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International audience; In a risk assessment perspective, this work aims to assess the bioaccessibility of PCBs in meat. A standardised in vitro static digestion protocol was set up and coupled with extraction, clean-up and GC × GC-ToF/MS multianalyte method to monitor the fate of PCBs in meat during digestion. Starting with spiked meat, PCB bioaccessibility in 11% fat medium-cooked meat varied in adults from 20.6% to 30.5% according to congeners. PCB bioaccessibility increased to 44.2–50.1% in 5% fat meat and decreased to 6.2–9.1% and to 14.6–19.4% in digestion conditions mimicking infants and elderly, respectively. Intense cooking also decreased PCB bioaccessibility to 18.0–26.7%. Bioaccessibility data obtained with spiked meat were validated with measurements carried out in incurred meat samples. Finally, mean uptake distributions are obtained from a modular Bayesian approach. These distributions feature a lower mode when the fat content is higher, the meat is well-done cooked, and the consumers are older.

Volatile organic Compounds (VOC)-based metabolomics, or volatolomics, was investigated for revealing livestock exposure to chemical contamination. Three farm animals, namely laying hens, broilers, and pigs, were experimentally exposed to 5 or 50 ng α-HBCDD g-1 feed. Liver and egg yolk for hens were analysed by headspace-SPME-GC-MS to reveal candidate markers of the livestock exposure to α-HBCDD. For hens, 2-butanol was found as marker in egg. In liver, twelve VOCs were highlighted as markers, with three aromatic VOCs – styrene, o-xylene, α-methylstyrene – highlighted for the two α-HBCDD doses. For broilers, six markers were revealed, with interestingly, styrene and phenol which were also found as markers in hen liver. For pigs, ten markers were revealed and the seven tentatively identified markers were oxygenated and sulfur VOCs. The candidate markers tentatively identified were discussed in light of previous volatolomics data, in particular from a γ-HBCDD exposure of laying hens.

Food safety is a growing concern for consumers, public authorities and food-chain stakeholders. Ensuring food safety is becoming increasingly important with regard to changing food habits and the globalization of food supply. This makes assessing chemical food safety a crucial issue, as food can be contaminated by various toxicants throughout the food chain. At farm level, raw materials can be contaminated by agrochemicals, including pesticides and veterinary drugs, as well as by environmental micropollutants such as POPs or heavy metals. Further chemical hazards associated to the occurrence of toxicants or to cross-contaminations can also arise during transport, processing or storage. This article presents and discusses recent advances in chemical food safety. Taking meat as a model, it gives an overview of promising novel approaches to better control the occurrence of chemical toxicants along the food chain, improve their risk assessment, and reduce their impact on human health by proposing novel mitigation strategies. Industrial relevance As meat may be contaminated by various chemical toxicants, its chemical safety is a growing concern for public authorities, industrials and consumers. This paper gives the different toxic contaminants potentially found in meat products and the possible strategies for their detection, mitigation and health impact assessment. This knowledge would permit industrials to develop new distinctive labels for safe food as well as to produce new ready-to-eat foods free of process-induced toxicants or original recipes to add to dishes to reduce the health impact of these toxicants. Knowing the toxicant bioaccessibility would also permit industrials to target precise food product composition depending on the raw materials and the consumers' class. It finally proposes emerging analytical approaches to enable a more systematic control of meat chain. All the strategies developed herein on meat products could be transposable to other food chains of industrial interest and with products potentially contaminated from farm to fork.

