Feasibility of FT–Raman spectroscopy for rapid screening for DON toxin in ground wheat and barley

Integrated Mycotoxin Management System in the Feed Supply Chain: Innovative Approaches

Exposure to mycotoxins is a worldwide concern as their occurrence is unavoidable and varies among geographical regions. Mycotoxins can affect the performance and quality of livestock production and act as carriers putting human health at risk. Feed can be contaminated by various fungal species, and mycotoxins co-occurrence, and modified and emerging mycotoxins are at the centre of modern mycotoxin research. Preventing mould and mycotoxin contamination is almost impossible; it is necessary for producers to implement a comprehensive mycotoxin management program to moderate these risks along the animal feed supply chain in an HACCP perspective. The objective of this paper is to suggest an innovative integrated system for handling mycotoxins in the feed chain, with an emphasis on novel strategies for mycotoxin control. Specific and selected technologies, such as nanotechnologies, and management protocols are reported as promising and sustainable options for implementing mycotoxins control, prevention, and management. Further research should be concentrated on methods to determine multi-contaminated samples, and emerging and modified mycotoxins.

Detection of mycotoxins and toxigenic fungi in cereal grains using vibrational spectroscopic techniques: a review

Nutrition-rich cereal grains and oil seeds are the major sources of food and feed for human and livestock, respectively. Infected by fungi and contaminated with mycotoxins are serious problems worldwide for cereals and oil seeds before and after harvest. The growth and development activities of fungi consume seed nutrients and destroy seed structures, leading to dramatic declines of crop yield and quality. In addition, the toxic secondary metabolites produced by these fungi pose a well-known threat to both human and animals. The existence of fungi and mycotoxins has been a redoubtable problem worldwide for decades but tends to be a severe food safety issue in developing countries and regions, such as China and Africa. Detection of fungal infection at an early stage and of mycotoxin contaminants, even at a small amount, is of great significance to prevent harmful toxins from entering the food supply chains worldwide. This review focuses on the recent advancements in utilising infrared spectroscopy, Raman spectroscopy, and hyperspectral imaging to detect fungal infections and mycotoxin contaminants in cereals and oil seeds worldwide, with an emphasis on recent progress in China. Brief introduction of principles, and corresponding shortcomings, as well as latest advances of each technique, are also being presented herein.

Fourier transform near-infrared and mid-infrared spectroscopy as efficient tools for rapid screening of deoxynivalenol contamination in wheat bran

BACKGROUND

Deoxynivalenol (DON) is the most common Fusarium mycotoxin occurring in wheat and wheat-derived products, with several adverse and toxic effects in animals and humans. Although bran fractions produced by milling wheat have numerous health benefits, cereal bran is the part of the grain with the highest concentration of DON, thus representing a risk for consumers. Increased efforts have been made to develop analytical methods suitable for rapid DON screening.

RESULTS

The applicability of Fourier transform near-infrared (FTNIR), or mid-infrared (FTMIR) spectroscopy, and their combination for rapid analysis of DON in wheat bran, was investigated for the classification of samples into compliant and non-compliant groups regarding the EU legal limit of 750 µg kg^-1 . Partial least squares-discriminant analysis (PLS-DA) and principal component-linear discriminant analysis (PC-LDA) were employed as classification techniques using a cutoff value of 400 µg kg^-1 DON to distinguish the two classes. Depending on the classification model, overall discrimination rates were from 87% to 91% for FTNIR and from 86% to 87% for the FTMIR spectral range. The FTNIR spectroscopy gave the highest overall classification rate of wheat bran samples, with no false compliant samples and 18% false noncompliant samples when the PC-LDA classification model was applied. The combination of the two spectral ranges did not provide a substantial improvement in classification results in comparison with FTNIR.

CONCLUSIONS

Fourier transform near-infrared spectroscopy in combination with classification models was an efficient tool to screen many DON-contaminated wheat bran samples and assess their compliance with EU regulations. © 2018 Society of Chemical Industry.

Quantitative assessment of zearalenone in maize using multivariate algorithms coupled to Raman spectroscopy

Zearalenone is a contaminant in food and feed products which are hazardous to humans and animals. This study explored the feasibility of the Raman rapid screening technique for zearalenone in contaminated maize. For representative Raman spectra acquisition, the ground maize samples were collected by extended sample area to avoid the adverse effect of heterogeneous component. Regression models were built with partial least squares (PLS) and compared with those built with other variable selection algorithms such as synergy interval PLS (siPLS), ant colony optimization PLS (ACO-PLS) and siPLS-ACO. SiPLS-ACO algorithm was superior to others in terms of predictive power performance for zearalenone analysis. The best model based on siPLS-ACO achieved coefficients of correlation (R_p) of 0.9260 and RMSEP of 87.9132 μg/kg in the prediction set, respectively. Raman spectroscopy combined multivariate calibration showed promising results for the rapid screening large numbers of zearalenone maize contaminations in bulk quantities without sample-extraction steps.

