Global Fruit Size Grading Equipment Market Strategic Research Report
By Type: Belt-type, Roller-type
By Application: Fruit Packaging Factory, Fruit Processing Factory, Other
Regional Forecast: Asia Pacific, Latin America, MEA, Europe, North America
Key Players: GREEFA, Aweta, Unitec Group, MAF RODA, ELISAM, Ellips, Futura, Ser.mac, GP Graders, Maf Agrobotic, Sormac, ICOEL, Burg’s Machinefabriek, Tong Engineering, Key Technology, Bühler Group, Raytec Vision, Tolsma-Grisnich, Shibuya Seiki, Eshet Eilon Industries, Reemoon Technology Co., Ltd., Hefei Meyer Optoelectronic Technology Inc.
نظرة عامة
Scope of the Report
The global Fruit Size Grading Equipment market size is predicted to grow from US$ 1,409 million in 2025 to US$ 1,813 million in 2032; it is expected to grow at a CAGR of 3.6% from 2026 to 2032.
In 2025, global Fruit Size Grading Equipment production reached approximately 320 thousand units, with an average global market price of around US$4500 per thousand units. Fruit Size Grading Equipment refers to machinery used to sort and classify fruits according to their physical size, such as diameter, length, width, volume, or overall shape. It typically uses rollers, belts, screens, adjustable gaps, optical sensors, or machine vision systems to separate fruits into different size grades. This equipment is widely used in orchards, fruit packing houses, agricultural cooperatives, food processing plants, and export preparation facilities to improve grading efficiency, standardize packaging specifications, reduce manual sorting errors, and meet retail or export market requirements for uniform fruit appearance and size.
The Fruit Size Grading Equipment market is an important sub-segment of the fruit post-harvest processing equipment industry, mainly serving orchards, fruit packing houses, agricultural cooperatives, fresh produce exporters, cold-chain logistics centers and food processing plants that need to classify fruits by diameter, length, width, volume or overall size uniformity. Compared with general fruit grading equipment, size grading equipment focuses more specifically on physical dimensions, helping operators standardize packaging specifications, improve product appearance consistency, reduce manual sorting errors and support differentiated pricing by grade. The market includes simple mechanical sizers, roller-type graders, belt and gap graders, drum or screen-type graders, cup-type grading machines and advanced optical size grading systems integrated with camera-based measurement. In mature fruit-producing regions, demand is increasingly concentrated on high-speed, low-damage and digitally controlled systems, while in emerging markets, basic mechanical and semi-automatic size graders still account for a significant share because many small and medium-sized farms are upgrading from manual grading to mechanized post-harvest handling. Upstream, the industry relies on stainless steel frames, food-grade plastics, rollers, belts, motors, bearings, reducers, sensors, load cells, PLCs, industrial cameras, lighting systems, servo drives, pneumatic components and control software. For high-end equipment, machine vision, optical sensors and image-processing algorithms are becoming increasingly important, because modern fruit grading systems often combine size measurement with color, shape, defect and maturity recognition. Studies on fruit quality grading have shown that machine vision can be used to estimate attributes such as fruit size, color and external blemishes, supporting more automated and consistent grading decisions. Midstream equipment suppliers compete mainly through grading accuracy, capacity, fruit damage control, flexibility for different fruit varieties, ease of cleaning, modular design, after-sales service and integration capability with washing, drying, waxing, labeling, packing and palletizing lines. Downstream demand is especially strong for apples, citrus, pears, peaches, kiwifruit, mangoes, avocados, cherries, blueberries and other fruits where uniform appearance and size directly influence retail pricing, export acceptance and consumer preference. TOMRA, for example, offers fruit sorting, grading, packing and filling solutions for apples, avocados, blueberries, cherries, citrus, kiwifruit, stonefruit and other categories, reflecting the broad application scope of advanced fruit grading systems. Market growth is mainly driven by rising labor costs, labor shortages during harvest seasons, stricter supermarket and export standards, the expansion of branded fruit sales, growth of fresh e-commerce and the need to reduce post-harvest losses. Size grading also supports more efficient packaging and logistics because fruits can be grouped into standardized cartons, trays or retail packs, improving downstream handling and inventory management. However, the market faces several restraints, including high initial investment for automated lines, seasonal utilization of equipment, calibration requirements, maintenance costs and the difficulty of designing one machine that can handle fruits with very different shapes, skin sensitivity and size ranges. In the future, Fruit Size Grading Equipment will move from simple mechanical size separation toward intelligent, multi-parameter and flexible grading platforms. Optical grading is already a key direction in commercial fruit packing, with suppliers emphasizing speed, gentle handling, blemish detection and sorting accuracy for categories such as citrus. Future systems are expected to combine size grading with weight, color, shape, surface defect, ripeness, firmness and internal quality detection, using AI and multi-view imaging to improve classification accuracy. Recent research also indicates that deep-learning and machine-vision methods can support fruit grading by analyzing attributes such as size, ripeness, health condition and surface quality, although real-world deployment still requires robust datasets and practical validation. Overall, the market outlook is positive, supported by agricultural modernization, post-harvest loss reduction, export-oriented fruit production and the digital transformation of fresh produce supply chains. Suppliers that can provide modular, cost-effective, easy-to-maintain and low-damage size grading solutions for both small farms and large packing plants are likely to gain stronger competitiveness in the coming years.
