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.

CE method for analyzing Salmonella typhimurium in water samples.

Salmonella typhimurium is commonly described as a food-borne pathogen. However, natural and drinking water are known to be important sources for the transmission of this pathogen in developing and developed countries. The standard method to determine Salmonella is laborious and many false positives are detected. To solve this, the present work was focused on the development of a capillary zone electrophoresis method coupled to ultraviolet detection for determination of Salmonella typhimurium in water (mineral and tap water). Separations were performed in less than 11 minutes using 4.5 mM Tris (hydroxymethyl)-aminomethane, 4.5 mM boric acid and 0.1 mM ethylene diamine tetraacetate (pH 8.4) with 0.1% v/v poly ethylene oxide as separation buffer. The precision of the method was evaluated in terms of repeatability obtaining a relative standard deviation of 10.5%. Using the proposed method Salmonella typhimurium could be separated from other bacteria that could be present in water such as Escherichia coli. Finally, the proposed methodology was applied to determine Salmonella typhimurium in tap and mineral water.

Analytical strategy for determination of known and unknown destruxins using hybrid quadrupole-Orbitrap high-resolution mass spectrometry.

An analytical strategy based on a hybrid quadrupole-Orbitrap mass spectrometry was proposed for the simultaneous screening of known destruxins and characterization of potential members of this class of secondary metabolites, in order to evaluate the metabolite production of entomopathogenic fungi used as biocontrol agents. Initially, the fragmentation pathway of the known and commercially available destruxin A was established combining high resolution mass spectrometry (HRMS) and multiple stage MS data in order to obtain the strategy for the characterization of other destruxins for which reference standards were not available. Nineteen known destruxins including A, B, C, D, Ed, F, A1, B1, Ed1, A2, B2, D2, A3, DesmA, DesmB, DesmC, DesmB2, and two chloro-derivatives (Cl and E2 chlorohydrin) were unequivocally identified in Metarhizium brunneum using the proposed strategy. In addition, four unknown destruxins, namely C1, Ed2, G, and G1, were structurally elucidated and characterized for the first time in this fungal strain.

Extraction of toxic compounds from saliva by magnetic-stirring-assisted micro-solid-phase extraction step followed by headspace-gas chromatography-ion mobility spectrometry.

A new sample extraction procedure based on micro-solid-phase extraction (µSPE) using a mixture of sorbents of different polarities (polymeric reversed-phase sorbent HLB, silica-based sorbent C18, and multiwalled carbon nanotubes) was applied to extract benzene, toluene, butyraldehyde, benzaldehyde, and tolualdehyde present in saliva to avoid interference from moisture and matrix components and enhance sensitivity and selectivity of the ion mobility spectrometry (IMS) methodology proposed. The extraction of target analytes from saliva samples by using µSPE were followed by the desorption step carried out in the headspace vials placed in the autosampler of the IMS device. Then, 200 µL of headspace was injected into the GC column coupled to the IMS for its analysis. The method was fully validated in terms of sensitivity, precision, and recovery. The LODs and LOQs obtained, when analytes were dissolved in saliva samples to consider the matrix effect, were within the range of 0.38-0.49 and 1.26-1.66 µg mL(-1), respectively. The relative standard deviations were <3.5 % for retention time and drift time values, which indicate that the method proposed can be applied to determine toxic compounds in saliva samples. Graphical abstract Summary of steps followed in the experimental set up of this work.

Instrumental Techniques to Classify Olive Oils according to Their Quality.

This review includes an update of the publications on quality classification of olive oils into extra, virgin or lampante olive oil categories. Nowadays, the official method to carry out this classification is time-consuming and, sometimes, it is not systematic and/or objective. It is based on conventional physicochemical analysis and on a sensorial tasting of olive oils carried out by a panel of experts. The aim of this review was to explore and give value to the alternative techniques reported in the bibliography to complement the current official methods established for that classification of olive oils. Specifically considered were non-separation and separation analytical techniques which could contribute to correctly classify olive oils according to their physicochemical and/or sensorial characteristics. An in-depth description has been written on the methods used to differentiate these three types of olive oils and the main advantages and disadvantages of the proposed procedures. The techniques here reviewed could be a real and fast option to complement or even substitute some of the analysis included in the official method. Finally, general trends and detected difficulties found to address this issue have been discussed throughout the article.

Feed Supplementation Detection during the Last Productive Stage of the Acorn-Fed Iberian Pig through a Faecal Volatilome Analysis.

