Dr Daisuke Ogawa, Institute of Crop Science, National Agriculture and Food Research Organisation
Title: Insight on time-series phenotyping of rice in the field using UAVs
Plant Research Centre Auditorium, 28 March, 3:00 pm – 4:00 pm
Maximising crop yield is one of the main interests of agricultural researchers. My team is carrying out research on how growth pattern is effective in producing rice yield. We developed the method for time-series data on vegetation fraction (VF) as a vegetation index and canopy height (CH) as a vertical growth parameter in rice using UAVs. Using the method, we detected QTLs for VF and CH through genetic analysis using our multiparent advanced generation intercross (MAGIC) lines and showed the relevance of the QTLs for yield-related traits. I would like to share the progress of my recent work and discuss the use of high-throughput phenotyping data.
Publication list:
1) Phenology analysis for trait prediction using UAVs in a MAGIC rice population with different transplanting protocols. Frontiers in Artificial Intelligence. DOI: 10.3389/frai.2024.1477637
2) Prediction of heading date, culm length, and biomass from canopy-height-related parameters derived from time-series UAV observations of rice. Frontiers in Plant Science. DOI: 10.3389/fpls.2022.998803
3) Remote-Sensing-Combined Haplotype Analysis Using Multi-Parental Advanced Generation Inter-Cross Lines Reveals Phenology QTLs for Canopy Height in Rice. Frontiers in Plant Science. DOI: 10.3389/fpls.2021.715184
4) Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture. JXB. DOI: 10.1093/jxb/eraa605
5) Surveillance of panicle positions by unmanned aerial vehicle to reveal morphological features of rice. PLOS ONE. DOI: 10.1371/journal.pone.0224386
6) Discovery of QTL Alleles for Grain Shape in the Japan-MAGIC Rice Population Using Haplotype Information. G3. DOI: 10.1534/g3.118.200558
7) Haplotype-based allele mining in the Japan-MAGIC rice population. Scientific reports. DOI: 10.1038/s41598-018-22657-3