The document describes research on developing an expert system using forward chaining to diagnose diseases in tamarillo plants. Key points:
- Researchers created an expert system to help farmers diagnose diseases in tamarillo plants based on visible symptoms, as information on tamarillo diseases is currently limited.
- The expert system uses forward chaining reasoning techniques to develop rules based on symptom identification to determine pest or disease.
- Common tamarillo plant diseases include viral infections, powdery mildew, bacterial attack, aphids, caterpillars, and mites. The expert system analyzes symptoms that appear on the plant to diagnose the issue.
- The system aims to provide easily accessible information to
A study on real time plant disease diagonsis systemIJARIIT
The document discusses developing a real-time plant disease diagnosis mobile application. It aims to allow farmers to easily capture images of plant leaves using a mobile camera, send the images to a central system for analysis, and receive diagnoses and treatment recommendations. The proposed system would use image processing and data mining techniques to analyze leaf images for abnormalities, identify the plant species, recognize any diseases present, and recommend appropriate pesticides and estimate treatment costs. This would provide a low-cost, convenient solution for farmers to quickly diagnose and respond to plant diseases.
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.
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This document discusses various techniques for detecting diseases in pomegranate leaves, including visual inspection, spectral imaging, and machine learning approaches. It analyzes several studies that evaluated these techniques and their effectiveness in detecting common diseases like bacterial blight, anthracnose, and powdery mildew. Machine learning techniques like convolutional neural networks were shown to outperform other methods in accuracy and speed of detection. The document highlights the potential of these techniques, especially deep learning, to develop automated disease monitoring systems and aid farmers in managing diseases.
POMDETECT: AN INVESTIGATION INTO LEAF DISEASE DETECTION TECHNIQUESIRJET Journal
This document discusses various techniques for detecting diseases in pomegranate leaves, including visual inspection, spectral imaging, and machine learning approaches. It analyzes several studies that evaluated these techniques and their effectiveness in detecting common diseases like bacterial blight, anthracnose, and powdery mildew. Machine learning techniques like convolutional neural networks were shown to outperform other methods in accuracy and speed of detection. The document highlights the potential of automated disease detection systems to help farmers manage diseases and improve crop yields.
This document discusses a proposed loss-fused convolutional neural network model for identifying and classifying plant disease. The model aims to improve predictive performance by combining the advantages of two different loss functions. The model was tested on a dataset from the Plant Village Database and achieved 98.93% accuracy in discriminating between affected and unaffected plant leaf samples, outperforming other existing methodologies. The paper provides background on plant disease detection techniques and reviews related work applying machine learning and deep learning methods.
This document discusses the various applications of information technology in veterinary science. It begins by introducing veterinary informatics and some key areas where IT is applied, including disease surveillance using geo-informatics, disease diagnosis using various imaging technologies, artificial intelligence in health management, and data analysis. It then discusses veterinary hospital management software and its features and advantages. Next, it covers dairy herd management software and its benefits. Finally, it briefly mentions telemedicine and its role in veterinary care.
This document discusses techniques for detecting plant diseases using leaf images and convolutional neural networks. It begins with an abstract describing how image processing can be used for plant disease detection by applying techniques like preprocessing, segmentation, feature extraction, and classification to images. It then provides background on the importance of accurate plant disease detection. The paper reviews existing literature on plant disease detection methods and summarizes the datasets and techniques used in the proposed system, which applies a pretrained convolutional neural network model to classify leaf images as either healthy or diseased with common maize diseases.
A study on real time plant disease diagonsis systemIJARIIT
The document discusses developing a real-time plant disease diagnosis mobile application. It aims to allow farmers to easily capture images of plant leaves using a mobile camera, send the images to a central system for analysis, and receive diagnoses and treatment recommendations. The proposed system would use image processing and data mining techniques to analyze leaf images for abnormalities, identify the plant species, recognize any diseases present, and recommend appropriate pesticides and estimate treatment costs. This would provide a low-cost, convenient solution for farmers to quickly diagnose and respond to plant diseases.
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.
POMDETECT: AN INVESTIGATION INTO LEAF DISEASE DETECTION TECHNIQUESIRJET Journal
This document discusses various techniques for detecting diseases in pomegranate leaves, including visual inspection, spectral imaging, and machine learning approaches. It analyzes several studies that evaluated these techniques and their effectiveness in detecting common diseases like bacterial blight, anthracnose, and powdery mildew. Machine learning techniques like convolutional neural networks were shown to outperform other methods in accuracy and speed of detection. The document highlights the potential of these techniques, especially deep learning, to develop automated disease monitoring systems and aid farmers in managing diseases.
