scholarly journals Sustainable agriculture and plant diseases: an epidemiological perspective

2007 ◽  
Vol 363 (1492) ◽  
pp. 741-759 ◽  
Author(s):  
Christopher A Gilligan
Keyword(s):  
Plant Disease ◽  
Plant Diseases ◽  
Control Measures ◽  
Social Constraints ◽  
Successful Implementation ◽  
Epidemiological Models ◽  
Modern Biology ◽  
New Approaches ◽  
Evolutionary Changes ◽  
Wide Range

The potential for modern biology to identify new sources for genetical, chemical and biological control of plant disease is remarkably high. Successful implementation of these methods within globally and locally changing agricultural environments demands new approaches to durable control. This, in turn, requires fusion of population genetics and epidemiology at a range of scales from the field to the landscape and even to continental deployment of control measures. It also requires an understanding of economic and social constraints that influence the deployment of control. Here I propose an epidemiological framework to model invasion, persistence and variability of epidemics that encompasses a wide range of scales and topologies through which disease spreads. By considering how to map control methods onto epidemiological parameters and variables, some new approaches towards optimizing the efficiency of control at the landscape scale are introduced. Epidemiological strategies to minimize the risks of failure of chemical and genetical control are presented and some consequences of heterogeneous selection pressures in time and space on the persistence and evolutionary changes of the pathogen population are discussed. Finally, some approaches towards embedding epidemiological models for the deployment of control in an economically plausible framework are presented.

scholarly journals Microbial antagonists against plant pathogens in Iran: A review

2020 ◽  
Vol 5 (1) ◽  
pp. 404-440 ◽  
Author(s):  
Mehrdad Alizadeh ◽  
Yalda Vasebi ◽  
Naser Safaie
Keyword(s):  
Biological Control ◽  
Chemical Control ◽  
Plant Disease ◽  
Plant Pathogens ◽  
Plant Diseases ◽  
Agricultural Products ◽  
Control Measures ◽  
Wide Range ◽  
Plant Disease Management ◽  
Published Research

AbstractThe purpose of this article was to give a comprehensive review of the published research works on biological control of different fungal, bacterial, and nematode plant diseases in Iran from 1992 to 2018. Plant pathogens cause economical loss in many agricultural products in Iran. In an attempt to prevent these serious losses, chemical control measures have usually been applied to reduce diseases in farms, gardens, and greenhouses. In recent decades, using the biological control against plant diseases has been considered as a beneficial and alternative method to chemical control due to its potential in integrated plant disease management as well as the increasing yield in an eco-friendly manner. Based on the reported studies, various species of Trichoderma, Pseudomonas, and Bacillus were the most common biocontrol agents with the ability to control the wide range of plant pathogens in Iran from lab to the greenhouse and field conditions.

scholarly journals Epidemiology: Past, Present, and Future Impacts on Understanding Disease Dynamics and Improving Plant Disease Management—A Summary of Focus Issue Articles

2017 ◽  
Vol 107 (10) ◽  
pp. 1092-1094 ◽  
Author(s):  
P. S. Ojiambo ◽  
J. Yuen ◽  
F. van den Bosch ◽  
L. V. Madden
Keyword(s):  
Population Biology ◽  
Large Scale ◽  
Plant Disease ◽  
Spatial Scales ◽  
Rapid Development ◽  
Plant Diseases ◽  
Disease Spread ◽  
Disease Assessment ◽  
Wide Range ◽  
Disease Epidemics

Epidemiology has made significant contributions to plant pathology by elucidating the general principles underlying the development of disease epidemics. This has resulted in a greatly improved theoretical and empirical understanding of the dynamics of disease epidemics in time and space, predictions of disease outbreaks or the need for disease control in real-time basis, and tactical and strategic solutions to disease problems. Availability of high-resolution experimental data at multiple temporal and spatial scales has now provided a platform to test and validate theories on the spread of diseases at a wide range of spatial scales ranging from the local to the landscape level. Relatively new approaches in plant disease epidemiology, ranging from network to information theory, coupled with the availability of large-scale datasets and the rapid development of computer technology, are leading to revolutionary thinking about epidemics that can result in considerable improvement of strategic and tactical decision making in the control and management of plant diseases. Methods that were previously restricted to topics such as population biology or evolution are now being employed in epidemiology to enable a better understanding of the forces that drive the development of plant disease epidemics in space and time. This Focus Issue of Phytopathology features research articles that address broad themes in epidemiology including social and political consequences of disease epidemics, decision theory and support, pathogen dispersal and disease spread, disease assessment and pathogen biology and disease resistance. It is important to emphasize that these articles are just a sample of the types of research projects that are relevant to epidemiology. Below, we provide a succinct summary of the articles that are published in this Focus Issue .

