Detection, Identification, and Control of Plant Pathogens
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Crop Protection, Diseases, Pests and Weeds".
Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 4488
Special Issue Editors
Interests: plant pathology; fungal and bacterial diseases; management of plant diseases; vegetable crops
2. Department of Plant Sciences, University of Manitoba, Winnipeg, MB, Canada
Interests: phytobacterial pathogens; bacterial taxonomy; molecular detection; genome-based identification; beneficial bacteria and biological control
Special Issue Information
Dear Colleagues,
Biotic diseases of agricultural crops cause significant yield losses of up to 16% globally, with potential negative impacts on food security. Due to global warming, coupled with high rainfall, diseases of important cultivated crops are predicted to increase as a result of new emerging and old re-emerging plant pathogens. Early detection, accurate identification, and predictive modeling are essential strategies for the mitigation of these biotic threats in agricultural cropping systems. Pathogen detection systems/tools generally lead to a reduced use of chemical pesticides with benefits to the environment and public health. Additionally, accurate identification of plant pathogens provides evidence-based technical advice for farmers/stakeholders, leading to the selection of effective control methods.
This Special Issue is aimed at innovative research dealing with detection, identification/characterization, predictive modeling, and control (biological/chemical) of plant pathogens, such as bacteria, fungi, viruses, phytoplasmas, and nematodes. Manuscripts of original research and review articles are encouraged. Studies of agronomic practices, with demonstrated direct effects on the prevalence, incidence, and/or severity of plant diseases, are within the scope of this issue. Finally, first disease reports will be considered, if the pathogen(s) is/are well characterized using a combination of classical and molecular methods, and Koch’s postulate is verified.
Dr. Bhabesh Dutta
Dr. James T. Tambong
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Molecular identification and detection
- Classical identification
- Plant pathogens
- Plant diseases
- Chemical pesticides
- Biological control
- Disease forecasts/modeling
- Genome-based identification of pathogens
- Pathogen characterization
