Literature DB >> 33720345

Plant pest surveillance: from satellites to molecules.

Gonçalo Silva1, Jenny Tomlinson2, Nawaporn Onkokesung3, Sarah Sommer3, Latifa Mrisho4, James Legg4, Ian P Adams2, Yaiza Gutierrez-Vazquez2, Thomas P Howard3, Alex Laverick3, Oindrila Hossain5, Qingshan Wei5, Kaitlin M Gold6, Neil Boonham3.   

Abstract

Plant pests and diseases impact both food security and natural ecosystems, and the impact has been accelerated in recent years due to several confounding factors. The globalisation of trade has moved pests out of natural ranges, creating damaging epidemics in new regions. Climate change has extended the range of pests and the pathogens they vector. Resistance to agrochemicals has made pathogens, pests, and weeds more difficult to control. Early detection is critical to achieve effective control, both from a biosecurity as well as an endemic pest perspective. Molecular diagnostics has revolutionised our ability to identify pests and diseases over the past two decades, but more recent technological innovations are enabling us to achieve better pest surveillance. In this review, we will explore the different technologies that are enabling this advancing capability and discuss the drivers that will shape its future deployment.
© 2021 The Author(s).

Entities:  

Keywords:  biosecurity; diagnostics; phytopathology; surveillance

Year:  2021        PMID: 33720345     DOI: 10.1042/ETLS20200300

Source DB:  PubMed          Journal:  Emerg Top Life Sci        ISSN: 2397-8554


  5 in total

1.  The Viral Threat in Cotton: How New and Emerging Technologies Accelerate Virus Identification and Virus Resistance Breeding.

Authors:  Roberto Tarazi; Maite F S Vaslin
Journal:  Front Plant Sci       Date:  2022-04-05       Impact factor: 6.627

2.  Digital plant pathology: a foundation and guide to modern agriculture.

Authors:  Matheus Thomas Kuska; René H J Heim; Ina Geedicke; Kaitlin M Gold; Anna Brugger; Stefan Paulus
Journal:  J Plant Dis Prot (2006)       Date:  2022-04-28       Impact factor: 1.847

Review 3.  Machine Learning for Plant Stress Modeling: A Perspective towards Hormesis Management.

Authors:  Amanda Kim Rico-Chávez; Jesus Alejandro Franco; Arturo Alfonso Fernandez-Jaramillo; Luis Miguel Contreras-Medina; Ramón Gerardo Guevara-González; Quetzalcoatl Hernandez-Escobedo
Journal:  Plants (Basel)       Date:  2022-04-02

4.  Epidemiologically-based strategies for the detection of emerging plant pathogens.

Authors:  Alexander J Mastin; Frank van den Bosch; Yoann Bourhis; Stephen Parnell
Journal:  Sci Rep       Date:  2022-06-29       Impact factor: 4.996

Review 5.  New-Generation Sequencing Technology in Diagnosis of Fungal Plant Pathogens: A Dream Comes True?

Authors:  Maria Aragona; Anita Haegi; Maria Teresa Valente; Luca Riccioni; Laura Orzali; Salvatore Vitale; Laura Luongo; Alessandro Infantino
Journal:  J Fungi (Basel)       Date:  2022-07-16
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.