Epidemiology and Plant Disease Forecasting | Agriculture Optional Notes for UPSC PDF Download

Disease Forecasting

Plant disease forecasting is the process of predicting the occurrence of plant diseases in a specific area in advance. The goal is to anticipate and prepare for potential disease outbreaks or escalations in disease intensity, enabling proactive measures to mitigate losses. Disease forecasts require coordinated efforts, along with investments of time, resources, and funds. They serve as a valuable tool for the timely application of chemical treatments. The earliest warning services for growers, like the grapevine downy mildew forecasting programs in France, Germany, and Italy in the 1920s, were among the first to establish such forecasting schemes. Various methods for disease forecasting are available for different plant diseases.

Information’s needed for disease forecasting

To effectively forecast diseases, it's essential to have a foundation in epidemiology, which deals with how diseases develop due to various factors related to the host, pathogen, and environment. Before making forecasts, understanding the elements of an epidemic and its constituents is crucial.
The key information required for disease forecasting includes:

Host Factors

• Prevalence of susceptible plant varieties in the specific area.
• Understanding how the host responds to pathogen activity at different growth stages. Some diseases may affect seedlings, while others target mature plants.
• The density and distribution of host plants within the area. High-density populations of susceptible varieties can lead to rapid epidemic spread. Growing susceptible plants in isolated areas and within limited areas are less susceptible to widespread disease outbreaks.

Pathogen Factors

• The initial amount of inoculum (disease-causing agents) in the air, soil, or planting material.
• The dispersal of these inoculums.
• Factors affecting spore germination.
• The infection process.
• The incubation period for the pathogen within the host.
• Spore production on infected hosts.
• The re-dispersal and dissemination of spores.
• The presence of perennial stages in the pathogen's life cycle.
• The density and potential of inoculum in seeds, soil, and the air.

Environmental Factors

• Temperature levels.
• Humidity levels.
• Light intensity.
• Wind speed.

Requirements or conditions for disease forecasting

There are five primary requirements or conditions that must be met for a disease forecast to be useful and successful:

• Economic Significance: The disease in question should cause significant damage in terms of yield loss or product quality. Assessing the extent of damage is crucial for developing a disease control strategy. For example, annual yield loss estimates due to barley powdery mildew in England and Wales have ranged from 6 to 13%. Potato late blight can lead to a yield loss of 28% if it reaches 75% infection by mid-August. Diseases like apple scab and potato common scab not only lower the quality of the produce but also reduce the value of the harvested crop, resulting in substantial financial losses for growers.
• Cost-Effective Control Measures: Effective control measures must be available at a cost that is economically acceptable.
• Seasonal Variation: The disease should exhibit seasonal variation in terms of the timing of the first infections and the rate of its subsequent progress. If the disease doesn't show such variation, there is no need for forecasting.
• Scientific Basis: The criteria or model used to make predictions must be based on solid investigative work conducted in both the laboratory and the field. It should be tested over several years to establish its accuracy and applicability across all the locations where it is intended to be used.
• Resources for Implementation: Growers should have sufficient manpower and equipment to apply control measures when disease warnings are issued. Long-term forecasts or predictions are generally more useful than short-term ones.

Methods of disease forecasting

Disease forecasting methods involve a combination of field observations, weather data collection, and correlations between different variables.
The following methods are commonly used in disease forecasting:

