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
forecasting is the first step for IPM. forecasting reduce the protection cost.various models and software are now known to present days ,Which are useful in control the pest.
Now a days new apps and applications came into existence which are routinely using by public..in this context use of these software tools and android applications can be exploited to help the farming community for real time solutions without any gap in transfer of IPM information.This ppt useful to know the areas and forms of usage of computers in IPM.
forecasting is the first step for IPM. forecasting reduce the protection cost.various models and software are now known to present days ,Which are useful in control the pest.
Now a days new apps and applications came into existence which are routinely using by public..in this context use of these software tools and android applications can be exploited to help the farming community for real time solutions without any gap in transfer of IPM information.This ppt useful to know the areas and forms of usage of computers in IPM.
Parasitoids and Predators, their attributes.Bhumika Kapoor
Insect parasitoids have an immature life stage that develops on or within a single insect host, ultimately killing the host, hence the value of parasitoids as natural enemies. Adult parasitoids are free-living and may be predaceous. Parasitoids are often called parasites, but the term parasitoid is more technically correct. Most beneficial insect parasitoids are wasps or flies, although some rove beetles (see Predators) and other insects may have life stages that are parasitoids.
where as the Major characteristics of arthropod predators includes adults and immatures are often generalists rather than specialists, they generally are larger than their prey, they kill or consume many prey males, females, immatures, and adults may be predatory and they attack immature and adult prey.
the repeated use of the same chemical which has the same mode of action that leads to the loss of insect sensitivity and also heritable change would occur in the genome nothing but resistance that means the population not able to control with the normal dose need to develop resistant management strategies
Parasitoids and Predators, their attributes.Bhumika Kapoor
Insect parasitoids have an immature life stage that develops on or within a single insect host, ultimately killing the host, hence the value of parasitoids as natural enemies. Adult parasitoids are free-living and may be predaceous. Parasitoids are often called parasites, but the term parasitoid is more technically correct. Most beneficial insect parasitoids are wasps or flies, although some rove beetles (see Predators) and other insects may have life stages that are parasitoids.
where as the Major characteristics of arthropod predators includes adults and immatures are often generalists rather than specialists, they generally are larger than their prey, they kill or consume many prey males, females, immatures, and adults may be predatory and they attack immature and adult prey.
the repeated use of the same chemical which has the same mode of action that leads to the loss of insect sensitivity and also heritable change would occur in the genome nothing but resistance that means the population not able to control with the normal dose need to develop resistant management strategies
Mathematical Modeling for Practical ProblemsLiwei Ren任力偉
Mathematical modeling is an important step for developing many advanced technologies in various domains such as network security, data mining and etc… This lecture introduces a process that the speaker summarizes from his past practice of mathematical modeling and algorithmic solutions in IT industry, as an applied mathematician, algorithm specialist or software engineer , and even as an entrepreneur. A practical problem from DLP system will be used as an example for creating math models and providing algorithmic solutions.
Mobile Data Collection and Data Management in Modern AgricultureCAPIGI
Presentation by Thinus Glitz of Claas Agrosystems on Claas' vision and systems for precision agriculture, held at CAPIGI 2011 4-6 April 2011 in Amsterdam.
Seed treatment, Seed germination and crop establishment in relation to soil m...Alkesh Patel
Detailed information about the seed treatments, methods of seed treatments, different equipment used in seed treatments, seed germination, component related to seed germination and establishment of crop in relation to soil moisture content.
To get the presentation contact me on alkesh.patel,2711@gmail.com
CROP MODELING IN VEGETABLES ( AABID AYOUB SKUAST-K).pptxAabidAyoub
crop modeling is future in agriculture to tackle changing environment conditions and increase food security in the world. These models incorporate various factors such as climate, soil characteristics, agronomic practices, and crop physiology to predict crop yields, water usage, nutrient uptake, and other important parameters. Crop modeling helps in understanding the complex interactions between different variables affecting crop growth and assists farmers, researchers, and policymakers in making informed decisions related to crop management, resource allocation, and risk assessment.
