Prevalence of Paslahepevirus balayani in commercial swine food products from Spain.

Paslahepevirus balayani (formerly known as hepatitis E virus) is an emerging cause of foodborne disease in Europe, transmitted mainly by the consumption of raw or undercooked pork. Since little is known about the presence of the virus in several pork products that are eaten uncooked, our aim was to evaluate the prevalence of Paslahepevirus balayani in groups of commercial pork products intended for human consumption subjected to different processing techniques. A total of 1265 samples of pork products from Spain were divided into four groups and tested for the presence of Paslahepevirus balayani RNA: unprocessed pig and wild boar meat frozen at -20 °C (n = 389), dry-cured pork products (n = 391), dry-cured and salted pork products (n = 219), and boiled products (n = 266) (none of these products contained pork liver). Five samples were positive for Paslahepevirus balayani RNA (overall prevalence: 0.4%; 95% CI: 0.17% - 0.92%). All positive samples were from unprocessed meat stored at -20 °C, with a prevalence in this group of 1.3% (95% CI: 0.42-3.44); two samples came from pigs (1.1%; 95% CI: 0.13-3.81) and three from wild boar (1.5%; 95% CI: 0.31-4.28). None of the pork samples in the other groups was positive. In conclusion, Paslahepevirus balayani was found in unprocessed swine products form Spain, but not in processed products intended to be consumed undercooked, demonstrating that transmission of this zoonotic virus by eating these pork products should be more seriously considered.

Geographical origin, curing plant and commercial category discrimination of cured Iberian hams through volatilome analysis at industry level.

Cured Iberian ham is a worldwide known product due to its high quality. Nowadays, there is a lack of official analytical methods to differentiate geographical origin (Protected Designation of Origin (PDO)), the curing plant where hams are processed, as well as the commercial categories in each industry. In this work, volatile organic compounds (VOCs) extracted from 998 Iberian hams were analyzed by Gas Chromatography coupled to Ion Mobility Spectrometry (GC-IMS), using the subsequent information to design discriminant models. High classification percentages were obtained for the three objectives of the study: 98,5% for geographical origin, 93,5% and 100% for curing plant discrimination, and an average rate of 84,5% for commercial category discrimination in the seven curing plants subject to study. Differences obtained in discriminant models are probably due to the complexity of Iberian ham manufacturing process. In this sense, the results obtained in the present study suggest slight differences between geographical areas and industries evaluated, even covered by the same PDO. Also, those differences may be related to the existing variability in terms of breed purity and feeding regime of Iberian pigs, which are two of the main determining factors of ham aroma.

Full Workflows for the Analysis of Gas Chromatography-Ion Mobility Spectrometry in Foodomics: Application to the Analysis of Iberian Ham Aroma.

Gas chromatography-ion mobility spectrometry (GC-IMS) allows the fast, reliable, and inexpensive chemical composition analysis of volatile mixtures. This sensing technology has been successfully employed in food science to determine food origin, freshness and preventing alimentary fraud. However, GC-IMS data is highly dimensional, complex, and suffers from strong non-linearities, baseline problems, misalignments, peak overlaps, long peak tails, etc., all of which must be corrected to properly extract the relevant features from samples. In this work, a pipeline for signal pre-processing, followed by four different approaches for feature extraction in GC-IMS data, is presented. More precisely, these approaches consist of extracting data features from: (1) the total area of the reactant ion peak chromatogram (RIC); (2) the full RIC response; (3) the unfolded sample matrix; and (4) the ion peak volumes. The resulting pipelines for data processing were applied to a dataset consisting of two different quality class Iberian ham samples, based on their feeding regime. The ability to infer chemical information from samples was tested by comparing the classification results obtained from partial least-squares discriminant analysis (PLS-DA) and the samples' variable importance for projection (VIP) scores. The choice of a feature extraction strategy is a trade-off between the amount of chemical information that is preserved, and the computational effort required to generate the data models.

