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 a specific region to predict the outbreak and intensity of disease in the near future. In this way, the plant disease forecasting system tells the growers in advance whether or not to adapt the methods to protect a specific crop from pests.
When timely and accurately predicted, the disease forecasting system reduces economic cost, yield loss for the farmers, and the adverse impact on the environment. These systems should be adapted for such diseases, which are not of regular occurrence but rather come in destructive forms, when weather conditions are favorable.
Spray warning services for the downy mildew of grapevine in France, Italy and Germany during the 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 disease outbreak in the near future, data on these factors are prerequisite.

1. Host factors

Disease triangle

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

2. Pathogen factors

Based on the previous history or survey data, the presence of a pathogen determine the disease epidemics. Data on the amount of inoculum, their germination, dispersal, incubation period, sporulation, perenating stages are essential for the 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, the presence of primary inoculum, their density and viability are 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, the presence and density of pathogens are tested by culturing them on a specific culture medium. In air, the 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 soil are also measured.

3.Forecasting based on correlative information

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

4.Computer-based disease forecasting models

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

Forecast system	Diseases	Country
EPIDEM	Early blight of potato and tomato caused by Alternaria solani	NA
TOMCAST/FAST	Early blight of potato and tomato caused by Alternaria solani	NA
MYCOS	Mycosphaerella blight of Chrysanthemum	NA
EPIVEN	Apple scab caused by Venturia inaequalis	NA
PLASMO	Downy mildew of grapevine caused by Plasmopara viticola	NA
EPICORN	Southern corn leaf blight caused by Helminthosporium maydis	NA
BLIGHTCAST	Late blight of potato caused by Phytophthora infestans	NA
USABlight	Late blight of potato caused by Phytophthora infestans	USA
NDAWN	late blight and early blight	Dakota
Indo-BlightCast	Late blight of potato caused by Phytophthora infestans	India
Phytoprog	Late blight of potato caused byPhytophthora infestans	NA
CERCOS	Cercospora blight of celery	NA
EPIDEMIC	Designed for stripe rust of wheat, but could be modified for other diseases	NA
MARYBLIGHT	Fire blight on apple caused by Erwinia amylovora	NA

Examples of disease forecasting

1. Late blight of potato

Late blight of potato is forecasted after the 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, computerized models, such as, BLIGHTCAST, Indo-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 the basis of the correlative information method. The disease is predicted when, minimum night temperature ranges between 20 and 26 °C in association with 90 % or above relative humidity.

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First published on 01-07-2020
Last updated on 19-09-2024

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