scholarly journals Attention-Based Recurrent Neural Network for Plant Disease Classification

2020 ◽  
Vol 11 ◽  
Author(s):  
Sue Han Lee ◽  
Hervé Goëau ◽  
Pierre Bonnet ◽  
Alexis Joly
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Plant Disease ◽  
Effective Means ◽  
Plant Diseases ◽  
Control Measures ◽  
Disease Classification ◽  
Effective Control ◽  
Healthy Plant ◽  
Major Interest

Plant diseases have a significant impact on global food security and the world's agricultural economy. Their early detection and classification increase the chances of setting up effective control measures, which is why the search for automatic systems that allow this is of major interest to our society. Several recent studies have reported promising results in the classification of plant diseases from RGB images on the basis of Convolutional Neural Networks (CNN). These studies have been successfully experimented on a large number of crops and symptoms, and they have shown significant advantages in the support of human expertise. However, the CNN models still have limitations. In particular, CNN models do not necessarily focus on the visible parts affected by a plant disease to allow their classification, and they can sometimes take into account irrelevant backgrounds or healthy plant parts. In this paper, we therefore develop a new technique based on a Recurrent Neural Network (RNN) to automatically locate infected regions and extract relevant features for disease classification. We show experimentally that our RNN-based approach is more robust and has a greater ability to generalize to unseen infected crop species as well as to different plant disease domain images compared to classical CNN approaches. We also analyze the focus of attention as learned by our RNN and show that our approach is capable of accurately locating infectious diseases in plants. Our approach, which has been tested on a large number of plant species, should thus contribute to the development of more effective means of detecting and classifying crop pathogens in the near future.

IMPROVEMENT OF INNOVATIVE ACTIVITY OF THE ENTERPRISE

2017 ◽  
Author(s):  
Nataliya Stoyanets ◽  
◽  
Mathias Onuh Aboyi ◽  
Keyword(s):  
Value Chain ◽  
Net Present Value ◽  
Successful Implementation ◽  
Innovative Development ◽  
Technological Equipment ◽  
Alliance Partner ◽  
Innovation Potential ◽  
Wide Range ◽  
Technological Platform ◽  
The Cost

The article defines that for the successful implementation of an innovative project and the introduction of a new product into production it is necessary to use advanced technologies and modern software, which is an integral part of successful innovation by taking into account the life cycle of innovations. It is proposed to consider the general potential of the enterprise through its main components, namely: production and technological, scientific and technical, financial and economic, personnel and actual innovation potential. Base for the introduction of technological innovations LLC "ALLIANCE- PARTNER", which provides a wide range of support and consulting services, services in the employment market, tourism, insurance, translation and more. To form a model of innovative development of the enterprise, it is advisable to establish the following key aspects: the system of value creation through the model of cooperation with partners and suppliers; creating a value chain; technological platform; infrastructure, determine the cost of supply, the cost of activities for customers and for the enterprise as a whole. The system of factors of influence on formation of model of strategic innovative development of the enterprise is offered. The expediency of the cost of the complex of technological equipment, which is 6800.0 thousand UAH, is economically calculated. Given the fact that the company plans to receive funds under the program of socio-economic development of Sumy region, the evaluation of the effectiveness of the innovation project, the purchase of technological equipment, it is determined that the payback period of the project is 3 years 10 months. In terms of net present value (NPV), the project under study is profitable. The project profitability index (PI) meets the requirements for a positive decision on project implementation> 1.0. The internal rate of return of the project (IRR) also has a positive value of 22% because it exceeds the discount rate.

