Sala 39, ISA | 7 SETEMBRO 2023, 12h00
shimono

To boost rice productivity under a changing climate

Global food demand has been rising to support future population growth under changing climates. My research interest is to increase crop yield (productivity per unit land area) in response to environmental changes, G x E interaction, using field phenotyping, crop growth model, QTL and GWAS analysis for mainly rice (Oryza sativa L.), addition to soybean and sweet potato. I want to share two topics of my current works, (1) Phenotypic plasticity: Breeding target for adapting future environments, and (2) Big data analysis: Upcycle yield trial data for future breeding.  Also, I want to introduce life in Japan. 

 

Below are related articles in my talk

  1. Shimono, H.* et. (2007) Modeling the effects of water temperature on rice growth and yield under a cool climate: I. Model development. Agron. J. 99 : 1327-1337.
  2. Shimono, H.*, et (2007) Modeling the effects of water temperature on rice growth and yield under a cool climate: II. Model application. Agron. J. 99 : 1338-1344.
  3. Shimono, H.*, et (2013) Lower responsiveness of canopy evapotranspiration rate than of leaf stomatal conductance to open-air CO2 elevation in rice. Global Change Biol.  19 : 2444-2453.
  4. Shimono, H.* and Bunce, J. A. (2009) Acclimation of nitrogen uptake capacity of rice to elevated atmospheric CO2 concentration. Ann. Bot. London 103 : 87-94.
  5. Shimono, H.*, et. (2009) Genotypic variation in rice yield enhancement by elevated CO2 relates to growth before heading, and not to maturity group. J. Exp. Bot. 60 : 523-532. 
  6. Kumagai, E.†, ... Shimono, H.† (2015) Phenotypic plasticity conditions the response of soybean seed yield to elevated atmospheric CO2 concentration. Plant Physiol. 169: 2021-2029.
  7. Kikuchi, S.,... and Shimono, H.* (2017) Genome-wide association mapping for phenotypic plasticity in rice. Plant Cell Environ. 40 : 1565-1575.
  8. Masuya, Y. and Shimono, H.* (2017) Mining a yield-trial database to identify high-yielding cultivars by simulation modeling: a case study for rice. J. Agric. Meteorol. 73 : 51-58.
  9. Shimono, H., Farquhar, G., et (2019) Prescreening in large populations as a tool for identifying elevated CO2-responsive genotypes in plants. Functional Plant Biology 46: 1-14.
  10. Shimono, H.*, Abe, A., Kim, C.H., Iwata, H. 2023. Upcycling rice yield trial data using a weather-driven crop growth model. Communications Biology, 6, Article number: 764. https://www.nature.com/articles/s42003-023-05145-x#

More in https://scholar.google.co.jp/citations?user=wviygTYAAAAJ&hl=ja

 

Link zoom: https://videoconf-colibri.zoom.us/j/95048618689?pwd=Yy83UGZVM2FYTXUwQlpy...