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.
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.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
A pest can be defined as a plant, animal, insect, or pathogen, acting singly or in combination, often aggravated by environmental stresses, which by its presence, abundance, or activity interferes with accomplishment of resource management goals and objectives.
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.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
A pest can be defined as a plant, animal, insect, or pathogen, acting singly or in combination, often aggravated by environmental stresses, which by its presence, abundance, or activity interferes with accomplishment of resource management goals and objectives.
Integrated Pest Management (IPM) by TS- Shiven R. TrambadiaSHIVENPATEL10
PLEASE LIKE | SHARE | FOLLOW me to get more science related presentations.
This presentation is on "Integrated Pest Management", in which I've included 1) What is IPM?, 2)History, 3)Principles and 4)Applications of IPM.
Note:- Any part (text, photo, picture, clip-art, video, images etc.) included in this presentation are mostly correct according to the author of this presentation. Moreover any part (text, photo, picture, clip-art, video, images etc.) of this presentation, if includes your / from your related resource, is just a matter of coincidence.
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.
Environmental problems and human health, risk assessment and risk managementMd Fahimuzzaman
Environmental problems and human health, risk assessment and risk management
The process of estimating the potential impact of a chemical, physical, microbiological or psychosocial hazard on a specified human population or ecological system under a specific set of conditions and for a certain time frame.
The five stages of environmental health risk assessment:
1. Issue identification
2. Hazard assessment
3. Dose-response
4. Exposure
5. Risk characterisation
Assessment of Pest Severity and Biological Parameters of Bactrocera minax in ...AI Publications
Chinese Citrus fly, Bactrocera(Tetradacus) minax(Enderlein), univoltine fruit fly species, is a serious insect pest in Nepal, Bhutan, China, India causing 100% fruit drop in sweet orange (Citrus sinensis L.) orchards in severe case. Four elevation ranges: 1400-1474masl, 1475-1549masl, 1550-1624masl and >1624masl of Ramechhap district were taken for the study of severity of infestation by this fly species in November 2018. A subsequent rearing was conducted at Agriculture and Forestry University, Chitwan, Nepal upto April 2019 to assess various developmental parameters of Bactrocera minax starting from larval stage in infested sweet oranges to the adult flies. Elevation range had the most significant effect (P<0.05) on pest severity (2017/18). Pest severity had strong relationship on elevation of orchards (R2=0.6638). Maximum pest severity (37.12%) was found in 1550-1624masl and minimum (2.90%) in 1400-1474masl. Maximum mean maggots/fruit (6.40±1.25) at 1550-1624masl and minimum (3.95±0.92) at 1475-1549masl were recorded. Post-pupal mortality was higher than pre-pupal mortality. Maximum pre-pupal mortality (11.13±5.24%) at >1624masl and the minimum (2.08±1.46%) at 1550-1624masl were recorded while 1475-1549masl and 1400-1474masl had the respective minimum (25.81±7.59%) and maximum (36.08±9.17%) post-pupal mortality. Most adult flies emerged by 2nd week of March lasting 115 days for adult eclosion. Sex ratio (male: female) was maximum (2.5) at 1400-1474masl and minimum (1.2) at >1624masl. Without feeding an adult fly survived upto 3 days. It can be speculated that besides other meteorological factors, elevation affects geographical distribution of fly and its subsequent biological parameters.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability
[1] ijrei vol 1, issue-2Community analysis of key pests associated with menth...editorijrei
An extensive survey was carried out during 2013 for the real situation in the crop to study the plant pathogenic fungus, bacteria and nematodes associated with Japanese Mint Mentha arvensis var piperascense growing fields. Soil and root samples were collected from 24 Mentha fields represents 15 different locations (villages) Akhtarpur, Tiwaripur, Shuklapur, Katia, Oripur, Ghuripur, Padariya and Dafara. Out of 120 soil samples, 16 soil samples were found infected with Fusarium oxysporum and 27 soil samples with Alternaria spp. 36 samples have the plant parasitic nematodes population. Results revealed that the maximum disease prevalence (DP) of Fusarium oxysporum was recorded at Shuklapur (27%), while the minimum disease prevalence was recorded at Ghuripur (3.4%). Alternaria spp. was more prevalent at Tiwaripur (42%) while root-knot nematode (Meloidogyne incognita) incidence was maximum at Katia (43%). The plant extracts were not so promising for inhibition of pathogenic fungi of Mentha crop.
