Epidemiology of Rice Blast Disease in Egypt

Kamel, Serag-El-Din; El-Bigawi, Thoraya; Ismail, Ismail; Sehly, M. R.

doi:10.4197/edu.1-1.4

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both empirical and explanatory simulation models have been developed to predict rice blast in Japan (Uehara et al, 1988;Ishiguro & Hashimoto, 1991), Korea (Choi et al, 1988;Lee et al, 1989;Kim & Kim, 1993), China (Zhejiang Research Group, 1986), Taiwan (Tsai, 1986), Iran (Izadyar & Baradaran, 1990), Egypt (Kamel & El Sharkawy, 1989), India (Manibhushanrao & Krishnan, 1991), Thailand (Surin et al, 1991), and the Philippines (El Refaei, 1977;Calvero & Teng, 1991). However, most of these models have not been used by farmers to manage rice blast because of two plausible reasons: firstly, growers/farmers tend to be risk-aversed on the use of disease forecasting tools (Campbell & Madden, 1990), and secondly, the models may include weather factors (a weather factor is calculated from a weather variable of a specific time scale and/or value, e.g.…”

Section: Introductionmentioning

confidence: 99%

Development of empirical forecasting models for rice blast based on weather factors

1996

View full text Add to dashboard Cite

Regression equations used as empirical models to predict rice blast caused by Pyricularia grisea on cv. Jinheung at Icheon, South Korea, and on cvs. IR50 and C22 at Cavinti, Philippines, were generated, using weather factors identified by the WINDOW PANE program to be highly correlated with disease. Consecutive days with RH≥80% (CDRH80), number of days with RH≥80% (NDRH80), consecutive days with precipitation, and number of days with precipitation ≥ 84 mm day−1 were important variables predicting blast at Icheon. Total precipitation, precipitation frequency, mean maximum and minimum temperatures, number of days with wind speed above 3.5 m s−1, CDRH80, and NDRH80 were important predictors of blast at Cavinti. The Allen’s predicted error sum of squares (PRESS) criterion and a cross‐validation procedure were used to evaluate the models using data that were not included in model development. Validation test showed that all models developed for the two sites, except the models predicting maximum lesion number and panicle blast incidence at Icheon, and panicle blast severity on IR50 at Cavinti, predicted blast reasonably well based on low PRESS values and close to zero average prediction errors. These models can be applied in actual rice production systems, but future validation is needed to further improve their predictive ability.

show abstract

Section: Introductionmentioning

confidence: 99%

Development of empirical forecasting models for rice blast based on weather factors

1996

View full text Add to dashboard Cite

show abstract

“…Hence, integration of possible cultural practices like well managed flooded and fertilized with optimum N application field is necessary along with fungicidal application. Kamel and Sharkawy (1989) reported that the pathogen is extremely variable and its management required short and long term measures. These include exclusion through strict quarantine, cultural practices such as early planting, elimination of alternative hosts, chemotherapy and breeding varieties with stable resistance.…”

Section: Integrated Disease Managementmentioning

confidence: 99%