The Existing Methods and Novel Approaches in Mycotoxins’ Detection

Janik, Edyta; Niemcewicz, Marcin; Podogrocki, Marcin; Ceremuga, Michał; Gorniak, Leslaw; Stela, Maksymilian; Bijak, Michał

doi:10.3390/molecules26133981

Cited by 41 publications

(22 citation statements)

References 159 publications

(168 reference statements)

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“…In addition, it indirectly reduces the uncertainties of contamination. These digital technologies have been explored by various imaging methods (Janik et al, 2021;Ziyaee et al, 2021). Therefore, by assisting our own abilities with artificial cognitive capabilities we can enhance our decision-making potential, and then use this for a purpose of global utility: high sanitary quality.…”

Section: Discussionmentioning

confidence: 99%

Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality

Sudki

Oliveira²,

Medeiros³

et al. 2023

Front. Plant Sci.

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The sanitary quality of seed is essential in agriculture. This is because pathogenic fungi compromise seed physiological quality and prevent the formation of plants in the field, which causes losses to farmers. Multispectral images technologies coupled with machine learning algorithms can optimize the identification of healthy peanut seeds, greatly improving the sanitary quality. The objective was to verify whether multispectral images technologies and artificial intelligence tools are effective for discriminating pathogenic fungi in tropical peanut seeds. For this purpose, dry peanut seeds infected by fungi (A. flavus, A. niger, Penicillium sp., and Rhizopus sp.) were used to acquire images at different wavelengths (365 to 970 nm). Multispectral markers of peanut seed health quality were found. The incubation period of 216 h was the one that most contributed to discriminating healthy seeds from those containing fungi through multispectral images. Texture (Percent Run), color (CIELab L*) and reflectance (490 nm) were highly effective in discriminating the sanitary quality of peanut seeds. Machine learning algorithms (LDA, MLP, RF, and SVM) demonstrated high accuracy in autonomous detection of seed health status (90 to 100%). Thus, multispectral images coupled with machine learning algorithms are effective for screening peanut seeds with superior sanitary quality.

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Section: Discussionmentioning

confidence: 99%

Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality

Sudki

Oliveira²,

Medeiros³

et al. 2023

Front. Plant Sci.

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“…Among the mycotoxins, Ochratoxin A (OTA), aflatoxins, patulin, zearalenone (ZEN), fumonisins, and trichocenes such as deoxynivalenol and T-2 toxin are of most concern. [48] The application of biosensors and immunosensors for the detection of mycotoxins has been reviewed and investigated in several studies. [49] In this case, the NFs-based (bio)sensor assay enables increased surface area and accessibility, as well as low mass transport resistance, enhancing diffusion of the analyte across the sensor film simply due to the aforementioned unique properties of NFs.…”

Section: Detection Of Mycotoxinsmentioning

confidence: 99%

Electrochemical Sensing Based on Nanofibers Modified Electrodes for Application in Diagnostic, Food and Waste Water Samples

Nazari,

Kashanian,

Parnianchi

et al. 2023

ChemElectroChem

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Electrochemical sensors and biosensors are today important analytical and monitoring tools in various fields, from agriculture and the food industry to environmental and biomedical/pharmaceutical applications. In particular, the integration of nanotechnology with electrochemical sensors and biosensors to develop a new generation of sensor platforms has made enormous progress in recent years. The outstanding properties of one‐dimensional (1D) nanofibers (NFs), such as high porosity, superior mechanical properties and high specific surface area have made them attractive electrocatalysts, support materials for the immobilization of biomolecules as well as mimetic materials for sensing and biosensing applications. Moreover, the possibility of fabricating multifunctional composites based on NFs increases (bio)sensing capabilities through synergistic effects and additive properties. This review describes the progress made over the last decade in the use of multifunctional NFs‐based composites as modified electrodes for the sensing of various analytes in biomedical, food, and wastewater treatment applications. The aim of this review is to provide a comprehensive overview and a guide for researchers from different disciplines to fabricate and improve their selective NFs‐based (bio)sensor platforms for the detection of desired analytes or multi‐analytes.

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“…Analytical approaches depending on large-scale instruments have been explored to accurately measure AFB 1 , such as thin layer chromatography (TLC) (Var et al 2007), high-performance liquid chromatography (HPLC) (Mochamad and Hermanto 2017) and liquid chromatography-tandem mass spectrometry (LC-MS) (Janik et al 2021). However, certain downsides of poor response, low e ciency, and excellent professionalism limit the application of methods in rapid food safety testing.…”

Section: Introductionmentioning

confidence: 99%

3D plasmonic SERS aptasensor for rapid detection of aflatoxin B1 combined with Au@Ag bimetallic nanostars and Fe3O4 @MoS2 magnetic nanoflowers

Chen

et al. 2023

Preprint

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As a virulent metabolite, aflatoxin B1 (AFB1) presented in various cereal grain is tightly implicated in severe human diseases. In this study, 3D plasmonic nanohybirds of Raman molecule 4-mercaptobenzoic acid (4-MBA)-embedded and AFB1 aptamer-modified bimetallic nanostars as probes bound to magnetic nanoflowers were fabricated and demonstrated as a high-performance SERS-active aptasensor to quantitatively analyze AFB1. Bimetallic Au@Ag SERS plasmonic nanoprobes with enhanced properties were capable of enhancing discriminative Raman peaks of 4-MBA. Then, the integration of iron tetroxide nanoparticles (Fe3O4 NPs) and molybdenum disulfide nanosheets (MoS2 NSs) with huge specific surface area constituted stable 3D Fe3O4@MoS2 plasmonic nanoflowers, facilitating the bind of numerous aptamer-based SERS probes via the non-covalent interaction between MoS2 NSs and aptamer, which were ideal candidates for SERS-active substrates. Additionally, Fe3O4 NPs as magenetic core endowed 3D nanocomposites with specific magnetic separation characteristic that caused the collected SERS hotspots to exhibit superior signal response, and further strengthening the sensitivity in a complex food matrix. Aptamer-target AFB1 specific recognition triggered linearly diminished 4-MBA signal intensity (I4 − MBA) on the substrate to achieve a low detection limit of 58.9 pg/mL. Furthermore, the sensor has the potential to be a promising monitoring tool for trace contaminants.

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The Existing Methods and Novel Approaches in Mycotoxins’ Detection

Cited by 41 publications

References 159 publications

Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality

Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality

Electrochemical Sensing Based on Nanofibers Modified Electrodes for Application in Diagnostic, Food and Waste Water Samples

3D plasmonic SERS aptasensor for rapid detection of aflatoxin B1 combined with Au@Ag bimetallic nanostars and Fe3O4 @MoS2 magnetic nanoflowers

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