A rapid fluorescence polarization (FP) immunoassay has been developed for the simultaneous determination of T-2 and HT-2 toxins in naturally contaminated wheat samples. Syntheses of four fluorescein-labelled T-2 orHT-2 toxin tracers were carried out and their binding response with sevenmonoclonal antibodies was evaluated. The most sensitive antibody-tracer combination was obtained by using an HT-2- specific antibody and a fluorescein-HT-2 tracer. The developed competitive FP immunoassay in solution showed high crossreactivity for T-2 toxin (CR%=100%) while a very low CR% for neosolaniol (0.12%) and no cross-reactivity with other mycotoxins frequently occurring in wheat. A rapid extraction procedure using 90% methanol was applied to wheat samples prior to FP immunoassay. The average recovery from spiked wheat samples (50 to 200 ?g kg-1) was 96% with relative standard deviation generally lower than 8%. A limit of detection of 8 ?g kg-1 for the combined toxins was determined. Comparative analyses of 45 naturally contaminated and spiked wheat samples by both the FP immunoassay and high-performance liquid chromatography/immunoaffinityclean-up showed a good correlation (r=0.964). These results, combined with the rapidity (10 min) and simplicity of the assay, show that this method is suitable for high throughput screening as well as for quantitative determination of T-2 and HT-2 toxins in wheat.

Introduction: The Quality Level (QL) of table grape is defined through sensory evaluation of the its overall appearance by a five-point rating scale (from 5: excellent to 1: extremely poor). Since this evaluation is dependent on subjective judgments, the aim of this work was to develop methods based on MS-eNose and 1H NMR data for an objective QL assessment of two table grape cultivars, i.e. Vittoria and Italia.Methods: Table grape bunches were stored at 5 and 10 °C and sampled after a number of days needed to reach each QL. Berries were homogenized, centrifuged and the supernatant was analyzed by HS-SPME MS-eNose and 1H NMR. LDA and PLS-DA were applied on data to discriminate samples based on the five QLs (five class discrimination) and on their marketability/non-marketability (two class discrimination).Results: The model performances were expressed in terms of the prediction ability calculated by V-fold cross-validation procedure (CV=20%). For both cultivar, NMR model average prediction abilities ranged from 92 to 93%, and from 76 to 79%, in the two and five class discrimination, respectively. Better results were obtained in case of the MS-eNose models with mean prediction abilities ranged from 98 to 100% (two class discrimination), and from 86 to 100% (five class discrimination). In particular, the best prediction abilities of 100% were obtained in case of cv. Vittoria for MS-eNose PCA-LDA in both discriminations (two and five class discriminations) and for MS-eNose PLS-DA in the two class discimination.Conclusions: Taking into account the results obtained, both analytical technologies adopted herein could be used as valid and rapid tools for the table grape quality evaluation. In details, although NMR data can provides additional information on the identification of quality marker metabolites MS-eNose predictive models showed better performances in both types of discriminations.

The significance of laboratory sample preparation for the determination of two important mycotoxins, ochratoxin A (OTA) and deoxynivalenol (DON), in wheat was investigated by comparing water-slurry mixing and dry-milling procedures. The distribution of OTA and DON in 10 kg samples of naturally contaminated wheat was established by analyzing one hundred 100 g subsamples of each sample. A normal distribution and a good repeatability of DON measurements was observed for both water-slurry mixing (mean 2290 microg/kg, CV 4.6%, median 2290 microg/kg) and dry milling (mean 2310 microg/kg, CV 6.4%, median 2290 microg/kg) procedures. For OTA determinations, reliable results could be obtained only by slurry mixing sample preparation (mean 2.62 microg/kg, CV 4.0%, median 2.62 microg/kg), whereas dry-milling comminution resulted in an inhomogeneous distribution with a high variability (mean 0.83 microg/kg, CV 75.2%, median 0.60 microg/kg) and a positive skewness (2.12). Ad hoc experiments were performed on different size portions of the same sample (10 kg) to assess accuracy and precision of the comminution/homogenization procedures (slurry mixing and dry milling). Very good results were obtained for DON determination with both procedures in terms of accuracy (>98.7% of the "weighted value") and precision (CV <3%). For OTA determination good results were only obtained by slurry mixing (99.4% of the "weighted value," CV 10%), whereas dry milling provided results with low accuracy (43.2% of the "weighted value") and high variability (CV 110%). This study clearly demonstrated that sample preparation by slurry mixing is strictly necessary to obtain reliable laboratory samples for OTA determination in wheat to minimize misclassification of acceptable/rejectable lots, mainly within official control.

A rapid and accurate fluorescence polarization (FP) immunoassay has been optimized for the determination of deoxynivalenol (DON) in wheat bran and whole-wheat flour. A preliminary treatment with activated charcoal was used to eliminate the strong matrix effect due to highly colored interfering compounds present in raw wheat bran extracts. In particular, matrix effect was removed by adding activated charcoal to the wheat bran extract (3.5 mg/mL) and mixing for 3 min of incubation time prior to the FP immunoassay analysis. No preliminary treatment was necessary for whole-wheat flour. Average recoveries from samples spiked with DON at levels of 500, 1,000, and 1,500 mu g/kg were 95 % for wheat bran and 94 % for whole-wheat flour, with relative standard deviation generally lower than 13 %. Limits of quantification of the optimized FP immunoassay were 120 mu g/kg for both matrices. The overall time of analysis was lower than 15 min for wheat bran and 10 min for whole-wheat flour. Good correlations (r > 0.971) were observed between DON contents obtained by both FP immunoassay and high-performance liquid chromatography with immunoaffinity cleanup for 37 and 23 samples of naturally contaminated wheat bran and whole-wheat flour, respectively. These results show that the FP immunoassay is suitable for high-throughput screening as well as for quantitative determination of DON in wheat bran and whole-wheat flour.

