Computer Application for Predicting & Forecasting pest outbreak and disease

1. COMPUTER APPLICATION FOR PREDICTING & FORECASTING
PEST OUTBREAK AND DISEASE
SUBMITTED BY-
DIKSHA SINHA BAC/M/PLPATH/001/2017-18
ENT-518

2. FORECASTING
Forecasting involves all the activities involved in
ascertaining & notifying the growers in a region
that-
• conditions are sufficiently favourable for certain
diseases or pest outbreak
• application of appropriate control measures will
result in economic gain,or
• the amount expected is unlikely to be enough
to justify the expenditure of time,energy and
money for control.

3. OBJECTIVES OF PEST FORECASTING
• To predict the forthcoming infestation level of the pest.
• To find out the critical stage at which the application of insecticides
would provide maximum protection.
• To guide farmers about the timing and biology of insect
incidence,reduce pesticide amounts and achieve quality results.
• To allow farmers to arrange their cropping system to minimise pest
damage, yield loss & maximise harvest.

4. TYPES OF PEST FORECASTING
Pest forecasting may be divided into 2 categories-
1. Short-term forecasting:
It covers a particular season or one or two successive seasons only.
It is usually sampled from a particular area under a crop.
e.g. Wheat grain aphid (Sitobion avenae)
2. Long-term forecasting:
These are based on possible effect of weather on the pest population.
It covers a large area.
e.g. Brown planthopper(Nilaparvata lugens) and white-backed plant
hopper
(Sogatella furcifera)

5. REMOTE SENSING
• Remote sensing technologies are used to gather information about
the surface of the earth from a distant platform, usually a satellite or
airborne sensor.
• The integration of RS, GPS, GIS are valuable tools that enable
resource managers to develop distribution maps of insect infestations
and disease occurrence over large areas.
• Site-specific data, such as type of insect, level of damage, stage of
attack and yield loss are collected, stored and managed in database.

6. DATA BASE MANAGEMENT & COMPUTER PROGRAMMING
• Database management is widely used in pest identification,
monitoring, population modelling, biology, exploring control measures
and Decision Support System(DSS) to take decision in pest
management interventions.
• The database has been developed in the form of internet based DSS,
expert system,etc.
• The National Centre for Integrated Pest Management (NCIPM),New
Delhi has developed database management system with information
on pest and disease management, in different crops grown in India.

7. DECISION SUPPORT SYSTEM (DSS)
• DSS are computer based information system designed to help
farmers to select one of the many alternative solutions to a plant
protection problem.
• In IPM, DSSs are widely used for identification,recommendation of
insecticides, pest outbreaks.
• The DSS suppports adoption of IPM technologies to reduce
production cost & minimise environmental and public hazard.

10. COMPUTER BASED EXPERT SYSTEMS (EXS)
• Another computer programme based on database
management is Expert System (ES).
• It differs from DSS in objectives, operational differences,
users and development methodology.
• The ES help in identification of insect-pest, estimating
risk, control measures recommendations,etc.

14. MODELS FOR DISEASE PREDICTION
• Empirical models-
based on experience of growers, the S scientists or both
• Simulation models-
based on theoretical relationships

15. One such computer based programmes in the USA is known as
‘Blitecast’ for potato late blight (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.

16. 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 forecast (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 and feeds the new
data into the computer.
• Within a fraction of second the computer analyses the data.
• It returns a 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.

17. Examples of well developed forecasting systems are given below.
In West Germany, ‘Phytoprog’ is the programme used for potato late blight . It is
based on measurements of temperature, relative humidity and rainfall.
In India, EPIBLASTComputer based forecasting system for rice blast ( Pyricularia
ozyzae) has been developed.
‘Epimay’ is a system for forecasting Southern corn leaf blight (Bipolaris
maydis) in the USA based on conceptual model.