predict_brown_spot: Predict Rice Brown Spot Intensity
In adamhsparks/epiRice: Simulation Modelling of Crop Diseases Using a Susceptible-Exposed-Infectious-Removed (SEIR) Model
View source: R/predict_brown_spot.R
predict_brown_spot R Documentation
Predict Rice Brown Spot Intensity
Description
A dynamic mechanistic simulation of rice brown spot, causal agent
Cochliobolus miyabeanus. The model is driven by daily weather data, which
can easily be accessed usingget_wth() to download weather data from
NASA POWER using nasapower.
Usage
predict_brown_spot(wth, emergence)
predict_bs(wth, emergence)
Arguments
wth
Weather data with a daily time-step, normally NASA
POWER data from get_wth(), but anybase::data.frame() object
that has the following properly named columns in them will work.
Field Name Value
YYYYMMDD Date as Year Month Day (ISO8601)
DOY Consecutive day of year, commonly called "Julian date"
TEMP Mean daily temperature (°C)
RHUM Mean daily relative humidity (%)
RAIN Mean daily rainfall (mm)
LAT Optional latitude of weather observation. See LAT/LON Note.
LON Optional longitude of weather observation. See LAT/LON Note.
emergence
Expected date of crop emergence
Details
The model represents site size as 10
mm2 of a rice plant's leaf.
Default values for this disease model are derived from Table 2 (Savary
et al. 2012).
predict_bs() is a shorthand alias for predict_brown_spot().
Value
A data.table::data.table() of disease intensity and infection
sites. See SEIR() for a full description of the column values.
Note
Adapted from cropsim package version 0.2.0-5 by Adam H. Sparks,
Department of Primary Industries and Regional Development, WA, AU.
Original model development: Serge Savary & Rene Pangga (IRRI).
Original R implementation by Robert J. Hijmans, Rene Pangga, & Jorrel
Aunario (IRRI).
If the wth object provides LAT and LON columns, these will be included
in the output for mapping purposes. Both values must be present. These
columns are provided by default when using get_wth().
The optimum temperature for brown spot as presented in Table 2 of
Savary et al. 2012 has a typo. The optimal value should be 25 °C, not
20 °C as shown. The correct value, 25 °C, is used in this implementation.
Author(s)
Serge Savary, Ireneo Pangga, Robert Hijmans, Jorrel Khalil Aunario
References
Klomp, A.O., 1977. Early senescence of rice and Drechslera
oryzae in the Wageningen polder, Surinam. PhD Thesis, 97p.
Levy, Y. and Cohen, Y., 1980. Sporulation of Helminthosporium turcicum on
sweet corn: Effects of temperature and dew period. Canadian Journal of Plant
Pathology 2:65-69. DOI: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/07060668009501440")}.
Luo Wei-Hong, 1996. Simulation and measurement of leaf wetness formation in
paddy rice crops. PhD, Wageningen Agricultural University, 87 p.
Padmanabhan, S.Y. and Ganguly, D. 1954. Relation between the age of rice
plant and its susceptibility to Helminthosporium and blast disease.
Proceedings of the Indian Academy of Sciences B 29:44-50.
Sarkar, A.K. and Sen Gupta, P.K., 1977. Effect of temperature and humidity on
disease development and sporulation of Helminthosporium oryzae on rice.
Indian Phytopathology 30:258-259.
Savary, S., Nelson, A., Willocquet, L., Pangga, I., and Aunario, J. Modeling
and mapping potential epidemics of rice diseases globally. Crop Protection,
Volume 34, 2012, Pages 6-17, ISSN 0261-2194 DOI:
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.cropro.2011.11.009")}.
Waggoner. P.E., Horsfall, J.G., and Lukens, R.J. 1972. EPIMAY. A Simulator of
Southern Corn Leaf Blight. Bulletin of the Connecticut Experiment Station,
New Haven, 85 p.