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method.

Risks to human and animal health related to the presence of deoxynivalenol and its acetylated and modified forms in food and feed

Deoxynivalenol (DON) is a mycotoxin primarily produced by Fusarium fungi, occurring predominantly in cereal grains. Following the request of the European Commission, the CONTAM Panel assessed the risk to animal and human health related to DON, 3-acetyl-DON (3-Ac-DON), 15-acetyl-DON (15-Ac-DON) and DON-3-glucoside in food and feed. A total of 27,537, 13,892, 7,270 and 2,266 analytical data for DON, 3-Ac-DON, 15-Ac-DON and DON-3-glucoside, respectively, in food, feed and unprocessed grains collected from 2007 to 2014 were used. For human exposure, grains and grain-based products were main sources, whereas in farm and companion animals, cereal grains, cereal by-products and forage maize contributed most. DON is rapidly absorbed, distributed, and excreted. Since 3-Ac-DON and 15-Ac-DON are largely deacetylated and DON-3-glucoside cleaved in the intestines the same toxic effects as DON can be expected. The TDI of 1 μg/kg bw per day, that was established for DON based on reduced body weight gain in mice, was therefore used as a group-TDI for the sum of DON, 3-Ac-DON, 15-Ac-DON and DON-3-glucoside. In order to assess acute human health risk, epidemiological data from mycotoxicoses were assessed and a group-ARfD of 8 μg/kg bw per eating occasion was calculated. Estimates of acute dietary exposures were below this dose and did not raise a health concern in humans. The estimated mean chronic dietary exposure was above the group-TDI in infants, toddlers and other children, and at high exposure also in adolescents and adults, indicating a potential health concern. Based on estimated mean dietary concentrations in ruminants, poultry, rabbits, dogs and cats, most farmed fish species and horses, adverse effects are not expected. At the high dietary concentrations, there is a potential risk for chronic adverse effects in pigs and fish and for acute adverse effects in cats and farmed mink.

Analytical techniques for deoxynivalenol detection and quantification in wheat destined for the manufacture of commercial products

The concern regarding toxicity from the presence of deoxynivalenol (DON) in wheat that affects both economy and public health leads to the need to find appropriate detection methods for determining the degree of DON contamination in terms of the equipment available and the speed required for obtaining the incidence. The objective of this study was to compare the performance of two alternative analytical techniques for DON quantification for use in the food industry with a reference technique. Samples of wheat and the commercial by-products were analysed by high-performance liquid chromatography (HPLC) with an ultraviolet detector as the reference method and the results compared with those obtained from a rapid lateral-flow immunochromatographic device (Reveal Q+) and of a Fourier-transform-infrared (FTIR) spectroscopy technique. Pearson’s correlation coefficient between the HPLC and Reveal-Q+ data (0.45), although significant (P<0.0003), was lower than that obtained between HPLC and the FTIR method (0.94, P<0.0001). Both methods were considered efficient in quantifying DON levels in wheat-flour samples. This study was aimed at assisting the producers in choosing an appropriate tool for the purpose of analysis and upon consideration of the available equipment.

A rapid Raman detection of deoxynivalenol in agricultural products

Mycotoxin results in financial damage and considerable safety risks. In this paper, the possibility of portable Raman system-based surface-enhanced Raman scattering (SERS) for a rapid detection of deoxynivalenol (DON) a mycotoxin in cereals was investigated. Under an optimized condition, SERS analysis for pure DON solution has a wide dynamic concentration range from 10^-7M to 10^-2M with the limit of detection (LOD) down to 100nM. Density functional theory (DFT) analysis at the level of B3LYP/6-311++G(d, p) was also preformed for vibrational assignment. For practical application, the LOD of the proposed Raman method for both DON-contaminated corns and kidney beans were validated as 10^-6M and the LOD for DON-contaminated oats was 10^-4M. As a perspective, the SERS-based technology could be developed into an alternatively promising assay for on-field detection of DON residues at various cereals due to it high sensitivity and selectivity.

Recent Advances for the Detection of Ochratoxin A

Ochratoxin A (OTA) is one of the mycotoxins secreted by Aspersillus and Penicillium that can easily colonize various grains like coffee, peanut, rice, and maize. Since OTA is a chemically stable compound that can endure the physicochemical conditions of modern food processing, additional research efforts have been devoted to develop sensitive and cost-effective surveillance solutions. Although traditional chromatographic and immunoassays appear to be mature enough to attain sensitivity up to the regulation levels, alternative detection schemes are still being enthusiastically pursued in an attempt to meet the requirements of rapid and cost-effective detections. Herein, this review presents recent progresses in OTA detections with minimal instrumental usage, which have been facilitated by the development of OTA aptamers and by the innovations in functional nanomaterials. In addition to the introduction of aptamer-based OTA detection techniques, OTA-specific detection principles are also presented, which exclusively take advantage of the unique chemical structure and related physicochemical characteristics.