Key Questions Addressed in this Report
What is the 10-year outlook for the global Fruit Size Grading Equipment market?
What factors are driving Fruit Size Grading Equipment market growth, globally and by region?
Which technologies are poised for the fastest growth by market and region?
How do Fruit Size Grading Equipment market opportunities vary by end market size?
How does Fruit Size Grading Equipment break out by Type, by Application?
This report presents a comprehensive overview of the global Fruit Size Grading Equipment market, covering market size and forecast, segmentation by product type and application, competitive landscape, leading players and regional and country-level outlook.
Segment by Type
- Belt-type
- Roller-type
Segment by Detection Technology
- Optical
- Near-infrared
Segment by Application
- Fruit Packaging Factory
- Fruit Processing Factory
- Other
Who Can Use This Report?
This report is written for decision-makers who need a clear, data-backed view of the global Fruit Size Grading Equipment market:
- Manufacturers, suppliers and solution providers benchmarking their position and planning product, capacity and go-to-market strategy
- Distributors, channel partners and end users in Fruit Packaging Factory, Fruit Processing Factory, Other evaluating demand and sourcing options
- Investors, financial analysts and consultants assessing growth opportunities, competitive dynamics and M&A potential
- Government agencies, industry associations and research institutions tracking industry developments and policy impact
Market snapshot
Global Fruit Size Grading Equipment Market Strategic Research Report snapshot, 2025–2032
© MarketResearchReports.comDisclaimer: The actual data may vary in the final report which undergoes verification check post order confirmation.Segments covered in this report
Table of contents
01Executive Summary
02Industry Overview & Forecast
- 2.1.1 Market Definition and Scope
- 2.1.2 Market Size and Growth Forecast
- 2.1.3 Volume Analysis
- 2.1.4 Segment Outlook by Type
- 2.1.5 Segment Outlook by Application
- 2.1.6 Regional Outlook
- 2.1.7 Structural Developments Shaping the Forecast
- 2.1.8 Forecast Risks and Sensitivities
03Market Segmentation by Type
- 3.1 Market Segmentation by Type
- 3.1.1 Market by Type Overview
- 3.1.2 Belt-type
- 3.1.3 Roller-type
- 3.1.4 Volume Analysis
04Market Segmentation by Application
- 4.1 Market Segmentation by Application
- 4.1.1 Market by Application Overview
- 4.1.2 Fruit Packaging Factory
- 4.1.3 Fruit Processing Factory
- 4.1.4 Other
- 4.1.5 Volume Analysis
05Regional Market Forecast
- Asia Pacific
- North America
- Europe
- Middle East & Africa
- Latin America
06Country-Level Market Forecast
- 6.1 Asia Pacific
- 6.1.1 China
- 6.1.2 Japan
- 6.1.3 Korea
- 6.1.4 Southeast Asia
- 6.1.5 India
- 6.1.6 Australia
- 6.1.7 Rest of Asia Pacific
- 6.2 North America
- 6.2.1 United States
- 6.2.2 Canada
- 6.2.3 Mexico
- 6.2.4 Rest of North America
- 6.3 Europe
- 6.3.1 Germany
- 6.3.2 France
- 6.3.3 UK
- 6.3.4 Italy
- 6.3.5 Russia
- 6.3.6 Rest of Europe
- 6.4 Middle East & Africa
- 6.4.1 Egypt
- 6.4.2 South Africa
- 6.4.3 Israel
- 6.4.4 Turkey
- 6.4.5 GCC Countries
- 6.4.6 Rest of Middle East & Africa
- 6.5 Latin America
- 6.5.1 Brazil
- 6.5.2 Rest of Latin America
07Growth Drivers & Inhibitors
- 7.1 Growth Drivers & Inhibitors
- 7.1.1 Section Overview
- 7.1.2 Growth Drivers
- 7.1.3 Growth Inhibitors
- 7.1.4 Driver and Inhibitor Impact Assessment
- 7.1.5 Analyst Perspective
08Key Company Profiles
- 8.1 GREEFA