See Also
SEIR()
Other predict functions:
predict_bacterial_blight(),
predict_leaf_blast(),
predict_sheath_blight(),
predict_tungro()
Examples
# get weather for IRRI Zeigler Experiment Station in wet season 2000
wth <- get_wth(
lonlat = c(121.25562, 14.6774),
dates = c("2000-06-30", "2000-12-31")
)
bs <- predict_brown_spot(wth, emergence = "2000-07-01")
plot(x = bs$dates, y = bs$intensity, type = "l")
# use shorthand function
bs <- predict_bs(wth, emergence = "2000-07-01")
plot(x = bs$dates, y = bs$intensity, type = "l")
adamhsparks/epiRice documentation built on Nov. 23, 2023, 12:31 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
View source: R/predict_brown_spot.R
| predict_brown_spot | R Documentation |
Predict Rice Brown Spot Intensity
Description
A dynamic mechanistic simulation of rice brown spot, causal agent
Cochliobolus miyabeanus. The model is driven by daily weather data, which
can easily be accessed usingget_wth() to download weather data from
NASA POWER using nasapower.
Usage
predict_brown_spot(wth, emergence)
predict_bs(wth, emergence)
Arguments
wth |
Weather data with a daily time-step, normally NASA
POWER data from
| |||||||||||||||||
emergence |
Expected date of crop emergence |
Details
The model represents site size as 10 mm2 of a rice plant's leaf.
Default values for this disease model are derived from Table 2 (Savary et al. 2012).
predict_bs() is a shorthand alias for predict_brown_spot().
Value
A data.table::data.table() of disease intensity and infection
sites. See SEIR() for a full description of the column values.
Note
Adapted from cropsim package version 0.2.0-5 by Adam H. Sparks, Department of Primary Industries and Regional Development, WA, AU. Original model development: Serge Savary & Rene Pangga (IRRI). Original R implementation by Robert J. Hijmans, Rene Pangga, & Jorrel Aunario (IRRI).
If the wth object provides LAT and LON columns, these will be included
in the output for mapping purposes. Both values must be present. These
columns are provided by default when using get_wth().
The optimum temperature for brown spot as presented in Table 2 of Savary et al. 2012 has a typo. The optimal value should be 25 °C, not 20 °C as shown. The correct value, 25 °C, is used in this implementation.
Author(s)
Serge Savary, Ireneo Pangga, Robert Hijmans, Jorrel Khalil Aunario
References
Klomp, A.O., 1977. Early senescence of rice and Drechslera oryzae in the Wageningen polder, Surinam. PhD Thesis, 97p.
Levy, Y. and Cohen, Y., 1980. Sporulation of Helminthosporium turcicum on sweet corn: Effects of temperature and dew period. Canadian Journal of Plant Pathology 2:65-69. DOI: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/07060668009501440")}.
Luo Wei-Hong, 1996. Simulation and measurement of leaf wetness formation in paddy rice crops. PhD, Wageningen Agricultural University, 87 p.
Padmanabhan, S.Y. and Ganguly, D. 1954. Relation between the age of rice plant and its susceptibility to Helminthosporium and blast disease. Proceedings of the Indian Academy of Sciences B 29:44-50.
Sarkar, A.K. and Sen Gupta, P.K., 1977. Effect of temperature and humidity on disease development and sporulation of Helminthosporium oryzae on rice. Indian Phytopathology 30:258-259.
Savary, S., Nelson, A., Willocquet, L., Pangga, I., and Aunario, J. Modeling and mapping potential epidemics of rice diseases globally. Crop Protection, Volume 34, 2012, Pages 6-17, ISSN 0261-2194 DOI: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.cropro.2011.11.009")}.
Waggoner. P.E., Horsfall, J.G., and Lukens, R.J. 1972. EPIMAY. A Simulator of Southern Corn Leaf Blight. Bulletin of the Connecticut Experiment Station, New Haven, 85 p.
See Also
SEIR()
Other predict functions:
predict_bacterial_blight(),
predict_leaf_blast(),
predict_sheath_blight(),
predict_tungro()
Examples
# get weather for IRRI Zeigler Experiment Station in wet season 2000
wth <- get_wth(
lonlat = c(121.25562, 14.6774),
dates = c("2000-06-30", "2000-12-31")
)
bs <- predict_brown_spot(wth, emergence = "2000-07-01")
plot(x = bs$dates, y = bs$intensity, type = "l")
# use shorthand function
bs <- predict_bs(wth, emergence = "2000-07-01")
plot(x = bs$dates, y = bs$intensity, type = "l")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.