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.
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.
Pesticide recommendation system for cotton crop diseases due to the climatic ...IJMREMJournal
Data mining is a process of extracting knowledge from a vast database using tools and techniques. Data
mining plays an important role in decision making on issues related to many real-time problems such as
business, education, agriculture etc. Data mining in agriculture helps the farmers to decide on crop yield ratio,
water resource management, pesticides management and fertilizer management. Nowadays, climatic change is
one of the challenging problems in agriculture which has a greater impact on productivity. Many
researchers have contributed in the field of agriculture data mining i) To predict crop productivity, ii) water
management, iii) air pollution using the naïve bias and decision tree algorithms. The Proposed work is to
predict the diseases due to Climatic changes and recommended pesticide for the disease. Decision tree
algorithm is used to develop a recommendation system which helps to the farmer in the usage of pesticide for
the incidence of crop diseases.
Abstract
Cotton is the important cash crop of Pakistan and a major source of foreign earnings. However cotton crop is
facing many problems, such as disease and pest attacks. One way to reduce losses caused by disease and pest
attack is the use integrated pest management (IPM) practices. Keeping in view the importance of this technique,
the present study analyzed the adoption of IPM along with estimation of risk involved in the adoption process.
To estimate the cotton yield, two types of production functions (one for adopter and other for non-adopters) were
estimated using the regression analysis. Then estimate of regression models was used further in risk analysis.
The results of non-adopters of IPM showed that cost of urea bags, cost of nitro-phosphate bags, cost of herbicide
and rainfall were -0.038, 0.00475, 0.301 and 0.164 respectively and all of these significant at 10 percent level.
For non-adopters of IPM the coefficient values of seed expenditure, temperature, humidity and spray cost were
0.0035, 0.026,-.0.00093 and 0.00027 respectively. The results of IPM adopters showed that coefficient of
temperature, seed expenditure, spray cost, urea cost and rainfall equal to 0.0305,0.100,0.0029,-.000213 and
0.894 respectively and significant at ten percent level. Coefficient values of cost of nitro-phosphate bags,
herbicide cost, humidity were 0.00035, 0.100.-0.000671 and -0.000445 respectively.
Keywords: Cotton, IPM, herbicide, evaluation, risk, Coefficient, Hyderabad.
Integrated Pest Management (IPM) by TS- Shiven R. TrambadiaSHIVENPATEL10
PLEASE LIKE | SHARE | FOLLOW me to get more science related presentations.
This presentation is on "Integrated Pest Management", in which I've included 1) What is IPM?, 2)History, 3)Principles and 4)Applications of IPM.
Note:- Any part (text, photo, picture, clip-art, video, images etc.) included in this presentation are mostly correct according to the author of this presentation. Moreover any part (text, photo, picture, clip-art, video, images etc.) of this presentation, if includes your / from your related resource, is just a matter of coincidence.
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.
Environmental problems and human health, risk assessment and risk managementMd Fahimuzzaman
Environmental problems and human health, risk assessment and risk management
The process of estimating the potential impact of a chemical, physical, microbiological or psychosocial hazard on a specified human population or ecological system under a specific set of conditions and for a certain time frame.