A rapid fluorescence polarization immunoassay (FPIA) was optimized and validated for the determination of ochratoxin A (OTA) in rye and rye crispbread. Samples were extracted with a mixture of acetonitrile/water (60:40, v/v) and purified by SPE-aminopropyl column clean-up before performing the FPIA. Overall mean recoveries were 86 and 95% for spiked rye and rye crispbread with relative standard deviations lower than 6%. Limits of detection (LOD) of the optimized FPIA was 0.6 mug/kg for rye and rye crispbread, respectively. Good correlations (r > 0.977) were observed between OTA contents in contaminated samples obtained by FPIA and high-performance liquid chromatography (HPLC) with immunoaffinity cleanup used as reference method. Furthermore, single laboratory validation and small-scale collaborative trials were carried out for the determination of OTA in rye according to Regulation 519/2014/EU laying down procedures for the validation of screening methods. The precision profile of the method, cut-off level and rate of false suspect results confirm the satisfactory analytical performances of assay as a screening method. These findings show that the optimized FPIA is suitable for high-throughput screening, and permits reliable quantitative determination of OTA in rye and rye crispbread at levels that fall below the EU regulatory limits.

Lentil (Lens culinaris Medik.) is the fourth most important pulse crop in the world after bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), and chickpea (Cicer arietinum L.). Canada is the world's largest exporter of lentils, while in Italy lentils are a minor legume and can be found in restricted areas. However, Italian lentils present unique and characteristic qualities giving them a higher value, so that many of them have obtained international and national marks linked to their geographical origins, such as "protected geographical indication" (PGI), "traditional food products" (PAT) and Slow Food Presidium. For these reasons, there is a growing demand for analytical methods able to certify the declared geographical origin of lentils, in order to protect consumers and producers from fraud and unfair competition. In the present work, non-targeted 1H-NMR fingerprinting, in combination with different multivariate statistical analysis techniques, was used to classify lentils according to their geographical origin. In particular, 85 lentil samples from two different countries, i.e. Italy and Canada, were collected from retail markets and analysed by using an optimized 1H-NMR protocol. Principal component analysis showed partial grouping of samples on the basis of origin with overlapping zones. Therefore, a class-modeling technique, Soft Independent Modelling of Class Analogy (SIMCA), and three discriminant techniques, such as k - Nearest Neighbor (k-NN), Linear Discriminant Analysis (LDA), Partial Least Squares - Discriminant Analysis (PLS-DA), were used and the performances of the resulting models were compared. The best average recognition and cross-validation prediction abilities, 100% and 93.7% respectively, were obtained by the LDA model, performed on a set of 20 principal components previously selected by a stepwise decorrelation procedure. The other models, except the SIMCA one, also showed good performances (above 90%). All tested statistical models were validated by evaluating the prediction abilities on an external set of lentil samples. LDA model showed the best results with an external prediction ability of 100%, but also the other models showed remarkable performances (above or near 90%).These findings demonstrated the suitability of the methods developed to discriminate geographical origin of lentils and confirmed the applicability of the NMR data, in combination with chemometrics, to solve geographic origin issues of foodstuffs.

Introduction:In the last years the Italian imports of oranges, mainly from Spain and South-Africa, have significantly increased, therefore there is a real possibility for the Italian consumer to buy foreign products sold fraudulently as Italian. For this reason, in this work an HS-SPME/MS-eNose method for the discrimination of the geographical origins of oranges was developed and validated.Methods: Oranges samples coming from Italy, Spain and South Africa were analyzed by an HS-SPME/MS-eNose method. Subsequently, three multivariate statistical models, i.e. PCA/LDA, SELECT/LDA and PLS-DA, were built for the geographical origin discrimination and the relevant performances were compared. Moreover, an HS-SPME/GC-MS method combined with ANOVA was used to identify discriminating compounds. Results:Although all tested statistical models gave acceptable performance, the SELECT/LDA model showed the highest percentages in terms of prediction ability in cross-validation and external validation, with average values of 97.8% and 95.7%, respectively. In particular, the external prediction ability of 95.7% was obtained with all South African and Spanish samples correctly recognized while only 2 samples out of 19 Italian samples were not correctly assigned, with a specific prediction rates of 89.5%. Moreover HS-SPME/GC-MS analysis showed that, although 28 out of 65 identified VOCs had a different content in samples belonging to different origin classes, no compound was able to discriminate at the same time the three geographical origins.Conclusions: In this study, a rapid and inexpensive method based on MS-eNose analysis in combination with chemometrics was successfully used to discriminate oranges coming from Italy, Spain and South Africa. Although HS-SPME/GC-MS analysis showed the absence of specific markers, differences in the pattern and content of VOCs of orange samples of the three different geographical origins were observed.

