Antibacterial Activity of Oregano (Origanum vulgare L.) Essential Oil Vapors against Microbial Contaminants of Food-Contact Surfaces.

The antimicrobial effect of eight essential oils' vapors against pathogens and spoilage bacteria was assayed. Oreganum vulgare L. essential oil (OVO) showed a broad antibacterial effect, with Minimum Inhibitory Concentration (MIC) values ranging from 94 to 754 µg cm-3 air, depending on the bacterial species. Then, gaseous OVO was used for the treatment of stainless steel, polypropylene, and glass surfaces contaminated with four bacterial pathogens at 6-7 log cfu coupon-1. No viable cells were found after OVO treatment on all food-contact surfaces contaminated with all pathogens, with the exception of Sta. aureus DSM 799 on the glass surface. The antimicrobial activity of OVO after the addition of beef extract as a soiling agent reduced the Sta. aureus DSM 799 viable cell count by more than 5 log cfu coupon-1 on polypropylene and glass, while no viable cells were found in the case of stainless steel. HS-GC-MS analysis of the headspace of the boxes used for the antibacterial assay revealed 14 different volatile compounds with α-Pinene (62-63%), and p-Cymene (21%) as the main terpenes. In conclusion, gaseous OVO could be used for the microbial decontamination of food-contact surfaces, although its efficacy needs to be evaluated since it depends on several parameters such as target microorganisms, food-contact material, temperature, time of contact, and relative humidity.

Does alteration of fumonisin production in Fusarium verticillioides lead to volatolome variation?

Fusarium verticillioides, a major fungal pathogen of maize, produces fumonisins, mycotoxins of global food safety concern. Control practices are needed to reduce the negative health and economic impacts of fumonisins. Therefore, we investigated volatile organic compounds (VOCs) emitted by fumonisin-producing (wild-type) and nonproducing (mutant) strains of F. verticillioides. VOC emissions were analyzed by gas chromatography-mass spectrometry following inoculation of maize kernels, and fumonisin accumulation was analyzed by high-performance liquid chromatography. Mutants emitted VOCs, including ethyl 3-methylbutanoate, that the wild type did not emit. In particular, ANOVA analysis showed significant differences between mutants and wild type for 4 VOCs which emission was correlated with absence of fumonisins. Exogenous ethyl 3-methylbutanoate reduced growth and fumonisin production in wild-type F. verticillioides, showing its potential in biocontrol. Together, our findings offer valuable insights into how mycotoxin production can impact VOC emissions from F. verticillioides and reveal a potential biocontrol strategy to reduce fumonisin contamination.

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.

Effect of Gaseous Citral on Table Grapes Contaminated by Rhizopus oryzae ITEM 18876.

Rhizopus oryzae is responsible for rapidly producing a deliquescent appearance in grape berries, generally favoured by cold chain interruptions. To counteract fruit spoilage and to meet consumer acceptance, innovative strategies based on the application of natural compounds are ongoing. Due to their biological activities, including antimicrobial ones, natural flavour compounds extend the shelf life and improve the nutritional value as well as the organoleptic properties of foods. Thus, in this work, the application of the antimicrobial citral, a flavor component of monoterpenes identified in plant and fruit essential oils, was developed and validated against one spoiler of R. oryzae. Citral, as pure compound, was first investigated in vitro against R. oryzae ITEM 18876; then, concentrations equal to the minimal inhibitory concentration (MIC) and 4-fold MIC (4MIC) value were applied on the table grape cv Italia infected with this strain and stored. The MIC value was equal to 0.0125 µL/cm3; both citral concentrations (0.0125 and 0.05 µL/cm3) were effective in counteracting the microbial decay of infected table grapes over the storage period. The HS-SPME/GC-MS method showed citral persistence in the head space of plastic trays with the infected samples; as expected, a higher content of citral isomers was found in the sample treated with 4MIC value. In conclusion, citral revealed its efficacy to counteract the onset of soft rot by R. oryzae ITEM 18876 under storage conditions. Thus, it could be successfully exploited to develop an active packaging or natural preservatives to extend table grape shelf life without affecting its quality and sensory characteristics, whilst also satisfying the consumer demand for natural preservative agents.

