scholarly journals Leaf Disease Detection

2021 ◽  
Vol 9 (VII) ◽  
pp. 3324-3329
Author(s):  
Shivangi Singh
Keyword(s):  
Developing Countries ◽  
Agricultural Production ◽  
Large Scale ◽  
Plant Diseases ◽  
Technical Knowledge ◽  
Plant Leaves ◽  
Employment Opportunities ◽  
Leaf Disease ◽  
Village People ◽  
The Many

Agriculture is a key source of livelihood. Agriculture provides employment opportunities for village people on a large scale in developing countries like India. India's agriculture consists of the many crops and consistent with survey nearly 70% population is depends on agriculture. Most of Indian farmers are adopting manual cultivation thanks to lagging of technical knowledge. Farmers are unaware of what quite crops that grows well on their land. When plants are suffering from heterogeneous diseases through their leaves which will effect on the production of agriculture and profitable loss, also reduction in both quality and quantity of agricultural production. Leaves are important for fast growing of plant and to extend production of crops. Identifying diseases in plant leaves is challenging for farmers and also for researchers. Currently farmers are spraying pesticides to the plants but it affects humans directly or indirectly by health or also economically. To detect these plant diseases many fast techniques got to be adopt. In this paper, we have done surveys on different leaf diseases and various advanced techniques to detect these diseases. As said by Mahatma Gandhi, "Agriculture is the backbone of the Indian Economy". Hence the detection of leaf diseases is an important aspect in increasing the yield of a crop. By detecting the leaf disease farmer can increase the crop yield which leads in growth of country’s economy.

scholarly journals Plant leaf Damage Detection using Segmentation

2019 ◽  
Vol 9 (2S3) ◽  
pp. 238-243
Keyword(s):  
Agricultural Production ◽  
Primary Source ◽  
Plant Diseases ◽  
Leaf Damage ◽  
Agricultural System ◽  
Technical Knowledge ◽  
Plant Leaves ◽  
Employment Opportunities ◽  
Plant Leaf ◽  
Advanced Technologies

A primary source of livelihood is agriculture. In developing country like India, wide-ranging employment opportunities are provided by Agriculture for the villagers. Various crops are included in the agricultural system of India and 70% of the population depends upon agriculture as reported by survey. Because of lagging in technical knowledge, manual cultivation is adopted by majority of the Indian farmers. The kind of crops that grows well on their land is unaware by the farmers. The agriculture production is affected by the heterogeneous diseases that affect the plant leaves and result in the productive loss. Moreover, the quality as well as quantity of the agricultural production is reduced by it. A key role is played by the leaves in the rapid growth of the plants and production of crops. The identification of diseases related to plant leaf is a difficult task for the farmers and for the researchers. At present, various pesticides were sprayed on the plants that directly or indirectly affect the human health and the economy. Various methods must be adopted for detecting these kinds of plant diseases. This paper presents a review of various plant diseases and several advanced technologies in detecting the diseases.

scholarly journals A Chaotic Salp Swarm Feature Selection Algorithm for Apple and Tomato Plant Leaf Disease Detection

2021 ◽  
Vol 10 (5) ◽  
pp. 3037-3045
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Detection System ◽  
Plant Diseases ◽  
Healthy Plant ◽  
Disease Detection ◽  
Test Accuracy ◽  
Plant Leaves ◽  
Leaf Disease ◽  
Deep Learning Network

Plants are seen as vital because they provide mankind with energy. Plant diseases can harm the leaf at any time between planting and harvesting, resulting in enormous losses in crop output and market value. A leaf disease detection system acts asignificant role in agricultural production. A large amount of labour is required for this process as well as an in-depth understanding of plant diseases. Determining the presence of illnesses in plant leaves requires the use of deep learning and machine learning methods, which classify the data based on a specified set. In this paper, apple and tomato leaves disease detection process is carried out by Chaotic Salp Swarm algorithm (CSSA) followed by Bi-directional Long Short Term Memory (Bi-LSTM) technique for classification. We've used the Bi-LSTM architecture to sense disease in tomato and apple leaves in studies. In order to determine the type of leaves, we trained a deep learning network using the PlantVillage dataset of damaged and healthy plant leaves. It is estimated that the trained model achieves a test accuracy of 96%.

scholarly journals Development of durian leaf disease detection on Android device

2021 ◽  
Vol 11 (6) ◽  
pp. 4962
Author(s):  
A. L. Sabarre ◽  
A. S. Navidad ◽  
D. S. Torbela ◽  
J. J. Adtoon
Keyword(s):  
Visual Processing ◽  
Large Scale ◽  
Smallholder Farmers ◽  
Economic Loss ◽  
The Philippines ◽  
Mobile App ◽  
Plant Diseases ◽  
Disease Detection ◽  
Agricultural Industry ◽  
Leaf Disease

