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63 articles for “Plant disease”
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The Implementation of Machine Learning in the Search to Fight Plant Disease
Abstract: The agriculture business loses money and time due to plant diseases. Diagnosing disease accurately takes skill and devotion. Infected plants may have spots or streaks of a different color on their leaves. Several fungal, bacterial, and viral species can also infect plants. Individual plant disease signs and indications are assessed. Neural network applications are growing. Recent research studies have determined how well machine learning reviews traditional plant disease diagnosis methods. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 25–34 Read article
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Deep Learning for Smarter Farming: Innovations in Plant Disease Identification
Abstract: Agriculture is the backbone of global food security, yet plant diseases significantly impact crop yields and farmers' livelihoods. Traditional disease detection methods are often time-consuming and require expert intervention, making them less feasible for large-scale farming. Recent advancements in deep learning have revolutionized plant disease identification by offering automated, accurate, and efficient solutions. This article explores innovative deep learning techniques, including convolutional neural networks (CNNs) and transformer-based models, that enhance …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 27–32 Read article
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Comparison of Various Methodologies used for Automating Plant Disease Detection using Image Processing
Abstract: In India, major of economy and development depends on agriculture, so plant disease detection becomeimportant for us so that if any crop is destroyed due to diseases is known to us prior and we can overcomethe loss of crops due to plant diseases. It is better to catch the disease in the initial phase so that the largescaledamage of crops can be prevented. Traditionally, the diseases incurred via the naked …
Published in International Journal of Agrochemistry · Vol. 7, Issue 1, 2021 · pp. 20–23 Read article
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Recent Advancement of Nanotechnology in Plant Disease Management
Abstract: Nanoparticles are small size particles having potential to work in large surface area. Size of nanoparticles vary from 1-100 nm. The composition of nano-formulation should break down quickly in the soil and sluggishly in plants with remnant levels under the regulatory standards in foodstuffs. The nanoparticle synthesis methods can be categorized into bottom-up or top-down method Physical- Ball milling, nanolithography, pulsed laser, electrochemical; Chemical- Vaccum deposition and vaporization, chemical vapor …
Published in International Journal of Applied Nanotechnology · Vol. 7, Issue 2, 2021 · pp. 34–42 Read article
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Iot Based Smart Farming with Plant Disease Detection Using CNN
Abstract: In this project, we have discussed the utilization of the power of contemporary technology like sensors and cloudcomputing. IoT-based smart farming is revolutionizing traditional agricultural practices. Additionally, this project enables farmersto manage their farms remotely. This project's primary goal is to support an existing farmer and a new farmer who wants to startfarming as their side income source through remote farming. Farmers can monitor numerous environmental elements includingtemperature, humidity, soil …
Published in International Journal of Analog Integrated Circuits · Vol. 9, Issue 1, 2023 · pp. 36–47 Read article
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Advancing Maize Leaf Disease Detection: A Machine Learning Approach
Abstract: Every day, countless grains and fruits are cultivated around the world. To keep up with the growing population’s needs, farmers are constantly adopting new and advanced techniques. Furthermore, the development and application of new technologies enable the quick and simple detection of plant diseases. Identifying plant diseases at an early stage is crucial to minimizing their effects on crop productivity and quality. Traditional diagnostic methods often rely on expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 17–25 Read article
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Predictive Farming Using Image Based Machine Learning
Abstract: Agriculture sector is considered as central pillar of Indian economics contributing approximately18% of total GDP employing almost 78% of rural population. Export of agro- based commodities hasincreased by 7-folds in past 1.5 decade. Therefore, it is necessary to uplift quality of agro-commoditiesproductions. Improving crop quality and quantity by sowing appropriate crop according to soil typeand weather condition become an hour’s need today. There are variety of soil series available in …
Published in International Journal of Agrochemistry · Vol. 7, Issue 1, 2021 · pp. 24–32 Read article
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Identification of Plant Leaf Diseases Using CNN
Abstract: The proposed approach helps detect leaf withering and provides a treatment. Databases retrieved from the internet are strictly isolated; unique leaf seeds are recognized and renamed to create an acceptable database. Next, you will receive a test database consisting of a series of leaf rots that will be used to verify the accuracy and reliability stages of your project. Already used. Then use the coaching statistics to train the classifier …
Published in International Journal of Software Computing and Testing · Vol. 8, Issue 1, 2022 · pp. 1–5 Read article
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Role of Plants Against Human Skin Diseases: AComprehensive Study
Abstract: Humans are infected by different types of skin diseases caused by Bacteria, Viruses and Fungi. Abscess caused by Staphylococcus bacteria, Genital herpes, resulting from the herpes simplex virus (HSV), is among the prevalent skin conditions affecting individuals worldwide, irrespective of their country's level of development. Skin diseases should be prevented by the allopathy, homeopathy and ayurvedic methods. Ayurvedic methods are based on application of natural resources are preferred over allopathy …
Published in International Journal of Plant Biotechnology · Vol. 10, Issue 1, 2024 · pp. 43–48 Read article
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Detection of Leaf Diseases Using Image Processing Techniques
Abstract: Agricultural field plays a vital role in the earning to feed ever growing population. The productivity of the crop depends on pest attack, disease, weather, etc. The disease in plants will affect the production of crops. Detecting diseases in plants through visualization is a traditional method which is not relevant. We are focusing on reliable, fast and accurate detection method that can be done using image processing techniques to monitor …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 5, Issue 2, 2019 · pp. 14–19 Read article
