Development of an Integrated Coastal Monitoring System for Sustainable Fisheries

To realize sustainable fisheries, we are developing an integrated coastal monitoring and data analytics system that covers both terrestrial and marine domains. Through this research, we aim to elucidate how terrestrial economic activities—including agriculture and industry—as well as meteorological conditions, interact with and influence marine fisheries. By clarifying these land–sea interactions, the project seeks to […]

Development of AI‑Based Food Quality Evaluation Technology Leveraging Comprehensive Digitalization of Food Components

The graphite sheet–assisted LDI‑MS method is a novel and innovative analytical technique that enables simultaneous analysis of both hydrophobic and hydrophilic compounds without any sample pretreatment. In this proposal, by leveraging this technology—which allows any user to easily digitize food component information—we aim to establish an AI‑based food quality evaluation technology. Through this approach, we […]

Development of a Fleet Network System Using VDES

In fisheries that operate in vessel fleets, effective information sharing significantly improves operational efficiency. In offshore areas where internet connectivity is unavailable, communication still relies primarily on voice radio, highlighting the need for a more efficient alternative. In this project, we are developing a fleet networking technology based on VDES, a next‑generation maritime digital communication […]

Advancement of Cell Culture Technologies Toward the Realization of Cultured Eel Meat

In this study, we aim to establish large‑scale culture technologies for Japanese eel (Anguilla japonica) myoblasts and adipocytes, and to develop foundational technologies for the commercialization of cultured eel meat. By combining stirred‑tank bioreactors with immobilized cell culture bioreactors, we will optimize cell proliferation and differentiation to achieve high‑density, large‑scale cell production. In addition, to […]

Improving the Efficiency of Forest Resource Assessment Using a Forest Vegetation Classification AI with Rapid Training Image Generation

By extending and improving the “Fragmented Image Method,” which enables rapid creation of training images, we will build forest vegetation classification AI models with less than one‑tenth of the labor time required by conventional AI approaches. This significant cost reduction will bring innovation to forestry sites where AI adoption has previously been limited. By enabling […]

Development of a Functional Mushroom Cultivation Substrate with High Nutritional Value and Reduced Calorie and Phosphorus Content, and Verification of Its Health-Related Functions

In this project, we will develop a cultivation substrate preparation technology using underutilized biomass and osmotic regulators, with the goal of producing novel mushrooms that are highly nutritious, low in potassium and phosphorus, and offer a wide range of functional benefits. Through this work, we aim to (1) create new health-food markets for people with […]

Research and Development of Artificial Antimicrobial Enzymes for Animals to Reduce the Risk of Antimicrobial Resistance

Antimicrobial enzymes are bactericidal agents that kill bacteria by disrupting the bacterial cell wall, and are expected to be socially implemented as alternatives to conventional antibiotics. In this research project, aiming to create innovation in the veterinary antimicrobial market, we will develop technologies for generating high‑performance artificial antimicrobial enzymes using data science and synthetic biology […]

Development of a Bud- and Leaf-Harvesting End Effector Capable of Simultaneous Generation of High-Fidelity Plant Digital Twins

Leaf harvesting and leaf–bud pruning account for a substantial portion of labor time in plant production, creating a strong demand for automation. However, the diverse and complex shapes of leaves make fully automated robotic operation technically challenging. In this study, we will develop an end effector that enables robotic leaf and bud sampling by simultaneously […]