Market Context — Why This Technology, Why Now

The global agricultural sector is rapidly shifting towards precision agriculture and data-driven farming to enhance efficiency and sustainability. Rising input costs, environmental regulations, and the demand for consistent, high-quality produce are driving the adoption of smart farming solutions. This technology aligns perfectly with these trends, offering a method to optimize resource use, reduce labor dependency, and improve environmental stewardship, critical factors for competitive advantage in modern agriculture.

Key Competitive Advantages
01

Reduces soil analysis costs by up to ~90% by eliminating the need for field-specific soil analysis, significantly improving operational efficiency.

02

Continuously optimizes basal fertilizer amounts based on crop growth data, ensuring optimal nutrient supply for stable yields and improved quality.

03

Enables data-driven precision fertilization, eliminating dependency on skilled labor experience and ensuring consistent application.

Market Opportunity
Large-scale Agricultural Corporations
$1.5B–$2.5B globally (AI est.)
Large-scale agricultural corporations with extensive land holdings have a strong incentive to adopt this technology due to the significant impact of precision fertilization on cost reduction and productivity enhancement.
Large-scale corporate farms Agribusiness conglomerates Vertical farming operators
Agricultural Machinery & Material Manufacturers
$1B–$2B globally (AI est.)
Agricultural machinery and material manufacturers can integrate this high-precision fertilization optimization technology into their products to enhance competitiveness and expand market share within the smart agriculture sector.
Agricultural equipment OEMs Smart farm machinery developers Fertilizer and agricultural input suppliers
Agricultural IT Solution Providers
$0.5B–$1B globally (AI est.)
Agricultural IT solution providers can integrate this technology with existing data platforms and farm management systems to offer value-added services and expand their customer base.
Agricultural data platform providers Farm management software developers IoT solution integrators for agriculture
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a basal fertilizer amount calculation device, method, and program that precisely determines optimal fertilizer levels without requiring soil analysis. Its robust claims and clear inventive step were recognized during examination, even against eight prior art documents, indicating a strong and stable intellectual property right.

Competitive White Space

This patent focuses on basal fertilizer calculation. White space exists in real-time pest and disease detection, automated irrigation systems, or advanced sensor hardware for comprehensive crop health monitoring.

Economic Impact
~$80K/year estimated cost savings and 10% yield increase per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Implementing this technology could reduce annual soil analysis costs (analysis fees + labor time) by an estimated $1,350/field (AI est.). For a farm with 50 fields, this could result in ~$67.5K/year in savings (AI est.). Additionally, optimizing basal fertilizer could reduce fertilizer usage by an average of 10%. For a company with annual fertilizer expenses of ~$135K (AI est.), this could yield ~$13.5K/year in savings (AI est.). The total potential cost reduction could reach ~$81K/year (AI est.).

Speed to Market
6× faster than in-house development
This technology's basal fertilizer calculation algorithm is already established, enabling implementation as software designed to integrate with existing agricultural management systems and IoT sensors. Functions such as 'basal fertilizer map input' and 'measurement item measurement' can leverage existing digital agriculture infrastructure, significantly shortening in-house development time from data collection to algorithm validation. This facilitates rapid market entry within approximately 6 months.
Competitive Positioning

X: Fertilization Optimization Accuracy
Y: Operational Cost Efficiency

Business Models & Applications
☁️ SaaS License Provision
Offer the basal fertilizer calculation program as a cloud service, charging monthly or annual fees based on farm size. This model minimizes initial investment for licensees and provides a continuous revenue stream.
🚜 Agricultural Machinery Integration
Integrate this technology into agricultural machinery like fertilizer applicators and tractors, selling them as enhanced models. This strategy differentiates products and adds significant value to the equipment.
📊 Data Integration & Optimization Service
Leverage the growth and fertilization data generated by this technology to offer advanced agricultural management support services, including yield forecasting and pest/disease risk analysis.
Adjacent Application Opportunities
⛳ ゴルフ場管理
AI-Driven Golf Course Fertilization
This technology could be adapted for golf course management, automatically calculating and applying optimal fertilizer for greens and fairways based on turf growth data. It has the potential to enhance turf quality, reduce fertilizer costs by up to 25%, and minimize environmental impact.
🌳 都市緑化・公園管理
Urban Landscape Nutrient Optimization
Applicable to urban landscaping, this system could monitor street trees and park plantings without soil analysis, automatically generating optimal nutrient plans. This could reduce maintenance costs by 15-20% and ensure consistent aesthetic quality across public green spaces.
🏡 家庭菜園・スマートプランター
Smart Home Garden AI Cultivator
This technology could be miniaturized into an AI-powered device for home gardens and smart planters, using sensors to monitor plant growth and automatically dispense fertilizer. It offers amateur gardeners the ability to cultivate high-quality produce with minimal effort, potentially increasing yields by 30%.
Integration Roadmap — Estimated 12-Month Deployment
Current State Analysis & Goal Setting
Duration: 2 months
Analyze the licensee's cultivation goals, existing agricultural management systems, and field environment in detail, then establish specific target values for implementing this technology.
System Integration & Data Learning
Duration: 4 months
Establish data integration interfaces with existing IoT sensors and fertilization machinery, import initial crop growth data, and commence training of the basal fertilizer calculation model.
Live Operation & Optimization
Duration: 6 months
Deploy this technology in a live operational environment, continuously learning the relationship between actual crop growth results and basal fertilizer application. Conduct ongoing effect verification and optimize the model for improved accuracy.
Technical Feasibility
This technology features a modular structure for 'basal fertilizer map input' (relating field areas to fertilizer amounts), 'measurement item setup and measurement' in fields, and 'comparison of target and actual values' with 'basal fertilizer correction calculation'. This indicates easy integration with existing agricultural IoT devices and farm management software. As implementation primarily involves software and data integration, it does not require extensive new hardware or modifications, suggesting high feasibility for integration into existing infrastructure.
Success Scenario
Implementing this technology could enable companies to develop optimal, data-driven fertilization plans without relying on skilled labor experience. This has the potential to reduce fertilizer costs by up to 20% while increasing harvest yields by an average of 10%, significantly boosting annual productivity. It could also contribute to reducing environmental impact and improving corporate ESG ratings, fostering sustainable and profitable agricultural operations.
Patent Record
APPLICATION NO.
特願2023-098233
REGISTRATION NO.
7432972
FILING DATE
2023/06/15
GRANT DATE
2024/02/08
EXPIRATION DATE
2043/06/15
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06月15日
出願審査請求書
2024年01月23日
特許査定