The five stages of environmental health risk assessment:
1. Issue identification
2. Hazard assessment
3. Dose-response
4. Exposure
5. Risk characterisation
Assessment of Pest Severity and Biological Parameters of Bactrocera minax in ...AI Publications
Chinese Citrus fly, Bactrocera(Tetradacus) minax(Enderlein), univoltine fruit fly species, is a serious insect pest in Nepal, Bhutan, China, India causing 100% fruit drop in sweet orange (Citrus sinensis L.) orchards in severe case. Four elevation ranges: 1400-1474masl, 1475-1549masl, 1550-1624masl and >1624masl of Ramechhap district were taken for the study of severity of infestation by this fly species in November 2018. A subsequent rearing was conducted at Agriculture and Forestry University, Chitwan, Nepal upto April 2019 to assess various developmental parameters of Bactrocera minax starting from larval stage in infested sweet oranges to the adult flies. Elevation range had the most significant effect (P<0.05) on pest severity (2017/18). Pest severity had strong relationship on elevation of orchards (R2=0.6638). Maximum pest severity (37.12%) was found in 1550-1624masl and minimum (2.90%) in 1400-1474masl. Maximum mean maggots/fruit (6.40±1.25) at 1550-1624masl and minimum (3.95±0.92) at 1475-1549masl were recorded. Post-pupal mortality was higher than pre-pupal mortality. Maximum pre-pupal mortality (11.13±5.24%) at >1624masl and the minimum (2.08±1.46%) at 1550-1624masl were recorded while 1475-1549masl and 1400-1474masl had the respective minimum (25.81±7.59%) and maximum (36.08±9.17%) post-pupal mortality. Most adult flies emerged by 2nd week of March lasting 115 days for adult eclosion. Sex ratio (male: female) was maximum (2.5) at 1400-1474masl and minimum (1.2) at >1624masl. Without feeding an adult fly survived upto 3 days. It can be speculated that besides other meteorological factors, elevation affects geographical distribution of fly and its subsequent biological parameters.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability
[1] ijrei vol 1, issue-2Community analysis of key pests associated with menth...editorijrei
An extensive survey was carried out during 2013 for the real situation in the crop to study the plant pathogenic fungus, bacteria and nematodes associated with Japanese Mint Mentha arvensis var piperascense growing fields. Soil and root samples were collected from 24 Mentha fields represents 15 different locations (villages) Akhtarpur, Tiwaripur, Shuklapur, Katia, Oripur, Ghuripur, Padariya and Dafara. Out of 120 soil samples, 16 soil samples were found infected with Fusarium oxysporum and 27 soil samples with Alternaria spp. 36 samples have the plant parasitic nematodes population. Results revealed that the maximum disease prevalence (DP) of Fusarium oxysporum was recorded at Shuklapur (27%), while the minimum disease prevalence was recorded at Ghuripur (3.4%). Alternaria spp. was more prevalent at Tiwaripur (42%) while root-knot nematode (Meloidogyne incognita) incidence was maximum at Katia (43%). The plant extracts were not so promising for inhibition of pathogenic fungi of Mentha crop.
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.
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.
Pesticide recommendation system for cotton crop diseases due to the climatic ...IJMREMJournal
Data mining is a process of extracting knowledge from a vast database using tools and techniques. Data
mining plays an important role in decision making on issues related to many real-time problems such as
business, education, agriculture etc. Data mining in agriculture helps the farmers to decide on crop yield ratio,
water resource management, pesticides management and fertilizer management. Nowadays, climatic change is
one of the challenging problems in agriculture which has a greater impact on productivity. Many
researchers have contributed in the field of agriculture data mining i) To predict crop productivity, ii) water
management, iii) air pollution using the naïve bias and decision tree algorithms. The Proposed work is to
predict the diseases due to Climatic changes and recommended pesticide for the disease. Decision tree
algorithm is used to develop a recommendation system which helps to the farmer in the usage of pesticide for
the incidence of crop diseases.
Abstract
Cotton is the important cash crop of Pakistan and a major source of foreign earnings. However cotton crop is
facing many problems, such as disease and pest attacks. One way to reduce losses caused by disease and pest
attack is the use integrated pest management (IPM) practices. Keeping in view the importance of this technique,
the present study analyzed the adoption of IPM along with estimation of risk involved in the adoption process.
To estimate the cotton yield, two types of production functions (one for adopter and other for non-adopters) were
estimated using the regression analysis. Then estimate of regression models was used further in risk analysis.
The results of non-adopters of IPM showed that cost of urea bags, cost of nitro-phosphate bags, cost of herbicide
and rainfall were -0.038, 0.00475, 0.301 and 0.164 respectively and all of these significant at 10 percent level.
For non-adopters of IPM the coefficient values of seed expenditure, temperature, humidity and spray cost were
0.0035, 0.026,-.0.00093 and 0.00027 respectively. The results of IPM adopters showed that coefficient of
temperature, seed expenditure, spray cost, urea cost and rainfall equal to 0.0305,0.100,0.0029,-.000213 and
0.894 respectively and significant at ten percent level. Coefficient values of cost of nitro-phosphate bags,
herbicide cost, humidity were 0.00035, 0.100.-0.000671 and -0.000445 respectively.
Keywords: Cotton, IPM, herbicide, evaluation, risk, Coefficient, Hyderabad.
