Abstract

High-speed optical sorting of seeds in commercial processing is routinely practiced for removal of discolored seeds, seeds from volunteer plants, and non-seed objects. Sorters are conventionally based on monochromatic or bichromatic light from broad wavebands in the visible and near-infrared regions of energy. A particular challenge for these devices has been the recognition and removal of wheat kernels that have been damaged by the mold caused by the fungal disease Fusarium Head Blight. Previous research using an off-the-shelf bichromatic design on Fusarium-damaged wheat kernels demonstrated that approximately half of damaged kernels were positively detected. The research described herein examines an alternative design for bichromatic lighting and applies this design to two scenarios: sound vs. Fusarium-damaged wheat and red vs. white wheat. The new design utilizes two high-power (HP) LEDs and one silicon photo diode detector. The LEDs are flashed in alternating sequence at high frequency (2,000 Hz), such that during the half-cycle time period (0.25 ms) that each LED is on, reflected energy readings at a 10× sampling frequency are captured from a kernel in flight. This permits the capture of approximately 20 cycles of pulsed light during the time the free-falling kernel passes through the field of view of a fiber optic probe. A linear discriminant analysis (LDA) classification algorithm was applied that used two values derived from the reflected energy readings. Based on the new design, the accuracy of sound vs. Fusarium-damaged classification was 78% on average; for red vs. white wheat classification, the average accuracy was 76%. Although these accuracy values are not at the level as that obtained from LDA models that utilize reflected energy readings at two wavelengths from stationary kernels (95% and 92% for sound vs. Fusarium-damaged and red vs. white, respectively), the new design offers an improvement over conventional bichromatic designs.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call