A dynamic mechanistic simulation of leaf blast disease of rice, causal agent
Magnaporthe oryzae. The model is driven by daily weather data, which can
easily be accessed usingget_wth() to download weather data from
NASA POWER using nasapower.
predict_leaf_blast(wth, emergence)
predict_lb(wth, emergence)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. |
Expected date of crop emergence
A data.table::data.table() of disease intensity and infection
sites. See SEIR() for a full description of the column values.
The model represents site size as 45 mm2 of a rice plant's leaf.
Default values for this disease model are derived from Table 2 (Savary et al. 2012).
predict_lb() is a shorthand alias for predict_leaf_blast().
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 leaf blast as presented in Table 2 of Savary et al. 2012 has a typo. The optimal value should be 20 °C, not 25 °C as shown. The correct value, 20 °C, is used in this implementation.
El Refaei, M.I., 1977. Epidemiology of rice blast disease in the tropics with special reference to the leaf wetness in relation to disease development. PhD Thesis, Indian Agricultural Research Institute, New Delhi, 195 p.
Hemmi, T., Abe, T., Ikaya, J., and Inoue, Y. 1936. Studies on the rice blast disease. IV. Relation of the environment to the development of blast disease and physiologic specialization in the rice blast fungus. Materials for Rural Improvement, Department of Agriculture and Forestry, Japan No. 105, 145p.
Hwang, B.K., Koh, Y.J., Chung, H.S., 1987. Effects of adult-plant resistance on blast severity and yield of rice. Plant Disease 71:1035-1038. DOI: doi:10.1094/PD-71-1035 .
Kato, H. and Kozaka, T., 1974. Effect of temperature on lesion enlargement and sporulation of Pyricularia oryzae in rice leaves. Phytopathology 64:828-830. DOI: doi:10.1094/Phyto-64-828 .
Wei-Hong, L. 1996. Simulation and measurement of leaf wetness formation in paddy rice crops. PhD Thesis, Wageningen Agricultural University, 87 p.
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: doi:10.1016/j.cropro.2011.11.009 .
Torres, C.Q., 1986. Effect of plant age on the expression of resistance to Pyricularia oryzae Cav. in upland rice varieties. PhD Thesis, University of the Philippines at Los Baños, 82 p.
Other predict functions:
predict_bacterial_blight(),
predict_brown_spot(),
predict_sheath_blight(),
predict_tungro()
if (FALSE) { # interactive()
# 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")
)
lb <- predict_leaf_blast(wth, emergence = "2000-07-01")
plot(x = lb$dates, y = lb$intensity, type = "l")
}
if (FALSE) { # interactive()
# use shorthand function
lb <- predict_lb(wth, emergence = "2000-07-01")
plot(x = lb$dates, y = lb$intensity, type = "l")
}