Dispersive and FT-Raman spectroscopic methods in food analysis

Raman spectroscopy is a powerful technique for molecular analysis of food samples.

An empirical evaluation of three vibrational spectroscopic methods for detection of aflatoxins in maize

Three commercially available vibrational spectroscopic techniques, including Raman, Fourier transform near infrared reflectance (FT-NIR), and Fourier transform infrared (FTIR) were evaluated to help users determine the spectroscopic method best suitable for aflatoxin analysis in maize (Zea mays L.) grain based on their relative efficiency and predictive ability. Spectral differences of Raman and FTIR spectra were more marked and pronounced among aflatoxin contamination groups than those of FT-NIR spectra. From the observations and findings in our current and previous studies, Raman and FTIR spectroscopic methods are superior to FT-NIR method in terms of predictive power and model performance for aflatoxin analysis and they are equally effective and accurate in predicting aflatoxin concentration in maize. The present study is considered as the first attempt to assess how spectroscopic techniques with different physical processes can influence and improve accuracy and reliability for rapid screening of aflatoxin contaminated maize samples.

Feasibility of surface-enhanced Raman spectroscopy for rapid detection of aflatoxins in maize

Rapid and sensitive surface-enhanced Raman spectroscopy (SERS) for aflatoxin detection was employed for development of the models to classify and quantify aflatoxin levels in maize at concentrations of 0 to 1,206 μg/kg. Highly effective SERS substrate (Ag nanosphere) was prepared and mixed with a sample extract for SERS measurement. Strong Raman bands associated with aflatoxins and changes in maize kernels induced by aflatoxin contamination were observed in different SERS spectroscopic regions. The k-nearest neighbors (KNN) classification model yielded high classification accuracy and lower prediction error with no misclassification of contaminated samples as aflatoxin negative. The multiple linear regression (MLR) models showed a higher predictive accuracy with stronger correlation coefficients (r = 0.939-0.967) and a higher sensitivity with lower limits of detection (13-36 μg/kg) and quantitation (44-121 μg/kg) over other quantification models. Paired sample t test exhibited no statistically significant difference between the reference values and the predicted values of SERS in most chemometric models. The proposed SERS method would be a more effective and efficient analytical tool with a higher accuracy and lower constraints for aflatoxin analysis in maize compared to other existing spectroscopic methods and conventional Raman spectroscopy.

Imaging surface plasmon resonance for multiplex microassay sensing of mycotoxins

A prototype imaging surface plasmon resonance-based multiplex microimmunoassay for mycotoxins is described. A microarray of mycotoxin-protein conjugates was fabricated using a continuous flow microspotter device. A competitive inhibition immunoassay format was developed for the simultaneous detection of deoxynivalenol (DON) and zearalenone (ZEN), using a single sensor chip. Initial in-house validation showed limits of detection of 21 and 17 ng/mL for DON and 16 and 10 ng/mL for ZEN in extracts, which corresponds to 84 and 68 μg/kg for DON and 64 and 40 μg/kg for ZEN in maize and wheat samples, respectively. Finally, the results were critically compared with data obtained from liquid chromatography-mass spectrometry confirmatory analysis method and found to be in good agreement. The described multiplex immunoassay for the rapid screening of several mycotoxins meets European Union regulatory limits and represents a robust platform for mycotoxin analysis in food and feed samples.

Developments in mycotoxin analysis: an update for 2009-2010

This review highlights developments in mycotoxin analysis and sampling over a period between mid-2009 and mid-2010. It covers the major mycotoxins aflatoxins, Alternaria toxins, ergot alkaloids, fumonisins, ochratoxin, patulin, trichothecenes, and zearalenone. New and improved methods for mycotoxins continue to be published. Immunological-based method developments continue to be of wide interest in a broad range of formats. Multimycotoxin determination by LC-MS/MS is now being targeted at the specific ranges of mycotoxins and matrices of interest or concern to the individual laboratory. Although falling outside the main emphasis of the review, some aspects of natural occurrence have been mentioned, especially if linked to novel method developments.

Rapid surface plasmon resonance immunoassay for the determination of deoxynivalenol in wheat, wheat products, and maize-based baby food

A rapid screening assay (9 min/sample) has been developed and validated for the detection of deoxynivalenol in durum wheat, wheat products, and maize-based baby foods using an SPR biosensor. Through a single laboratory validation, the limits of detection (LOD) for wheat, wheat-based breakfast cereal, and maize-based baby food were 57, 9, and 6 μg/kg, respectively. Intra-assay and interassay precisions were calculated for each matrix at the maximum and half-maximum European Union regulatory limits and expressed as the coefficient of variation (CV). All CVs fell below 10% with the exception of the between-run CV for breakfast cereal. Recoveries at the concentrations tested ranged from 92 to 115% for all matrices. Action limits of 161, 348, and 1378 μg/kg were calculated for baby food, wheat-based breakfast cereal, and wheat, respectively, and the linear range of the assay was determined as 250-2000 μg/kg.