This document discusses the use of computer applications for predicting and forecasting pest outbreaks. It describes how short-term and long-term pest forecasting can help farmers take timely action to control pests. Remote sensing, geographic information systems, databases, and decision support systems are computer tools that can monitor pest infestation levels, identify pest-damaged crops, store pest data, and provide recommendations to farmers. Expert systems have also been developed to help identify pests, estimate pest risk, and recommend control measures. Overall, computer applications are improving pest management by enabling early detection of pest issues and advising farmers on optimal control strategies.
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.
Successful case studies of national as well as international IPM programmessharanabasapppa
Discovery of synthetic pesticides in 1940, the whole scenario of pest management has changed.
From late 1940 to mid 1960 has been called “the dark ages” of pest control.
The insecticidal properties of DDT (dichloro diphenyl trichlorethane) discovered by Paul Muller in 1939 triggered this “dark age” of pest control.
Resistance of pests to pesticides was observed, the minor pests to major pests due to killing beneficial insects.
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.
Successful case studies of national as well as international IPM programmessharanabasapppa
Discovery of synthetic pesticides in 1940, the whole scenario of pest management has changed.
From late 1940 to mid 1960 has been called “the dark ages” of pest control.
The insecticidal properties of DDT (dichloro diphenyl trichlorethane) discovered by Paul Muller in 1939 triggered this “dark age” of pest control.
Resistance of pests to pesticides was observed, the minor pests to major pests due to killing beneficial insects.
Content:
Introduction
Importance of Host Plant Resistance
Historical perspectives
Advantages and Disadvantages of HPR
Mechanisms of Resistance
Adaptation of Resistance in Plant to Insect
Morphological
Anatomical
Biochemical
Assembly of plant species - Gene Pool
Behavior in Relation to Host Plant Factor
FUNGICIDES COMPATIABILITY WITH AGRO-CHEMICALSsubhashB10
In this presentation you will come to learn (or) you will learn about the different types of fungicides and its application towards plants in the Sevier infestation of the plant diseases in an particular crop. and also you will come to learn about the different AGRO-CHEMICALS used for eradication of the particular plant diseases. and also you will come to know about the different FUNGICIDES mixtures & AGRO-CHEMICAL mixtures used for curing an particular plant disease or an diseases as a whole.
Content:
Introduction
Importance of Host Plant Resistance
Historical perspectives
Advantages and Disadvantages of HPR
Mechanisms of Resistance
Adaptation of Resistance in Plant to Insect
Morphological
Anatomical
Biochemical
Assembly of plant species - Gene Pool
Behavior in Relation to Host Plant Factor
FUNGICIDES COMPATIABILITY WITH AGRO-CHEMICALSsubhashB10
In this presentation you will come to learn (or) you will learn about the different types of fungicides and its application towards plants in the Sevier infestation of the plant diseases in an particular crop. and also you will come to learn about the different AGRO-CHEMICALS used for eradication of the particular plant diseases. and also you will come to know about the different FUNGICIDES mixtures & AGRO-CHEMICAL mixtures used for curing an particular plant disease or an diseases as a whole.
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.
Enhancing the roles of ecosystem services in agriculture: agroecological prin...FAO
Presentation from Etienne Hainzelin from CIRAD, describing the principles of agroecological systems and the role of research within these. The presentation was prepared and delivered in occasion of the International Symposium on Agroecology for Food Security and Nutrition, held at FAO in Rome on 18-19 September 2014.
Birds and Bats: Pest Management Tips for the Educational Environment Facility Masters
Learn corrective actions, inspections and preventive measures to respond to and control bird and bat nuisance issues. Featuring Paul Duerre (Killeen ISD, TX) and Lynn Braband (NYS Community IPM Program at Cornell University).
The Green Revolution: Lessons for the FutureCIMMYT
Presentation delivered by Sir Gordon Conway (Imperial College London, UK) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
Conservation Farming Workshop and Field Demonstration Plot conducted by Allan Sorflaten, PAg and CESO volunteer in Bana, an area in Northwest Cameroon suffering from infertile soil and food insecurity. Under the leadership of Integrated Development Foundation, Bamenda, farming groups met to choose representatives to attend the workshops.
