Sorting Aflatoxin Contaminated Maize Kernels with Fluorescence Spectra

Aflatoxin is a mycotoxin mainly produced by Aspergillus flavus (A. flavus) and A.parasitiucus fungi under certain environmental conditions. Aflatoxin contamination in maize is a worldwide problem, especially in the tropic, sub-tropic, and even moderate temperature regions. Consumption of food or feed contaminated with aflatoxin can cause serious health problems in people and domestic animals. Thus, many countries have established strict regulations for permissible levels of aflatoxin in food and feed. For example, the allowable levels of aflatoxins in the US are 20ppb for humans and 100ppb for large animals. Conventional analytical methods for aflatoxin detection such as thin-layer chromatography (TLC) and high performance liquid chromatography (HPLC) are time consuming, expensive, and require the destruction of samples. It is always desired to have rapid and non-invasive alternatives for aflatoxin detection in commodities. Previous studies have shown that fluorescence hyperspectral imaging could be a potential rapid, and non-invasive method for contamination detection in maize. These studies indicated contaminated maize kernels had different spectral signatures from clean kernel. The current study aims to use two wavelengths identified from previous work to sort aflatoxin contaminated maize kernels from clean kernels. In this experiment, a total of 5 kg of maize kernels were divided into 100 samples, each weighing 50 g. Each clean sample was mixed with one contaminated maize kernel. The mixed samples were imaged with a fluorescence hyperspectral imaging system. A sorting algorithm based on the two pre-defined wavelengths was applied to separate the maize sample into contaminated and clean groups. The actual aflatoxin content of the two groups was later verified through a standard destructive chemical analysis process. The results indicate that with a rejection rate of 1%, the total aflatoxin from the 5 kg sample was reduced by 30% after the sorting process. These results would be useful when developing rapid and non-invasive methods for aflatoxin detection and screening.