Low-Cost Pocket Fluorometer and Chemometric Tools for Green and Rapid Screening of Deoxynivalenol in Durum Wheat Bran.

Cereal crops are frequently contaminated by deoxynivalenol (DON), a harmful type of mycotoxin produced by several Fusarium species fungi. The early detection of mycotoxin contamination is crucial for ensuring safety and quality of food and feed products, for preventing health risks and for avoiding economic losses because of product rejection or costly mycotoxin removal. A LED-based pocket-size fluorometer is presented that allows a rapid and low-cost screening of DON-contaminated durum wheat bran samples, without using chemicals or product handling. Forty-two samples with DON contamination in the 40-1650 µg/kg range were considered. A chemometric processing of spectroscopic data allowed distinguishing of samples based on their DON content using a cut-off level set at 400 µg/kg DON. Although much lower than the EU limit of 750 µg/kg for wheat bran, this cut-off limit was considered useful whether accepting the sample as safe or implying further inspection by means of more accurate but also more expensive standard analytical techniques. Chemometric data processing using Principal Component Analysis and Quadratic Discriminant Analysis demonstrated a classification rate of 79% in cross-validation. To the best of our knowledge, this is the first time that a pocket-size fluorometer was used for DON screening of wheat bran.

Industrial-Scale Cleaning Solutions for the Reduction of Fusarium Toxins in Maize.

Grain cleaning is the most effective non-destructive post-harvest mitigation strategy to reduce high levels of mycotoxins on account of the removal of mold-infected grains and grain fractions with high mycotoxin content. In this study, the reduction in the concentration of some co-occurring Fusarium toxins in maize, namely deoxynivalenol (DON), zearalenone (ZEA) and fumonisins B1 and B2 (FBs), was evaluated at an industrial-scale level by mechanical removal (sieving and density separation) of dust, coarse, small, broken, shriveled and low-density kernels and/or optical sorting of defected kernels. Samples were dynamically collected according to the Commission Regulation No. 401/2006 along the entire process line. Mycotoxin analyses of water-slurry aggregate samples were performed by validated LC methods. Depending on the contamination levels in raw incoming maize, the overall reduction rates ranged from 36 to 67% for DON, from 67 to 87% for ZEA and from 27 to 67% for FBs. High levels of DON, ZEA and FBs were found in all rejected fractions with values, respectively, up to 3030%, 1510% and 2680%, compared to their content in uncleaned maize. Results showed that grain cleaning equipment based on mechanical and or optical sorting technologies can provide a significant reduction in Fusarium toxin contamination in maize.

Overview of Recent Liquid Chromatography Mass Spectrometry-Based Methods for Natural Toxins Detection in Food Products.

Natural toxins include a wide range of toxic metabolites also occurring in food and products, thus representing a risk for consumer health. In the last few decades, several robust and sensitive analytical methods able to determine their occurrence in food have been developed. Liquid chromatography mass spectrometry is the most powerful tool for the simultaneous detection of these toxins due to its advantages in terms of sensitivity and selectivity. A comprehensive review on the most relevant papers on methods based on liquid chromatography mass spectrometry for the analysis of mycotoxins, alkaloids, marine toxins, glycoalkaloids, cyanogenic glycosides and furocoumarins in food is reported herein. Specifically, a literature search from 2011 to 2021 was carried out, selecting a total of 96 papers. Different approaches to sample preparation, chromatographic separation and detection mode are discussed. Particular attention is given to the analytical performance characteristics obtained in the validation process and the relevant application to real samples.

Mass spectrometry-based electronic nose to authenticate 100% Italian durum wheat pasta and characterization of volatile compounds.

Headspace solid-phase microextraction (HS-SPME) coupled with mass spectrometry-based electronic nose (MS-eNose), in combination with multivariate statistical analysis was used as untargeted method for the rapid authentication of 100% Italian durum wheat pasta. Among the tested classification models, i.e. PCA-LDA, PLS-DA and SVMc, SVMc provided the highest accuracy results in both calibration (90%) and validation (92%) processes. Potential markers discriminating pasta samples were identified by HS-SPME/GC-MS analysis. Specifically, the content of a pattern of 8 out of 59 volatile organic compounds (VOCs) was significantly different between samples of 100% Italian durum wheat pasta and pasta produced with durum wheat of different origins, most of which were related to different lipidic oxidation in the two classes of pasta. The proposed MS-eNose method is a rapid and reliable tool to be used for authenticating Italian pasta useful to promote its typicity and preserving consumers from fraudulent practices.

