Sorting of Fungal-damaged White Sorghum

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A high-speed, color image-based sorting machine was modified to separate white sorghum with symptoms of fungal damage. Most of the sorghum tested was typically white, but over 27% of the bulk contained grains with fungal damage of various degrees, from severe to very slight. Grains with slight fungal damage were characterized as having several tiny black spots randomly spread across the pericarp surface. To identify small dark spots or blemishes, real-time spot detection algorithms were implemented on a fieldprogrammable gate array (FPGA) directly linked to a color image sensor. Concurrently, grains with large amounts of fungal damage were identified using color histogram algorithms. With the FPGA communicating directly with the camera, image analysis speed was maximized by performing many operations in parallel, including inspection of up to four grains at any given time. Sorting tests indicated that after two passes through the sorter, over 90% of the grains with slight fungal damage and nearly 100% of the grains with large amounts of fungal damage were separated from the original bulk. The germination rates of the grains classified by the sorter as having fungal damage were about half of those that were accepted by the sorter as undamaged. The hardness of the grains accepted by the sorter was also 4% higher after sorting when compared with the original sample and the rejected grains. This sorting system can be used to improve the sorghum quality of food products and seed germination rates and might also be used for other grains or pulse crops for which seeds with localized spots need to be removed.