1. Muhammad QasimAroj BashirDept. Environmental SciencesUniversity 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 MODLINGWhat is Insect: A small arthropod animal that has six legsand generally one or two pairs of wings.What is Modeling: The act or art of making a model from whicha work of art is to be executed; the formationof a work of art from some plastic material. Insect Modeling are used for a variety ofpurposes from study of the dynamics of theInsect population, determine the importanceof factors of regulating of population,individual development of insects and futureprojections of insect development 4. WHY INSECT MODLINGIMPORTANT On the planet of earth most adverse conditionoccur like climate change , global warming ,earth quick and flood etc. In these all phenomena's the population ofinsects are disturb. Increasing population and increasing demandof foods in this aspect of all over the world useinsecticides and pesticides to kill the insectsand save the foods. For the study of the effect of insecticides andpesticides on insects. For the study of increasing of population anddecline of population in insects. 5. WHY INSECT MODELINGIMPORTANT There are hundreds of thousands ofdifferent kinds of insects present. The Smithsonian Institution reportsthere are approximately 900,000different kinds of known insects on theplanet. Insect colors and forms vary widely. F0r distribution and study of species ofinsect 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 MODELAbout Plant Diseases Model A plant disease model is a mathematicaldescription of the interaction betweenenvironmental, host, and pathogen variables thatcan result in disease. A model can be presented as a simple rule, anequation, a graph, or a table. The output of a model can be a numerical indexof disease risk, predicted disease incidence orseverity, and/or predicted inoculumsdevelopment. 8. MODEL DEVELOPMENT, VALIDITIONAND IMPLITION Plant disease models typically aredeveloped from laboratory and/or fieldstudies by researchers cooperating withextension personnel. The goal is to predict the risk of diseaseand/or development of inoculum, basedon monitoring key environmental, host,and pathogen variables. Models should be evaluated in the field,and actual disease compared to predicteddisease. 9. MODEL DEVELOPMENT,VALIDITION AND IMPLITION Validation" means testing of the model inthe field over several cropping seasonsand/or locations to evaluate the ability of amodel to assess or predict disease. Typically a researcher will fine-tune andre-test a model several times. Models developed in one area arefrequently validated by researchers inother areas. The models may need region-specificmodifications. 10. MODEL DEVELOPMENT, VALIDITIONAND IMPLITION After being found to predict disease orinoculum levels adequately. Models can be used with micro scaleweather data obtained through the use ofon-site, user-friendly electronic weatherstations that monitor microclimatevariables such as air temperature, relativehumidity, hours of free moisture, andprecipitation. The use of the model to guide the timing offungicide applications. 11. FUNGICIDES AND DIEASEFORECASTING These plant disease models can be usedto predict the timing of fungicideapplications. Exercise caution when using thesemodels because disease control in thefield depends on many additionalvariables. Important variables include a fungicide'sactivity, weather, eradicative, other arehost phenology or growth stage, andpathogen virulence. 12. CROP DIEASESCrop Name DieaseAlmond Shot hole, ScapApple Fire Blight, ScapCarrot Alternaria leaf blightTomato Powdery mildewGrape Botrytis bunch rot,Powdery mildewPotato Late blight 13. SIMPLE SIMULATION MODEL A simple simulation model is described for populations of theblue-green lucerne aphid (Acyrthosiphon kondoi Shinji) andused to determine the importance of factors regulating thepopulation. Simulation modeling as a tool has much to offer in the fields ofinsect ecology and pest management. 14. ROLE OF SIMPLE SIMULATIONMODEL The role of modeling in helping tounderstand an insect's populationdynamics. Identifying the nature and causes ofpopulation change. Graphically illustrated by the problem ofpredicting the growth of populationswith overlapping generations. It was attempted over 50 years ago byThompson (1931) and his paper is asalutory example of the power oftechnology to render routine what wasonce a major undertaking. 15. AIM OF SIMPLE SIMULATIONMODEL The aim was to account for observed behavior of thepopulations by assembling existing information in thesimplest possible model. In this case aphids were stored in a 2-dimensional matrix. the columns being day age-classes and the 3 rows beingnumbers of apterae. Numbers of alates. and the dav-demee total above 2.6degree accumulated by the age-class. The model is written in FORTRAN and operates incalendar time with a step-length of 1 day. 16. AIM OF SIMPLE SIMULATION MODELSurvival following grazing or cuttingof the lucerne had to be estimated inthe same way.The main documented source ofadditional effective mortality is theproduction anddispersal of winged alatesWhich is accounted'for in the model byusing observed proportions of alatesamong 4th instar nymphs and assumingthat all fly as adults before reproducingThe developmental threshold of 2.6OCis below virtually all daily minima, day-degreescould be accumulated bysimply subtracting 2.6 from the meantemperature each day. 17. CONULSIONS OF SIMPLESIMULATION MODEL There are 2 possible approaches to modeling blue-greenlucerne aphid populations. One is to express the temperature-dependent exponentialgrowth rate of the whole population. the density of natural enemies, suitably weighted. the second, more detailed modeling approach describedin this paper is a more appropriate research tool, and assuch has yielded 3 useful conclusions. 