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시장보고서
상품코드
2083431
정밀 포도 재배 시장 : 구성 요소, 기술, 용도, 최종 사용자, 배포 모드별 - 세계 시장 예측(2026-2032년)Precision Viticulture Market by Component, Technology, Application, End User, Deployment Mode - Global Forecast 2026-2032 |
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360iResearch
정밀 포도 재배 시장은 2032년까지 연평균 복합 성장률(CAGR) 11.34%로 성장해 40억 9,000만 달러 규모로 확대될 것으로 예측됩니다.
| 주요 시장 통계 | |
|---|---|
| 기준 연도(2025년) | 19억 2,000만 달러 |
| 추정 연도(2026년) | 21억 3,000만 달러 |
| 예측 연도(2032년) | 40억 9,000만 달러 |
| CAGR(%) | 11.34% |
정밀 포도 재배는 틈새 농업 기술 분야에서 포도 재배 농가, 와이너리, 협동조합, 자재 공급업체, 농업 기술 제공업체를 위한 전략적 운영 모델로 전환되고 있습니다. 이 분야는 명확한 운영상의 필요에 따라 형성되었습니다. 즉, 포도원은 기후 변동이 더욱 심한 조건에서 운영되는 가운데, 수확량 예측 가능성, 과실 품질, 노동 생산성, 물 이용 효율 및 병해 방제를 개선해야 합니다.
국제포도·와인기구(OIV)의 공개 자료에 따르면, 전 세계 포도원 면적은 여전히 주요 와인 생산 지역에 집중되어 있지만, 최근 몇 년간의 수확은 가뭄, 폭염, 서리, 산불 연기와 극심한 강우의 영향을 크게 받고 있습니다. 이러한 배경 하에, 정밀 포도 재배에서는 원격 감지, 포도원 매핑, 토양 및 수관 분석, 기상 관측소, 가변 시비 기술, 로봇 공학, 의사결정 지원 소프트웨어를 활용하여 포도밭의 변동성을 실질적인 관리 판단으로 전환하고 있습니다.
시장 분석의 관점에서 볼 때, 이 분야를 정의하는 가장 중요한 키워드로는 정밀 포도 재배, 스마트 포도원 관리, 포도원 원격 감지, 포도 재배에 적용된 AI, 포도원 모니터링 시스템, 가변 시비 기술, 와이너리용 디지털 농업, 그리고 기후 스마트형 포도 재배 등이 있습니다.
정밀 포도 재배 동향의 획기적인 변화
정밀 포도 재배 분야는 기후 리스크, 디지털 농업 인프라, 데이터 기반 와인 품질 관리라는 세 가지 요소가 결합되어 혁신이 진행되고 있습니다. 기존의 획일적인 포도원 관리 방식으로는 구획별 생육 상황, 수분 상태, 해충 피해 상황, 수확 시기의 차이를 파악하기 어려운 경우가 많기 때문에 생산자들은 센서, 드론, 위성 이미지, 예측 분석을 도입하고 있습니다.
인공지능이 정밀 포도 재배에 미치는 누적 영향
인공지능은 포도원 관련 단편적인 데이터를 예측적·처방적 인사이트로 전환함으로써 정밀 포도 재배의 가치를 높이고 있습니다. 머신러닝 모델은 과거 기상 데이터, 토양 수분, 수관 이미지, 생물계절학 기록, 병해 관찰 데이터를 분석하여 관개 일정 수립, 흰가루병 및 잎마름병 위험 평가, 수확량 추정, 수확 우선순위 결정 등을 지원합니다.
세계 정밀 포도 재배의 주요 지역별 인사이트
아시아태평양은 호주, 중국, 일본, 한국을 필두로 급속히 발전하고 있는 정밀 포도 재배 지역입니다. 호주에서는 대규모 상업용 포도원, 반복되는 가뭄의 영향, 그리고 잘 구축된 농업 연구 생태계가 원격 감지, 관개 분석, 수확량 추정 및 포도원 구역 설정의 활용을 뒷받침하고 있습니다. 중국에서는 계속해서 규모가 확대되고 있는 와인 산지에서 디지털 농업을 활용하여 입지 선정, 포도원의 균일성, 품질의 일관성을 높이고 있습니다. 한편, 일본과 한국에서는 농업 종사자의 고령화와 적합한 포도원 부지 부족 문제에 대응하기 위해 고부가가치 생산, 자동화 및 노동력 절감 기술에 중점을 두고 있습니다.