International audience; Hexabromocyclododecane (HBCD) is a critical emerging brominated flame retardant to which consumers can be exposed at high doses through a single food intake. Based on an animal experiment involving 3 groups of laying hens fed during 70 days with a control diet or gamma-HBCD-contaminated diets at 0.1 or 10mug gamma-HBCD g-1 feed, this study aims to use the volatolome of biological samples for revealing markers of livestock exposure to HBCD. Liquid chromatography-tandem mass spectrometry was used to monitor the time-course of HBCD levels in bodily samples. Each liver was analyzed by solid-phase microextraction-gas chromatography-mass spectrometry for volatolome profiling. After 70 days, gamma-HBCD concentrations in egg yolk, fat, liver and serum reached 54±4, 85±6, 31±6, and 32±4ngg-1 lw, respectively, for the low exposure level and 4.6+/5.7, 7.8+/6.5, 3.9+/3.0 and 3.9+/6.1mugg-1 lw, respectively, for the high exposure level. Isomerization of gamma-HBCD into alpha- and beta-HBCD was observed in all tissues, at least for the high exposure level. Volatolome data allowed a significant discrimination between control and exposed animals whatever the feed contamination load, demonstrating a liver metabolic response to gamma-HBCD exposure. The relevance of the twenty nine volatile exposure markers tentatively identified was discussed in light of literature data.

International audience

There is rising consumer demand for guarantees on the quality and safety of their food, especially for farmed-animal products. This growing need is largely driven by frequent widely-publicized food safety scares, and cases of inappropriate risk management practices. Consumers are aware that the quality of an animal product is largely determined by production conditions, and are pressing for guaranteed traceability on food chain. High on the list of the critical control issues is the animal production systems used to farm livestock, particularly diet and the feedstuffs consumed by the animals which impact the quality of animal-origin foods. Animal diet authentication from these products obtained with particular animal diet is thus a growing demand, even if other rearing parameters can make it difficult the authentication diagnosis. The chapter reviews the candidate markers in foods of animal origin for authenticating animal diet and discusses the relevant analytical means of characterizing these key compounds.

International audience; The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not highlight the most influencing variables for each separation, whereas the ICA Loadings highlighted the same variables as did CCA. This study shows the potential of CCA for the extraction of pertinent information from a data matrix, using a procedure based on an original optimisation criterion, to produce results that are complementary, and in some cases may be superior, to those of PCA and ICA.

Benzo[a]pyrene (B[a]P) is a ubiquitous, persistent, and carcinogenic pollutant that belongs to the large family of polycyclic aromatic hydrocarbons. Population exposure primarily occurs via contaminated food products, which introduces the pollutant to the digestive tract. Although the metabolism of B[a]P by host cells is well known, its impacts on the human gut microbiota, which plays a key role in health and disease, remain unexplored. We performed an in vitro assay using 16S barcoding, metatranscriptomics and volatile metabolomics to study the impact of B[a]P on two distinct human fecal microbiota. B[a]P exposure did not induce a significant change in the microbial structure; however, it altered the microbial volatolome in a dose-dependent manner. The transcript levels related to several metabolic pathways, such as vitamin and cofactor metabolism, cell wall compound metabolism, DNA repair and replication systems, and aromatic compound metabolism, were upregulated, whereas the transcript levels related to the glycolysis-gluconeogenesis pathway and bacterial chemotaxis toward simple carbohydrates were downregulated. These primary findings show that food pollutants, such as B[a]P, alter human gut microbiota activity. The observed shift in the volatolome demonstrates that B[a]P induces a specific deviation in the microbial metabolism.

International audience; Starting from a critical analysis of a first "proof of concept" study on the utility of the liver volatolome for detecting livestock exposure to environmental micropollutants (Berge et al., 2011), the primary aim of this paper is to improve extraction conditions so as to obtain more representative extracts by using an extraction temperature closer to livestock physiological conditions while minimizing analytical variability and maximizing Volatile Organic Compound (VOC) abundancies. Levers related to extraction conditions and sample preparation were assessed in the light of both abundance and coefficient of variation of 22 candidate VOC markers identified in earlier volatolomic studies. Starting with a CAR/PDMS fiber and a 30min extraction, the reduction of SPME temperature to 40°C resulted in a significant decrease in the area of 14 candidate VOC markers (p

