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Development of High-Speed Dual-Camera System for Batch Screening of Aflatoxin Contamination of Corn Using Multispectral Fluorescence Imaging

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Transactions of the ASABE. 62(2): 381-391. (doi: 10.13031/trans.13125) @2019
Authors:   Deok Han, Haibo Yao, Zuzana Hruska, Russell Kincaid, Kanniah Rajasekaran, Deepak Bhatnagar
Keywords:   Aflatoxin, Corn, Dual cameras, Fluorescence image, Multispectral image, Rapid and non-destructive detection, detection.

Abstract. Aflatoxins are fungal toxins produced by . Food and feed crops contaminated with carcinogenic aflatoxins result in economic losses as well as potentially serious health issues. Grain elevators need to unload, on average, one 2.27 metric ton (MT) truckload every 2 min. Current sampling-based analytical chemistry methods for aflatoxin detection cannot meet these large throughput screening requirements. Therefore, a high-speed, batch screening system with reliable accuracy is needed. To develop a high-speed multispectral screening system, two high-performance cameras in conjunction with dual UV excitation sources and novel image processing software were used to collect fluorescence images of corn samples. Each camera simultaneously captures a single-band fluorescence image (436 nm or 532 nm) from corn kernel samples, and the detection software processes the images to automatically detect contaminated kernels using a normalized difference fluorescence index (NDFI). The system was tested with various commercial samples collected from different locations in the U.S. and baseline samples that were prepared by artificial field inoculation. Each sample was imaged and screened four times, and the screened samples were chemically analyzed for aflatoxin content. All samples were shuffled between imaging repetitions to increase the likelihood of screening both the germ and endosperm sides of every kernel. Processing time for each screening was less than 1 s. Sensitivity and specificity were measured over given thresholds for NDFI, and the results were promising. High sensitivity (0.987) and specificity (0.96) were achieved for the baseline samples, and high sensitivity (0.75 to 1) and somewhat lower specificity were obtained for the commercial samples.

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