정밀 포도 재배 도입을 주도하는 주요 그룹에 대한 인사이트
아세안 지역은 정밀 포도 재배에 있어 새로운 기회를 안고 있습니다. 특히, 병해의 위협, 습도, 지역별 기후 변화로 인해 치밀한 모니터링이 필요한 틈새 시장인 열대 및 고지대 포도 재배 분야에서 그 가능성은 높습니다. 도입에 있어서는 대규모 포도원의 기계화보다는 보호 재배, 기상 분석, 병해 예측, 그리고 소규모 농가를 위한 디지털 자문 도구에 중점을 둘 것으로 보입니다.
정밀 포도 재배의 성장을 위한 주요 국가의 인사이트
미국은 고급 와인 산지, 선진적인 디지털 농업의 도입, 대학을 통한 광범위한 보급 지원, 그리고 물 관리, 병해 관리, 연기 피해 위험 관리, 인력 관리 도구에 대한 강력한 수요 덕분에 정밀 포도 재배 도입 분야에서 세계를 선도하고 있습니다. 캐나다에서는 브리티시컬럼비아주나 온타리오주 등의 지역에서 서늘한 기후 하의 포도 재배, 겨울철 피해 위험, 병해 압력, 품질 향상을 위한 관리에 정밀 도구를 활용하고 있습니다. 바하 캘리포니아주를 포함한 멕시코의 와인 산지에서는 물 부족 문제, 포도원 간 편차, 프리미엄화 추세에 대응하기 위해 관개 및 기후 모니터링 시스템이 도입되고 있습니다.
정밀 포도 재배의 선도자를 위한 실천적 제안
업계 리더는 원격 감지, 지상 센서, 기상 데이터, 현장 관측, 기계 데이터를 단일 운영 워크플로우로 통합하는 통합형 포도원 인텔리전스 플랫폼을 우선적으로 도입해야 합니다. 관개, 살포, 수관 관리, 규정 준수 관련 서류, 수확 및 물류와 관련해 생산자가 보다 신속한 의사 결정을 내려야 할 경우, 단일 도구만으로는 경쟁력이 떨어집니다.
정밀 포도 재배에 관한 지식 조사 방법
본 요약본은 널리 인정받는 시장 정보 분석 관행에 따라, 2차 조사를 중심으로 한 조사 기법을 사용하여 작성되었습니다. 분석에는 국제포도·와인기구(OIV)의 데이터, 유엔 식량농업기구(FAO)의 농업 관련 자료, 각국의 통계 기관, 대학의 보급·계몽 간행물, 와인 업계 단체, 지속가능성 프레임워크, 그리고 원격 감지, 인공지능, 디지털 농업 분야의 문서화된 진전 등, 일반적으로 공개되어 기관 차원에서 신뢰성이 높은 정보원이 활용되고 있습니다.
결론 : 정밀 포도 재배의 미래
정밀 포도 재배는 전 세계 와인 및 포도 밸류체인 전반에 걸쳐 기후 변화에 대한 저항력, 고품질 포도 생산, 그리고 운영 효율성을 실현하기 위한 핵심 요소로 자리 잡고 있습니다. 기후 변동이 심화되고 노동력, 물, 투입 비용에 대한 압박이 커지는 가운데, 생산자들은 점점 더 데이터 기반의 포도원 관리 방식으로 전환하고 있습니다.