Lentil (Lens culinaris Medik.) is the fourth most important pulse crop in the world after bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), and chickpea (Cicer arietinum L.). Canada is the world's largest exporter of lentils, while in Italy lentils are a minor legume and can be found in restricted areas. However, Italian lentils present unique and characteristic qualities giving them a higher value, so that many of them have obtained international and national marks linked to their geographical origins, such as "protected geographical indication" (PGI), "traditional food products" (PAT) and Slow Food Presidium. For these reasons, there is a growing demand for analytical methods able to certify the declared geographical origin of lentils, in order to protect consumers and producers from fraud and unfair competition. In the present work, non-targeted 1H-NMR fingerprinting, in combination with different multivariate statistical analysis techniques, was used to classify lentils according to their geographical origin. In particular, 85 lentil samples from two different countries, i.e. Italy and Canada, were collected from retail markets and analysed by using an optimized 1H-NMR protocol. Principal component analysis showed partial grouping of samples on the basis of origin with overlapping zones. Therefore, two class-modeling techniques such as Soft Independent Modelling of Class Analogy (SIMCA) and UNEQual dispersed classes (UNEQ) and three discriminant techniques, such as k - Nearest Neighbor (k-NN), Linear Discriminant Analysis (LDA), Partial Least Squares - Discriminant Analysis (PLS-DA), were used and the performances of the resulting models were compared. The best average recognition and cross-validation prediction abilities, 100% and 93.7% respectively, were obtained by the LDA model, performed on a set of 20 principal components previously selected by a stepwise decorrelation procedure. The other models, except the SIMCA one, also showed good performances (above 90%). All tested statistical models were validated by evaluating the prediction abilities on an external set of lentil samples. LDA model showed the best results with an external prediction ability of 100%, but also the other models showed remarkable performances (above or near 90%).These findings demonstrated the suitability of the methods developed to discriminate geographical origin of lentils and confirmed the applicability of the NMR data, in combination with chemometrics, to solve geographic origin issues of foodstuffs.

Deoxynivalenol (DON) is a Fusarium toxin which frequently occurs in grains. Because of the toxic effectsinduced by DON, many regulations worldwide have established safety levels in food and feed. For instance,the EC maximum limit for DON in unprocessed wheat bran has been set at 750 ?g/kg. New devices areenvisaged for the rapid detection of DON in grain stocks in order to verify the compliance with EUregulation and to perform a quick assessment of contamination without using chemicals and benchanalytical instruments. Optical spectroscopy is currently emerging as a modern and "green" analyticaltechnique for intact food analyses, thanks to the non-destructive nature of light measurements whichenable rapid checks without making use of reagents or chemical treatments, thus avoiding the problem ofwaste disposal.The objective of this study was to assess the use of Raman spectroscopy, excited at 1064 nm by using adispersive detection scheme, for rapid screening of DON in wheat bran. Twelve wheat bran samplescontaminated with DON in the range <=100-1600 ?g/kg were considered. Four replica measurements werecarried out for each sample, thus taking into account unavoidable inhomogeneity of contamination. Ramanspectra were processed using Standard Normal Variate (SNV) and Orthogonal Signal Correction (OSC) forcompensation of scattering influence, and removal of DON-independent effects. Then, Partial Least Squareregression was applied as a predictive model for DON quantification. A coefficient of determinationR2=0.72 was obtained, together with a root means square error of calibration RMSEC=313 ?g/kg, thusindicating that Raman spectroscopy has good potential as a rapid tool for DON detection.

Fungal starter, such as Penicillium nalgiovense, are commonly used to inoculate sausages before seasoning process. However, P. nordicum, a well-known ochratoxin A (OTA) producer frequently isolated from seasoning rooms, could colonize the casing surface during the early stage of production. The relationship between OTA accumulation and simultaneous inoculation of P. nalgiovense and P. nordicum at different rates was evaluated. After 14 days of seasoning, the persistence of P. nordicum was assessed by LAMP assay revealing its capability to colonize and grow on salami surface at all the contamination rates. At the end of seasoning, OTA was accumulated both in mycelium and dry-cured meat when P. nordicum contamination rate ranged from 25% to 100% of inoculum, while no OTA was detected in dry-cured meat at 2.5% and 0.25%. Results demonstrated that contamination of fungal starter by P. nordicum could represent a serious concern during salami production and therefore represents an important critical point to be monitored.

Mycotoxins are naturally occurring toxic metabolites produced by filamentous fungi under a wide range of climatic conditions on different agricultural crops during growth, drying and subsequent storage. Monitoring, control, risk assessment and prevention of mycotoxins in foods are important issues worldwide associated with public health, agricultural production, food processing and trade. For these reasons the European Commission has set recommended levels or maximum permitted levels for mycotoxins of major concern in a wide range of foodstuffs.Analytical methods for the determination of mycotoxins in foods are commonly based on chromatographic techniques (GC, HPLC or LC-MS). Although these methods permit a sensitive and accurate determination of the analyte, they require skilled personnel and are time-consuming, expensive, and unsuitable for screening purposes. Simple, rapid, and more effective screening methods for mycotoxins determination are highly demanded.Fluorescence polarization immunoassay (FPIA) is a homogenous assay that measures competition between a fluorescently labelled antigen (tracer) and unlabelled antigen in solution for binding a specific antibody. The FP signal is inversely related to the antigen content that competes with the tracer, and it increases when the binding of specific antibody to the tracer increases. Unlike most immunoassays (e.g., ELISA), the main advantage of this format is that additional manipulation steps, as multiple washing steps or separation of free from antibody-bound analyte, are not necessary. The selection of the appropriate antibody-tracer combination determines the speed, accuracy, precision and sensitivity of a FPIA. Incubation times, cross-reactivity, compatibility with organic solvents and matrix effects are analytical parameters to be evaluated and optimized in the development of a FPIA. We have recently developed several FPIAs for the determination of mycotoxins in cereals and processed products, including deoxynivalenol in wheat and derived products, ochratoxin A in wheat, T-2 and HT-2 toxins in wheat, barley, oats and oatflakes [1-3]. An accurate validation of these assays has been performed on each tested matrix using either artificially and naturally contaminated samples, and reference materials. These FPIAs are rapid, easy-to-use, readily automated, and suitable for high-throughput screening as well as for the quantitative determination of mycotoxins in foodstuffs at levels below regulatory levels.

