Smart Vineyard Management Market by Component (Hardware, Services, Software), Technology (AI Analytics, IoT Sensors, Robotics), Vineyard Size, Application, Deployment - Global Forecast 2025-2032
Description
The Smart Vineyard Management Market was valued at USD 3.78 billion in 2024 and is projected to grow to USD 4.10 billion in 2025, with a CAGR of 8.58%, reaching USD 7.31 billion by 2032.
An evidence-driven introduction to how data, sensors, and analytics are redefining vineyard operations for enhanced crop quality and operational resilience
The precision viticulture landscape is evolving rapidly as growers, technology providers, and agribusinesses converge on data-driven practices to enhance quality, resilience, and operational efficiency. Digital transformation in vineyards is no longer a niche experiment; it is becoming embedded in vineyard operations through integrated hardware, software, and service ecosystems that collect, interpret, and act on environmental and biological data. This integration supports more informed irrigation choices, targeted disease management, and optimized harvest timing, all of which directly influence crop quality and input efficiency.
Transitioning from traditional, observational decision-making to evidence-based management requires not only sensor deployment and analytics, but also changes in organizational workflows and farmer mindsets. Success is determined by the interoperability of hardware components, the usability of software platforms, and the availability of advisory services that bridge technical capability with practical farming knowledge. As a result, stakeholders across the value chain-from equipment manufacturers to agronomists-are redefining roles and collaborating to deliver end-to-end solutions that align agronomic goals with commercial realities.
How advancements in sensing, analytics, autonomy, and supportive services are converging to transform vineyard management practices and decision-making processes
Multiple transformative shifts are reshaping the vineyard management ecosystem, driven by advances in sensors, connectivity, analytics, and automation. Edge-capable IoT sensors and resilient connectivity options allow near-real-time monitoring of soil moisture, canopy conditions, and microclimates, enabling managers to move from reactive interventions to proactive and predictive practices. Concurrently, AI-driven analytics and decision-support tools are transforming raw telemetry into prescriptive insights, offering clear recommendations for irrigation, disease mitigation, and harvest scheduling.
Robotics and unmanned aerial vehicles are extending the reach of agronomic teams, performing tasks from targeted spraying to high-resolution imaging that reveals early stress indicators. Cloud-native platforms and modular on-premise solutions are broadening deployment options, making sophisticated analytics accessible to both large estates and smaller growers. These shifts are complemented by a growing services ecosystem-consulting, training, and support-that helps translate technology outputs into agronomic actions. Ultimately, the combination of sensor proliferation, smarter analytics, and service-led adoption is accelerating operational change while raising expectations for interoperability, data governance, and outcomes-based service models.
Strategic implications of recent US tariff measures on procurement, supplier strategies, and technology adoption dynamics across the vineyard technology supply chain
The evolving tariff landscape in the United States introduces new considerations for players involved in cross-border supply chains for viticulture technologies, components, and services. Tariffs affect sourcing strategies for hardware elements such as connectivity modules, controllers, and imaging sensors, and can influence vendor selection and inventory planning decisions. Organizations are responding by reassessing supplier diversification, exploring nearshoring alternatives, and evaluating long-term contractual structures to mitigate exposure to sudden changes in trade policy.
These trade-related shifts also have downstream effects on procurement cycles and adoption timelines. Equipment manufacturers and integrators may adjust price lists, absorb incremental costs through margin strategies, or redesign product configurations to use locally sourced components when feasible. For growers and service providers, total cost of deployment and replacement cycles become more prominent factors in technology selection, thereby influencing the pace at which new systems are adopted. In this environment, strategic sourcing, flexible deployment models, and clear value articulation will be essential to sustain technology uptake and support resilient vineyard operations.
Comprehensive segmentation insights connecting components, applications, technologies, deployment models, and vineyard scale to strategic product and service priorities
Segment-level differentiation reveals where investment and innovation are concentrated, and helps stakeholders prioritize product development and go-to-market strategies. Component segmentation uncovers distinct demand drivers for hardware, services, and software. Within hardware, connectivity modules demand attention for cellular, LoRaWAN, and Wi‑Fi options that match vineyard topology and scale, while controllers and a diverse array of sensors-from imaging systems to soil moisture probes and weather stations-serve discrete monitoring and actuation needs. Services such as consulting, support and maintenance, and training are critical to bridge the gap between technology capability and agronomic practice, ensuring sustained adoption and value realization. Software segmentation highlights the need for robust data analytics platforms, intuitive decision support tools, and comprehensive farm management platforms that synthesize sensor streams into actionable workflows.