Portable Raman Spectrometer as a Screening Tool for Characterization of Iberian Dry-Cured Ham.

Dry-cured Iberian ham is officially classified into different commercial categories according to the pig's breed and feeding regime. These reach very different prices, thus promoting labelling fraud and causing great damage to the food sector. In this work, a method based on Raman spectroscopy was explored as a rapid in situ screening tool for Iberian ham samples. A total of 110 samples were analyzed to assess the potential of this technique to differentiate purebred, crossbred, acorn-fed and feed-fed dry-cured Iberian ham. A continuous signal probably due to sample fluorescence was obtained, which hid the Raman scattering signal. Therefore, chemometric treatment was applied in order to extract non-apparent information. High validated classification rates were obtained for feeding regime (83.3%) and breed (86.7%). In addition, an interlaboratory study was carried out to confirm the applicability of the method with 52 samples, obtaining a validated rate above 80%.

Usage considerations for headspace-gas chromatography-ion mobility spectrometry as a suitable technique for qualitative analysis in a routine lab.

The potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to perform non-targeted qualitative analysis of complex samples has led to an unprecedented increase in its popularity in recent years. The operating principle of IMS makes quality control essential to ensure adequate results. Besides this, the suitability of GC-IMS is determined by multiple phenomena that take place before and during IMS detection. The present work discusses a novel GC-IMS quality control protocol for both beginners and experienced users. Likewise, it describes factors that must be taken into account in order to develop a robust GC-IMS qualitative analysis method and, if needed, to achieve the identification of VOCs present in real samples. The developed quality control protocol was successfully employed in our laboratory for the routine analysis of >500 real samples (olive oil and Iberian ham) for 6 months, thus it is recommended for the analysis of a great number of complex samples. Furthermore, the behaviour of the ions produced in the ionisation chamber and the possible reactions between them in GC-IMS qualitative analysis were assessed.

Use of a non-destructive sampling method for characterization of Iberian cured ham breed and feeding regime using GC-IMS.

Iberian cured ham from purebred pigs fattened on grazing acorns is a highly appreciated product. There are several analytical methods to avoid its labelling fraud; however, these require opening the ham. The aim of this work is testing a non-destructive sampling method which does not spoil the physical integrity of the ham. It consists of a puncture with a needle imitating a traditional olfactory system. After removing the needle impregnated with fat, its volatiles are analyzed with a Gas Chromatography (GC) coupled to Ion Mobility Spectrometry (IMS). The potential of this methodology was studied analyzing 156 Iberian hams from pigs under two different feeding regimes (acorns versus feed) and from different breed (Iberian versus Duroc crossed). Intensity of GC-IMS plot features was extracted and chemometric differentiation models were obtained; one for feeding regime and another for breed, providing validated classification rates of 91.7% and 100%, respectively. In addition, 29 features used for construction of both models were tentatively identified using chemical standards. The suitability of the method for quality control analysis was characterized by means of a precision study. As a conclusion, GC-IMS becomes a useful tool to guarantee dry-cured Iberian ham authenticity and detect labelling fraud.

Target vs spectral fingerprint data analysis of Iberian ham samples for avoiding labelling fraud using headspace - gas chromatography-ion mobility spectrometry.

The data obtained with a polar or non-polar gas chromatography (GC) column coupled to ion mobility spectrometry (IMS) has been explored to classify Iberian ham, to detect possible frauds in their labelling. GC-IMS was used to detect the volatile compound profile of dry-cured Iberian ham from pigs fattened on acorn and pasture or on feed. Due to the two-dimensional nature of GC-IMS measurements, great quantities of data are obtained and an exhaustive chemometric processing is required. A first approach was based on the processing of the complete spectral fingerprint, while the second consisted of the selection of individual markers that appeared throughout the spectra. A classification rate of 90% was obtained with the first strategy, and the second approach correctly classified all Iberian ham samples according to the pigs' diet (classification rate of 100%). No significant differences were found between the GC columns tested in terms of classification rate.