An untargeted evaluation of food contact materials by flow injection analysis-mass spectrometry (FIA-MS) combined with independent components analysis (ICA).

Food contact materials (FCMs), especially plastics, are known to be a potential source of contaminants in food. In fact, various groups of additives are used to protect the integrity of the material during processing and life time. However, these intentionally added substances (IAS) could also lead to degradation products called non-intentionally added substances (NIAS), due to reactions occurring in the polymeric material. Complex mixtures of components may therefore be generated within the material, creating a source of potential migrating substances towards food in contact. In this context, an innovative analytical approach is proposed in order to assess IAS and NIAS in plastic FCMs for a fast screening of their composition. For this purpose, solvent extracts of polyethylene (PE) pellets, containers and films were analyzed by flow injection analysis-mass spectrometry (FIA-MS). This direct approach offers the ability to perform a large number of analyses in a short time. Mass spectral fingerprints were then treated by a multivariate data analysis technique called independent components analysis (ICA) in order to overcome the complexity of such data and to highlight hidden information related to IAS and NIAS molecules. ICA applied on mass spectral fingerprints of PE extracts highlighted group discriminations related to different m/z values which were putatively assigned to IAS and also to NIAS. In order to confirm these putative annotations, a hybrid LTQ-Orbitrap was used for high resolution mass spectrometry analysis. Moreover, MS/MS experiments were performed on some discriminant ions to improve their putative identification. The proposed methodology combining FIA-MS fingerprints and ICA proved its efficiency in identifying IAS and NIAS in plastic FCMs and its capability to discriminate different PE samples, in a relatively fast approach compared to classical analytical techniques. This approach may help the FCMs classification for compounders in the selection of the starting substances in plastic formulation and for plastic converters in the control of manufacturing processes as well as for the monitoring of final products.

Attenuated total reflectance-mid infrared spectroscopy (ATR-MIR) coupled with independent components analysis (ICA): A fast method to determine plasticizers in polylactide (PLA).

Compliance of plastic food contact materials (FCMs) with regulatory specifications in force, requires a better knowledge of their interaction phenomena with food or food simulants in contact. However these migration tests could be very complex, expensive and time-consuming. Therefore, alternative procedures were introduced based on the determination of potential migrants in the initial material, allowing the use of mathematical modeling, worst case scenarios and other alternative approaches, for simple and fast compliance testing. In this work, polylactide (PLA), plasticized with four different plasticizers, was considered as a model plastic formulation. An innovative analytical approach was developed, based on the extraction of qualitative and quantitative information from attenuated total reflectance (ATR) mid-infrared (MIR) spectral fingerprints, using independent components analysis (ICA). Two novel chemometric methods, Random_ICA and ICA_corr_y, were used to determine the optimal number of independent components (ICs). Both qualitative and quantitative information, related to the identity and the quantity of plasticizers in PLA, were retrieved through a direct and fast analytical method, without any prior sample preparations. Through a single qualitative model with 11 ICs, a clear and clean classification of PLA samples was obtained, according to the identity of plasticizers incorporated in their formulations. Moreover, a quantitative model was established for each formulation, correlating proportions estimated by ICA and known concentrations of plasticizers in PLA. High coefficients of determination (higher than 0.96) and recoveries (higher than 95%) proved the good predictability of the proposed models.

A comprehensive NMR methodology to assess the composition of biobased and biodegradable polymers in contact with food.

A nuclear magnetic resonance (NMR) methodology was assessed regarding the identification and quantification of additives in three types of polylactide (PLA) intended as food contact materials. Additives were identified using the LNE/NMR database which clusters NMR datasets on more than 130 substances authorized by European Regulation No. 10/2011. Of the 12 additives spiked in the three types of PLA pellets, 10 were rapidly identified by the database and correlated with spectral comparison. The levels of the 12 additives were estimated using quantitative NMR combined with graphical computation. A comparison with chromatographic methods tended to prove the sensitivity of NMR by demonstrating an analytical difference of less than 15%. Our results therefore demonstrated the efficiency of the proposed NMR methodology for rapid assessment of the composition of PLA.