Adoption of crop scheduling techniques in India for sugarcane and pomegranate
production has been disappointing. The challenge is to use state of the art technology to provide
practical and useful advice to farmers and further to convince farmers of the benefits of crop
scheduling by on-farm demonstration. The purpose of this project is to describe: 1. To expose the
system to the practical aspects of farming in order to refine it if necessary. 2. To evaluate the
accuracy of the system to predict crop growth and health. 3. A high technology system to provide
practical, real time cropping advice on climate situations. The system consists of a web-based
simulation model that estimates the recent, current and future crop status and yield from field
information and real time weather data. The system automatically generates and distributes simple
advice by SMS to farmers’ cellular phones. The system is evaluated on a small-scale sugarcane and
pomegranate scheme at Pandharpur, Maharashtra. Yields are not affected significantly and
profitability is enhanced considerably.
Crops diseases detection and solution systemIJECEIAES
The technology based modern agriculture industries are today’s requirement in every part of agriculture in Bangladesh. In this technology, the disease of plants is precisely controlled. Due to the variable atmospheric circumstances these conditions sometimes the farmer doesn’t know what type of disease on the plant and which type of medicine provide them to avoid diseases. This research developed for crops diseases detection and to provide solutions by using image processing techniques. We have used Android Studio to develop the system. The crops diseases detection and solution system is compared the image of affected crops with database of CDDASS (Crops Diseases Detection and Solution system). If CDDASS detect any disease symptom, then provide suggestion so that farmers can take proper decision to provide medicine to the affected crops. The application has developed with user friendly features so that farmers can use it easily.
The technology based modern agriculture industries are today‟s requirement in every part of agriculture in Bangladesh. In this technology, the disease of plants is precisely controlled. Due to the variable atmospheric circumstances these conditions sometimes the farmer doesn‟t know what type of disease on the plant and which type of medicine provide them to avoid diseases. This research developed for crops diseases detection and to provides solution by using image processing techniques. We have used Android Studio to develop the system. The crops diseases detection and solution system is compared the image of affected crops with database of CDDASS (Crops Diseases Detection and Solution system). If CDDASS detect any disease symptom, then provide suggestion so that farmers can take proper decision to provide medicine to the affected crops. The application has developed with user friendly features so that farmers can use it easily.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
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.
DECISION MAKING IN INTEGRATED PEST MANAGEMENT AND BAYESIAN NETWORK
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
DOI:10.5121/ijcsit.2017.9203 31
DECISION MAKING IN INTEGRATED PEST
MANAGEMENT AND BAYESIAN NETWORK
Niranjan Singh and Neha Gupta
Faculty of Computer Application,ManavRachna International University,
Faridabad-121004, India
ABSTRACT
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.
KEYWORDS
IPM, field scouting, decision-making, ETL, agro-ecological situation
1. INTRODUCTION
Excessive, injudicious and irrational use of chemical pesticide by the farmers for pest control
causes significant damage to the environment, human health and also negatively impacts the crop
production. There is a growing awareness world over on the need for promoting environmentally
sustainable agriculture practices. Integrated Pest Management is a globally accepted strategy for
promoting sustainable agriculture [10]. The IPM has been evolving over the decades to address
the negative impact of chemical pesticides on environment ultimately affecting the interests of the
farmers. The major goal of IPM is not to eradicate all pest populations but rather to accept a
tolerable pest density above the Economic Threshold Level[6]. For several decades ETL has been
the basis for IPM decision-making but in modern IPM emphasis is being given on field agro-
ecological situation where pest management decisions are based on larger range of field
observations such as crop health, natural enemies’ population, and weather etc. beside pest
information. Easy and timely availability of expert support on IPM decision-making is the biggest
problem faced by the farmers in India. ‘Whether and what pest management option is required’ is
the most important decision concern of the farmers. Many ICT based DSSs as web-based
applications are available in the country but most of them provide information about for pest
identification and management. Some initiatives have also been taken to provide ETL based
decision support to the farmers on ‘weather and what pest management option is required’ which
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
32
capture quantitative pest information scientifically obtained by trained pest scouts through regular
field scouting. But there are no DSSs to provide decision support to the farmers on ‘weather and
what pest management option is required’ on the basis of farmer’s field agro-ecological situation
neither there are techniques which can be used in these DSSs for selecting appropriate pest
management option on the basis of tentative agro-ecological information obtained by the farmers.
Large Indian farming community cannot scientifically observe such certain information rather
they may obtain tentative information. Hence, Bayesian Network is widely used in ecological
decision-making could be the suitable approach to develop expert technique/model for selecting
appropriate pest management option on the basis of tentative agro-ecological information
obtained from farmer fields. The technique thus developed can be used in field scouting based
DSSs to automate the process of providing field agro-ecological situation based pest management
advisories to the farmers.