Starting with an experiment to authenticate walnut oils based on GC-MS analysis of the volatolome, this paper aims to demonstrate the relevance of a two-step alignment-based strategy for the systematic research of VOC markers. The first step of the treatment consists of roughly reducing the time shifts with efficient, known warping techniques like COW (Correlation Optimized Warping). The second step relies on an accurate peak apex alignment in order to refine residual local misalignments and to enable further systematic marker research through univariate or multivariate data treatments. This two-step strategy was implemented on 117 GC-MS analyses of the volatolome of three vegetable oils with very similar composition. During the analysis campaign, the GC-MS system was intentionally subjected to instrumental drifts in order to generate realistic signal shifts. The first part of this study aims to assess the efficiency of the warping-based strategy in terms of signal alignment and sample discrimination. Whereas no distinction between the three oils was possible with unaligned raw GC-MS data, the application of COW enabled a significant but insufficient improvement of both reduction of temporal drifts and between-group separation with 79% of samples being well-classified according to Linear Discriminant Analysis (LDA). Applying the peak apex alignment procedure to COW-treated signals resulted in a suitable correction of the remaining local distortions and improved the proportion of well-classified samples in LDA to 100%. The second part of this study assesses the robustness of the discriminant markers highlighted in this approach by: (i) discussing the relevance of the best markers involved in the LDA model, where a close review of literature confirmed the consistency for two of them, and (ii) validating highlighted makers by retrieving the set of the 23 markers previously determined by manual processing among those automatically found. The third part shows the potential of the systematic approach for untargeted detection of 184 highly significant relevant markers from the oil volatolome. Finally, the fourth part presents a comparison of our hybrid alignment strategy with two reference alignment methods (iCoshift and STW) in order to assess quality alignment of the GC-MS data and to show the three methods' abilities to detect discriminant markers.

International audience; This work presents the effects of pan cooking on PCBs, PCDD/Fs, pesticides and trace elements in meat from a risk assessment perspective. Three different realistic cooking intensities were studied. A GC_GC-TOF/MS method was set up for the multiresidue analysis of 189 PCBs, 17 PCDD/Fs and 16 pesticides whereas Cd, As, Pb and Hg were assayed by ICP-MS. In terms of quantity, average PCB losses after cooking were 18 ± 5% for rare, 30 ± 3% for medium, and 48 ± 2% for well-done meat. In contrast, average PCDD/F losses were not significant. For pesticides, no loss occurred for aldrin, lindane, DDE or DDD, whereas losses exceeding 80% were found for dieldrin, sulfotep or phorate. Losses close to the margin of error were observed for trace elements. These results are discussed in light of the physicochemical properties of the micropollutants as well as of water and fat losses into cooking juice.

International audience; Benzo[a]pyrene (B[a]P) is a ubiquitous, persistent, and carcinogenic pollutant that belongs to the large family of polycyclic aromatic hydrocarbons. Population exposure primarily occurs via contaminated food products, which introduces the pollutant to the digestive tract. Although the metabolism of B[a]P by host cells is well known, its impacts on the human gut microbiota, which plays a key role in health and disease, remain unexplored. We performed an in vitro assay using 16S barcoding, metatranscriptomics and volatile metabolomics to study the impact of B[a]P on two distinct human fecal microbiota. B[a]P exposure did not induce a significant change in the microbial structure; however, it altered the microbial volatolome in a dose-dependent manner. The transcript levels related to several metabolic pathways, such as vitamin and cofactor metabolism, cell wall compound metabolism, DNA repair and replication systems, and aromatic compound metabolism, were upregulated, whereas the transcript levels related to the glycolysis-gluconeogenesis pathway and bacterial chemotaxis toward simple carbohydrates were downregulated. These primary findings show that food pollutants, such as B[a]P, alter human gut microbiota activity. The observed shift in the volatolome demonstrates that B[a]P induces a specific deviation in the microbial metabolism.

