Literature DB >> 19385729

Plant disease diagnostic capabilities and networks.

Sally A Miller1, Fen D Beed, Carrie Lapaire Harmon.   

Abstract

Emerging, re-emerging and endemic plant pathogens continue to challege our ability to safeguard plant health worldwide. Further, globalization, climate change, increased human mobility, and pathogen and vector evolution have combined to increase the spread of invasive plant pathogens. Early and accurate diagnoses and pathogen surveillance on local, regional, and global scales are necessary to predict outbreaks and allow time for development and application of mitigation strategies. Plant disease diagnostic networks have developed worldwide to address the problems of efficient and effective disease diagnosis and pathogen detection, engendering cooperation of institutions and experts within countries and across national borders. Networking maximizes impact in the face of shrinking government investments in agriculture and diminishing human resource capacity in diagnostics and applied pathology. New technologies promise to improve the speed and accuracy of disease diagnostics and pathogen detection. Widespread adoption of standard operating procedures and diagnostic laboratory accreditation serve to build trust and confidence among institutions. Case studies of national, regional, and international diagnostic networks are presented.

Entities:  

Mesh:

Year:  2009        PMID: 19385729     DOI: 10.1146/annurev-phyto-080508-081743

Source DB:  PubMed          Journal:  Annu Rev Phytopathol        ISSN: 0066-4286            Impact factor:   13.078


  13 in total

1.  Rapid detection of Ceratocystis platani inoculum by quantitative real-time PCR assay.

Authors:  Nicola Luchi; Luisa Ghelardini; Lassaâd Belbahri; Marion Quartier; Alberto Santini
Journal:  Appl Environ Microbiol       Date:  2013-06-28       Impact factor: 4.792

Review 2.  Nanotechnological interventions for plant health improvement and sustainable agriculture.

Authors:  Madhu Kamle; Dipendra Kumar Mahato; Sheetal Devi; Ramendra Soni; Vijay Tripathi; Awdhesh Kumar Mishra; Pradeep Kumar
Journal:  3 Biotech       Date:  2020-03-14       Impact factor: 2.406

3.  Network epidemiology and plant trade networks.

Authors:  Marco Pautasso; Mike J Jeger
Journal:  AoB Plants       Date:  2014-04-29       Impact factor: 3.276

4.  Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification.

Authors:  Srdjan Sladojevic; Marko Arsenovic; Andras Anderla; Dubravko Culibrk; Darko Stefanovic
Journal:  Comput Intell Neurosci       Date:  2016-06-22

5.  A multi-target, non-infectious and clonable artificial positive control for routine PCR-based assays.

Authors:  Donna Ria J Caasi; Mohammad Arif; Mark Payton; Ulrich Melcher; Louise Winder; Francisco M Ochoa-Corona
Journal:  J Microbiol Methods       Date:  2013-09-05       Impact factor: 2.363

6.  Visual DNA diagnosis of Tomato yellow leaf curl virus with integrated recombinase polymerase amplification and a gold-nanoparticle probe.

Authors:  Tzu-Ming Wang; Jing-Tang Yang
Journal:  Sci Rep       Date:  2019-10-22       Impact factor: 4.379

7.  Microeukaryotic Communities on the Fruit of Gardenia thunbergia Thunb. with a Focus on Pathogenic Fungi.

Authors:  Bastian Steudel; Himansu Baijnath; Thorben Schwedt; Armin Otto Schmitt
Journal:  Pathogens       Date:  2021-05-04

8.  Detection of Begomovirus in chilli and tomato plants using functionalized gold nanoparticles.

Authors:  R Lavanya; V Arun
Journal:  Sci Rep       Date:  2021-07-09       Impact factor: 4.379

9.  Effect of Agricultural Amendments on Cajanus cajan (Pigeon Pea) and Its Rhizospheric Microbial Communities--A Comparison between Chemical Fertilizers and Bioinoculants.

Authors:  Rashi Gupta; V S Bisaria; Shilpi Sharma
Journal:  PLoS One       Date:  2015-07-31       Impact factor: 3.240

10.  Dissecting the economic impact of soybean diseases in the United States over two decades.

Authors:  Ananda Y Bandara; Dilooshi K Weerasooriya; Carl A Bradley; Tom W Allen; Paul D Esker
Journal:  PLoS One       Date:  2020-04-02       Impact factor: 3.240

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