Independent components analysis coupled with 3D-front-face fluorescence spectroscopy to study the interaction between plastic food packaging and olive oil.

Olive oil is one of the most valued sources of fats in the Mediterranean diet. Its storage was generally done using glass or metallic packaging materials. Nowadays, plastic packaging has gained worldwide spread for the storage of olive oil. However, plastics are not inert and interaction phenomena may occur between packaging materials and olive oil. In this study, extra virgin olive oil samples were submitted to accelerated interaction conditions, in contact with polypropylene (PP) and polylactide (PLA) plastic packaging materials. 3D-front-face fluorescence spectroscopy, being a simple, fast and non destructive analytical technique, was used to study this interaction. Independent components analysis (ICA) was used to analyze raw 3D-front-face fluorescence spectra of olive oil. ICA was able to highlight a probable effect of a migration of substances with antioxidant activity. The signals extracted by ICA corresponded to natural olive oil fluorophores (tocopherols and polyphenols) as well as newly formed ones which were tentatively identified as fluorescent oxidation products. Based on the extracted fluorescent signals, olive oil in contact with plastics had slower aging rates in comparison with reference oils. Peroxide and free acidity values validated the results obtained by ICA, related to olive oil oxidation rates. Sorbed olive oil in plastic was also quantified given that this sorption could induce a swelling of the polymer thus promoting migration.

Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA).

Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of the proposed approach was also tested using two spectrometers with considerable differences in their sensitivities. Discrimination rates were not affected proving that the developed approach could be extrapolated to different spectrometers. MIR combined with ICA is a promising tool for plastic waste separation that can help improve performance in this field; however further technological improvements and developments are required before it can be applied at an industrial level given that all tests presented here were performed under laboratory conditions.

Interactions of flavoured oil in-water emulsions with polylactide.

Polylactide (PLA), a biobased polymer, might prove suitable as eco-friendly packaging, if it proves efficient at maintaining food quality. To assess interactions between PLA and food, an oïl in-water model emulsion was formulated containing aroma compounds representing different chemical structure classes (ethyl esters, 2-nonanone, benzaldehyde) at a concentration typically found in foodstuff (100 ppm). To study non-equilibrium effects during food shelf life, the emulsions were stored in a PLA pack (tray and lid). To assess equilibrium effects, PLA was conditioned in vapour contact with the aroma compounds at concentrations comparable to headspace conditions of real foods. PLA/emulsion interactions showed minor oil and aroma compound sorption in the packaging. Among tested aroma compounds, benzaldehyde and ethyl acetate were most sorbed and preferentially into the lid through the emulsion headspace. Equilibrium effects showed synergy of ethyl acetate and benzaldehyde, favouring sorption of additional aroma compounds in PLA. This should be anticipated during the formulation of food products.

Chemometric tools to highlight possible migration of compounds from packaging to sunflower oils.

Polyethylene terephthalate (PET) could be considered for the packaging of vegetable oils taking into account the impact of its oxygen permeability on the oxidation of the oil and the migration of volatile organic compounds (VOC) from the polymer matrix. After accelerated aging tests at 40 °C for 10, 20, and 30 days, the headspace of three sunflower oils packed in PET with high density polyethylene caps was carried out using solid phase microextraction. VOCs such as benzene hydrocarbons, ethylbenzene, xylene isomers and diethyl phthalate were identified in vegetable oils by gas chromatography coupled to mass spectrometry. Chemometric tools such as principal components analysis (PCA), independent components analysis (ICA), and a multiblocks analysis, common components and specific weight analysis (CCSWA) applied to analytical data were revealed to be very efficient to discriminate between samples according to oil oxidation products (hexanal, heptanal, 2-pentenal) and to the migration of packaging contaminants (xylene).

Chemometric tools to highlight non-intentionally added substances (NIAS) in polyethylene terephthalate (PET).