An In-Silico Pipeline for Rapid Screening of DNA Aptamers against Mycotoxins: The Case-Study of Fumonisin B1, Aflatoxin B1 and Ochratoxin A.

Aptamers are single-stranded oligonucleotides selected by SELEX (Systematic Evolution of Ligands by EXponential Enrichment) able to discriminate target molecules with high affinity and specificity, even in the case of very closely related structures. Aptamers have been produced for several targets including small molecules like mycotoxins; however, the high affinity for their respective target molecules is a critical requirement. In the last decade, the screening through computational methods of aptamers for their affinity against specific targets has greatly increased and is becoming a commonly used procedure due to its convenience and low costs. This paper describes an in-silico approach for rapid screening of ten ssDNA aptamer sequences against fumonisin B1 (FB1, n = 3), aflatoxin B1 (AFB1, n = 2) and ochratoxin A (OTA, n = 5). Theoretical results were compared with those obtained by testing the same aptamers by fluorescent microscale thermophoresis and by magnetic beads assay for their binding affinity (KD) revealing a good agreement.

Rapid Authentication of 100% Italian Durum Wheat Pasta by FT-NIR Spectroscopy Combined with Chemometric Tools.

Italy is the country with the largest durum wheat pasta production and consumption. The mandatory labelling for pasta indicating the country of origin of wheat has made consumers more aware about the consumed pasta products and is influencing their choice towards 100% Italian wheat pasta. This aspect highlights the need to promote the use of domestic wheat as well as to develop rapid methodologies for the authentication of pasta. A rapid, inexpensive, and easy-to-use method based on infrared spectroscopy was developed and validated for authenticating pasta made with 100% Italian durum wheat. The study was conducted on pasta marketed in Italy and made with durum wheat cultivated in Italy (n = 176 samples) and on pasta made with mixtures of wheat cultivated in Italy and/or abroad (n = 185 samples). Pasta samples were analyzed by Fourier transform-near infrared (FT-NIR) spectroscopy coupled with supervised classification models. The good performance results of the validation set (sensitivity of 95%, specificity and accuracy of 94%) obtained using principal component-linear discriminant analysis (PC-LDA) clearly demonstrated the high prediction capability of this method and its suitability for authenticating 100% Italian durum wheat pasta. This output is of great interest for both producers of Italian pasta pointing toward authentication purposes of their products and consumer associations aimed to preserve and promote the typicity of Italian products.

A simple design for the validation of a FT-NIR screening method: Application to the detection of durum wheat pasta adulteration.

The demand for the development of fast, easy-to-use and low-cost analytical methods for food adulteration analysis has being increasing in the last years. Although infrared spectroscopic techniques offer these advantages, the validation of screening methods requiring the application of multivariate data treatment is less frequently described in literature thus limiting their use as routine tools in control laboratories for food fraud monitoring. In this paper, an EU-validation procedure for screening methods was successfully applied to a multivariate FT-NIR spectroscopic method for the screening of durum wheat pasta samples adulterated with common wheat at the screening target concentration of 3%. Good results in terms of the cut-off value (2.32% mass fraction of soft wheat) and false suspect rates (0.1% for blanks; 13% at 1% mass fraction) demonstrated that the present validation approach would be a proof-of-strategy to be used for multivariate infrared methods applied for screening purposes.

Aflatoxin Reduction in Maize by Industrial-Scale Cleaning Solutions.

Different batches of biomass/feed quality maize contaminated by aflatoxins were processed at the industrial scale (a continuous process and separate discontinuous steps) to evaluate the effect of different cleaning solutions on toxin reduction. The investigated cleaning solutions included: (i) mechanical size separation of coarse, small and broken kernels, (ii) removal of dust/fine particles through an aspiration channel, (iii) separation of kernels based on gravity and (iv) optical sorting of spatial and spectral kernel defects. Depending on the sampled fraction, dynamic or static sampling was performed according to the Commission Regulation No. 401/2006 along the entire cleaning process lines. Aflatoxin analyses of the water-slurry aggregate samples were performed according to the AOAC Official Method No. 2005.008 based on high-performance liquid chromatography and immunoaffinity column cleanup of the extracts. A significant reduction in aflatoxin content in the cleaned products, ranging from 65% to 84% with respect to the uncleaned products, was observed when continuous cleaning lines were used. Additionally, an overall aflatoxin reduction from 55% to 94% was obtained by combining results from separate cleaning steps. High levels of aflatoxins (up to 490 µg/kg) were found in the rejected fractions, with the highest levels in dust and in the rejected fractions from the aspirator and optical sorting. This study shows that a cleaning line combining both mechanical and optical sorting technologies provides an efficient solution for reducing aflatoxin contamination in maize.