2. DECISION-MAKING IN IPM
Decision-making is a mental process resulting in the selection of an action among several
alternative solutions. Every decision-making process produces a final choice [4].Decision-making
starts with the identification of a problem, which requires the collection of all relevant
information for critical analysis of the problem. This analysis leads to development of a set of
available alternative courses of actions to solve the problem; only realistic solutions should be
selected considering multiple criteria e.g. effectiveness, benefits, costs and the constraints e.g.
ease of implementation and technical or legislative constraints. Based on this analysis, the best
solution is selected, and the decision is converted into an action [9].
Decision-making in IPM is a dynamic and complex process (Fig. 1) which requires much more
knowledge and support than the conventional agriculture. The core of IPM framework is the
decision-making process. The first decision concerns pest identification and second decision
concerns ‘whether and what pest management option is required’. Regular field scouting is the
corner stone of the IPM. Whenever the decision maker notices any pest activity while scouting
the field, he needs to identify the pest and scientifically observe the exact pest and other relevant
information necessary for IPM decision-making. After the analyzing the information observed,
first decision to be made is whether pest management action is required and if so, what is the
most appropriate option; physical, biological or chemical, their doses, application methods,
Fig: 1 IPM Decision making
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
33
frequency etc. In IPM, sustainable biological, physical, and other non-chemical methods which
are safer to environment and human health are preferred to chemical methods [9].
ETL VS. AGRO-ECOLOGICAL SITUATION, BASIS FOR IPM DECISION-MAKING
ETL is an important concept for IPM which integrates biology and economics and uses
pesticides, or other management actions, only when economic loss in anticipated [6]. ETL is the
best known and widely used concept in making IPM decisions but here are many reasons for not
to use this method. One of the problems of the ETL is that it is based on parameters that are
changing all the time, and that are often not known. ETL is defined as the population density at
which control measures should be initiated against an increasing pest population to prevent
economic damage. It is expressed as insect numbers. It is calculated on the basis of management
cost per hectare, price of the farm produce/ kilogram and expected damage (kilogram/pest). So, it
is possible to estimate the pest management cost but is very difficult to know the farm produce
while crop is still growing. Similarly, pest damage too cannot be predicted as it depends upon
many factors: crop health, weather, presence of pest natural enemies etc.
Analysis of field agro-ecological situation considers large rage of pest relevant information such
as crop health, weather conditions and natural enemies’ population beside pest incidence thus is
more holistic approach than ETL. In agro-ecological situation based IPM, understanding the
intricate interactions in an ecosystem can play a critical role in pest management. Agro-ecological
situation based IPM results in more reduction of chemical pesticide usage and conserves the agro-
ecosystems in comparison to ETL based IPM. Farmers cannot base decisions on only a simple
pest count but have to consider many other aspects such as crop health, natural enemies and
weather condition etc. Hence, IPM specialists have realized the limitations of the ETL and
gradually shifted towards agro-ecological situation based IPM decision-making.
3. LIMITATIONS OF EXISTING FIELD SCOUTING BASED IPM DECISION
SUPPORT SYSTEMS
In spite of development and wide spread of ICT, still there are limitations to the use of DSSs in
IPM. One of the major limitation is that pest management DSSs do not adequately consider all
aspects of IPM. Most of the available DSSs address only specific aspect of IPM. Several DSSs
require too much time to use because of delays in data processing or tedious and input
requirements whereas pest is very dynamic specie and can cause significant crop losses if not
managed timely. For effective and successful IPM, farmer need easy and timely access to the
knowledge or expertise so as to make appropriate decision as per his field situation.
Most of the IPM DSSs have been built to provide support on pest identification and their
management. Only few DSSs are available andthese too provide real-time decision support to the
farmers on the basis of pest situation in their fields ‘whether pest incidence level has reached near
ETL or crossed ETL’. These DSS scapture the quantitative pest incidence information
scientifically obtained by trained pest scouts through regular scouting of farmer fields and
produce ETL based pest reports to the experts so as to select appropriate pest management option
to be advised to the farmers. Whereas in modern IPM the basis of IPM decision making has
changed to field agro-ecological situation instead of pest ETL which requires large range of
certain pest relevant information scientifically obtained from farmer fields through regular field
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
34
scouting. But regular scientific observation of such information form farmer fields require large
number of trained manpower which is a difficult and costly proposition for state plant protection
agencies. So, can the farmers themselves do the filed scouting? They can, but large farming
community is not able to scientifically observe such information rather they can obtain tentative
information which consists lot of uncertainty. But there are no techniques available which can be
used in field scouting based DSSs to select appropriate pest management option on the basis of
tentative pest relevant information to be advised to the farmers.