International audience

Recent studies have evidenced volatile biomarkers in ruminant tissues that distinguish between exclusive pasture and exclusive concentrate diets. As ruminants usually alternate these diets, we set out to monitor the persistence of volatile tracers of pasture diet in perirenal fat and caudal subcutaneous fat in lambs ( n = 28) fed on pasture and then fattened at increasing levels with concentrate: Four groups of lambs ( n = 7) were stall-finished to achieve a final weight gain of 0, 4, 8, and 12 kg, respectively. Thirty nine pasture diet tracers including terpenes, 2,3-octanedione and toluene were found that distinguish between the four different diets in both tissues. According to their clearance rates monitored in the adipose tissues of lambs fattened with different amounts of concentrate, different types of persistence were evidenced. Most of the compounds exhibited a “short” persistence, e.g. 2,3-octanedione and terpenes, while some displayed a “medium” or “long” persistence. Finally, performing discriminant analysis on ratios of tracers from the two adipose tissues enabled the correct differentiation of the four different diets.

The objective of the work was to assess the relevance for the authentication of food of a novel chemometric method developed to correct mass spectrometry (MS) data from instrumental drifts, namely, the comprehensive combinatory standard correction (CCSC). Applied to gas chromatography (GC)–MS data, the method consists in analyzing a liquid sample with a mixture of n internal standards and in using the best combination of standards to correct the MS signal provided by each compound. The paper focuses on the authentication of the type of feeding in farm animals based on the composition in volatile constituents of their adipose tissues. The first step of the work enabled on one hand to ensure the feasibility of the conversion of the adipose tissue sample into a liquid phase required for the use of the CCSC method and on the other hand, to determine the key parameters of the extraction of the volatile fraction from this liquid phase by dynamic headspace. The second step showed the relevance of the CCSC pre-processing of the MS fingerprints generated by dynamic headspace-MS analysis of lamb tissues, for the discrimination of animals fed exclusively with pasture ( n = 8) or concentrate ( n = 8). When compared with filtering of raw data, internal normalization and correction by a single standard, the CCSC method increased by 17.1-, 3.3- and 1.3-fold, respectively, the number of mass fragments which discriminated the type of feeding. The final step confirmed the advantage of the CCSC pre-processing of dynamic headspace-gas chromatography-MS data for revealing molecular tracers of the type of feeding those number ( n = 72) was greater when compared to the number of tracers obtained with raw data ( n = 42), internal normalization ( n = 63) and correction by a single standard ( n = 57). The relevance of the information gained by using the CCSC method is discussed.

International audience

In addition to microbiological issues, meat chemical safety is a growing concern for the public authorities, chain stakeholders and consumers. Meat may be contaminated by various chemical toxicants originating from the environment, treatments of agricultural production or food processing. Generally found at trace levels in meat, these toxicants may harm human health during chronic exposure. This paper overviews the key issues to be considered to ensure better control of their occurrence in meat and assessment of the related health risk. We first describe potential contaminants of meat products. Strategies to move towards a more efficient and systematic control of meat chemical safety are then presented in a second part, with a focus on emerging approaches based on toxicogenomics. The third part presents mitigation strategies to limit the impact of process-induced toxicants in meat. Finally, the last part introduces methodological advances to refine chemical risk assessment related to the occurrence of toxicants in meat by quantifying the influence of digestion on the fraction of food contaminants that may be assimilated by the human body.

