Mycotoxins are toxic compounds produced mainly by fungi of the genera Aspergillus,
Fusarium and Penicillium. In the food chain, the original mycotoxin may be transformed in other
toxic compounds, reaching the consumer. A good example is the occurrence of aflatoxin M1 (AFM1)
in dairy products, which is due to the presence of aflatoxin B1 (AFB1) in the animal feed. Thus, milkbased
foods, such as cheese and yogurts, may be contaminated with this toxin, which, although less
toxic than AFB1, also exhibits hepatotoxic and carcinogenic effects and is relatively stable during
pasteurization, storage and processing. For this reason, the establishment of allowed maximum
limits in dairy products and the development of methodologies for its detection and quantification
are of extreme importance. There are several methods for the detection of AFM1 in dairy products.
Usually, the analytical procedures go through the following stages: sampling, extraction, clean‐up,
determination and quantification. For the extraction stage, the use of organic solvents (as acetonitrile
and methanol) is still the most common, but recent advances include the use of the Quick, Easy,
Cheap, Effective, Rugged, and Safe method (QuEChERS) and proteolytic enzymes, which have been
demonstrated to be good alternatives. For the clean‐up stage, the high selectivity of immunoaffinity
columns is still a good option, but alternative and cheaper techniques are becoming more
competitive. Regarding quantification of the toxin, screening strategies include the use of the
enzyme‐linked immunosorbent assay (ELISA) to select presumptive positive samples from a wider
range of samples, and more reliable methods—high performance liquid chromatography with
fluorescence detection or mass spectroscopy—for the separation, identification and quantification
of the toxin.
This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the
scope of the strategic funding of UIDB/04469/2020 unit and BioTecNorte operation (NORTE‐01‐0145‐FEDER‐
000004) funded by the European Regional Development Fund under the scope of Norte2020 ‐ Programa
Operacional Regional do Norte. PR is grateful to FCT and FEDER under Programme PT2020 for financial
support to CIMO (UID/AGR/00690/2019). We would like to thank the Foundation for Science and Technology (FCT) for the Ph.D. scholarship given to Andreia Vaz (SFRH/BD/129775/2017).