- 8.1.1 Company Overview
- 8.1.2 Key Products & Segments
- 8.1.3 Financial Performance (2023–2025)
- 8.1.4 Business Strategy
- 8.1.5 SWOT Analysis
- 8.1.6 Strategic Implications (2026–2032)
- 8.2 Aweta
- 8.2.1 Company Overview
- 8.2.2 Key Products & Segments
- 8.2.3 Financial Performance (2023–2025)
- 8.2.4 Business Strategy
- 8.2.5 SWOT Analysis
- 8.2.6 Strategic Implications (2026–2032)
- 8.3 Unitec Group
- 8.3.1 Company Overview
- 8.3.2 Key Products & Segments
- 8.3.3 Financial Performance (2023–2025)
- 8.3.4 Business Strategy
- 8.3.5 SWOT Analysis
- 8.3.6 Strategic Implications (2026–2032)
- 8.4 MAF RODA
- 8.4.1 Company Overview
- 8.4.2 Key Products & Segments
- 8.4.3 Financial Performance (2023–2025)
- 8.4.4 Business Strategy
- 8.4.5 SWOT Analysis
- 8.4.6 Strategic Implications (2026–2032)
- 8.5 ELISAM
- 8.5.1 Company Overview
- 8.5.2 Key Products & Segments
- 8.5.3 Financial Performance (2023–2025)
- 8.5.4 Business Strategy
- 8.5.5 SWOT Analysis
- 8.5.6 Strategic Implications (2026–2032)
- 8.6 Ellips
- 8.6.1 Company Overview
- 8.6.2 Key Products & Segments
- 8.6.3 Financial Performance (2023–2025)
- 8.6.4 Business Strategy
- 8.6.5 SWOT Analysis
- 8.6.6 Strategic Implications (2026–2032)
- 8.7 Futura
- 8.7.1 Company Overview
- 8.7.2 Key Products & Segments
- 8.7.3 Financial Performance (2023–2025)
- 8.7.4 Business Strategy
- 8.7.5 SWOT Analysis
- 8.7.6 Strategic Implications (2026–2032)
- 8.8 Ser.mac
- 8.8.1 Company Overview
- 8.8.2 Key Products & Segments
- 8.8.3 Financial Performance (2023–2025)
- 8.8.4 Business Strategy
- 8.8.5 SWOT Analysis
- 8.8.6 Strategic Implications (2026–2032)
- 8.9 GP Graders
- 8.9.1 Company Overview
- 8.9.2 Key Products & Segments
- 8.9.3 Financial Performance (2023–2025)
- 8.9.4 Business Strategy
- 8.9.5 SWOT Analysis
- 8.9.6 Strategic Implications (2026–2032)
- 8.10 Maf Agrobotic
- 8.10.1 Company Overview
- 8.10.2 Key Products & Segments
- 8.10.3 Financial Performance (2023–2025)
- 8.10.4 Business Strategy
- 8.10.5 SWOT Analysis
- 8.10.6 Strategic Implications (2026–2032)
- 8.11 Sormac
- 8.11.1 Company Overview
- 8.11.2 Key Products & Segments
- 8.11.3 Financial Performance (2023–2025)
- 8.11.4 Business Strategy
- 8.11.5 SWOT Analysis
- 8.11.6 Strategic Implications (2026–2032)
- 8.12 ICOEL
- 8.12.1 Company Overview
- 8.12.2 Key Products & Segments
- 8.12.3 Financial Performance (2023–2025)
- 8.12.4 Business Strategy
- 8.12.5 SWOT Analysis
- 8.12.6 Strategic Implications (2026–2032)
- 8.13 Burg’s Machinefabriek
- 8.13.1 Company Overview
- 8.13.2 Key Products & Segments
- 8.13.3 Financial Performance (2023–2025)
- 8.13.4 Business Strategy
- 8.13.5 SWOT Analysis
- 8.13.6 Strategic Implications (2026–2032)
- 8.14 Tong Engineering
- 8.14.1 Company Overview
- 8.14.2 Key Products & Segments
- 8.14.3 Financial Performance (2023–2025)
- 8.14.4 Business Strategy
- 8.14.5 SWOT Analysis
- 8.14.6 Strategic Implications (2026–2032)
- 8.15 Key Technology
- 8.15.1 Company Overview
- 8.15.2 Key Products & Segments
- 8.15.3 Financial Performance (2023–2025)
- 8.15.4 Business Strategy
- 8.15.5 SWOT Analysis
- 8.15.6 Strategic Implications (2026–2032)
- 8.16 Bühler Group
- 8.16.1 Company Overview
- 8.16.2 Key Products & Segments
- 8.16.3 Financial Performance (2023–2025)
- 8.16.4 Business Strategy
- 8.16.5 SWOT Analysis
- 8.16.6 Strategic Implications (2026–2032)
- 8.17 Raytec Vision
- 8.17.1 Company Overview
- 8.17.2 Key Products & Segments
- 8.17.3 Financial Performance (2023–2025)
- 8.17.4 Business Strategy
- 8.17.5 SWOT Analysis