자주 묻는 질문
목차
제1장 서문
제2장 조사 방법
제3장 주요 요약
제4장 시장 개요
제5장 시장 인사이트
제6장 AI의 누적 영향(2026년)
제7장 정밀 포도 재배 시장 : 구성 요소별
제8장 정밀 포도 재배 시장 : 기술별
제9장 정밀 포도 재배 시장 : 용도별
제10장 정밀 포도 재배 시장 : 최종 사용자별
제11장 정밀 포도 재배 시장 : 도입 모드별
제12장 정밀 포도 재배 시장 : 지역별
제13장 정밀 포도 재배 시장 : 그룹별
제14장 정밀 포도 재배 시장 : 국가별
제15장 경쟁 구도
제16장 기업 개요
KTH 26.07.15The Precision Viticulture Market is projected to grow by USD 4.09 billion at a CAGR of 11.34% by 2032.
| KEY MARKET STATISTICS | |
|---|---|
| Base Year [2025] | USD 1.92 billion |
| Estimated Year [2026] | USD 2.13 billion |
| Forecast Year [2032] | USD 4.09 billion |
| CAGR (%) | 11.34% |
Precision viticulture is moving from a niche farm technology category to a strategic operating model for grape growers, wineries, cooperatives, input suppliers, and agricultural technology providers. The sector is shaped by a clear operational need: vineyards must improve yield predictability, fruit quality, labor productivity, water efficiency, and disease control while operating under more volatile climate conditions.
Public data from the International Organisation of Vine and Wine shows that the global vineyard surface remains concentrated across established wine-producing regions, while recent harvests have been heavily affected by drought, heat, frost, wildfire smoke, and extreme rainfall. Against this backdrop, precision viticulture uses remote sensing, vineyard mapping, soil and canopy analytics, weather stations, variable-rate application, robotics, and decision-support software to convert field variability into actionable management decisions.
For market intelligence purposes, the most important keywords defining this landscape include precision viticulture, smart vineyard management, vineyard remote sensing, AI in viticulture, vineyard monitoring systems, variable-rate technology, digital agriculture for wineries, and climate-smart viticulture.
Transformative Shifts in the Precision Viticulture Landscape
The precision viticulture landscape is being transformed by three converging forces: climate risk, digital farm infrastructure, and data-driven wine quality management. Growers are adopting sensors, drones, satellite imagery, and predictive analytics because traditional uniform vineyard practices often fail to capture block-level differences in vigor, water status, pest pressure, and harvest timing.
Satellite and aerial imagery have become more commercially practical as revisit frequency, image resolution, and cloud-based analytics improve. At the same time, soil moisture probes, automated weather stations, and canopy sensors are helping growers make more targeted irrigation, spraying, pruning, and harvest decisions. These tools are especially important in high-value wine grape regions where small changes in ripeness, canopy density, and disease pressure can materially affect grape quality.
The market is also shifting from hardware-led adoption toward integrated platforms. Buyers increasingly expect interoperability between farm management software, geospatial data, machinery guidance systems, and compliance documentation. This is raising the competitive importance of open data standards, agronomic advisory services, and subscription-based decision support.
Cumulative Impact of Artificial Intelligence on Precision Viticulture
Artificial intelligence is amplifying the value of precision viticulture by turning fragmented vineyard data into predictive and prescriptive insights. Machine learning models can analyze weather history, soil moisture, canopy imagery, phenology records, and disease observations to support decisions on irrigation scheduling, powdery mildew risk, downy mildew risk, crop load estimation, and harvest prioritization.
The cumulative impact of AI is strongest where growers already have reliable data streams. Computer vision can detect vine stress, missing vines, canopy gaps, weed pressure, and cluster development from drone or tractor-mounted imagery. Predictive models can improve labor planning and help wineries align tank capacity, logistics, and grape intake with expected maturity windows.
AI adoption is not without constraints. Model accuracy depends on localized training data, sensor calibration, agronomic validation, and transparent recommendations. Industry leaders are therefore prioritizing explainable AI, field-verified models, cybersecurity, and human-in-the-loop decision-making to ensure that automation supports, rather than replaces, experienced viticulturists.
Key Regional Insights Across Global Precision Viticulture
Asia-Pacific is a fast-evolving precision viticulture region, led by Australia, China, Japan, and South Korea. Australia's large commercial vineyards, recurrent drought exposure, and strong agricultural research ecosystem support the use of remote sensing, irrigation analytics, yield estimation, and vineyard zoning. China's expanding wine regions are using digital agriculture to improve site selection, vineyard uniformity, and quality consistency, while Japan and South Korea emphasize high-value production, automation, and labor-saving technologies in response to aging agricultural workforces and limited suitable vineyard land.
