Insect Modeling are used for a variety of purposes from study of the dynamics of the Insect population, determine the importance of factors of regulating of population, individual development of insects and future projections of insect development

1. Muhammad Qasim
Aroj Bashir
Dept. Environmental Sciences
University of Gujrat

2. OBJECTIVES
 WHAT IS INSECT MODLING
 WHY INSECT MODLING IMPORTANT
 SOME NAME OF MODELS
 PLANT DISEASES MODEL
 SIMPLE SIMULATION MODEL
 DSSAT CROPPING SYSTEM MODEL
 INSECT DEGREE DAY MODEL

3. WHAT IS INSECT MODLING
What is Insect:
 A small arthropod animal that has six legs
and generally one or two pairs of wings.
What is Modeling:
 The act or art of making a model from which
a work of art is to be executed; the formation
of a work of art from some plastic material.
 Insect Modeling are used for a variety of
purposes from study of the dynamics of the
Insect population, determine the importance
of factors of regulating of population,
individual development of insects and future
projections of insect development

4. WHY INSECT MODLING
IMPORTANT
 On the planet of earth most adverse condition
occur like climate change , global warming ,
earth quick and flood etc.
 In these all phenomena's the population of
insects are disturb.
 Increasing population and increasing demand
of foods in this aspect of all over the world use
insecticides and pesticides to kill the insects
and save the foods.
 For the study of the effect of insecticides and
pesticides on insects.
 For the study of increasing of population and
decline of population in insects.

5. WHY INSECT MODELING
IMPORTANT
 There are hundreds of thousands of
different kinds of insects present.
 The Smithsonian Institution reports
there are approximately 900,000
different kinds of known insects on the
planet.
 Insect colors and forms vary widely.
 F0r distribution and study of species of
insect we build model.

6. SOME NAME OF MODELS
 Plant Diseases Model
 Simple Simulation Model
 DSSAT Cropping System Model
 Insect Degree Day Model

7. PLANT DIEASES MODEL
About Plant Diseases Model
 A plant disease model is a mathematical
description of the interaction between
environmental, host, and pathogen variables that
can result in disease.
 A model can be presented as a simple rule, an
equation, a graph, or a table.
 The output of a model can be a numerical index
of disease risk, predicted disease incidence or
severity, and/or predicted inoculums
development.

8. MODEL DEVELOPMENT, VALIDITION
AND IMPLITION
 Plant disease models typically are
developed from laboratory and/or field
studies by researchers cooperating with
extension personnel.
 The goal is to predict the risk of disease
and/or development of inoculum, based
on monitoring key environmental, host,
and pathogen variables.
 Models should be evaluated in the field,
and actual disease compared to predicted
disease.

9. MODEL DEVELOPMENT,
VALIDITION AND IMPLITION
 Validation" means testing of the model in
the field over several cropping seasons
and/or locations to evaluate the ability of a
model to assess or predict disease.
 Typically a researcher will fine-tune and
re-test a model several times.
 Models developed in one area are
frequently validated by researchers in
other areas.
 The models may need region-specific
modifications.

10. MODEL DEVELOPMENT, VALIDITION
AND IMPLITION
 After being found to predict disease or
inoculum levels adequately.
 Models can be used with micro scale
weather data obtained through the use of
on-site, user-friendly electronic weather
stations that monitor microclimate
variables such as air temperature, relative
humidity, hours of free moisture, and
precipitation.
 The use of the model to guide the timing of
fungicide applications.

11. FUNGICIDES AND DIEASE
FORECASTING
 These plant disease models can be used
to predict the timing of fungicide
applications.
 Exercise caution when using these
models because disease control in the
field depends on many additional
variables.
 Important variables include a fungicide's
activity, weather, eradicative, other are
host phenology or growth stage, and
pathogen virulence.

12. CROP DIEASES
Crop Name Diease
Almond Shot hole, Scap
Apple Fire Blight, Scap
Carrot Alternaria leaf blight
Tomato Powdery mildew
Grape Botrytis bunch rot,
Powdery mildew
Potato Late blight

13. SIMPLE SIMULATION MODEL
 A simple simulation model is described for populations of the
blue-green lucerne aphid (Acyrthosiphon kondoi Shinji) and
used to determine the importance of factors regulating the
population.
 Simulation modeling as a tool has much to offer in the fields of
insect ecology and pest management.

14. ROLE OF SIMPLE SIMULATION
MODEL
 The role of modeling in helping to
understand an insect's population
dynamics.
 Identifying the nature and causes of
population change.
 Graphically illustrated by the problem of
predicting the growth of populations
with overlapping generations.
 It was attempted over 50 years ago by
Thompson (1931) and his paper is a
salutory example of the power of
technology to render routine what was
once a major undertaking.

15. AIM OF SIMPLE SIMULATION
MODEL
 The aim was to account for observed behavior of the
populations by assembling existing information in the
simplest possible model.
 In this case aphids were stored in a 2-dimensional matrix.
 the columns being day age-classes and the 3 rows being
numbers of apterae.
 Numbers of alates. and the dav-demee total above 2.6
degree accumulated by the age-class.
 The model is written in FORTRAN and operates in
calendar time with a step-length of 1 day.

16. AIM OF SIMPLE SIMULATION MODEL
Survival following grazing or cutting
of the lucerne had to be estimated in
the same way.
The main documented source of
additional effective mortality is the
production and
dispersal of winged alates
Which is accounted'for in the model by
using observed proportions of alates
among 4th instar nymphs and assuming
that all fly as adults before reproducing
The developmental threshold of 2.6OC
is below virtually all daily minima, day-degrees
could be accumulated by
simply subtracting 2.6 from the mean
temperature each day.