Application-oriented segmentation demonstrates how use cases determine technology and service mixes; crop monitoring and disease detection emphasize sensor fidelity and analytics sensitivity, harvest management and irrigation management require precise actuation and scheduling capabilities, while yield prediction leans heavily on historical data integration and model calibration. Technology segmentation distinguishes AI analytics, IoT sensors, robotics, and UAV imaging with UAV capabilities split across multi-spectral, RGB, and thermal imaging-each providing complementary insight into vine health and microclimate. Deployment preferences between cloud and on-premise solutions influence latency, data residency, and integration considerations, while vineyard size-ranging from large estates to small and medium holdings-shapes purchasing power, preferred pricing models, and the degree of customization required. Together, these segment lenses create a multidimensional view of where solutions must evolve to meet diverse grower needs and operational constraints.
Regional dynamics shaping adoption, support ecosystems, and technology priorities across the Americas, Europe Middle East & Africa, and Asia-Pacific viticulture landscapes
Regional dynamics vary considerably and influence technology adoption, regulatory considerations, and support ecosystems. In the Americas, growers benefit from mature precision-agriculture supplier networks, a high penetration of cellular connectivity in many regions, and strong demand for analytics that support irrigation efficiency and disease management; however, adoption heterogeneity exists between large commercial estates and fragmented smallholder operations. Europe, the Middle East & Africa encompasses a diverse set of regulatory regimes and climatologies; advanced viticulture regions often lead on high-resolution imaging and integrated farm management platforms, while water-stressed areas prioritize irrigation management and drought-resilient practices. In the broader Africa and Middle East contexts, access to connectivity and localized support services can be limiting factors, driving interest in low-power wide-area networking and service delivery models that emphasize training and remote support.
Asia-Pacific presents a mix of rapidly modernizing production zones and traditional smallholder operations. High-growth pockets within the region show strong uptake of UAV imaging and AI analytics, particularly where export-oriented quality standards reward precision interventions. Across regions, local channel partners, availability of financing, and regulatory frameworks for data and drone operations play pivotal roles in shaping adoption curves. Understanding these regional contours enables solution providers and investors to tailor offerings that address specific infrastructure constraints, agronomic priorities, and commercial incentives.
Vendor differentiation and partnership models that combine hardware reliability, validated analytics, and service-led approaches to accelerate adoption and sustain customer success
Companies operating in the vineyard technology space are differentiating along several axes: product breadth and depth, integration capabilities, agronomic validity, and service delivery models. Market leaders typically combine sensor reliability with strong data ingestion pipelines and analytics that are validated against field trials and agronomic benchmarks. Mid-tier providers often compete on ease of deployment, cost-effectiveness, and localized service networks, catering to growers who require rapid time to benefit without extensive customization. Emerging vendors focus on specialized capabilities such as advanced imaging modalities, robotics for labor-constrained tasks, or niche decision-support algorithms tailored to specific disease pressures or varietal characteristics.
Partnerships between hardware manufacturers, software integrators, and advisory services are increasingly common, enabling bundled solutions that reduce implementation complexity for end users. Strategic alliances with research institutions and extension services help vendors demonstrate agronomic efficacy and accelerate credibility. Additionally, vendor strategies that emphasize modular offerings-allowing growers to start with a sensor or analytics module and progressively expand-tend to lower entry barriers and support wider adoption. High-performing companies also invest in training, after-sales support, and local presence to ensure sustained customer success and to convert early trials into long-term deployments.
Practical recommendations for industry leaders to accelerate adoption through interoperability, service-driven engagement, modular commercial models, and resilient sourcing
Leaders in the vineyard technology ecosystem should adopt an action-oriented approach that balances product innovation with practical deployment strategies. First, prioritize interoperability and standards-based connectivity to ensure sensors, controllers, and platforms can integrate with existing vineyard systems and future devices. Second, invest in service offerings-consulting, training, and long-term support-that enable growers to translate data into agronomic decisions and sustained operational change. Third, design modular commercial models that accommodate both large estates seeking full-stack solutions and smaller holdings that prefer phased adoption with lower upfront costs.