Fluorescence polarisation immunoassay (FPIA) is a type of homogeneous assay. For low molecular weight antigens, such as mycotoxins, it is based on the competition between an unlabeled antigen and its fluorescent-labelled derivative (tracer) for an antigen-specific antibody. The antigen content is determined by measuring the reduction of fluorescence polarisation signal, which in turn is determined by the reduction of tracer molecules able to bind antibody in solution. To develop a competitive FPIA for mycotoxin measurement the tracer has to be synthesised and its binding response with a specific antibody should be tested. Selectivity and sensitivity of the FPIA methods are strictly related to the antibody/tracer combination used. Several FPIA methods for the detection of the major mycotoxins, including aflatoxins, fumonisins, ochratoxin A, deoxynivalenol, T-2 and HT-2 toxins and zearalenone in food and beverages have been developed in the last decade. Basic principles, key elements, advantages and limitations of these methods are reviewed. These FPIA methods are simple, readily automated, rapid, and suitable for high-throughput screening, as well as for the reliable quantitative determination of mycotoxins in foods and commodities.

T-2 toxin (T-2) and HT-2 toxin (HT-2) are type A trichothecene mycotoxins produced by several Fusarium species, mainly Fusarium sporotrichioides, Fusarium langsethiae and Fusarium poae. Generally, these Fusarium species can grow on cereals and produce T-2 and HT-2 under moist cool conditions already prior to harvesting [1]. Among cereals, oats, wheat, rye and derived products are key dietary sources of T-2 and HT-2 exposure [1]. Fluorescence polarization (FP) immunoassay is a homogeneous technique that is getting attention as a screening tool in food safety control due to its simplicity, rapidity, cheapness and reliability. A rapid, sensitive and reliable FP immunoassay has been recently reported for the determination of the sum of T-2 and HT- 2 toxins in wheat [2]. The aim of present work was to evaluate the applicability of the above-mentioned FP immunoassay to other unprocessed cereals, such as rye, and cereal-based products, such as oats crispbread, for the quantitative determination of the total content of T-2 and HT-2. The concept of determining the total content of T-2 and HT-2 in cereal samples for both official control purposes and risk assessment studies results in line with the EC Recommendation [3]. No purification step of extracts was required, although in order to reduce the matrix effect a dilution step with NaCl solution (4 % for rye and 1% for oats crispbread), in a ratio 1:5 (v/v), was necessary to let precipitation of proteins and matrix interfering compounds. For the optimized FP immunoassay, LOD of 0.20 ng/mL (equivalent to 20 ?g/kg in rye and oats crispbread) was calculated. Overall mean recoveries of the optimized FP immunoassay were 105 and 107% for rye and oats crispbread, respectively, with relative standard deviations lower than 4%. The analytical performances of the optimized FP immunoassay in terms of accuracy and precision fulfill the criteria established by the European Commission [4]. In addition, a comparative analysis of the levels of contamination in spiked and blank samples was performed by both FP immunoassay and UHPLC method. In particular, a total of 30 rye and oats crispbread samples, of which 20 spiked samples at levels from 50 to 700 ?g/kg and 10 uncontaminated samples, were analyzed. The proposed method coupled performances in terms of sensitivity, accuracy and precision comparable to those of a chromatographic technique with rapidity (20 min), costs and simplicity typical of a high-throughput screening method and can be used as a valid alternative to more expensive and time-consuming LC methods for quantitative determination in rye and oats crispbread [5].ACKNOWLEDGMENTSThis work has been supported by the Italian Ministry of Education, University and Research (MIUR) project no. CTN01_00230 CL.A.N. Cluster Tecnologici Nazionali - SAFE&SMART project "New enabling technologies for food safety and food chain integrity within a global scenario". REFERENCES[1] EFSA Panel on Contaminants in the Food Chai

A sensitive and accurate fluorescence polarization (FP) immunoassay has been developed for the determination of ochratoxin A (OTA) in naturally contaminated wheat samples. A fluorescein-labeled OTA tracer was synthesized, and its binding response with three monoclonal antibodies was tested. The most sensitive competitive FP immunoassay showed an IC50 value of 0.48 ng/mL with a negligible cross-reactivity for ochratoxin B (1.7 %) and no cross-reactivity with other mycotoxins commonly occurring in wheat. The wheat sample was extracted with acetonitrile/water (60:40, v/v) and purified by a rapid solid-phase extraction procedure using an aminopropyl column prior to the FP immunoassay. The overall time of analysis was less than 20 min. The average recovery from spiked wheat samples (3 to 10 mu g/kg) was 87 %, with relative standard deviations generally lower than 6 %. Limits of detection and quantification were 0.8 and 2.0 mu g/kg, respectively. The trueness of the method was assessed by using two reference materials for OTA showing good accuracy and precision. A good correlation (r = 0.995) was observed between OTA contamination of 19 naturally contaminated wheat samples analyzed by both FP immunoassay and high-performance liquid chromatography/immunoaffinity clean-up used as reference method. These results show that the developed FP method is suitable for high-throughput screening, as well as for reliable quantitative determination of OTA in wheat at level far below the EU regulatory limits.

