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市場調查報告書
商品編碼
1836417
2032 年食品分選系統市場預測:按產品類型、分選機制、技術、應用、最終用戶和地區進行的全球分析Food Sorting Systems Market Forecasts to 2032 - Global Analysis By Product Type (Belt Sorters, Freefall Sorters, Channel Sorters, ADR Systems, and Other Product Types), Sorting Mechanism, Technology, Application, End User and By Geography |
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根據 Stratistics MRC 的數據,全球食品分類系統市場預計在 2025 年達到 26 億美元,到 2032 年將達到 35 億美元,預測期內的複合年成長率為 4.5%。
食品分選系統是用於食品加工的自動化機器,旨在確保品質和安全。它們利用攝影機、感測器和雷射器,根據產品的大小、顏色、形狀以及生物或化學缺陷進行檢測。它們使用氣流和機械手臂自動將好產品與壞產品(例如腐爛的蔬菜或異物)區分開來。這項技術可以提高效率、降低人事費用、最大限度地減少廢棄物,並確保產品始終如一地保持高品質,滿足消費者嚴格的食品安全標準。
據陶朗食品稱,新型人工智慧光學分類機可減少高達 15% 的食物廢棄物,在加工商追求效率和永續性的背景下,成為全球市場成長的主要驅動力。
對高效品質保證的需求日益成長
食品業越來越重視品質保證,以滿足嚴格的安全法規和消費者的期望。自動化分類系統透過最大限度地減少人為錯誤並確保產品品質的一致性來提高效率。在外觀和結構完整性至關重要的行業,例如生鮮食品、肉類和包裝食品,這種需求尤其強烈。光學感測器和即時分析等先進技術正在整合,以檢測缺陷、污染物和不一致性。隨著全球食品消費量的不斷成長,製造商正在投資高速、高精度的分類系統,以維護品牌聲譽並減少整個供應鏈的浪費。
設備安裝成本高
儘管食品分類系統好處多多,但其需要大量的資本投入,這對中小企業來說可能是一個障礙。安裝成本不僅包括機器設備,還包括基礎設施升級、員工培訓和持續維護。針對特定食品類型和生產線的客製化服務進一步增加了成本。此外,將此類系統與現有工作流程和數位平台整合可能既複雜又昂貴。在新興市場,資金籌措和技術純熟勞工的匱乏進一步加劇了這項挑戰。這些資金障礙阻礙了其普及,尤其是在那些由於人工分類成本低廉且易於操作而仍然盛行的地區。
基於人工智慧的排序演算法的整合
人工智慧正透過打造更智慧、更快速、更具適應性的系統,徹底改變食品分類。基於人工智慧的演算法可以分析海量資料集,從而改善缺陷檢測、預測維護需求並即時最佳化分類參數。機器學習模型會從過往的分類結果中學習,以提高準確率、減少誤報並提升產量比率。這為製造商提供了處理複雜分類任務的機會,例如成熟度分級、異物檢測和過敏原識別。隨著人工智慧的應用越來越廣泛,企業可以擴大營運規模、減少浪費,並以更高的準確度和靈活性滿足不斷變化的監管標準。
供應鏈中斷
全球供應鏈不穩定對食品分類系統市場構成重大威脅。地緣政治緊張局勢、自然災害或疫情造成的干擾可能會延遲設備交付、增加成本並阻礙系統部署。感測器、晶片和馬達等關鍵部件的短缺可能會影響生產計劃和服務可用性。此外,物流瓶頸和原物料價格波動也挑戰著製造商維持穩定產量的能力。這種不確定性可能迫使企業重新評估籌資策略,實現供應商多元化,並投資於更具韌性的基礎設施,從而在短期內減緩市場成長和創新。
新冠疫情加速了食品加工(包括分類系統)的自動化進程。在人手不足的情況下,對能夠維持產量的衛生、非接觸式解決方案的需求激增。然而,疫情也擾亂了供應鏈,導致安裝延誤並推高了成本。遠端試運行和數位化支援服務變得日益流行,使製造商能夠以最少的現場人員部署和維護系統。整體而言,新冠疫情既是創新的催化劑,也是限制因素,同時也揭露了全球採購和部署策略的漏洞。
預計預測期內,帶式分類機市場規模最大
預計帶式分類機細分市場將在預測期內佔據最大市場佔有率,這得益於其多功能性、擴充性和高效性。這些系統廣泛應用於各種食品類別,包括水果、蔬菜、穀物和包裝食品。它們能夠以始終如一的精度處理大量食品,是大規模生產的理想選擇。多感測器整合和模組化設計等技術進步進一步增強了它們的吸引力。帶式分類機還能適應各種分類標準,包括顏色、形狀、尺寸和缺陷,使其成為尋求最大化產量比率和減少浪費的製造商的首選。
預測期內,機械分類領域預計將以最高複合年成長率成長
機械分選領域憑藉其成本效益和適應性,預計將在預測期內實現最高成長率。這些系統利用重量、尺寸和形狀等物理特性來分離食品,非常適合中小型設施的基本分選任務。機械設計和自動化領域的創新正在擴展其功能,並使其能夠與數位控制和感測器整合。隨著新興市場對經濟實惠、低維護解決方案的需求日益成長,機械分選機為自動化領域提供了一個極具吸引力的切入點,推動了其快速普及和市場擴張。
由於快速的工業化、不斷成長的食品需求以及監管的加強,預計亞太地區將在預測期內佔據最大的市場佔有率。中國、印度和日本等國家正大力投資食品加工基礎設施,以滿足國內和出口需求。政府推動食品安全和自動化的措施正在加速其應用。該地區龐大的農業基礎和不斷壯大的中階進一步推動了對高品質、高效分選食品的需求。本地製造商也正在進入市場,提供針對當地需求的具有成本競爭力的解決方案,以鞏固其在亞太地區的地位。
在預測期內,北美預計將在技術創新和強力的法規結構的推動下,實現最高的複合年成長率。該地區對食品安全、永續性和營運效率的重視,推動了對先進分類解決方案的需求。企業正在採用人工智慧、機器視覺和機器人技術來提高分類精度並減少對勞動力的依賴。關鍵產業參與者的存在和強大的研發生態系統支持著持續的技術創新。此外,消費者對優質和可追溯食品的偏好,正在推動美國和加拿大對高性能分揀系統的投資。