Tracing the Geographical Origin of Durum Wheat by FT-NIR Spectroscopy.

Fourier transform near infrared (FT-NIR) spectroscopy, in combination with principal component-linear discriminant analysis (PC-LDA), was used for tracing the geographical origin of durum wheat samples. The classification model PC-LDA was applied to discriminate durum wheat samples originating from Northern, Central, and Southern Italy (n = 181), and to differentiate Italian durum wheat samples from those cultivated in other countries across the world (n = 134). Developed models were validated on a separated set of wheat samples. Different pre-treatments of spectral data and different spectral regions were selected and compared in terms of overall discrimination (OD) rates obtained in validation. The LDA models were able to correctly discriminate durum Italian wheat samples according to their geographical origin (i.e., North, Central, and South) with OD rates of up of 96.7%. Better results were obtained when LDA models were applied to the discrimination of Italian durum wheat samples from those originating from other countries across the world, having OD rates of up to 100%. The excellent results obtained herein clearly indicate the potential of FT-NIR spectroscopy to be used for the discrimination of durum wheat samples according to their geographical origin.

Fluorescence Polarization Immunoassay for the Determination of T-2 and HT-2 Toxins and Their Glucosides in Wheat.

T-2 and HT-2 toxins and their main modified forms (T-2 glucoside and HT-2 glucoside) may co-occur in cereals and cereal-based products. A fluorescence polarization immunoassay (FPIA) was developed for the simultaneous determination of T-2 toxin, HT-2 toxin and relevant glucosides, expressed as sum. The developed FPIA, using a HT-2-specific antibody, showed high sensitivity (IC50 = 2.0 ng/mL) and high cross-reactivity (100% for T-2 toxin and 80% for T-2 and HT-2 glucosides). The FPIA has been used to develop two rapid and easy-to-use methods using two different extraction protocols, based on the use of organic (methanol/water, 90:10, v/v) and non-organic (water) solvents, for the determination of these toxins in wheat. The two proposed methods showed analytical performances in terms of sensitivity (LOD 10 µg/kg) recovery (92-97%) and precision (relative standard deviations ≤13%), fulfilling the criteria for acceptability of an analytical method for the quantitative determination of T-2 and HT-2 toxins established by the European Union. Furthermore, the methods were then validated in accordance with the harmonized guidelines for the validation of screening methods included in the Regulation (EU) No. 519/2014. The satisfactory analytical performances, in terms of intermediate precision (≤25%), cut-off level (80 and 96 µg/kg for the two methods) and rate of false positives (<0.1%) confirmed the applicability of the proposed methods as screening method for assessing the content of these toxins in wheat at the EU indicative levels reported for T-2 and HT-2 toxins.

Determination of Fumonisin B1 in maize using molecularly imprinted polymer nanoparticles-based assay.

Fumonisin B1 (FB1) is a carcinogenic mycotoxin produced by Fusarium species contaminating maize. At present, fumonisin determination is performed using costly and demanding chromatography techniques or immunoassays. Recently, a molecularly imprinted polymer nanoparticles (nanoMIPs) - based assay (MINA) has been developed for FB1 detection. Herein, we have applied MINA for the determination of FB1 in naturally contaminated maize samples and results were compared with those obtained with ELISA and a reference HPLC method (AOAC No. 2001.04). The nanoMIPs as a recognition element mimicking antibodies used in ELISA were produced by solid phase synthesis and used in MINA for FB1 determination in 53 maize samples. As a result, 18 maize samples were contaminated with FB1 at levels higher than 0.25 mg/kg. Fumonisin concentrations from samples measured by MINA were well correlated with those using ELISA and HPLC. Therefore, MINA could be used as an alternative technique for FB1 determination in maize.

Performance Evaluation of LC-MS Methods for Multimycotoxin Determination.

