Optimizing extraction solvents for deoxynivalenol analysis in maize <i>via</i> infrared attenuated total reflection spectroscopy and chemometric methods

Femenias, Antoni; Fomina, Polina; Tafintseva, Valeria; Freitag, Stephan; Shapaval, Volha; Sulyok, Michael; Zimmermann, Boris; Marı́n, Sonia; Krska, Rudolf; Köhler, Achim; Mizaikoff, Boris

doi:10.1039/d2ay00995a

Cited by 4 publications

(15 citation statements)

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“…This could be attributed to the distinct chemical composition of maize and wheat and/or the nature of the fungal contamination: the type of fungal strains grown, which metabolites they produce, and how they degrade the food matrix. 31 The high classification accuracy of the models achieved in the present study is indeed consistent with the literature. Several other studies that applied IR-ATR spectroscopy for mycotoxins analysis in cereals or other matrices demonstrate Acc cv > 90%.…”

Section: Discussionsupporting

confidence: 92%

“…No evidence was found that this clustering influences the classification according to the DON levels. 31 From the obtained SPLS-DA results (Table 2), it is evident that all the models show a high classification accuracy of crossvalidation (Acc cv > 0.840). The prediction models exhibit high values of sensitivity and specificity, suggesting a balanced classification of both classes: low and high DON (Table 2).…”

Section: Discussionmentioning

confidence: 90%

“…Therefore, we assume that IR-spectroscopic approaches are indirect analysis methods that rely on associated changes in the matrix due to fungal infection and fungal growth. In Femenias et al, the authors showed comparable findings . This assumption allows us to interpret further data analysis outcomes.…”

Section: Discussionmentioning

confidence: 97%

“…It is noteworthy that during the investigation of DON-contaminated maize samples in other studies, methanolic solvents exhibited superior performance compared to aqueous solutions. This could be attributed to the distinct chemical composition of maize and wheat and/or the nature of the fungal contamination: the type of fungal strains grown, which metabolites they produce, and how they degrade the food matrix …”

Section: Discussionmentioning

confidence: 99%

“…The classification of maize into high vs low DON-contaminated samples (EU-regulatory limit for DON in corn is 1750 μg/kg) was achieved with high accuracy using water and methanol/water (70:30) mixtures as solvents for DON extraction. Sparse partial least-squares discriminant analysis (SPLS-DA) models with an accuracy of cross-validation equal to 86.7% were shown for DON extracts using water as a solvent and 90.8% for DON extracts using methanol/water (70:30) . SPLS-DA analysis was preferred over PLS-DA as it is a variable selection method that allows building sparse classification models.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis

Fomina,

Femenias,

Tafintseva

et al. 2024

ACS Food Sci. Technol.

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The climate crisis further exacerbates the challenges for food production. For instance, the increasingly unpredictable growth of fungal species in the field can lead to an unprecedented high prevalence of several mycotoxins, including the most important toxic secondary metabolite produced by Fusarium spp., i.e., deoxynivalenol (DON). The presence of DON in crops may cause health problems in the population and livestock. Hence, there is a demand for advanced strategies facilitating the detection of DON contamination in cereal-based products. To address this need, we introduce infrared attenuated total reflection (IR-ATR) spectroscopy combined with advanced data modeling routines and optimized sample preparation protocols. In this study, we address the limited exploration of wheat commodities to date via IR-ATR spectroscopy. The focus of this study was optimizing the extraction protocol for wheat by testing various solvents aligned with a greener and more sustainable analytical approach. The employed chemometric method, i.e., sparse partial least-squares discriminant analysis, not only facilitated establishing robust classification models capable of discriminating between high vs low DON-contaminated samples adhering to the EU regulatory limit of 1250 μg/ kg but also provided valuable insights into the relevant parameters shaping these models.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis

Fomina,

Femenias,

Tafintseva

et al. 2024

ACS Food Sci. Technol.

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Stakeholder assessment for mycotoxin analysis: exploring the demand along the European food supply chain

Csenki,

Mikulás,

Freitag

et al. 2023

World Mycotox. J.

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Mycotoxins are amongst the most prevalent food contaminants leading to serious health implications for humans and animals. Limiting exposure to them within the population remains a pressing food safety challenge. Prevention and timely detection are crucial for minimising mycotoxin contamination in food and feed. Therefore easy-to-use, rapid, eco-friendly and low-cost screening methods are increasingly implemented. Early-stage end-user engagement in the technological development process aids and guides the research towards increased societal impact. To investigate these end-user needs, the limitations of the currently used methods and the expectations towards a novel approach were mapped among stakeholders in a comprehensive survey. Stakeholders along the food supply chain (agricultural, food processing, retail, food safety and control, laboratories) were identified in five European countries and contacted. A total of 63 participants completed the survey, which was followed-up by an interview. The results of the survey revealed that different end-user groups have different priorities. Important limiting factors for agricultural, processing and retail stakeholders of the current methodologies include the complexity of sample preparation, high cost and time-to-results. Complementing the accredited laboratory tests with a pre-screening device would be especially interesting for agricultural producers (87.5% of the participants are interested) and food processors (80%), since there is an increasing demand for on-site detection of contamination. On the other hand, food control authorities and commercial laboratories indicated higher priority towards low quantification limits and multi-compound methods. The time to get the results was found to be more important than the testing cost (important aspect for 74.6 versus 66.7%). Overall, the findings of this study are critical input for end-user-targeted development of novel mycotoxin detection platforms.

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A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis

et al. 2023

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The analytical performance of a compact infrared attenuated total reflection spectrometer using a pyroelectric detector array has been evaluated and compared to a conventional laboratory Fourier transform infrared system for applications in food analysis. Analytical characteristics including sensitivity, repeatability, linearity of the calibration functions, signal-to-noise ratio, and spectral resolution have been derived for both approaches. Representative analytes of relevance in food industries (i.e., organic solvents, fatty acids, and mycotoxins) have been used for the assessment of the performance of the device and to discuss the potential of this technology in food and feed analysis.

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Optimizing extraction solvents for deoxynivalenol analysis in maize via infrared attenuated total reflection spectroscopy and chemometric methods

Abstract: Farmers, cereal suppliers and processors demand rapid techniques for the assessment of mould-associated contamination. Deoxynivalenol (DON) is among the most important Fusarium toxins and related to human and animal diseases...

Cited by 4 publications

References 46 publications

Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis

Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis

Stakeholder assessment for mycotoxin analysis: exploring the demand along the European food supply chain

A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis

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