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.

Natural Occurrence of Ochratoxin A in Blood and Milk Samples from Jennies and Their Foals after Delivery.

An assessment of the natural ochratoxin A (OTA) exposure of seven Martina Franca jennies was carried out by analyzing blood and milk samples collected close to and after delivery. A total of 41 and 34 blood samples were collected from jennies and foals, respectively, and analyzed by ELISA. A total of 33 milk samples were collected from jennies and analyzed by the HPLC/FLD method based on IAC clean-up. Furthermore, 53 feed samples were collected from January to September and analyzed by a reference method (AOAC Official Method No. 2000.03) for OTA content. Feed samples showed OTA levels up to 2.7 ng/g with an incidence of 32%, while the OTA incidence rate in jennies' blood samples was 73%, with a median value of 97 ng/L and concentrations ranging from

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.

Quality evaluation of table grapes during storage by using 1H NMR, LC-HRMS, MS-eNose and multivariate statistical analysis.

Three non-targeted methods, i.e. 1H NMR, LC-HRMS, and HS-SPME/MS-eNose, combined with chemometrics, were used to classify two table grape cultivars (Italia and Victoria) based on five quality levels (5, 4, 3, 2, 1). Grapes at marketable quality levels (5, 4, 3) were also discriminated from non-marketable quality levels (2 and 1). PCA-LDA and PLS-DA were applied, and results showed that, the MS-eNose provided the best results. Specifically, with the Italia table grapes, mean prediction abilities ranging from 87% to 88% and from 98% to 99% were obtained for discrimination amongst the five quality levels and of marketability/non-marketability, respectively. For the cultivar Victoria, mean predictive abilities higher than 99% were achieved for both classifications. Good models were also obtained for both cultivars using NMR and HRMS data, but only for classification by marketability. Satisfying models were further validated by MCCV. Finally, the compounds that contributed the most to the discriminations were identified.

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.

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.

Discrimination of geographical origin of oranges (Citrus sinensis L. Osbeck) by mass spectrometry-based electronic nose and characterization of volatile compounds.

An untargeted method using headspace solid-phase microextraction coupled to electronic nose based on mass spectrometry (HS-SPME/MS-eNose) in combination with chemometrics was developed for the discrimination of oranges of three geographical origins (Italy, South Africa and Spain). Three multivariate statistical models, i.e. PCA/LDA, SELECT/LDA and PLS-DA, were built and relevant performances were compared. Among the tested models, SELECT/LDA provided the highest prediction abilities in cross-validation and external validation with mean values of 97.8% and 95.7%, respectively. Moreover, HS-SPME/GC-MS analysis was used to identify potential markers to distinguish the geographical origin of oranges. Although 28 out of 65 identified VOCs showed a different content in samples belonging to different classes, a pattern of analytes able to discriminate simultaneously samples of three origins was not found. These results indicate that the proposed MS-eNose method in combination with multivariate statistical analysis provided an effective and rapid tool for authentication of the orange's geographical origin.

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.

Study of gene expression and OTA production by Penicillium nordicum during a small-scale seasoning process of salami.

Penicillium nordicum, an important and consistent producer of ochratoxin A (OTA), is a widely distributed contaminant of protein rich food with elevated NaCl. It is usually found on dry-cured meat products and is considered the main species responsible for 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 30days. Gene expression and OTA production were monitored throughout the seasoning process after 4, 5, 6, 7, 10, 14, and 30days. The expression of otapksPN gene was already detected after 4days and increased significantly after 7days of seasoning, reaching the maximum expression level after 10days (1.69×10(4)copies/100mg). Consistently with gene expression monitoring, OTA was detected from the 4th day and its content increased significantly from the 7th day, reaching the maximum level after 10days. In the late stages of the seasoning process, OTA did not increase further and the number of gene copies was progressively reduced after 14 and 30days.

Rapid prediction of ochratoxin A-producing strains of Penicillium on dry-cured meat by MOS-based electronic nose.

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 non-invasive 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 Penicillium nordicum and two OTA non-producing strains of Penicillium nalgiovense and Penicillium 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 e-nose method was performed using 60 dry-cured meat samples produced by an industrial-scale 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-α-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.

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.