North America remains one of the most mature regions for precision viticulture, with the United States and Canada deploying vineyard sensors, aerial imaging, farm management software, and variable-rate technologies across premium wine regions. California, Washington, Oregon, British Columbia, and Ontario are important adoption centers because they combine high-value grape production with climate pressure, water management needs, wildfire and smoke-risk monitoring, cool-climate risk management, and access to digital agriculture expertise.
Latin America is gaining momentum as Chile, Argentina, Brazil, and Mexico modernize vineyard operations for export competitiveness and climate resilience, particularly through irrigation monitoring, canopy mapping, and disease-risk analytics. Europe remains central to global viticulture, with France, Italy, Spain, Germany, and the United Kingdom using precision tools to improve quality, traceability, pesticide reduction, water stewardship, and sustainability compliance under increasingly stringent agricultural and environmental policies. The Middle East has a smaller but technically advanced opportunity base where controlled irrigation, arid-climate farming expertise, and high-value horticulture systems are critical. Africa, led by South Africa and emerging North African production areas, is adopting precision viticulture to manage water stress, improve fruit quality, strengthen traceability, and support export-oriented production.
Key Group Insights Shaping Precision Viticulture Adoption
ASEAN represents an emerging opportunity for precision viticulture, particularly in niche tropical and highland grape production where disease pressure, humidity, and site-specific climate variation require close monitoring. Adoption is likely to center on protected cultivation, weather analytics, disease forecasting, and smallholder-friendly digital advisory tools rather than large-scale vineyard mechanization.
The GCC is not a traditional wine grape production center, but its relevance comes from arid-land agriculture, controlled-environment systems, desalination-linked irrigation, fertigation, and premium horticulture technologies. These capabilities can influence precision viticulture solutions for water-scarce regions globally. The European Union is one of the most important policy-driven environments for precision viticulture, with sustainability regulation, digital farm records, pesticide reduction goals, water stewardship requirements, and strong wine sector institutions supporting precision agriculture adoption.
BRICS countries provide a diverse development platform, combining China's scale, India's expanding grape cultivation, Brazil's regional wine development, Russia's vineyard modernization, and South Africa's export-oriented production. The G7 includes several advanced wine and technology economies, including the United States, Canada, France, Germany, Italy, Japan, and the United Kingdom, making it important for premium vineyard analytics, AI-enabled farm management, and sustainability-linked digital reporting. NATO countries overlap significantly with North American and European wine regions, where geospatial capabilities, satellite infrastructure, secure communications, and cybersecurity standards indirectly strengthen agricultural technology ecosystems.
Key Country Insights for Precision Viticulture Growth
The United States is a leading precision viticulture adopter due to premium wine regions, advanced digital agriculture deployment, extensive university extension support, and strong demand for water, disease, smoke-risk, and labor management tools. Canada is using precision tools to manage cool-climate viticulture, winter injury risk, disease pressure, and quality improvement in regions such as British Columbia and Ontario. Mexico's wine regions, including Baja California, are adopting irrigation and climate monitoring to address water stress, vineyard variability, and premiumization.
Brazil is investing in vineyard modernization across established and emerging regions, including applications for canopy monitoring, tropical viticulture management, and quality consistency. The United Kingdom is using precision viticulture to support its rapidly developing sparkling wine sector in a cool-climate setting where frost, disease pressure, and harvest timing are critical. Germany and France emphasize quality, traceability, disease management, terroir mapping, and sustainability. Italy and Spain are major adoption environments because of their large vineyard areas, diverse terroirs, and increasing need for water-efficient production. Russia is modernizing selected vineyard regions, with opportunities for monitoring, mechanization, yield stabilization, and cold-climate risk management.
China is scaling digital vineyard management in both established and newer wine regions, with emphasis on site suitability, irrigation efficiency, vineyard uniformity, and quality control. India applies precision tools across table grapes and wine grapes, particularly for irrigation scheduling, disease management, residue compliance, and export quality. Japan and South Korea favor automation, high-quality production, and labor-saving systems suited to smaller, high-value agricultural operations. Australia is one of the most data-driven precision viticulture countries because water scarcity, variable climate conditions, export quality requirements, and applied research strongly support adoption.
