Blurred lines: integrating emerging technologies to advance plant biosecurity

Yiheng Hu; Salome Wilson; Benjamin Schwessinger; John P. Rathjen

doi:10.1016/j.pbi.2020.04.011

Blurred lines: integrating emerging technologies to advance plant biosecurity

Yiheng Hu, Salome Wilson, Benjamin Schwessinger, John P. Rathjen

Research output: Contribution to journal › Review article › peer-review

7 Citations (Scopus)

Abstract

Plant diseases threaten global food security and biodiversity. Rapid dispersal of pathogens particularly via human means has accelerated in recent years. Timely detection of plant pathogens is essential to limit their spread. At the same time, international regulations must keep abreast of advances in plant disease diagnostics. In this review we describe recent progress in developing modern plant disease diagnostics based on detection of pathogen components, high-throughput image analysis, remote sensing, and machine learning. We discuss how different diagnostic approaches can be integrated in detection frameworks that can work at different scales and account for sampling biases. Lastly, we briefly discuss the requirements to apply these advances under regulatory settings to improve biosecurity measures globally.

Original language	English
Pages (from-to)	127-134
Number of pages	8
Journal	Current Opinion in Plant Biology
Volume	56
DOIs	https://doi.org/10.1016/j.pbi.2020.04.011
Publication status	Published - Aug 2020

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10.1016/j.pbi.2020.04.011

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title = "Blurred lines: integrating emerging technologies to advance plant biosecurity",

abstract = "Plant diseases threaten global food security and biodiversity. Rapid dispersal of pathogens particularly via human means has accelerated in recent years. Timely detection of plant pathogens is essential to limit their spread. At the same time, international regulations must keep abreast of advances in plant disease diagnostics. In this review we describe recent progress in developing modern plant disease diagnostics based on detection of pathogen components, high-throughput image analysis, remote sensing, and machine learning. We discuss how different diagnostic approaches can be integrated in detection frameworks that can work at different scales and account for sampling biases. Lastly, we briefly discuss the requirements to apply these advances under regulatory settings to improve biosecurity measures globally.",

author = "Yiheng Hu and Salome Wilson and Benjamin Schwessinger and Rathjen, {John P.}",

note = "Publisher Copyright: {\textcopyright} 2020",

year = "2020",

month = aug,

doi = "10.1016/j.pbi.2020.04.011",

language = "English",

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T2 - integrating emerging technologies to advance plant biosecurity

AU - Hu, Yiheng

AU - Wilson, Salome

AU - Schwessinger, Benjamin

AU - Rathjen, John P.

PY - 2020/8

Y1 - 2020/8

N2 - Plant diseases threaten global food security and biodiversity. Rapid dispersal of pathogens particularly via human means has accelerated in recent years. Timely detection of plant pathogens is essential to limit their spread. At the same time, international regulations must keep abreast of advances in plant disease diagnostics. In this review we describe recent progress in developing modern plant disease diagnostics based on detection of pathogen components, high-throughput image analysis, remote sensing, and machine learning. We discuss how different diagnostic approaches can be integrated in detection frameworks that can work at different scales and account for sampling biases. Lastly, we briefly discuss the requirements to apply these advances under regulatory settings to improve biosecurity measures globally.

AB - Plant diseases threaten global food security and biodiversity. Rapid dispersal of pathogens particularly via human means has accelerated in recent years. Timely detection of plant pathogens is essential to limit their spread. At the same time, international regulations must keep abreast of advances in plant disease diagnostics. In this review we describe recent progress in developing modern plant disease diagnostics based on detection of pathogen components, high-throughput image analysis, remote sensing, and machine learning. We discuss how different diagnostic approaches can be integrated in detection frameworks that can work at different scales and account for sampling biases. Lastly, we briefly discuss the requirements to apply these advances under regulatory settings to improve biosecurity measures globally.

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U2 - 10.1016/j.pbi.2020.04.011

DO - 10.1016/j.pbi.2020.04.011

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VL - 56

SP - 127

EP - 134

JO - Current Opinion in Plant Biology

JF - Current Opinion in Plant Biology

ER -

Blurred lines: integrating emerging technologies to advance plant biosecurity

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