International audience; tThe assessment of the dual impact of heating treatments on food safety and aroma is a major issue for thefood sector. The aim of the present study was to demonstrate the relevance of multidimensional GC tech-niques, olfactometry and mass spectrometry for the parallel determination of process-induced toxicantsand odorants in food starting with cooked meat as a food model. PAHs were analyzed by comprehensivetwo-dimensional gas chromatography-time-of-flight mass spectrometry after extraction by acceler-ated solvent extraction (ASE-GC × GC–TOF/MS). Odour-active compounds were determined by dynamicheadspace–GC hyphenated with eightbooth olfactometry and mass spectrometry (DH–GC–MS/8O)and DH-heart-cutting multidimensional GC hyphenated with olfactometry and mass spectrometry(DH–GC–GC–MS/O). For PAH determination, the GC × GC conditions consisted of a combination of aprimary non-polar BPX-5 column and a secondary polar BPX-50 column, and a modulation period of 5 s.In terms of linearity (R2ranging from 0.985 to 0.997), recovery rate (84–111%) and limit of detection(5–65 ng/kg of cooked meat), the ASE-GC × GC–TOF/MS method was found consistent with the mul-tiresidue determination of 16 PAHs including benzo[a]pyrene in cooked meat. For aroma compounds,DH–GC–MS/8O and DH–GC–MS/O revealed 53 major meat odour-active compounds. A customizedheart-cutting GC–GC–MS/O enabled the coeluting odour zones with high odour-activity to be resolvedand revealed 15 additional odour-active compounds. Finally, these developments of multidimensionalapproaches were used to investigate the balance between 16 PAHs and 68 odour-active compoundsgenerated with different cooking techniques

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National audience

The current work describes a new method, the comprehensive combinatory standard correction (CCSC), for the correction of instrumental signal drifts in GC-MS systems. The method consists in analyzing together with the products of interest a mixture of n selected internal standards, and in normalizing the peak area of each analyte by the sum of standard areas and then, select among the summation operator sigma(p = 1)(n)C(n)p possible sums, the sum that enables the best product discrimination. The CCSC method was compared with classical techniques of data pre-processing like internal normalization (IN) or single standard correction (SSC) on their ability to correct raw data from the main drifts occurring in a dynamic headspace-gas chromatography-mass spectrometry system. Three edible oils with closely similar compositions in volatile compounds were analysed using a device which performance was modulated by using new or used dynamic headspace traps and GC-columns, and by modifying the tuning of the mass spectrometer. According to one-way ANOVA, the CCSC method increased the number of analytes discriminating the products (31 after CCSC versus 25 with raw data or after IN and 26 after SSC). Moreover, CCSC enabled a satisfactory discrimination of the products irrespective of the drifts. In a factorial discriminant analysis, 100% of the samples (n = 121) were well-classified after CCSC versus 45% for raw data, 90 and 93%, respectively after IN and SSC.

International audience; This paper evaluates different multiresidue methods based on comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC x GC-TOF/MS) to analyze dioxin-related micropollutants in complex food matrices. In a first step, the column sets Rtx-PCB/BPX-50 and Rtx-Dioxin2/BPX-50 were compared in terms of peak shape (width and symmetry) and resolution for the separation of polychlorinated biphenyls (PCBs) and polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) in solvent. A satisfactory separation of 206 dioxin-related micropollutants including the 17 toxic PCDD/Fs was achieved in 75 min with the column set Rtx-Dioxin2/BPX-50. In a second time, the GC x GC-TOF/MS method was spread to the analysis of dioxin-related micropollutants in complex food matrices. An extraction procedure including accelerated solvent extraction (ASE), centrifugal evaporation and gel permeation chromatography (GPC) was optimized. Starting with meat as a model matrix, a micropollutant spiking method was then set up by comparing seven methods in terms of recoveries and reproducibility. The method combining immersion of the meat in a large volume of solvent containing micropollutants followed by homogenization by blender induced recoveries in the acceptable range of 70-130% and satisfactory standard deviations (