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Crop Disease Classification and Detection Using Deep Learning Approach
Abstract: Early diagnosis of plant diseases is essential because they have an effect on the evolution of their unique species. For the identification and classification of plant diseases, a variety of Machine Learning (ML) models have been employed, but with the advent of Deep Learning (DL), a subset of ML, this area of research now seems to offer substantial potential for increased accuracy. The 4th most common staple food consumed worldwide …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 22–27 Read article
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Mycoplasma Like Organisms or Pleuro Pneumonia Like Organisms (PPLO)
Abstract: Mycoplasma like Organisms is the smallest of microorganisms causing plant disease. Viruses are acutely small (they can be seen only with the aid of an electron microscope), being composed of nothing more than a protein shell consisting a small amount of genetic material. Plant viruses commonly survive year-round in perennial weeds and trees or insect vectors, and are transmitted to other plants via feeding activities of certain insects, usually aphids, …
Published in International Journal of Plant Biotechnology · Vol. 3, Issue 1, 2017 · pp. 1–4 Read article
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Classification and Detection of Cabbage Leaf Diseases from Images Using Deep Learning Methods
Abstract: The presented work uses Deep learning methods to detect diseases in cabbage leaves. To avoid a reduction in agricultural product yield, disease diagnosis in plants is crucial. Manual plant disease monitoring is challenging and time-consuming at every stage. Five major types of diseases are considered. Initially, the input images are classified as healthy and diseased. Further, the diseased images are classified into five different varieties. Early and precise biotic stress …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 8, Issue 2, 2022 · pp. 23–32 Read article
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Bio-Fertilizer in Forest Nursery-A Review
Abstract: Many micro-organisms like bacteria, fungi, algae possess plant growth promoting mechanisms. These micro-organisms may be implemented as biofertilizers in agriculture and forestry, improving crop yields. These Biofertilizers can enhance plant increase through numerous different mechanisms. The synthesis of plant nutrients or phytohormones, which may be absorbed with the aid of using plants, mobilization of soil compounds, making them to be available for the plant for use as nutrients, the safety …
Published in International Journal of Industrial Biotechnology and Biomaterials · Vol. 6, Issue 2, 2020 · pp. 1–14 Read article
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Comparative efficacy of insecticides and plant extracts to manage Bemisia tabaci (Genn.) and tomato leaf curl virus disease
Abstract: Tomato (Lycopersiconesculentum) is most important vegetable crop of Pakistan. It is attacked by many biotic and abiotic diseases. Among the viral disease tomato leaf curl virus disease (TLCVD) is most important disease that causes heavy yield losses. Under natural field conditions, TLCVD is transmitted by Bemisia tabaci. Comparative efficacy of insecticides and plant extracts to manage Bemisia tabaci (Genn.) and tomato leaf curl virus disease was studied under natural field …
Published in International Journal of Agrochemistry · Vol. 4, Issue 1, 2018 · pp. 7–14 Read article
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A Sensor-Based Soil Monitoring System for Better Crop Harvesting
Abstract: Crop productivity is strongly affected by soil health, environmental conditions, and the availability of timely and accurate monitoring data. Traditional soil testing and crop assessment methods are labor-intensive and time-consuming. They also lack real-time capabilities, which limits efficient agricultural decision-making. This paper proposes an IoT-enabled smart soil monitoring and crop management system that provides real-time analysis of important soil and environmental parameters to improve agricultural productivity. The proposed system uses …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 1, 2026 · pp. 18–24 Read article
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Mass Production and Isolation of Trichoderma harzianum from Different Media Using Liquid and Solid Fermentation Technique and Evolution against Fusarium oxysporum
Abstract: Mycelial growth conidal production and biomass yield of trichoderma species (Trichoderma harzianum) were examined on different culture media including potato dextrose media, waksman media, soyabean meal media, glucose peptone media, jaggery media, malt extract media, cornmeal media, czepaks media. A big factor in growth rate was the medium. The optimum medium in terms of growth spore generation and biomass output was soyabean meal media. For mycelial growth, biomass output, and …
Published in International Journal of Chemical Separation Technology · Vol. 8, Issue 1, 2022 · pp. 27–37 Read article
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A Review on Potential use of Bioherbicides for preventing the growth of weed plants
Abstract: Like pests, disease and other hazards weeds are one of the major problems for farmers. They not only compete with crops for water, nutrients, sunlight, and space but also harbor insect and disease pests, clog irrigation and drainage systems undermine crop quality and deposit weed seeds into crop harvests. They can heavily damage the production of crops as well as they reduce the value of land. Weeds can also host …
Published in International Journal of Agrochemistry · Vol. 3, Issue 2, 2017 · pp. 10–13 Read article
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Advancement in Nanodiagnostic for Plant Pathogen Detection
Abstract: Nanotechnology refers to a nanoscale innovation, which has promising applications in everyday life. The word nanotechnology is generally used when referring to materials with the size of 0.1 to 100 nanometers. Nanotechnology is a multi-displinary science involving knowledge fro biology, chemistry, physics and other disciplines. The nanoparticles have small size, large surface area and high reactivity. These properties of nanoparticles revolutionized the agriculture researches. Rapid disease detection, targeted treatments, enhancing …
Published in International journal of Nanobiotechnology · Vol. 4, Issue 2, 2018 · pp. 1–7 Read article
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Biofertilizers: A Review
Abstract: One of the significant in today's world is the pollution and contamination of soil. The utilization of chemical fertilizers and pesticides has caused gigantic harm to the environment. An answer to this is the biofertilizer, an Eco Friendly fertilizer now used in most countries. Biofertilizers are organisms that enrich the nutrient quality of soil. The main sources of biofertilizers are bacteria, fungi, and Cyanobacteria (blue-green algae). The most marked relationship …
Published in International Journal of Industrial Biotechnology and Biomaterials · Vol. 3, Issue 1, 2017 · pp. 5–12 Read article