Fusarium toxins, a group of mycotoxins, can be produced by Fusarium fungi under temperate climatic conditions on agricultural commodities, mainly cereals, in field as well as during storage. As a defensive response of the host plant, Fusarium toxins can be metabolized by forming modified mycotoxins, often called "masked" mycotoxins. It has been shown that many modified forms are hydrolysed into the parent mycotoxin during digestion. In order to protect consumer health from the risk of exposure to modified and parent forms of Fusarium toxins, the development of rapid, sensitive and reliable methods for their simultaneous determination in cereals is highly demanded. Currently, fluorescence polarization immunoassay (FPIA) is getting the attention as a screening tool in food safety control due to its simplicity, rapidity, cheapness and reliability. The focus of our work is to develop and validate quantitative FPIAs for simultaneous determination of DON and its acetylated (3-acetyl-DON, 15-acetyl-DON) and glycosylated forms (DON-3-glucoside) and T-2/HT-2 toxins and their glycosylated forms (T2-glucoside, HT2-glucoside) in wheat. A fluorescein-label (tracer) of DON (DON-FL) and four T2- and HT2-fluerescein tracers (T2-FL, HT2-FL1a, HT2-FL1b and HT2-FL2) were synthesized and purified. The assessment of the antibody-tracer binding was performed using four DON monoclonal antibodies (MAbs), and ten T2-glucoside MAbs, one HT-2 MAb and two T-2 MAbs, at different concentrations. Concerning the FPIA for the determination of DON, its acetylated and glycosylated forms, the highest antibody-tracer binding was observed for the clone 22/DON-FL combination, while in the FPIA for the determination of T-2/HT-2 toxins and their glycosylated forms, the highest bindings were observed for thirteen T2-glucoside MAbs with T2-FL and HT2-FL1b combinations, as well as for HT-2 MAb/HT2-FL1a combination and for T-2 MAb/T2-FL and HT2-FL1a combinations. Competitive FPIAs were performed with the selected antibody combinations. In particular, FPIA for the determination of DON, its acetylated and glycosylated forms showed IC50=23.5 ng/mL for DON and exhibited 204%, 45% and 11% as cross-reactivity, respectively, for 3-acetyl-DON, DON-3-glucoside and 15-acetyl-DON. While, among the selected combinations for T-2 and HT-2, the HT-2/HT2-FL1a combination exhibited 80% as cross-reactivity for T-2 and its glycosylated form and the highest sensitivity, with IC50 = 2.0, 2.6 and 2.7 ng/mL for HT2, T-2 and T2-glucoside, respectively. These findings showed the applicability of the developed FPIAs to the determination of parent and modified mycotoxins, expressed as sum, in solution. This work was supported by the MYCOKEY project which has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No 678781.

Deoxynivalenol (DON) is a type B trichothecene mycotoxin mainly produced by several Fusarium species occurring in cereals. Chromatographic methods are the most widely used for quantitative determination of DON in foodstuffs and feedstuffs. However, these methods are destructive, time-consuming, expensive, unsuitable for screening purposes, and require a preliminary cleanup of the extracts. A range of alternative methods have been published, including infrared spectroscopy. Some studies on the use of near infrared spectroscopy and mid-infrared spectroscopy to predict DON contamination in whole grain and flour of wheat, maize and other grain cereals have been reported. The feasibility of using Fourier-transform near infrared (FT-NIR) spectroscopy for rapid and non-invasive analysis of DON in unprocessed durum wheat at levels close to the EU regulatory level (1750 µg/kg) has been recently reported. A partial least-squares (PLS) regression model was developed using correlation data between FT-NIR and HPLC/FLD (confirming method). We have further implemented the PLS model in a larger study involving more calibration (n = 230) and validation (n = 230) samples from different cultivars of wheat naturally contaminated with DON at levels up to about 16000 µg/kg DON. Slope, coefficients of correlation (r) and root mean square errors (RMSE) were close to 0.73, 0.85 and 300 µg/kg, respectively, in both calibration and validation PLS models. Similar results were obtained when the PLS model was developed by using the cross validation approach on the entire set of data.The reliability of FT-NIR spectroscopy for qualitative discrimination of wheat samples based on DON content was also investigated. Linear discriminant analysis (LDA) was performed on the same calibration and validation sets of durum wheat samples. When a cut-off limit of 1500 µg/kg was used to distinguish the samples classes, the LDA analysis was able to correctly classify more than 85% of wheat samples. Performances of LDA and of PLS regression models suggest that FT-NIR analysis might be a promising screening tool to rapidly analyse durum wheat samples for DON content. Further activities will be carried out to improve the predictive ability of the FT-NIR calibration models in the tested range

Deoxynivalenol (DON) is a mycotoxin mainly produced by several Fusarium species occurring in cereals andderived products. Rapid, robust and inexpensive methods using Fourier-Transform-Near Infrared (FT-NIR)spectroscopy have been recently developed at ISPA-CNR to predict DON levels in durum wheat. LinearDiscriminant Analysis (LDA) models were developed based on different cut-off limits (i.e. 1000, 1200 and1400 ?g/kg DON) that were set at levels lower than the EC maximum limit for DON in unprocessed durumwheat (i.e. 1750 ?g/kg). The overall classification rates of models were 89-91% with false compliant valuesof 3-7%. Model using a cut-off of 1400 ?g/kg fulfilled the requirement of the European official guidelinesfor screening methods. Partial Least-Squares (PLS) regression analysis was also used to determine DONcontent in wheat samples in the range of <50-6000 ?g/kg (as determined by a reference HPLC method). Themodel displayed good regression quality with a root mean square error (RMSE) of prediction of 868 ?g/kg.The feasibility of using FT-NIR spectroscopy was also investigated to rapidly predict DON in durum wheatbran at levels up to 1600 ?g/kg by both LDA and PLS analysis. The LDA model used a cut-off value of 400?g/kg that was lower than the EC maximum limit for DON in bran (i.e. 750 ?g/kg) and displayed aclassification rate of 80% with 5% of false compliant samples. Good performance results were also obtainedby applying the PLS statistical model, confirming a good fit between HPLC and FT-NIR data in the testedrange with an RMSE of cross-validation of 191 ?g/kg.These findings confirmed the suitability of FT-NIR to rapidly screen a large number of wheat samples forDON contamination and to verify the compliance with EU regulation.

