About this Research Topic
By entering the new century, there is a proliferation of cutting-edge technologies including, but not limited to, high-throughput nucleotide sequencing, genome editing, and artificial intelligence. Optimistically, these burgeoning technologies promise to instigate groundbreaking changes to traditional agricultural strategies, offering innovative solutions to the challenges the world is confronting.
Leveraging these innovative technologies, transformative outcomes are anticipated in de novo planting patterns across diverse fields such as crop cultivation, gardening, and soil remediation. In an agricultural context, plants and soil constitute key elements, harmonizing with other influencers like environmental components, planting patterns, bio and bio stress and chemical applications, among others.
We aim to collect brilliant research results on new technologies and strategies contributing to high-efficiency and more eco-friendly agriculture. Research on herbicides, pesticides, soil management, soil microbes, pathology and relevant plant biology are all welcomed. The following topic areas to be included, but not limited to, in this Research Topic are:
1. Weed management by herbicide; weed herbicide-resistance precautions; new resistance loci identification; and the advanced utility of new herbicidal chemicals and potential threat to ecology.
2. Pesticide application and development; low toxicity pesticide and eco-friendly pest management strategy; pesticide resistance.
3. Soil Management, research focused on sustainable soil practices and conservation.
4. Soil Microbiology and Pathology, insights into the soil microbiome and disease management.
5. Genome Editing and novel gene function, enable the development of crops with desirable characteristics such as herbicide or pest resistance and nutritional enhancement, offering an eco-friendlier alternative to traditional genetically modified organisms (GMOs) by avoiding the introduction of foreign genes.
6. Artificial Intelligence (AI), utilizing deep learning to refine agricultural management strategies, enhancing decision-making through data analysis and predictive modelling.
7. Plant Biology, including plant growth, development, and adaptation mechanisms.
8. High Throughput Nucleotide Sequencing, accelerating the generation of crop genome data, and facilitating the identification of genes linked to vital agricultural traits.
Keywords: Agriculture, Plant, Soil, Microbe, Sequencing, Genome editing, Data mining, AI
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.