Role of AI in crop modeling: Artificial Intelligence (AI) plays a significant role in enhancing crop modeling by leveraging advanced computational techniques to improve model accuracy, efficiency, and scalability. One of the most important aspects of precision farming is sustainability. Using artificial neural networks (ANNs), a highly effective multilayer perceptron (MLP) model. The most common type in crop modeling is DSSAT , DSSAT (Decision Support System for Agro-technology Transfer).The Decision Support System for Agro-technology Transfer (DSSAT) is a software application program that comprises crop simulation models for over 42 crops (as of Version 4.8.2) as well as tools to facilitate effective use of the models. The tools include database management programs for soil, weather, crop management and experimental data, utilities, and application programs. The crop simulation models simulate growth, development and yield as a function of the soil-plant-atmosphere dynamics.DSSAT and its crop simulation models have been used for a wide range of applications at different spatial and temporal scales. This includes on-farm and precision management, regional assessments of the impact of climate variability and climate change, gene-based modeling and breeding selection, water use, greenhouse gas emissions, and long-term sustainability through the soil organic carbon and nitrogen balances.In conclusion, crop modeling stands as a crucial tool in modern agriculture, offering a systematic approach to understanding and predicting crop growth dynamics in diverse environmental conditions. By simulating the complex interactions between various factors influencing crop development, including climate, soil properties, agronomic practices, and genetic traits, crop models provide valuable insights for farmers, researchers, and policymakers.
CROP SIMULATION MODELS AND THEIR APPLICATIONS IN CROP PRODUCTION.pptxSarthakMoharana
CROP SIMULATION MODELS AND THEIR APPLICATIONS IN CROP PRODUCTION
Crop growth is a very complex phenomenon and a product of a series of complicated interactions of soil, plant and weather.
Crop growth simulation is a relatively recent technique that facilitates quantitative understanding of the effects of these factors and agronomic management factors on crop growth and productivity.
These models are quantitative description of the mechanisms and processes that result in growth of crop. The processes could be physiological, physical and chemical processes of crop.
MAJOR & POPULAR CROP SIMULATION MODELS:
DSSAT (Decision Support System for Agrotechnology Transfer)
Aqua Crop
Info Crop
APSIM (Agricultural Production System Simulator
These slides are about how crop and weather are interlinked an d how their association can be an impressive tools in the hands of the creative minds of the scientific world.
‘Crop Modeling for Stress Situation , Assessing Stress through Remote Sensing’AmanDohre
‘Crop Modeling for Stress Situation , Assessing Stress through Remote Sensing’
Crop modeling for stress situations involves utilizing mathematical models to simulate plant growth, development, and responses under various stress conditions. These models integrate data on environmental factors, soil properties, and crop physiology to predict crop performance and yield potential. By simulating stress scenarios such as drought, heat, or salinity, crop models help assess the impact of stress on crop growth and yield, enabling proactive management decisions and adaptation strategies.
Assessing stress through remote sensing involves using satellite or aerial imagery to monitor crop health, stress levels, and productivity. Remote sensing techniques, such as multispectral or thermal imaging, detect subtle changes in plant reflectance and temperature associated with stress-induced physiological responses. These data are processed using advanced algorithms to generate stress indices and maps, providing valuable insights into spatial and temporal patterns of stress distribution across agricultural landscapes. Integrating crop modeling with remote sensing enables more accurate and timely assessments of stress impacts, facilitating targeted interventions and resource allocation for stress mitigation and crop management.
IDM MODEL OF RED ROT OF SUGERCANE By Md. Kamaruzzaman ShakilMd. Kamaruzzaman
Red rot of sugarcane is one of the severe problem for fruitful profitable production of sugarcane. In this why IDM technology are very much helpful to control diseases, pest etc.
Crop modelling for stress situation (Sanjay Chetry).pptxsanjaychetry2
Stress in plants refers to external conditions that adversely affect growth, development or productivity of plants
Stresses trigger a wide range of plant responses like altered gene expression, cellular metabolism, changes in growth rates, crop yields, etc.
