Application of SWIR hyperspectral imaging coupled with chemometrics for rapid and non-destructive prediction of Aflatoxin B1 in single kernel almonds

Mishra, Gayatri; Panda, Brajesh Kumar; Ramirez, Wilmer Ariza; Jung, Hye-Won; Singh, Chandra B.; Lee, Sang‐Heon; Lee, Ivan

doi:10.1016/j.lwt.2021.112954

Cited by 28 publications

(9 citation statements)

References 49 publications

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“…In order to better explain the potentialities of our method, we report some recent studies published in the last three years showing the great practical-applicative potentialities of the use of NIR in monitoring mycotoxin contamination in several matrices used in animal or human nutrition in Table 8 . In particular, the results obtained in our study were in line with the classification studies reported below [ 65 , 66 , 67 , 68 , 69 , 70 , 71 ]. The study reported here gave a practical application of NIR calibration in order to underline the importance of this type of approach as a practical tool to assess the safety of silage.…”

Section: Discussionsupporting

confidence: 92%

A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy

Ghilardelli

Barbato

Gallo

2022

Toxins

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Mycotoxins should be monitored in order to properly evaluate corn silage safety quality. In the present study, corn silage samples (n = 115) were collected in a survey, characterized for concentrations of mycotoxins, and scanned by a NIR spectrometer. Random Forest classification models for NIR calibration were developed by applying different cut-offs to classify samples for concentration (i.e., μg/kg dry matter) or count (i.e., n) of (i) total detectable mycotoxins; (ii) regulated and emerging Fusarium toxins; (iii) emerging Fusarium toxins; (iv) Fumonisins and their metabolites; and (v) Penicillium toxins. An over- and under-sampling re-balancing technique was applied and performed 100 times. The best predictive model for total sum and count (i.e., accuracy mean ± standard deviation) was obtained by applying cut-offs of 10,000 µg/kg DM (i.e., 96.0 ± 2.7%) or 34 (i.e., 97.1 ± 1.8%), respectively. Regulated and emerging Fusarium mycotoxins achieved accuracies slightly less than 90%. For the Penicillium mycotoxin contamination category, an accuracy of 95.1 ± 2.8% was obtained by using a cut-off limit of 350 µg/kg DM as a total sum or 98.6 ± 1.3% for a cut-off limit of five as mycotoxin count. In conclusion, this work was a preliminary study to discriminate corn silage for high or low mycotoxin contamination by using NIR spectroscopy.

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Section: Discussionsupporting

confidence: 92%

A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy

Ghilardelli

Barbato

Gallo

2022

Toxins

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“…In addition to NIRS and MIRS, mainly used for the analysis of bulk samples, single kernel NIRS (SKNIR) and HSI have also been used for mycotoxin determination focusing on the analysis of individual kernels (Tables 4 and 5, respectively). Besides classic agricultural commodities as listed in Tables 1–5 MIRS, NIRS and HSI have also been used to analyze raisins (Galvis‐Sánchez et al., 2007; Heperkan & Gökmen, 2016), chili powder (Tripathi & Mishra, 2009), almonds (Liang et al., 2015; Mishra et al., 2022), pistachios (Kheiralipour et al., 2016; Wu & Xu, 2019), garlic (Liang et al., 2015), figs (Durmuş et al., 2017), green coffee (Taradolsirithitikul et al., 2017), milk (Jaiswal et al., 2018), green tea (Cao et al., 2020), corn silage (Ghilardelli et al., 2022), and bio‐ethanol byproducts (Tyska et al., 2022) regarding their contamination with mycotoxins or mycotoxigenic fungi infestation.…”

Section: Literature On Mycotoxin Analysis Using Ir Spectroscopymentioning

confidence: 99%

The potential and applicability of infrared spectroscopic methods for the rapid screening and routine analysis of mycotoxins in food crops

Freitag

Sulyok

Logan

et al. 2022

Comp Rev Food Sci Food Safe

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Infrared (IR) spectroscopy is increasingly being used to analyze food crops for quality and safety purposes in a rapid, nondestructive, and eco-friendly manner.The lack of sensitivity and the overlapping absorption characteristics of major sample matrix components, however, often prevent the direct determination of food contaminants at trace levels. By measuring fungal-induced matrix changes with near IR and mid IR spectroscopy as well as hyperspectral imaging, the indirect determination of mycotoxins in food crops has been realized. Recent studies underline that such IR spectroscopic platforms have great potential for the rapid analysis of mycotoxins along the food and feed supply chain. However, there are no published reports on the validation of IR methods according to official regulations, and those publications that demonstrate their applicability in a routine analytical set-up are scarce. Therefore, the purpose of this review is to discuss the current state-of-the-art and the potential of IR spectroscopic methods for the rapid determination of mycotoxins in food crops. The study critically reflects on the applicability and limitations of IR spectroscopy in routine analysis and provides guidance to non-spectroscopists from the food and feed sector considering implementation of IR spectroscopy for rapid mycotoxin screening. Finally, an outlook on trends, possible fields of applications, and different ways of implementation in the food and feed safety area are discussed.

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“…A atoxin B 1 (AFB 1 ) derived from fungi species is difuran-coumarin compound with the most poisonous activities (Marchese et al 2018). Over the last few decades, AFB 1 contamination in a wide variety of common foodstuffs has become an unavoidable global concern, containing grains (corn, wheat and peanuts) and snack foods (jerky, pistachios and almonds) (Mishra et al 2022;Pleadin et al 2015; Wu et al 2020). In particular, for peanuts, the AFB 1 detection rate reached 33.8% from four major production regions in China ).…”

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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Application of SWIR hyperspectral imaging coupled with chemometrics for rapid and non-destructive prediction of Aflatoxin B1 in single kernel almonds

Cited by 28 publications

References 49 publications

A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy

A Preliminary Study to Classify Corn Silage for High or Low Mycotoxin Contamination by Using near Infrared Spectroscopy

The potential and applicability of infrared spectroscopic methods for the rapid screening and routine analysis of mycotoxins in food crops

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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