The acorn-fed Iberian pig is known worldwide due to the quality of the resulting products commercialized after a natural and free grazing period of fattening in the dehesa agroforestry ecosystem. The quality regulation of the pig breed reserves "acorn" denomination for only those products obtained from animals exclusively fed grazing acorns and other natural resources; however, sometimes, feed supplementation of the pig's diet is fraudulently employed to reach an earlier slaughtering weight and to increase pig stocking rate, a strategy called postre (meaning "feed supplement"). In this sense, although many studies focused on Iberian pig diet have been published, the field detection of feed use for acorn-fed pig during the last finishing stage foraging in the dehesa, a practice which clashes with the official regulation, has not been explored yet. The present study employs a volatilome analysis (gas chromatography coupled to ion mobility spectrometry) of a non-invasive biological sample (faeces) to discriminate the grazing diet of only natural resources, that acorn-fed Iberian pigs are supposed to have, from those pigs that are also supplemented with feed. The results obtained show the suitability of the methodology used and the usefulness of the information obtained from faeces samples to discriminate and detect the fraudulent use of feed for acorn-fed Iberian pig fattening: a classification success ranging between 86.4% and 100% was obtained for the two chemometric approaches evaluated. These, together with the results of discriminant models, are discussed, in addition to the importance that the methodology optimized implies for the Iberian pig sector and market, which is also introduced. This methodology could be adapted to control organic farming animals or other upstanding livestock production systems which are supposed to be fully dependent on a natural grazing diet.

Comparing the potential of IR-spectroscopic techniques to gas chromatography coupled to ion mobility spectrometry for classifying virgin olive oil categories.

Virgin olive oil (OO) can be classified into three different categories: extra virgin, virgin and lampante. The official method for this classification, based on physicochemical analysis and sensory tasting, is considered useful and effective, although it is a costly and time-consuming process. The aim of this study was to assess the potential of some analytical techniques for classifying and predicting different OO categories to support official methods and to provide olive oil companies with a rapid tool to assess product quality. Thus, mid and near infrared spectroscopies (MIR and NIR) have been compared by using different instruments and with head-space gas chromatography coupled to an ion mobility spectrometer (HS-GC-IMS). High classification success rates in validation models were obtained using IR spectrometers (>70% and > 80% in average for ternary and binary classifications, respectively), although HS-GC-IMS showed greater classification potential (>85% and > 90%).

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.

Relationship between Volatile Organic Compounds and Microorganisms Isolated from Raw Sheep Milk Cheeses Determined by Sanger Sequencing and GC-IMS.

Recently, the interest of consumers regarding artisan cheeses worldwide has increased. The ability of different autochthonous and characterized lactic acid bacteria (LAB) to produce aromas and the identification of the volatile organic compounds (VOCs) responsible for flavor in cheeses are important aspects to consider when selecting strains with optimal aromatic properties, resulting in the diversification of cheese products. The objective of this work is to determine the relationship between VOCs and microorganisms isolated (Lacticaseibacillus paracasei, Lactiplantibacillus plantarum, Leuconostoc mesenteroides and Lactococcus lactis subsp. hordniae) from raw sheep milk cheeses (matured and creamy natural) using accuracy and alternative methods. On combining Sanger sequencing for LAB identification with Gas Chromatography coupled to Ion Mobility Spectrometry (GC−IMS) to determinate VOCs, we describe cheeses and differentiate the potential role of each microorganism in their volatilome. The contribution of each LAB can be described according to their different VOC profile. Differences between LAB behavior in each cheese are shown, especially between LAB involved in creamy cheeses. Only L. lactis subsp. hordniae and L. mesenteroides show the same VOC profile in de Man Rogosa and Sharpe (MRS) cultures, but for different cheeses, and show two differences in VOC production in skim milk cultures. The occurrence of Lactococcus lactis subsp. hordniae from cheese is reported for first time.

Detection of Mycobacterium tuberculosis complex field infections in cattle using fecal volatile organic compound analysis through gas chromatography-ion mobility spectrometry combined with chemometrics.

Bovine tuberculosis is considered a re-emerging disease caused by different species from the Mycobacterium tuberculosis complex (MTC), important not only for the livestock sector but also for public health due to its zoonotic character. Despite the numerous efforts that have been carried out to improve the performance of the current antemortem diagnostic procedures, nowadays, they still pose several drawbacks, such as moderate to low sensitivity, highlighting the necessity to develop alternative and innovative tools to complement control and surveillance frameworks. Volatilome analysis is considered an innovative approach which has been widely employed in animal science, including animal health field and diagnosis, due to the useful and interesting information provided by volatile metabolites. Therefore, this study assesses the potential of gas chromatography coupled to ion mobility spectrometry (GC-IMS) to discriminate cattle naturally infected (field infections) by MTC from non-infected animals. Volatile organic compounds (VOCs) produced from feces were analyzed, employing the subsequent information through chemometrics. After the evaluation of variable importance for the projection of compounds, the final discriminant models achieved a robust performance in cross-validation, as well as high percentages of correct classification (>90%) and optimal data of sensitivity (91.66%) and specificity (99.99%) in external validation. The tentative identification of some VOCs revealed some coincidences with previous studies, although potential new compounds associated with the discrimination of infected and non-infected subjects were also addressed. These results provide strong evidence that a volatilome analysis of feces through GC-IMS coupled to chemometrics could become a valuable methodology to discriminate the infection by MTC in cattle. IMPORTANCE Bovine tuberculosis is endemic in many countries worldwide and poses important concerns for public health because of their zoonotic condition. However, current diagnostic techniques present several hurdles, such as low sensitivity and complexity, among others. In this regard, the development of new approaches to improve the diagnosis and control of this disease is considered crucial. Volatile organic compounds are small molecular mass metabolites which compose volatilome, whose analysis has been widely employed with success in different areas of animal science including animal health. The present study seeks to evaluate the combination of fecal volatilome analysis with chemometrics to detect field infections by bovine tuberculosis (Mycobacterium tuberculosis complex) in cattle. The good robust performance of discriminant models as well as the optimal data of sensitivity and specificity achieved highlight volatilome analysis as an innovative approach with huge potential.

