Plant Virus Sensor for the Rapid Detection of Bean Pod Mottle Virus Using Virus-Specific Nanocavities.

agricultural sensor bean pod mottle virus molecularly imprinted polymer plant sensor virus detection

Journal

ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031

Informations de publication

Date de publication:
27 10 2023
Historique:
medline: 30 10 2023
pubmed: 22 9 2023
entrez: 22 9 2023
Statut: ppublish

Résumé

This study presents a miniaturized sensor for rapid, selective, and sensitive detection of bean pod mottle virus (BPMV) in soybean plants. The sensor employs molecularly imprinted polymer technology to generate BPMV-specific nanocavities in porous polypyrrole. Leveraging the porous structure, high surface reactivity, and electron transfer properties of polypyrrole, the sensor achieves a sensitivity of 143 μA ng

Identifiants

pubmed: 37738225
doi: 10.1021/acssensors.3c01478
doi:

Substances chimiques

Polymers 0
Pyrroles 0

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

3902-3913

Auteurs

Nawab Singh (N)

Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50011, United States.
Microelectronics Research Center, Iowa State University, Ames, Iowa 50011, United States.

Raufur Rahman Khan (RR)

Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50011, United States.
Microelectronics Research Center, Iowa State University, Ames, Iowa 50011, United States.

Weihui Xu (W)

Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, Iowa 50011, United States.

Steven A Whitham (SA)

Department of Plant Pathology, Entomology, and Microbiology, Iowa State University, Ames, Iowa 50011, United States.

Liang Dong (L)

Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50011, United States.
Microelectronics Research Center, Iowa State University, Ames, Iowa 50011, United States.

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Classifications MeSH