Innovative Strategies for Enhancing Crop Resilience Against Plant Viral Diseases-Pathogen Detection from Matatranscriptome to Artificial Intelligence

Chellappan Padmanabhan ^*

• Plant Pathogen Confirmatory Diagnostics Laboratory, USDA APHIS PPQ Science and Technology, Laurel, Maryland, United States

Artificial intelligence (AI): AI for pathogen detection is still in its early stages, and two research articles utilizing the YOLOv4 and PDLM-TK algorithm have elegantly described AI-based pathogen detection of plant leaf diseases. To enhance disease prediction systems in agriculture, a large number of images of healthy and diseased leaves from 14 species from the plant village dataset were utilized. The YOLOv4 has revealed high performance with high accuracy on the Plant Village dataset, including precision, recall, and F1-score. These findings showed YOLOv4 as an effective tool for accurate disease identification, highlighting significant advancements in plant disease detection Aldakheel et One of the research articles presented the application of the meta-transcriptome approach, which revealed the identification of virome associated with sugar beets. In addition to detecting known viruses infecting sugar beet, this study identified the spread of the beta vulgaris satellite virus in new locations, indicating their geographical expansion. In addition, a novel virus, the Erysiphe necator-associated abispo virus, was identified across all libraries and originated from different sugar beet growing locations in the United States Chinnadurai et al. Virus-pathogenesis: Currently, the Tomato leaf curl New Delhi virus (ToLCNDV) is recognized as a significant viral pathogen and provides a threat to tomato, pepper, and cucurbit crops across the world.In this study, coat protein swapping identified a single amino acid in the coat protein coding sequence ToLCNDV as the pathogenicity factor associated with virus infection in tomatoes. This research identified a critical molecular factor that can be used for future breeding for resistance against ToLCNDV Vo et al.Strawberry mottle mosaic virus (SMoV) impacts strawberry productivity.In this article, the authors have identified two silencing suppressors, Pro2Glu and P28, from SMoV.Further, Pro2Glu and P28 were found to have a role in increasing the accumulation of potato virus X.This study has implications for formulating strategies to control viral diseases in strawberries and other crops Fan et al.One of the articles presents the prevalence and transmission dynamics of black raspberry necrosis virus (BRNV) and other viruses affecting raspberry in Norway based on three years of data. Infection rates showed that the old raspberry cultivar Veten, including wild raspberry populations are susceptible to BRNV. Additionally, the known aphid vector, Amphorophora aidaei, is able to acquire the virus within one minute, and transmission can occur in an hour. Understanding the mechanisms behind virus transmission is essential for protecting raspberry crops from these ongoing agricultural threats Sapkota et al.One focus of the study on seed transmission and elimination strategies investigates how viral infections impact the alfalfa (Medicago sativa) industry, specifically targeting six significant viruses: Alfalfa mosaic virus (AMV), Medicago sativa alphapartitivirus1 (MsAPV1), MsAPV2, Medicago I n r e v i e w sativa deltapartitivirus 1 (MsDPV1), amalgavirus 1(MsAV1), and Cnidium vein yellowing virus 1 (CnVYV1).Virus transmission rates from alfalfa seeds to seedlings were about 44% to 88% using PCR assay. The authors have tested 16 virus elimination strategies for alfalfa seeds. Inconclusion, this research sheds light on critical virus transmission pathway sin alfalfa, offers practical methods for managing these diseases, and enhances agricultural productivity Li et al.