According to Stratistics MRC, the Global Food Sorting Systems Market is accounted for $2.6 billion in 2025 and is expected to reach $3.5 billion by 2032 growing at a CAGR of 4.5% during the forecast period. Food Sorting Systems are automated machines used in food processing to ensure quality and safety. They utilize cameras, sensors, and lasers to inspect products based on size, color, shape, and biological or chemical defects. Using air jets or mechanical arms, they automatically separate undesirable items (like rotten produce or foreign materials) from the good product. This technology enhances efficiency, reduces labor costs, minimizes waste, and ensures a consistent, high-quality output that meets stringent food safety standards for consumers.
According to TOMRA Food, new AI-powered optical sorters can now reduce food waste by up to 15%, a key driver for the global market's growth as processors seek efficiency and sustainability.
Rising demand for quality assurance efficiency
The food industry is increasingly prioritizing quality assurance to meet stringent safety regulations and consumer expectations. Automated sorting systems enhance efficiency by minimizing human error and ensuring consistent product quality. This demand is especially strong in sectors like fresh produce, meat, and packaged foods, where visual and structural integrity are critical. Advanced technologies such as optical sensors and real-time analytics are being integrated to detect defects, contaminants, and inconsistencies. As global food consumption rises, manufacturers are investing in high-speed, high-accuracy sorting systems to maintain brand reputation and reduce waste across supply chains.
High equipment installation costs
Despite their benefits, food sorting systems require substantial capital investment, which can deter small and medium-sized enterprises. Installation costs include not only the machinery but also infrastructure upgrades, staff training, and ongoing maintenance. Customization for specific food types or production lines further increases expenses. Additionally, integrating these systems with existing workflows and digital platforms can be complex and costly. In emerging markets, limited access to financing and skilled labor compounds the challenge. These financial barriers slow adoption, especially in regions where manual sorting remains prevalent due to affordability and operational simplicity.
Integration of AI-based sorting algorithms
Artificial intelligence is revolutionizing food sorting by enabling smarter, faster, and more adaptive systems. AI-based algorithms can analyze vast datasets to improve defect detection, predict maintenance needs, and optimize sorting parameters in real time. Machine learning models enhance accuracy by learning from past sorting outcomes, reducing false positives and improving yield. This opens opportunities for manufacturers to handle complex sorting tasks like ripeness grading, foreign object detection, and allergen identification. As AI becomes more accessible, companies can scale operations, reduce waste, and meet evolving regulatory standards with greater precision and agility.