Additionally, build resilience into supply chains by diversifying sourcing and considering local assembly or component substitution where tariffs or trade disruptions create risk. Emphasize field validation and transparent performance metrics to strengthen credibility; growers adopt technologies more readily when benefits are demonstrable in comparable contexts. Finally, cultivate partnerships with local agronomic advisors and extension networks to scale adoption through trusted channels, and invest in user-centric interfaces and workflows that reduce technical friction and accelerate time to actionable insight.
A mixed-methods research approach integrating primary interviews, field validations, and rigorous secondary analysis to ensure evidence-based precision viticulture insights
The research underpinning these insights combined primary qualitative interviews, secondary literature review, and structured field evaluations to build a holistic perspective on technology adoption and operational impact in vineyards. Primary engagements included discussions with grower groups, agronomists, technology vendors, and channel partners to capture practical deployment experiences, pain points, and success factors. Field evaluations assessed sensor performance, data fidelity, and integration workflows across representative vineyard topographies and varietal profiles to validate the operational applicability of proposed solutions.
Secondary research synthesized technical white papers, peer-reviewed agronomic studies, regulatory guidance on drone and data operations, and vendor product specifications to contextualize primary findings. Triangulation across these sources emphasized corroboration of claims, assessment of real-world constraints, and identification of scalable practices. Data integrity and reproducibility were reinforced by documenting evaluation protocols, calibration procedures for imaging and soil sensors, and criteria for selecting representative case studies. This mixed-methods approach supports a balanced, evidence-based set of conclusions that are grounded in both empirical testing and stakeholder perspectives.
Concluding synthesis on why integration, validation, and service-driven adoption are essential to unlock the full potential of precision viticulture
Precision viticulture represents a foundational shift in how vineyards are managed, moving from generalized assumptions to targeted, data-informed practices that enhance quality, reduce waste, and improve resilience. The interplay of advanced sensors, adaptive connectivity, analytic engines, and service delivery creates an ecosystem capable of addressing core grower priorities such as water efficiency, disease prevention, and optimized harvest timing. Realizing these benefits depends on more than technology alone; success hinges on integration, vendor accountability, and the translation of insights into agronomic actions through effective training and support.
As stakeholders navigate procurement, deployment, and scale-up decisions, attention to interoperability, field-validated performance, and flexible commercial models will determine who captures value in this evolving landscape. Regions and grower segments differ in priorities and constraints, so tailored strategies that align technology capabilities with local agronomy and operational realities will outperform one-size-fits-all approaches. Ultimately, the promise of precision viticulture lies in its capacity to make vineyard management more predictable, sustainable, and aligned with premium quality outcomes.
Note: PDF & Excel + Online Access - 1 Year
An evidence-driven introduction to how data, sensors, and analytics are redefining vineyard operations for enhanced crop quality and operational resilience
The precision viticulture landscape is evolving rapidly as growers, technology providers, and agribusinesses converge on data-driven practices to enhance quality, resilience, and operational efficiency. Digital transformation in vineyards is no longer a niche experiment; it is becoming embedded in vineyard operations through integrated hardware, software, and service ecosystems that collect, interpret, and act on environmental and biological data. This integration supports more informed irrigation choices, targeted disease management, and optimized harvest timing, all of which directly influence crop quality and input efficiency.
Transitioning from traditional, observational decision-making to evidence-based management requires not only sensor deployment and analytics, but also changes in organizational workflows and farmer mindsets. Success is determined by the interoperability of hardware components, the usability of software platforms, and the availability of advisory services that bridge technical capability with practical farming knowledge. As a result, stakeholders across the value chain-from equipment manufacturers to agronomists-are redefining roles and collaborating to deliver end-to-end solutions that align agronomic goals with commercial realities.
How advancements in sensing, analytics, autonomy, and supportive services are converging to transform vineyard management practices and decision-making processes
Multiple transformative shifts are reshaping the vineyard management ecosystem, driven by advances in sensors, connectivity, analytics, and automation. Edge-capable IoT sensors and resilient connectivity options allow near-real-time monitoring of soil moisture, canopy conditions, and microclimates, enabling managers to move from reactive interventions to proactive and predictive practices. Concurrently, AI-driven analytics and decision-support tools are transforming raw telemetry into prescriptive insights, offering clear recommendations for irrigation, disease mitigation, and harvest scheduling.
