Disease forecasting

Plant disease forecasting

Plant disease forecasting is a management system for predicting the occurrence of diseases ahead of time. This management system utilizes the data of current and forecast weather conditions of an specific region to predict the outbreak and intensity of disease in near future. In this way plant disease forecasting system tells the growers in advance to or not to adapt the methods to protect a specific crops from the pests.
When timely and accurately predicted, the disease forecasting system reduces economic cost, yield loss of the farmers and reduce the adverse impact on environment. These systems should be adapted for such diseases, which are not of regular occurrence, rather comes in destructive forms, when weather conditions are favorable.
Spray warning services for the downy mildew of grapevine in France, Italy and Germany during 1920s were among the first forecasting systems used for the growers.

Requirements for disease forecasting

Plant disease forecasting systems rely on the principle of interaction of environment with host and pathogen, so called, disease triangle. Thus for successful prediction of a diseases outbreak in near future, data on these factors are prerequisite.

1. Host factors

Disease triangle
Disease triangle
A host can be susceptible or resistant. The stages of a host plant also determine the development of diseases. Some pathogen attack in seedling stages, while other infect when plant is grown-up. The outbreak of a disease also depends upon the population of plant. Densely populated plantation favors, while scattered plantation suppress the disease epidemics.

2. Pathogen factors

Based on previous history or survey data the presence of a determine the disease epidemics. Data on amount of inoculum, their germination, dispersal, incubation period, sporulation, perenating stages are essential for disease forecasting system for accurate prediction of disease. 

3. Environment factors

Environmental factors play a very critical role in interaction between  a host and pathogen. current and forecast data on temperature, relative humidity, direction and speed of wind are utilized as environmental factors in determining the outbreak of a plant disease.

Methods of disease forecasting

1.Forecasting based on primary inoculums

In this method, presence of primary inoculum, their density and viability is tested in the planting material, soil or in the air. Planting materials are randomly tested by different testing methods and recommendations are made for the chemical treatment of seed. Diseases, like Smut of wheat, ergot of pearl millet can be tested easily. In soil, presence and density of pathogens are tested by culturing them on specific culture medium. In air, spore of the pathogens are determined through the spore trap method.

2.Forecasting based on weather conditions

In this method, different parameters of weather conditions during and between the crop seasons are considered. These parameters include, temperature, relative humidity, rainfall, wind direction, light, etc. Weather conditions above the crops and of soil is also measured.

3.Forecasting based on correlative information

In this method, data of several years on weather is collected and correlated with the occurrence and intensity of the diseases. On basis of correlation disease forecasting is done. On basis of correlative information forecasting of barley powdery mildew and fire blight of apple have been made.

4.Computer-based disease forecasting models

These models works by processing the data on above mentioned factors and warn about the outbreak and severity of a diseases in near future. Among the computer-based models, EPIDEM was developed in 1969 for early bight of potato and tomato caused by Alternaria solani. Since then following models have been established to simulate the disease epidemics.

Forecast systemDiseasesCountry
EPIDEMEarly blight of potato and tomato caused by Alternaria solaniNA
TOMCAST/FASTEarly blight of potato and tomato caused by Alternaria solaniNA
MYCOSMycosphaerella blight of ChrysanthemumNA
EPIVENApple scab caused by Venturia inaequalisNA
PLASMODowny mildew of grapevine caused by Plasmopara viticolaNA
EPICORNSouthern corn leaf blight caused by Helminthosporium maydisNA
BLIGHTCASTLate blight of potato caused by Phytophthora infestansNA
USABlightLate blight of potato caused by Phytophthora infestansUSA
NDAWNlate blight and early blightDakota
Indo-BlightCastLate blight of potato caused by Phytophthora infestansIndia
PhytoprogLate blight of potato caused byPhytophthora infestansNA
CERCOSCercospora blight of celeryNA
EPIDEMICDesigned for stripe rust of wheat, but could be modified for other diseasesNA
MARYBLIGHTFire blight on apple caused by Erwinia amylovoraNA

Examples of disease forecasting

1. Late blight of potato

Late blight of potato is forecasted after occurrence of 7 to 14 days of blight favorable days. Blight favorable days are when, 5 day average temperature is 25.5°C and the total rainfall for the last 10 days is more than 3.0 cm.
Nowadays, computarized models, such as, BLIGHTCASTIndo-BlightCast and Phytoprog are available in different parts of the world, which tells the farmers about the outbreak of late blight of potato in advance. Blightcast is operated by Syngenta, U.K. Indo-blightcast is operated by CPRI and AICRP, Shimla in collaboration with Agromet Division of Indian Meteorological Department, New Delhi. Phytoprog is the forecasting model used in West Germany.

2. Rice blast

Rice blast caused by Pyrocularia oryzae is predicted on basis of correlative information method. The disease is predicted when, minimum night temperature range between 20 to 26 °C in association with 90 % or above relative humidity.