4. BAYESIAN NETWORK
Bayesian Network is a key computer technology for dealing with probabilities in Artificial
Intelligence. BN is one of the most effective theoretical models for uncertain knowledge
expression and reasoning [1]. Probabilistic reasoning approaches such as Bayesian network [7]
can be useful to develop technique for selecting appropriate pest management option on the basis
of uncertain or inexact pest and other relevant information obtained through scouting of farmer
fields. It was found through the literature review, that there have been very little efforts to use BN
for pest management decision-making specifically for “whether and what pest management
option is required’ on the basis of tentative agro ecological situation of farmer fields. BN can be
of great use in developing technique to better deal with this kind of tentative information obtained
by farmers from their fields for selecting appropriate pest management option.
BN graphical model that represents a set of random variables and their conditional dependencies
via anAcyclic Directed Graph (ADG). Because a Bayesian network is a complete model for the
variables and their relationships, it can be used to answer probabilistic queries about them.
Formally, a BN is a pair (G; P) where
G = (V; E) is a directed acyclic graph whose set of nodes V = {X1, X2, ………Xn} represents
the system variables and whose set of arcs E represents direct dependence relationships among
the variables, and
P is a set of conditional probability distributions containing a conditional probability distribution
P (Xi/pa (Xi)) for each variable X given the set of parents pa (Xi) in the graph.
The joint probability distribution over V can be recovered from this set P of conditional
probability distributions applying the chain rule as:
n
P(X1, ……,Xn)=∏P (Xi/pa (Xi))
i
The process of obtaining the graph and the probabilities of a BN can be done either manually,
from experts’ knowledge on the domain, or automatically, from databases [3].
BN that can represent and solve decision problems under uncertainty are called BDN. It is a
generalization of a Bayesian network, in which not only probabilistic inference problems but
also decision making problems can be modeled and solved. BN only contain chance nodes, each
representing a random variable, while BDN also contain decision nodes representing the options
available to decision makers and utility nodes representing the decision makers’ preferences. Arcs
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
coming into decision nodes represent the information that will be available when the decision is
made. Arcs coming into chance nodes represents probabilistic dependence.
BN has been effectively used in ecological decision making
and techniques keep increasing BN’S abilities and range of practical applications
Nevertheless, there are very few experiences of its usage in pest management
5. CONCEPTUAL BAYESIAN
5.1 Problem Description
So the major decision concern of the farmers related to IPM is
management option to apply on the basis of
Whenever he notices any pest activity,
information about crop condition, level of pest incidence, natural enemies and weather
from his field.
Crop condition is measured in terms of its phenology. The level of pest incidence, presence of
natural enemies and weather condition are important to estimate the intensity of the attack
crop condition, along with the intensi
plant health treatment or not and if yes then what is the correct IPM option.
conditional relationship among these agro ecological factors, a
built for selection of appropriate pest management option.
5.2 Model Structure& Parameterization
The construction of BN model structure included: identifying the important variables and
establishing the links between variables.
experts, BN model for agro ecological situation based IPM decision making was constructed.
prominent variables (nodes) of interest
presence of natural enemies, weather conditions,
Level of pest incidence, natural enemies and weather are the parent nodes of pest intensity and
pest intensity and crop health are the parent nodes for IPM option.
model for field agro ecological situation based
model represent the variables, with their causal relations depicted by black arrows.
.
International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
coming into decision nodes represent the information that will be available when the decision is
nodes represents probabilistic dependence.
BN has been effectively used in ecological decision making [8]. New computational methods
and techniques keep increasing BN’S abilities and range of practical applications
are very few experiences of its usage in pest management [2].
AYESIAN NETWORK MODEL FOR IPM DECISION
major decision concern of the farmers related to IPM is to decide whether and what pest
on the basis of tentative agro ecological situation of his field
ever he notices any pest activity, he needs to notes down the date of obser
crop condition, level of pest incidence, natural enemies and weather
Crop condition is measured in terms of its phenology. The level of pest incidence, presence of
natural enemies and weather condition are important to estimate the intensity of the attack
crop condition, along with the intensity of pest attack, determines whether there is need to apply
plant health treatment or not and if yes then what is the correct IPM option. So
conditional relationship among these agro ecological factors, a conceptual BN model
appropriate pest management option.
