The modern metagenomics- and transcriptomics-based identification of microbes has offered exceptional opportunities to understand microbial communities, compared to existing conventional technologies. The plant-associated microbial community plays essential roles in pathogenicity, plant growth, and development. Therefore, understanding the molecular interactions between microorganisms and plants is necessary to improve crop yields by utilizing beneficial microbes and eliminating disease-causing pathogens.
The emergence of microorganisms and their interactions should facilitate improvements in plant growth, crop protection, and yield, particularly in fruits and vegetable plants. However, research understanding on microbial communities associated with fruits and vegetable plants is still lacking. Furthermore, advanced microbial community mapping and modern detection methods such as Artificial Intelligence, CRISPR, and High Throughput Sequence technologies are of great interest.
The main goal of this Research Topic is to provide insights into metagenomic and metatranscriptomic techniques for studying fruits and vegetable plants-associated microbes and specific detection using Artificial Intelligence, CRISPR, and High Throughput Sequence (HTS) technologies. The identification of microbes associated with fruits and vegetable plants will enable researchers to determine potential pathogen elimination and utilize beneficial microbes as biocontrol agents. This collection aims to empower the scientific community and facilitate the publication of impactful research on understanding microbial networks in fruits and vegetable crops.
Authors are encouraged to submit research articles and/or review articles on the following topics:
• Utilizing metagenomics and transcriptomics technologies for identifying microbes associated with fruits and vegetable crops.
• Modern detection methods such as artificial intelligence, CRISPR, and high throughput sequencing (HTS) technologies for plant pathogenic microbe detection.
Keywords:
Metagenomics, Metatranscriptomics, Microbiome, Pathogen Detection, CRISPR, HTS, Artificial Intelligence
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The modern metagenomics- and transcriptomics-based identification of microbes has offered exceptional opportunities to understand microbial communities, compared to existing conventional technologies. The plant-associated microbial community plays essential roles in pathogenicity, plant growth, and development. Therefore, understanding the molecular interactions between microorganisms and plants is necessary to improve crop yields by utilizing beneficial microbes and eliminating disease-causing pathogens.
The emergence of microorganisms and their interactions should facilitate improvements in plant growth, crop protection, and yield, particularly in fruits and vegetable plants. However, research understanding on microbial communities associated with fruits and vegetable plants is still lacking. Furthermore, advanced microbial community mapping and modern detection methods such as Artificial Intelligence, CRISPR, and High Throughput Sequence technologies are of great interest.
The main goal of this Research Topic is to provide insights into metagenomic and metatranscriptomic techniques for studying fruits and vegetable plants-associated microbes and specific detection using Artificial Intelligence, CRISPR, and High Throughput Sequence (HTS) technologies. The identification of microbes associated with fruits and vegetable plants will enable researchers to determine potential pathogen elimination and utilize beneficial microbes as biocontrol agents. This collection aims to empower the scientific community and facilitate the publication of impactful research on understanding microbial networks in fruits and vegetable crops.
Authors are encouraged to submit research articles and/or review articles on the following topics:
• Utilizing metagenomics and transcriptomics technologies for identifying microbes associated with fruits and vegetable crops.
• Modern detection methods such as artificial intelligence, CRISPR, and high throughput sequencing (HTS) technologies for plant pathogenic microbe detection.
Keywords:
Metagenomics, Metatranscriptomics, Microbiome, Pathogen Detection, CRISPR, HTS, Artificial Intelligence
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.