Ochratoxin A (OTA) is a mycotoxin produced by several species of the genera Aspergillus and Penicillium, and can be frequently found in a variety of foods and beverages, including cereals, coffee, cocoa, spices, beer, wine, grape juice, and dried fruits. Effective monitoring of OTA should be undertaken and achieved through reliable and rapid analysis. Therefore, increased efforts have been made to develop analytical methods suitable for rapid OTA screening. In the present work the potential of using infrared spectroscopic for the screening of 229 wheat samples naturally contaminated with OTA in the range of < 0.15-54 µg/kg was investigated. Samples were analysed by both Fourier transform near- and mid-infrared spectroscopy (FT-NIR, FT-MIR). After a suitable pretreatment of the raw spectral data (baseline in combination with standard normal variate), Partial-Least Squares-Discriminant Analysis (PLS-DA) and Linear Discriminant Analysis (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. Models were developed using a cut-off limit set at 2 µg/kg OTA that is lower than the EC maximum limit for OTA in unprocessed durum wheat (i.e. 5 µg/kg). The spectral ranges considered were between 7500-4000 cm-1 for FT-NIR and 4000-400 cm-1 for FT-MIR. For each spectral range, the classification results of the external validation (70 samples) were expressed in terms of average prediction abilities and false compliant rates. The average prediction were 94% for FT-NIR range and 96% for FT-MIR range, independently from the classification model used (i.e. PLS-DA or LDA) thus confirming the reliability of the two statistical approaches used. False compliant rates of 9% were obtained for both spectral ranges and both classification models.These findings indicates that FT-NIR, as well as FT-MIR analysis, might be a promising, inexpensive and easy-to-use screening tool to rapidly discriminate wheat samples for OTA content and verify the compliance with the EU regulatory level.This work has been supported by the Italian Ministry of Education, University and Research (P.O.N. 2007-2013), project S.I.Mi.S.A. "New Strategies for Improvement of Food Safety: Prevention, Control, Correction".

Lentil samples coming from two different countries, i.e. Italy and Canada, were analysed using untargeted H-1 NMR fingerprinting in combination with chemometrics in order to build models able to classify them according to their geographical origin. For such aim, Soft Independent Modelling of Class Analogy (SIMCA), k-Nearest Neighbor (k-NN), Principal Component Analysis followed by Linear Discriminant Analysis (PCA-LDA) and Partial Least Squares-Discriminant Analysis (PLS-DA) were applied to the NMR data and the results were compared. The best combination of average recognition (100%) and cross-validation prediction abilities (96.7%) was obtained for the PCA-LDA. All the statistical models were validated both by using a test set and by carrying out a Monte Carlo Cross Validation: the obtained performances were found to be satisfying for all the models, with prediction abilities higher than 95% demonstrating the suitability of the developed methods. Finally, the metabolites that mostly contributed to the lentil discrimination were indicated. (C) 2017 Elsevier Ltd. All rights reserved.

T-2 and HT-2 toxins are mycotoxins produced by several Fusarium species that are commonly found in various cereal grains, including oats, barley, wheat and maize. Intake estimates indicate that the presence of these mycotoxins in the diet can be of concern for public health. In this work, the inclusion processes occurring between fluorescent anthracene-derivatives of T-2 and HT-2 toxinsand different cyclodextrin (CD) molecules were investigated in aqueous solutions by means of UV-Vis absorption, fluorescence emission and dynamic light scattering. Binding constant values and chemico-physical parameters were calculated. It was found that b-CDs give stronger inclusion reactions with both T-2 and HT-2 derivatives, as stated by important emission intensity increments. Suchinteractions were found to be fundamentally enthalpy-driven. Among b-CDs, the effect of the methylation at hydroxyl groups was tested: as a result, the di-methyl form of b-CD was found to induce the best fluorescence intensity enhancements.

A multiplex dipstick immunoassay based method for the simultaneous determination of major Fusarium toxins, namely zearalenone, T-2 and HT-2 toxins, deoxynivalenol and fumonisins in wheat, oats and maize has been developed. The dipstick format was based on an indirect competitive approach. Four test lines (mycotoxin-BSA conjugates) and one control line were located on the strip membrane. Labelled antibodies were freeze-dried within the microwell. Two matrix-related sample preparation protocols have been developed for wheat/oats (not containing fumonisins) and maize (containing fumonisins) respectively. The use of a methanol/water mixture for sample preparation allowed recoveries in the range 73-109% for all mycotoxins in all tested cereals, with relative standard deviation less than 10%. The optimized immunoassay was able to detect target mycotoxins at cut off levels equal to 80% of EU maximum permitted levels, i.e. 280, 400, 1400 and 3200 ?g kg-1, respectively, for zearalenone, T-2/HT-2 toxins, deoxynivalenol and fumonisins in maize, and 80, 400 and 1400 ?g kg-1, respectively, for zearalenone, T-2/HT-2 toxins and deoxynivalenol in wheat and oats. Analysis of naturally contaminated samples resulted in a good agreement between multiplex dipstick and validated confirmatory LC-MS/MS. The percentage of false positive results was less than or equal to 13%, whereas no false negative results were obtained. Data on the presence/absence of 6 mycotoxins at levels close to EU regulatory levels were obtained within 30 min. The proposed immunoassay protocol is rapid, inexpensive, easy-to-use and fit for purpose of rapid screening of mycotoxins in cereals.

