Science Heritage Journal (GWS) 4(1) (2020) 27-30 Quick Response Code Access this article online Website: www.jscienceheritage.com DOI: 10.26480/gws.01.2020.27.30 Cite the Article: Manoj Paudel, Kiran Parajuli, Sovit Parajuli, Sudip Regmi (2020). Molecular Diagnostic Approaches For Plant Pathogens Detection And Disease Management. Science Heritage Journal, 4(1): 27-30. ISSN: 2521-0858 (Print) ISSN: 2521-0866 (Online) CODEN: SHJCAS REVIEW ARTICLE Science Heritage Journal (GWS) DOI: http://doi.org/10.26480/gws.01.2020.27.30 MOLECULAR DIAGNOSTIC APPROACHES FOR PLANT PATHOGENS DETECTION AND DISEASE MANAGEMENT Manoj Paudel*, Kiran Parajuli, Sovit Parajuli, Sudip Regmi Agriculture and Forestry University, Chitwan, Nepal *Corresponding Author Email: mjpaudel@gmail.com This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ARTICLE DETAILS ABSTRACT Article History: Received 04 August 2020 Accepted 08 September 2020 Available Online 15 September 2020 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. KEYWORDS Pathogens, nucleic acid, genetic-marker, multiplexing, pandemic. 1. INTRODUCTION Various agricultural crops are being threatened by a wide variety of biotic stresses every year leading to decrease in production and reduction in quality of yield. About 42% of the world’s total agricultural crop is destroyed yearly by diseases and pests (Alvarez, 2004). Farmers often face one or more than one pest or disease and new pesticide-resistant pathogenic strains attacking the same crop. In plant science also, molecular diagnostic technologies can be adopted to identify the microorganisms, pathogens prevalent in plants as like that in medical sectors. With the automation of molecular data acquisition, we can monitor the pathogens and beneficial microorganisms prevalent in soil, air, and water. Mostly plant pathogens are identified through visual examination in a tradition way. This is often possible only after major damage has already been done to the crop. To save plants from irreparable damage by pathogens, we need to be able to identify an infection even before it becomes visible. Pathogens produce proteins and toxins to facilitate their infection, before disease symptoms appear. Many plant pathogens have similar morphological characters which makes it complex for their identification and are time consuming and requires extensive knowledge in taxonomy. Molecular detection techniques can generate accurate results rapidly enough to be useful for disease management. We need a synthesis of population genetics and epidemiology, resulting in a population biology which would increase the benefits of studying genetic variation in populations of plant pathogens. It is necessary to conduct extensive research in food and economic crops as they are major source for feeding this rapidly increasing population. Any pandemic or epidemic when occurred in those crops in course of time, will affect large world population. Many would go under famine. Late Blight of Potato that caused a famine in Ireland, in 1846, and the Downy Mildew of Grapes that almost caused economic ruin for the wine industry in the Mediterranean, beginning in 1865 are some cases of the devastating losses caused by pathogens. Technology is an essential component of any scientific endeavor. Computer modeling could be applied to systems analysis and improve disease management in plants. Technological advances in the late 1980s and 1990s led to the development of easily accessible genetic markers such as Restriction Fragment Length Polymorphism (RFLPs), Random Amplified Polymorphic DNA (RAPDs), Amplified Fragment Length Polymorphism (AFLPs), microsatellite (Milgroom, 2001). These molecules play vital role in the development of plant diagnostic kits. These kits are designed to detect plant diseases early, either by identifying the presence of the pathogen in the plant or the proteins produced by either the pathogen or the plant during infection. Using Real Time PCR, it is possible not only to detect the presence or absence of the target pathogen, but also possible to quantify the number of the pathogen in the sample. The polymerase chain reaction (PCR), the exponential amplification of a target DNA strand catalyzed by a thermo stable DNA polymerase has become the foundation of Nucleic Acid-based pathogen detection (Vincelli and