New Approaches in the Detection of Plant Pathogens

Fast (early), sensitive and accurate detection of plant pathogens is of utmost importance in plant health, not only for management purposes but also for improved surveillance of emerging pathogens and unwanted introductions. Over time, many research groups greatly invested in developing diagnostic tools that can overcome the most important disadvantages of the classic DNA/RNA based techniques. Focusing on reducing analysis time, high input costs, sensitivity, and robustness, they are working towards more generic tools that can simultaneously detect a wide range of pathogens, not forgetting the efforts that are made to increase the throughput of the detection methodologies. Even after the introduction of real-time quantitative PCR, which was a massive improvement to diagnostics at the time of its introduction (Heid et al., 1996) and still remains the gold standard in most plant health diagnostic laboratories. However, particularly for export/import screening, yet also for in-field applications, the search for better, faster and more broadly applicable detection methods continued unabated. This lead to the development of point-of-care molecular diagnostic tools based on isothermal amplification such as LAMP (Loop-mediated isothermal identification; Notomi et al. 2000) or HDA (Helicase dependent amplification; Vincent et al. 2004). Simplifying the crucial extraction step from sometimes difficult matrices, or particularly for the development of point-of-care diagnostics (eg. in combination with the isothermal amplification techniques) is also still one of the top priorities.

With high-throughput-sequencing techniques becoming affordable to be used in plant health diagnostics, many labs started exploring the possibility to exploit its huge advantage, namely allowing untargeted virus discovery, eg. in view of resolving crop problems displaying an unknown disease etiology. This evolution not only required knowledge in the diverse wet lab techniques, yet also huge investments in data handling and standardizing bioinformatics pipelines. Gradually, HTS techniques not only gained interest in virus diagnostics but also for the detection and identification of nematodes, fungi, bacteria and even insects and mites (Piombo et al. 2021; Haegeman et al. 2021).

However, a lot of progress is still needed to achieve the ultimate goal; a fast, sensitive and reliable universal detection tool that allows simultaneous detection and identification of a wide range of plant pathogens and even pests. In addition to the strategies described above which are mostly used in routine plant health laboratories, methods based on the analysis of volatile compounds as biomarkers, remote sensing-based technologies (eg. plant-disease assessment based on hyperspectral datasets) in support of surveillance, spectroscopy-based methods (including visual -, near infrared -, shortwave infrared -, and thermal infrared wavelength based imaging), and finally biosensor development, such as biophotonics, are innovative methods that can strongly contribute to a more efficient plant disease assessment and monitoring.

In this Research Topic we aim to publish state of the art original research and reviews on the following, but not limited to, topics:

• The development and validation of generic and specific detection methods for plant pathogens
• Innovative technologies that assist detection and identification of plant pathogens in support of eg. early detection, warning systems, emerging problems and actual problems putting pressure on crop cultivation in horticulture and agriculture
• Integration of HTS technologies in plant-pathogen diagnostics in particular, and (regulatory) plant health in general