Two type of stress
Biotic Stress
Biotic stress in plants is caused by living organisms, specially viruses, bacteria, fungi, nematodes, insects, arachnids and weeds. The agents causing biotic stress directly deprive their host of its nutrients can lead to death of plants
Abiotic Stress
Abiotic stresses such as drought, excessive watering (water logging), extreme temperatures (cold, frost and heat), salinity and mineral toxicity negatively impact growth, development, yield and seed quality of crop and other plants
Crop Modelling
Crop models are a formal way to present quantitative knowledge about how a crop grows in interaction with its environment
Applications of Crop Models
Research on Interaction of Plant, Soil, Weather and Management Practices
Prediction of Crop Growth as well as Limiting factors
On farm decision making and agronomic management
Optimizing management using climatic predictions
Precision Farming and Site Specific Experimentation
Weather Based agro advisory services
Yield analysis and Forecasting
Introduction and Breeding of New Varieties
Policy Management
Mineral nutrients and nutrition
Micro nutrients
Macro nutrients
Primary nutrients
Secondary nutrients
Mobile nutrients
Immobile nutrients
Classification of essential nutrients
Classification based on amount required
Classification in the basis amount present in plant tissue
Classification based on biochemical and physiological functions
Classification based on nutrient mobility in the plants
Partially mobile nutrients
Nitrogen uptake
In a computer simulation of an epidemic, the computer is given data describing the various sub components of the epidemic and control practices at specific points in time (such as at weekly intervals).Computer simulation of epidemics is extremely useful as an educational exercise for students of plant pathology and also for farmers so that they can better understand and appreciate the effect of each epidemic sub component on the final size of their crop loss.Simulators serve as tools that can evaluate the importance of the size of each epidemic sub component at a particular point in time of the epidemic by projecting its effect on the final crop loss.Computer simulation are expert systems,that try to equal and suppress the logic and ability of an expert professional in solving problems.Systems are used in plant pathology frequently for diagnosis of plant diseases.Systems can advice growers in making decisions on disease management in respect of kind, amount and time of application of pesticides etc.Simulators can decompose disease progress so they are used now to develop forecaster.
Applications of Aqua crop Model for Improved Field Management Strategies and ...CrimsonpublishersMCDA
To quantify, integrate and assess the impacts from weather and climate change/variability on crop growth and productivity, crop models have been used for several years as decision support tools in the world. This paper is reviewed to assess applications of Aqua crop model as a decision support tool for simulating and validating crop management practices and climate change adaptation strategies. This model is devised by the FAO irrigation and drainage team. This model is very important especially, to guide as a decision support tool for dry land areas where soil moisture is very critical to affect crop productivity. It maintains the balance between simplicity, accuracy and robustness. The model has been calibrated and validated to simulate growth and productivity of crops, soil moisture balance, water use efficiency, evapo-transpiration and climate change impact assessment in different climate, management (water, fertilizer, sowing date, spacing etc.) practices around the world, especially in areas where soil moisture stress prevails. Maize, wheat, barley, tee, sorghum, pulse crops such as groundnut, soybean, vegetables (tomato, cabbage) have been tested using this model. The model comprehensively uses stress coefficients (water stress, fertilizer and temperature coefficients) to compute the effect of the factors on crop canopy, dry matter, stomatal closure, flowering, pollination and harvest index build up.
https://crimsonpublishers.com/mcda/fulltext/MCDA.000558.php
For more open access journals in Crimson Publishers please click on link: https://crimsonpublishers.com
For more articles on International Journal of Agronomy please click on below link: https://crimsonpublishers.com/mcda/
Simulation models of agricultural systems, when coupled with appropriate
data sources, have a great potential for bringing agricultural research and development into the age of information technology.