In an effort to identify non-intentionally added substances (NIAS), which is still a challenging task for analytical chemists, PET pellets, preforms and bottles were analyzed by an optimized headspace solid phase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS). Fingerprints obtained by the proposed method were analyzed by three chemometric tools: Principal Components Analysis (PCA), Independent Components Analysis (ICA) and a multi-block method (Common Components and Specific Weights Analysis CCSWA) in order to extract pertinent variations in NIAS concentrations. Total ion current (TIC) chromatograms were used for PCA and ICA while extracted ion chromatograms (EIC) were used for CCSWA, each ion corresponding to a block. PCA managed to discriminate pellets and preforms from bottles due to several NIAS. Volatiles like 2-methyl-1,3-dioxolane, ethylene glycol, ethylbenzene and xylene were responsible for the discrimination of pellets and preforms. Less volatile compounds like linear aldehydes and phthalates were responsible for the discrimination of bottles. ICA showed more specific discriminations especially for bottles and pellets while CCSWA managed to discriminate preforms. The proposed methodology, combining HS-SPME/GC-MS with chemometric tools proved its efficiency in highlighting NIAS in PET samples in a relatively simple and fast approach compared to classical techniques.

Local demixion in plasticized polylactide probed by electron spin resonance.

Improving the barrier properties to gas and organic compounds of biosourced polyesters, such as polylactides (PLAs), by increasing their crystallinity has been suggested by several authors. This paper investigates the risk of microphase separation for a technological approach that would involve a plasticization of PLA, to further its crystallization kinetics, with common plasticizers: Acetyl tributyl citrate (ATBC) and Poly(ethylene glycol) (PEG). Overplasticization effects following microphase separation were monitored along the film thickness by exposing dynamically thermo-compressed films to nitroxide spin-probes. The method enabled a scan of the local polymer mobility for different concentration profiles in spin-probes, with in particular a maximum moving continuously in time towards the geometric center. The results were interpreted as excess local temperatures that would give similar ESR spectra motion in the bulk. It was shown that measured excess temperatures could be related to local shifts in the glass transition temperature along the film thickness.

Use of inverse gas chromatography to determine thermodynamic parameters of aroma-starch interactions.

Interactions between aroma compounds (d-limonene, ethyl hexanoate, octanal and 1-hexanol) and high amylose cornstarch were studied using inverse gas chromatography. Free energies of adsorption (deltaGa) and enthalpies of adsorption (deltaHa) of aroma compounds on starch were measured in the temperature range of 33-40 degrees C. The results showed existence of interactions between aroma compounds and starch, involving hydrogen bounds and dipole-dipole interactions. Sorption isotherms and Henry's law solubility coefficients (S) were determined at 40 degrees C. Three different shapes of isotherms were obtained according to the BET classification: type III for d-limonene, type II for ethyl hexanoate and linear for octanal and 1-hexanol.

Optimization of headspace solid-phase Microextraction (SPME) for the odor analysis of surface-ripened cheese.

Fifty volatile compounds of surface smear-ripened cheese were detected and identified using headspace solid-phase microextraction (HS-SPME) and vacuum distillation coupled to gas chromatography-mass spectrometry. Changes in the headspace of aroma compounds were monitored over the whole packaging period (47 days) using the HS-SPME method. Initially, the concentration of methanethiol increased before reaching a plateau. This evolution could be linked to the growth of Brevibacterium linens. During the shelf life of cheese, levels of acetic acid and 3-methylbutanoic acid remained constant, whereas butane-2,3-dione, 3-hydroxybutan-2-one, and hydroxypropan-2-one levels gradually declined and acetone and 3-methylbutanol levels dropped sharply to a plateau. Changes in odor could be related to changes of the rind, which behaved as a barrier, strongly influencing the distribution of volatile compounds in the headspace. Using a gas chromatography-olfactometry technique without separation, it was shown that the SPME extract was representative of the cheese odor.