COVID-19 Outbreak Prediction with Machine Learning

2020 ◽  
Author(s):  
Sina Faizollahzadeh Ardabili ◽  
Amir Mosavi ◽  
Pedram Ghamisi ◽  
Filip Ferdinand ◽  
Annamaria R. Varkonyi-Koczy ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Fuzzy Inference ◽  
Control Measures ◽  
Future Research ◽  
Complex Nature ◽  
Inference System ◽  
Wide Range ◽  
Standard Models ◽  
High Level

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

NEW APPROACHES TO THE ORGANIZATIONAL AND TECHNICAL SUPPORT OF THE EXAMINATION OF COMPETITIVE APPLICATIONS FOR STATE SUPPORT IN THE FORM OF GRANTS OF THE PRESIDENT OF THE RUSSIAN FEDERATION TO YOUNG RUSSIAN SCIENTISTS – DOCTORS OF SCIENCES AND PHILOSOPHY DOCTORS (DOCTORS AND Ph. D.) AND LEADING SCIENTIFIC SCHOOLS

2020 ◽  
pp. 59-67
Author(s):  
N.A. Mironov ◽  
E.A. Maryshev ◽  
N.A. Divueva
Keyword(s):  
Information System ◽  
Russian Federation ◽  
Technical Support ◽  
Examination System ◽  
State Support ◽  
New Approaches ◽  
Wide Range ◽  
Integrated Information System ◽  
The Russian Federation ◽  
Integrated Information

The article discusses the issues of improving the examination system of competitive applications for state support in the form of grants of the President of the Russian Federation on the basis of an integrated information system that includes the information support system of the Grants Council of the President of the Russian Federation and the information system of the Federal Roster of Scientific and Technological Experts and containing information about experts, applications and expert examination results. In order to improve the principles of transparency and openness of support programs and competition winners, to ensure the objectivity of the competitive selection of projects, a number of organizational and technical solutions are proposed in the application examination system based on an integrated information system. The new and proposed new approaches to the organizational and technical support of the examination of competitive applications for state support in the form of grants of the President of the Russian Federation to young Russian scientists made it possible, by attracting a wide range of scientific and technological communities, to conduct examination of more than five thousand applications with high quality and deadlines set by the Ministry of Education and Science of Russia.

scholarly journals Trends in Molecular Diagnosis and Diversity Studies for Phytosanitary Regulated Xanthomonas

2021 ◽  
Vol 9 (4) ◽  
pp. 862
Author(s):  
Vittoria Catara ◽  
Jaime Cubero ◽  
Joël F. Pothier ◽  
Eran Bosis ◽  
Claude Bragard ◽  
...  
Keyword(s):  
Molecular Diagnosis ◽  
Bacterial Species ◽  
Management Strategies ◽  
Diagnostic Methods ◽  
Plant Diseases ◽  
Wild Plants ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Wide Range ◽  
Diversity Studies

Bacteria in the genus Xanthomonas infect a wide range of crops and wild plants, with most species responsible for plant diseases that have a global economic and environmental impact on the seed, plant, and food trade. Infections by Xanthomonas spp. cause a wide variety of non-specific symptoms, making their identification difficult. The coexistence of phylogenetically close strains, but drastically different in their phenotype, poses an added challenge to diagnosis. Data on future climate change scenarios predict an increase in the severity of epidemics and a geographical expansion of pathogens, increasing pressure on plant health services. In this context, the effectiveness of integrated disease management strategies strongly depends on the availability of rapid, sensitive, and specific diagnostic methods. The accumulation of genomic information in recent years has facilitated the identification of new DNA markers, a cornerstone for the development of more sensitive and specific methods. Nevertheless, the challenges that the taxonomic complexity of this genus represents in terms of diagnosis together with the fact that within the same bacterial species, groups of strains may interact with distinct host species demonstrate that there is still a long way to go. In this review, we describe and discuss the current molecular-based methods for the diagnosis and detection of regulated Xanthomonas, taxonomic and diversity studies in Xanthomonas and genomic approaches for molecular diagnosis.