Agricultural environments are often simplified with less
habitat diversity than natural ecosystems. Furthermore, many
of the natural resistance traits that exist in wild plants may
have inadvertently been lost while selecting for crop yield and
quality in a pesticide-treated background. To reduce pesticide
dependency, agriculturalists are faced with the challenge of
bringing the resistance mechanisms found in wild plants back
into the elite crop cultivars (Bruce, 2012) and improving biocontrol
by natural enemies of pests. Reducing the losses to
global harvests caused by pests, which remain high even with
pesticide use, could provide a tangible way of producing more
‘crop per drop’ or unit area of land.
This presentation, discussing some concepts of ecological based pest management and vegetable entomology research findings, was given by Dr. Ayanava Majumdar at the Alabama Food and Farm Forum, 2010, in Selma, AL (USA). Please acknowledge the author and Alabama Cooperative Extension System when using the data for education and training. The research data is preliminary and should be interpreted with caution. For further information about this or other slideshows contact Dr. A at 251-331-8416.
A study on real time plant disease diagonsis systemIJARIIT
We aim to develop a real time application to the farmers for managing crop diseases. However, disease detection requires
continuous monitoring of experts which might be prohibitively expensive in large farms area. Automatic detection of plant diseases
is an essential research topic as it may prove benefits in monitoring large fields of crops and thus automatically detect the symptoms
of diseases as soon as they appear on plant leaves. Regarding plant disease diagnosis methodologies to detect diseases on crops,
image processing in disease diagnosis and eAGROBOT was studied. This paper is aiming to all are collectively used and formed
semi real time system for a disease diagnosis which uses image processing and data mining concepts to give pesticide
recommendation and pesticide cost estimation system. Thus the android application makes a good foundation for following effective
characteristic parameters for the disease diagnoses and setting up recommender system. The system is to be designed and developed
using Android studio as front-end software and SQLite as back-end software. The pictures and remedial measures of the diseases
were stored in the database and can be retrieved whenever necessary. The challenge is to make the farmers listen to the crop disease
diagnosis system and to get the advice related to the crop diseases. The constraint here is to develop the expert in local languages so
that farmers can operate the ES by themselves and get expert advice from the system.
Timely availability of expert support to the farmers for appropriate decision-making on ‘whether and what pest management option is required’ is imperative for effective Integrated Pest Management (IPM). For several decades Economic Threshold Level (ETL) has been the basis for decision-making but in modern IPM emphasis is given on agro-ecological situation wherein IPM decisions are based on large range of pest relevant information such as crop health, natural enemies, weather etc. beside pest incidence scientifically obtained through farmers’ field scouting. But large farming community in India can rather obtain the tentative information of this kind, consisting uncertainties. Bayesian Network (BN),anartificial intelligence approach could help in developing technique/model to deal with tentative pest relevant information which can be used in field scouting based IPM Decision Support Systems (DSSs) to automate the process of advising appropriate pest management option to the farmers on the basis of tentative agroecological situation of their fields.
Decision Making in Integrated Pest Management and Bayesian Networkdannyijwest
Timely availability of expert support to the farmers for appropriate decision-making on ‘whether and what
pest management option is required’ is imperative for effective Integrated Pest Management (IPM). For
several decades Economic Threshold Level (ETL) has been the basis for decision-making but in modern
IPM emphasis is given on agro-ecological situation wherein IPM decisions are based on large range of
pest relevant information such as crop health, natural enemies, weather etc. beside pest incidence
scientifically obtained through farmers’ field scouting. But large farming community in India can rather
obtain the tentative information of this kind, consisting uncertainties. Bayesian Network (BN),anartificial
intelligence approach could help in developing technique/model to deal with tentative pest relevant
information which can be used in field scouting based IPM Decision Support Systems (DSSs) to automate
the process of advising appropriate pest management option to the farmers on the basis of tentative agro-
ecological situation of their fields.
DECISION MAKING IN INTEGRATED PEST MANAGEMENT AND BAYESIAN NETWORKijcsit
Timely availability of expert support to the farmers for appropriate decision-making on ‘whether and what pest management option is required’ is imperative for effective Integrated Pest Management (IPM). For several decades Economic Threshold Level (ETL) has been the basis for decision-making but in modern IPM emphasis is given on agro-ecological situation wherein IPM decisions are based on large range of pest relevant information such as crop health, natural enemies, weather etc. beside pest incidence
scientifically obtained through farmers’ field scouting. But large farming community in India can rather obtain the tentative information of this kind, consisting uncertainties. Bayesian Network (BN),anartificial intelligence approach could help in developing technique/model to deal with tentative pest relevant
information which can be used in field scouting based IPM Decision Support Systems (DSSs) to automate the process of advising appropriate pest management option to the farmers on the basis of tentative agroecological situation of their fields.
