Underground Mechanism to Enhance Nutrient Use Efficiency in Rice
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Plant Sciences".
Deadline for manuscript submissions: closed (29 October 2021) | Viewed by 9894
Special Issue Editor
Interests: rice; root hair development; pollen genetics; ROS process; abiotic stress tolerance; transcirptome analysis; network analysis; genome editing; phylogenomics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rice (Oryza sativa L.) is not only a major staple food for the world’s population but also a model crop plant for studying the mode of action of agronomically valuable traits, suggesting ideas for application to other crop plants. The roots of the plant demonstrate a range of essential functions, including the acquisition of water and nutrient and structural support. A molecular and genetic understanding of the mechanism by which nutrient use efficiency is enhanced in rice, as a model crop plant, is very important for crop productivity. Advances in integrating omics studies using the genome, transcriptome, proteome, metabolome, and functional genomics will provide valuable insights into low-input and sustainable crop production.
Papers submitted to this Special Issue must report novel results and/or plausible and testable new models. This Special Issue includes studies involving physiological and chemical analysis associated with the transcriptome, proteome, metabolome, and integrating omics for nutrient use efficiency in crop plants and developing crops with enhanced nutrient use efficiency through the improvement of root traits using natural variation, biotechnology, and gene editing techniques. In addition, related database issues are also welcome.
Prof. Dr. Ki-Hong Jung
Guest Editor
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Keywords
- rice
- root
- nutrient use efficiency (nitrogen, phosphate, potassium)
- utilization of micronutrients (boron, chlorine, copper, iron, manganese, and zinc)
- reactive oxygen species (ROS)
- transcriptomics
- proteomics
- metabolomics
- integrating omics
- genome-wide association study (GWAS)
- mutant analysis
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