The natural co-occurrence of aflatoxins (AFB1, AFB2, AFG1 and AFG2) and ochratoxin A (OTA) in dried split ginger purchased from different local markets in Lagos, South West Nigeria has been investigated. A total of 120 ginger samples, 31 collected during the rainy season and 89 during the dry season, were analyzed. Mycotoxins were determined according to the AOAC Official Method 2008.02 based on multi-toxin immunoaffinity column clean up and liquid chromatography quantification. The incidence of contamination with aflatoxins (AFs) and OTA was significantly higher during the rainy season (81% and 77%, respectively) than the dry season (46% and 37%, respectively). Average levels of AFs and OTA in positive samples were 3.13 and 5.10 ?g/kg in the rainy season (range 0.11-9.52 ?g/kg and 0.20-9.90 ?g/kg) and 1.18 and 2.76 ?g/kg (range 0.20-3.57 ?g/kg and 0.17-12.02 ?g/kg) in the dry season, respectively. Furthermore, the levels of AFB1 detected in 7 out of 31 samples (23%) collected during the rainy season were above the European Union (EU) maximum permitted level (i.e. 5 ?g/kg). No samples were found above the EU regulatory limits established for OTA in ginger (i.e. 15 ?g/kg). Moreover, a higher co-occurrence of AFs and OTA was observed in samples collected during the rainy season (65%) than the dry season (21%). Data showed that high humidity and temperature occurring during storage, which are prevalent in the rainy season, offer favorable conditions for AFs and OTA fungal production. This is the first report on the co-occurrence of AFs and OTA in ginger samples from Nigeria. Our results demonstrate that, in order to minimize the risks for consumers, the monitoring of the co-occurrence of these mycotoxins in ginger is highly recommended.

To date it is well known that there is not a unique best analytical technique that alone is capable of answering the question whether a food is authentic or not, nor there is the best mathematical classifier to correctly interpret the results assigning one sample to one or another population. A holistic and multidisciplinary approach benefitting from the knowledge and the skills/expertise acquired by different researches is therefore necessary to tackle this task. In this regard, it is fundamental to know in details the product, the different variables involved, the raw materials and the production processes. It is important to have an in thorough knowledge of the storage conditions of the food along the process chain, and to combine all the available information into an experimental design that should consider all the possible sources of variation.The collection of all these preliminary information represents the starting point to develop tailor-made projects, specifically designed on the objective of the study.In this regard, we need:o representative sampling, with respect to the objective to be achieved;o robust analytical results;o appropriate data interpretation (method, theoretical classification and real classification) based on mathematical classifiers able to distinguish / classify according to the pre-established purpose;o validation protocols. All these issues will be schematized and concisely presented in the present communication, aiming at establishing a universal protocol to be intended as guideline by food industries, suppliers, control laboratories, etc.. to help developing non targeted based methodologies. All authors thank Food Integrity Project, Università del Piemonte Orientale, CNR-ISPA, Innovative Solutions, ICETA, Coop Italia, Thermo Fisher Scientific and Mérieux NutriSciences for the opportunity to participate in this Research, of utmost importance for the dissemination of analytical services designed to verify the full transparency of final food products in terms of Authenticity and Integrity.

A fluorescence polarization (FP) immunoassay has been optimized and validated for rapid quantification of T-2 and HT-2 toxins in both unprocessed cereals, including oats, barley and rye, and cereal-based products for direct human consumption, such as oat flakes, oats crispbread and pasta. Samples were extracted with 90 % methanol, and the extract was filtered and diluted with water or sodium chloride solution prior to the FP immunoassay. Overall mean recoveries from spiked oats, rye, barley, oat flakes, oats crispbread and pasta ranged from 101 to 107 %, with relative standard deviations lower than 7 %. Limits of detection (LODs) of the FP immunoassay were 70 mu g/kg for oats, 40 mu g/kg for oat flakes and barley, 25 mu g/kg for pasta and 20 mu g/kg for rye and oats crispbread. The trueness of the immunoassay was assessed by using two oat and oat flake reference materials for T-2 and HT-2 toxins, showing good accuracy and precision. Good correlations (r > 0.953) were observed between T-2 and HT-2 toxin contents in naturally and artificially contaminated samples determined by both FP immunoassay and ultra-high-performance liquid chromatography (UHPLC) with immunoaffinity column cleanup used as reference method. These results, combined with rapidity and simplicity of the assay, show that the optimized assay is suitable for high-throughput screening, as well as for reliable quantitative determination of T-2 and HT-2 toxins in cereals and cereal-based products.

The problem of food fraud is getting a rapidly increasing interest at global level. Food fraud costs the global food industry several billion dollars every year, negatively impacts public confidence in food producers and regulators, and can result in unfortunate public health consequences. Fighting food fraud is a very complicated area caused by several elements. The possibility to detect fraudulent activities depends on the type of fraud, ranging from altered composition and labelling, geographic origin, mixtures and mimicking supplements to claims of sustainable production or unethical actions. Different types of fraud request the application of different analytical methods based on targeted or non-targeted approaches. Although targeted methods Non-targeted methods have gained recent interest due to their rapidity and high potential in authentication processes aiming at a comprehensive characterization of complex food matrices. There is a high demand of a process of harmonization and standardization of the methods to be used for routine analysis and official control. Potential and limitations of non-targeted methods for authentication of food will be presented. This presentation will give also an overview of the rapid non-targeted methodologies commonly used at ISPA-CNR based on DART-MS, NIR, MS-nose and NMR technologies to assess food authenticity.

