Peptic Ulcers and their Complications

Kumar, Akhilesh; Kumar, Dhanesh; Kumar, Ramesh; Prasad, Jhakeshwar; Kumar, Mohit; Joshi, Prachita; Fulzele, Pratiksha

doi:10.22270/jddt.v10i3-s.4082

Cited by 6 publications

(6 citation statements)

References 28 publications

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“…By leveraging deep learning techniques, such as CNNs, this system demonstrates the capability to improve agricultural practices by efficiently detecting and addressing crop diseases. Sandeep Kumar [3] proposed a system for Leaf Disease Detection and Classification based on Machine Learning, aiming to address the significant role of agriculture in the economy and the common occurrence of plant diseases, which profoundly affect agricultural productivity. In the agricultural sector, detecting infections in plants is crucial, as it helps in timely intervention to help the impact of diseases on crop yields.…”

Section: IImentioning

confidence: 99%

Leaf Disease Detection System

Kamble,

Gadale,

Pawar

et al. 2024

IJRASET

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The agricultural sector plays a crucial role in sustaining the world's growing population. However, the prevalence of plant leaf diseases can significantly impact crop yields and quality. This project leverages the power of deep learning techniques to develop an automated system for the early detection of plant leaf diseases. By utilizing a large dataset of annotated leaf images and state-of-the-art convolutional neural networks (CNNs), this research aims to accurately identify and classify various plant leaf diseases, including but not limited to fungal, bacterial, and viral infections. In this project, we propose an innovative approach to tackle this issue. Specifically, we utilize convolutional neural networks (CNNs) to analyze images of plant leaves and classify them into healthy or diseased categories. To ensure the robustness of our model, we curate an extensive dataset comprising images of various plant diseases and healthy leaves. This project stands to benefit the agriculture industry by offering a cost-effective, scalable, and timely solution for plant disease detection.

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Section: IImentioning

confidence: 99%

Leaf Disease Detection System

Kamble,

Gadale,

Pawar

et al. 2024

IJRASET

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“…Also, the paddy stubble finds its applicability in the bed material during the winter for the cattle and is a traditional, conventional and regular form of practice in India. This bedding material formed from the residues of paddy renders an improved ability of milking pertaining to quantity and quality thus contributing udder health and relaxed sleep for the cattle [36]. Moreover, it can be processed for the compost by alternative forms of methods through the applicability of microbial organism and amendments on the farm itself [37].…”

Section: Eco-friendly Management Of Paddy Crop Residuementioning

confidence: 99%

In-situ management of paddy stubble through microbial biodegradation

Sangwan

Deswal

2021

E3S Web Conf.

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After the harvest of crop, the disposal of the rice stubbles remains a notable area of interest in all the growing areas of rice. The present review paper explores and highlights an effective strategy of decomposing the decomposers of the paddy stubble. Due to the increasing production of rice, there is an increase in rice crop residues and stubbles production. Conventional methods of management of paddy involve burning, surface retention, mulching, bailing, incorporation/amalgamation and direct removal. However, there are certain environmental challenges by using available agricultural implements. Thus, this current study demonstrates strategic management of the paddy crop residue for a sustainable environment. The developed eco-friendly methods will render new dimensions for the application of the post harvested residues. The review paper will be significant for sustainable management of the wastes of the paddy crop and hence strategic decomposition method, which will be beneficial for the society, farmers as well as the environment

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“…destruction of fungal pathogen by action of lytic enzymes (e.g. chitinase and β-1,3-glucanase) and HCN that degrade fungal cell wall and uncharacterized antifungal factors [44,45]. Recent work on the broad spectrum of PGPR-mediated induced systemic resistance against different pathogens in different crops has gained importance.…”

Section: Integrated Disease Management (Idm)mentioning

confidence: 99%

Integrated Disease Management of Chickpea Fusarium Wilt

Kumar

2020

CJAST

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Chickpea (Cicer arietinum) is one of the world’s major legume crops and suffers substantial damage from wilt disease caused by Fusarium oxysporum f. sp. ciceri( Padwick) with yield loss over 60 per cent. It is an important soil borne plant pathogen and is difficult to manage by application of chemical pesticides. Moreover, the chemical control is costly and leads to residual effect. A plethora of reports indictes the efforts made to reduce environmental effects and rationalize the use of pesticides and manage the pathogen more effectively through Integration of Disease Management (IDM). Application of soil amendments and specific bio-control agents also incorporated in IDM which has potential to suppress soil-borne pathogens through manipulation of the physicochemical and microbiological environment. Therefore, IDM approach for controlling chickpea Fusarium wilt might be a cost effective and eco-friendly approach.

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Peptic Ulcers and their Complications

Cited by 6 publications

References 28 publications

Leaf Disease Detection System

Leaf Disease Detection System

In-situ management of paddy stubble through microbial biodegradation

Integrated Disease Management of Chickpea Fusarium Wilt

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