Prediction Models for Identification and Diagnosis of Tomato Plant Diseases

Verma, Shradha; Chug, Anuradha; Singh, Amit Prakash

doi:10.1109/icacci.2018.8554842

Cited by 44 publications

(16 citation statements)

References 19 publications

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“…In the world, India is one among top three nations of huge production tomato and produces 18.7 Million tons of tomato, but the quality, as well as productivity, declined due to various diseases, pest attacks, nutrient deficiency, and uneven climatic conditions. Existing agricultural practices usually lacks in proper soil testing, watering, and water testing, fertilizer calculation, proper pest management, data collection of micro-organisms [5]. All this needs a more human resource.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, the researcher's findings support a predator-in-first augmentation approach for management of TLM. Verma, S., Chug, A., & Singh, A.P, have presented about Prediction models for identification and diagnosis of Tomato Plant Diseases [5]. In this paper, the researcher presented a survey on detection and prediction models for tomato plant diseases, based on Image processing and IoT sensors and summarizes the studied approaches and methodologies.…”

Section: Background Studymentioning

confidence: 99%

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Precision Data Acquisition and Analysis for Nutrient Management of Tomatoes

Yogeswari

Padmapriya²

2019

AJCST

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Agriculture is the soul of every nation, where it considers some factors such as uneven rainfall, changing climate and weather conditions, monsoon for soil and nutrient during the crop growth. Agriculture is predominantly essential and the main source of our livelihood. Nutrient management is a major thirst area and to be the focus in the field of agriculture. Due to the paucity of nutrients in plants, the human is forced to face many challenges in day-to-day life. Restoration of nutrient is crucial, in this view there is need to espouse the precision agriculture system which alters crop related plan and policies. The main aim of this research is to collect some of the factors influencing nutrients in plant growth and analyze them. The data collection is done by both manual and precision methods. The plant chosen for the analysis is Tomato – a horticulture crop. This is an attempt towards developing an expert system based on precision data.

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Section: Methodsmentioning

confidence: 99%

Section: Background Studymentioning

confidence: 99%

Precision Data Acquisition and Analysis for Nutrient Management of Tomatoes

Yogeswari

Padmapriya²

2019

AJCST

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“…The article [4] describes about the two main pests occur while planting tomatoes in terrace garden and gives the remedy based on android platform. The research work [5] has the brief concept of various pest and diseases occurred in tomato gardening system and identify those diseases based on IOT detection sensors services and explains the whole works. The research article [6] describes the modern tools, new farming techniques and various traditional techniques used in farming.…”

Section: Literature Reviewmentioning

confidence: 99%

“…They are nothing but, the pest lives nearby or inside the plants and eats the tissues [5] and leaves of the tomato plant [6]. Symptoms may be look like crooked circuitous ash color lines and patches on the leaves.…”

Section: B Leaf Miner Flies (6 Weeks)mentioning

confidence: 99%

Recommender System for Nutrient Management Based on Precision Agriculture

Yogeswari,

Padmapriya

2019

IJRTE

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Agriculture is the heart of our nation and society. It is influenced by several factors and parameters such as uneven monsoon, changing climate as well as weather circumstances, rainfall and nutrient facts during the harvest. Agriculture is primarily crucial and also the main source of our livelihood. But, owed to the scarceness of nutrients in plants, the human is strained to handle many dare in everyday life. The restoration of the nutrient is essential, in this view there is need to adopt precision agriculture system which change crop related plans and regulations, whereas nutrient management is a major domain that is needed to be spotlight in the field of farming techniques. The main aim of this research is to create an idea of developing a precision based recommender system for nutrient management and the main scope of this paper to describe the initial phase of the research. The experimental study of this research work is conducted using a terrace garden. The nutrient management with respect to the horticulture crop tomato is considered as the objective. The samples are grouped as two sets namely A and B representing samples without using natural fertilizers/manures and with natural fertilizers/manures. The growth parameters are analyzed and the results are presented. The data collection phase using sensors and Arduino kit is described here. The impact of pests and the remedy taken during the period of growth is recorded. The advices from the experts given in the soil tests are considered for preparing this nutrient management system.

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“…Morphological operations are used to remove the unwanted elements in the classified image [11]. Shradha Verma-2018 et.al, presented a survey on the current techniques and prediction models, based on Image processing and the role of Internet of Things (IoT), being applied for identification, detection as well as quantification of Tomato plant diseases [12]. Muhammad Danish Gondal-2015 et.al, proposed Computer vision techniques provide effective ways for analyzing the images of leaves.…”

Section: Introductionmentioning

confidence: 99%

Pest Detection in Crop using Video and Image Processing

Chodey¹

2020

IJRASET

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Detection of pests of various species is one of the compelling tasks in pest management involving detection and classification which is much more difficult than common object detection because of the apparent differences among pest species. Early diagnosis of pest is more essential to enhance the production of healthy crops as well as to diminish the economic loss. However, one major challenge is the difficulty in determining the physical, chemical, and biological changes in plants during the asymptomatic stages of an infection. To overcome these challenge, a huge count of traditional techniques were formulated. Many algorithms were introduced to detect the pests from leaves. Such techniques are not efficient for all the types of pest. To overcome the above said problem, this paper deals with pest detection, identification using segmentation and classification algorithms.

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Prediction Models for Identification and Diagnosis of Tomato Plant Diseases

Cited by 44 publications

References 19 publications

Precision Data Acquisition and Analysis for Nutrient Management of Tomatoes

Precision Data Acquisition and Analysis for Nutrient Management of Tomatoes

Recommender System for Nutrient Management Based on Precision Agriculture

Pest Detection in Crop using Video and Image Processing

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