17. CONULSIONS OF SIMPLE
SIMULATION MODEL
 There are 2 possible approaches to modeling blue-green
lucerne aphid populations.
 One is to express the temperature-dependent exponential
growth rate of the whole population.
 the density of natural enemies, suitably weighted.
 the second, more detailed modeling approach described
in this paper is a more appropriate research tool, and as
such has yielded 3 useful conclusions.

18. CONULSIONS OF SIMPLE
SIMULATION MODEL
 First, it showed that the commonly accepted
cause of population declines, namely alate
production, does not in fact account for them
and that other mechanisms must be involved.
 Second, it demonstrated the relative importance
of these factors in population regulation, once
their existence and individual effects had been
determined by experiment.
 Finally, it highlighted a deficiency in current
knowledge, particularly of the factors which
depress aphid performance in the field below
the temperature-dependent potentials
identified in laboratory experiments.

19. DSSAT CROPING SYSTEM MODEL
 The decision support system for agro
technology transfer (DSSAT).
 DSSAT has been in use for the last 15 years by
researchers worldwide.
 Information needs for agricultural decision
making at all levels are increasing rapidly due
to increased demands for agricultural
products and increased pressures on land,
water, and other natural resources check by
DSSAT model.
 To facilitate the application of crop models in
a systems approach to agronomic research by
DSSAT model.

20. DSSAT CROPING SYSTEM MODEL
 The decision to make these models compatible led to
the design of the DSSAT and the ultimate
development of compatible models for additional
crops, such as potato, rice, dry beans, sunflower and
sugarcane

21. OVERALL DESCRIPTION OF THE DSSAT CROPPING
SYSTEM MODEL
 Development and yield of a crop growing on a uniform
area of land under prescribed or simulated management
as well as the changes in soil water, carbon, and nitrogen
that take place under the cropping system over time.
 The most important features of our approach are.
 It separates modules along disciplinary lines.
 It defines clear and simple interfaces for each module.
 It enables individual components to be plugged in or
unplugged with little impact on the main program or
other modules, i.e. for comparison of different models or
model components,

22. OVERALL DESCRIPTION OF THE
DSSAT CROPING SYSTEM MODEL
 It enables modules written in different programming
languages to be linked together.
 It facilitates cooperation among different model
development groups where each can focus on specific
modules as building blocks for expanding the scope
and utility of the CSM. All coauthors of this paper
actively contributed to the overall design of
DSSAT/CSM, provided modules, and are responsible
for maintenance of specific modules.

23. COMPONENT DESCRIPTIONS OF
DSSAT CROP MODLING
 The main program reads information from the DSSAT
standard file that describes a particular experiment or
situation to be simulated.
 It initiates the simulation by setting the DYNAMIC
variable for initializing the run and calls the Land Unit
module.
 Then starts a crop season time loop and calls the Land
Unit module for initializing variables that must be set at
the start of each season
 The Land Unit module calls each of the primary cropping
system modules shown in day.

24. SOME BASIC MODULE IS GIVEN
 Weather module
 Soil module
 Soil temperature sub module
 Soil/plant/atmosphere module
 Template crop module
 Management module
 Pest module

25. EXAMPLE APPLICATIONS OF DSSAT
MODEL
 Many of these applications have been done
to study management
 Options at study sites, including fertilizer,
irrigation, pest management, and site-specific
farming.
 These applications have been conducted by
agricultural researchers from different
disciplines, frequently working in teams to
integrate cropping systems analysis using
models with field agronomic
 Research and socioeconomic information to
answer complex questions about
production, economics, and the
environment.

26. DEGREE-DAY MODELS
 Phenology models, also known as degree-day
models.
 Phenology is the study of relationships
between the weather and biological
processes such as insect development.
 It help predict the best timing of pest
management activities such as pesticide
applications.
 These models are based on the fact that an
insect's growth is closely linked to the
temperature where it is found.
 Phenology models do not operate on a
calendar-day basis but on a heat unit
(degree-day) scale.

27. HOW DEGREE-DAY MODELS WORK
 The temperature limits on physiological
reactions are called the upper and lower
developmental thresholds.
 The heat-unit scale is often called a
physiological time scale.
 When the temperature rises above the
upper threshold, development stops and
if temperatures continue to rise, the
insect dies.
 When the temperature drops below the
lower threshold, development stops, but
insects rarely die unless the water in their
cells freezes.

28. HOW DEGREE DAY MODELS ARE
DEVELOPED
 The number of degree days needed for a certain
insect to develop can be calculated in a
laboratory.
 30 or more insects are reared at a constant
temperature and the time needed for each insect
to complete each stage- egg, larva ,pupa and
adult-is recorded.
 The rate of development at the various
temperatures is then plotted and from the graph
the lower and upper development thresholds
and the degree days needed to complete a stage
of development can be calculated.
 Field information from several different sites and
several different years is required to validate the
models.

29. DEGREE-DAY MODELS
 Most degree-day models use a sine-wave curve to
approximate the daily temperature cycle from night to
day. The upper threshold can have at least two forms:
 A horizontal cutoff, where degree-day accumulations
above the upper threshold do not count.
 A vertical cutoff where, once the upper threshold is
surpassed, no more degree-days are accumulated until
the temperature drops below the threshold again.

30. SUCCESSFUL MODELS
 Degree-day models for the following tree
fruit pests are available inWashington.
 It is used in most fruit growing regions of
the United States to time sprays.
 The model allows us to get maximum
longevity of the cover sprays.
 It is critical to apply them as close to the
predicted time as possible.
 When sprays are applied late, more
larvae already will have entered the fruit
where they are difficult to kill.