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

• A method based on HPTLC-image quantification analysis was established for the cost-effective and rapid preliminary screening of AFB1 and DON in grain samples. • The HPTLC-ImageJ analysis method enables the specific identification and quantitative analysis of AFB1 and vomitoxin in grain samples. • The combination of ImageJ, smartphone image capture, and HPTLC offers a cost-effective method for analysis. • Quantitative analysis using ImageJ is recognized as an ideal choice for laboratories operating in resource-limited settings, as it provides reliable image analysis results under cost constraints. Aflatoxin B 1 (AFB 1 ) 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 AFB 1 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 MgSO 4 , 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 AlCl 3 (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 (AFB 1 : 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 (AFB 1 : correlation coefficient ( R 2 ) = 0.967 within 1−80 ng/band, DON: R 2 = 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 AFB 1 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 AFB 1 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.

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Publication Details

Journal
Journal of Future Foods
Published
2025-04-21
DOI
https://doi.org/10.1016/j.jfutfo.2024.08.011
Citations
10
Primary Topic
Mycotoxins in Agriculture and Food
Type
article
Field-Weighted Citation Impact
17.50

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article

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

Xiaoqian Tang, Xingjun Xi, Yisheng Chen, Xudong Shi
10 citations
Journal of Future Foods
Mycotoxins in Agriculture and Food
17.50
article

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

Xiaoqian Tang, Xingjun Xi, Yisheng Chen, Xudong Shi
article en
10 citations

Abstract

• A method based on HPTLC-image quantification analysis was established for the cost-effective and rapid preliminary screening of AFB1 and DON in grain samples. • The HPTLC-ImageJ analysis method enables the specific identification and quantitative analysis of AFB1 and vomitoxin in grain samples. • The combination of ImageJ, smartphone image capture, and HPTLC offers a cost-effective method for analysis. • Quantitative analysis using ImageJ is recognized as an ideal choice for laboratories operating in resource-limited settings, as it provides reliable image analysis results under cost constraints. Aflatoxin B 1 (AFB 1 ) 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 AFB 1 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 MgSO 4 , 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 AlCl 3 (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 (AFB 1 : 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 (AFB 1 : correlation coefficient ( R 2 ) = 0.967 within 1−80 ng/band, DON: R 2 = 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 AFB 1 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 AFB 1 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.

Journal of Future FoodsVol. 6(1)
Shanxi Agricultural University (CN), China National Institute of Standardization (CN), Ministry of Agriculture and Rural Affairs (CN)
Ministry of Agriculture and Rural Affairs of the People's Republic of China, Shanxi Agricultural University
Zero hunger
Openalex Percentile: Top 1%
Mycotoxins in Agriculture and Food
17.50
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