- 8.17.6 Strategic Implications (2026–2032)
- 8.18 Tolsma-Grisnich
- 8.18.1 Company Overview
- 8.18.2 Key Products & Segments
- 8.18.3 Financial Performance (2023–2025)
- 8.18.4 Business Strategy
- 8.18.5 SWOT Analysis
- 8.18.6 Strategic Implications (2026–2032)
- 8.19 Shibuya Seiki
- 8.19.1 Company Overview
- 8.19.2 Key Products & Segments
- 8.19.3 Financial Performance (2023–2025)
- 8.19.4 Business Strategy
- 8.19.5 SWOT Analysis
- 8.19.6 Strategic Implications (2026–2032)
- 8.20 Eshet Eilon Industries
- 8.20.1 Company Overview
- 8.20.2 Key Products & Segments
- 8.20.3 Financial Performance (2023–2025)
- 8.20.4 Business Strategy
- 8.20.5 SWOT Analysis
- 8.20.6 Strategic Implications (2026–2032)
- 8.21 Reemoon Technology Co., Ltd.
- 8.21.1 Company Overview
- 8.21.2 Key Products & Segments
- 8.21.3 Financial Performance (2023–2025)
- 8.21.4 Business Strategy
- 8.21.5 SWOT Analysis
- 8.21.6 Strategic Implications (2026–2032)
- 8.22 Hefei Meyer Optoelectronic Technology Inc.
- 8.22.1 Company Overview
- 8.22.2 Key Products & Segments
- 8.22.3 Financial Performance (2023–2025)
- 8.22.4 Business Strategy
- 8.22.5 SWOT Analysis
- 8.22.6 Strategic Implications (2026–2032)
09Competitive Landscape
- 9.1 Competitive Landscape Overview
- 9.2 Competitive Intensity Assessment
- 9.3 Key Player Strategies & Positioning
- 9.4 Competitive Dynamics & Strategic Outlook
- 9.4.1 Emerging Competitive Threats
- 9.4.2 Consolidation vs. Fragmentation Outlook
- 9.4.3 Competitive Response Matrix
- 9.4.4 Strategic Recommendations, 2026–2032
10Porter's Five Forces Analysis
- 10.1 Threat of New Entrants
- 10.2 Bargaining Power of Buyers
- 10.3 Bargaining Power of Suppliers
- 10.4 Threat of Substitutes
- 10.5 Competitive Rivalry
11PESTLE Analysis
- 11.1 Political
- 11.2 Economic
- 11.3 Social and Demographic
- 11.4 Technological
- 11.5 Legal and Regulatory
- 11.6 Environmental
- 11.7 Strategic Implications of the PESTLE Assessment
12SWOT Analysis
13Future Trends & Outlook
- 13.1 Future Trends & Outlook
- 13.1.1 Trend Summary and Commercial Maturity Assessment
- 13.1.2 Technology and Innovation Trends
- 13.1.3 Long-Term Market Outlook
- 13.1.4 Investment & M&A Activity Outlook
- 13.1.5 Overall Outlook Assessment
Frequently asked questions
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Research Methodology
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Systematic collection from 500+ verified sources including SEC filings, industry databases (Bloomberg, Statista, OECD), regulatory filings, trade publications, patent databases, and company annual reports. AI-assisted extraction identifies relevant data points across 10,000+ documents per report.
Dual-validation approach: bottom-up sizing aggregates segment-level production, consumption, and trade data; top-down sizing cross-validates against macroeconomic indicators and total addressable market estimates. Discrepancies >5% trigger analyst review.
Company profiles built from public financial disclosures, product launches, M&A activity, job postings (as capability proxies), and supply chain mapping. Market share estimates triangulated across revenue, capacity, and shipment data.
CAGR projections use time-series regression on 5-10 years of historical data, adjusted for identified demand drivers (technology adoption curves, regulatory catalysts, demographic shifts) and demand inhibitors (cost barriers, substitution risk). Scenario modeling covers base, optimistic, and conservative cases.
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