The co-occurrence of regulated mycotoxins in foods and feeds, together with modified ("masked") and emerging mycotoxins, has been increasingly reported worldwide in recent years. Therefore, sensitive, accurate, and validated methods for the simultaneous determination of these hazardous contaminants in different matrices are highly demanded to fulfil regulatory requirements and to carry out reliable surveillance programs. In these last years, LC-MS methodologies for multimycotoxin screening and/or quantification are being routinely used in control laboratories. However, to date, only one European Standard for multimycotoxin determination is based on LC-MS (EN 16877:2016). The need for standardized LC-MS methods for multimycotoxin determination has been highlighted by regulatory authorities and scientific advisory bodies, including the U.S. Food and Drug Administration and the European Commission. The European Committee for Standardization (CEN) has issued calls for tender for the development of standardized LC-MS methods for mycotoxins in food and animal feeding stuffs. As deliverables, some LC-MS based methods for multimycotoxin determination are currently under approval as European Standards. In addition, the European Commission has recently established specific criteria with which screening methods for mycotoxins, including LC-MS methods, have to comply for use for regulatory purposes. Validation procedures by single-laboratory and collaborative trials have been defined. This paper provides insights and advances on guidelines and tools for performance evaluation of LC-MS methods intended for quantitative determination and for semiquantitative screening of multimycotoxins. In particular, performance criteria set in the European Union and the United States are critically overviewed, and expectations, needs, and future challenges relevant to LC-MS methods for multimycotoxin determination are also discussed.

Rapid screening of ochratoxin A in wheat by infrared spectroscopy.

The use of infrared spectroscopy for the screening of 229 unprocessed durum wheat samples naturally contaminated with OTA has been investigated. Samples were analysed by both Fourier Transform near- and mid-infrared spectroscopy (FT-NIR, FT-MIR). Partial-Least Squares-Discriminant Analysis (PLS-DA) and Principal Component-Linear Discriminant Analysis (PC-LDA) classification models were used to differentiate highly contaminated durum wheat samples from low contaminated ones and the performances of the resulting models were compared. The overall discrimination rates were higher than 94% for both FT-NIR and FT-MIR range by using a cut-off limit set at 2 µg/kg OTA, independently from the classification model used thus confirming the reliability of the two statistical approaches used. False compliant rates of 6% were obtained for both spectral ranges and both classification models. These findings indicate that FT-NIR, as well as FT-MIR analysis, might be a promising, inexpensive and easy-to-use screening tool to rapidly discriminate unprocessed wheat samples for OTA content.

Evaluation of Mycotoxin Screening Tests in a Verification Study Involving First Time Users.

(AFB1) in maize and wheat using LFD and LC-HRMS, respectively. The results of analyses were used to calculate intermediate precision (RSDip, covering the inter-analyst variability in preparing the analytical samples and the precision under repeatability conditions) cut-off values and false suspect rates. RSDip ranged from 6.5% to 30% for DON, and from 16% to 33% for AFB1. The highest obtained variances were associated with the AFB1 analyses due to working with much lower mass fractions. The rate of false suspect results were lower than 0.1% for all tested methods. All methods showed a fit-for-purpose method performance profile, which allowed a clear distinction of samples containing the analytes at the screening target concentration (STC) from negative control samples. Moreover, the first time users obtained method performances similar to those obtained for validation studies previously performed on the screening methods included in the training course.

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.

Rapid prediction of deoxynivalenol contamination in wheat bran by MOS-based electronic nose and characterization of the relevant pattern of volatile compounds.

BACKGROUND: Deoxynivalenol (DON) is a mycotoxin, mainly produced by Fusarium sp., most frequently occurring in cereals and cereal-based products. Wheat bran refers to the outer layers of the kernel, which has a high risk of damage due to chemical hazards, including mycotoxins. Rapid methods for DON detection in wheat bran are required. RESULTS: A rapid screening method using an electronic nose (e-nose), based on metal oxide semiconductor sensors, has been developed to distinguish wheat bran samples with different levels of DON contamination. A total of 470 naturally contaminated wheat bran samples were analyzed by e-nose analysis. Wheat bran samples were divided in two contamination classes: class A ([DON] ≤ 400 µg kg-1 , 225 samples) and class B ([DON] > 400 µg kg-1 , 245 samples). Discriminant function analysis (DFA) classified wheat bran samples with good mean recognizability in terms of both calibration (92%) and validation (89%). A pattern of 17 volatile compounds of wheat bran samples that were associated (positively or negatively) with DON content was also characterized by HS-SPME/GC-MS. CONCLUSIONS: These results indicate that the e-nose method could be a useful tool for high-throughput screening of DON-contaminated wheat bran samples for their classification as acceptable / rejectable at contamination levels close to the EU maximum limit for DON, reducing the number of samples to be analyzed with a confirmatory method. © 2018 Society of Chemical Industry.

Comparison of In-Solution Biorecognition Properties of Aptamers against Ochratoxin A.