Livestock are farm animals who are raised to generate profit. They are used for the commodities such as meat, eggs, milk, fur, leather and wool. Livestock animals usually distribute in remote areas, with relatively poor condition of disease diagnosis. Generally, it is difficult to carry out disease diagnosis rapidly and accurately.
Livestock diseases often pose a risk to public health and even affects the economy at large extent as we are quite dependent on the essential commodities we procure from the livestock. It is necessary to detect the disease outcome in the livestock to take the precautionary measures in order to avoid spread amongst them. So, there is a need for a system which can help in predicting the diseases among livestock on the basis of symptoms and suggest the precautionary measures to be taken with respect to the disease predicted. Our proposed system will predict the livestock (Cow, Sheep and Goat) disease using SVC (Support Vector Classifier) multi-class classification algorithm based on the symptoms and also provide the precautionary measures on the basis of disease predicted. There are some diseases which can prove to be fatal. So, our system will also alert the livestock owner if the predicted disease may cause a sudden death.
Crop Leaf Disease Diagnosis using Convolutional Neural Networkijtsrd
The major problem that the farmers around the world face is losses, because of pests, disease or a nutrient deficiency. They depend upon the information that they get from the agricultural departments for the diagnosis of plant leaf disease. This process is lengthy and complicated. Here comes a system to help farmers everywhere in the world by automatically detecting plant leaf diseases accurately and within no time. The proposed system is capable of identifying the disease of majorly 5 crops which are corn, sugarcane, wheat, and grape. In this paper, the proposed system uses the Mobile Net model, a type of CNN for classification of leaf disease. Several experiments are performed on the dataset to get the accurate output. This system ensures to give more accurate results than the previous systems. Shivani Machha | Nikita Jadhav | Himali Kasar | Prof. Sumita Chandak ""Crop Leaf Disease Diagnosis using Convolutional Neural Network"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd29952.pdf
Paper Url : https://www.ijtsrd.com/engineering/information-technology/29952/crop-leaf-disease-diagnosis-using-convolutional-neural-network/shivani-machha
Applications of information technology in agriculture ws ns for environmental...Aboul Ella Hassanien
This presentation due the workshop at faculty of agriculture - Suss Canal University organized by scientific research group in Egypt (SRGE) on Tuesday 8 April 214
The UN-backed regional fund seeks to raise $20m in fight against the red palm weevil as UAE food security minister calls on nations to come together to protect vital date palms. “It is a huge threat,” Mariam Al Mehairi, UAE Minister of State for Food Security, told The National on March 9th 2019.
Survey of Diesease Prediction on Plants with the Helps of IOTrahulmonikasharma
overall climate change is a diversity in the long-term weather patterns that indicates the regions of the world. The term "weather" refers to the short-term (daily) changes in temperature, wind, and precipitation of a region.With the up-gradation in data mining and its applications, data mining is extensively used to make smarter decisions in farming.Agricultural forecasting is the science that employ knowledge in weather data relating to atmospheric environment observed by instruments on the ground and by remote sensing. Most of the data need to be processed for generating various decisions such as cropping and scheduling of irrigation.Various meteorological data like- temperature, humidity, leaf wetness duration (LWD) plays the vital roles in the growth of microorganism responsible for disease.Effective forecasting of such diseases on the basis of climate data can help the farmers to take timely actions to restrain the diseases. This can also justify the use of pesticides, which are one of the source behind land pollution. This paper illustrate the study which is useful for farmers in order to make decision if there is change occur in environment. In this study we are going to implement application which give the notification to farmers, if there is change in environment so based on that changes which disease should be affected to plant such type of notification will be generated on farmers mobile.Weather based forecasting system can be treated as a part of the Agricultural Decision Support System (ADSS) which is Knowledge Based System (KBS). IoT device that collects data regarding physical parameters, using a sophisticated microcontroller platform, from various types of sensors, through different modes of communication and then uploads the data to the Internet.
Role of expert systems in agriculture and its
applications in efficient crop production and
protection technologies has been reviewed and
discussed in this paper. Different domains of
agriculture are highlighted where expert systems can
play an important role for an expert in transferring
expert-driven knowledge instantly at the level of
farmer’s field. This paper explores structure of an
expert system, role of expert system in agriculture
along with details of expert system developed in the
different field of agriculture and also possibilities of
designing, developing and implementation of an
expert system for agriculture would motivate
scientists and extension workers to investigate
possible applications for the benefit of entire
agricultural community.