International audience; The present study discusses the relevance, performance and complementarities of flame photometric detector in phosphorus (FPD/P) and sulfur (FPD/S) modes, micro electron capture detector (mu ECD), nitrogen phosphorus detector (NPD), flame ionization detector (FID) and time-of-flight mass spectrometer (TOF/MS) for the comprehensive two-dimensional gas chromatography (GC x GC) analysis of pesticides. A mix of 41 pesticides including organophosphorus pesticides, synthetic pyrethroids and fungicides was investigated in order to benchmark GC x GC systems in terms of linearity (R-2), limits of detection (LOD), and peak shape measures (widths and asymmetries). A mixture of pesticides which contained the heteroatoms phosphorus, sulfur, nitrogen and one or several halogens, was used to acquire a comparative data set to monitor relative detector performances. GC x GC datasets were systematically compared to their GC counterpart acquired with an optimized one-dimensional GC configuration. Compared with FID, considered the most appropriate detector in terms of suitability for GC x GC, the element-selective detector FPD/P and mu ECD best met the peak widths (0.13-0.27 s for FPD/P; 0.22-0.26 s for mu ECD) and tailing factors (0.99-1.66 for FPD/P; 1.32-1.52 for mu ECD); NPD exhibited similar peak widths (0.23-0.30s), but exceeded those of the above detectors for tailing factors (1.97-2.13). These three detectors had improved detection limits of 3-7 times and 4-20 times lower LODs in GC x GC mode compared with FID and TOF-MS, respectively. In contrast FPD/S had poor peak shape (tailing factor 3.36-5.12) and much lower sensitivity (10-20 fold lower compared to FPD/P). In general, element-selective detectors with favorable detection metrics can be considered viable alternatives for pesticide determination using GC x GC in complex matrices. The controversial issue of sensitivity enhancement in GC x GC was considered for optimized GC and GC x GC operation. For all detectors, we found no significant LOD enhancement in GC x GC. (C) 2013 Elsevier B.V. All rights reserved.

The present paper introduces a new gas chromatography data processing procedure dubbed systematic ratio normalization (SRN) enabling to improve both sample set discrimination and biomarker identification. SRN consists in (1) calculating, for each sample, all the log-ratios between abundances of chromatography-analyzed compounds, then (2) selecting the log-ratio(s) that best maximize the discrimination between sample-sets. The relevance of SRN was evaluated on two data sets acquired through gas chromatography-mass spectrometry as part of separate studies designed (i) to discriminate source-origins between vegetable oils analyzed via an analytical system exposed to instrument drift (data set 1) and (ii) to discriminate animal feed between meat samples aged for different durations (data set 2). Applying SRN to raw data made it possible to obtain robust discrimination models for the two data sets by enhancing the contribution to the data variance of the factor-of-interest while stabilizing the contribution of the disturbance factor. The most discriminant log-ratios were shown to employ the most relevant biomarkers presenting relative independence of the factor-of-interest as well as co-behavior of the disturbance effects potentially biasing the discrimination, such as instrument drift or sample biochemical changes. SRN can be run a posteriori on any data set, and might be generalizable to most of separating methods. (C) 2012 Elsevier B.V. All rights reserved.

The study investigated the feasibility of using volatile compound signatures of liver tissues in poultry to detect previous dietary exposure to different types of xenobiotic. Six groups of broiler chickens were fed a similar diet either noncontaminated or contaminated with polychlorinated dibenzo-p-dioxins/-furans (PCDD/Fs; 3.14 pg WHO-TEQ/g feed, 12% moisture), polychlorinated biphenyls (PCBs; 0.08 pg WHO-TEQ/g feed, 12% moisture), polybrominated diphenyl ethers (PBDEs; 1.63 ng/g feed, 12% moisture), polycyclic aromatic hydrocarbons (PAHs; 0.72 μg/g fresh matter), or coccidiostats (0.5 mg/g feed, fresh matter). Each chicken liver was analyzed by solid-phase microextraction - mass spectrometry (SPME-MS) for volatile compound metabolic signature and by gas chromatography - high resolution mass spectrometry (GC-HRMS), gas chromatography - tandem mass spectrometry (GC-MS/MS), and liquid chromatography - tandem mass spectrometry (LC-MS/MS) to quantify xenobiotic residues. Volatile compound signature evidenced a liver metabolic response to PAH although these rapidly metabolized xenobiotics are undetectable in this organ by the reference methods. Similarly, the volatile compound metabolic signature enabled to differentiate the noncontaminated chickens from those contaminated with PBDEs or coccidiostats. In contrast, no clear signature was pointed out for slowly metabolized compounds such as PCDD/Fs and PCBs although their residues were found in liver at 50.93 (±6.71) and 0.67 (±0.1) pg WHO-TEQ/g fat, respectively.

