Optical detection of aflatoxins in maize using one- and two-photon induced fluorescence spectroscopy

Abstract

The presence of aflatoxins in food and feed products is considered as one of the most important food safety problems in the world. Aflatoxins occur in a wide range of food products and can cause serious health risks. Moreover, they can nowadays only be detected by the use of destructive, time-consuming and expensive chemical analyses. We investigate the use of one- and two-photon induced fluorescence spectroscopy as nondestructive detection methods for the identification of aflatoxins. Particularly, as the samples under test, we consider the aflatoxin-contamination of different maize batches since maize is the staple food in many countries and cultivates in climates that show an extensive presence of the fungi. We first characterize the one- and two-photon induced fluorescence spectrum of pure aflatoxin B1, when excited with 365 nm and 730 nm laser light respectively. Subsequently, we experimentally investigate the fluorescence spectrum of various healthy and aflatoxin-contaminated maize samples, when excited with 365 nm, 405 nm, 730 nm, 750 nm, 780 nm and 810 nm laser light. For all excitation wavelengths, an intrinsic fluorescence signal of the maize grains is observed. However, for the contaminated maize grains, the present aflatoxin B1 significantly influences the intrinsic fluorescence. Depending on the excitation wavelength, we observe a different spectral contrast between the healthy and contaminated samples. The largest optical difference is observed for excitation with 365 nm and 780 nm, during the one- and two-photon induced fluorescence measurements respectively. The comparison of the measured fluorescence signals allows us to define a detection criterion for the optical identification of the contaminated maize samples. We can conclude that fluorescence spectroscopy can be a valuable tool for the measurement of aflatoxin-contents in maize, paving the way for real-time non-destructive industrial scanning-based detection.