Use of carboxylic group functionalized magnetic nanoparticles for the preconcentration of metals in juice samples prior to the determination by capillary electrophoresis.

Nowadays food industry demands reliable and precise methods to resolve problems related to quality and security control. The pretreatment steps, prior to sample analysis, are necessary to extract the target analytes because of the complexities of the food samples matrices. In this work, we have studied, for the first time, the potential of carboxylic group functionalized magnetic nanoparticles to preconcentrate metals from liquid samples before CE analysis. For the extraction of metals, 10 mL of an aqueous sample containing the metal mixture was added to 2 mg carboxylic group functionalized magnetic nanoparticles. Metals retained in the nanoparticles were re-extracted with 200 µL solution consisting of 0.8 mM 1,10-phenanthroline and 0.04% hydroxylamine chloride at pH 2. The electrophoretic buffer used in this work to separate different metals (Co, Cu, Zn, Ni, and Cd) consisted of 30 mM hydroxylamine chloride, 0.30 mM 1,10-phenanthroline, 80 mM urea, 15 mM ammonium chloride, and 0.1% methanol at pH 3.6. Finally, measurements were made at 270 nm. Under the optimized conditions, detection limits for Co, Zn, Cu, Ni, and Cd were 0.004, 0.003, 0.004, 0.008, and 0.009 mg L(-1) , respectively.

Easy sample treatment for the determination of enrofloxacin and ciprofloxacin residues in raw bovine milk by capillary electrophoresis.

An easy, selective, and sensitive method has been developed for the determination of enrofloxacin (ENR) and its main active metabolite, ciprofloxacin (CIP), in raw bovine milk using CE with UV detection at 268 nm. Milk samples were prepared by a clean-up/extraction procedure based on protein precipitation with hydrochloride acid followed by being defatted by centrifugation and SPE using a hydrophilic-lipophilic balance cartridge. Optimum separation was obtained using a 50 mM phosphoric acid at pH 8.4 and the total electrophoretic run time was 6 min. Sample preparation by this method yielded clean extracts with quantitative and consistent mean recoveries from 89 to 97% for CIP and from 93 to 98% for ENR. LODs obtained were lower to the maximum residue limits for these fluoroquinolones. The precision of the ensuing method is acceptable; thus, the RSD for peak area and migration time was less than 8.5 and 0.5% for CIP and 9.9 and 0.9% for ENR, respectively. The results showed that the proposed method was efficient showing good recoveries, sensitivity, and precision for the studied compounds and could be satisfactorily applied in routine analysis for the monitoring of ENR and CIP residues in milk, due to its ruggedness and feasibility demonstrated.

Multi-capillary column-ion mobility spectrometry: a potential screening system to differentiate virgin olive oils.

The potential of a headspace device coupled to multi-capillary column-ion mobility spectrometry has been studied as a screening system to differentiate virgin olive oils ("lampante," "virgin," and "extra virgin" olive oil). The last two types are virgin olive oil samples of very similar characteristics, which were very difficult to distinguish with the existing analytical method. The procedure involves the direct introduction of the virgin olive oil sample into a vial, headspace generation, and automatic injection of the volatiles into a gas chromatograph-ion mobility spectrometer. The data obtained after the analysis by duplicate of 98 samples of three different categories of virgin olive oils, were preprocessed and submitted to a detailed chemometric treatment to classify the virgin olive oil samples according to their sensory quality. The same virgin olive oil samples were also analyzed by an expert's panel to establish their category and use these data as reference values to check the potential of this new screening system. This comparison confirms the potential of the results presented here. The model was able to classify 97% of virgin olive oil samples in their corresponding group. Finally, the chemometric method was validated obtaining a percentage of prediction of 87%. These results provide promising perspectives for the use of ion mobility spectrometry to differentiate virgin olive oil samples according to their quality instead of using the classical analytical procedure.

