Predict Rice Leaf Blast Intensity

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.

Usage

predict_leaf_blast(wth, emergence)

predict_lb(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

Value

A data.table::data.table() of disease intensity and infection sites. See SEIR() for a full description of the column values.

Details

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().

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 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.

References

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.

Author

Serge Savary, Ireneo Pangga, Robert Hijmans, Jorrel Khalil Aunario, and Adam H. Sparks

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")
)
lb <- predict_leaf_blast(wth, emergence = "2000-07-01")
plot(x = lb$dates, y = lb$intensity, type = "l")

# use shorthand function
lb <- predict_lb(wth, emergence = "2000-07-01")
plot(x = lb$dates, y = lb$intensity, type = "l")