POMDETECT: AN INVESTIGATION INTO LEAF DISEASE DETECTION TECHNIQUESIRJET Journal
This document discusses various techniques for detecting diseases in pomegranate leaves, including visual inspection, spectral imaging, and machine learning approaches. It analyzes several studies that evaluated these techniques and their effectiveness in detecting common diseases like bacterial blight, anthracnose, and powdery mildew. Machine learning techniques like convolutional neural networks were shown to outperform other methods in accuracy and speed of detection. The document highlights the potential of automated disease detection systems to help farmers manage diseases and improve crop yields.
This document discusses a proposed loss-fused convolutional neural network model for identifying and classifying plant disease. The model aims to improve predictive performance by combining the advantages of two different loss functions. The model was tested on a dataset from the Plant Village Database and achieved 98.93% accuracy in discriminating between affected and unaffected plant leaf samples, outperforming other existing methodologies. The paper provides background on plant disease detection techniques and reviews related work applying machine learning and deep learning methods.
This document discusses the various applications of information technology in veterinary science. It begins by introducing veterinary informatics and some key areas where IT is applied, including disease surveillance using geo-informatics, disease diagnosis using various imaging technologies, artificial intelligence in health management, and data analysis. It then discusses veterinary hospital management software and its features and advantages. Next, it covers dairy herd management software and its benefits. Finally, it briefly mentions telemedicine and its role in veterinary care.
This document discusses techniques for detecting plant diseases using leaf images and convolutional neural networks. It begins with an abstract describing how image processing can be used for plant disease detection by applying techniques like preprocessing, segmentation, feature extraction, and classification to images. It then provides background on the importance of accurate plant disease detection. The paper reviews existing literature on plant disease detection methods and summarizes the datasets and techniques used in the proposed system, which applies a pretrained convolutional neural network model to classify leaf images as either healthy or diseased with common maize diseases.
Plant Disease Detection Technique Using Image Processing and machine LearningJitendra111809
This document discusses designing an image processing-based software solution for automatic detection and classification of plant leaf diseases. It aims to identify diseases using image processing and allow for early detection of diseases as soon as they appear on leaves. This would help farmers more quickly diagnose problems and improve crop yields. The document reviews literature on existing work using machine learning and deep learning for plant disease detection. It also discusses challenges farmers face and the benefits an automated detection system could provide like accelerated diagnosis. Feature extraction methods explored include color, texture, shape and morphology analysis to identify diseases. The document concludes an automated system is important for speeding up the crop diagnosis process.
Tomato Disease Fusion and Classification using Deep LearningIJCI JOURNAL
Tomato plants' susceptibility to diseases imperils agricultural yields. About 30% of the total crop loss is attributable to plants with disease. Detecting such illnesses in the plant is crucial to avoid significant output losses.This study introduces "data fusion" to enhance disease classification by amalgamating distinct disease-specific traits from leaf halves. Data fusion generates synthetic samples, fortifying a TensorFlow Keras deep learning model using a diverse tomato leaf image dataset. Results illuminate the augmented model's efficacy, particularly for diseases marked by overlapping traits. Enhanced disease recognition accuracy and insights into disease interactions transpire. Evaluation metrics (accuracy 0.95, precision 0.58, recall 0.50, F1 score 0.51) spotlight balanced performance. While attaining commendable accuracy, the intricate precision-recall interplay beckons further examination. In conclusion, data fusion emerges as a promising avenue for refining disease classification, effectively addressing challenges rooted in trait overlap. The integration of TensorFlow Keras underscores the potential for enhancing agricultural practices. Sustained endeavours toward enhanced recall remain pivotal, charting a trajectory for future advancements.
Final Year Project CHP 1& 2 CHENAI MAKOKO.docxChenaiMartha
The document proposes developing a model for early detection of layer bird diseases for layer poultry farmers. It discusses challenges small-scale farmers face in detecting diseases early due to limited access to veterinary support. Existing systems for disease detection include expert systems using certainty factors, deep learning models for detecting diseases from fecal images, and IoT-based frameworks. However, these systems either focus on expert diagnosis, rely on large datasets, or require specialized hardware. The proposed model aims to allow farmers to enter symptoms and receive recommendations to aid early disease detection.
Computer application in pest forecastingJayantyadav94
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.
The document proposes developing a system called the Layer Bird Vaccination Monitoring & Disease Detection System. This system would help small-scale layer poultry farmers in Zimbabwe track vaccinations, monitor treatments, and detect diseases early using data visualization and machine learning models. The system aims to address challenges small-scale farmers face like a lack of record keeping, monitoring of bird health, and limited access to veterinary support. It would allow farmers to enter bird symptom data and get recommendations to prevent losses from diseases.
