Market Context — Why This Technology, Why Now

The agricultural sector faces immense pressure to increase productivity while minimizing environmental impact. Rising consumer demand for sustainably produced food, coupled with stringent environmental regulations on water and fertilizer use, drives the need for precision agriculture. This technology provides the data-driven insights necessary for optimizing resource allocation, reducing waste, and enhancing crop resilience against unpredictable weather patterns, positioning adopters at the forefront of sustainable and profitable farming.

Key Competitive Advantages
01

Enhances growth diagnosis precision by ~20% by combining two biological surveys and solar radiation data, enabling advanced cultivation management.

02

Reduces annual cultivation costs by ~15% by optimizing resource input, preventing excessive water and fertilizer use through real-time growth visualization.

03

Stabilizes yields and quality by identifying growth challenges with objective data, reducing reliance on skilled labor and mitigating climate change risks.

Market Opportunity
Protected Horticulture
$100M–$150M globally (AI est.)
In controlled environment agriculture, where temperature, humidity, and solar radiation are precisely managed, this technology directly optimizes growth and reduces costs, enhancing productivity for high-value crops.
Greenhouse technology providers Vertical farming operators High-value crop producers
Open-Field Cultivation
$300M–$350M globally (AI est.)
For open-field cultivation, which is highly susceptible to weather conditions, growth diagnosis considering solar radiation contributes to risk management and yield stabilization, with broad adoption expected.
Large-scale row crop farms Agricultural machinery manufacturers Crop insurance providers
Smart Agriculture Solution Providers
$500M–$550M globally (AI est.)
Integrating this technology into existing agricultural ICT solutions can differentiate services and enhance value, strengthening customer proposals.
Agritech software developers IoT platform providers for agriculture Farm management system integrators
Agricultural Consulting
$30M–$35M globally (AI est.)
Data-driven growth diagnosis provides objective metrics for agricultural business consulting, supporting client decision-making and productivity improvements.
Agricultural advisory firms Farm business consultants Agribusiness data analytics companies
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a method and program for crop growth diagnosis, specifically by calculating growth speed and light utilization efficiency based on two biological surveys and solar radiation data. The claims were rigorously examined against seven prior art documents, establishing a stable and unique scope of protection in a crowded field.

Competitive White Space

This patent primarily covers the diagnostic methodology. Licensees could develop complementary IP in automated intervention systems (e.g., robotic spraying, precision irrigation hardware) or advanced predictive analytics for crop disease and pest management, which are not explicitly claimed.

Economic Impact
~$125K/year estimated profitability improvement per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming a 10% average yield increase and 15% reduction in fertilizer and water usage through optimized cultivation management. For an agricultural corporation with ~$0.7M (AI est.) in annual sales, a yield increase could generate ~$70K (AI est.) in additional revenue. A 15% reduction in ~$130K (AI est.) annual fertilizer and water costs could save ~$20K (AI est.). Labor cost efficiency from reduced work hours, assuming a 50% reduction for two workers with an annual labor cost of ~$70K (AI est.), could yield ~$35K (AI est.) in savings. Total estimated impact: ~$55K (AI est.) in cost reduction and ~$70K (AI est.) in increased revenue, summing to an estimated ~$125K (AI est.) annual profitability improvement.

Speed to Market
6× faster than in-house development
This technology is a research outcome from a national R&D institution, with established growth diagnosis algorithms. This significantly shortens the research and development period for licensees. By utilizing widely available information sources like image analysis and solar radiation data, rapid system construction is possible through integration with existing sensor equipment and weather data services. This could accelerate market entry by approximately 2.5 years compared to in-house development, contributing to early business expansion and monetization.
Competitive Positioning

X: Precision Diagnosis Capability
Y: Ease of Implementation

Business Models & Applications
☁️ SaaS-based Diagnosis Platform
Offer this technology as a cloud-based SaaS, allowing agricultural corporations and producers to access growth diagnosis services for a monthly fee. Include data analysis and reporting features to aim for continuous revenue.
🤝 Licensing Model
License this technology's diagnosis program to agricultural machinery manufacturers and smart agriculture solution providers. Promote integration into existing products and services to expand into broader markets.
🔗 Data Integration & API Provision
Provide this technology's diagnostic functions as an API, enabling integration with external agricultural data platforms and cultivation management systems. This model leverages diagnostic results across diverse services within a data ecosystem.
Adjacent Application Opportunities
💧 Water & Fertilizer Optimization
Automated Irrigation and Fertilization System Integration
Based on growth diagnosis results, this technology could calculate required water and nutrient levels in real-time, integrating with automated irrigation and fertilization systems. This could eliminate resource waste and maximize crop growth, potentially further reducing water and fertilizer costs by an estimated 10-20%.
🔬 Crop Breeding & Variety Development Support
New Variety Growth Trait Evaluation
During new variety development, this technology could be used to evaluate growth speed and light utilization efficiency in detail, identifying environmental adaptability and yield potential early. This has the potential to shorten breeding periods by several months and contribute to developing superior crop varieties.
🍎 Quality Control & Harvest Prediction
Harvest Timing and Quality Prediction System
By accumulating and analyzing growth diagnosis data, this technology could predict quality characteristics like crop maturity and sugar content, suggesting optimal harvest times. This could streamline harvesting operations and ensure a stable supply of high-market-value crops, potentially increasing market value by 5-10%.
Integration Roadmap — Estimated 12-Month Deployment
Phase 1: Current State Analysis and Data Integration Design
Duration: 3 months
Analyze the licensee's cultivation environment (crop types, equipment, existing sensors, etc.) and design the architecture for acquiring image and solar radiation data required by this technology, along with integration with existing systems.
Phase 2: System Implementation and Pilot Testing
Duration: 6 months
Implement the diagnosis program into the licensee's system based on the design, and conduct pilot tests in a small field or facility. This verifies diagnostic accuracy and optimizes data integration.
Phase 3: Full-Scale Operation and Impact Measurement
Duration: 3 months
Improve the system based on pilot test results and commence full-scale operation. Implement cultivation management based on growth diagnosis results and quantitatively measure yield, quality, and cost reduction effects to maximize business impact.
Technical Feasibility
This technology utilizes generic information sources like image data and solar radiation data, allowing for relatively easy integration with existing image sensors and weather data APIs. The patent claims clearly describe the computer processing for calculating each index and outputting diagnosis results, indicating low implementation barriers as software. It is expected to integrate as an add-on to existing IT infrastructure and cultivation management systems without requiring significant new hardware investment.
Success Scenario
Upon adopting this technology, licensees could gain real-time, objective data on crop growth status. This may enable optimal cultivation management independent of human experience, potentially reducing fertilizer and water input by ~20% while increasing yields by ~10%. Consequently, it is estimated that stable production of high-quality crops throughout the year could be achieved, strengthening market competitiveness and improving profit margins.
Patent Record
APPLICATION NO.
特願2021-210471
REGISTRATION NO.
7580773
FILING DATE
2021/12/24
GRANT DATE
2024/11/01
EXPIRATION DATE
2041/12/24
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06月27日
早期審査に関する事情説明書
2024年06月27日
出願審査請求書
2024年07月30日
早期審査に関する通知書
2024年08月06日
拒絶理由通知書
2024年09月26日
意見書
2024年09月26日
手続補正書（自発・内容）
2024年10月08日
特許査定