Silver nanostructure morphology-driven surface-enhanced infrared spectroscopy for determination of deoxynivalenol in wheat flour

The growing severity of food safety issues has made deoxynivalenol (DON), also known as vomitoxin, a significant concern in global food safety, as it is a common mycotoxin found in cereal grains. Conventional infrared spectroscopy faces challenges in detecting this compound due to its low detection sensitivity. In this study, we developed a highly sensitive detection method based on surface-enhanced infrared absorption spectroscopy (SEIRAS) for the quantitative analysis of DON in wheat flour. By manipulating the synthesis conditions, four distinct morphologies of silver nanoparticles (AgNPs) were prepared, and their performance as SEIRAS substrates for enhancing the characteristic infrared absorption peaks of DON was characterized and evaluated. Experimental results revealed that spherical silver nanoparticles (spherical AgNPs) exhibited significant signal enhancement at the characteristic DON peaks (1685 cm<sup>-1</sup>, 1027 cm<sup>-1</sup>, and 951 cm<sup>-1</sup>), owing to their highly symmetrical geometric structure and optimized localized surface plasmon resonance (LSPR) properties. The enhancement factor (EF) reached up to 281, with a detection limit as low as 0.722 ppm, significantly outperforming conventional infrared spectroscopy. Additionally, second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR) were employed to further validate the specificity of the DON characteristic peaks and the reliability of the detection method. This study provides an innovative solution for the detection of trace mycotoxins in complex food matrices and lays a theoretical and experimental foundation for the design of high-performance SEIRAS substrates.

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Publication Details

Journal
Analytical Methods
Published
2025-01-01
DOI
https://doi.org/10.1039/d5ay00378d
Citations
1
Primary Topic
Mycotoxins in Agriculture and Food
Type
article
Field-Weighted Citation Impact
1.75
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article

Silver nanostructure morphology-driven surface-enhanced infrared spectroscopy for determination of deoxynivalenol in wheat flour

Qian Wu, Miaomiao Zhang, Changhua Xu, Yuxi Zhang et al.
1 citations
Analytical Methods
Mycotoxins in Agriculture and Food
1.75
article

Silver nanostructure morphology-driven surface-enhanced infrared spectroscopy for determination of deoxynivalenol in wheat flour

Qian Wu, Miaomiao Zhang, Changhua Xu, Yuxi Zhang, Miao Feng, Yichen Zhu
article en
1 citations

Abstract

The growing severity of food safety issues has made deoxynivalenol (DON), also known as vomitoxin, a significant concern in global food safety, as it is a common mycotoxin found in cereal grains. Conventional infrared spectroscopy faces challenges in detecting this compound due to its low detection sensitivity. In this study, we developed a highly sensitive detection method based on surface-enhanced infrared absorption spectroscopy (SEIRAS) for the quantitative analysis of DON in wheat flour. By manipulating the synthesis conditions, four distinct morphologies of silver nanoparticles (AgNPs) were prepared, and their performance as SEIRAS substrates for enhancing the characteristic infrared absorption peaks of DON was characterized and evaluated. Experimental results revealed that spherical silver nanoparticles (spherical AgNPs) exhibited significant signal enhancement at the characteristic DON peaks (1685 cm<sup>-1</sup>, 1027 cm<sup>-1</sup>, and 951 cm<sup>-1</sup>), owing to their highly symmetrical geometric structure and optimized localized surface plasmon resonance (LSPR) properties. The enhancement factor (EF) reached up to 281, with a detection limit as low as 0.722 ppm, significantly outperforming conventional infrared spectroscopy. Additionally, second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR) were employed to further validate the specificity of the DON characteristic peaks and the reliability of the detection method. This study provides an innovative solution for the detection of trace mycotoxins in complex food matrices and lays a theoretical and experimental foundation for the design of high-performance SEIRAS substrates.

Analytical MethodsVol. 17(21)
Shanghai Harbour Engineering Design & Research Institute (CN), Shanghai Ocean University (CN)
Openalex Percentile: Top 15%
Mycotoxins in Agriculture and Food
1.75
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