Examining the spatial distribution pattern and optimum sample size for monito...AI Publications
The white mango scale insect, Aulacaspis tubercularis (Newstead) (Hemiptera: Diaspididae) is one of the most destructive pests of mango trees in Egypt. The main objective of the present work is to estimate the spatial distribution pattern and minimum sample size for monitoring populations of A. tubercularis on six different cultivars of mango through the two successive years of 2017/2018 and 2018/2019 at Esna district, Luxor Governorate, Egypt. Data on the indices of distribution and Taylor’s and Iwao’s regression analyses indicate significant aggregation behaviour during each year in all the tested cultivars of mango trees, that may be caused by environmental heterogeneity. The regression models of Taylor’s power law (b) and Iwao’s patchiness (β) were both significantly >1, indicating that A. tubercularis had an aggregation distribution with a negative binomial distribution during each year in all the tested mango cultivars. The Iwao regression coefficients were used to determine the optimum sample size required to estimate populations at three fixed precision levels. The optimum size decreased with increased density in all levels of precision (5, 10 and 15%) in all tested mango cultivars. These can be deployed to develop a sampling plan to estimate the population density accurately. Results suggesting that the optimum sample size was flexible and the precision levels of 5 and 10% were suitable for ecological or insect behavioral studies of A. tubercularis where a higher level of precision is required, whereas, for pest management programs, a 15% level would be acceptable. Furthermore, the distribution, different mango cultivars, and sampling protocol presented here could be used as a tool for future research on pest management methods for this pest.
The resistance of parasites to existing drugs and the availability of better technology platforms has driven the discovery of new drugs. Microfluidic devices have been used to facilitate faster screening of compounds, controlled sampling/sorting of whole animals, and automated behavioral pattern recognition. In most cases, drug effects on small creatures (e.g., Caenorhabditis elegans) are measuredelegant by a single parameter such as worm velocity or stroke frequency. We present a multi-parameter extraction method to characterize modes of paralysis in C. elegans over a longer duration. This was done using a microfluidic device featuring real-time imaging, exposing worms to four anthelmintic drugs at EC75, where 75% of the worm population is affected. We monitored the worms' behavior with metrics such as curls per second, types of paralyzation, mode frequency, and number/duration of active/immobilization periods. Differences were observed in how the worms paralyzed in the various drug environments at equivalent concentrations. This study highlights the importance of assessing drug effects on small animals with multiple parameters, measured at regular intervals over a prolonged period, to accurately detect resistance and adaptability in chemical environments.
Roy Lycke, Archana Parashar, and Santosh Pandey, "Microfluidics-enabled method to identify modes of Caenorhabditis elegans paralysis in four anthelmintics", Biomicrofluidics 7, 064103 (2013).
https://doi.org/10.1063/1.4829777
https://aip.scitation.org/doi/10.1063/1.4829777
Agent Based Modeling on Dynamic Spreading Dengue Fever EpidemicTELKOMNIKA JOURNAL
Agent based model (ABM) is a computational model for simulation, behavioral representation and interaction of autonomous agents. The main problem definition related to how to make a dynamic model of dengue fever with consideration of their behavioral and interaction agent. This paper aims to develop interactive behavioral agents and related simulation models for such dynamic spreading dengue fever epidemic. This model construction consists of two agents, namely a human agent as a host and mosquito as a vector, where temperature and humidity are the environmental parameters. These environmental parameters deployed data and information from National Meteorology Climatology and Geophysics agency and supported by recent community health data of Bogor region. The verification stage evaluated model performance of two periods between January to June and between July to December 2015 showed the fitness of the model. During simulation stage where 100 humans agent and 10 mosquitoes agent were observed, indicating the decreasing of mosquito by 26.3% and the number of infected human decrease to 16% from the period of January until June to July until December 2015 respectively. These evaluation results showed that the agent based model results succeeded to follow a similar trend of decreasing pattern as actual data.
HAZARDOUS SUBSTANCE RULES, 2003 by Muhammad Qasim, Aroj Bashir University of ...Muhammad Qasim
In exercise of the power conferred by section 31 ( Power to Make Regulation) of Pakistan Environmental Protection Act ,1997 and this read with section 14 ( Handling of Hazardous Substances).
Sampling of Atmospheric Volatile Organic Compounds (VOCS) by Muhammad Qasim, ...Muhammad Qasim
Experimental evidence collected over the last three decades has shown clearly that the accumulation in air of volatile organic compounds might represent an important source of risk for human health.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
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.