Occupational hazard in Malaysian traffic police: special focus on air pollutants

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Putri Anis Syahira Mohamad Jamil ◽  
Karmegam Karuppiah ◽  
Irniza Rasdi ◽  
Vivien How ◽  
Shamsul Bahri Mohd Tamrin ◽  
...  
Keyword(s):  
Occupational Injuries ◽  
Indicator System ◽  
Control Measures ◽  
Special Focus ◽  
Safety Measures ◽  
Traffic Police ◽  
Wide Range ◽  
And Control ◽  
Risk Occupation ◽  
High Risk Occupation

Abstract This paper provides a specific deliberation on occupational hazards confronted daily by Malaysian Traffic Police. Traffic police is a high-risk occupation that involves a wide range of tasks and, indirectly, faced with an equally wide variety of hazards at work namely, physical, biological, psychosocial, chemical, and ergonomic hazards. Thereupon, occupational injuries, diseases, and even death are common in the field. The objective of this paper is to collate and explain the major hazards of working as Malaysian traffic police especially in Point Duty Unit, their health effects, and control measures. There are many ways in which these hazards can be minimised by ensuring that sufficient safety measures are taken such as a wireless outdoor individual exposure indicator system for the traffic police. By having this system, air monitoring among traffic police may potentially be easier and accurate. Other methods of mitigating these unfortunate events are incorporated and addressed in this paper according to the duty and needs of traffic police.

scholarly journals Agro-Nanotechnology as an Emerging Field: A Novel Sustainable Approach for Improving Plant Growth by Reducing Biotic Stress

2021 ◽  
Vol 11 (5) ◽  
pp. 2282
Author(s):  
Masudulla Khan ◽  
Azhar U. Khan ◽  
Mohd Abul Hasan ◽  
Krishna Kumar Yadav ◽  
Marina M. C. Pinto ◽  
...  
Keyword(s):  
Plant Growth ◽  
Crop Yield ◽  
Biotic Stress ◽  
Crop Production ◽  
Plant Disease ◽  
Yield Loss ◽  
Growth Parameters ◽  
Plant Diseases ◽  
High Yield ◽  
Plant Disease Management

In the present era, the global need for food is increasing rapidly; nanomaterials are a useful tool for improving crop production and yield. The application of nanomaterials can improve plant growth parameters. Biotic stress is induced by many microbes in crops and causes disease and high yield loss. Every year, approximately 20–40% of crop yield is lost due to plant diseases caused by various pests and pathogens. Current plant disease or biotic stress management mainly relies on toxic fungicides and pesticides that are potentially harmful to the environment. Nanotechnology emerged as an alternative for the sustainable and eco-friendly management of biotic stress induced by pests and pathogens on crops. In this review article, we assess the role and impact of different nanoparticles in plant disease management, and this review explores the direction in which nanoparticles can be utilized for improving plant growth and crop yield.

scholarly journals Non-Invasive Identification of Nutrient Components in Grain

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3124
Author(s):  
Charles Farber ◽  
A. S. M. Faridul Islam ◽  
Endang M. Septiningsih ◽  
Michael J. Thomson ◽  
Dmitry Kurouski
Keyword(s):  
Rice Variety ◽  
Nutrient Content ◽  
Plant Diseases ◽  
Variety Identification ◽  
Successful Implementation ◽  
Label Free ◽  
Accurate Identification ◽  
Analytical Technique ◽  
Non Invasive ◽  
Digital Farming

Digital farming is a modern agricultural concept that aims to maximize the crop yield while simultaneously minimizing the environmental impact of farming. Successful implementation of digital farming requires development of sensors to detect and identify diseases and abiotic stresses in plants, as well as to probe the nutrient content of seeds and identify plant varieties. Experimental evidence of the suitability of Raman spectroscopy (RS) for confirmatory diagnostics of plant diseases was previously provided by our team and other research groups. In this study, we investigate the potential use of RS as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of nutrient components in the grains from 15 different rice genotypes. We demonstrate that spectroscopic analysis of intact rice seeds provides the accurate rice variety identification in ~86% of samples. These results suggest that RS can be used for fully automated, fast and accurate identification of seeds nutrient components.

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