Model Structure& Parameterization
The construction of BN model structure included: identifying the important variables and
establishing the links between variables. Based on knowledge elicited from literature and domain
BN model for agro ecological situation based IPM decision making was constructed.
prominent variables (nodes) of interest were identified in this case; level of pest incidence,
presence of natural enemies, weather conditions, crop health, pest intensity and IPM options.
Level of pest incidence, natural enemies and weather are the parent nodes of pest intensity and
pest intensity and crop health are the parent nodes for IPM option. Figure 2 shows the Bayesian
for field agro ecological situation based IPM decision making. The nodes in the BN
model represent the variables, with their causal relations depicted by black arrows.
International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
35
coming into decision nodes represent the information that will be available when the decision is
. New computational methods
and techniques keep increasing BN’S abilities and range of practical applications [5].
ECISION-MAKING
to decide whether and what pest
agro ecological situation of his field.
notes down the date of observation,
crop condition, level of pest incidence, natural enemies and weather condition
Crop condition is measured in terms of its phenology. The level of pest incidence, presence of
natural enemies and weather condition are important to estimate the intensity of the attack The
whether there is need to apply
So by using the
BN model has been
The construction of BN model structure included: identifying the important variables and
ature and domain
BN model for agro ecological situation based IPM decision making was constructed. Six
level of pest incidence,
crop health, pest intensity and IPM options.
Level of pest incidence, natural enemies and weather are the parent nodes of pest intensity and
shows the Bayesian
The nodes in the BN
model represent the variables, with their causal relations depicted by black arrows.
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
36
To keep the BN model for IPM decision making as simple as possible, each node was
discretized into necessary states only. The definition of these states was performed
through literature review and expert consultation. In the model—Crop Health (CH) and
Natural Enemies (NE) nodes are binary and other are ordered value. The conditional probabilities
of these nodes are estimated basedon the data records available with public research institution, to
keep the size of the CPs manageable, each node have been assigned the fewest number of states
necessary.
6. IMPLEMENTATION OF BAYESIAN NETWORK MODEL FOR IPM DECISION
SUPPORT
CPTs for conceptual BN model were approximated. Actual CPTs could be defined based on data
analysis of the records available for agro ecological regions or on the basis of expert knowledge
and subsequently the model is evaluated. Model evaluation helps ensure the model’s interactions
and outcomes are feasible. The model can be tested by applying different agro ecological
scenarios (i.e. combinations of inputs) and examining whether the resulting probabilities are
reasonable and logical. Ideally, the accuracy of the model should be tested with empirical data,
but in many studies that use BNs these data are not available, at least not voluminously[11].
Once model is evaluated, input obtained from farmers for level of pest incidence, natural
enemies, and weather and crop health be propagated to the model for PA, NE, weather and CH
nodes, which changes the CP of PM node. CP of PM node would be deciding the pest
management option to be applied in the farmers filed. Higher CP for PM node will lead to
selection of stronger IPM option application and for moderate CP, milder IPM option be selected.
If CP for PM node is very low than, there is no need for application of any pest treatment. The
model thus validated could be used in IPM DSSs for selecting appropriate pest management
option to be advised to the farmers on the basis of tentative agro ecological information provided
by as model input.
7. CONCLUSION
Many DDSs have been developed for IPM by private and public organizations in the country but
for extension workers only few for farmers. Most of these DSSs are either web database or
information systems which provides information particularly on pest identification and
management. Little efforts have been made to develop field scouting based DSSs to provide real-
time decision support to the farmers. Even those few available field scouting based DSSs use pest
ETL as the basis for decision-making capturing quantitative pest incidence information only
instead of field agro-ecological situation, more holistic approach. But agro ecological information
obtained by the farmers form their field is tentative and contains uncertainties. Bayesian network
has unique advantage in dealing with uncerta in information. In following study, we found that
use of Bayesian networks will be perfect approach to develop technique/model for selecting
appropriate pest management option on the basis of tentative agro-ecological information
obtained by the farmers through field scouting. Subsequently the technique thus developed can be
used in field scouting based IPM DSSs to automate the process of decision support to the farmers.
7. International Journal of Computer Science & Information Technology (IJCSIT) Vol 9, No 2, April 2017
37
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