An Innovative Approach for Tomato Leaf Disease Identification and its Benefic...IRJET Journal
This document summarizes an innovative approach for identifying diseases in tomato leaves using image processing and machine learning techniques. Specifically, a Convolutional Neural Network (CNN) model is developed and trained on a dataset of tomato leaf images showing various disease symptoms. Through testing and validation, the proposed approach achieves high accuracy in classifying different types of tomato leaf diseases. Integrating this method could enable timely disease detection, reduce crop losses, and optimize resource allocation for more sustainable agricultural practices. The research contributes a practical solution for automating tomato leaf disease detection to enhance disease management and food security.
This document discusses the use of artificial intelligence and machine learning techniques for chronic disease detection and management. It provides background on chronic diseases and their impact globally. It then discusses how machine learning algorithms can be used to analyze medical data from electronic health records to predict chronic diseases and suggest treatments. Various studies that have developed models using techniques like decision trees, neural networks, and random forests to detect diseases like cancer, kidney disease and diabetes are summarized. The ability of artificial intelligence to help diagnose chronic diseases earlier and improve healthcare management is also mentioned.
IRJET- Disease Analysis and Giving Remedies through an Android ApplicationIRJET Journal
The document describes a proposed Android application that uses decision trees to analyze symptoms and predict diseases. User-reported symptoms would be input to predict the disease and provide herbal remedies. The proposed system aims to overcome limitations of prior work by covering more diseases and their home remedies without side effects. It was developed using Android Studio and stores data in Firebase. The system uses a decision tree algorithm to predict disease based on symptom probability and scans a database to match remedies.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Integration of Other Software Components with the Agricultural Expert Systems...IJARTES
Expert System is a rapidly growing technology in
the field of Artificial Intelligence. It is a computer program
which captures the knowledge of a human expert on a given
problem, and uses this knowledge to solve problems in a
fashion similar to the expert. The system can assist the expert
during problem-solving, or act in the place of the expert in
those situations where the expertise is lacking. Expert systems
have been developed in such diverse areas as agriculture,
science, engineering, business, and medicine. In these areas,
they have increased the quality, efficiency, and competitive
leverage of the organizations employing the technology. This
paper highlights the major characteristics of expert systems,
reviews several systems developed for application in the area
of agriculture and an overview about the integration of other
software components with the agricultural expert systems.
Bacterial foraging optimization based adaptive neuro fuzzy inference system IJECEIAES
Life of human being and animals depend on the environment which is surrounded by plants. Like human beings, plants also suffer from lot of diseases. Plant gets affected by completely including leaf, stem, root, fruit and flower; this affects the normal growth of the plant. Manual identification and diagnosis of plant diseases is very difficult. This method is costly as well as time-consuming so it is inefficient to be highly specific. Plant pathology deals with the progress in developing classification of plant diseases and their identification. This work clarifies the identification of plant diseases using leaf images caused by bacteria, viruses and fungus. By this method it can be identified and control the diseases. To identify the plant leaf disease Adaptive Neuro Fuzzy Inference System (ANFIS) was proposed. The proposed method shows more refined results than the existing works.
Fruit Disease Detection and ClassificationIRJET Journal
This document proposes and experimentally validates a solution for detecting and classifying fruit diseases from images. The proposed approach uses K-means clustering for image segmentation, extracts features from the segmented image, and classifies the images using a Support Vector Machine (SVM). The experimental results show the proposed solution can accurately detect and automatically classify fruit diseases. It is intended to help farmers identify diseases early to improve crop management and reduce economic losses from diseases.
An AI-based Decision Platform built using unified data model, incorporating systems biology topics for unit analysis using semi-supervised learning models
Design and Implementation of an Expert Diet Prescription SystemWaqas Tariq
This document summarizes a research paper on the design and implementation of an expert diet prescription system. The system uses a knowledge base to identify ailments based on symptoms or name and prescribe appropriate diets. It has three access levels and a database of 7 ailments. The system was designed using Wamp server, PHP, MySQL and code charge studio. It aims to provide natural food-based treatments as an alternative to drugs to avoid adverse reactions.
Plug In Generator To Produce Variant Outputs For Unique Data.IJRES Journal
Our modern world comprising of abundant chronic diseases which are affecting humankind, awful thing is that they affect the people without being notified until the end. In this project we proposed a system in which the user identifies the disease by providing the symptoms which he is experiencing. The user selects the multiple symptoms which he/she is suffering and submits them for evaluation using String Matching System. The database consists of limited number of diseases, with well organized pattern structure of symptoms. Using a friendly interface, user can input the data in the questionnaire form developed. Artificial Bee Colony Optimization [ABC] algorithm, i.e., a Machine Learning algorithm embedded in the project provides an optimistic disease along with its prevention and curing methods, but before ABC produces optimistic disease, String Matching System approach gives an accurate disease with which the human is suffering from. The above said data transformed into web can be considered as an offline browsing system which can be used by any educated personalities, to generally know what is happening and gets enough idea before visiting the practitioner.
