[Cultivation with Information Science] Innovational technical basis for cultivation in cooperation with information science

※ Affiliations and titles are as of the end of the research activity.

Strategic Objects

“Establishment of an Environmentally Adaptive Plant Design System to Achieve a Stable Food Supply in the Age of Climate Change”
“Construction of Models for Mathematical Notation and Elucidation of Various Phenomena whose Ruling Principles and Laws in Society are Unclear”

Research Supervisor

photo:Seishi Ninomiya

Seishi Ninomiya (Professor, Graduate School of Agricultural and Life Sciences, The University of Tokyo)

Outline

The aim of this area is to achieve advanced cultivation techniques that will enable sustainable high-yield, high-quality agricultural production even under the various limitations resulting from climate change and the need for reduced environmental load and so on. To this end, collaboration between agricultural and plant science and information science (state-of-the-art measurements, data-driven science and so on) will be promoted to achieve the cultivation of plants adapted to various environments as well as control of plant growth to match production quality.

Specifically, these will include technologies for nondestructive measurement of plant biological functions, technologies to extract knowledge for ideal cultivation from diverse, large-scale data, general growth models capable of going beyond the site-specificity of plant cultivation, growth models that can consider uncertainty, complex system models that describe farm field ecosystems, technologies for precise control of growth in outdoor environments and so on.

For the pursuit of research in this area, the emphasis will be on the exchange of information, discussion and collaboration by researchers in information science and those in agricultural and plant science. Collaboration by PRESTO (Sakigake) researchers, each employing the strength of his or her specialist field, will be promoted to obtain the synergy resulting from mutual stimulation, in order to resolve food issues that will arise in the future. Furthermore, in order to maximize achievements for the achievement of the strategic objective, management of this research area will also be coordinated with the CREST “Creation of fundamental technologies contribute to the elucidation and application for the robustness in plants against environmental changes” research area and the PRESTO “Creation of Next-generation fundamental technologies for the control of biological phenomena in field-grown plants” research area.

Research Area Advisors

・Naonori Ueda
Deputy Director, RIKEN Center for Advanced Integrated Intelligence Research

・Tsutomu Kagami
Managing Director, Managing Executive Officer, SAKATA SEED CORPORATION

・Takaharu Kameoka
Professor Emeritus, Mie University

・Eiji Goto
Professor, Graduate School of Horticulture, Chiba University

・Miyuki Nakano
Professor,College of Liberal Arts,Tsuda University

・Takeshi Horie
Professor Emeritus, Kyoto University

・Tomoko Matsui
Professor, The Institute of Statistical Mathematics

※Affiliations and titles are as of March 31, 2021.

Research Area Management Advisors

・Sachiko Isobe
Laboratory Head, Department of Frontier Research, Laboratory of Plant Genomics and Genetics, Kazusa DNA Research Institute

・Hiroyuki Morikawa
Professor, Graduate School of Engineering, The University of Tokyo

※Affiliations and titles are as of March 31, 2021

Year Started : 2015

Data Assimilation of a forest vegetation model with a particle filter and projections of vegetation dynamics under environmental changes

PRESTO Researcher:
Takeshi Ise (Associate Professor, Field Science Education and Research Center, Kyoto University)

High resolution field sensing for monitoring individual plant growth

PRESTO Researcher:
Ryo Sugiura (Senior Researcher, Hokkaido Agricultural Research Center Large-scale Farming Research Division, National Agriculture and Food Research Organization)

Development of diagnosis method in plants and optimization of crop cultivation

PRESTO Researcher:
Michitaka Notaguchi (Associate Professor, Bioscience and Biotechnology Center, Nagoya University)

Elucidation of the plant production instability based on precious environmental and omics data

PRESTO Researcher:
Hirokazu Fukuda (Professor, Graduate School of Engineering, Osaka Prefecture University)

Development of a highly-accurate and self-adjusting prediction infrastructure for water stress-based cultivation method

PRESTO Researcher:
Hiroshi Mineno (Professor, College of Informatics, Academic Institute, Shizuoka University)

Modeling the gene-environment interaction by combining ecophysiological crop models with quantitative genetics for rice breeding

PRESTO Researcher:
Shiori Yabe (Researcher, Institute of Crop Science, National Agriculture and Food Research Organization)

Year Started : 2016

Establishment of soil diagnostics by field-pathogenomics

PRESTO Researcher:
Shuta Asai (PRESTO Researcher, Japan Science and Technology Agency)

Forecasting agricultural ecosystem dynamics using ecological networks

PRESTO Researcher:
Masayuki Ushio (Program-Specific Associate Professor, the Hakubi Center for Advanced Research, Kyoto University)

Development of rice growth model with high generalization capability by probability photosynthesis model

PRESTO Researcher:
Kenichi Tatsumi (Associate Professor, Graduate School of Agriculture, Tokyo University of Agriculture and Technology)

The investigation of a causal relationship between rice productivity and cultivation environment through the use of legacy agricultural data.

PRESTO Researcher:
Shunsaku Nishiuchi (Assistant Professor, Graduate School of Bioagricultural Sciences, Nagoya University)

Super-resolution phenotyping of plant shoot architecture by multiscale morphological data fusion

PRESTO Researcher:
Koji Noshita (Assistant Professor, Faculty of Science, Kyushu University)

Statistical prediction of plant growth based on the analysis of time course data

PRESTO Researcher:
Hidetoshi Matsui (Associate Professor, The Center for Data Science Edutation and Research, Shiga University)

Year Started : 2017

Bayesian optimization of cultivation conditions under uncertain environment

Research Director:
Koji Iwayama (Associate Professor, Field of Data Science, Shiga University)

Estimation of crop vitality based on Tensor decomposition and data fusion of multimodal, multitemporal leaf-scale aerial images

Research Director:
Kuniaki Uto (Assistant Professor, School of Computing, Tokyo Institute of Technology)

Three-dimensional plant structure modeling and lifelog generation for growth analysis and prediction in future cultivation

Research Director:
Fumio Okura (Associate Professor, Graduate School of Information and Technology, Osaka University)

Dynamic evaluation of photosynthetic induction time in crops under field conditions

Research Director:
Keisuke Ono (Principal Researcher, Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization)

Deep learning based image analysis for plant phenotypic analysis

Research Director:
Yosuke Toda (PRESTO Researcher, Japan Science and Technology Agency)

Computational Breeding Design of Least Allergen Crops

Research Director:
Sohiya Yotsukura (PRESTO Researcher, Japan Science and Technology Agency)