18. CONULSIONS OF SIMPLESIMULATION MODEL First, it showed that the commonly acceptedcause of population declines, namely alateproduction, does not in fact account for themand that other mechanisms must be involved. Second, it demonstrated the relative importanceof these factors in population regulation, oncetheir existence and individual effects had beendetermined by experiment. Finally, it highlighted a deficiency in currentknowledge, particularly of the factors whichdepress aphid performance in the field belowthe temperature-dependent potentialsidentified in laboratory experiments. 19. DSSAT CROPING SYSTEM MODEL The decision support system for agrotechnology transfer (DSSAT). DSSAT has been in use for the last 15 years byresearchers worldwide. Information needs for agricultural decisionmaking at all levels are increasing rapidly dueto increased demands for agriculturalproducts and increased pressures on land,water, and other natural resources check byDSSAT model. To facilitate the application of crop models ina systems approach to agronomic research byDSSAT model. 20. DSSAT CROPING SYSTEM MODEL The decision to make these models compatible led tothe design of the DSSAT and the ultimatedevelopment of compatible models for additionalcrops, such as potato, rice, dry beans, sunflower andsugarcane 21. OVERALL DESCRIPTION OF THE DSSAT CROPPINGSYSTEM MODEL Development and yield of a crop growing on a uniformarea of land under prescribed or simulated managementas well as the changes in soil water, carbon, and nitrogenthat 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 orunplugged with little impact on the main program orother modules, i.e. for comparison of different models ormodel components, 22. OVERALL DESCRIPTION OF THEDSSAT CROPING SYSTEM MODEL It enables modules written in different programminglanguages to be linked together. It facilitates cooperation among different modeldevelopment groups where each can focus on specificmodules as building blocks for expanding the scopeand utility of the CSM. All coauthors of this paperactively contributed to the overall design ofDSSAT/CSM, provided modules, and are responsiblefor maintenance of specific modules. 23. COMPONENT DESCRIPTIONS OFDSSAT CROP MODLING The main program reads information from the DSSATstandard file that describes a particular experiment orsituation to be simulated. It initiates the simulation by setting the DYNAMICvariable for initializing the run and calls the Land Unitmodule. Then starts a crop season time loop and calls the LandUnit module for initializing variables that must be set atthe start of each season The Land Unit module calls each of the primary croppingsystem 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 DSSATMODEL Many of these applications have been doneto study management Options at study sites, including fertilizer,irrigation, pest management, and site-specificfarming. These applications have been conducted byagricultural researchers from differentdisciplines, frequently working in teams tointegrate cropping systems analysis usingmodels with field agronomic Research and socioeconomic information toanswer complex questions aboutproduction, economics, and theenvironment. 26. DEGREE-DAY MODELS Phenology models, also known as degree-daymodels. Phenology is the study of relationshipsbetween the weather and biologicalprocesses such as insect development. It help predict the best timing of pestmanagement activities such as pesticideapplications. These models are based on the fact that aninsect's growth is closely linked to thetemperature where it is found. Phenology models do not operate on acalendar-day basis but on a heat unit(degree-day) scale. 27. HOW DEGREE-DAY MODELS WORK The temperature limits on physiologicalreactions are called the upper and lowerdevelopmental thresholds. The heat-unit scale is often called aphysiological time scale. When the temperature rises above theupper threshold, development stops andif temperatures continue to rise, theinsect dies. When the temperature drops below thelower threshold, development stops, butinsects rarely die unless the water in theircells freezes. 28. HOW DEGREE DAY MODELS AREDEVELOPED The number of degree days needed for a certaininsect to develop can be calculated in alaboratory. 30 or more insects are reared at a constanttemperature and the time needed for each insectto complete each stage- egg, larva ,pupa andadult-is recorded. The rate of development at the varioustemperatures is then plotted and from the graphthe lower and upper development thresholdsand the degree days needed to complete a stageof development can be calculated. Field information from several different sites andseveral different years is required to validate themodels. 29. DEGREE-DAY MODELS Most degree-day models use a sine-wave curve toapproximate the daily temperature cycle from night today. The upper threshold can have at least two forms: A horizontal cutoff, where degree-day accumulationsabove the upper threshold do not count. A vertical cutoff where, once the upper threshold issurpassed, no more degree-days are accumulated untilthe temperature drops below the threshold again. 30. SUCCESSFUL MODELS Degree-day models for the following treefruit pests are available inWashington. It is used in most fruit growing regions ofthe United States to time sprays. The model allows us to get maximumlongevity of the cover sprays. It is critical to apply them as close to thepredicted time as possible. When sprays are applied late, morelarvae already will have entered the fruitwhere they are difficult to kill.