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.

L'interesse per l'ozono quale agente sanitizzante nell'industria alimentare è aumentato negli ultimi anni in risposta ad una sempre crescente richiesta di una 'chimica verde'. L'ozono è infatti un composto rispettoso dell'ambiente in quanto si decompone rapidamente in ossigeno e non lascia residui negli alimenti. Tale gas è considerato un additivo alimentare GRAS (Generally Recognised As Safe) ed il suo utilizzo come additivo antimicrobico per il contatto diretto con gli alimenti è stato recentemente approvato dalla Food and Drug Administration (FDA). Recenti studi hanno mostrato come l'ozono sia efficace nel controllo di insetti, batteri e funghi e nel degradare pesticidi e micotossine che possono contaminare i cereali. Scopo del presente studio è stato quello di valutare l'effetto dei trattamenti con ozono gassoso a diverse concentrazioni (9,0-15,4-26,1 g/m3) e tempi di contatto (2-8-12-24 ore) sulla contaminazione da funghi filamentosi, lieviti e micotossine (in particolare deossinivalenolo e tossine T-2 e HT-2) in campioni di frumento duro utilizzando un prototipo di generatore di ozono progettato ad hoc per il trattamento delle cariossidi. E' stato inoltre valutato l'effetto dei trattamenti su alcuni parametri di qualità del frumento, in particolare sul contenuto in ceneri, proteine, amido, fibra, glutine e indice di giallo. I trattamenti con ozono alle concentrazioni di 9,0 e 15,4 g/m3 non hanno evidenziato effetti significativi sulla contaminazione da funghi filamentosi e lieviti per tutti i tempi di contatto, rispetto al controllo non trattato. In tali condizioni operative è stata osservata una riduzione del contenuto di DON (fino al 19%), rispetto al controllo non trattato, già a partire dalle 8 ore di contatto. I trattamenti con ozono a concentrazioni maggiori (26,1 g/m3) hanno determinato sia una riduzione significativa della carica microbica già a partire dalle 2 ore, sia una maggiore riduzione del contenuto di DON, fino al 32%, a partire dalle 12 ore di trattamento. Non è stata invece osservata alcuna variazione significativa del contenuto di tossine T-2 e HT-2 per tutti i trattamenti. Nelle diverse condizioni sperimentali non sono state osservate variazioni significative dei parametri qualitativi del frumento.

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.

Deoxynivalenol (DON) is a type B trichothecene mycotoxin mainly produced by several Fusarium species occurring in cereals and derived products. Fourier-Transform-Near Infrared (FT-NIR) spectroscopy has been used to develop classification and quantitative models for the rapid analysis of DON in durum wheat and durum wheat bran.Linear Discriminant Analysis (LDA) was successfully used to differentiate highly contaminated durum wheat samples from low contaminated ones in the range of <50-16000 µg/kg. Three LDA models were developed based on different cut-off limits (i.e. 1000, 1200 and 1400 µg/kg DON) that were set at levels lower than the EC maximum limit for DON in unprocessed durum wheat (i.e. 1750 µg/kg). The overall classification and false compliant rates were 75-91% and 3-7%, respectively, with LDA model using a cut-off of 1400 µg/kg fulfilling the requirement of the European official guidelines for screening methods. On the other hands, the partial least-squares (PLS) regression analysis gave models with a large root mean square error (RMSE) of prediction value (1,977 ?g/kg) as compared to the EU maximum limit for DON, thus making the PLS approach unsuitable for quantitative prediction of DON in durum wheat.The feasibility of using FT-NIR spectroscopy to rapidly predict DON in durum wheat bran at levels up to 1600 µg/kg was also investigated by both LDA and PLS analysis. The LDA model used a cut-off value of 400 µg/kg that was lower than the EC maximum limit for DON in bran (i.e. 750 µg/kg) and displayed a classification rate of 80% with 5% of false compliant samples. Good performance results were also obtained by applying the PLS statistical model in the tested range with an RMSE of cross-validation of 191 µg/kg. These findings confirmed the suitability of FT-NIR spectroscopy to rapidly screen a large number of wheat samples for DON contamination and to verify the compliance with EU regulation.

