Development of high speed dual-camera system for batch screening of aflatoxin contamination of corn using multispectral fluorescence imaging

Authors: HAN, DEOK - Mississippi State University; YAO, HAIBO - Mississippi State University; HRUSKA, ZUZANA - Mississippi State University; KINCAID, RUSSELL - Mississippi State University; RAMEZANPOUR, CHRISTOPHER - Secure Food Solutions; Rajasekaran, Kanniah - Rajah; Bhatnagar, Deepak

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 5/15/2018
Publication Date: 5/15/2018
Citation: Han, D., Yao, H., Hruska, Z., Kincaid, R., Ramezanpour, C., Rajasekaran, K., Bhatnagar, D. 2018. Development of high speed dual-camera system for batch screening of aflatoxin contamination of corn using multispectral fluorescence imaging. Proceedings of SPIE, Sensing for Agriculture and Food Quality and Safety X. Paper No. 106650J. https://doi.org/10.1117/12.2305148.
DOI: https://doi.org/10.1117/12.2305148

Interpretive Summary:

Technical Abstract: Aflatoxins are fungal toxins produced by Aspergillus flavus. Food and feed crops get contaminated with carcinogenic aflatoxins, which often results in economic losses as well as serious health issues. Grain elevators need to unload, on average, one 50,000-pound truckload every two minutes. Current chemical and optical methods for aflatoxin detection cannot meet the screening requirements. Therefore, a high speed batch screening system with reliable accuracy is necessary. The contaminated corn kernels were prepared in our laboratory by artificial inoculation of corn ears. One hundred 200g samples were selected for analysis. 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 utilized to collect fluorescence images of each sample. Each camera simultaneously captures a single band fluorescence image (436 nm and 532 nm) from corn samples, and the detection software processes the images to automatically detect contaminated kernels by using a normalized difference fluorescence index. Each sample was imaged/screened four times, and screened samples were chemically analyzed for aflatoxin content. All samples were shuffled between imaging repetitions to increase the likelihood of screening both sides of every kernel. Processing time for each screening was about 0.7s, and an optimal result of 98.65% was achieved for sensitivity and 96.6% for specificity.