Review of the Methodologies for Measurement of Greenhouse Gas Emissions in Livestock Farming: Pig Farms as a Case of Study.

The global emission and accumulation of gases due to livestock farming is estimated to contribute to about 14.5% of the global warming effect due to greenhouse gases (GHG). Pig farming represents 9% of global livestock GHG emissions, without considering other activities of pork production process, such as feed production. Most of information about pig farms GHG emissions is based on theoretical calculations with not too much accuracy. Hence, there is a critical need to study the best sampling and analytical techniques (portable or not) that can be used to map their contribution to GHG emissions. The selection of the best analytical detection method becomes important for public policies on climate change, and in order to evaluate animal and manure handling practices to reduce GHG and to combat global warming. In this article, different techniques, which could be used to measure the emissions of GHG from livestock, are reviewed, showing the advantages and disadvantages of each technique, with special emphasis on those already used in studies about GHG from pig farms and those that allow the simultaneous determination of several species of gases. Open chambers equipped with photoacoustic multi-gas monitor have been the techniques most employed in intensive pig farms studies. Gas Chromatography coupled to different detectors has been only widely used in pig farms to monitor simultaneously several GHG species using previous sampling devices. However, there are no studies in the literature based on extensive pig farms. In these systems, micrometeorological techniques could be a promising strategy.

Thirty years of capillary electrophoresis in food analysis laboratories: potential applications.

CE has generated considerable interest in the research community since instruments were introduced by different trading companies in the 1990s. Nowadays, CE is popular due to its simplicity, speed, highly efficient separations and minimal solvent and reagent consumption; it can also be included as a useful technique in the nanotechnology field and it covers a wide range of specific applications in different fields (chemical, pharmaceutical, genetic, clinical, food and environmental). CE has been very well evaluated in research laboratories for several years, and different new approaches to improve sensitivity (one of the main drawbacks of CE) and robustness have been proposed. However, this technique is still not well accepted in routine laboratories for food analysis. Researching in data bases, it is easy to find several electrophoretic methods to determine different groups of analytes and sometimes they are compared in terms of sensitivity, selectivity, precision and applicability with other separation techniques. Although these papers frequently prove the potential of this methodology in spiked samples, it is not common to find a discussion of the well-known complexity of the matrices to extract analytes from the sample and/or to study the interferences in the target analytes. Summarizing, the majority of CE scientific papers focus primarily on the effects upon the separation of the analytes while ignoring their behavior if these analytes are presented in real samples.

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock.

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

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.

Authentication of the Montanera Period on Carcasses of Iberian Pigs by Using Analytical Techniques and Chemometric Analyses.

The potential of two complementary analytical techniques (near infrared spectroscopy, NIRS and gas chromatography-ion mobility spectrometry, GC-IMS) was used to establish the time that Iberian pigs have been fed on acorns and pasture and to verify their genetic purity. For both techniques it was neither necessary to carry out any chemical treatment in advance nor to identify individual compounds. The results showed that both the NIR spectrum and the spectral fingerprint obtained by GC-IMS were affected by the time that the Iberian pig feeds on natural resources. High percentages of correct classification were achieved in the calibration for both techniques: >98% for the days of montanera and >96% for the breed by NIRS and >99% for the days of montanera and >98% for the breed by GC-IMS. The results obtained showed that NIR spectra taken from intact samples is a quick classification method according to the time of montanera and breed.

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%.

Neotropical mutualism between Acacia and Pseudomyrmex: phylogeny and divergence times.

The interaction between Acacia and Pseudomyrmex is a textbook example of mutualism between ants and plants, nevertheless aspects of its evolutionary biology have not been formally explored. In this paper we analyze primarily the phylogenies of both New World Acacia and of their associated species of ants, and the geographic origin of this mutualism. Until now, there has been no molecular analysis of this relationship in terms of its origin and age. We analyzed three chloroplast markers (matK, psaB-rps14, and trnL-trnF) on a total of 70 taxa of legumes from the subfamily Mimosoideae, and two nuclear regions (long-wavelength rhodopsine and wingless) on a total of 43 taxa of ants from subfamily Pseudomyrmecinae. The monophyly of subgenus Acacia and within the New World lineages that of the myrmecophilous Acacia group was established. In addition, our results supported the monophyly of the genus Pseudomyrmex and of the associated acacia-ants P. ferrugineus group. Using Bayesian methods and calibration data, the estimated divergence times for the groups involved in the mutualism are: 5.44+/-1.93 My for the myrmecophilous acacias and 4.58+/-0.82 My for their associated ant species, implying that their relationship originated in Mesoamerica between the late Miocene to the middle Pliocene, with eventual diversification of both groups in Mexico.