Innovational technical basis for cultivation in cooperation with information science

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)


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
NTT Fellow/Head of Ueda Research Laboratory, Director of Machine Learning and Data Science Center, NTT Communication Science Laboratories, Nippon Telegraph and Telephone Corporation

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

・Takaharu Kameoka
Professor, Graduate School of Bioresources, Mie University

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

・Miyuki Nakano
Professor, Master Program of Information Systems Architecture, Advanced Institute of Industrial Technology

・Takeshi Horie
Professor Emeritus, Kyoto University

・Tomoko Matsui
Professor, Department of Statistical Modeling, The Institute of Statistical Mathematics

・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

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 (Assistant Professor, Institute for Advanced Research, Nagoya University)

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

PRESTO Researcher:
Hirokazu Fukuda (Associate 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 (Associate 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 (PRESTO Researcher, Japan Science and Technology Agency)

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 (PRESTO Researcher, Japan Science and Technology Agency)

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)

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