IRJET- A System for Complete Healthcare Management: Ask-Us-Health A Secon...IRJET Journal
This document proposes a system called ASK-US-HEALTH that uses machine learning algorithms and data mining to provide healthcare management. It aims to help patients access a second medical opinion by entering symptoms and receiving the probable diagnosis. It would also provide doctor recommendations and store patient medical histories and prescriptions. The system intends to improve healthcare access and help manage patient care and data for research through connecting patients, doctors, and nearby pharmacies via a web application.
RECOMMENDER SYSTEM FOR DETECTION OF DENGUE USING FUZZY LOGICIAEME Publication
The recommender System involved in health care is important since user can detect whether he has problem or not. A user will get whole information on the go. Today user doesn’t have much time and information about the dengue and it will be disclosed to the user at later stages. The dengue is deadly disease so its information should be disclosed at earlier stage. The proposed system works toward this aspect. The set of parameters including fever, TLC, blood pressure, severe headache etc. are analysed in proposed system. The filtering mechanism is also utilised in the proposed system which is integral part of recommender system. The content based filtering will be utilised in proposed system.
This document summarizes a research paper on developing a cloud-based health prediction system. The system allows users to enter their health issues and details like weight and height online. It then provides an accurate health prediction by matching the user's data to an analysis database. The cloud-based system is designed to be user-friendly and accessible from anywhere at any time. It aims to help users identify potential health problems early without visiting a doctor. The system architecture uses HTML, CSS, JavaScript, PHP and a MySQL database. It flows user data through registration, selecting health details, and logout for security.
Importance Of Top-Rated Essay Writing Services - A Helpful Tool ForSean Flores
The document discusses the steps to use an essay writing service:
1. Create an account with personal information.
2. Complete a form providing instructions, sources, deadline and sample work.
3. Review bids from writers and choose one based on qualifications.
4. Review the paper and authorize payment or request revisions if needed. The service offers refunds for plagiarized work.
Linking Words For Essay Telegraph. Online assignment writing service.Sean Flores
1. The document provides instructions for how to request and receive writing assistance from the HelpWriting.net website. It outlines a 5-step process for creating an account, submitting a request, reviewing bids from writers, revising the paper if needed, and requesting revisions.
2. The process involves registering with a password and email, completing a request form with instructions and deadlines, choosing a writer based on their profile, paying a deposit to start the work, reviewing and authorizing payment for the completed paper or requesting revisions.
3. HelpWriting.net uses a bidding system where writers submit proposals, and clients can ensure their needs will be fully met with original, high-quality content or receive a refund if plag
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Plant Disease Detection Technique Using Image Processing and machine LearningJitendra111809
This document discusses designing an image processing-based software solution for automatic detection and classification of plant leaf diseases. It aims to identify diseases using image processing and allow for early detection of diseases as soon as they appear on leaves. This would help farmers more quickly diagnose problems and improve crop yields. The document reviews literature on existing work using machine learning and deep learning for plant disease detection. It also discusses challenges farmers face and the benefits an automated detection system could provide like accelerated diagnosis. Feature extraction methods explored include color, texture, shape and morphology analysis to identify diseases. The document concludes an automated system is important for speeding up the crop diagnosis process.
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Tomato plants' susceptibility to diseases imperils agricultural yields. About 30% of the total crop loss is attributable to plants with disease. Detecting such illnesses in the plant is crucial to avoid significant output losses.This study introduces "data fusion" to enhance disease classification by amalgamating distinct disease-specific traits from leaf halves. Data fusion generates synthetic samples, fortifying a TensorFlow Keras deep learning model using a diverse tomato leaf image dataset. Results illuminate the augmented model's efficacy, particularly for diseases marked by overlapping traits. Enhanced disease recognition accuracy and insights into disease interactions transpire. Evaluation metrics (accuracy 0.95, precision 0.58, recall 0.50, F1 score 0.51) spotlight balanced performance. While attaining commendable accuracy, the intricate precision-recall interplay beckons further examination. In conclusion, data fusion emerges as a promising avenue for refining disease classification, effectively addressing challenges rooted in trait overlap. The integration of TensorFlow Keras underscores the potential for enhancing agricultural practices. Sustained endeavours toward enhanced recall remain pivotal, charting a trajectory for future advancements.
