Science Heritage Journal | Galeri Warisan Sains (GWS)

MOLECULAR DIAGNOSTIC APPROACHES FOR PLANT PATHOGENS DETECTION AND DISEASE MANAGEMENT

September 18, 2020 Posted by din In GWS

ABSTRACT

MOLECULAR DIAGNOSTIC APPROACHES FOR PLANT PATHOGENS DETECTION AND DISEASE MANAGEMENT

Journal: Science Heritage Journal | Galeri Warisan Sains (GWS)
Author: Manoj Paudel, Kiran Parajuli, Sovit Parajuli, Sudip Regmi

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Doi: 10.26480/gws.01.2020.27.30

Every year huge crop losses occur due to different pathogens and disease. The traditional method of pathogen detection, which is still in practice, through visual examination is not always precise. Early detection of plant pathogens prior to severe infection is very crucial which is possible through molecular diagnostic approaches and nucleic acid-based tests. As the genetic materials are the ultimate information storage sites in living organism, their exploration through the use of nanotechnology provides the path forward for the three Ds of genomic analysis of pathogens: Diversity, Detection, and Disease diagnosis. Molecular detection method is not only precise and accurate but also faster and easier approach. Pathogen detection through PCR based tests, microarray technology, multiplexing, gene sequencing, genetic markers play a pivotal role in timely detection of causatives and take proper action to prevent the pandemic in plant population and safeguard against possible risks and famine. It is of utmost importance to prioritize such methods to detect plant pathogens, to increase our understanding of ecology and epidemiology and to prevent the spread of inoculum prior to disease spread. The application of novel diagnostic methods to inoculum detection will guide towards better understanding of the temporal and spatial dynamics of epidemic development, and open up new opportunities for disease forecasting and management.

Pages 27-30
Year 2020
Issue 1
Volume 4

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