Market Context — Why This Technology, Why Now

The global push for sustainable agriculture, driven by consumer demand and stricter environmental regulations, is accelerating the adoption of precision farming technologies. Farmers worldwide are seeking solutions to optimize resource allocation, reduce ecological footprints, and enhance profitability in the face of volatile input costs and climate variability. This technology provides a critical tool for achieving these goals, enabling data-driven decisions that improve efficiency and resilience across diverse agricultural landscapes.

Key Competitive Advantages
01

Automates fertilizer optimization, eliminating reliance on skilled labor and personal expertise

02

Generates high-precision fertilizer maps, potentially reducing over-application by ~20% and lowering environmental impact

03

Adapts rapidly to changing conditions, ensuring consistently high-precision fertilizer management

Market Opportunity
Large-Scale Crop Farmers
$330M globally (AI est.)
For large-scale farms managing extensive fields, optimizing fertilizer application and reducing costs are critical. This technology's automated optimization directly translates to significant savings in labor and fertilizer expenses, driving profitability and offering high adoption incentives.
Large-scale grain producers Commercial vegetable farms Agribusiness conglomerates
Agricultural Machinery and Drone Manufacturers
$6.5B globally (AI est.)
Integrating this technology into existing agricultural machinery and drones could significantly enhance product value. Its precision fertilizer application feature offers a key differentiator for smart agriculture solutions, strengthening market competitiveness.
Global agricultural equipment OEMs Drone manufacturers specializing in agriculture Precision agriculture hardware developers
Smart Agriculture Solution Providers
$200M globally (AI est.)
For companies offering data analytics and AI-driven agricultural support services, this technology could strengthen existing platforms and enhance customer value. It provides a powerful tool for expanding service offerings and attracting new clients.
Agricultural data analytics firms Farm management software companies AI-driven agritech startups
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent broadly protects an apparatus, method, and program for automatically calculating fertilizer application based on field data, with 8 claims. Its resilience, having overcome two office actions with strong legal representation, indicates a robust and difficult-to-invalidate intellectual property, offering licensees a secure foundation for business expansion.

Competitive White Space

This patent primarily covers the software and method for fertilizer calculation. White space exists in developing novel sensor hardware for data collection, integrating with advanced autonomous farm vehicles, or extending the system to holistic farm management beyond fertilization.

Economic Impact
~$30K/year estimated economic impact per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Reducing fertilizer over-application could cut annual fertilizer costs by ~20% (e.g., $35K/year fertilizer spend could save ~$5K/year (AI est.)). Optimizing fertilizer management could increase yields by ~15% (e.g., $13.5K/hectare annual gross profit could increase by ~$2K (AI est.)). Additionally, significant reduction in labor for soil analysis and manual fertilizer planning could save ~$20K/year (AI est.) (50% reduction of one operator's annual cost of ~$40K). Total estimated economic impact per facility could reach ~$30K/year (AI est.).

Speed to Market
8× faster than in-house development
This technology, developed by the National Agriculture and Food Research Organization, features a fully established automatic fertilizer calculation algorithm. It operates using data from existing field machinery, sensors, and drones, often requiring no new hardware development. This allows licensees to significantly reduce development time compared to building a similar system from scratch, potentially accelerating market entry by approximately 3.5 years. Rapid transition from Proof of Concept (PoC) to full operational deployment is expected.
Competitive Positioning

X: Precision Fertilizer Application Accuracy
Y: Ease of Implementation & Operation

Business Models & Applications
💻 Software License Provision
Offer licenses for this fertilizer calculation program to agricultural machinery manufacturers and smart agriculture solution providers, promoting integration into existing products and platforms for widespread adoption.
☁️ SaaS Data Analytics Service
Provide a cloud-based SaaS for collecting and analyzing field data to generate optimal fertilizer maps. Farmers could subscribe, enabling precision agriculture adoption with reduced upfront investment.
🤝 Collaborative Research & Technical Consulting
Offer joint development of optimization models tailored to specific crops or regions, along with technical consulting for precision agriculture implementation. Collaboration with the National Research and Development Agency provides deeper expertise.
Adjacent Application Opportunities
🌲 Green Space & Park Management
Automated Fertilization Planning System
Applying this technology to green space management, such as urban parks, golf course lawns, and street trees, could automate optimal fertilization planning based on soil conditions and plant growth. This has the potential to reduce fertilizer costs by ~15-20% and enhance landscape maintenance efficiency.
🌳 Forestry & Forest Management
Forest Growth Optimization System
In forestry, this technology could be applied to optimize fertilization schedules and thinning times for planted trees, using growth data (e.g., tree height, leaf color) collected by drones. This could contribute to more efficient resource utilization and healthier forest development, potentially improving timber yields by 10-15%.
🧪 Environmental Monitoring
Soil Nutrient Dynamics Prediction
This technology could be adapted to predict soil nutrient dynamics (N, P, K, etc.) based on extensive soil and environmental factor data. This could serve as a decision-support tool for reducing environmental impact and promoting soil conservation, potentially cutting nutrient runoff by ~25%.
Integration Roadmap — Estimated 22-Month Deployment
Phase 1: Technology Validation & Data Integration
Duration: 4 months
Establish data integration interfaces with existing agricultural machinery (drones, sensors) and build data input flows to the technology's calculation unit. Conduct a Proof of Concept (PoC) in a specific field to verify basic performance.
Phase 2: Model Adaptation & Feature Development
Duration: 9 months
Initialize the fertilizer function based on target crop and regional characteristics, enhancing model adaptability with real-world data. Develop user interfaces and add fertilizer map visualization features to improve field usability.
Phase 3: Operational Rollout & Crop Expansion
Duration: 9 months
Begin operational deployment across multiple fields and farms, collecting continuous feedback to further enhance system accuracy and stability. Future expansion could include broadening target crops to address diverse agricultural needs.
Technical Feasibility
This technology is a software-centric system that calculates fertilizer amounts based on field data obtained from machinery. It exhibits high compatibility with existing smart agriculture sensors (e.g., leaf color, soil temperature sensors) and drone imagery. Patent claims explicitly mention 'correction based on measurement item data,' suggesting a design compatible with general-purpose data formats. This indicates that licensees could achieve rapid deployment and early operationalization by integrating it as a software update into existing agricultural infrastructure, without requiring significant capital investment.
Success Scenario
Upon adopting this technology, field data collected by drones and sensors could be automatically fed into the fertilizer calculation system, displaying optimized fertilizer maps on tablets within days. This could reduce the time spent on fertilizer planning, which previously relied on skilled expertise, by ~80% and cut annual fertilizer waste by ~20%. Consequently, crop growth may become more uniform, potentially increasing yields by 10-15%, significantly contributing to sustainable agricultural management and profitability.
Patent Record
APPLICATION NO.
特願2023-133741
REGISTRATION NO.
7591310
FILING DATE
2023/08/21
GRANT DATE
2024/11/20
EXPIRATION DATE
2043/08/21
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
2023年08月21日
出願審査請求書
2024年05月07日
拒絶理由通知書
2024年07月08日
意見書
2024年07月08日
手続補正書（自発・内容）
2024年09月10日
拒絶理由通知書
2024年09月27日
意見書
2024年09月27日
手続補正書（自発・内容）
2024年11月05日
特許査定