Research Progress in the Detection of Mycotoxins in Cereals and Their Products by Vibrational Spectroscopy

Abstract

Grains and their derivatives play a crucial role as staple foods for the global population. Identifying grains in the food chain that are free from mycotoxin contamination is essential. Researchers have explored various traditional detection methods to address this concern. However, as grain consumption becomes increasingly time-sensitive and dynamic, traditional approaches face growing limitations. In recent years, emerging techniques-particularly molecular-based vibrational spectroscopy methods such as visible-near-infrared (Vis-NIR), near-infrared (NIR), Raman, mid-infrared (MIR) spectroscopy, and hyperspectral imaging (HSI)-have been applied to assess fungal contamination in grains and their products. This review summarizes research advances and applications of vibrational spectroscopy in detecting mycotoxins in grains from 2019 to 2025. The fundamentals of their work, information acquisition characteristics and their applicability in food matrices were outlined. The findings indicate that vibrational spectroscopy techniques can serve as valuable tools for identifying fungal contamination risks during the production, transportation, and storage of grains and related products, with each technique suited to specific applications. Given the close link between grain-based foods and humans, future efforts should further enhance the practicality of vibrational spectroscopy by simultaneously optimizing spectral analysis strategies across multiple aspects, including chemometrics, model transfer, and data-driven artificial intelligence.

Keywords: grains; mycotoxins; non-destructive testing; vibrational spectroscopy analysis technology.

Figure 1

Wavelength range of different vibrational spectra.

Figure 2

Data acquisition methods for NIR spectroscopy and hyperspectral systems. (a) Diffuse reflectance. (b) Interactance. (c) Full transmittance. (d) Partial transmittance.

Figure 3

Classical Raman spectrum acquisition system.

Figure 4

Classical HSI acquisition system.

Figure 5

Spectral analysis framework.