Optical sorting machines, a cornerstone of modern industrial automation, have revolutionized quality control across agriculture, food processing, recycling, and more. Their development spans nearly a century, driven by technological innovation and the growing demand for efficiency and precision. Let’s explore this fascinating history.

Early Beginnings: The Birth of Color Sorting (1930s–1960s)

The concept of automated optical sorting emerged in the 1930s, rooted in agriculture. In 1932, the Electric Sorting Company (later part of Satake’s legacy) commercialized the world’s first color sorter for Michigan’s bean farmers, enabling the removal of discolored beans using basic optical filters. By 1937, the UK developed its first machine, and Japan adopted the technology in 1966, where it became pivotal for rice quality control.

These early systems relied on photodiodes and fluorescent lamps, offering limited resolution and stability. Yet, they laid the groundwork for replacing manual sorting, particularly in labor-intensive sectors like coffee bean processing, where color defects were critical to product quality

Technological Leaps: From Analog to Digital (1970s–2000s)

The 1970s–1980s marked a turning point. Satake, a Japanese leader, introduced bichromatic sensors and CCD cameras, enhancing defect detection in rice and grains. Meanwhile, advancements in LED lighting and FPGA/DSP processors in the 1990s improved machine stability and enabled grayscale imaging, forming the "second generation" of sorters.

By the 2000s, RGB CCD cameras and CMOS technology allowed third-generation machines to analyze color, shape, and size simultaneously. This era saw applications expand beyond agriculture into recycling (e.g., separating metals and plastics) and food processing (e.g., nuts, spices). Hyperspectral imaging also began emerging, enabling chemical composition analysis.

China’s Rise in Optical Sorting (1990s–Present)

Initially reliant on imports from Japan and Europe, China started developing domestic color sorters in the 1990s. Breakthroughs like the MMS-24A (1994) and digital double-sided sorters (2000) broke foreign monopolies. By 2021, Chinese manufacturers dominated 70% of the domestic market, leveraging high-resolution CCD lenses to achieve precision down to 0.08 mm². Companies like Hefei Meiya Optoelectronics pioneered AI-driven models, integrating deep learning for texture recognition and defect classification

Modern Innovations: AI and Beyond (2010s–Present)

The fourth generation of sorters combines AI, GPU processing, and hyperspectral imaging. Machines now detect subtle texture differences—like cracked peanut shells or crab gender—using deep learning models For example, Satake’s MIR multi-wavelength technology and Bühler’s SORTEX systems employ RGB, UV, and IR sensors to address diverse needs, from coffee bean grading to plastic recycling

Hyperspectral cameras, splitting light into hundreds of bands, create unique "spectral fingerprints" for materials, enabling sorting based on chemical properties—a game-changer for food safety and recycling

Future Trends: Smarter, Faster, Greener

The next frontier includes multispectral integration and IoT-enabled "smart factories," where real-time data optimizes sorting parameters. Sustainability is also key: optical sorters reduce waste in recycling and improve crop yields, aligning with global carbon-neutral goals

Conclusion

From rudimentary color filters to AI-powered hyperspectral systems, optical sorting has transformed industries by ensuring quality, safety, and efficiency. As technology evolves, these machines will continue to redefine automation, proving that even the smallest defect—or pixel—can drive monumental change.

For further reading, explore sources from Satake, Bühler Group, and academic insights on hyperspectral advancements