Robotics and unmanned aerial vehicles are extending the reach of agronomic teams, performing tasks from targeted spraying to high-resolution imaging that reveals early stress indicators. Cloud-native platforms and modular on-premise solutions are broadening deployment options, making sophisticated analytics accessible to both large estates and smaller growers. These shifts are complemented by a growing services ecosystem-consulting, training, and support-that helps translate technology outputs into agronomic actions. Ultimately, the combination of sensor proliferation, smarter analytics, and service-led adoption is accelerating operational change while raising expectations for interoperability, data governance, and outcomes-based service models.
Strategic implications of recent US tariff measures on procurement, supplier strategies, and technology adoption dynamics across the vineyard technology supply chain
The evolving tariff landscape in the United States introduces new considerations for players involved in cross-border supply chains for viticulture technologies, components, and services. Tariffs affect sourcing strategies for hardware elements such as connectivity modules, controllers, and imaging sensors, and can influence vendor selection and inventory planning decisions. Organizations are responding by reassessing supplier diversification, exploring nearshoring alternatives, and evaluating long-term contractual structures to mitigate exposure to sudden changes in trade policy.
These trade-related shifts also have downstream effects on procurement cycles and adoption timelines. Equipment manufacturers and integrators may adjust price lists, absorb incremental costs through margin strategies, or redesign product configurations to use locally sourced components when feasible. For growers and service providers, total cost of deployment and replacement cycles become more prominent factors in technology selection, thereby influencing the pace at which new systems are adopted. In this environment, strategic sourcing, flexible deployment models, and clear value articulation will be essential to sustain technology uptake and support resilient vineyard operations.
Comprehensive segmentation insights connecting components, applications, technologies, deployment models, and vineyard scale to strategic product and service priorities
Segment-level differentiation reveals where investment and innovation are concentrated, and helps stakeholders prioritize product development and go-to-market strategies. Component segmentation uncovers distinct demand drivers for hardware, services, and software. Within hardware, connectivity modules demand attention for cellular, LoRaWAN, and Wi‑Fi options that match vineyard topology and scale, while controllers and a diverse array of sensors-from imaging systems to soil moisture probes and weather stations-serve discrete monitoring and actuation needs. Services such as consulting, support and maintenance, and training are critical to bridge the gap between technology capability and agronomic practice, ensuring sustained adoption and value realization. Software segmentation highlights the need for robust data analytics platforms, intuitive decision support tools, and comprehensive farm management platforms that synthesize sensor streams into actionable workflows.
Application-oriented segmentation demonstrates how use cases determine technology and service mixes; crop monitoring and disease detection emphasize sensor fidelity and analytics sensitivity, harvest management and irrigation management require precise actuation and scheduling capabilities, while yield prediction leans heavily on historical data integration and model calibration. Technology segmentation distinguishes AI analytics, IoT sensors, robotics, and UAV imaging with UAV capabilities split across multi-spectral, RGB, and thermal imaging-each providing complementary insight into vine health and microclimate. Deployment preferences between cloud and on-premise solutions influence latency, data residency, and integration considerations, while vineyard size-ranging from large estates to small and medium holdings-shapes purchasing power, preferred pricing models, and the degree of customization required. Together, these segment lenses create a multidimensional view of where solutions must evolve to meet diverse grower needs and operational constraints.
Regional dynamics shaping adoption, support ecosystems, and technology priorities across the Americas, Europe Middle East & Africa, and Asia-Pacific viticulture landscapes
Regional dynamics vary considerably and influence technology adoption, regulatory considerations, and support ecosystems. In the Americas, growers benefit from mature precision-agriculture supplier networks, a high penetration of cellular connectivity in many regions, and strong demand for analytics that support irrigation efficiency and disease management; however, adoption heterogeneity exists between large commercial estates and fragmented smallholder operations. Europe, the Middle East & Africa encompasses a diverse set of regulatory regimes and climatologies; advanced viticulture regions often lead on high-resolution imaging and integrated farm management platforms, while water-stressed areas prioritize irrigation management and drought-resilient practices. In the broader Africa and Middle East contexts, access to connectivity and localized support services can be limiting factors, driving interest in low-power wide-area networking and service delivery models that emphasize training and remote support.
Asia-Pacific presents a mix of rapidly modernizing production zones and traditional smallholder operations. High-growth pockets within the region show strong uptake of UAV imaging and AI analytics, particularly where export-oriented quality standards reward precision interventions. Across regions, local channel partners, availability of financing, and regulatory frameworks for data and drone operations play pivotal roles in shaping adoption curves. Understanding these regional contours enables solution providers and investors to tailor offerings that address specific infrastructure constraints, agronomic priorities, and commercial incentives.
