cercospoRa is a mechanistic epidemiological model for estimating epidemics of Cercospora beticola in sugar beet farms, available as an R package.
Installation
This package imports epiphytoolR. To install this package run the following code in R.
remotes::install_github(repo = "PaulMelloy/epiphytoolR")Next install the package
remotes::install_github(repo = "PaulMelloy/cercospoRa")Getting started
Format weather data
library(epiphytoolR)
library(cercospoRa)
# Inspect raw weather station data
head(cercospoRa::weathr)weathr is a data.table containing weather data recorded at a sugar beet field trial observing the spread and severity of C. beticola.
# make a copy of the data
wthr <- data.table(weathr)
# Format times to POSIXct time with UTC timezone
wthr[,Time := as.POSIXct(paste0(Datum, " ",Stunde,":00"),tz = "UTC")]
# Nominate Latitude and Longitude location of the weather station.
# While not needed in cercospoRa some plant disease models will use location to
# decide the closest weather station to pull weather from
wthr[, c("lon","lat") := list(9.916,51.41866)]
# weather is hourly and will error if we don't specify a standard deviation of
# weather direction. This is intentional to force the user to decide how variable
# the wind direction data could be.
wthr[, wd_std := 20]
# remove all data after September as it contains missing data
wthr <- wthr[Datum < as.POSIXct("2022-10-01")]
# set NA wind speed values to zero
wthr[is.na(WG200),WG200 := 0]
# set NA wind direction values to 20 degrees. Wind is not important for this model
wthr[is.na(WR200),WR200 := 20]
# format_weather() is a function from epiphytoolR that formats weather data to
# hourly and checks for missing data or any issues that may cause downstream faults
# in the model.
wthr <-
epiphytoolR::format_weather(wthr,
POSIXct_time = "Time",
time_zone = "UTC",
temp = "T200",
rain = "N100",
rh = "F200",
wd = "WR200",
ws = "WG200",
station = "Station",
lon = "lon",
lat = "lat",
wd_sd = "wd_std",
data_check = FALSE # this stops the function from checking for faults
)Calculate the proportional progress towards an epidemic
# susceptible cultivar
calc_epidemic_onset(c_closure = as.POSIXct("2022-07-01"),
weather = wthr,
cultivar_sus = 3)
# resistant cultivar
calc_epidemic_onset(c_closure = as.POSIXct("2022-07-01"),
weather = wthr,
cultivar_sus = 5)
This returns a POSIXct date for the onset of an epidemic for the susceptible and more resistant cultivar. If the input weather data does not provide a window where a epidemic onset date is met, the proportional progress towards an epidemic is returned.
calc_epidemic_onset() is a wrapper for calc_DIV() which returns a data.table detailing the daily contribution towards the “daily infection values” (Wolf and Verreet, 2005). For more detailed output of daily infection values call calc_DIV()
Calculate daily infection values
calc_DIV(dat = wthr)This produces a data.table detailing the daily infection value for each day using the method described in Wolf and Verreet (2005).
Note: Missing humidity values do not prevent the model from running and these days are assumed to not progress the model. The Racca and Jörg model returns NA values and the Wolf model returns 0 as seen in the calc_DIV(dat = bris_formated) function output.
Notes for contributors
The main branch is the production branch and only provides functions to recreate the model described in Wolf and Verreet (2005) as explained in the paper. The main branch is locked, please contribute to the dev branch. The dev (development) branch also includes functions to recreate other C. beticola mechanistic models published by Racca and Jörg (2007) and auxiliary functions which might be helpful for future versions.
References
Wolf, P. F., & Verreet, J. A. (2005). Factors Affecting the Onset of Cercospora Leaf Spot Epidemics in Sugar Beet and Establishment of Disease-Monitoring Thresholds. Phytopathology, 95(3), 269-274.
Racca, P., and Jörg, E. (2007). CERCBET 3 – a forecaster for epidemic development of Cercospora beticola. EPPO Bulletin, 37(2), 344-349.