Actionable Recommendations for Precision Viticulture Leaders
Industry leaders should prioritize integrated vineyard intelligence platforms that combine remote sensing, ground sensors, weather data, field observations, and machinery data into a single operational workflow. Standalone tools are less competitive when growers need faster decisions on irrigation, spraying, canopy work, compliance documentation, and harvest logistics.
Technology providers should build localized agronomic models, partner with universities and extension networks, and validate AI recommendations under real vineyard conditions. Wineries and growers should begin with high-value use cases such as water management, disease risk forecasting, yield estimation, canopy zoning, input optimization, and harvest prioritization before scaling across broader operations.
Executives should also invest in data governance, interoperability, cybersecurity, and workforce training. The most successful precision viticulture programs combine skilled viticulturists with digital tools that are easy to use, economically justified, field-validated, and aligned with sustainability reporting requirements.
Research Methodology for Precision Viticulture Insights
This executive summary is developed using a secondary research-led methodology aligned with recognized market intelligence practices. The analysis draws on publicly available and institutionally credible sources, including International Organisation of Vine and Wine data, FAO agricultural references, national statistical agencies, university extension publications, wine industry bodies, sustainability frameworks, and documented developments in remote sensing, artificial intelligence, and digital agriculture.
The research approach triangulates regional production patterns, technology adoption drivers, climate risk indicators, policy direction, vineyard management challenges, and commercial deployment trends. Insights are structured to support executive decision-making across technology vendors, vineyard owners, wineries, investors, cooperatives, input suppliers, and strategic planners.
The methodology avoids unsupported market sizing claims and instead emphasizes verifiable indicators, observable adoption patterns, peer-reviewed agronomic knowledge, and evidence-backed implications for the precision viticulture ecosystem.
Conclusion: The Future of Precision Viticulture
Precision viticulture is becoming a core enabler of climate resilience, premium grape quality, and operational efficiency across the global wine and grape value chain. As weather volatility intensifies and labor, water, and input costs remain under pressure, growers are increasingly turning to data-driven vineyard management.
The next phase of industry development will be defined by AI-enabled decision support, integrated software platforms, localized agronomic intelligence, interoperable data systems, and measurable sustainability outcomes. Organizations that combine credible data, practical workflows, field-validated analytics, and trusted agronomic expertise will be best positioned to lead in precision viticulture.
Table of Contents
1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Definition
- 1.3. Market Segmentation & Coverage
- 1.4. Years Considered for the Study
- 1.5. Currency Considered for the Study
- 1.6. Language Considered for the Study
- 1.7. Key Stakeholders
2. Research Methodology
- 2.1. Introduction
- 2.2. Research Design
- 2.2.1. Primary Research
- 2.2.2. Secondary Research
- 2.3. Research Framework
- 2.3.1. Qualitative Analysis
- 2.3.2. Quantitative Analysis
- 2.4. Market Size Estimation
- 2.4.1. Top-Down Approach
- 2.4.2. Bottom-Up Approach
- 2.5. Data Triangulation
- 2.6. Research Outcomes
- 2.7. Research Assumptions
- 2.8. Research Limitations
3. Executive Summary
- 3.1. Introduction
- 3.2. CXO Perspective
- 3.3. Market Size & Growth Trends