• Forecasting Based on Primary Inoculum: This method involves determining the presence, density, and viability of primary inoculum in the air, soil, or planting material. Various devices, such as spore traps, are used to assess the occurrence of viable spores or propagules in the air. For soil-borne diseases, the monoculture method can be employed to determine the primary inoculum in the soil. Seed testing methods are also used to detect diseases in seed lots.
• Forecasting Based on Weather Conditions: Weather conditions, including temperature, relative humidity, rainfall, light, and wind velocity, are monitored during the crop season and the intercrop season. Data regarding weather conditions above the crop and at the soil surface are also recorded.
• Forecasting Based on Correlative Information: Data from several years are collected and correlated with disease intensity to develop forecasting criteria. The relationship between disease observations and standard meteorological data is used to forecast diseases such as Septoria leaf blotch of wheat, fire blight of apple, and barley powdery mildew.
• Use of Computers for Disease Forecasting: In advanced countries, computer-based programs are used for disease forecasting. These programs provide quick results and are widely used for predicting diseases. For example, the "Blitecast" program is used for forecasting potato late blight in the USA. This system requires the input of environmental data to make forecasts.
  Examples of well developed forecasting systems are given below:
  a. Early and late leaf spots of groundnut A technique has been developed for forecasting early and late leaf spots of groundnut in the U.S.A. When the groundnut foliage remains wet for a period greater than or equal to 10 h and the minimum temperature is 21°C or higher for two consecutive days or nights, the disease development is forecasted. A computer programme has been developed in the USA. This is accurate and is widely used in the USA. The data on hours for day with relative humidity (RH) of 95% and above and minimum temperature (T) during the RH observations for the period, for the previous 5 days are fed to the computer. Calculations are rounded to whole numbers. The T/RH index for each of the five days is calculated e.g., when hours of the RH 95% equal 10 and the minimum temperature during the period equals 21.1°C the T/RH index is 2.0 .The T/RH indices for days 4 and 5 are summed. If the total index exceeds 4 disease is forecasted. If the index is 3 or less no disease is forecasted.
  b. Late blight of potato In the USA a forecasting programme has been developed for late blight of potato (Phytophthora infestans). The initial appearance of late blight is forecasted 7 to 14 days after the occurrence of 10 consecutive blight favourable days. A day is considered to be blight favourable when the 5 day average temperature is 25.5°C and the total rainfall for the last 10 days is more than 3.0 cm. A computerized version (Blitecast) has also been developed in the U.S.A for forecasting potato late blight. Blitecast is written in Fortran IV. When a farmer desires blight cast (blitecast) he telephones the blight cast operator and reports the most recently recorded environmental data. The operator calls for the blight cast programmes in the computer viz., typewriter terminal and feeds the new data into the computer. Within a fraction of second the computer analyses the data and series of a forecast and spray recommendations to the operator who relays it to the farmer. The entire operation can be completed during standard three minutes telephone call. The system makes one of the four recommendations viz., no spray, late blight warning, 7 days spray schedule or 5 days spray schedule. The last 5 days spray schedule is issued only during severe blight weather. In West Germany, ‘Phytoprog’ is the programme used. It is based on measurements of temperature, relative humidity and rainfall. Phytoprog provides a negative prognose (an indication of when the usual routine spray application should be dispensed with).
  c. Blister blight of tea A system for predicting epidemics of blister blight of tea ( Exobasidium vexans) has been developed based on the number of spores in the air in the tea plantation and the duration of surface wetness on the leaves. The duration of sunshine is negatively correlated with the duration of surface wetness. The following prediction equation has been developed. Y = 1.8324 + 0.8439 X1 + 0.9665 X2 – 0.1031 X3where, X1 = log % infection t2X2 = log % infection t2 – log infection t1Y = log of the number of spores in the air and t1 – t2 three weeksX3 = mean daily sunshine for a 7 days period preceding t2
  d. Southern corn leaf blight ‘Epimay’ is a system for forecasting Southern corn leaf blight (Bipolaris maydis) based on conceptual model.
  e. Rice blast In India, forecasting rice blast ( Pyricularia ozyzae) is done by correlative information method. It is predicted on the basis of minimum night temperature 20 to 26°C in association with high relative humidity of 90% or above. Computer based forecasting system has also been developed for rice blast in India.
  f. Wheat stem rust Forecasting wheat stem rust epidemic is done by analysing therain samples which give precise data for inoculum present in the air. Moreover several wind trajectors are also prepared to survey the air-borne primary inoculums and its deposition. It has been observed that primary inoculum comes from South India, to the plains of Central and North India.
  g. Brown stripe downy mildew of corn The forecasting of brown stripe downy mildew of corn (Sclerophthora raysise var. zeae ) which is restricted to India is done on the basis of average rainfall 100 to 200 cm or more accompanied by low temperature ( 25°C or less). Spore trappingTechniques of acquisition of biological data for consecutive forecasting models are important. Spore traps have been widely used in to complete disease with weather conditions. Spore trapping is useful for understanding epidemiology of a disease and behaviour of the pathogens. This helps in developing models on dispersal of pathogens or on epidemiology of the disease and to formulate methods of management.
  Methodology of spore trapping depends on the following objectives of the worker:
  1. Biology of the pathogen
  2. For infection forecasting
  3. Spore dispersal gradients
  4. Management of the disease 

In epidemics of air-borne plant diseases the number of spores of the pathogen landing on the plant which depends on the number of spores in the atmosphere above the crop is an important factor for the quantitative sampling of the atmosphere (number of spores per unit volume of air).For trapping and estimating these studies different types of traps are used. The following spore traps are usually employed in trapping of fungal spores. Cylindrical rods or microscopic glass slides: It helps to gather data on the spore arrival in a locality. In this, the surface of microscopic slide is smeared with grease and made sticky.
In the method, quantitative estimation is not possible as number of spores collected is very low:

• Hirst’s volumetric spore trap (Hirst 1952) In this instrument, air is sucked into at a controlled rate and impinged on to a glass slide moved by a clockwork mechanism past the orifice. It gives continuous count of spores in 24 h. The number of spores per unit volume of air at any given time can thus be calculated. 
• Rotorod sampler or rotorod spore trap (Sutton and Jones 1976) It comprises of a ‘U’ shaped rod attached at its mid point to the shaft of a small battery operated electric motor. In this equipment the surface of the rod is covered with a vaseline strip of transparent cellophanes to catch spores which can be taken off and mounted on a glass slide. From the area of the strip and the speed of rotation, the volume of air samples can be calculated. 
• Anderson cascade spore sampler It is a device where Petri plates with nutrient agar are used to collect the spores. 
• Bourdillon slit sampler Air is sucked in a chamber by vacuum pump which strikes the rotating Petri dish containing agar medium. The agar medium retains the spores sucked in the air. Concentration of viable spores is calculated after counting germinated spores in the medium. 
• Burkard’s 7 day volumetric spore trap This device records spores in the air drawn by a pump on 7 days basis on a cellophane strip wrapped on a drum rotating inside a chamber. 
• Jet spore trap In the above sampling methods, the viability of the spores cannot be determined. To overcome this, living plants have been used as spore traps. A jet spore trap in which spores are impacted in an air jet into a column of still air, through which they fall, to settle on leaf segments exposed at the base of the chamber. In this trap, suitable cultivars of host plants can be employed to determine number of viable spores.