Advances in Plant Virus/Viroid Detection and Identification Methods
A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "Viruses of Plants, Fungi and Protozoa".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 139
Special Issue Editors
Interests: plant virus detection and identification; virus–vector–plant interactions
Special Issues, Collections and Topics in MDPI journals
Interests: viral disease in horticultural and ornamental crops; diagnostic techniques (serological and molecular); validation of protocols; participation to test performance study and proficiency tests
Interests: plant virology; tobamovirus; tomato viruses; TPS and PT planning and joining; protocol validation; molecular diagnosis
Interests: plant virus/viroid detection and identification; disease etiology
Special Issue Information
Dear Colleagues,
Plant viruses and viroids cause serious crop losses and thus are of global economic importance. Once a virus/viroid is established in a field, it can spread, thus becoming difficult to control. Several factors including international trade and climate change increase the spread of emerging viruses and viroids. To prevent or limit the damage caused by viruses and viroids, a prompt response by developing accurate, reliable, and rapid diagnostic methods is required not only for new viruses/viroids but also new variants of known ones.
There has been an increase in the number of polymerase chain reaction (PCR)-based detection protocols such as real-time PCR and loop-mediated isothermal amplification (LAMP). In addition, the use of high-throughput sequencing (HTS) and bioinformatic tools has been increasing for the identification and characterization of disease-causing agents, allowing the discovery of many new viruses. Digital droplet PCR enables the more precise quantification of viral nucleic acids with high sensitivity, allowing researchers to accurately monitor and manage viral infections. Moreover, other methods such as biosensors and CRISPR-Cas can play a crucial role by enabling rapid and accurate detection. Additionally, the combination of hyperspectral imaging and machine learning (ML) offers detailed spectral information on the changes in plant physiology and structure caused by virus infections, enabling early detection. Utilizing such advanced methods will revolutionize agricultural practices by providing more accurate, faster, and high-throughput techniques, enhancing our ability to monitor and manage infections.
The purpose of this Special Issue is to collect original research and methodology articles, reviews, and short communications on the latest advances in the different aspects of plant virus detection, identification, and characterization methods using modern and advanced technologies including PCR-based methods, biosensors, CRISPR-Cas, HTS, bioinformatics, imaging, and ML.
Dr. Yahya Z. A. Gaafar
Dr. Laura Tomassoli
Dr. Antonio Tiberini
Dr. Harvinder Bennypaul
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. Viruses 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
- plant viruses and viroids diagnostics
- high-throughput sequencing
- bioinformatics
- virus taxonomy
- virus/viroid–plant–vector interactions
- real-time PCR
- digital droplet PCR
- hyperspectral imaging
- machine learning
- artificial intelligence
- biosensors