<span lang="EN-US">Durian is exceedingly abundant in the Philippines, providing incomes for smallholder farmers. But amidst these things, durian is still vulnerable to different plant diseases that can cause significant economic loss in the agricultural industry. The conventional way of dealing plant disease detection is through naked-eye observation done by experts. To control such diseases using the old method is extensively laborious, time-consuming and costly especially in dealing with large fields. Hence, the proponent’s objective of this study is to create a standalone mobile app for durian leaf disease detection using the transfer learning approach. In this approach, the chosen network MobileNets, is pre-trained with a large scale of general datasets namely ImageNet to effective function as a generic template for visual processing. The pre-trained network transfers all the learned parameters and set as a feature extractor for the target task to be executed. Four health conditions are addressed in this study, 10 per classification with a total of 40 samples tested to evaluate the accuracy of the system. The result showed 90% in overall accuracy for detecting algalspot, cercospora, leaf discoloration and healthy leaf.</span>

AGRICULTURAL PRODUCTION OF CA DONG PEOPLE IN RESETTLEMENT AREA OF TRANH RIVER HYDROPOWER NUMBER 2: CURRENT SITUATION AND IMPACT FACTORS

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Bùi Thị Bích Lan
Keyword(s):  
Social Relations ◽  
Agricultural Production ◽  
Large Scale ◽  
Transition Process ◽  
Impact Factors ◽  
Small Scale ◽  
Scale Production ◽  
Technical Application ◽  
Production Models ◽  
Role Of The State

In Vietnam, the construction of hydropower projects has contributed significantly in the cause of industrialization and modernization of the country. The place where hydropower projects are built is mostly inhabited by ethnic minorities - communities that rely primarily on land, a very important source of livelihood security. In the context of the lack of common productive land in resettlement areas, the orientation for agricultural production is to promote indigenous knowledge combined with increasing scientific and technical application; shifting from small-scale production practices to large-scale commodity production. However, the research results of this article show that many obstacles in the transition process are being posed such as limitations on natural resources, traditional production thinking or the suitability and effectiveness of scientific - technical application models. When agricultural production does not ensure food security, a number of implications for people’s lives are increasingly evident, such as poverty, preserving cultural identity, social relations and resource protection. Since then, it has set the role of the State in researching and building appropriate agricultural production models to exploit local strengths and ensure sustainability.

Integration of Ecological and Engineering Aspects in Planning Large Scale Tidal Power Development in the Bay of Fundy, Canada

1984 ◽  
Vol 16 (1-2) ◽  
pp. 281-295 ◽  
Author(s):  
Donald C Gordon
Keyword(s):  
Large Scale ◽  
Feasibility Studies ◽  
Bay Of Fundy ◽  
Final Decision ◽  
Power Development ◽  
Tidal Power ◽  
History Of ◽  
Scientists And Engineers ◽  
The Many ◽  
University Scientists

Large-scale tidal power development in the Bay of Fundy has been given serious consideration for over 60 years. There has been a long history of productive interaction between environmental scientists and engineers durinn the many feasibility studies undertaken. Up until recently, tidal power proposals were dropped on economic grounds. However, large-scale development in the upper reaches of the Bay of Fundy now appears to be economically viable and a pre-commitment design program is highly likely in the near future. A large number of basic scientific research studies have been and are being conducted by government and university scientists. Likely environmental impacts have been examined by scientists and engineers together in a preliminary fashion on several occasions. A full environmental assessment will be conducted before a final decision is made and the results will definately influence the outcome.

scholarly journals A Novel Unsupervised Classification Method for Sandy Land Using Fully Polarimetric SAR Data

2021 ◽  
Vol 13 (3) ◽  
pp. 355
Author(s):  
Weixian Tan ◽  
Borong Sun ◽  
Chenyu Xiao ◽  
Pingping Huang ◽  
Wei Xu ◽  
...  
Keyword(s):  
Spectral Clustering ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Feature Vector ◽  
Unsupervised Classification ◽  
Classification Method ◽  
Sandy Land ◽  
Classification Methods ◽  
The Many ◽  
Representative Points

Classification based on polarimetric synthetic aperture radar (PolSAR) images is an emerging technology, and recent years have seen the introduction of various classification methods that have been proven to be effective to identify typical features of many terrain types. Among the many regions of the study, the Hunshandake Sandy Land in Inner Mongolia, China stands out for its vast area of sandy land, variety of ground objects, and intricate structure, with more irregular characteristics than conventional land cover. Accounting for the particular surface features of the Hunshandake Sandy Land, an unsupervised classification method based on new decomposition and large-scale spectral clustering with superpixels (ND-LSC) is proposed in this study. Firstly, the polarization scattering parameters are extracted through a new decomposition, rather than other decomposition approaches, which gives rise to more accurate feature vector estimate. Secondly, a large-scale spectral clustering is applied as appropriate to meet the massive land and complex terrain. More specifically, this involves a beginning sub-step of superpixels generation via the Adaptive Simple Linear Iterative Clustering (ASLIC) algorithm when the feature vector combined with the spatial coordinate information are employed as input, and subsequently a sub-step of representative points selection as well as bipartite graph formation, followed by the spectral clustering algorithm to complete the classification task. Finally, testing and analysis are conducted on the RADARSAT-2 fully PolSAR dataset acquired over the Hunshandake Sandy Land in 2016. Both qualitative and quantitative experiments compared with several classification methods are conducted to show that proposed method can significantly improve performance on classification.