Final Year Project CHP 1& 2 CHENAI MAKOKO.docxChenaiMartha
The document proposes developing a model for early detection of layer bird diseases for layer poultry farmers. It discusses challenges small-scale farmers face in detecting diseases early due to limited access to veterinary support. Existing systems for disease detection include expert systems using certainty factors, deep learning models for detecting diseases from fecal images, and IoT-based frameworks. However, these systems either focus on expert diagnosis, rely on large datasets, or require specialized hardware. The proposed model aims to allow farmers to enter symptoms and receive recommendations to aid early disease detection.
Computer application in pest forecastingJayantyadav94
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.
The document proposes developing a system called the Layer Bird Vaccination Monitoring & Disease Detection System. This system would help small-scale layer poultry farmers in Zimbabwe track vaccinations, monitor treatments, and detect diseases early using data visualization and machine learning models. The system aims to address challenges small-scale farmers face like a lack of record keeping, monitoring of bird health, and limited access to veterinary support. It would allow farmers to enter bird symptom data and get recommendations to prevent losses from diseases.
An Innovative Approach for Tomato Leaf Disease Identification and its Benefic...IRJET Journal
This document summarizes an innovative approach for identifying diseases in tomato leaves using image processing and machine learning techniques. Specifically, a Convolutional Neural Network (CNN) model is developed and trained on a dataset of tomato leaf images showing various disease symptoms. Through testing and validation, the proposed approach achieves high accuracy in classifying different types of tomato leaf diseases. Integrating this method could enable timely disease detection, reduce crop losses, and optimize resource allocation for more sustainable agricultural practices. The research contributes a practical solution for automating tomato leaf disease detection to enhance disease management and food security.
This document discusses the use of artificial intelligence and machine learning techniques for chronic disease detection and management. It provides background on chronic diseases and their impact globally. It then discusses how machine learning algorithms can be used to analyze medical data from electronic health records to predict chronic diseases and suggest treatments. Various studies that have developed models using techniques like decision trees, neural networks, and random forests to detect diseases like cancer, kidney disease and diabetes are summarized. The ability of artificial intelligence to help diagnose chronic diseases earlier and improve healthcare management is also mentioned.
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The document describes a proposed Android application that uses decision trees to analyze symptoms and predict diseases. User-reported symptoms would be input to predict the disease and provide herbal remedies. The proposed system aims to overcome limitations of prior work by covering more diseases and their home remedies without side effects. It was developed using Android Studio and stores data in Firebase. The system uses a decision tree algorithm to predict disease based on symptom probability and scans a database to match remedies.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Research Inventy : International Journal of Engineering and Scienceresearchinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Integration of Other Software Components with the Agricultural Expert Systems...IJARTES
Expert System is a rapidly growing technology in
the field of Artificial Intelligence. It is a computer program
which captures the knowledge of a human expert on a given
problem, and uses this knowledge to solve problems in a
fashion similar to the expert. The system can assist the expert
during problem-solving, or act in the place of the expert in
those situations where the expertise is lacking. Expert systems
have been developed in such diverse areas as agriculture,
science, engineering, business, and medicine. In these areas,
they have increased the quality, efficiency, and competitive
leverage of the organizations employing the technology. This
paper highlights the major characteristics of expert systems,
reviews several systems developed for application in the area
of agriculture and an overview about the integration of other
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Life of human being and animals depend on the environment which is surrounded by plants. Like human beings, plants also suffer from lot of diseases. Plant gets affected by completely including leaf, stem, root, fruit and flower; this affects the normal growth of the plant. Manual identification and diagnosis of plant diseases is very difficult. This method is costly as well as time-consuming so it is inefficient to be highly specific. Plant pathology deals with the progress in developing classification of plant diseases and their identification. This work clarifies the identification of plant diseases using leaf images caused by bacteria, viruses and fungus. By this method it can be identified and control the diseases. To identify the plant leaf disease Adaptive Neuro Fuzzy Inference System (ANFIS) was proposed. The proposed method shows more refined results than the existing works.
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Our modern world comprising of abundant chronic diseases which are affecting humankind, awful thing is that they affect the people without being notified until the end. In this project we proposed a system in which the user identifies the disease by providing the symptoms which he is experiencing. The user selects the multiple symptoms which he/she is suffering and submits them for evaluation using String Matching System. The database consists of limited number of diseases, with well organized pattern structure of symptoms. Using a friendly interface, user can input the data in the questionnaire form developed. Artificial Bee Colony Optimization [ABC] algorithm, i.e., a Machine Learning algorithm embedded in the project provides an optimistic disease along with its prevention and curing methods, but before ABC produces optimistic disease, String Matching System approach gives an accurate disease with which the human is suffering from. The above said data transformed into web can be considered as an offline browsing system which can be used by any educated personalities, to generally know what is happening and gets enough idea before visiting the practitioner.