Cotton, known as “White Gold”, is the premier commercial crop in India. Among the different constraints that limit the yield of cotton in India, insect pests are considered to be the most serious. Among these insect pests nowadays, Whitefly, Bemisia tabaci (Gennadius) is most important. It is highly polyphagous pest and feeds on over 600 plant species including many agricultural crops (Oliveira et al., 2001). During last week of September, 1994 the whitefly assumed an epidemic form on cotton and brinjal crops at farmers fields throughout the Haryana state (Sharma and Batra, 1995). There are 24 different biotypes of whitefly. It transmits more than 111 species of plant pathogenic viruses (Jones, 2003). There are many approaches for controlling this pest viz., physical, cultural,biotechnological, biological, chemical, biopesticides and biorationals. Yellow sticky traps in various forms can catch large no. of whiteflies (Gerling and Horowitz, 1984). Use of light emitting diodes increase the attractiveness, specificity and adaptability of these visual traps (Stukenberg, 2014). There are cultural practices such as avoidance in time, avoidance in space and behavioural manipulations to manage whiteflies (Hilje et al., 2001). A reflective mulch (also called silver and metallic) treatment resulted in a lower incidence of adult whiteflies as compared with a standard black mulch treatment (Simmons et al., 2010). Biopesticides such as fungi and azadirachtin are also used to manage whitefly. In pot culture, 2% concentration of mineral oil + neem oil and mineral oil + Pongamia glabra seed oil were effective against Bemisia tabaci with a mean population reduction of 81.83% and 81.52% respectively (Chandra Shekhar et al., 2015). Five species of predators : Serangium parcesetosum, Brumoides suturalis, Cheilomenes sexmaculata, Coccinella septempunctata, Chrysoperla zastrowi and a parasitoid, Encarsia lutea were identified in Haryana (Kedar et al., 2014). Pyriproxyfen 10 EC @ 125gm a.i/ha was found most effective Insect Growth Regulator against whitefly (Kumar et al., 2014). Imidacloprid proved to be the most effective insecticide against whitefly upto seven days after application (Afzal et al., 2014). Spiromesifen 240 SC @ 0.4 ml/lt followed by buprofezin 10 EC @ 1.0 ml/lt were found as the most effective treatments with more than 75 per cent mean reduction in nymphal population of whiteflies (Maha Lakshmi et al., 2015). A chitin inhibitor gene Tma12 from a fern Tectaria spp. was identified for whitefly defence. RNA interference (RNAi)- mediated gene silencing was explored for the control of Bemisia tabaci (Upadhyay et al., 2011).
Status of Transgenics in Pest Management: Global and Indian ScenarioJayantyadav94
A transgenic crop plant contains a foreign gene or group of genes which have been artificially inserted instead of the plant acquiring them through pollination. Up to 17 million farmers in 24 countries planted 189.8 million hectares (469 million acres) in 2017, an increase of 3% or 4.7 million hectares (11.6 million acres) from 2016.
Defense Mechanism in Plants Against InsectsJayantyadav94
Plants and insects living together for more than 350 million years
Evolutionary between plants and insects resulted in the development of defence system in plants that has the ability to recognize signals from damaged cells
Activates the plant immune response against the insects
Plants have the ability to distinguish between herbivory and mechanical damage, such as hail and wind, as well as to recognize oviposition.
This feature is needed to avoid wasting expensive defence resources, since production and release of defence responses only benefits herbivore challenged plants.
According to the U.S. Center for Disease Control and Prevention (2008), Bioterrorism is the deliberate release of viruses, bacteria, toxins or other harmful agents to cause illness or death in people, animals, or plants.