International audience; Several studies have shown that volatile compounds are particularly well-suited for the authentication lamb diet by gas chromatography-mass spectrometry (GC-MS) analysis of adipose tissue. The aim of the present work was to use dynamic headspace-GC-MS to study the variations in the amounts of volatile diet tracers in perirenal fat (PRF) and caudal subcutaneous fat (CSCF) in lambs (n = 24) that were fed with concentrate and then allowed to graze for 0, 17, 51, or 85 days. Twenty-six volatile compounds were found to distinguish between the four diets (p < 0.05) in both PRF and CSCF. Of these diet tracers, 16 were found to be related to the pasture diet and increased at different rates according to the time spent at pasture (latency), while 10 were found in higher amounts in tissues of lambs fed with exclusive concentrate and exhibited different rates of clearance (persistence). Twenty-four of these discriminant compounds, including alkanes, ketones, terpenes, and 2,3-octanedione, were previously stated as pasture diet tracers in several earlier studies, suggesting their potential universality. All degrees of latency or persistence were exhibited by the pasture and concentrate diet tracers, respectively. A principal component analysis performed on ratios of selected diet tracers from both adipose tissues evidenced successful differentiation of the four feeding situation.

International audience; Animal-derived products are particularly vulnerable to contamination by volatile organic compounds (VOCs). These lipophilic substances, which are generated by an increasing number of sources, are easily transferred to the atmosphere, water, soil, and plants. They are ingested by livestock and become trapped in the fat fraction of edible animal tissues. The aim of this work was to determine the occurrence, risk for human health and entryways of benzenic and halogenated VOCs (BHVOCs) in meat products, milks and sea foods using gas chromatography- mass spectrometry (GC-MS) techniques. In the first part, the occurrence and levels of the BHVOCs in animal products were studied. One muscle and three fat tissues were analysed by GC-Quad/MS in 16 lambs. Of 52 BHVOCs identified, 46 were found in the three fat tissues and 29 in all four tissues, confirming that VOCs are widely disseminated in the body. Twenty-six BHVOCs were quantified in fat tissues, and risk for consumer health was assessed for six of these compounds regulated by the US Environmental Protection Agency (EPA). The BHVOC content was found to be consistent with previous reports and was below the maximum contaminant levels set by the EPA. In the second part, the performance of GCxGC-TOF/MS for comprehensively detecting BHVOCs and showing their entryways in animal-derived food chains was assessed. Meat, milk and oysters were analysed by GC-Quad/MS and GCxGC-TOF/MS. For all these products, at least a 7-fold increase in the contaminants detected was achieved with the GCxGC-TOF/MS technique. The results showed that the production surroundings, through animal feeding or geographical location, were key determinants of BHVOC composition in the animal products.