Vendor differentiation and partnership models that combine hardware reliability, validated analytics, and service-led approaches to accelerate adoption and sustain customer success
Companies operating in the vineyard technology space are differentiating along several axes: product breadth and depth, integration capabilities, agronomic validity, and service delivery models. Market leaders typically combine sensor reliability with strong data ingestion pipelines and analytics that are validated against field trials and agronomic benchmarks. Mid-tier providers often compete on ease of deployment, cost-effectiveness, and localized service networks, catering to growers who require rapid time to benefit without extensive customization. Emerging vendors focus on specialized capabilities such as advanced imaging modalities, robotics for labor-constrained tasks, or niche decision-support algorithms tailored to specific disease pressures or varietal characteristics.
Partnerships between hardware manufacturers, software integrators, and advisory services are increasingly common, enabling bundled solutions that reduce implementation complexity for end users. Strategic alliances with research institutions and extension services help vendors demonstrate agronomic efficacy and accelerate credibility. Additionally, vendor strategies that emphasize modular offerings-allowing growers to start with a sensor or analytics module and progressively expand-tend to lower entry barriers and support wider adoption. High-performing companies also invest in training, after-sales support, and local presence to ensure sustained customer success and to convert early trials into long-term deployments.
Practical recommendations for industry leaders to accelerate adoption through interoperability, service-driven engagement, modular commercial models, and resilient sourcing
Leaders in the vineyard technology ecosystem should adopt an action-oriented approach that balances product innovation with practical deployment strategies. First, prioritize interoperability and standards-based connectivity to ensure sensors, controllers, and platforms can integrate with existing vineyard systems and future devices. Second, invest in service offerings-consulting, training, and long-term support-that enable growers to translate data into agronomic decisions and sustained operational change. Third, design modular commercial models that accommodate both large estates seeking full-stack solutions and smaller holdings that prefer phased adoption with lower upfront costs.
Additionally, build resilience into supply chains by diversifying sourcing and considering local assembly or component substitution where tariffs or trade disruptions create risk. Emphasize field validation and transparent performance metrics to strengthen credibility; growers adopt technologies more readily when benefits are demonstrable in comparable contexts. Finally, cultivate partnerships with local agronomic advisors and extension networks to scale adoption through trusted channels, and invest in user-centric interfaces and workflows that reduce technical friction and accelerate time to actionable insight.
A mixed-methods research approach integrating primary interviews, field validations, and rigorous secondary analysis to ensure evidence-based precision viticulture insights
The research underpinning these insights combined primary qualitative interviews, secondary literature review, and structured field evaluations to build a holistic perspective on technology adoption and operational impact in vineyards. Primary engagements included discussions with grower groups, agronomists, technology vendors, and channel partners to capture practical deployment experiences, pain points, and success factors. Field evaluations assessed sensor performance, data fidelity, and integration workflows across representative vineyard topographies and varietal profiles to validate the operational applicability of proposed solutions.
Secondary research synthesized technical white papers, peer-reviewed agronomic studies, regulatory guidance on drone and data operations, and vendor product specifications to contextualize primary findings. Triangulation across these sources emphasized corroboration of claims, assessment of real-world constraints, and identification of scalable practices. Data integrity and reproducibility were reinforced by documenting evaluation protocols, calibration procedures for imaging and soil sensors, and criteria for selecting representative case studies. This mixed-methods approach supports a balanced, evidence-based set of conclusions that are grounded in both empirical testing and stakeholder perspectives.
Concluding synthesis on why integration, validation, and service-driven adoption are essential to unlock the full potential of precision viticulture
Precision viticulture represents a foundational shift in how vineyards are managed, moving from generalized assumptions to targeted, data-informed practices that enhance quality, reduce waste, and improve resilience. The interplay of advanced sensors, adaptive connectivity, analytic engines, and service delivery creates an ecosystem capable of addressing core grower priorities such as water efficiency, disease prevention, and optimized harvest timing. Realizing these benefits depends on more than technology alone; success hinges on integration, vendor accountability, and the translation of insights into agronomic actions through effective training and support.
