JOURNAL ARTICLE
In Situ Diagnosis and Digital Cataloguing of Plant Pathogenic Fungi Through Mobile‐Based Foldscope Microscopy.
Published In: Journal of Phytopathology, 2024, v. 172, n. 6. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Mooventhan, Palanisamy; Sivalingam, Palaiyur Nanjappan; Singh, Harvinder Kumar; Sahu, Manoj Kumar; Dhimar, Yogita; Singh, Uttam; Kaushal, Pankaj; Ghosh, Probir Kumar 3 of 3
Abstract
Agriculture confronts multifaceted challenges across the spectrum of crop production, with pest and disease management being a prominent concern. Timely diagnosis of crop diseases is imperative for mitigating production costs and curbing the adverse environmental impacts of chemical pesticides. In the present investigation, mobile phone‐based foldscope microscopy (MBFM) was used to diagnose various field samples infected with fungal diseases of field and horticultural crops, and the same was validated with the normal microscope pictures and field symptoms. The MBFM was also used to diagnose seed‐borne microflora associated with wheat and spores of commercial formulation of bioagents and validated. The MBFM utilises both symptoms and morphological structures of pathogen for in situ field diagnosis and hence advantages over the symptom‐based mobile Apps. This study underscores the utility of foldscope microscope as a potent technique for plant pathologists and extension workers to enable real‐time and in situ identification of diseases caused by fungal pathogens in various agricultural crops. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Phytopathology. 2024/11, Vol. 172, Issue 6, p1
- Document Type:Article
- Subject Area:Botany
- Publication Date:2024
- ISSN:0931-1785
- DOI:10.1111/jph.13422
- Accession Number:181921648
- Copyright Statement:Copyright of Journal of Phytopathology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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