Sound Strategies: the 65-million-year-old battle between Bats and InsectsJayantyadav94
An ancient battle rages high above our heads in the night sky as bats, the consummate nocturnal predators hunt their insect prey using ultrasonic sonar. One of the most important factors in the successful adaptive radiation of bats is their effective echolocation system. Echolocating bats emit ultrasonic pulses and listen for the presence, delay, and harmonic structure of the echoes reflected from the objects in the environment (Jones and Teeling, 2006). The frequency of the echolocation calls varies from 8 to 215 kHz depending on the bat species. The pulse repetition rate of the calls can vary from roughly 3 to approximately 200 pulses s−1 (Simmons et al., 1979). The echolocation sequence of hunting insectivorous bats involves three main phases: search, approach, and terminal (buzz) (Griffin et al., 1960). Many, if not most, cases of insect hearing probably originated as a means for detecting and avoiding predators such as sensitivity to ultrasound appears to have coevolved with echolocation signaling by insectivorous bats (Greenfield, 2016). In moths bat-detection was the principal purpose of hearing, as evidenced by comparable hearing physiology with best sensitivity in the bat echolocation range, 20–60 kHz, across moths in spite of diverse ear morphology (Nakano et al., 2015). Tympanic organs (ears) of moths are sufficiently sensitive to detect the echolocation cries of most bats before the bats can register their echo (Greenfield, 2014 and Goerlitz et al., 2010). In addition to hearing ultrasound, many moths belonging to sub-family Arctiinae are also capable of producing ultrasound in the form of short, repetitive clicks in response to tactile stimulation and the ultrasonic signals of echolocating bats when they detect the sonar signals of attacking bats (Corcoran et al., 2010). Anti-bat sounds function in acoustic aposematism, startle, Batesian mimicry, Mullerian mimicry and sonar jamming. Beetles, mantids, lacewings, crickets, mole crickets, katydids, and locusts can detect the sonar emissions of bats and exhibit various forms of anti-bat behavior. Researchers are beginning to use sophisticated high-speed infrared videography and high-frequency microphone arrays to study bat-insect interactions under natural conditions that will yield a multitude of exciting predator-prey interactions in the future.
Role of Synergists in Resistance ManagementJayantyadav94
Any chemical which in itself is not toxic to insects as dosages used, but when combined with an insecticide greatly enhances the toxicity of insecticide is known as synergist. Process of activation is synergism. Helps in penetration and stabilization of insecticides, and prevents the detoxification of insecticides
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Impact of Ethnobotany in traditional medicine,
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Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
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The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
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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!
Overview on Edible Vaccine: Pros & Cons with Mechanism
Computer application in pest forecasting
1. SCOPE AND PROSPECTS OF
COMPUTER APPLICATION IN
PREDICTION AND
FORECASTING OF PEST
OUTBREAK
BY : JAYANT YADAV, CCSHAU, HISAR, HARYANA
2. These predictions help in forewarning the
growers/farmers to take timely and judicious
intervention
2
Prediction
Pest
Outbreaks
Stages of
Pest
Pest
Population
3. Forecasting is the prediction of severity of pest population
which can cause economic damage to the crop.
Insect forecasting service may thus serve:
To predict the forth coming infestation level of the pest.
To find out the critical stage at which the application of
insecticides would afford maximum protection.
• The forecasting of pests guides the farmers about the
timing and biology of insect incidence, and to
eliminate blanket application, reduce pesticide
amounts and achieve quality results.
• The farmers can take to timely action of applying
various pest control measures to harvest maximum
returns.
4. Pest forecasting may be divided into two categories:-
1. Short-term forecasting : It covers a particular season or one
or two successive seasons only and is usually sampled from a
particular area within a crop using appropriate sampling
technique and the relationship is established between weather
data and progress in pest infestation.
e.g. Wheat grain aphid, Sitobion avenae (Fabricius) based on
multiple regressions
2. Long-term forecasting : These are based on possible effect of
weather on the pest population and cover a large area or by
extrapolating from the present population density into future.
e.g. Management strategies for Brown Planthopper, Nilaparvata
lugens (Stal) and White-backed Planthopper, Sogatella
furcifera (Horvath)
5. The application of the computer in agriculture
research originally exploited for the conversion of
statistical formula or complex model in digital form
for easy and accurate calculation which are found
relatively tedious in manual calculation.
Recently remote sensing and geographic information
system has place a major and crucial role in agriculture
research especially in the field of yield prediction,
suitability of soil for particular crop, and site specific
resource allocation of agriculture inputs, etc.
6. Remote sensing refers to the process of gathering
information about an object, at a distance, without
touching the object itself.
Certain phenomenon, which cannot be seen by human eye,
can be observed through remote sensing techniques i.e. the
trees, which are affected by disease, or insect-pests attack
can be detected by remote sensing techniques much before
human eyes see them.
Geographical Information System is a computer-based
information system that can acquire spatial data from a
variety of sources, change the data into useful formats,
store the data, and retrieve and manipulate the data for
analysis.
