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Article . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
ZENODO
Article . 2023
License: CC BY
Data sources: Datacite
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Diagnostic Techniques For Early Detection Of Phytoplasma Diseases

Authors: Naofel Aljafer; Hail Rihan;

Diagnostic Techniques For Early Detection Of Phytoplasma Diseases

Abstract

Phytoplasmas are a type of bacteria, specifically belonging to the group of Mollicutes, characterized by their lack of cell walls and inability to be cultured in lab settings. They pose a significant threat to various plant species, both wild and cultivated, spanning across different plant families. This wide-ranging infection results in substantial agricultural losses and economically devastating global epidemics. Phytoplasmas are known to infect crucial crops such as fruit trees, annual crops, palms and grapevines. Therefore, controlling these diseases has become a top priority, with the first crucial step being accurate and efficient diagnosis of phytoplasma infections. Identifying phytoplasmas presents a formidable challenge due to their uneven distribution within afflicted plants and their low concentration in infected plant tissues. Over the past few decades, a significant portion of research devoted to phytoplasma detection has leaned on nucleic acid-based methods, notably PCR (Polymerase Chain Reaction). PCR is used to amplify specific sections of phytoplasma genomes found within infected plants. However, standard diagnostic practices have transitioned from traditional PCR to real-time PCR. This shift is primarily attributed to its heightened sensitivity and the reduced risk of contamination, thanks to the utilization of a sealed detection system. Furthermore, this technique can be adapted for semi-quantitative analysis. Keyworks : Phytoplamas Diseases, Diagnostic Techniques, 16S Ribosomal RNA, LAMP.

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Keywords

diagnostic techniques, Science, Q, 16s ribosomal rna, phytoplamas diseases

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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