Ochratoxin A (OTA) is a mycotoxin produced as a secondary metabolite by several species of Aspergillus and Penicillium and frequently found as a natural contaminant in a wide range of food commodities. Novel and robust biorecognition agents for detecting this molecule are required. Aptamers are artificial nucleic acid ligands able to bind with high affinity and specificity to a given target molecule. In the last few years, three separate research groups have selected aptamers for ochratoxin A. While each of these three families of aptamers have been incorporated into various methods for detecting OTA, it is unclear if each aptamer candidate is better suited for a particular application. Here, we perform the first head-to-head comparison of solution-based binding parameters for these groups of aptamers. Based on our results, we provide recommendations for the appropriate choice of aptamer for incorporation into solution-based biorecognition assays and applications.

Screening and Identification of DNA Aptamers to Tyramine Using in Vitro Selection and High-Throughput Sequencing.

Aptamers are synthetic single-stranded DNA or RNA sequences that can fold into tertiary structures allowing them to interact with and bind to targets with high affinity and specificity. This paper describes the first selection and identification of DNA aptamers able to recognize the biogenic amine tyramine. To successfully isolate aptamers to this challenging small molecule target, the SELEX methodology was adapted by combining a systematic strategy to increase the selection stringency and monitor enrichment success. As the benefits of applying high-throughput sequencing (HTS) in SELEX experiments is becoming more clear, this method was employed in combination with bioinformatics analysis to evaluate the utility of the selection strategy and to uncover new potential high affinity sequences. On the basis of the presence of consensus regions (sequence families) and family similarities (clusters), 15 putative aptamers to tyramine were identified. A recently described workflow approach to perform a primary screening and characterization of the aptamer candidates by microequilibrium dialysis and by microscale thermophoresis was next leveraged. These candidate aptamers exhibited dissociation constant (Kd) values in the range of 0.2-152 µM with aptamer Tyr_10 as the most promising one followed by aptamer Tyr_14. These aptamers could be used as promising molecular recognition tools for the development of inexpensive, robust and innovative biosensor platforms for the detection of tyramine in food and beverages.

Comprehensive analytical comparison of strategies used for small molecule aptamer evaluation.

Nucleic acid aptamers are versatile molecular recognition agents that bind to their targets with high selectivity and affinity. The past few years have seen a dramatic increase in aptamer development and interest for diagnostic and therapeutic applications. As the applications for aptamers expand, the need for a more standardized, stringent, and informative characterization and validation methodology increases. Here we performed a comprehensive analysis of a panel of conventional affinity binding assays using a suite of aptamers for the small molecule target ochratoxin A (OTA). Our results highlight inconsistency between conventional affinity assays and the need for multiple characterization strategies. To mitigate some of the challenges revealed in our head-to-head comparison of aptamer binding assays, we further developed and evaluated a set of novel strategies that facilitate efficient screening and characterization of aptamers in solution. Finally, we provide a workflow that permits rapid and robust screening, characterization, and functional verification of aptamers thus improving their development and integration into novel applications.

Rapid analysis of deoxynivalenol in durum wheat by FT-NIR spectroscopy.

Fourier-transform-near infrared (FT-NIR) spectroscopy has been used to develop quantitative and classification models for the prediction of deoxynivalenol (DON) levels in durum wheat samples. Partial least-squares (PLS) regression analysis was used to determine DON in wheat samples in the range of <50-16,000 µg/kg DON. The model displayed a large root mean square error of prediction value (1,977 µg/kg) as compared to the EU maximum limit for DON in unprocessed durum wheat (i.e., 1,750 µg/kg), thus making the PLS approach unsuitable for quantitative prediction of DON in durum wheat. Linear discriminant analysis (LDA) was successfully used to differentiate wheat samples based on their DON content. A first approach used LDA to group wheat samples into three classes: A (DON ≤ 1,000 µg/kg), B (1,000 < DON ≤ 2,500 µg/kg), and C (DON > 2,500 µg/kg) (LDA I). A second approach was used to discriminate highly contaminated wheat samples based on three different cut-off limits, namely 1,000 (LDA II), 1,200 (LDA III) and 1,400 µg/kg DON (LDA IV). The overall classification and false compliant rates for the three models were 75%-90% and 3%-7%, respectively, with model LDA IV using a cut-off of 1,400 µg/kg fulfilling the requirement of the European official guidelines for screening methods. These findings confirmed the suitability of FT-NIR to screen a large number of wheat samples for DON contamination and to verify the compliance with EU regulation.