Quantitation of common mycotoxins (aflatoxin B1 and deoxynivalenol) in cereals by high performance thin layer chromatography with smartphone image capture and ImageJ analysis

Abstract

Aflatoxin B₁ (AFB₁) and deoxynivalenol (DON) are among the most frequently detected mycotoxin in cereals, posing great challenge to human health. This work proposed a cost-efficient and robust planar chromatography method for the rapid screening AFB₁ in millet and buckwheat, as well as DON in wheat, corn, barley, and oats, achieving detection of the two common fungal toxins in cereals. First, the sample preparation was realized by a simple extraction with 10 mL of acetonitrile, both containing 4 g of anhydrous MgSO₄, 1 g of NaCl, and 25 mg of primary secondary amine adsorbent. After high throughput chromatography, which resulted in the separation of the targeted compound from background noise and derivatization with 10% ethanol solution of AlCl₃ (only for the visualization of DON). The separation results were recorded using a smartphone in a dark chamber equipped with a 366 nm ultraviolet source. To simplify the analysis, the quantification of the graphical outcome was carried out using the open-source software ImageJ, based on quantifying digitalized pixel values. It was demonstrated that the detection sensitivity (AFB₁: limit of detection (LOD) = 14.2 μg/kg, DON: LOD = 64.3 μg/kg) was adequate to meet the strict maximum residue limit stipulated for both targeted compounds, while calibration curves gave good linearity (AFB₁: correlation coefficient (R²) = 0.967 within 1−80 ng/band, DON: R²= 0.998 within 50−800 ng/band). Then the method accuracy and precision were evaluated by spiking-recovery experiments, showing that the recovery rates of AFB₁ was within 76.9%−113.6% and those DON within 91.0%−116.5%, with relative standard deviations of less than 4.9% and 5.8% for AFB₁ and DON, respectively. The conceptual validation of this study demonstrates that the high performance thin layer chromatography (HPTLC)-image quantification method has effectively addressed the limitation of HPTLC imaging results being confined to preliminary screening without the capability of precise quantification, thereby bridging the gap between imaging and quantification. This method exhibits promising analytical tool characteristics and is suitable for screening mycotoxins in cereal samples.