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This document proposes a system called ASK-US-HEALTH that uses machine learning algorithms and data mining to provide healthcare management. It aims to help patients access a second medical opinion by entering symptoms and receiving the probable diagnosis. It would also provide doctor recommendations and store patient medical histories and prescriptions. The system intends to improve healthcare access and help manage patient care and data for research through connecting patients, doctors, and nearby pharmacies via a web application.
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This document summarizes a research paper on developing a cloud-based health prediction system. The system allows users to enter their health issues and details like weight and height online. It then provides an accurate health prediction by matching the user's data to an analysis database. The cloud-based system is designed to be user-friendly and accessible from anywhere at any time. It aims to help users identify potential health problems early without visiting a doctor. The system architecture uses HTML, CSS, JavaScript, PHP and a MySQL database. It flows user data through registration, selecting health details, and logout for security.
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The document discusses how the endocrine system maintains homeostasis in the body. It does so by secreting hormones into the bloodstream which help regulate growth, reproduction, and other bodily functions. The hormones released by the endocrine system's glands, such as the pituitary, thyroid, and adrenal glands, work to keep hormonal levels constant and stable, allowing the body to maintain its natural state of homeostasis.
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Trade protectionism refers to policies that place restrictions on imports or promote exports, usually through the use of tariffs, quotas, and subsidies. While protectionism aims to protect domestic industries from foreign competition, it can lead to less efficient production and higher prices for consumers. There is typically debate around whether the benefits of protecting certain industries outweigh the costs of reduced trade and higher prices.
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1. The document discusses a linear regression model that was run using an index of attitudes toward income inequality as the independent variable.
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In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Philippine Edukasyong Pantahanan at Pangkabuhayan (EPP) CurriculumMJDuyan
(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
A Forward Chaining Trace Analysis In Diagnosing Tamarillo Disease
1. The 6th
International Conference on Cyber and IT Service Management (CITSM 2018)
Inna Parapat Hotel – Medan, August 7-9, 2018
A Forward Chaining Trace Analysis In Diagnosing
Tamarillo Disease
Mikha Dayan Sinaga, Bob Subhan Riza, Juli Iriani, Ivi Lazuly, Daifiria, Edy Victor Haryanto S
Faculty of Engineering and Computer Science
Universitas Potensi Utama
Jl. K.L. Yos Sudarso Km. 6,5 No. 3A – Medan, 20241, Indonesia
Abstract— In the development of science found some search
techniques, one of them is forward chaining. advanced chaining
tracing techniques can be used to analyze certain diseases, both
human, animal, and plant diseases. Reasoning is made of
symptoms that appear physically to the tamarillo plant. Based on
these symptoms made the rules that then become a knowledge
base that will be applied to the inference machine to find out
what the disease experienced by the tamarillo plant. The results
of this program indicate that expert systems can be used as a
medium that can provide information about tamarillo plants.
This expert system can be used to speed up the search and access
to knowledge by people who need information.
Keywords— Expert System, Forward Chaining, Tamarillo,
Knowledge Based.
I. INTRODUCTION
Expert system is one component of artificial intelligence
that works like an expert but can not replace human
intelligence. It supports the experts in making decisions.
Sometimes in turn is used as a knowledge-based system and is
a computer software that makes decisions like an expert. the
advantage of expert systems is the use of traditional
programming languages and not dependent on the code, and
also on data stored in different locations called knowledge
bases. For this reason, expert systems do not need to be
programmed because domain knowledge changes over time or
from experts to expert knowledge. In real situations,
intelligent systems are applied in different decision-making
processes from medical activities to intelligent decision-
making purposes [1].
Community or farmer knowledge of pests or viruses that
can attack tamarillo plant disease is still lacking, because
information concerning pests and viruses tamarillo plant is
still small. For that reason researchers feel the need to create
an expert system that can diagnose diseases caused by pests or
viruses from tamarillo plants, so it can help the tamarillo
farmers.
The designed expert system will be equipped with
advanced chaining tracing techniques. the search techniques
applied in this system will produce rules that will serve as a
benchmark in detecting pests or diseases from tamarillo plants.
the advanced chaining trace technique begins by identifying
the symptoms that appear on the physical plant of tamarillo.
From these symptoms can be drawn a conclusion of pests
or diseases suffered by tamarillo plants.
II. RELATED WORK
To give more prespective about expert system, this
section describes and examines previous work done in field of
expert system.
S Abu Naser, Abed ELhaleem Ahmad El-Najjar “An
expert system for nausea and vomiting problems in infants and
children” says a proposed expert system was presented for
aiding Physicians in diagnosing patients with possible Nausea
and Vomiting in Infants and Children [1].