7. Remote sensing technology has long been used for
monitoring insect infestation in field crops.
It is based on the principle that the absorbance and
reflectance of plants in response to pest attack
changes and these changes are recorded by a device
from far away.
The early identification of damage due to two spotted
spider mite, Tetranychus urticae, on greenhouse
pepper can be obtained by multispectral means. As it
can be spectrally detected in the reflectance of the
visible and near – infrared regions.
8.
9. Database management has been widely used in pest
identification, managing pest monitoring data, population
modelling, exploring control strategies, biology of pests and
decision support system to take decision for adopting
intervention for pest management in field which are important
in IPM.
The database has been developed in the form of CD-ROM,
internet based decision support systems, expert systems etc.
The National Centre for Integrated Pest Management (NCIPM),
New Delhi has developed database management system
(www.ncipm.org.in/agroweb), where the information is available
on pest, disease management, nutritional deficiency and
physiological disorder in different crops grown in India.
10. Decision support system are computer based information
system designed in such a way that they help farmers to
select one of the many alternative solutions to a pest
problem.
In IPM, DSSs are widely used for identification,
recommendation of insecticides, emergence of insect pests
outbreaks.
The DSS supports adoption of IPM technologies to reduce
the cost of production and minimizing environmental and
public hazard.
• DSS has also developed at NCIPM, which provides
information on pest management systems, forecasting of
pests, and distribution maps.
11. A number of decision support system have been developed
in different countries on different crops.
Codling Moth Information Support System (CMISS)
http://ipmnet.org/codlingmoth/ site contains various
knowledge bases, databases, phenology models, and links
to worldwide resources on codling moth.
A spatial DSS MedCila was developed in Israel for
controlling Mediterranean fruit fly, Ceratitis capitata, in
citrus in 2004. The recommendations of MedCila are
generally accepted and reduce the unnecessary sprays.
12. Decision
support
system
Crop Target Pest Country Function
EntomoLOGI
C
Cotton Helicoverpa
spp., two
spotted spider
mite
Australia Predicting
future pest
numbers
proPlant Oilseed rape Cabbage stem
flea beetle,
Psylliodes
chrysocephala
,
Rape stem
weevil,
Dasineura
brassicae
Europe Predicts the
start of pest
infestation
and provides
selection, date
and rate of
chemical
application
SIMLEP Slash and Pine
seed orchards
Colorado
potato beetle,
Leptinotarsa
decimlineata
Slovenia Forecasted the
first
occurrence of
young and old
larvae
(www.dssresources.com)12
13. Another computer programme based on database
management is Expert Systems (ES)
Though both DSS and ES seek to improve the quality
of the decision, these are distinguished based on
objectives , operational differences, users and
development methodology.
The different Expert Systems (ES) have been designed
which help in identification of insect-pests, estimating
risk from pests, control measure recommendations
etc.
14. Computer based Expert Systems (EXS)
Rice BPH Expert System
Constructed to diagnose and
pesticide recommendations for brown
plant hopper in Zhejiang Province,
China
Help in the identification of research,
surveillance and monitoring needs
(Holt et al 1990)
SGA Pro
Stored Grain Advisory Pro was developed to provide insect pest
management information for wheat stored at commercial elevators
The program uses a model to predict future risks based on current
insect density, grain temperature and moisture
(Flinn et al 2007)
14
15. Expert
systems
Crop Target pest Country Function
TEAPEST Tea Pests of tea India Identify and
suggest
appropriate
control
measures
SOYPEST(Soybe
an Pest Expert
System)
Soybean 120 pests India Idetification and
decision in IPM
GyMEs(Gypsy
Moth Expert
System)
Different plant
species in
forests
Gypsy Moth North America Estimate risk to
forest from
pests.
16.
17.
18.
19.
20. Injudicious and untimely application of pest control
measures has led to situation of repeated pest outbreaks,
pesticide resistance, pest resurgence and secondary
pest outbreak.
The various decision support systems and expert systems
are providing quite useful information for enhancing
awareness among farmers about insect pests of crops,
requirement of crops, taking decisions to initiate control
measures etc.
A close collaboration between computer programmers and
plant protection scientists is essential to develop farmer
friendly systems.
21. Computer based information systems have changed
the way we do research.
They have enhanced our ability to identify and solve
problems and to perform tasks that are beyond our
physical ability.
Information system technology, bioinformatics, and
nanotechnology no doubt will continue to provide new
horizon to us in the years to come.