International audience; Authentication of farm animal rearing conditions, especially the type of feeding, is a key issue in certification of meat quality and meat products. The purpose of this article was to analyze in parallel the volatile fraction of three adipose tissues excised from 16 lambs in order to authenticate two animal diets: pasture (n = 8) and concentrate (n = 8). On the basis of growth rate and anatomical location, three different lamb adipose tissues were analyzed: perirenal fat (PRF), caudal subcutaneous fat (CSCF), and heart fat (HF). An initial experiment was used to optimize the extraction of volatile compounds from the adipose tissues. Using a lipid liquid phase extraction, heating the ground tissue to 70 °C, was shown to be the best sample preparation mode before dynamic headspace−gas chromatography−mass spectrometry (DH-GC-MS) analysis to achieve a good representation of the starting material, while getting a good extraction and reproducibility. Next, the application of an instrumental drifts correction procedure to DH-GC-MS data enabled the identification of 130 volatile compounds that discriminate the two diets in one or several of the three tissues: 104 were found in PRF, 75 in CSCF, and 70 in HF. Forty-eight of these diet tracers, including 2,3-octanedione, toluene, terpenes, alkanes, alkenes, and ketones, had previously been identified as ruminant pasture-diet tracers and can be considered generic of this type of animal feeding. Moreover, 49 of the 130 compounds could identify diets in only one tissue, suggesting that complementary analysis of several tissues is superior for diet identification. Finally, multivariate discriminant analyses confirmed that the discrimination was improved when PRF, CSCF, and HF were considered simultaneously, even if HF contributed minimal information.

This study was undertaken to investigate the relevance of using the pyrolysis-MS (Py-MS) technique to discriminate the production area of oysters harvested over two years and to assess from the data of the second year of harvest the potential of an alternative MS-based technique, the solid phase microextraction-MS (SPME-MS), to perform this discrimination. Oysters were harvested in various areas of France, and models of discrimination according to harvest season were built from Py-MS fingerprints and from virtual SPME-MS fingerprints obtained by summing the mass spectra generated by the SPME-GC-MS system. The treatment of the Py-MS data by a 21-12-3 artificial neural networks led to a correct classification of only 89.2% of the oyster samples according to shoreline. The misclassifications thus did not allow use of the Py-MS technique as a relevant tool for authentication of oyster origin. The assessment of the potential of the virtual SPME-MS fingerprints to discriminate the production area of oysters was undertaken on a part of the sample set. The virtual SPME-MS data were pretreated according to two methods, filtering of raw data (FRD) and comprehensive combinatory standard correction (CCSC), a recently developed chemometric method used for the correction of instrumental signal drifts in MS systems. The results obtained with the virtual SPME-MS fingerprints are promising because this technique, when the data were pretreated by the CCSC method, led to a successful discrimination of the oyster samples not only according to shoreline but also according to production region. This study confirms that an efficient correction method (CCSC) of instrumental drifts can considerably increase the discriminative information contained in the volatile fraction of food products.

The authentication of the conditions of animal production, based on the analysis of meat commercial cuts, is a major challenge on both societal and analytical grounds. The aim of the present work was to propose a method for the extraction of the volatile compounds from ruminant raw muscles trimmed of fat and to assess by mass spectrometry-based techniques the relevance of these compounds for the authentication of the type of feeding offered to the animals. The first step of the study consisted of validating conditions of dynamic headspace (DH) extraction of volatile compounds that enabled us to minimize the appearance of heat-induced artifacts and to maximize the richness of the DH-gas chromatography-mass spectrometry profile (DH-GC-MS) of raw lamb muscle. An extraction temperature of 35 degrees C (vs 60 and 90 degrees C) and a sample mass of 6.25 g (vs 12.5, 25, and 50 g) were shown to be suitable. The second step aimed at identifying volatile compounds enabling us to discriminate muscle samples from 16 experimental lambs fed either concentrate (n = 8) or pasture (n = 8). Before, to carefully explore the information given by the DH-GC-MS signal, the MS spectra acquired along the chromatogram were summed and then converted in a virtual-DH-MS spectral fingerprint to have a quick overview of the discriminative potential of the volatile fraction. According to univariate (analysis of variance) and to multivariate (principal component analysis) data treatments performed on virtual-DH-MS fingerprints, the meat volatile fraction was relevant to reveal the type of feeding of the living animal. The detailed examination of the information given by the GC dimension showed that 33 volatile compounds among the 204 detected in the muscle by DH-GC-MS enabled us to discriminate the type of feeding of the lambs. The relevance of these results is discussed in light of previous studies performed on adipose tissues.

International audience