As stakeholders navigate procurement, deployment, and scale-up decisions, attention to interoperability, field-validated performance, and flexible commercial models will determine who captures value in this evolving landscape. Regions and grower segments differ in priorities and constraints, so tailored strategies that align technology capabilities with local agronomy and operational realities will outperform one-size-fits-all approaches. Ultimately, the promise of precision viticulture lies in its capacity to make vineyard management more predictable, sustainable, and aligned with premium quality outcomes.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
188 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Integration of IoT soil moisture sensors with AI-driven irrigation scheduling to optimize water use in vineyards
- 5.2. Adoption of drone-based multispectral imaging for early disease detection and canopy health monitoring in vineyards
- 5.3. Deployment of blockchain-enabled traceability platforms for transparent wine supply chain management
- 5.4. Implementation of autonomous ground vehicles for precision pesticide application in sensitive vineyard terrains
- 5.5. Use of predictive analytics models combining weather forecasts and historical yield data to forecast optimal harvest timing
- 5.6. Integration of solar-powered wireless sensor networks for real-time microclimate monitoring across vineyard blocks
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Smart Vineyard Management Market, by Component
- 8.1. Hardware
- 8.1.1. Connectivity Modules
- 8.1.1.1. Cellular Modules
- 8.1.1.2. LoRaWAN Modules
- 8.1.1.3. Wi-Fi Modules
- 8.1.2. Controllers
- 8.1.3. Sensors
- 8.1.3.1. Imaging Sensors
- 8.1.3.2. Soil Moisture
- 8.1.3.3. Weather Stations
- 8.2. Services
- 8.2.1. Consulting Services
- 8.2.2. Support And Maintenance
- 8.2.3. Training Services
- 8.3. Software
- 8.3.1. Data Analytics Platforms
- 8.3.2. Decision Support Tools
- 8.3.3. Farm Management Platforms
- 9. Smart Vineyard Management Market, by Technology
- 9.1. AI Analytics
- 9.2. IoT Sensors
- 9.3. Robotics
- 9.4. UAV Imaging
- 9.4.1. Multi-Spectral Imaging
- 9.4.2. RGB Imaging
- 9.4.3. Thermal Imaging
- 10. Smart Vineyard Management Market, by Vineyard Size
- 10.1. Large
- 10.2. Small And Medium
- 11. Smart Vineyard Management Market, by Application
- 11.1. Crop Monitoring
- 11.2. Disease Detection
- 11.3. Harvest Management
- 11.4. Irrigation Management
- 11.5. Yield Prediction
- 12. Smart Vineyard Management Market, by Deployment
- 12.1. Cloud
- 12.2. On-Premise
- 13. Smart Vineyard Management Market, by Region
- 13.1. Americas
- 13.1.1. North America
- 13.1.2. Latin America
- 13.2. Europe, Middle East & Africa
- 13.2.1. Europe
- 13.2.2. Middle East
- 13.2.3. Africa
- 13.3. Asia-Pacific
- 14. Smart Vineyard Management Market, by Group
- 14.1. ASEAN
- 14.2. GCC
- 14.3. European Union
- 14.4. BRICS
- 14.5. G7
- 14.6. NATO
- 15. Smart Vineyard Management Market, by Country
- 15.1. United States
- 15.2. Canada
- 15.3. Mexico
- 15.4. Brazil
- 15.5. United Kingdom
- 15.6. Germany
- 15.7. France
- 15.8. Russia
- 15.9. Italy
- 15.10. Spain
- 15.11. China
- 15.12. India
- 15.13. Japan
- 15.14. Australia
- 15.15. South Korea
- 16. Competitive Landscape
- 16.1. Market Share Analysis, 2024
- 16.2. FPNV Positioning Matrix, 2024
- 16.3. Competitive Analysis
- 16.3.1. Advance Management Systems Ltd.
- 16.3.2. AgCode. Inc.
- 16.3.3. AGRIVI Ltd.
- 16.3.4. AHA Viticulture
- 16.3.5. DeVineWare
- 16.3.6. Elmibit d.o.o.
- 16.3.7. GRAPEGEARS
- 16.3.8. IVISsoftware
- 16.3.9. Microworkers Technologies Inc.
- 16.3.10. Orion Wine Software
- 16.3.11. PrecisionHawk, Inc.
- 16.3.12. Process2wine
- 16.3.13. SureHarvest Services, LLC
- 16.3.14. TeeJet Technologies
- 16.3.15. TracMap Limited
- 16.3.16. Trimble Inc.
- 16.3.17. VineView
- 16.3.18. Vinsight Software
- 16.3.19. VinSuite
- 16.3.20. Vintegrate
- 16.3.21. WineDirect
- 16.3.22. YANMAR HOLDINGS CO., LTD.
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