scholarly journals Strategic deployment of riparian buffers and windbreaks in Europe can co-deliver biomass and environmental benefits

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Oskar Englund ◽  
Pål Börjesson ◽  
Blas Mola-Yudego ◽  
Göran Berndes ◽  
Ioannis Dimitriou ◽  
...  
Keyword(s):  
Agricultural Production ◽  
Large Scale ◽  
Production Systems ◽  
Riparian Buffers ◽  
Environmental Benefits ◽  
The European Union ◽  
Negative Effects ◽  
Nitrogen Emissions ◽  
Environmental Objectives ◽  
Eu Policies

AbstractWithin the scope of the new Common Agricultural Policy of the European Union, in coherence with other EU policies, new incentives are developed for farmers to deploy practices that are beneficial for climate, water, soil, air, and biodiversity. Such practices include establishment of multifunctional biomass production systems, designed to reduce environmental impacts while providing biomass for food, feed, bioenergy, and other biobased products. Here, we model three scenarios of large-scale deployment for two such systems, riparian buffers and windbreaks, across over 81,000 landscapes in Europe, and quantify the corresponding areas, biomass output, and environmental benefits. The results show that these systems can effectively reduce nitrogen emissions to water and soil loss by wind erosion, while simultaneously providing substantial environmental co-benefits, having limited negative effects on current agricultural production. This kind of beneficial land-use change using strategic perennialization is important for meeting environmental objectives while advancing towards a sustainable bioeconomy.

scholarly journals Grounding semantic transparency in context

Morphology ◽  
2021 ◽  
Author(s):  
Rossella Varvara ◽  
Gabriella Lapesa ◽  
Sebastian Padó
Keyword(s):  
Large Scale ◽  
Point Of View ◽  
Distributional Semantics ◽  
Semantic Transparency ◽  
Inclusion Measure ◽  
The Difference ◽  
Semantic Point ◽  
The Many ◽  
The Relationship

AbstractWe present the results of a large-scale corpus-based comparison of two German event nominalization patterns: deverbal nouns in -ung (e.g., die Evaluierung, ‘the evaluation’) and nominal infinitives (e.g., das Evaluieren, ‘the evaluating’). Among the many available event nominalization patterns for German, we selected these two because they are both highly productive and challenging from the semantic point of view. Both patterns are known to keep a tight relation with the event denoted by the base verb, but with different nuances. Our study targets a better understanding of the differences in their semantic import.The key notion of our comparison is that of semantic transparency, and we propose a usage-based characterization of the relationship between derived nominals and their bases. Using methods from distributional semantics, we bring to bear two concrete measures of transparency which highlight different nuances: the first one, cosine, detects nominalizations which are semantically similar to their bases; the second one, distributional inclusion, detects nominalizations which are used in a subset of the contexts of the base verb. We find that only the inclusion measure helps in characterizing the difference between the two types of nominalizations, in relation with the traditionally considered variable of relative frequency (Hay, 2001). Finally, the distributional analysis allows us to frame our comparison in the broader coordinates of the inflection vs. derivation cline.

Toolkit for Epidemiologic Response to an Acute Chemical Release

2016 ◽  
Vol 10 (4) ◽  
pp. 631-632 ◽  
Author(s):  
Mary Anne Duncan ◽  
Maureen F. Orr
Keyword(s):  
Public Health ◽  
Large Scale ◽  
Technical Assistance ◽  
Local Health ◽  
Toxic Substances ◽  
Public Health Action ◽  
Public Health Agencies ◽  
Chemical Release ◽  
State And Local ◽  
The Many

AbstractWhen a large chemical incident occurs and people are injured, public health agencies need to be able to provide guidance and respond to questions from the public, the media, and public officials. Because of this urgent need for information to support appropriate public health action, the Agency for Toxic Substances and Disease Registry (ATSDR) of the US Department of Health and Human Services has developed the Assessment of Chemical Exposures (ACE) Toolkit. The ACE Toolkit, available on the ATSDR website, offers materials including surveys, consent forms, databases, and training materials that state and local health personnel can use to rapidly conduct an epidemiologic investigation after a large-scale acute chemical release. All materials are readily adaptable to the many different chemical incident scenarios that may occur and the data needs of the responding agency. An expert ACE team is available to provide technical assistance on site or remotely. (Disaster Med Public Health Preparedness. 2016;10:631–632)

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