Negli ultimi anni il consumo di alimenti a base di crusca ha avuto un notevole incremento grazie al loro apporto di fibre, acidi grassi essenziali, amido, proteine, vitamine e minerali. Tuttavia diversi studi hanno anche dimostrato che la crusca di frumento duro e i prodotti derivati risultano essere frequentemente contaminati da deossinivalenolo (DON), una micotossina prodotta da funghi del genere Fusarium. Al fine di proteggere la salute del consumatore dall'esposizione al DON, la Commissione Europea ha fissato i limiti massimi ammissibili di DON in diversi prodotti, tra cui la crusca destinata al consumo umano diretto. I metaboliti fungini volatili sono stati utilizzati come indicatori della contaminazione da micotossine in cereali. A tal proposito, è stato sviluppato un metodo rapido, di facile realizzazione e non-distruttivo basato sull'impiego di un naso elettronico (e-nose) con sensori a tecnologia MOS (Metal Oxide Semiconductors) per distinguere campioni di crusca di frumento duro sulla base del contenuto di DON. In particolare i campioni, analizzati con metodo HPLC di riferimento, sono stati distinti in due classi: classe A ([DON] <= 400 µg/kg) e classe B ([DON] > 400 µg/kg). Lo sviluppo del metodo analitico è stato condotto su 410 campioni di crusca di frumento duro naturalmente contaminato da DON con livelli fino a 1600 µg/kg. L'analisi statistica multivariata, condotta mediante Discriminant Function Analysis (DFA), ha fornito un modello di calibrazione che permette di classificare i campioni di crusca con una percentuale di riconoscimento totale dell'89%. I campioni in classe A e classe B sono stati riconosciuti con percentuali rispettivamente dell'88% e 91%. La validazione del modello è stata condotta mediante procedura di cross-validazione (leave-more-out) escludendo in maniera random il 30% dei campioni dai dati in calibrazione e ponendo gli stessi in validazione. La percentuale di riconoscimento totale ottenuta in validazione è risultata pari all'87%, con valori percentuali simili per le classi A e B. E' stato inoltre ottimizzato un metodo SPME-GC-MS per caratterizzare la componente volatile di campioni di crusca di frumento duro in presenza ed in assenza di contaminazione da DON. La componente volatile ottenuta è risultata composta da idrocarburi alifatici e aromatici, acidi, esteri, alcoli, aldeidi, chetoni, terpeni e composti furanici. E' stato inoltre identificato un pattern di 8 molecole aventi correlazione positiva con il contenuto di DON, quali il 2-metil-1-propanolo, ?-caprolattone, 1-pentanolo, 1-otten-3-olo, esanale, 1-esanolo e tridecano o negativa come il 2-pentil-furano. Tali risultati confermano che il metodo e-nose sviluppato potrebbe essere un utile strumento per lo screening di DON in campioni di crusca di frumento duro.

Fungi have an important role in the production of dry-cured meat products, especially during the seasoning period, when the salami surface, both industrially and handmade, is quickly colonized by a composite mycobiota. This mycobiota could have beneficial or undesirable effects on the products depending on its peculiar composition. Various genera of fungi could colonize salami (i.e. Aspergillus¸ Cladosporium, Eurotium, Penicillium), but Penicillium species are predominant, being P. nalgiovense, P. olsonii, P. brevicompactum, P. chrysogenum and a new recently described species P. salamii, the main occurring. As part of the Ministerial project "SAFE-MEAT", aiming to increase food safety and quality of pork-based products, new interesting results to prevent and control ochratoxin A (OTA) risk, and improvements of the quality of salami production have been achieved. In comparison with P. nalgiovense, P. salamii has been proved to be a fast growing mould on dry-cured sausages casing, well adapted to the seasoning process, with higher lipolytic and proteolytic enzymatic activities that could contribute to confer typical sensory characteristics to meat products. Thus, P. salamii resulted a promising candidate for new fungal starter formulations for meat industry. However, salami could be also colonized by P. nordicum, an important and consistent producer of the potent nephrotoxin OTA, widely reported as undesirable contaminant of dry-cured meat products. To this purpose, a high sensitive and easy to use LAMP assay, has been developed for P. nordicum detection on salami surface co-inoculated with P. nalgiovense and P. nordicum at different rates. Moreover, monitoring gene expression of a key gene of OTA biosynthesis in P. nordicum and toxin accumulation in meat during the seasoning process revealed that expression profile was consistent with OTA accumulation. Gene expression was observed since the 4th day after inoculation and progressively increased up to the 10th day when OTA reached the maximum level. Indeed, contamination of dry-cured meat products by P. nordicum could represent a serious concern for salami production and therefore molecular tools, such as LAMP and gene expression assay, should be considered for new HACCP plans in order toprevent and control OTA risk in dry-cured meat production.

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 g/kg DON. The model displayed a large root mean square error of prediction value (1,977 g/kg) as compared to the EU maximum limit for DON in unprocessed durum wheat (i.e., 1,750 g/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 g/kg), B (1,000 < DON <= 2,500 g/kg), and C (DON > 2,500 g/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 g/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 g/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.

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.

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.