Supply chain disruptions
Global supply chain instability poses a significant threat to the food sorting systems market. Disruptions caused by geopolitical tensions, natural disasters, or pandemics can delay equipment delivery, inflate costs, and hinder system deployment. Shortages in critical components like sensors, chips, and motors affect production timelines and service availability. Additionally, logistical bottlenecks and fluctuating raw material prices challenge manufacturers' ability to maintain consistent output. These uncertainties force companies to reassess procurement strategies, diversify suppliers, and invest in more resilient infrastructure, potentially slowing market growth and innovation in the short term.
The COVID-19 pandemic accelerated automation in food processing, including sorting systems, as companies sought to reduce human contact and ensure operational continuity. Demand surged for hygienic, contactless solutions capable of maintaining throughput amid labor shortages. However, the pandemic also disrupted supply chains, delaying installations and increasing costs. Remote commissioning and digital support services gained traction, enabling manufacturers to deploy and maintain systems with minimal on-site presence. Overall, COVID-19 acted as both a catalyst and a constraint driving innovation while exposing vulnerabilities in global sourcing and deployment strategies.
The belt sorters segment is expected to be the largest during the forecast period
The belt sorters segment is expected to account for the largest market share during the forecast period, due to their versatility, scalability, and efficiency. These systems are widely used across various food categories, including fruits, vegetables, grains, and packaged goods. Their ability to handle high volumes with consistent accuracy makes them ideal for large-scale operations. Technological advancements such as multi-sensor integration and modular designs have further enhanced their appeal. Belt sorters also support diverse sorting criteria color, shape, size, and defects making them a preferred choice for manufacturers aiming to maximize yield and minimize waste.
The mechanical sorting segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the mechanical sorting segment is predicted to witness the highest growth rate, due to their cost-effectiveness and adaptability. These systems use physical properties like weight, size, and shape to sort food items, making them suitable for basic sorting tasks in small and mid-sized facilities. Innovations in mechanical design and automation are expanding their capabilities, allowing integration with digital controls and sensors. As demand grows for affordable, low-maintenance solutions in emerging markets, mechanical sorters offer an attractive entry point for automation, driving rapid adoption and market expansion.
During the forecast period, the Asia Pacific region is expected to hold the largest market share, driven by rapid industrialization, rising food demand, and increasing regulatory scrutiny. Countries like China, India, and Japan are investing heavily in food processing infrastructure to meet domestic and export needs. Government initiatives promoting food safety and automation are accelerating adoption. The region's large agricultural base and growing middle class further fuel demand for high-quality, efficiently sorted food products. Local manufacturers are also entering the market, offering cost-competitive solutions tailored to regional needs, solidifying Asia Pacific's dominant position.
Over the forecast period, the North America region is anticipated to exhibit the highest CAGR fueled by technological innovation and strong regulatory frameworks. The region's emphasis on food safety, sustainability, and operational efficiency drives demand for advanced sorting solutions. Companies are adopting AI, machine vision, and robotics to enhance sorting precision and reduce labor dependency. The presence of key industry players and robust R&D ecosystems supports continuous innovation. Additionally, consumer preferences for premium, traceable food products encourage investment in high-performance sorting systems across the U.S. and Canada.
Key players in the market
Some of the key players in Food Sorting Systems Market include TOMRA Systems ASA, Buhler Group, SATAKE Corporation, Sesotec GmbH, Newtec A/S, AWETA, Greefa, Maf Roda Agrobotic, Cimbria, Multiscan Technologies, Raytec Vision SpA, Hefei Meyer Optoelectronic Technology Inc., Anhui Jiexun Optoelectronic Technology Co., Ltd., Binder+Co AG, Ellips B.V., BBC Technologies, Optimum NV, Reemoon Technology Holdings Co., Ltd. and Innotech Process Equipment
In August 2025, TOMRA Systems ASA launched the new LUCAI AI platform for its food sorters, utilizing deep learning to identify and remove subtle defects like mildew on nuts and internal defects in fruits with 99.9% accuracy.
In July 2025, Buhler Group introduced the new Sortex A2000 optical sorter for rice and grains, featuring hyperspectral imaging to detect and eject mycotoxins and pesticide residues, ensuring compliance with stringent new EU food safety standards.
In June 2025, SATAKE Corporation announced a strategic 'Make in India' initiative to locally manufacture its flagship Colorvision sorters, making advanced optical sorting technology more accessible to India's growing food processing industry.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.