Market Context — Why This Technology, Why Now

The global agricultural sector is rapidly adopting smart farming technologies to combat rising operational costs, labor scarcity, and environmental pressures. Demand for IoT, AI, and data analytics in crop management is surging, driven by the need for higher yields, reduced resource consumption, and improved food quality. This technology aligns perfectly with this trend, offering a proven solution for precision horticulture that enhances sustainability and profitability across the value chain.

Key Competitive Advantages
01

Achieves high-precision total leaf area calculation by resolving leaf overlap with a blower and integrating past data, overcoming limitations of conventional image analysis.

02

Provides real-time visualization of growth status by continuously acquiring leaf area data through regular automatic measurements, enabling data-driven precision management.

03

Reduces manual labor for leaf area measurement by ~80% and stabilizes quality, contributing to increased yield and reduced variation through data-driven cultivation.

Market Opportunity
Large-Scale Strawberry Farmers
$65M–$650M globally (AI est.)
Large-scale strawberry farmers are highly motivated to invest in precise growth management and labor-saving technologies due to labor shortages and the desire for improved profitability. This technology contributes to high value-addition by simultaneously maximizing yield and reducing costs.
Large-scale commercial strawberry growers Agribusinesses specializing in fruit production High-tech horticulture farms
Plant Factories & Greenhouses
$650M–$6B globally (AI est.)
In plant factories and greenhouses with strict environmental control, detailed growth data for each plant is essential for optimizing environmental conditions. This technology supports the construction of precise, data-driven cultivation processes, thereby improving production efficiency.
Controlled environment agriculture (CEA) operators Vertical farm developers Greenhouse technology providers
Agricultural Machinery & System Integrators
$6.5B–$60B globally (AI est.)
Incorporating this technology as part of smart agriculture solutions can enhance the added value of products and services. Integration with existing agricultural machinery and cultivation management systems can create new market opportunities.
Agricultural equipment manufacturers Smart farming solution providers AgTech system integrators IoT platform developers for agriculture
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a system for high-precision strawberry leaf area calculation, specifically covering the use of a blower to resolve leaf overlap and an information processing unit combining current and historical leaf data. Its claims were upheld against six prior art references, establishing clear differentiation and a robust scope of protection.

Competitive White Space

This patent focuses on leaf area measurement. White space exists for developing IP in automated disease detection, fruit ripeness analysis, or integrated robotic harvesting systems.

Economic Impact
~$50K/year estimated cost savings and revenue increase per facility (est.).
estimated ROI · USD · AI analysis
ROI Calculation Logic

This technology could reduce manual leaf area measurement labor costs by approximately 80%, from an estimated $2,700 (AI est.) annually to $550 (AI est.) per facility. Furthermore, precise fertilization and water management, guided by leaf area data, could boost yields by 5%. For a strawberry farm with $1.5M (AI est.) in annual revenue, this could lead to an estimated $50K (AI est.) increase in annual revenue. The combined economic impact is estimated to exceed $50K (AI est.) annually.

Speed to Market
6× faster than in-house development
This technology, developed by a national research and development agency, has completed fundamental research and validation. The granted patent confirms its technical feasibility, significantly reducing the development effort for licensees. The system uses generic components like a blower, camera, and information processing unit, making integration into existing cultivation environments relatively straightforward and enabling rapid deployment and market entry.
Competitive Positioning

X: Measurement Accuracy & Reliability
Y: Operational Efficiency & Labor Saving

Business Models & Applications
📊 Data Utilization Licensing Model
A model to monetize by licensing the high-precision leaf area and growth data acquired by this technology to agricultural AI development companies and research institutions.
🛠️ System Implementation & Maintenance Service Model
A model to secure stable revenue by implementing this system for strawberry farmers and plant factories, and providing continuous maintenance and software updates.
📈 Yield Prediction SaaS Model
Offer a SaaS service that utilizes accumulated leaf area data from this technology to provide high-precision yield prediction and disease risk diagnosis. Monetization is expected through monthly subscriptions.
Adjacent Application Opportunities
🍎 Fruit Tree Cultivation
High-Precision Fruit Tree Growth Monitoring
In fruit tree cultivation (e.g., apples, grapes), apply this technology's image analysis and leaf dispersion techniques to precisely monitor not only leaf area but also canopy structure and fruit growth. This could be used for harvest yield prediction and quality control, potentially improving yield forecasts by 10-15%.
🥬 Leafy Vegetable Cultivation
Automated Leafy Vegetable Growth Diagnosis & Harvest Prediction
In leafy vegetable cultivation (e.g., lettuce, spinach), apply this technology to automatically diagnose growth stages from leaf development and area. This could aid in predicting optimal harvest times and early disease detection, potentially increasing harvest efficiency by 20% and stabilizing quality.
🌳 Breeding & Research Support
Automated Growth Data Acquisition for New Variety Development
Offer this system to agricultural research institutions and seed companies for efficient, high-precision automated acquisition of growth data during new variety breeding. This could accelerate breeding programs, reducing development cycles by up to 25% through data-driven insights.
Integration Roadmap — Estimated 12-Month Deployment
Technology Suitability & Initial Design
Duration: 3 months
Assess the technology's suitability for the licensee's existing cultivation environment (e.g., greenhouses, cultivation systems), define customization requirements, and conduct initial system design.
System Development & Prototype Deployment
Duration: 5 months
Based on the initial design, proceed with specific selection and integrated development of the blower, camera, and information processing unit. Subsequently, deploy a prototype in a small-scale environment for basic functional verification and data acquisition testing.
Full Operation & Impact Verification
Duration: 4 months
Optimize the system based on prototype verification results and commence full-scale operation. Utilize acquired leaf area data for cultivation management and conduct quantitative impact verification, including yield, quality, and cost reduction effects.
Technical Feasibility
This technology is based on a versatile hardware configuration including a blower, camera, and information processing unit. As described in the patent claims, these devices can be relatively easily installed and integrated into existing greenhouses and cultivation facilities. The image analysis algorithm is implemented as software, allowing for flexible adjustments to specific cultivation environments and crop characteristics, and facilitating integration with existing cultivation management systems. Adoption is expected to leverage existing infrastructure without requiring significant capital investment.
Success Scenario
Implementing this technology could eliminate manual leaf area measurement in strawberry cultivation, leading to significant labor savings. Real-time growth data for each plant would enable data-driven optimization of fertilization and irrigation, moving beyond reliance on experience and intuition. Early detection of diseases could also reduce losses. This is estimated to improve final yields by 5%–10% compared to current levels and stabilize product quality.
Patent Record
APPLICATION NO.
特願2021-140856
REGISTRATION NO.
7616656
FILING DATE
2021/08/31
GRANT DATE
2025/01/08
EXPIRATION DATE
2041/08/31
PATENT HOLDER
国立研究開発法人農業・食品産業技術総合研究機構
Examination History
2024年04月12日
出願審査請求書
2024年12月17日
特許査定