A.A.L.C. Amarathunga, et al “Expert System For
Diagnosis Of Skin Diseases” says that an expert system can be
used to diagnosing Skin Disease. In this expert system while
administrator managing the information of skin disease,
symptoms, medical treatment suggestions and it prepared
statement to view the summery about Skin Disease [2].
Avneet Pannu, M. Tech Student “Survey on Expert System
and its Research Areas” says that Expert system will continue
to play an increasingly important role in the various fields. In
the survey done in this paper biomedical, automobile and
agriculture areas comes under the diagnosis and the other
areas such as education that uses the fuzzy logic comes under
the decision area of expert system [3].
Monish Kumar Choudhury, Neelanjana Baruah “A Fuzzy
Logic Based Expert System For Determination Of Health Risk
Level Of Patient” says that a fuzzy expert system for
determination of the risk level of patient, which can be used
in any situation when it is necessary to predict the health
status of patient. The designed system can be used by the
doctor or by the patient himself [4].
C. F. Tan, et al “The Application Of Expert System: A
Review Of Research And Applications” says that Modern
businesses, academicians, scientists, engineers, manufacturers
or individual were recommended to compile resources and
expertise data which significantly will benefit other people.
For companies, it could be the master storage the knowledge
and operation expertise in keeping survival the operation of
the company and eliminate a problem hiring or replacing
human
experts [5].
2. The 6th
International Conference on Cyber and IT Service Management (CITSM 2018)
Inna Parapat Hotel – Medan, August 7-9, 2018
Dr. Nadeem Ahmed, et al “Role of Expert Systems in
Identification and Overcoming of Dengue Fever” says that In
computer science, systems that can solve a specific problem
and can reason rationally are known as Expert Systems. These
systems require knowledge of the relevant problem and
techniques to infer the result in order to make decision. In
recent years, different researchers have proposed different
expert systems for identification, prescribe medicine and
overcoming Dengue disease. These expert systems use
different technique for getting better result like Bayesian
Belief Network (BBN), Artificial Neural Networks (ANN),
Fuzzy inference and Hybrid learning algorithm for ANIS [6].
Ayangbekun Oluwafemi J, Jimoh Ibrahim A. “Expert
System for Diagnosis Neurodegenerative Diseases” says that
an expert system in Healthcare management hospitals presents
as one of the best applications for deriving meaningful
diagnosis of human health challenges. From the study, this
application serves as a model tool that will enable hospitals to
effectively monitor patients‟ medical records without
ambiguity. This will provide a great reduction in the hours
wasted in most conventional hospitals without this tool [7].
III. RESEARCH METHODS
The inference engine in forward chainning uses the
information specified by the user to move the logic and and or
until the object is specified. If the inference engine can not
determine the object it will ask for other information.
Therefore, to achieve the object must meet all the rules. One
method that can be applied in an expert system is the forward
chaining method. Forward chaining is also called reasoning
from the bottom up. A chain that is sought or traversed from a
problem to obtain the solution is called forward chaining.
Another way of describing forward chaining is by reasoning
from fact to conclusion derived from fact [8].
Forward Chaining is a method of searching / retrieving
conclusions based on existing data or facts leading to
conclusions, tracing begins with existing facts and moving
forward through the bottom up reasoning premises [9].
Fig 1. Forward Chaining Reasoning
IV. RESULT AND DISCUSSION
A. Tamarillo Plant
From its Latin name, can be seen not one genus with
eggplant (Solanum sp.). Tamarillo comes from the Andes
Mountains in South America, particularly in Peru, then spread
to regions such as Chile, Ecuador, Bolivia, Argentina and
Colombia. In Indonesia tamarillo is common in North Sumatra
[10].
Tamrillo is a fruit that contains nutrients and vitamins that
are very important for the health of the human body such as
anthocyanin, carotenoids, vitamins A, B6, C and E and rich in
iron, potassium and fiber. tamarillo has a low sodium content.
The average tamarillo has a calorie of less than 40 calories (±
160 kilojoules) [10].
These trees include pest-resistant attacks. The main pests
that often attack are aphids (aphids), leaf-eating caterpillars
(Spodoptera Litura), mites and root-knot nematodes
(Meloidigyne spp) are also harmful and together with the virus
will lead to stunted and unproductive plants. High
temperatures and humidity will make things worse. How to
control it with Folidol or the like, so no harm to those who
consume [10].
The main diseases that attack tamarillo plants according
to fruit plant research centers are: [10]
1. Viral infections, among others tamarillo mosaic
viruses, cucumber mosaics, Arab mosaics and one or
more unidentified viruses. These viruses spread
rapidly causing the decline of tamarillo gardens.
Healthy plants should be planted as far as possible
from older trees. Prevention of the virus can be done
by closely watching the cleanliness of the orchard
and its vector eradication is the main way to prevent
the virus.