The availability of rapid diagnostic methods for monitoring ochratoxigenic species during the seasoning processes for dry-cured meats is crucial and constitutes a key stage in order to prevent the risk of ochratoxin A (OTA) contamination. A rapid, easy-to-perform and noninvasive method using an electronic nose (e-nose) based on metal oxide semiconductors (MOS) was developed to discriminate dry-cured meat samples in two classes based on the fungal contamination: class P (samples contaminated by OTA-producing Penicillium strains) and class NP (samples contaminated by OTA non-producing Penicillium strains). Two OTA-producing strains of P. nordicum and two OTA non-producing strains of P. nalgiovense and P. salamii, were tested. The feasibility of this approach was initially evaluated by e-nose analysis of 480 samples of both Yeast Extract Sucrose (YES) and meat-based agar media inoculated with the tested Penicillium strains and incubated up to 14 days. The high recognition percentages (higher than 82%) obtained by Discriminant Function Analysis (DFA), either in calibration and cross-validation (leave-more-out approach), for both YES and meat-based samples demonstrated the validity of the used approach. The e-nose method was subsequently developed and validated for the analysis of dry-cured meat samples. A total of 240 e-nose analyses were carried out using inoculated sausages, seasoned by a laboratory-scale process and sampled at 5, 7, 10 and 14 days. DFA provided calibration models that permitted discrimination of dry-cured meat samples after only 5 days of seasoning with mean recognition percentages in calibration and cross-validation of 98 and 88%, respectively. A further validation of the developed enose method was performed using 60 dry-cured meat samples produced by an industrialscale seasoning process showing a total recognition percentage of 73%. The pattern of volatile compounds of dry-cured meat samples was identified and characterized by a developed HS-SPME/GC-MS method. Seven volatile compounds (2-methyl-1-butanol, octane, 1R-?-pinene, D-limonene, undecane, tetradecanal, 9-(Z)-octadecenoic acid methyl ester) allowed discrimination between dry-cured meat samples of classes P and NP. These results demonstrate that MOS-based electronic nose can be a useful tool for a rapid screening in preventing OTA contamination in the cured meat supply chain.

Le micotossine sono sostanze naturali con attività tossica prodotte da diverse specie fungine appartenenti principalmente ai generi Aspergillus, Penicillium e Fusarium. La loro presenza negli alimenti e nei mangimi può essere nociva per la salute umana ed animale. Al fine di garantire programmi di monitoraggio affidabili per una corretta valutazione del rischio associato alla loro esposizione e il rispetto dei livelli massimi ammissibili stabiliti in varie derrate alimentari, sono necessari metodi validati con caratteristiche che soddisfino determinati criteri di accettabilità. In questo articolo viene presentata una breve panoramica di recenti attività svolte presso l'Istituto di Scienze delle Produzioni Alimentari del Consiglio Nazionale delle Ricerche (ISPA-CNR) per lo sviluppo e validazione di metodi analitici per la determinazione di micotossine nei cereali e prodotti a base di cereali.

Penicillium nordicum, an important and consistent producer of ochratoxin A (OTA), is a widely distributed contaminant of NaCl and protein rich food. It is usually found on dry-cured meat products and is considered the main responsible of their contamination by OTA. The aim of this work was to study the gene expression of a polyketide synthase (otapksPN), involved in P. nordicum OTA biosynthesis, and OTA production during a small-scale seasoning process. Fresh pork sausages were surface inoculated with P. nordicum and seasoned for 30 days. Gene expression and OTA production were monitored throughout the seasoning process after 4, 5, 6, 7, 10, 14, and 30 days. The expression of otapksPN gene was already detected after 4 days and increased significantly after 7 days of seasoning, reaching the maximum expression level after 10 days (1.69·104 copies/100 mg). Consistently with gene expression monitoring, OTA was detected since the 4th dayand its content increased significantly from the 7th day, reaching the maximum level after 10 days. In the late stages of seasoning process, OTA did not increase further and the number of gene copies was progressively reduced after 14 and 30 days.

The feasibility of applying the infrared spectroscopy for the geographical origin traceability of lentils from two different countries (Italy and Canada) was investigated. In particular, lentil samples were analyzed by Fourier transform near- and mid-infrared (FT-NIR and FT-MIR) spectroscopy and then discriminated by applying supervised models, i.e., linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA). To avoid LDA overfitting, two variable strategies were adopted, i.e., a variable reduction by principal component analysis and a variable compression by wavelet packet transform algorithm. FT-MIR models were more discriminating compared to FT-NIR ones with prediction abilities ranging from 98 to 100% and from 91 to 100% for cross- and external validation, respectively. The combination of the FT-MIR and FT-NIR data did not improve the model performances. These findings demonstrated the suitability of the FT-MIR spectroscopy, in combination with supervised pattern recognition techniques, to successfully classify lentils according to their geographical origin.

Lentil (Lens culinaris Medik.) is the fourth most important pulse crop in the world after bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), and chickpea (Cicer arietinum L.). Canada is the world's largest exporter of lentils, while in Italy lentils are a minor legume and can be found in restricted areas. However, Italian lentils present unique and characteristic qualities giving them a higher value, so that many of them have obtained international and national marks linked to their geographical origins, such as "protected geographical indication" (PGI), "traditional food products" (PAT) and Slow Food Presidium. For these reasons, there is a growing demand for analytical methods able to certify the declared geographical origin of lentils, in order to protect consumers and producers from fraud and unfair competition. In the present work, the potential of infrared spectroscopic fingerprinting technique for the geographical origin traceability of lentils was investigated. In particular, lentil samples from two different countries, i.e. Italy and Canada, were collected from retail markets and analysed by Fourier transform near- and mid-infrared spectroscopy (FT-NIR, FT-MIR). After a suitable pretreatment of the raw spectral data, Linear Discriminant Analysis (LDA) was used examining the FT-NIR and FT-MIR fingerprints separately and in combination in order to evaluate the spectral range mostly influenced by geographical origin. The LDA classification results were expressed in terms of recognition and prediction abilities (cross validation and external validation). Good classification results were obtained for both FT-NIR and FT-MIR ranges with FT-MIR one giving better prediction abilities, i.e. 95% and 92% for cross and external validation, respectively. The combination of the FT-MIR and F-NIR did not improve the model performances. These findings demonstrated the suitability of the methods developed to discriminate geographical origin of lentils and confirmed the applicability of the infrared spectroscopy, in combination with chemometrics, to solve geographic origin issues of foodstuffs.