- 3.4. Market Share Analysis, 2025
- 3.5. FPNV Positioning Matrix, 2025
- 3.6. New Revenue Opportunities
- 3.7. Next-Generation Business Models
- 3.8. Industry Roadmap
4. Market Overview
- 4.1. Introduction
- 4.2. Industry Ecosystem & Value Chain Analysis
- 4.2.1. Supply-Side Analysis
- 4.2.2. Demand-Side Analysis
- 4.2.3. Stakeholder Analysis
- 4.3. Market Dynamics
- 4.3.1. Key Drivers
- 4.3.2. Key Restraints
- 4.3.3. Key Opportunities
- 4.3.4. Key Challenges
- 4.4. Porter's Five Forces Analysis
- 4.5. PESTLE Analysis
- 4.6. Market Outlook
- 4.6.1. Near-Term Market Outlook (0-2 Years)
- 4.6.2. Medium-Term Market Outlook (3-5 Years)
- 4.6.3. Long-Term Market Outlook (5-10 Years)
- 4.7. Go-to-Market Strategy
5. Market Insights
- 5.1. Consumer Insights & End-User Perspective
- 5.2. Consumer Experience Benchmarking
- 5.3. Opportunity Mapping
- 5.4. Distribution Channel Analysis
- 5.5. Pricing Trend Analysis
- 5.6. Regulatory Compliance & Standards Framework
- 5.7. ESG & Sustainability Analysis
- 5.8. Disruption & Risk Scenarios
- 5.9. Return on Investment & Cost-Benefit Analysis
6. Cumulative Impact of Artificial Intelligence 2026
7. Precision Viticulture Market, by Component
- 7.1. Hardware
- 7.1.1. Actuators
- 7.1.2. Communication Modules
- 7.1.3. Imaging Devices
- 7.1.4. Sensors
- 7.1.4.1. Humidity Sensors
- 7.1.4.2. PH Sensors
- 7.1.4.3. Soil Moisture Sensors
- 7.1.4.4. Temperature Sensors
- 7.2. Services
- 7.2.1. Consulting
- 7.2.2. Integration & Testing
- 7.2.3. Maintenance & Support
- 7.3. Software
- 7.3.1. Farm Management Information Systems (FMIS)
- 7.3.2. Mapping & Visualization
- 7.3.3. Predictive Analytics & Simulation
8. Precision Viticulture Market, by Technology
- 8.1. Data Management Software
- 8.2. GIS and GPS
- 8.2.1. Geospatial Analysis
- 8.2.2. Vineyard Mapping
- 8.3. Remote Sensing
- 8.4. Sensor Technology
- 8.5. Variable Rate Technology (VRT)
- 8.5.1. Variable Rate Fertilization
- 8.5.2. Variable Rate Irrigation
- 8.5.3. Variable Rate Pesticide Application
9. Precision Viticulture Market, by Application
- 9.1. Crop Scouting and Health Monitoring
- 9.2. Harvest Planning
- 9.3. Irrigation Management
- 9.3.1. Drip Irrigation Optimization
- 9.3.2. Spray Irrigation Management
- 9.3.3. Sprinkler Irrigation Control
- 9.4. Pest and Disease Control
- 9.5. Soil Monitoring and Analysis
- 9.6. Yield Monitoring and Forecasting
10. Precision Viticulture Market, by End User
- 10.1. Large-Scale Vineyards & Commercial Wineries
- 10.2. Medium & Small-Scale Vineyards
- 10.3. Research Institutions & Agricultural Bodies
- 10.4. Viticulture Cooperatives & Associations
11. Precision Viticulture Market, by Deployment Mode
- 11.1. Cloud-Based Solutions
- 11.2. On-Premise Solutions
12. Precision Viticulture Market, by Region
- 12.1. Asia-Pacific
- 12.2. North America
- 12.3. Latin America
- 12.4. Europe
- 12.5. Middle East
- 12.6. Africa
13. Precision Viticulture Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
14. Precision Viticulture Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
15. Competitive Landscape
- 15.1. Market Concentration Analysis, 2025
- 15.1.1. Concentration Ratio (CR)
- 15.1.2. Herfindahl Hirschman Index (HHI)
- 15.2. Recent Developments & Impact Analysis, 2025
- 15.3. Product Portfolio Analysis, 2025
- 15.4. Benchmarking Analysis, 2025
16. Company Profiles
- 16.1. Advance Management Systems Ltd.
- 16.2. AGCO Corporation
- 16.3. AgCode. Inc.
- 16.4. AGRIVI Ltd.
- 16.5. AHA Viticulture
- 16.6. ATEKNEA SOLUTIONS CATALONIA S.L.
- 16.7. Atlas Vineyard Management, LLC
- 16.8. CNH Industrial N.V.
- 16.9. Deere & Company
- 16.10. DeVineWare
- 16.11. Elmibit d.o.o.
- 16.12. eVineyard
- 16.13. GRAPEGEARS
- 16.14. Groupe ICV
- 16.15. Hexagon AB
- 16.16. IVISsoftware
- 16.17. Kubota Corporation
- 16.18. Lallemand Inc
- 16.19. Microworkers Technologies Inc.
- 16.20. Orion Wine Software
- 16.21. Process2wine
- 16.22. SureHarvest Services, LLC