2. The most disturbing fungal disease is powdery
mildew. If the attack is severe, it will cause old
leaves to fall out early. This disease can be overcome
by regular treatment of sulfur or a more specific
fungicide. Another alternative is to maintain a
sufficiently high growth rate to replace the lost
leaves.
3. Bacterial attack caused by Pfeudomonas syringae.
B. Needs Analysis
The expert system detects the disease of this Tamarillo
plant performing advanced searches of visible symptoms to
obtain diagnostic results. Therefore we need clear symptom
data to be able to give the right diagnosis result.
Tamarillo plants have about 7 diseases or pests such as
aphids, caterpillars, mites, bacterial wilt, fruit rot, dew fungus
and viruses. All diseases or pests are analyzed based on the
symptoms that appear on the plant. If there are no visible
symptoms in the plant it can be concluded that the Tamarillo
plant is healthy. To investigate the disease in Tamarillo plants
does not require lab tests, because the diseases of the
Tamarillo plant have symptoms that appear directly. The
following data from the symptoms of Tamarillo plant disease
based on research conducted as in table 1 below: [11]
3. The 6th
International Conference on Cyber and IT Service Management (CITSM 2018)
Inna Parapat Hotel – Medan, August 7-9, 2018
TABLE I
DATA DISEASES AND SYMPTOMS
No Diseases / Pests Criteria
1 Flea Leaf
- Make the leaves roll up
- Make the leaves become curly
- There are lice on the leaves.
2 Leaf Caterpillar - Hole leaves
3 Mite
- The leaves have brownish or
black spots
4 Bacterial Wilt
-The plants become withered
suddenly
5 Rotten Fruit - Fruit has brownish spots
6 Dew fungus
- There are white grains like flour
on a leaf
7 Virus
-Tree becomes dwarf (slow
growth)
- Small fruit
- The leaves are falling
C. Presentation of Facts and Rules
Presentation of facts and rules for the detection of
diseases in Dutch plants is made into the form of tables as
follows:
TABLE II
RULES
No Rules
1
IF Making the leaves rolled is True
AND Make curly leaves is True
AND Dislike pressure is True
THEN Fleas Leaves
2
IF Hollow Leaf is True
THEN Caterpillar Leaves
3
IF Leaves have brownish or black red spots is True
THEN Mites
4
IF Crops withered suddenly is True
THEN Layu Bakteri
5
IF There are brownish spots on the leaves is True
THEN Rotten Fruit
6
IF There are white grains like flour on leaves is True
THEN Dew Fungus
7
IF Tree becomes dwarf (slow growth) is True
AND Small fruit is True
AND Leaves falling is True
THEN Virus
D. Testing Result
One of the results of system testing can be seen in the
following table.
TABLE III
TESTING RESULT
From table above after being entered the answer on the
expert system program found the type of aphids disease. This
is because of the question items more directed to the existing
rule in accordance with the disease aphids.
V. CONCLUSION
Based on the research and discussion conducted, it can be
concluded as follows:
1. By using forward chaining method then the process
of disease analysis on tamarillo plant. can be done, so
it will produce a rule base that can be used to trace
diseases or pests that can attack tamarillo plants.
based on apparent symptoms.
2. the application of advanced chaining tracing
techniques will produce rules that can be used as a
reference in detecting or diagnosing pests and
diseases of tamarillo plants.
ACKNOWLEDGMENT
The authors would like to thank Universitas Potensi
Utama for their advice and financial support. The authors also
thank to patients who are willing to provide data related to
diseases caused by salmonella bacteria.
REFERENCES
[1] Abu Naser, Samy S., and Abed ELhaleem A. El-Najjar.
"An expert system for nausea and vomiting problems in
infants and children." (2016).
Question Answer
What is Rolling Leaves? Yes
Are There Lice Looks On Leaves? Yes
What is Curly Leaves? Yes
Does Leaves Look Hollow? No
Does On Leaf Look Red or Brown Or Black
Spots?
No
Is the Plant Experiencing the Woods
Suddenly?
No
Are There Fruits Available in White Grains? No
Does the Tree Not Increase Big (dwarf)? No
Is the Fruit Small? No
Are the Leaves Falling? No
Is There Fruit There Are Brown Spot? No
Leaf lice disease. Solution: Set the planting time, Crop
rotation, Use of natural enemies such as Parasitoid
Aphelinus gossypi (Timberlake), Lysiphlebus testaceipes
(Cresson). Predators Coccinella transversalis and
Entomopatogen Fungus Neozygites fresenii
4. The 6th
International Conference on Cyber and IT Service Management (CITSM 2018)
Inna Parapat Hotel – Medan, August 7-9, 2018
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